WorldWideScience

Sample records for based wind-noise algorithm

  1. Wind Noise Reduction using Non-negative Sparse Coding

    DEFF Research Database (Denmark)

    Schmidt, Mikkel N.; Larsen, Jan; Hsiao, Fu-Tien

    2007-01-01

    We introduce a new speaker independent method for reducing wind noise in single-channel recordings of noisy speech. The method is based on non-negative sparse coding and relies on a wind noise dictionary which is estimated from an isolated noise recording. We estimate the parameters of the model ...... and discuss their sensitivity. We then compare the algorithm with the classical spectral subtraction method and the Qualcomm-ICSI-OGI noise reduction method. We optimize the sound quality in terms of signal-to-noise ratio and provide results on a noisy speech recognition task....

  2. Noise from wind turbines

    International Nuclear Information System (INIS)

    Andersen, B.; Jakobsen, J.

    1992-11-01

    Based on a previous project concerning the calculation of the amount of noise emanating from wind turbine arrays, this one examines the subject further by investigating whether there could be significant differences in the amount of noise made by individual wind turbines in an array, and whether the noise is transmitted in varying directions - so that when it is carried in the same direction as the wind blows it would appear to be louder. The aim was also to determine whether the previously used method of calculation lacked precision. It was found that differences in noise niveaux related to individual wind turbines were insignificant and that noise was not so loud when it was not borne in the direction of the wind. It was necessary to change the method of calculation as reckoning should include the influence of the terrain, wind velocity and distance. The measuring and calculation methods are exemplified and the resulting measurements are presented in detail. (AB)

  3. Wind noise under a pine tree canopy.

    Science.gov (United States)

    Raspet, Richard; Webster, Jeremy

    2015-02-01

    It is well known that infrasonic wind noise levels are lower for arrays placed in forests and under vegetation than for those in open areas. In this research, the wind noise levels, turbulence spectra, and wind velocity profiles are measured in a pine forest. A prediction of the wind noise spectra from the measured meteorological parameters is developed based on recent research on wind noise above a flat plane. The resulting wind noise spectrum is the sum of the low frequency wind noise generated by the turbulence-shear interaction near and above the tops of the trees and higher frequency wind noise generated by the turbulence-turbulence interaction near the ground within the tree layer. The convection velocity of the low frequency wind noise corresponds to the wind speed above the trees while the measurements showed that the wind noise generated by the turbulence-turbulence interaction is near stationary and is generated by the slow moving turbulence adjacent to the ground. Comparison of the predicted wind noise spectrum with the measured wind noise spectrum shows good agreement for four measurement sets. The prediction can be applied to meteorological estimates to predict the wind noise under other pine forests.

  4. Noise from offshore wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Soendergaard, B.; Plovsing, B.

    2005-07-01

    Noise assessment of wind turbines through calculations is based on sound power levels measured according to e.g. IEC 61400-11. With larger wind turbines and distances some of the calculation models give erroneous results. Noise propagation over water is different from propagation over land. For that reason it is important be able to make valid noise assessments for offshore wind farms. A suggestion for an offshore measurement method is described and a survey of models for noise propagation offshore has been made. (au)

  5. Health-based audible noise guidelines account for infrasound and low-frequency noise produced by wind turbines.

    Science.gov (United States)

    Berger, Robert G; Ashtiani, Payam; Ollson, Christopher A; Whitfield Aslund, Melissa; McCallum, Lindsay C; Leventhall, Geoff; Knopper, Loren D

    2015-01-01

    Setbacks for wind turbines have been established in many jurisdictions to address potential health concerns associated with audible noise. However, in recent years, it has been suggested that infrasound (IS) and low-frequency noise (LFN) could be responsible for the onset of adverse health effects self-reported by some individuals living in proximity to wind turbines, even when audible noise limits are met. The purpose of this paper was to investigate whether current audible noise-based guidelines for wind turbines account for the protection of human health, given the levels of IS and LFN typically produced by wind turbines. New field measurements of indoor IS and outdoor LFN at locations between 400 and 900 m from the nearest turbine, which were previously underrepresented in the scientific literature, are reported and put into context with existing published works. Our analysis showed that indoor IS levels were below auditory threshold levels while LFN levels at distances >500 m were similar to background LFN levels. A clear contribution to LFN due to wind turbine operation (i.e., measured with turbines on in comparison to with turbines off) was noted at a distance of 480 m. However, this corresponded to an increase in overall audible sound measures as reported in dB(A), supporting the hypothesis that controlling audible sound produced by normally operating wind turbines will also control for LFN. Overall, the available data from this and other studies suggest that health-based audible noise wind turbine siting guidelines provide an effective means to evaluate, monitor, and protect potential receptors from audible noise as well as IS and LFN.

  6. Health-Based Audible Noise Guidelines Account for Infrasound and Low-Frequency Noise Produced by Wind Turbines

    Science.gov (United States)

    Berger, Robert G.; Ashtiani, Payam; Ollson, Christopher A.; Whitfield Aslund, Melissa; McCallum, Lindsay C.; Leventhall, Geoff; Knopper, Loren D.

    2015-01-01

    Setbacks for wind turbines have been established in many jurisdictions to address potential health concerns associated with audible noise. However, in recent years, it has been suggested that infrasound (IS) and low-frequency noise (LFN) could be responsible for the onset of adverse health effects self-reported by some individuals living in proximity to wind turbines, even when audible noise limits are met. The purpose of this paper was to investigate whether current audible noise-based guidelines for wind turbines account for the protection of human health, given the levels of IS and LFN typically produced by wind turbines. New field measurements of indoor IS and outdoor LFN at locations between 400 and 900 m from the nearest turbine, which were previously underrepresented in the scientific literature, are reported and put into context with existing published works. Our analysis showed that indoor IS levels were below auditory threshold levels while LFN levels at distances >500 m were similar to background LFN levels. A clear contribution to LFN due to wind turbine operation (i.e., measured with turbines on in comparison to with turbines off) was noted at a distance of 480 m. However, this corresponded to an increase in overall audible sound measures as reported in dB(A), supporting the hypothesis that controlling audible sound produced by normally operating wind turbines will also control for LFN. Overall, the available data from this and other studies suggest that health-based audible noise wind turbine siting guidelines provide an effective means to evaluate, monitor, and protect potential receptors from audible noise as well as IS and LFN. PMID:25759808

  7. Noise filtering algorithm for the MFTF-B computer based control system

    International Nuclear Information System (INIS)

    Minor, E.G.

    1983-01-01

    An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions

  8. A method of measuring and correcting tilt of anti - vibration wind turbines based on screening algorithm

    Science.gov (United States)

    Xiao, Zhongxiu

    2018-04-01

    A Method of Measuring and Correcting Tilt of Anti - vibration Wind Turbines Based on Screening Algorithm is proposed in this paper. First of all, we design a device which the core is the acceleration sensor ADXL203, the inclination is measured by installing it on the tower of the wind turbine as well as the engine room. Next using the Kalman filter algorithm to filter effectively by establishing a state space model for signal and noise. Then we use matlab for simulation. Considering the impact of the tower and nacelle vibration on the collected data, the original data and the filtering data are classified and stored by the Screening algorithm, then filter the filtering data to make the output data more accurate. Finally, we eliminate installation errors by using algorithm to achieve the tilt correction. The device based on this method has high precision, low cost and anti-vibration advantages. It has a wide range of application and promotion value.

  9. Noise from wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Fegeant, Olivier [Royal Inst. of Tech., Stockholm (Sweden). Dept. of Building Sciences

    2002-02-01

    A rapid growth of installed wind power capacity is expected in the next few years. However, the siting of wind turbines on a large scale raises concerns about their environmental impact, notably with respect to noise. To this end, variable speed wind turbines offer a promising solution for applications in densely populated areas like the European countries, as this design would enable an efficient utilisation of the masking effect due to ambient noise. In rural and recreational areas where wind turbines are sited, the ambient noise originates from the action of wind on the vegetation and about the listener's ear (pseudo-noise). It shows a wind speed dependence similar to that of the noise from a variable speed wind turbine and can therefore mask the latter for a wide range of conditions. However, a problem inherent to the design of these machines is their proclivity to pure tone generation, because of the enhanced difficulty of avoiding structural resonances in the mechanical parts. Pure tones are deemed highly annoying and are severely regulated by most noise policies. In relation to this problem, the vibration transmission of structure-borne sound to the tower of the turbine is investigated, in particular when the tower is stiffened at its upper end. Furthermore, since noise annoyance due to wind turbine is mostly a masking issue, the wind-related sources of ambient noise are studied and their masking potentials assessed. With this aim, prediction models for wind-induced vegetation noise and pseudo-noise have been developed. Finally, closely related to the effect of masking, is the difficulty, regularly encountered by local authorities and wind farm developers, to measure noise immission from wind turbines. A new measurement technique has thus been developed in the course of this work. Through improving the signal-to-noise ratio between wind turbine noise and ambient noise, the new technique yields more accurate measurement results.

  10. Noise annoyance from wind turbines a review

    International Nuclear Information System (INIS)

    Pedersen, Eja

    2003-08-01

    This study summarises present knowledge on noise perception and annoyances from wind turbines in areas were people live or spend recreation time. There are two main types of noise from a wind turbine: mechanical noise and aerodynamic noise. The aerodynamic noise emits from the rotor blades passing the air. It has a swishing character with a modulation that makes it noticeable from the background noise. This part of the wind turbine noise was found to be the most annoying. Field studies performed among people living in the vicinity of wind turbines showed that there was a correlation between sound pressure level and noise annoyance, but annoyance was also influenced by visual factors such as the attitude to wind turbines' impact on the landscape. Noise annoyance was found at lower sound pressure levels than in studies of annoyance from traffic noise. There is no scientific evidence that noise at levels created by wind turbines could cause health problems other than annoyance. No studies on noise from wind turbines in wilderness areas have been found, but the reaction to other noise sources such as aircraft have been studied. In recreational areas, the expectation of quietness is high among visitors, but wind turbines are, in contrary to aircraft, stationary and could be avoided by recreationists. The visual impact of wind turbines might though be the dominant source of annoyance. Regulations on noise from wind turbines are based on different principles. Some states, e.g. Denmark, have a special legislation concerning wind turbines, while others, like Sweden, have used recommendations originally developed for a different noise source. The noise level could either be absolute, as in Germany, or related to the background noise level as in France. This background noise level could be standardised, measured or related to wind speed

  11. a Universal De-Noising Algorithm for Ground-Based LIDAR Signal

    Science.gov (United States)

    Ma, Xin; Xiang, Chengzhi; Gong, Wei

    2016-06-01

    Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.

  12. Assessment and prediction of wind turbine noise

    International Nuclear Information System (INIS)

    Lowson, M.V.

    1993-01-01

    The significance of basic aerodynamic noise sources for wind turbine noise are assessed, using information on the aero-acoustic mechanisms of other rotors, which have been studied in depth for many years. From the analysis, areas of potential improvement in wind turbine noise prediction are defined. Suggestions are made for approaches to wind turbine noise control which separate the noise problems at cut-in from those at rated power. Some of these offer the possibility of noise reduction without unfavourable effects on performance. Based on this analysis, a new model for prediction of wind turbine noise is presented and comparisons made between prediction and experiment. The model is based on well established aeroacoustic theory and published laboratory data for the two principal sources, inflow turbulence and boundary layer trailing edge interaction. The new method gives good agreement with experiment with the case studied so far. Parametric trends and sensitivities for the model are presented. Comparisons with previous prediction methods are also given. A consequence of the new model is to put more emphasis on boundary layer trailing edge interaction as a noise source. There are prospects for reducing noise from this source detail changes to the wind turbine design. (author)

  13. Microphone directionality, pre-emphasis filter, and wind noise in cochlear implants.

    Science.gov (United States)

    Chung, King; McKibben, Nicholas

    2011-10-01

    Wind noise can be a nuisance or a debilitating masker for cochlear implant users in outdoor environments. Previous studies indicated that wind noise at the microphone/hearing aid output had high levels of low-frequency energy and the amount of noise generated is related to the microphone directionality. Currently, cochlear implants only offer either directional microphones or omnidirectional microphones for users at-large. As all cochlear implants utilize pre-emphasis filters to reduce low-frequency energy before the signal is encoded, effective wind noise reduction algorithms for hearing aids might not be applicable for cochlear implants. The purposes of this study were to investigate the effect of microphone directionality on speech recognition and perceived sound quality of cochlear implant users in wind noise and to derive effective wind noise reduction strategies for cochlear implants. A repeated-measure design was used to examine the effects of spectral and temporal masking created by wind noise recorded through directional and omnidirectional microphones and the effects of pre-emphasis filters on cochlear implant performance. A digital hearing aid was programmed to have linear amplification and relatively flat in-situ frequency responses for the directional and omnidirectional modes. The hearing aid output was then recorded from 0 to 360° at flow velocities of 4.5 and 13.5 m/sec in a quiet wind tunnel. Sixteen postlingually deafened adult cochlear implant listeners who reported to be able to communicate on the phone with friends and family without text messages participated in the study. Cochlear implant users listened to speech in wind noise recorded at locations that the directional and omnidirectional microphones yielded the lowest noise levels. Cochlear implant listeners repeated the sentences and rated the sound quality of the testing materials. Spectral and temporal characteristics of flow noise, as well as speech and/or noise characteristics before

  14. Verification test for on-line diagnosis algorithm based on noise analysis

    International Nuclear Information System (INIS)

    Tamaoki, T.; Naito, N.; Tsunoda, T.; Sato, M.; Kameda, A.

    1980-01-01

    An on-line diagnosis algorithm was developed and its verification test was performed using a minicomputer. This algorithm identifies the plant state by analyzing various system noise patterns, such as power spectral densities, coherence functions etc., in three procedure steps. Each obtained noise pattern is examined by using the distances from its reference patterns prepared for various plant states. Then, the plant state is identified by synthesizing each result with an evaluation weight. This weight is determined automatically from the reference noise patterns prior to on-line diagnosis. The test was performed with 50 MW (th) Steam Generator noise data recorded under various controller parameter values. The algorithm performance was evaluated based on a newly devised index. The results obtained with one kind of weight showed the algorithm efficiency under the proper selection of noise patterns. Results for another kind of weight showed the robustness of the algorithm to this selection. (orig.)

  15. A New Fault Diagnosis Algorithm for PMSG Wind Turbine Power Converters under Variable Wind Speed Conditions

    Directory of Open Access Journals (Sweden)

    Yingning Qiu

    2016-07-01

    Full Text Available Although Permanent Magnet Synchronous Generator (PMSG wind turbines (WTs mitigate gearbox impacts, they requires high reliability of generators and converters. Statistical analysis shows that the failure rate of direct-drive PMSG wind turbines’ generators and inverters are high. Intelligent fault diagnosis algorithms to detect inverters faults is a premise for the condition monitoring system aimed at improving wind turbines’ reliability and availability. The influences of random wind speed and diversified control strategies lead to challenges for developing intelligent fault diagnosis algorithms for converters. This paper studies open-circuit fault features of wind turbine converters in variable wind speed situations through systematic simulation and experiment. A new fault diagnosis algorithm named Wind Speed Based Normalized Current Trajectory is proposed and used to accurately detect and locate faulted IGBT in the circuit arms. It is compared to direct current monitoring and current vector trajectory pattern approaches. The results show that the proposed method has advantages in the accuracy of fault diagnosis and has superior anti-noise capability in variable wind speed situations. The impact of the control strategy is also identified. Experimental results demonstrate its applicability on practical WT condition monitoring system which is used to improve wind turbine reliability and reduce their maintenance cost.

  16. Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach

    International Nuclear Information System (INIS)

    Mittal, Prateek; Mitra, Kishalay; Kulkarni, Kedar

    2017-01-01

    Highlights: • Concurrent resolution of turbine number and locations during micro-siting. • Effect of noise on energy-noise multi-objective optimization is demonstrated. • A hybrid algorithm is proposed utilizing probabilistic and deterministic methods. • ∼24% improved performance is achieved over the benchmark case study. • ∼29% enhanced efficiency over real-binary genetic algorithm alone can be observed. - Abstract: Micro-siting is an optimal way of placing turbines inside a wind farm while considering various design objectives and constraints. Using a well-established Jensen wake model and ISO-9613-2 noise calculation, this study performs a wind farm layout optimization based on a multi-objective trade-off between minimization of the noise propagation and maximization of the energy generation. A novel hybrid methodology is developed which is a combination of probabilistic real-binary coded multi-objective evolutionary algorithm and a newly proposed deterministic gradient based non-dominated normalized normal constraint method. Based on the Inverted Generational Distance metric, the performance of the proposed method is found to be better than the conventional normalized normal constraint method or the concerned evolutionary method alone. Moreover, in contrast to the previous studies, the generated non-dominated front is capable of providing a trade-off between various alternative energy-noise solutions, along with an additional information about the corresponding turbine numbers and their optimal location coordinates. As a result, the decision maker can choose from different competing wind turbine layouts based on existing noise and other standard regulations.

  17. Noise immission from wind turbines

    International Nuclear Information System (INIS)

    1999-01-01

    The project has dealt with practical ways to reduce the influence of background noise caused by wind acting on the measuring microphones. The uncertainty of measured noise emission (source strength) has been investigated. The main activity was a Round Robin Test involving measurements by five laboratories at the same wind turbine. Each laboratory brought its own instrumentation and performed the measurements and analyses according to their interpretation. The tonality of wind turbine noise is an essential component of the noise impact on the environment. In the present project the uncertainty in the newest existing methods for assessing tonality was investigated. The project included noise propagation measurements in different weather conditions around wind turbines situated in different types of terrain. The results were used to validate a noise propagation model developed in the project. Finally, the project also included a study with listeners evaluating recordings of wind turbine noise. The results are intended as guidance for wind turbine manufacturers in identifying the aspects of wind turbine noise most important to annoyance. (author)

  18. Comparisons of spectral characteristics of wind noise between omnidirectional and directional microphones.

    Science.gov (United States)

    Chung, King

    2012-06-01

    Wind noise reduction is a topic of ongoing research and development for hearing aids and cochlear implants. The purposes of this study were to examine spectral characteristics of wind noise generated by directional (DIR) and omnidirectional (OMNI) microphones on different styles of hearing aids and to derive wind noise reduction strategies. Three digital hearing aids (BTE, ITE, and ITC) were fitted to Knowles Electronic Manikin for Acoustic Research. They were programmed to have linear amplification and matching frequency responses between the DIR and OMNI modes. Flow noise recordings were made from 0° to 360° azimuths at flow velocities of 4.5, 9.0, and 13.5 m/s in a quiet wind tunnel. Noise levels were analyzed in one-third octave bands from 100 to 8000 Hz. Comparison of wind noise revealed that DIR generally produced higher noise levels than OMNI for all hearing aids, but it could result in lower levels than OMNI at some frequencies and head angles. Wind noise reduction algorithms can be designed to detect noise levels of DIR and OMNI outputs in each frequency channel, remove the constraint to switch to OMNI in low-frequency channel(s) only, and adopt the microphone mode with lower noise levels to take advantage of the microphone differences.

  19. Annoyance rating of wind turbine noise

    International Nuclear Information System (INIS)

    Iredale, R.

    1993-01-01

    Annoyance rating is important, but more important still is agreement on techniques for formulating minimal complaint criteria for design and specification purposes thus integrating noise control into the plant at the outset. A minimal complaint design criteria is suggested that finds its origin in the logic and techniques used successfully over many years for a wide range of power plant and other installations. The criterion is based on the masking of the wind turbine noise by the wind generated background noise. Satisfactory use of the criterion depends on the specification of inaudibility for the tones generated by the mechanical plant. Wind turbines generate more drive train noise than is realized and this contains many tones which tend to characterize the noise. Reduction of drive train noise would not only reduce the overall noise level but also give it a more acceptable character providing a margin against complaint in unusual circumstances of propagation. This requires very careful design of noise and vibration control in individual components. Vibration isolation between the support structures and the nacelle also requires careful attention. (UK)

  20. A combined model based on CEEMDAN and modified flower pollination algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Zhang, Wenyu; Qu, Zongxi; Zhang, Kequan; Mao, Wenqian; Ma, Yining; Fan, Xu

    2017-01-01

    Highlights: • A CEEMDAN-CLSFPA combined model is proposed for short-term wind speed forecasting. • The CEEMDAN technique is used to decompose the original wind speed series. • A modified optimization algorithm-CLSFPA is proposed to optimize the weights of the combined model. • The no negative constraint theory is applied to the combined model. • Robustness of the proposed model is validated by data sampled from four different wind farms. - Abstract: Wind energy, which is stochastic and intermittent by nature, has a significant influence on power system operation, power grid security and market economics. Precise and reliable wind speed prediction is vital for wind farm planning and operational planning for power grids. To improve wind speed forecasting accuracy, a large number of forecasting approaches have been proposed; however, these models typically do not account for the importance of data preprocessing and are limited by the use of individual models. In this paper, a novel combined model – combining complete ensemble empirical mode decomposition adaptive noise (CEEMDAN), flower pollination algorithm with chaotic local search (CLSFPA), five neural networks and no negative constraint theory (NNCT) – is proposed for short-term wind speed forecasting. First, a recent CEEMDAN is employed to divide the original wind speed data into a finite set of IMF components, and then a combined model, based on NNCT, is proposed for forecasting each decomposition signal. To improve the forecasting capacity of the combined model, a modified flower pollination algorithm (FPA) with chaotic local search (CLS) is proposed and employed to determine the optimal weight coefficients of the combined model, and the final prediction values were obtained by reconstructing the refined series. To evaluate the forecasting ability of the proposed combined model, 15-min wind speed data from four wind farms in the eastern coastal areas of China are used. The experimental results of

  1. The MIGHTI Wind Retrieval Algorithm: Description and Verification

    Science.gov (United States)

    Harding, Brian J.; Makela, Jonathan J.; Englert, Christoph R.; Marr, Kenneth D.; Harlander, John M.; England, Scott L.; Immel, Thomas J.

    2017-10-01

    We present an algorithm to retrieve thermospheric wind profiles from measurements by the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) instrument on NASA's Ionospheric Connection Explorer (ICON) mission. MIGHTI measures interferometric limb images of the green and red atomic oxygen emissions at 557.7 nm and 630.0 nm, spanning 90-300 km. The Doppler shift of these emissions represents a remote measurement of the wind at the tangent point of the line of sight. Here we describe the algorithm which uses these images to retrieve altitude profiles of the line-of-sight wind. By combining the measurements from two MIGHTI sensors with perpendicular lines of sight, both components of the vector horizontal wind are retrieved. A comprehensive truth model simulation that is based on TIME-GCM winds and various airglow models is used to determine the accuracy and precision of the MIGHTI data product. Accuracy is limited primarily by spherical asymmetry of the atmosphere over the spatial scale of the limb observation, a fundamental limitation of space-based wind measurements. For 80% of the retrieved wind samples, the accuracy is found to be better than 5.8 m/s (green) and 3.5 m/s (red). As expected, significant errors are found near the day/night boundary and occasionally near the equatorial ionization anomaly, due to significant variations of wind and emission rate along the line of sight. The precision calculation includes pointing uncertainty and shot, read, and dark noise. For average solar minimum conditions, the expected precision meets requirements, ranging from 1.2 to 4.7 m/s.

  2. Multi-objective genetic algorithm based innovative wind farm layout optimization method

    International Nuclear Information System (INIS)

    Chen, Ying; Li, Hua; He, Bang; Wang, Pengcheng; Jin, Kai

    2015-01-01

    Highlights: • Innovative optimization procedures for both regular and irregular shape wind farm. • Using real wind condition and commercial wind turbine parameters. • Using multiple-objective genetic algorithm optimization method. • Optimize the selection of different wind turbine types and their hub heights. - Abstract: Layout optimization has become one of the critical approaches to increase power output and decrease total cost of a wind farm. Previous researches have applied intelligent algorithms to optimizing the wind farm layout. However, those wind conditions used in most of previous research are simplified and not accurate enough to match the real world wind conditions. In this paper, the authors propose an innovative optimization method based on multi-objective genetic algorithm, and test it with real wind condition and commercial wind turbine parameters. Four case studies are conducted to investigate the number of wind turbines needed in the given wind farm. Different cost models are also considered in the case studies. The results clearly demonstrate that the new method is able to optimize the layout of a given wind farm with real commercial data and wind conditions in both regular and irregular shapes, and achieve a better result by selecting different type and hub height wind turbines.

  3. Optimization design of airfoil profiles based on the noise of wind turbines

    DEFF Research Database (Denmark)

    Cheng, Jiangtao; Chen, Jin; Cheng, Jiangtao

    2012-01-01

    Based on design theory of airfoil profiles and airfoil self-noise prediction model, a new method with the target of the airfoil average efficiency-noise ratio of design ranges for angle of attack had been developed for designing wind turbine airfoils. The airfoil design method was optimized for a...

  4. Wind turbine noise diagnostics

    International Nuclear Information System (INIS)

    Richarz, W.; Richarz, H.

    2009-01-01

    This presentation proposed a self-consistent model for broad-band noise emitted from modern wind turbines. The simple source model was consistent with the physics of sound generation and considered the unique features of wind turbines. Although the acoustics of wind turbines are similar to those of conventional propellers, the dimensions of wind turbines pose unique challenges in diagnosing noise emission. The general features of the sound field were deduced. Source motion and source directivity appear to be responsible for amplitude variations. The amplitude modulation is likely to make wind-turbine noise more audible, and may be partly responsible for annoyance that has been reported in the literature. Acoustic array data suggests that broad-band noise is emitted predominantly during the downward sweep of each rotor blade. Source motion and source directivity account for the observed pattern. Rotor-tower interaction effects are of lesser importance. Predicted amplitude modulation ranges from 1 dB to 6dB. 2 refs., 9 figs.

  5. Noise from wind turbines

    International Nuclear Information System (INIS)

    Andersen, B.; Larsen, P.

    1993-01-01

    Denmark has 3200 wind turbines with an installed maximum capacity of 418MW. The most important Danish research projects into wind turbine noise and the main results are listed. These date from 1983. Two comprehensive studies are currently in progress. The first is an analytical and empirical investigation of aerodynamic noise from wind turbine rotors and has so far dealt mainly with tip noise. The measurement method, using a hard board mounted microphone on the ground near the turbine, is described. Four different tip designs have been tested. Some examples of reference sound power level spectra for three of the designs are presented. During the past two years a computerbased data acquisition system has been used for real-time determination of sound power levels. The second study, which has just commenced, is on annoyance from wind turbine noise. It will include noise measurements, masking calculations and a social survey on the perceived nuisance. (UK)

  6. Noise impact assessment of wind farms

    International Nuclear Information System (INIS)

    Hayes, M.

    1993-01-01

    The noise impact assessment of a wind farm is dependent upon a number of factors pertinent to the site. The most controversial is the selection of a criterion which is acceptable to both the developer of a site, in terms of maximising the number of turbines he may operate without fear of injunction to stop, and the local residents and Environmental Health Officer who will have to enforce any agreements. A number of British Standards exist which cover noise issues. There are, however, certain reservations about their use when applied to potential wind farm developments; some of the more relevant standards are outlined. In addition, Draft Planning Guidance notes which have recently been issued are discussed. These are intended to provide an indication to local planning authorities as to what noise levels and criteria may be acceptable when considering noise emitted by wind farms. No European standard for noise emission from wind farms exists but the legislative position in Denmark, the Netherlands, Germany and Sweden is briefly considered. It is considered that when a maximum level criterion is set it should take into account the existing background noise levels based on measurements which are taken at the most sensitive dwellings to the site. A method for calculating emitted noise levels from turbine arrays is described. (UK)

  7. Quality-aware features-based noise level estimator for block matching and three-dimensional filtering algorithm

    Science.gov (United States)

    Xu, Shaoping; Hu, Lingyan; Yang, Xiaohui

    2016-01-01

    The performance of conventional denoising algorithms is usually controlled by one or several parameters whose optimal settings depend on the contents of the processed images and the characteristics of the noises. Among these parameters, noise level is a fundamental parameter that is always assumed to be known by most of the existing denoising algorithms (so-called nonblind denoising algorithms), which largely limits the applicability of these nonblind denoising algorithms in many applications. Moreover, these nonblind algorithms do not always achieve the best denoised images in visual quality even when fed with the actual noise level parameter. To address these shortcomings, in this paper we propose a new quality-aware features-based noise level estimator (NLE), which consists of quality-aware features extraction and optimal noise level parameter prediction. First, considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we utilize the marginal statistics of two local contrast operators, i.e., the gradient magnitude and the Laplacian of Gaussian (LOG), to extract quality-aware features. The proposed quality-aware features have very low computational complexity, making them well suited for time-constrained applications. Then we propose a learning-based framework where the noise level parameter is estimated based on the quality-aware features. Based on the proposed NLE, we develop a blind block matching and three-dimensional filtering (BBM3D) denoising algorithm which is capable of effectively removing additive white Gaussian noise, even coupled with impulse noise. The noise level parameter of the BBM3D algorithm is automatically tuned according to the quality-aware features, guaranteeing the best performance. As such, the classical block matching and three-dimensional algorithm can be transformed into a blind one in an unsupervised manner. Experimental results demonstrate that the

  8. Seismic noise attenuation using an online subspace tracking algorithm

    Science.gov (United States)

    Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

    2018-02-01

    We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

  9. An aerodynamic noise propagation model for wind turbines

    DEFF Research Database (Denmark)

    Zhu, Wei Jun; Sørensen, Jens Nørkær; Shen, Wen Zhong

    2005-01-01

    A model based on 2-D sound ray theory for aerodynamic noise propagation from wind turbine rotating blades is introduced. The model includes attenuation factors from geometric spreading, sound directivity of source, air absorption, ground deflection and reflection, as well as effects from temperat......A model based on 2-D sound ray theory for aerodynamic noise propagation from wind turbine rotating blades is introduced. The model includes attenuation factors from geometric spreading, sound directivity of source, air absorption, ground deflection and reflection, as well as effects from...... temperature and airflow. At a given receiver point, the sound pressure is corrected by taking into account these propagation effects. As an overall assumption, the noise field generated by the wind turbine is simplified as a point source placed at the hub height of the wind turbine. This assumtion...... is reasonable, for the receiver is located in the far field, at distances from the wind turbine that are much longer than the diameter of the rotor....

  10. Aerodynamical noise from wind turbine generators

    International Nuclear Information System (INIS)

    Jakobsen, J.; Andersen, B.

    1993-06-01

    Two extensive measurement series of noise from wind turbines have been made during different modifications of their rotors. One series focused on the influence from the tip shape on the noise, while the other series dealt with the influence from the trailing edge. The experimental layout for the two investigations was identical. The total A-weighted noise from the wind turbine was measured in 1/3 octave bands from 50 Hz to 10 kHz in 1-minute periods simultaneously with wind speed measurements. The microphone was mounted on a hard board on the ground about 40 m directly downwind of the wind turbine, and the wind speed meter was placed at the same distance upwind of the wind turbine 10 m above ground. Regression analysis was made between noise and wind speed in each 1/3 octave band to determine the spectrum at 8 m/s. During the measurements care was taken to avoid influence from background noise, and the influence from machinery noise was minimized and corrected for. Thus the results display the aerodynamic rotor noise from the wind turbines. By use of this measurement technique, the uncertainty has been reduced to 1.5 - 2 dB per 1/3 octave band in the relevant frequency range and to about 1 dB on the total A-weighted levels. (au) (10 refs.)

  11. Noise emission from wind turbines in wake. Project report

    Energy Technology Data Exchange (ETDEWEB)

    Dam Madsen, K.; Plovsing, B. (DELTA, Hoersholm (Denmark)); Soerensen, Thomas (EMD International A/S, Aalborg (Denmark)); Aagaard Madsen, H.; Bertagnolio, F. (Technical Univ. of Denmark, Risoe National Lab. for Sustainable Energy, Roskilde (Denmark))

    2011-03-15

    When installing wind turbines in clusters or wind farms the inflow conditions to the wind turbines can be disturbed due to wake effects from other wind turbines. The effect of wake on noise generation from wind turbines are described in this report. The work is based on measurements carried out on a M80 2 MW wind turbine. To investigate the relationship between the far field noise levels and the surface pressure and inflow angles measured by sensors on an instrumented wind turbine blade, a parabolic measurement system (PMMS) was designed and tested as part of this project. Based on the measurement results obtained with surface pressure sensors and results from the far field measurements using the PMMS it is concluded that: The variance of surface pressure at the trailing edge (TE) agrees with the theory with regard to variation of pressure spectra with varying inflow angle (AoA) to the blade. Low frequency TE surface pressure increases with increased AoA and high frequency surface pressure decreases with increased AoA. It seems that the TE surface pressure remains almost unaltered during wake operation. Results from the surface transducers at the leading edge (LE) and the inflow angles determined from the pitot tube indicates that the inflow at LE is more turbulent in wake for the same AoA and with a low frequency characteristic, thereby giving rise to more low frequency noise generated during wake operation. The far field measurements supports that on one hand there will be produced relative more low frequency noise due to a turbulent inflow to the blade and on the other hand there will be produced less noise in the broader frequency range/high frequency range due to a lower inflow angle caused by the wind deficit in the wake. The net effect of wake on the total noise level is unresolved. As a secondary result it is seen that noise observed from a position on the ground is related to directional effects of the noise radiated from the wind turbine blade. For an

  12. Wavelet-based de-noising algorithm for images acquired with parallel magnetic resonance imaging (MRI)

    International Nuclear Information System (INIS)

    Delakis, Ioannis; Hammad, Omer; Kitney, Richard I

    2007-01-01

    Wavelet-based de-noising has been shown to improve image signal-to-noise ratio in magnetic resonance imaging (MRI) while maintaining spatial resolution. Wavelet-based de-noising techniques typically implemented in MRI require that noise displays uniform spatial distribution. However, images acquired with parallel MRI have spatially varying noise levels. In this work, a new algorithm for filtering images with parallel MRI is presented. The proposed algorithm extracts the edges from the original image and then generates a noise map from the wavelet coefficients at finer scales. The noise map is zeroed at locations where edges have been detected and directional analysis is also used to calculate noise in regions of low-contrast edges that may not have been detected. The new methodology was applied on phantom and brain images and compared with other applicable de-noising techniques. The performance of the proposed algorithm was shown to be comparable with other techniques in central areas of the images, where noise levels are high. In addition, finer details and edges were maintained in peripheral areas, where noise levels are low. The proposed methodology is fully automated and can be applied on final reconstructed images without requiring sensitivity profiles or noise matrices of the receiver coils, therefore making it suitable for implementation in a clinical MRI setting

  13. [Research on electrocardiogram de-noising algorithm based on wavelet neural networks].

    Science.gov (United States)

    Wan, Xiangkui; Zhang, Jun

    2010-12-01

    In this paper, the ECG de-noising technology based on wavelet neural networks (WNN) is used to deal with the noises in Electrocardiogram (ECG) signal. The structure of WNN, which has the outstanding nonlinear mapping capability, is designed as a nonlinear filter used for ECG to cancel the baseline wander, electromyo-graphical interference and powerline interference. The network training algorithm and de-noising experiments results are presented, and some key points of the WNN filter using ECG de-noising are discussed.

  14. The wind power prediction research based on mind evolutionary algorithm

    Science.gov (United States)

    Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

    2018-04-01

    When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

  15. MPPT Algorithm for Small Wind Systems based on Speed Control Strategy

    Directory of Open Access Journals (Sweden)

    Ciprian VLAD

    2008-07-01

    Full Text Available This paper presents experimental results of an autonomous low-power wind energy conversion system (WECS, based on a permanent-magnet synchronous generator (PMSG connected directly to the wind turbine. The purpose of this paper is to present an improving method for MPPT (Maximum Power Point Tracking algorithm based shaft rotational speed optimal control. The proposed method concern the variable delay compensation between measured wind speed from anemometer and wind shaft rotational speed proportional signal. Experimental results aiming to prove the efficiency of the proposed method are presented.

  16. Effects of venting on wind noise levels measured at the eardrum.

    Science.gov (United States)

    Chung, King

    2013-01-01

    Wind noise can be a nuisance to hearing aid users. With the advent of sophisticated feedback reduction algorithms, people with higher degrees of hearing loss are fit with larger vents than previously allowed, and more people with lesser degrees of hearing loss are fit with open hearing aids. The purpose of this study was to examine the effects of venting on wind noise levels in the ear canal for hearing aids with omnidirectional and directional microphones. Two behind-the-ear hearing aids were programmed when they were worn on a Knowles Electronics Manikin for Acoustic Research. The hearing aid worn on the right ear was programmed to the omnidirectional microphone mode and the one on the left to the directional microphone mode. The hearing aids were adjusted to linear amplification with flat frequency response in an anechoic chamber. Gains below 10 dB were used to avoid output limiting of wind noise levels at low input levels. Wind noise samples were recorded at the eardrum location in a wind tunnel at wind velocities ranging from a gentle to a strong breeze. The hearing aids were coupled to #13 tubings (i.e., open vent), or conventional skeleton earmolds with no vent, pressure vents, or 3mm vents. Polar and spectral characteristics of wind noise were analyzed off-line using MatLab programs. Wind noise levels in the ear canals were mostly predicted by vent-induced frequency response changes in the conventional earmold conditions for both omnidirectional and directional hearing aids. The open vent condition, however, yielded the lowest levels, which could not be entirely predicted by the frequency response changes of the hearing aids. This indicated that a wind-related vent effect permitted an additional amount of sound reduction in the ear canal, which could not be explained by known vent effects. For the microphone location, form factor, and gain settings tested, open fit hearing aids yielded lower noise levels at the eardrum location than conventional behind

  17. Development of an advanced noise propagation model for noise optimization in wind farm

    DEFF Research Database (Denmark)

    Barlas, Emre

    2017-01-01

    Increasing demand in renewable energy has resulted in large wind energy deployment. Even though wind turbines are among the most environmentally friendly way of generating electricity, the noise emitted by them is one of the main obstacles for further installation. Wind farm developers rely...... wind directions or time of the day). The latter causes turbines to be located at less resourceful sites in advance. Both of these scenarios increase the cost of energy. Hence there is a need for more accurate noise mapping tools. The thesis addresses this issue via development of a new tool based...... field sound pressure levels are addressed both in steady and unsteady manner. Enhanced far fields amplitude modulation is observed and associated with the wake dynamics and the rotating blades. Lastly, the developed tool is used for an onshore wind farm noise prediction taking the terrain and the flow...

  18. Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer

    Directory of Open Access Journals (Sweden)

    Byung Eun Lee

    2014-09-01

    Full Text Available This paper proposes an algorithm for fault detection, faulted phase and winding identification of a three-winding power transformer based on the induced voltages in the electrical power system. The ratio of the induced voltages of the primary-secondary, primary-tertiary and secondary-tertiary windings is the same as the corresponding turns ratio during normal operating conditions, magnetic inrush, and over-excitation. It differs from the turns ratio during an internal fault. For a single phase and a three-phase power transformer with wye-connected windings, the induced voltages of each pair of windings are estimated. For a three-phase power transformer with delta-connected windings, the induced voltage differences are estimated to use the line currents, because the delta winding currents are practically unavailable. Six detectors are suggested for fault detection. An additional three detectors and a rule for faulted phase and winding identification are presented as well. The proposed algorithm can not only detect an internal fault, but also identify the faulted phase and winding of a three-winding power transformer. The various test results with Electromagnetic Transients Program (EMTP-generated data show that the proposed algorithm successfully discriminates internal faults from normal operating conditions including magnetic inrush and over-excitation. This paper concludes by implementing the algorithm into a prototype relay based on a digital signal processor.

  19. Fast noise level estimation algorithm based on principal component analysis transform and nonlinear rectification

    Science.gov (United States)

    Xu, Shaoping; Zeng, Xiaoxia; Jiang, Yinnan; Tang, Yiling

    2018-01-01

    We proposed a noniterative principal component analysis (PCA)-based noise level estimation (NLE) algorithm that addresses the problem of estimating the noise level with a two-step scheme. First, we randomly extracted a number of raw patches from a given noisy image and took the smallest eigenvalue of the covariance matrix of the raw patches as the preliminary estimation of the noise level. Next, the final estimation was directly obtained with a nonlinear mapping (rectification) function that was trained on some representative noisy images corrupted with different known noise levels. Compared with the state-of-art NLE algorithms, the experiment results show that the proposed NLE algorithm can reliably infer the noise level and has robust performance over a wide range of image contents and noise levels, showing a good compromise between speed and accuracy in general.

  20. Comparison of four Adaboost algorithm based artificial neural networks in wind speed predictions

    International Nuclear Information System (INIS)

    Liu, Hui; Tian, Hong-qi; Li, Yan-fei; Zhang, Lei

    2015-01-01

    Highlights: • Four hybrid algorithms are proposed for the wind speed decomposition. • Adaboost algorithm is adopted to provide a hybrid training framework. • MLP neural networks are built to do the forecasting computation. • Four important network training algorithms are included in the MLP networks. • All the proposed hybrid algorithms are suitable for the wind speed predictions. - Abstract: The technology of wind speed prediction is important to guarantee the safety of wind power utilization. In this paper, four different hybrid methods are proposed for the high-precision multi-step wind speed predictions based on the Adaboost (Adaptive Boosting) algorithm and the MLP (Multilayer Perceptron) neural networks. In the hybrid Adaboost–MLP forecasting architecture, four important algorithms are adopted for the training and modeling of the MLP neural networks, including GD-ALR-BP algorithm, GDM-ALR-BP algorithm, CG-BP-FR algorithm and BFGS algorithm. The aim of the study is to investigate the promoted forecasting percentages of the MLP neural networks by the Adaboost algorithm’ optimization under various training algorithms. The hybrid models in the performance comparison include Adaboost–GD-ALR-BP–MLP, Adaboost–GDM-ALR-BP–MLP, Adaboost–CG-BP-FR–MLP, Adaboost–BFGS–MLP, GD-ALR-BP–MLP, GDM-ALR-BP–MLP, CG-BP-FR–MLP and BFGS–MLP. Two experimental results show that: (1) the proposed hybrid Adaboost–MLP forecasting architecture is effective for the wind speed predictions; (2) the Adaboost algorithm has promoted the forecasting performance of the MLP neural networks considerably; (3) among the proposed Adaboost–MLP forecasting models, the Adaboost–CG-BP-FR–MLP model has the best performance; and (4) the improved percentages of the MLP neural networks by the Adaboost algorithm decrease step by step with the following sequence of training algorithms as: GD-ALR-BP, GDM-ALR-BP, CG-BP-FR and BFGS

  1. Wind dependence of ambient noise in a biologically rich coastal area.

    Science.gov (United States)

    Mathias, Delphine; Gervaise, Cédric; Di Iorio, Lucia

    2016-02-01

    The wind dependence of acoustic spectrum between 100 Hz and 16 kHz is investigated for coastal biologically rich areas. The analysis of 5 months of continuous measurements run in a 10 m deep shallow water environment off Brittany (France) showed that wind dependence of spectral levels is subject to masking by biological sounds. When dealing with raw data, the wind dependence of spectral levels was not significant for frequencies where biological sounds were present (2 to 10 kHz). An algorithm developed by Kinda, Simard, Gervaise, Mars, and Fortier [J. Acoust. Soc. Am. 134(1), 77-87 (2013)] was used to automatically filter out the loud distinctive biological contribution and estimated the ambient noise spectrum. The wind dependence of ambient noise spectrum was always significant after application of this filter. A mixture model for ambient noise spectrum which accounts for the richness of the soundscape is proposed. This model revealed that wind dependence holds once the wind speed was strong enough to produce sounds higher in amplitude than the biological chorus (9 kn at 3 kHz, 11 kn at 8 kHz). For these higher wind speeds, a logarithmic affine law was adequate and its estimated parameters were compatible with previous studies (average slope 27.1 dB per decade of wind speed increase).

  2. Noise pollution from wind turbine gears loudness of structural noise sources related to gears

    International Nuclear Information System (INIS)

    Crone, A.

    1995-04-01

    The purpose of the project has been to develop a method for determination of the structure-borne noise source strength of the gearbox in a typical modern Danish wind turbine construction, with special reference to the tonal noise emission form the turbines. Through study and evaluation of eight potential methods, a simple method has ben formulated. The method is based on measurements of the free vibration velocity level on the gearbox in a load test bed. The relation between this source strength measure and the gearbox related noise from wind turbines has been documented by measurements made during the project together with earlier measurements. The method is intended as a tool for the wind turbine manufacturer, for control of the gearbox related noise from the wind turbines, due to structure-borne noise from the gearbox. It may be used for preparation of specifications to the gearbox manufacturer on test procedure and acceptable source strength levels. Also, it may be used for evaluation of the transmission and radiation of gearbox related noise, for example in order to uncover weaknesses in a prototype turbine. Suggestions for adaptation and evolution of the method has been given, thereby improving the strength of the method for the individual wind turbine manufacturer. (au) 19 refs

  3. Annoyance, detection and recognition of wind turbine noise.

    Science.gov (United States)

    Van Renterghem, Timothy; Bockstael, Annelies; De Weirt, Valentine; Botteldooren, Dick

    2013-07-01

    Annoyance, recognition and detection of noise from a single wind turbine were studied by means of a two-stage listening experiment with 50 participants with normal hearing abilities. In-situ recordings made at close distance from a 1.8-MW wind turbine operating at 22 rpm were mixed with road traffic noise, and processed to simulate indoor sound pressure levels at LAeq 40 dBA. In a first part, where people were unaware of the true purpose of the experiment, samples were played during a quiet leisure activity. Under these conditions, pure wind turbine noise gave very similar annoyance ratings as unmixed highway noise at the same equivalent level, while annoyance by local road traffic noise was significantly higher. In a second experiment, listeners were asked to identify the sample containing wind turbine noise in a paired comparison test. The detection limit of wind turbine noise in presence of highway noise was estimated to be as low as a signal-to-noise ratio of -23 dBA. When mixed with local road traffic, such a detection limit could not be determined. These findings support that noticing the sound could be an important aspect of wind turbine noise annoyance at the low equivalent levels typically observed indoors in practice. Participants that easily recognized wind-turbine(-like) sounds could detect wind turbine noise better when submersed in road traffic noise. Recognition of wind turbine sounds is also linked to higher annoyance. Awareness of the source is therefore a relevant aspect of wind turbine noise perception which is consistent with previous research. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. The noise generated by wind turbines

    International Nuclear Information System (INIS)

    Anon.

    2012-01-01

    Sound propagation damps down with distance and varies according to different parameters like wind direction and temperature. This article begins by recalling the basic physics of sound wave propagation and gives a list of common noises and corresponding decibels. The habitual noise of wind turbines 500 m away is 35 decibels which ranks it between a quiet bedroom (30 decibels) and a calm office (40 decibels). The question about whether wind turbines are a noise nuisance is all the more difficult as the feeling of a nuisance is so objective and personal. Any project of wind turbines requires a thorough study of its estimated acoustic impact. This study is a 3 step approach: first the initial noise environment is measured, secondly the propagation of the sound generated by the wind turbine farm is modelled and adequate mitigation measures are proposed to comply the law. The law stipulates that the increase of noise must be less than 5 db during daylight and less than 3 db during night. (A.C.)

  5. Evaluation of Noise Exposure Secondary to Wind Noise in Cyclists.

    Science.gov (United States)

    Seidman, Michael D; Wertz, Anna G; Smith, Matthew M; Jacob, Steve; Ahsan, Syed F

    2017-11-01

    Objective Determine if the noise levels of wind exposure experienced by cyclists reach levels that could contribute to noise-induced hearing loss. Study Design Industrial lab research. Setting Industrial wind tunnel. Subjects and Methods A commercial-grade electric wind tunnel was used to simulate different speeds encountered by a cyclist. A single cyclist was used during the simulation for audiometric measurements. Microphones attached near the ears of the cyclist were used to measure the sound (dB sound pressure level) experienced by the cyclist. Loudness levels were measured with the head positioned at 15-degree increments from 0 degrees to 180 degrees relative to the oncoming wind at different speeds (10-60 mph). Results Wind noise ranged from 84.9 dB at 10 mph and increased proportionally with speed to a maximum of 120.3 dB at 60 mph. The maximum of 120.3 dB was measured at the downwind ear when the ear was 90 degrees away from the wind. Conclusions Wind noise experienced by a cyclist is proportional to the speed and the directionality of the wind current. Turbulent air flow patterns are observed that contribute to increased sound exposure in the downwind ear. Consideration of ear deflection equipment without compromising sound awareness for cyclists during prolonged rides is advised to avoid potential noise trauma. Future research is warranted and can include long-term studies including dosimetry measures of the sound and yearly pre- and postexposure audiograms of cyclists to detect if any hearing loss occurs with long-term cycling.

  6. Preliminary Assessment of Noise Pollution Prevention in Wind Turbines Based on an Exergy Approach

    Directory of Open Access Journals (Sweden)

    Ofelia A. Jianu

    2017-06-01

    Full Text Available Most existing methods for energy transformation and use are inadvertently contaminating our watersupplies, releasing greenhouse gasses into the atmosphere, emitting compounds that diminish the earth'sprotective blanket of ozone, and depleting the earth's crust of natural resources. As a result, scientists andengineers are increasingly pursuing sustainable technologies so that costs associated with global warmingcan be minimized and adverse impact on living organisms can be prevented. A promising sustainablemethod is to harness energy from the wind via wind turbines. However, the noise generated by wind turbinesproves to be one of the most significant hindrances to the extensive use of wind turbines. In this study,noise generation produced by flow over objects is investigated to characterize the noise generated due toflow-structure interaction and aeroacoustics. As a benchmark, flow over a cylinder has been chosen for thisstudy, with the aim of correlating three main characteristics in noise generation. Hence, the generated soundpressure level, exergy destroyed and the normal flow velocity (∪ ∞ are employed to characterize the systemin order to relate the exergy destruction to the noise generated in the flow. The correlation has the potentialto be used in wind turbine designs to minimize noise pollution due to aerodynamic noise.

  7. Estimations of Kappa parameter using quasi-thermal noise spectroscopy: Applications on Wind spacecraft

    Science.gov (United States)

    Martinović, M.

    2017-12-01

    Quasi-thermal noise (QTN) spectroscopy is an accurate technique for in situ measurements of electron density and temperature in space plasmas. The QTN spectrum has a characteristic noise peak just above the plasma frequency produced by electron quasi-thermal fluctuations, which allows a very accurate measurement of the electron density. The size and shape of the peak are determined by suprathermal electrons. Since this nonthermal electron population is well described by a generalized Lorentzian - Kappa velocity distribution, it is possible to determinate the distribution properties in the solar wind from a measured spectrum. In this work, we discuss some basic properties of the QTN spectrum dependence of the Kappa distribution parameters - total electron density, temperature and the Kappa index, giving an overview on how instrument characteristics and environment conditions affect quality of the measurements. Further on, we aim to apply the method to Wind Thermal Noise Receiver (TNR) measurements. However, the spectra observed by this instrument usually contain contributions from nonthermal phenomena, like ion acoustic waves below, or galactic noise above the plasma frequency. This is why, besides comparison of the theory with observations, work with Wind data requires development of a sophisticated algorithm that distinguish parts of the spectra that are dominated by the QTN, and therefore can be used in our study. Postulates of this algorithm, as well as major results of its implementation, are also presented.

  8. Annoyance rating of wind turbine noise

    International Nuclear Information System (INIS)

    Iredale, R.A.

    1992-01-01

    This paper proposes a simple criterion for noise limitation of wind turbines: 'The La A50 from a Wind Farm should not exceeding the L A50 of the wind generated background plus 5dB at any place of potential complaint'. This criterion is then examined and developed in the light of experience to date with turbine noise complaint and procedures. (author)

  9. Noise from wind power plants

    International Nuclear Information System (INIS)

    Ljunggren, S.

    2001-12-01

    First, the generation of noise at wind power plants and the character of the sound is described. The propagation of the sound and its dependence on the structure of the ground and on wind and temperature is treated next. Models for calculation of the noise emission are reviewed and examples of applications are given. Different means for reducing the disturbances are described

  10. Aero-acoustics noise assessment for Wind-Lens turbine

    International Nuclear Information System (INIS)

    Hashem, I.; Mohamed, M.H.; Hafiz, A.A.

    2017-01-01

    This paper introduces an aero-acoustic computational study that investigates the noise caused by one of the most promising wind energy conversion concepts, namely the 'Wind-Lens' technology. The hybrid method - where the flow field and acoustic field are solved separately, was deemed to be an appropriate tool to compute this study. The need to investigate this phenomenon increased gradually, since the feasibility of utilizing Wind-Lens turbine within densely populated cities and urban areas depends largely on their noise generation. Ffowcs Williams-Hawkings (FW-H) equation and its integral solution are used to predict the noise radiating to the farfield. CFD Simulations of transient three-dimensional flow field using (URANS) unsteady Reynolds-averaged Navier-Stokes equations are computed to acquire the acoustic sources location and sound intensity. Then, the noise propagates from the before-mentioned sources to pre-defined virtual microphones positioned in different locations. ANSYS-FLUENT is used to calculate the flow field on and around such turbines which is required for the FW-H code. Some effective parameters are investigated such as Wind-Lens shape, brim height and tip speed ratio. Comparison of the noise emitted from the bare wind turbine and different types of Wind-Lens turbine reveals that, the Wind-Lens generates higher noise intensity. - Highlights: • Aero-acoustic noise generated by wind turbines are one of the major challenges. • Noise from wind turbine equipped with a brimmed diffuser is investigated. • A computational aero-acoustic study using the hybrid method is introduced. • Effective parameters are studied such Wind-Lens shape, brim height and speed ratio. • The optimal shape has a moderate power coefficient and the less noise generation.

  11. Adaptive neuro-fuzzy methodology for noise assessment of wind turbine.

    Science.gov (United States)

    Shamshirband, Shahaboddin; Petković, Dalibor; Hashim, Roslan; Motamedi, Shervin

    2014-01-01

    Wind turbine noise is one of the major obstacles for the widespread use of wind energy. Noise tone can greatly increase the annoyance factor and the negative impact on human health. Noise annoyance caused by wind turbines has become an emerging problem in recent years, due to the rapid increase in number of wind turbines, triggered by sustainable energy goals set forward at the national and international level. Up to now, not all aspects of the generation, propagation and perception of wind turbine noise are well understood. For a modern large wind turbine, aerodynamic noise from the blades is generally considered to be the dominant noise source, provided that mechanical noise is adequately eliminated. The sources of aerodynamic noise can be divided into tonal noise, inflow turbulence noise, and airfoil self-noise. Many analytical and experimental acoustical studies performed the wind turbines. Since the wind turbine noise level analyzing by numerical methods or computational fluid dynamics (CFD) could be very challenging and time consuming, soft computing techniques are preferred. To estimate noise level of wind turbine, this paper constructed a process which simulates the wind turbine noise levels in regard to wind speed and sound frequency with adaptive neuro-fuzzy inference system (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

  12. Ultra-Short-Term Wind-Power Forecasting Based on the Weighted Random Forest Optimized by the Niche Immune Lion Algorithm

    Directory of Open Access Journals (Sweden)

    Dongxiao Niu

    2018-04-01

    Full Text Available The continuous increase in energy consumption has made the potential of wind-power generation tremendous. However, the obvious intermittency and randomness of wind speed results in the fluctuation of the output power in a wind farm, seriously affecting the power quality. Therefore, the accurate prediction of wind power in advance can improve the ability of wind-power integration and enhance the reliability of the power system. In this paper, a model of wavelet decomposition (WD and weighted random forest (WRF optimized by the niche immune lion algorithm (NILA-WRF is presented for ultra-short-term wind power prediction. Firstly, the original serials of wind speed and power are decomposed into several sub-serials by WD because the original serials have no obvious day characteristics. Then, the model parameters are set and the model trained with the sub-serials of wind speed and wind power decomposed. Finally, the WD-NILA-WRF model is used to predict the wind power of the relative sub-serials and the result is reconstructed to obtain the final prediction result. The WD-NILA-WRF model combines the advantage of each single model, which uses WD for signal de-noising, and uses the niche immune lion algorithm (NILA to improve the model’s optimization efficiency. In this paper, two empirical analyses are carried out to prove the accuracy of the model, and the experimental results verify the proposed model’s validity and superiority compared with the back propagation neural network (BP neural network, support vector machine (SVM, RF and NILA-RF, indicating that the proposed method is superior in cases influenced by noise and unstable factors, and possesses an excellent generalization ability and robustness.

  13. Adaptive Neuro-Fuzzy Methodology for Noise Assessment of Wind Turbine

    Science.gov (United States)

    Shamshirband, Shahaboddin; Petković, Dalibor; Hashim, Roslan; Motamedi, Shervin

    2014-01-01

    Wind turbine noise is one of the major obstacles for the widespread use of wind energy. Noise tone can greatly increase the annoyance factor and the negative impact on human health. Noise annoyance caused by wind turbines has become an emerging problem in recent years, due to the rapid increase in number of wind turbines, triggered by sustainable energy goals set forward at the national and international level. Up to now, not all aspects of the generation, propagation and perception of wind turbine noise are well understood. For a modern large wind turbine, aerodynamic noise from the blades is generally considered to be the dominant noise source, provided that mechanical noise is adequately eliminated. The sources of aerodynamic noise can be divided into tonal noise, inflow turbulence noise, and airfoil self-noise. Many analytical and experimental acoustical studies performed the wind turbines. Since the wind turbine noise level analyzing by numerical methods or computational fluid dynamics (CFD) could be very challenging and time consuming, soft computing techniques are preferred. To estimate noise level of wind turbine, this paper constructed a process which simulates the wind turbine noise levels in regard to wind speed and sound frequency with adaptive neuro-fuzzy inference system (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method. PMID:25075621

  14. Adaptive neuro-fuzzy methodology for noise assessment of wind turbine.

    Directory of Open Access Journals (Sweden)

    Shahaboddin Shamshirband

    Full Text Available Wind turbine noise is one of the major obstacles for the widespread use of wind energy. Noise tone can greatly increase the annoyance factor and the negative impact on human health. Noise annoyance caused by wind turbines has become an emerging problem in recent years, due to the rapid increase in number of wind turbines, triggered by sustainable energy goals set forward at the national and international level. Up to now, not all aspects of the generation, propagation and perception of wind turbine noise are well understood. For a modern large wind turbine, aerodynamic noise from the blades is generally considered to be the dominant noise source, provided that mechanical noise is adequately eliminated. The sources of aerodynamic noise can be divided into tonal noise, inflow turbulence noise, and airfoil self-noise. Many analytical and experimental acoustical studies performed the wind turbines. Since the wind turbine noise level analyzing by numerical methods or computational fluid dynamics (CFD could be very challenging and time consuming, soft computing techniques are preferred. To estimate noise level of wind turbine, this paper constructed a process which simulates the wind turbine noise levels in regard to wind speed and sound frequency with adaptive neuro-fuzzy inference system (ANFIS. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

  15. Multi-step wind speed forecasting based on a hybrid forecasting architecture and an improved bat algorithm

    International Nuclear Information System (INIS)

    Xiao, Liye; Qian, Feng; Shao, Wei

    2017-01-01

    Highlights: • Propose a hybrid architecture based on a modified bat algorithm for multi-step wind speed forecasting. • Improve the accuracy of multi-step wind speed forecasting. • Modify bat algorithm with CG to improve optimized performance. - Abstract: As one of the most promising sustainable energy sources, wind energy plays an important role in energy development because of its cleanliness without causing pollution. Generally, wind speed forecasting, which has an essential influence on wind power systems, is regarded as a challenging task. Analyses based on single-step wind speed forecasting have been widely used, but their results are insufficient in ensuring the reliability and controllability of wind power systems. In this paper, a new forecasting architecture based on decomposing algorithms and modified neural networks is successfully developed for multi-step wind speed forecasting. Four different hybrid models are contained in this architecture, and to further improve the forecasting performance, a modified bat algorithm (BA) with the conjugate gradient (CG) method is developed to optimize the initial weights between layers and thresholds of the hidden layer of neural networks. To investigate the forecasting abilities of the four models, the wind speed data collected from four different wind power stations in Penglai, China, were used as a case study. The numerical experiments showed that the hybrid model including the singular spectrum analysis and general regression neural network with CG-BA (SSA-CG-BA-GRNN) achieved the most accurate forecasting results in one-step to three-step wind speed forecasting.

  16. Research status and trend of wind turbine aerodynamic noise?

    Institute of Scientific and Technical Information of China (English)

    Xiaodong LI; Baohong BAI; Yingbo XU; Min JIANG

    2016-01-01

    The main components of the wind turbine aerodynamic noise are introduced. A detailed review is given on the theoretical prediction, experimental measurement, and numerical simulation methods of wind turbine noise, with speci?c attention to appli-cations. Furthermore, suppression techniques of wind turbine aerodynamic noise are discussed. The perspective of future research on the wind turbine aerodynamic noise is presented.

  17. Impact of wind turbine noise in the Netherlands.

    Science.gov (United States)

    Verheijen, Edwin; Jabben, Jan; Schreurs, Eric; Smith, Kevin B

    2011-01-01

    The Dutch government aims at an increase of wind energy up to 6 000 MW in 2020 by placing new wind turbines on land or offshore. At the same time, the existing noise legislation for wind turbines is being reconsidered. For the purpose of establishing a new noise reception limit value expressed in L den , the impact of wind turbine noise under the given policy targets needs to be explored. For this purpose, the consequences of different reception limit values for the new Dutch noise legislation have been studied, both in terms of effects on the population and regarding sustainable energy policy targets. On the basis of a nation-wide noise map containing all wind turbines in The Netherlands, it is calculated that 3% of the inhabitants of The Netherlands are currently exposed to noise from wind turbines above 28 dB(A) at the faηade. Newly established dose-response relationships indicate that about 1500 of these inhabitants are likely to be severely annoyed inside their dwellings. The available space for new wind turbines strongly depends on the noise limit value that will be chosen. This study suggests an outdoor A-weighted reception limit of L den = 45 dB as a trade-off between the need for protection against noise annoyance and the feasibility of national targets for renewable energy.

  18. An NMR log echo data de-noising method based on the wavelet packet threshold algorithm

    International Nuclear Information System (INIS)

    Meng, Xiangning; Xie, Ranhong; Li, Changxi; Hu, Falong; Li, Chaoliu; Zhou, Cancan

    2015-01-01

    To improve the de-noising effects of low signal-to-noise ratio (SNR) nuclear magnetic resonance (NMR) log echo data, this paper applies the wavelet packet threshold algorithm to the data. The principle of the algorithm is elaborated in detail. By comparing the properties of a series of wavelet packet bases and the relevance between them and the NMR log echo train signal, ‘sym7’ is found to be the optimal wavelet packet basis of the wavelet packet threshold algorithm to de-noise the NMR log echo train signal. A new method is presented to determine the optimal wavelet packet decomposition scale; this is within the scope of its maximum, using the modulus maxima and the Shannon entropy minimum standards to determine the global and local optimal wavelet packet decomposition scales, respectively. The results of applying the method to the simulated and actual NMR log echo data indicate that compared with the wavelet threshold algorithm, the wavelet packet threshold algorithm, which shows higher decomposition accuracy and better de-noising effect, is much more suitable for de-noising low SNR–NMR log echo data. (paper)

  19. Proceedings of a workshop on wind turbine noise

    International Nuclear Information System (INIS)

    Legerton, M.

    1993-08-01

    Noise generated by wind turbines is an environmental constraint on the exploitation of wind energy. It is a major consideration when seeking planning consent for the siting of machines due to the high population density in the UK and low levels of background noise in rural areas. There is, therefore, a need to identify the sources and characteristics of noise emitted by wind turbine generators, assess the influences on the propagation of noise through the atmosphere, and provide information to both wind farm developers and planning regulators on noise levels. A one day workshop was organised to provide an opportunity for experts in the field of wind turbine noise to present the current thoughts on the subject and so allow a wide ranging discussion of particular issues of interest. This volume contains the 10 papers presented at the workshop for each of which a separate abstract has been prepared. (author)

  20. Wind Noise Reduction in a Non-Porous Subsurface Windscreen

    Science.gov (United States)

    Zuckerwar, Allan J.; Shams, Qamar A.; Knight, H. Keith

    2012-01-01

    Measurements of wind noise reduction were conducted on a box-shaped, subsurface windscreen made of closed cell polyurethane foam. The windscreen was installed in the ground with the lid flush with the ground surface. The wind was generated by means of a fan, situated on the ground, and the wind speed was measured at the center of the windscreen lid with an ultrasonic anemometer. The wind speed was controlled by moving the fan to selected distances from the windscreen. The wind noise was measured on a PCB Piezotronics 3†electret microphone. Wind noise spectra were measured with the microphone exposed directly to the wind (atop the windscreen lid) and with the microphone installed inside the windscreen. The difference between the two spectra comprises the wind noise reduction. At wind speeds of 3, 5, and 7 m/s, the wind noise reduction is typically 15 dB over the frequency range of 0.1-20 Hz.

  1. Noise measurements in 4 wind turbine farms

    International Nuclear Information System (INIS)

    Van Zuylen, E.J.; Koerts, M.

    1993-02-01

    The title wind turbine arrays are situated in Herbayum (Newinco 23PI250), Callantsoog (Bouma 160/20), Noordoostpolder (Windmaster WM300), and Ulketocht (Newinco 500 kW). Measurements were carried out by means of the so-called Ecofys Correlating Noise Meter to determine the source level of the wind turbines. The resulting source level as a function of the wind speed is interpolated to a source level for a wind speed of 8 m/s at 10 m height, on the basis of which the noise contours can be calculated. The noise contours are determined to analyze the noise load for people living in the neighbourhood of the wind parks. The source levels are compared with values as indicated in certificates, which are granted on the basis of a so-called Restricted Quality Certificate (BKC, abbreviated in Dutch) or the new standard NNI 6096/2 for the above-mentioned wind turbines. In general the results of this study agree quite well with the certified values. 12 figs., 7 tabs., 6 refs

  2. Wind turbines - generating noise or electricity?

    International Nuclear Information System (INIS)

    Russell, Eric

    1999-01-01

    Wind turbine technology has made great strides in the past few years. Annual energy output is up by two orders of magnitude and nacelle weight and noise has been halved. Computational fluid dynamics has paid a part in advancing knowledge of air flow and turbulence around wind generators. Current research is focused on how to increase turbine size and improve efficiency. A problem is that while larger wind turbines will produce cheaper electricity, the noise problem will mean that the number of acceptable sites will decrease. The biggest wind generators will need about 800 m clearance from the nearest house. (UK)

  3. Health Effects Related to Wind Turbine Noise Exposure

    DEFF Research Database (Denmark)

    Schmidt, Jesper Hvass; Klokker, Mads

    2014-01-01

    BACKGROUND: Wind turbine noise exposure and suspected health-related effects thereof have attracted substantial attention. Various symptoms such as sleep-related problems, headache, tinnitus and vertigo have been described by subjects suspected of having been exposed to wind turbine noise...... existing statistically-significant evidence indicating any association between wind turbine noise exposure and tinnitus, hearing loss, vertigo or headache. LIMITATIONS: Selection bias and information bias of differing magnitudes were found to be present in all current studies investigating wind turbine...

  4. Wind turbine airfoil design method with low noise and experimental analysis

    DEFF Research Database (Denmark)

    Wang, Quan; Chen, Jin; Cheng, Jiangtao

    2015-01-01

    In order to study the noise characteristic of wind turbine airfoils, the airfoil optimal design mathematic model was built based on airfoil functional integrated theory and noise calculated model. The new optimized objective function of maximizing lift/drag to noise was developed on the design......, though there is a certain difference between the theory results and experiment data. Compared with NACA-64-618 airfoil, the CQU-DTU-B18 airfoil exhibits lower noise, which validates the feasibility of this design method. It is a guide to design wind turbine airfoil with lower noise and to reduce airfoil...

  5. Wavelet Adaptive Algorithm and Its Application to MRE Noise Control System

    Directory of Open Access Journals (Sweden)

    Zhang Yulin

    2015-01-01

    Full Text Available To address the limitation of conventional adaptive algorithm used for active noise control (ANC system, this paper proposed and studied two adaptive algorithms based on Wavelet. The twos are applied to a noise control system including magnetorheological elastomers (MRE, which is a smart viscoelastic material characterized by a complex modulus dependent on vibration frequency and controllable by external magnetic fields. Simulation results reveal that the Decomposition LMS algorithm (D-LMS and Decomposition and Reconstruction LMS algorithm (DR-LMS based on Wavelet can significantly improve the noise reduction performance of MRE control system compared with traditional LMS algorithm.

  6. Potential of neuro-fuzzy methodology to estimate noise level of wind turbines

    Science.gov (United States)

    Nikolić, Vlastimir; Petković, Dalibor; Por, Lip Yee; Shamshirband, Shahaboddin; Zamani, Mazdak; Ćojbašić, Žarko; Motamedi, Shervin

    2016-01-01

    Wind turbines noise effect became large problem because of increasing of wind farms numbers since renewable energy becomes the most influential energy sources. However, wind turbine noise generation and propagation is not understandable in all aspects. Mechanical noise of wind turbines can be ignored since aerodynamic noise of wind turbine blades is the main source of the noise generation. Numerical simulations of the noise effects of the wind turbine can be very challenging task. Therefore in this article soft computing method is used to evaluate noise level of wind turbines. The main goal of the study is to estimate wind turbine noise in regard of wind speed at different heights and for different sound frequency. Adaptive neuro-fuzzy inference system (ANFIS) is used to estimate the wind turbine noise levels.

  7. Applications of aero-acoustic analysis to wind turbine noise control

    International Nuclear Information System (INIS)

    Lowson, M.V.

    1992-01-01

    Wind turbine noise generation mechanisms are essentially equivalent to the aero-acoustic mechanisms of other rotors, which have been studied in depth for many years. Basic sources for the wind turbine noise radiation process are defined, and their significance assessed. From the analysis, areas of potential improvement in wind turbine noise prediction are defined. Suggestions are made for approaches to wind turbine noise control which separate the noise problems at cut-in from those at rated power. Some of these offer the possibility of noise reduction without unfavourable effects on performance. (author)

  8. Applications of aero-acoustic analysis to wind turbine noise control

    International Nuclear Information System (INIS)

    Lowson, M.

    1993-01-01

    Wind turbine noise generation mechanisms are essentially equivalent to the aero-acoustic mechanisms of other rotors, which have been studied in depth for many years. Basic sources for the wind turbine noise radiation process are defined, and their significance assessed. From the analysis, areas of potential improvement in wind turbine noise prediction are defined. Suggestions are made for approaches to wind turbine noise control which separate the noise problems at cut-in from those at rated power. Some of these offer the possibility of noise reduction without unfavourable effects on performance. (author)

  9. Research status on aero-acoustic noise from wind turbine blades

    International Nuclear Information System (INIS)

    Yang, B

    2013-01-01

    This paper describes the noise mechanisms and categories of modern large wind turbine and main noise sources. Then the latest progresses in wind turbine noise researches are described from three aspects: noise prediction model, detection of noise sources by microphone array technique and methods for noise reduction. Although the turbine is restricted to horizontal axis wind turbines, the noise prediction model and reduction methods also can be applied to other turbines when the noise mechanisms are similar. Microphone array technique can be applied to locate any kind of noise sources

  10. Maximum power point tracking-based control algorithm for PMSG wind generation system without mechanical sensors

    International Nuclear Information System (INIS)

    Hong, Chih-Ming; Chen, Chiung-Hsing; Tu, Chia-Sheng

    2013-01-01

    Highlights: ► This paper presents MPPT based control for optimal wind energy capture using RBFN. ► MPSO is adopted to adjust the learning rates to improve the learning capability. ► This technique can maintain the system stability and reach the desired performance. ► The EMF in the rotating reference frame is utilized in order to estimate speed. - Abstract: This paper presents maximum-power-point-tracking (MPPT) based control algorithms for optimal wind energy capture using radial basis function network (RBFN) and a proposed torque observer MPPT algorithm. The design of a high-performance on-line training RBFN using back-propagation learning algorithm with modified particle swarm optimization (MPSO) regulating controller for the sensorless control of a permanent magnet synchronous generator (PMSG). The MPSO is adopted in this study to adapt the learning rates in the back-propagation process of the RBFN to improve the learning capability. The PMSG is controlled by the loss-minimization control with MPPT below the base speed, which corresponds to low and high wind speed, and the maximum energy can be captured from the wind. Then the observed disturbance torque is feed-forward to increase the robustness of the PMSG system

  11. Comparison of SAR Wind Speed Retrieval Algorithms for Evaluating Offshore Wind Energy Resources

    DEFF Research Database (Denmark)

    Kozai, K.; Ohsawa, T.; Takeyama, Y.

    2010-01-01

    Envisat/ASAR-derived offshore wind speeds and energy densities based on 4 different SAR wind speed retrieval algorithms (CMOD4, CMOD-IFR2, CMOD5, CMOD5.N) are compared with observed wind speeds and energy densities for evaluating offshore wind energy resources. CMOD4 ignores effects of atmospheri...

  12. Assessing noise from wind farm developments in Ireland: A consideration of critical wind speeds and turbine choice

    International Nuclear Information System (INIS)

    King, E.A.; Pilla, F.; Mahon, J.

    2012-01-01

    Wind farms are becoming increasingly popular in Ireland in an effort to increase the production of green energy within the state. As with any infrastructural development, wind farms must consider potential environmental impacts prior to construction. One particular issue that must be examined is the emission of noise from the development. In Ireland wind farm developments must adhere to planning conditions that usually outline permissible noise levels for both the construction and operational phases of the development. The critical wind speed is often cited as the wind speed at which these limits apply. This paper examines how the critical wind speed is determined and investigates its relationship with background noise levels and turbine choice. The study consisted of ten one-week monitoring periods during which meteorological conditions and background noise levels were simultaneously recorded. It was found that the critical wind speed is non-transferable, i.e. it depends on both the turbine choice and background noise environment and is specific to that particular turbine/site combination. Furthermore the critical wind speed during the night-time is often different to the overall critical wind speed suggesting that future noise studies should consider a range of critical wind speeds, particularly for night-time noise assessments. - Highlights: ► This paper considers the use of the critical wind speed when assessing noise impacts from wind farms. ► It was found that the critical wind speed could vary depending on the time of the day. ► The critical wind speed was found to be a non-transferable value. ► Noise assessments for wind farms should be developed over a range of critical wind speeds.

  13. Wind Turbine Generator System Acoustic Noise Test Report for the Gaia Wind 11-kW Wind Turbine

    Energy Technology Data Exchange (ETDEWEB)

    Huskey, A.

    2011-11-01

    This report details the acoustic noise test conducted on the Gaia-Wind 11-kW wind turbine at the National Wind Technology Center. The test turbine is a two- bladed, downwind wind turbine with a rated power of 11 kW. The test turbine was tested in accordance with the International Electrotechnical Commission standard, IEC 61400-11 Ed 2.1 2006-11 Wind Turbine Generator Systems -- Part 11 Acoustic Noise Measurement Techniques.

  14. Health effects related to wind turbine noise exposure: a systematic review.

    Science.gov (United States)

    Schmidt, Jesper Hvass; Klokker, Mads

    2014-01-01

    Wind turbine noise exposure and suspected health-related effects thereof have attracted substantial attention. Various symptoms such as sleep-related problems, headache, tinnitus and vertigo have been described by subjects suspected of having been exposed to wind turbine noise. This review was conducted systematically with the purpose of identifying any reported associations between wind turbine noise exposure and suspected health-related effects. A search of the scientific literature concerning the health-related effects of wind turbine noise was conducted on PubMed, Web of Science, Google Scholar and various other Internet sources. All studies investigating suspected health-related outcomes associated with wind turbine noise exposure were included. Wind turbines emit noise, including low-frequency noise, which decreases incrementally with increases in distance from the wind turbines. Likewise, evidence of a dose-response relationship between wind turbine noise linked to noise annoyance, sleep disturbance and possibly even psychological distress was present in the literature. Currently, there is no further existing statistically-significant evidence indicating any association between wind turbine noise exposure and tinnitus, hearing loss, vertigo or headache. Selection bias and information bias of differing magnitudes were found to be present in all current studies investigating wind turbine noise exposure and adverse health effects. Only articles published in English, German or Scandinavian languages were reviewed. Exposure to wind turbines does seem to increase the risk of annoyance and self-reported sleep disturbance in a dose-response relationship. There appears, though, to be a tolerable level of around LAeq of 35 dB. Of the many other claimed health effects of wind turbine noise exposure reported in the literature, however, no conclusive evidence could be found. Future studies should focus on investigations aimed at objectively demonstrating whether or not

  15. The assessment and rating of noise from wind farms. Final report

    International Nuclear Information System (INIS)

    1996-09-01

    The findings of a Working Group on Wind Turbine Noise in the United Kingdom are presented. The broad topics covered are: the philosophy and practice of noise emission control; description of noise emission from wind turbines; a review of current practice and guidance; a survey of public reaction to noise from wind farms; recommendations on noise limits; noise monitoring; the planning obligation. In deriving suggested noise limits, a reasonable degree of protection to wind farm neighbours has been sought which will not place unreasonable restrictions and undue added costs and administrative burdens on wind farm developers or local authorities. Examples of practice in the control of noise emissions at wind farms in the United Kingdom and the USA are assembled in an Appendix. (29 figures; 13 tables; 32 references) (UK)

  16. Research on wind field algorithm of wind lidar based on BP neural network and grey prediction

    Science.gov (United States)

    Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei

    2018-01-01

    This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.

  17. Characterization and Impact of Low Frequency Wind Turbine Noise Emissions

    Science.gov (United States)

    Finch, James

    Wind turbine noise is a complex issue that requires due diligence to minimize any potential impact on quality of life. This study enhances existing knowledge of wind turbine noise through focused analyses of downwind sound propagation, directionality, and the low frequency component of the noise. Measurements were conducted at four wind speeds according to a design of experiments at incremental distances and angles. Wind turbine noise is shown to be highly directional, while downwind sound propagation is spherical with limited ground absorption. The noise is found to have a significant low frequency component that is largely independent of wind speed over the 20-250 Hz range. The generated low frequency noise is shown to be audible above 40 Hz at the MOE setback distance of 550 m. Infrasound levels exhibit higher dependency on wind speed, but remain below audible levels up to 15 m/s.

  18. A Novel Integrated Algorithm for Wind Vector Retrieval from Conically Scanning Scatterometers

    Directory of Open Access Journals (Sweden)

    Xuetong Xie

    2013-11-01

    Full Text Available Due to the lower efficiency and the larger wind direction error of traditional algorithms, a novel integrated wind retrieval algorithm is proposed for conically scanning scatterometers. The proposed algorithm has the dual advantages of less computational cost and higher wind direction retrieval accuracy by integrating the wind speed standard deviation (WSSD algorithm and the wind direction interval retrieval (DIR algorithm. It adopts wind speed standard deviation as a criterion for searching possible wind vector solutions and retrieving a potential wind direction interval based on the change rate of the wind speed standard deviation. Moreover, a modified three-step ambiguity removal method is designed to let more wind directions be selected in the process of nudging and filtering. The performance of the new algorithm is illustrated by retrieval experiments using 300 orbits of SeaWinds/QuikSCAT L2A data (backscatter coefficients at 25 km resolution and co-located buoy data. Experimental results indicate that the new algorithm can evidently enhance the wind direction retrieval accuracy, especially in the nadir region. In comparison with the SeaWinds L2B Version 2 25 km selected wind product (retrieved wind fields, an improvement of 5.1° in wind direction retrieval can be made by the new algorithm for that region.

  19. Optimization of wind farm turbines layout using an evolutive algorithm

    International Nuclear Information System (INIS)

    Gonzalez, Javier Serrano; Santos, Jesus Riquelme; Payan, Manuel Burgos; Gonzalez Rodriguez, Angel G.; Mora, Jose Castro

    2010-01-01

    The optimum wind farm configuration problem is discussed in this paper and an evolutive algorithm to optimize the wind farm layout is proposed. The algorithm's optimization process is based on a global wind farm cost model using the initial investment and the present value of the yearly net cash flow during the entire wind-farm life span. The proposed algorithm calculates the yearly income due to the sale of the net generated energy taking into account the individual wind turbine loss of production due to wake decay effects and it can deal with areas or terrains with non-uniform load-bearing capacity soil and different roughness length for every wind direction or restrictions such as forbidden areas or limitations in the number of wind turbines or the investment. The results are first favorably compared with those previously published and a second collection of test cases is used to proof the performance and suitability of the proposed evolutive algorithm to find the optimum wind farm configuration. (author)

  20. Wind reconstruction algorithm for Viking Lander 1

    Science.gov (United States)

    Kynkäänniemi, Tuomas; Kemppinen, Osku; Harri, Ari-Matti; Schmidt, Walter

    2017-06-01

    The wind measurement sensors of Viking Lander 1 (VL1) were only fully operational for the first 45 sols of the mission. We have developed an algorithm for reconstructing the wind measurement data after the wind measurement sensor failures. The algorithm for wind reconstruction enables the processing of wind data during the complete VL1 mission. The heater element of the quadrant sensor, which provided auxiliary measurement for wind direction, failed during the 45th sol of the VL1 mission. Additionally, one of the wind sensors of VL1 broke down during sol 378. Regardless of the failures, it was still possible to reconstruct the wind measurement data, because the failed components of the sensors did not prevent the determination of the wind direction and speed, as some of the components of the wind measurement setup remained intact for the complete mission. This article concentrates on presenting the wind reconstruction algorithm and methods for validating the operation of the algorithm. The algorithm enables the reconstruction of wind measurements for the complete VL1 mission. The amount of available sols is extended from 350 to 2245 sols.

  1. Wind reconstruction algorithm for Viking Lander 1

    Directory of Open Access Journals (Sweden)

    T. Kynkäänniemi

    2017-06-01

    Full Text Available The wind measurement sensors of Viking Lander 1 (VL1 were only fully operational for the first 45 sols of the mission. We have developed an algorithm for reconstructing the wind measurement data after the wind measurement sensor failures. The algorithm for wind reconstruction enables the processing of wind data during the complete VL1 mission. The heater element of the quadrant sensor, which provided auxiliary measurement for wind direction, failed during the 45th sol of the VL1 mission. Additionally, one of the wind sensors of VL1 broke down during sol 378. Regardless of the failures, it was still possible to reconstruct the wind measurement data, because the failed components of the sensors did not prevent the determination of the wind direction and speed, as some of the components of the wind measurement setup remained intact for the complete mission. This article concentrates on presenting the wind reconstruction algorithm and methods for validating the operation of the algorithm. The algorithm enables the reconstruction of wind measurements for the complete VL1 mission. The amount of available sols is extended from 350 to 2245 sols.

  2. Seismic noise attenuation using an online subspace tracking algorithm

    NARCIS (Netherlands)

    Zhou, Yatong; Li, Shuhua; Zhang, D.; Chen, Yangkang

    2018-01-01

    We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient

  3. Rolling scheduling of electric power system with wind power based on improved NNIA algorithm

    Science.gov (United States)

    Xu, Q. S.; Luo, C. J.; Yang, D. J.; Fan, Y. H.; Sang, Z. X.; Lei, H.

    2017-11-01

    This paper puts forth a rolling modification strategy for day-ahead scheduling of electric power system with wind power, which takes the operation cost increment of unit and curtailed wind power of power grid as double modification functions. Additionally, an improved Nondominated Neighbor Immune Algorithm (NNIA) is proposed for solution. The proposed rolling scheduling model has further improved the operation cost of system in the intra-day generation process, enhanced the system’s accommodation capacity of wind power, and modified the key transmission section power flow in a rolling manner to satisfy the security constraint of power grid. The improved NNIA algorithm has defined an antibody preference relation model based on equal incremental rate, regulation deviation constraints and maximum & minimum technical outputs of units. The model can noticeably guide the direction of antibody evolution, and significantly speed up the process of algorithm convergence to final solution, and enhance the local search capability.

  4. A new wind speed forecasting strategy based on the chaotic time series modelling technique and the Apriori algorithm

    International Nuclear Information System (INIS)

    Guo, Zhenhai; Chi, Dezhong; Wu, Jie; Zhang, Wenyu

    2014-01-01

    Highlights: • Impact of meteorological factors on wind speed forecasting is taken into account. • Forecasted wind speed results are corrected by the associated rules. • Forecasting accuracy is improved by the new wind speed forecasting strategy. • Robust of the proposed model is validated by data sampled from different sites. - Abstract: Wind energy has been the fastest growing renewable energy resource in recent years. Because of the intermittent nature of wind, wind power is a fluctuating source of electrical energy. Therefore, to minimize the impact of wind power on the electrical grid, accurate and reliable wind power forecasting is mandatory. In this paper, a new wind speed forecasting approach based on based on the chaotic time series modelling technique and the Apriori algorithm has been developed. The new approach consists of four procedures: (I) Clustering by using the k-means clustering approach; (II) Employing the Apriori algorithm to discover the association rules; (III) Forecasting the wind speed according to the chaotic time series forecasting model; and (IV) Correcting the forecasted wind speed data using the associated rules discovered previously. This procedure has been verified by 31-day-ahead daily average wind speed forecasting case studies, which employed the wind speed and other meteorological data collected from four meteorological stations located in the Hexi Corridor area of China. The results of these case studies reveal that the chaotic forecasting model can efficiently improve the accuracy of the wind speed forecasting, and the Apriori algorithm can effectively discover the association rules between the wind speed and other meteorological factors. In addition, the correction results demonstrate that the association rules discovered by the Apriori algorithm have powerful capacities in handling the forecasted wind speed values correction when the forecasted values do not match the classification discovered by the association rules

  5. Expert group study on recommended practices for wind turbine testing and evaluation. 10. Measurement of noise immission from wind turbines at noise receptor locations

    International Nuclear Information System (INIS)

    Ljunggren, S.

    1997-01-01

    The purpose of this guide is to provide a set of techniques and methods for the measurement and description of wind turbine noise immission, that is, wind turbine noise at receptor locations. These techniques and methods have been prepared so that they can be used by: manufacturers; developers; operators; planning authorities; research and development engineers, for the purpose of verification of compliance with noise immission limits and of noise propagation models. The measurement of noise immission from wind turbines is a complex acoustic task. This guideline cannot cover all possible problems that may be encountered on, for instance: determination of wind speed; measurements in cases of low signal-to-noise ratio; allowance for reflections from buildings. Thus, it is strongly recommended that the measurements described in this guide are always carried out by experienced acousticians. (au)

  6. Noise from wind turbines. Final report of project JOU2-CT92-0124

    International Nuclear Information System (INIS)

    Van der Borg, N.; Andersen, B.; Mackinnon, A.; Klug, H.; Theofiloyannakos, D.

    1995-04-01

    Part of the planning procedure for the erection of a wind turbine or a wind farm is the prediction of the acoustic noise due to the wind turbine(s) at the nearest dwelling. The noise is normally predicted using the acoustic characteristics of the regarded wind turbine as measured on a wind turbine of equal make and model and using a general noise propagation model. Both inputs introduce uncertainties in the predicted noise level: (a) turbines of equal make and model may have different acoustic characteristics; (b) the acoustic characteristics of a turbine may change in time - from day to day (repeatability of the measurement), - during the years (ageing of the turbine); (c) the general propagation model does not take into account the effects of source elevation and wind. The project aimed at the quantification of these uncertainties and at the development of a wind turbine noise propagation model. Statistical information has been collected on the individual differences of the sound power and tonality of turbines of equal make and model by measuring 6 different types of wind turbines. Of each type 5 individual turbines have been measured (total 30 turbines). Additionally the sound power of a series of 4 wind turbines and of a series of 29 wind turbines (from earlier measurements) have been introduced into the project. Statistical information has been collected on the day to day variations of the sound power and tonality of wind turbines by measuring 3 different turbines 5 times (total 15 measurements). Statistical information has been collected on the effect of ageing on the sound power and tonality of wind turbines by the repeated measurement of 5 wind turbines that have been measured in an identical situation 3 to 7 years earlier. A method for the prediction of wind turbine noise propagation has been developed based on measurements of sound propagation from an elevated noise source and theoretical calculations. (Abstract Truncated)

  7. Validation of an Aero-Acoustic Wind Turbine Noise Model Using Advanced Noise Source Measurements of a 500kW Turbine

    DEFF Research Database (Denmark)

    Bertagnolio, Franck; Aagaard Madsen, Helge; Fischer, Andreas

    2016-01-01

    rotor noise model is presented. It includes the main sources of aeroacoustic noise from wind turbines: turbulent inflow, trailing edge and stall noise. The noise measured by one microphone located directly downstream of the wind turbine is compared to the model predictions at the microphone location....... A good qualitative agreement is found. When wind speed increases, the rotor noise model shows that at high frequencies the stall noise becomes dominant. It also shows that turbulent inflow noise is dominant at low frequencies for all wind speeds and that trailing edge noise is dominant at low wind speeds...

  8. Does noise from wind turbines change due to age?

    International Nuclear Information System (INIS)

    Andersen, B.; Jakobsen, J.

    1995-06-01

    It has been discussed whether the noise from a wind turbine increases due to wear of the mechanical parts or to pollution of the rotor blades. If this is so it should be taken into consideration at the design stage. The noise from wind turbines that had been measured several years before was measured again, and results were compared. A number of modifications of the same wind turbine was made throughout a period of two years during which noise was measured several times. No evidence that noise increases in accordance with the age of the windmill was found. A 75 kW wind turbine seems to have an unchanged A-weighted source strength L WA after a period of 6 years. The level of the tones in the noise from the large generator engaged had increased slightly. The noise from operation of the small generator showed a pronounced increase of one tone (approximately 10 dB), while two other tones were largely unchanged. In the case of periodic measurements of the noise from a 300 kW wind turbine, the gearbox tone noise was found to change markedly, without any obvious pattern. The large, apparently random, fluctuations mask any tendency towards changes of the tone level with time. Repeated measurements of four identical 100 kW wind turbines, show a general tendency towards an increase of the A-weighted source strength (L WA ). The increase of L WA between 1 and 2.7 dB, was found mainly in the frequency range 800 Hz to 3 kHz. The level of the third octave band, which includes a weak gearbox tone (315 Hz), seemed unchanged. Other measurements indicate a constant level of noise during the first three years of operation. (AB)

  9. Predicting annoyance by wind turbine noise

    NARCIS (Netherlands)

    Janssen, S.A.; Vos, H.; Eisses, A.R.; Pedersen, E.

    2010-01-01

    While wind turbines have beneficial effects for the environment, they inevitably generate environmental noise. In order to protect residents against unacceptable levels of noise, exposure-response relationships are needed to predict the expected percentage of people annoyed or highly annoyed at a

  10. Objective and subjective rating of tonal noise radiated from UK wind farms

    International Nuclear Information System (INIS)

    1996-01-01

    The radiation of noise to the environment is currently a major issue with regard to U.K. wind farm developments. The reason for this concern is not that wind turbines are unduly noisy, but rather because wind farms are often located in rural areas where background noise levels can fall very low. The fact that background noise levels fall so low in these areas means that the permissible noise radiation from wind farms must also be kept similarly low if nuisance to local residents is to be avoided. However, ensuring that the overall noise level of the wind farm does not exceed the pre-existing background noise level by more than a set amount is not the whole story. Noise radiated from wind turbines can exhibit characteristics that set it apart from the natural background noises typically found in quiet rural areas, where ''natural'' background noises might include the sound of the wind blowing through trees, or the sound of running water. One of the acoustic characteristics that can be attributed to some wind turbines is the radiation of tonal noise from mechanical plant located in the nacelles. It is well accepted that tonal components in otherwise broad band, or ''characterless'', noise, can increase the subjective perception of that noise. Account for increased annoyance due to tones is found in both of the British Standards which relate to environmental noise; BS4142 and BS7445. (UK)

  11. Numerical modeling of wind turbine aerodynamic noise in the time domain.

    Science.gov (United States)

    Lee, Seunghoon; Lee, Seungmin; Lee, Soogab

    2013-02-01

    Aerodynamic noise from a wind turbine is numerically modeled in the time domain. An analytic trailing edge noise model is used to determine the unsteady pressure on the blade surface. The far-field noise due to the unsteady pressure is calculated using the acoustic analogy theory. By using a strip theory approach, the two-dimensional noise model is applied to rotating wind turbine blades. The numerical results indicate that, although the operating and atmospheric conditions are identical, the acoustical characteristics of wind turbine noise can be quite different with respect to the distance and direction from the wind turbine.

  12. A curvature-based weighted fuzzy c-means algorithm for point clouds de-noising

    Science.gov (United States)

    Cui, Xin; Li, Shipeng; Yan, Xiutian; He, Xinhua

    2018-04-01

    In order to remove the noise of three-dimensional scattered point cloud and smooth the data without damnify the sharp geometric feature simultaneity, a novel algorithm is proposed in this paper. The feature-preserving weight is added to fuzzy c-means algorithm which invented a curvature weighted fuzzy c-means clustering algorithm. Firstly, the large-scale outliers are removed by the statistics of r radius neighboring points. Then, the algorithm estimates the curvature of the point cloud data by using conicoid parabolic fitting method and calculates the curvature feature value. Finally, the proposed clustering algorithm is adapted to calculate the weighted cluster centers. The cluster centers are regarded as the new points. The experimental results show that this approach is efficient to different scale and intensities of noise in point cloud with a high precision, and perform a feature-preserving nature at the same time. Also it is robust enough to different noise model.

  13. A de-noising algorithm based on wavelet threshold-exponential adaptive window width-fitting for ground electrical source airborne transient electromagnetic signal

    Science.gov (United States)

    Ji, Yanju; Li, Dongsheng; Yu, Mingmei; Wang, Yuan; Wu, Qiong; Lin, Jun

    2016-05-01

    The ground electrical source airborne transient electromagnetic system (GREATEM) on an unmanned aircraft enjoys considerable prospecting depth, lateral resolution and detection efficiency, etc. In recent years it has become an important technical means of rapid resources exploration. However, GREATEM data are extremely vulnerable to stationary white noise and non-stationary electromagnetic noise (sferics noise, aircraft engine noise and other human electromagnetic noises). These noises will cause degradation of the imaging quality for data interpretation. Based on the characteristics of the GREATEM data and major noises, we propose a de-noising algorithm utilizing wavelet threshold method and exponential adaptive window width-fitting. Firstly, the white noise is filtered in the measured data using the wavelet threshold method. Then, the data are segmented using data window whose step length is even logarithmic intervals. The data polluted by electromagnetic noise are identified within each window based on the discriminating principle of energy detection, and the attenuation characteristics of the data slope are extracted. Eventually, an exponential fitting algorithm is adopted to fit the attenuation curve of each window, and the data polluted by non-stationary electromagnetic noise are replaced with their fitting results. Thus the non-stationary electromagnetic noise can be effectively removed. The proposed algorithm is verified by the synthetic and real GREATEM signals. The results show that in GREATEM signal, stationary white noise and non-stationary electromagnetic noise can be effectively filtered using the wavelet threshold-exponential adaptive window width-fitting algorithm, which enhances the imaging quality.

  14. Genetic Algorithms in Wind Turbine Airfoil Design

    Energy Technology Data Exchange (ETDEWEB)

    Grasso, F. [ECN Wind Energy, Petten (Netherlands); Bizzarrini, N.; Coiro, D.P. [Department of Aerospace Engineering, University of Napoli ' Federico II' , Napoli (Italy)

    2011-03-15

    One key element in the aerodynamic design of wind turbines is the use of specially tailored airfoils to increase the ratio of energy capture to the loading and thereby to reduce cost of energy. This work is focused on the design of a wind turbine airfoil by using numerical optimization. Firstly, the optimization approach is presented; a genetic algorithm is used, coupled with RFOIL solver and a composite Bezier geometrical parameterization. A particularly sensitive point is the choice and implementation of constraints; in order to formalize in the most complete and effective way the design requirements, the effects of activating specific constraints are discussed. A numerical example regarding the design of a high efficiency airfoil for the outer part of a blade by using genetic algorithms is illustrated and the results are compared with existing wind turbine airfoils. Finally a new hybrid design strategy is illustrated and discussed, in which the genetic algorithms are used at the beginning of the design process to explore a wide domain. Then, the gradient based algorithms are used in order to improve the first stage optimum.

  15. Noise Emission of a 200 kW Vertical Axis Wind Turbine

    Directory of Open Access Journals (Sweden)

    Erik Möllerström

    2015-12-01

    Full Text Available The noise emission from a vertical axis wind turbine (VAWT has been investigated. A noise measurement campaign on a 200 kW straight-bladed VAWT has been conducted, and the result has been compared to a semi-empirical model for turbulent-boundary-layer trailing edge (TBL-TE noise. The noise emission from the wind turbine was measured, at wind speed 8 m/s, 10 m above ground, to 96.2 dBA. At this wind speed, the turbine was stalling as it was run at a tip speed lower than optimal due to constructional constraints. The noise emission at a wind speed of 6 m/s, 10 m above ground was measured while operating at optimum tip speed and was found to be 94.1 dBA. A comparison with similar size horizontal axis wind turbines (HAWTs indicates a noise emission at the absolute bottom of the range. Furthermore, it is clear from the analysis that the turbulent-boundary-layer trailing-edge noise, as modeled here, is much lower than the measured levels, which suggests that other mechanisms are likely to be important, such as inflow turbulence.

  16. Efficient algorithm for baseline wander and powerline noise removal from ECG signals based on discrete Fourier series.

    Science.gov (United States)

    Bahaz, Mohamed; Benzid, Redha

    2018-03-01

    Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.

  17. Auditory Recognition of Familiar and Unfamiliar Subjects with Wind Turbine Noise

    Directory of Open Access Journals (Sweden)

    Luigi Maffei

    2015-04-01

    Full Text Available Considering the wide growth of the wind turbine market over the last decade as well as their increasing power size, more and more potential conflicts have arisen in society due to the noise radiated by these plants. Our goal was to determine whether the annoyance caused by wind farms is related to aspects other than noise. To accomplish this, an auditory experiment on the recognition of wind turbine noise was conducted to people with long experience of wind turbine noise exposure and to people with no previous experience to this type of noise source. Our findings demonstrated that the trend of the auditory recognition is the same for the two examined groups, as far as the increase of the distance and the decrease of the values of sound equivalent levels and loudness are concerned. Significant differences between the two groups were observed as the distance increases. People with wind turbine noise experience showed a higher tendency to report false alarms than people without experience.

  18. Auditory recognition of familiar and unfamiliar subjects with wind turbine noise.

    Science.gov (United States)

    Maffei, Luigi; Masullo, Massimiliano; Gabriele, Maria Di; Votsi, Nefta-Eleftheria P; Pantis, John D; Senese, Vincenzo Paolo

    2015-04-17

    Considering the wide growth of the wind turbine market over the last decade as well as their increasing power size, more and more potential conflicts have arisen in society due to the noise radiated by these plants. Our goal was to determine whether the annoyance caused by wind farms is related to aspects other than noise. To accomplish this, an auditory experiment on the recognition of wind turbine noise was conducted to people with long experience of wind turbine noise exposure and to people with no previous experience to this type of noise source. Our findings demonstrated that the trend of the auditory recognition is the same for the two examined groups, as far as the increase of the distance and the decrease of the values of sound equivalent levels and loudness are concerned. Significant differences between the two groups were observed as the distance increases. People with wind turbine noise experience showed a higher tendency to report false alarms than people without experience.

  19. Experimental characterization of vertical-axis wind turbine noise.

    Science.gov (United States)

    Pearson, C E; Graham, W R

    2015-01-01

    Vertical-axis wind turbines are wind-energy generators suitable for use in urban environments. Their associated noise thus needs to be characterized and understood. As a first step, this work investigates the relative importance of harmonic and broadband contributions via model-scale wind-tunnel experiments. Cross-spectra from a pair of flush-mounted wall microphones exhibit both components, but further analysis shows that the broadband dominates at frequencies corresponding to the audible range in full-scale operation. This observation has detrimental implications for noise-prediction reliability and hence also for acoustic design optimization.

  20. Low-frequency noise from large wind turbines

    DEFF Research Database (Denmark)

    Møller, Henrik; Pedersen, Christian Sejer

    2011-01-01

    As wind turbines get larger, worries have emerged that the turbine noise would move down in frequency and that the low-frequency noise would cause annoyance for the neighbors. The noise emission from 48 wind turbines with nominal electric power up to 3.6 MW is analyzed and discussed. The relative...... amount of low-frequency noise is higher for large turbines (2.3–3.6 MW) than for small turbines (≤ 2 MW), and the difference is statistically significant. The difference can also be expressed as a downward shift of the spectrum of approximately one-third of an octave. A further shift of similar size...... is suggested for future turbines in the 10-MW range. Due to the air absorption, the higher low-frequency content becomes even more pronounced, when sound pressure levels in relevant neighbor distances are considered. Even when A-weighted levels are considered, a substantial part of the noise is at low...

  1. Estimating annoyance to calculated wind turbine shadow flicker is improved when variables associated with wind turbine noise exposure are considered.

    Science.gov (United States)

    Voicescu, Sonia A; Michaud, David S; Feder, Katya; Marro, Leonora; Than, John; Guay, Mireille; Denning, Allison; Bower, Tara; van den Berg, Frits; Broner, Norm; Lavigne, Eric

    2016-03-01

    The Community Noise and Health Study conducted by Health Canada included randomly selected participants aged 18-79 yrs (606 males, 632 females, response rate 78.9%), living between 0.25 and 11.22 km from operational wind turbines. Annoyance to wind turbine noise (WTN) and other features, including shadow flicker (SF) was assessed. The current analysis reports on the degree to which estimating high annoyance to wind turbine shadow flicker (HAWTSF) was improved when variables known to be related to WTN exposure were also considered. As SF exposure increased [calculated as maximum minutes per day (SFm)], HAWTSF increased from 3.8% at 0 ≤ SFm wind turbine-related features, concern for physical safety, and noise sensitivity. Reported dizziness was also retained in the final model at p = 0.0581. Study findings add to the growing science base in this area and may be helpful in identifying factors associated with community reactions to SF exposure from wind turbines.

  2. Study on the Noise Reduction of Vehicle Exhaust NOX Spectra Based on Adaptive EEMD Algorithm

    Directory of Open Access Journals (Sweden)

    Kai Zhang

    2017-01-01

    Full Text Available It becomes a key technology to measure the concentration of the vehicle exhaust components with the transmission spectra. But in the conventional methods for noise reduction and baseline correction, such as wavelet transform, derivative, interpolation, polynomial fitting, and so forth, the basic functions of these algorithms, the number of decomposition layers, and the way to reconstruct the signal have to be adjusted according to the characteristics of different components in the transmission spectra. The parameter settings of the algorithms above are not transcendental, so with them, it is difficult to achieve the best noise reduction effect for the vehicle exhaust spectra which are sharp and drastic in the waveform. In this paper, an adaptive ensemble empirical mode decomposition (EEMD denoising model based on a special normalized index optimization is proposed and used in the spectral noise reduction of vehicle exhaust NOX. It is shown with the experimental results that the method can effectively improve the accuracy of the spectral noise reduction and simplify the denoising process and its operation difficulty.

  3. Optimal Wind Turbines Micrositing in Onshore Wind Farms Using Fuzzy Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2015-01-01

    Full Text Available With the fast growth in the number and size of installed wind farms (WFs around the world, optimal wind turbines (WTs micrositing has become a challenge from both technological and mathematical points of view. An appropriate layout of wind turbines is crucial to obtain adequate performance with respect to the development and operation of the wind power plant during its life span. This work presents a fuzzy genetic algorithm (FGA for maximizing the economic profitability of the project. The algorithm considers a new WF model including several important factors to the design of the layout. The model consists of wake loss, terrain effect, and economic benefits, which can be calculated by locations of wind turbines. The results demonstrate that the algorithm performs better than genetic algorithm, in terms of maximum values of net annual value of wind power plants and computational burden.

  4. Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

    Science.gov (United States)

    Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

    2017-07-01

    In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

  5. A modified gravitational search algorithm based on a non-dominated sorting genetic approach for hydro-thermal-wind economic emission dispatching

    International Nuclear Information System (INIS)

    Chen, Fang; Zhou, Jianzhong; Wang, Chao; Li, Chunlong; Lu, Peng

    2017-01-01

    Wind power is a type of clean and renewable energy, and reasonable utilization of wind power is beneficial to environmental protection and economic development. Therefore, a short-term hydro-thermal-wind economic emission dispatching (SHTW-EED) problem is presented in this paper. The proposed problem aims to distribute the load among hydro, thermal and wind power units to simultaneously minimize economic cost and pollutant emission. To solve the SHTW-EED problem with complex constraints, a modified gravitational search algorithm based on the non-dominated sorting genetic algorithm-III (MGSA-NSGA-III) is proposed. In the proposed MGSA-NSGA-III, a non-dominated sorting approach, reference-point based selection mechanism and chaotic mutation strategy are applied to improve the evolutionary process of the original gravitational search algorithm (GSA) and maintain the distribution diversity of Pareto optimal solutions. Moreover, a parallel computing strategy is introduced to improve the computational efficiency. Finally, the proposed MGSA-NSGA-III is applied to a typical hydro-thermal-wind system to verify its feasibility and effectiveness. The simulation results indicate that the proposed algorithm can obtain low economic cost and small pollutant emission when dealing with the SHTW-EED problem. - Highlights: • A hybrid algorithm is proposed to handle hydro-thermal-wind power dispatching. • Several improvement strategies are applied to the algorithm. • A parallel computing strategy is applied to improve computational efficiency. • Two cases are analyzed to verify the efficiency of the optimize mode.

  6. Image denoising based on noise detection

    Science.gov (United States)

    Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

    2018-03-01

    Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

  7. MMSE-based algorithm for joint signal detection, channel and noise variance estimation for OFDM systems

    CERN Document Server

    Savaux, Vincent

    2014-01-01

    This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is pr

  8. Reduction of the performance of a noise screen due to screen-induced wind-speed gradients: numerical computations and wind-tunnel experiments

    NARCIS (Netherlands)

    Salomons, E.M.

    1999-01-01

    Downwind sound propagation over a noise screen is investigated by numerical computations and scale model experiments in a wind tunnel. For the computations, the parabolic equation method is used, with a range-dependent sound-speed profile based on wind-speed profiles measured in the wind tunnel and

  9. Prediction and analysis of infra and low-frequency noise of upwind horizontal axis wind turbine using statistical wind speed model

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Gwang-Se; Cheong, Cheolung, E-mail: ccheong@pusan.ac.kr [School of Mechanical Engineering, Pusan National University, Busan, 609-745, Rep. of Korea (Korea, Republic of)

    2014-12-15

    Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs), few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF) wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF) noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.

  10. Prediction and analysis of infra and low-frequency noise of upwind horizontal axis wind turbine using statistical wind speed model

    Directory of Open Access Journals (Sweden)

    Gwang-Se Lee

    2014-12-01

    Full Text Available Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs, few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.

  11. Dynamic Power Dispatch Considering Electric Vehicles and Wind Power Using Decomposition Based Multi-Objective Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Boyang Qu

    2017-12-01

    Full Text Available The intermittency of wind power and the large-scale integration of electric vehicles (EVs bring new challenges to the reliability and economy of power system dispatching. In this paper, a novel multi-objective dynamic economic emission dispatch (DEED model is proposed considering the EVs and uncertainties of wind power. The total fuel cost and pollutant emission are considered as the optimization objectives, and the vehicle to grid (V2G power and the conventional generator output power are set as the decision variables. The stochastic wind power is derived by Weibull probability distribution function. Under the premise of meeting the system energy and user’s travel demand, the charging and discharging behavior of the EVs are dynamically managed. Moreover, we propose a two-step dynamic constraint processing strategy for decision variables based on penalty function, and, on this basis, the Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D algorithm is improved. The proposed model and approach are verified by the 10-generator system. The results demonstrate that the proposed DEED model and the improved MOEA/D algorithm are effective and reasonable.

  12. Acoustic noise production of wind turbines in practice

    International Nuclear Information System (INIS)

    Van der Borg, N.J.C.M.; Vink, P.W.

    1994-10-01

    Within the framework of national and European projects ECN has conducted various acoustic noise measurements on wind turbines. The measurements can be divided into the following two categories: (1) measurements of the total noise emitted by the turbine ('standard measurements') and (2) measurement of the noise emitted by different blades on the same rotor ('research measurements'). The applied procedures for the 'standard measurements' are given in IEA and IEC documents on wind turbine noise measurements. The applied procedures for the 'research measurements' are given in this paper. General results obtained with both kind of measurements are presented. The 'research measurements' have been performed on a limited number of turbines: the UNIWEX turbine in Germany and a commercial turbine in The Netherlands. The turbines were equipped with differently shaped blade tips or trailing edges on the same rotor. The experiments showed no large differences in the sound production of the different blades on the same rotor. The detailed information on the commercial wind turbine in The Netherlands is confidential. 9 figs., 2 tabs., 3 refs

  13. Measurement of the environmental noise at the Torseroed wind turbine site

    International Nuclear Information System (INIS)

    Fegeant, Olivier

    2000-12-01

    Further to complaints about the noise generated by a Micon 600 kW wind turbine, measurements of both noise immission and noise emission were performed at the Torseroed site. The measurements and analysis presented in this report were carried out by following the recommendations of the IEA documents for noise emission and immission measurements. It was found that the immission level, i.e. the wind turbine sound, at one of the nearest dwelling, namely Solglaentan, is 39 dB(A) for a wind speed of 8 m/s at hub height. Measurements carried out close to the turbine show that the sound power level of the turbine is 4.3 dB higher than the A-weighted level given by the supplier. Furthermore, the noise level increases more rapidly as a function of the wind speed than what is expected from the values furnished by the manufacturer. The measurements results also show that the background noise level is unusually low at Solglaentan

  14. Parameter Estimation for Traffic Noise Models Using a Harmony Search Algorithm

    Directory of Open Access Journals (Sweden)

    Deok-Soon An

    2013-01-01

    Full Text Available A technique has been developed for predicting road traffic noise for environmental assessment, taking into account traffic volume as well as road surface conditions. The ASJ model (ASJ Prediction Model for Road Traffic Noise, 1999, which is based on the sound power level of the noise emitted by the interaction between the road surface and tires, employs regression models for two road surface types: dense-graded asphalt (DGA and permeable asphalt (PA. However, these models are not applicable to other types of road surfaces. Accordingly, this paper introduces a parameter estimation procedure for ASJ-based noise prediction models, utilizing a harmony search (HS algorithm. Traffic noise measurement data for four different vehicle types were used in the algorithm to determine the regression parameters for several road surface types. The parameters of the traffic noise prediction models were evaluated using another measurement set, and good agreement was observed between the predicted and measured sound power levels.

  15. A New Switching-Based Median Filtering Scheme and Algorithm for Removal of High-Density Salt and Pepper Noise in Images

    Directory of Open Access Journals (Sweden)

    Jayaraj V

    2010-01-01

    Full Text Available A new switching-based median filtering scheme for restoration of images that are highly corrupted by salt and pepper noise is proposed. An algorithm based on the scheme is developed. The new scheme introduces the concept of substitution of noisy pixels by linear prediction prior to estimation. A novel simplified linear predictor is developed for this purpose. The objective of the scheme and algorithm is the removal of high-density salt and pepper noise in images. The new algorithm shows significantly better image quality with good PSNR, reduced MSE, good edge preservation, and reduced streaking. The good performance is achieved with reduced computational complexity. A comparison of the performance is made with several existing algorithms in terms of visual and quantitative results. The performance of the proposed scheme and algorithm is demonstrated.

  16. The influence of noise on the design of horizontal axis wind turbines

    International Nuclear Information System (INIS)

    Watson, I.

    1993-01-01

    This wind turbine noise study was initiated and funded by ETSU to help to eliminate noise as an obstacle to the harnessing of wind energy for the clean generation of electrical power. There is an abundance of theoretical papers on aerodynamic noise, but very few contain meaningful, practical verification of the complex analysis by tests on wind turbines where mechanical noise has been eliminated. This serious shortcoming initiated comprehensive tests on the 1MW, three bladed wind turbine at Richborough Power Station. This investigation is an integral part of this project. A study of the available literature on blade induced noise is also part of this project. A report on gearbox noise which is normally the main source of mechanical and discrete noise is also given. Four reports have been written to fulfil the objectives listed by ETSU. This final report summarises and comments on some of the work in the other three reports and also includes an appraisal of the effect and cost of basic design strategy to create acceptably quiet wind turbines. (author)

  17. Human response to wind turbine noise - perception, annoyance and moderating factors

    Energy Technology Data Exchange (ETDEWEB)

    Pedersen, Eja

    2007-05-15

    The aims of this thesis were to describe and gain an understanding of how people who live in the vicinity of wind turbines are affected by wind turbine noise, and how individual, situational and visual factors, as well as sound properties, moderate the response. Methods A cross-sectional study was carried out in a flat, mainly rural area in Sweden, with the objective to estimate the prevalence of noise annoyance and to examine the dose-response relationship between A-weighted sound pressure levels (SPLs) and perception of and annoyance with wind turbine noise. Subjective responses were obtained through a questionnaire (n = 513; response rate: 68%) and outdoor, A-weighted SPLs were calculated for each respondent. To gain a deeper understanding of the observed noise annoyance, 15 people living in an area were interviewed using open-ended questions. The interviews were analysed using the comparative method of Grounded Theory (GT). An additional cross-sectional study, mainly exploring the influence of individual and situational factors, was carried out in seven areas in Sweden that differed with regard to terrain (flat or complex) and degree of urbanization (n = 765; response rate: 58%). To further explore the impact of visual factors, data from the two cross-sectional studies were tested with structural equation modelling. A proposed model of the influence of visual attitude on noise annoyance, also comprising the influence of noise level and general attitude, was tested among respondents who could see wind turbines versus respondents who could not see wind turbines from their dwelling, and respondents living in flat versus complex terrain. Dose-response relationships were found both for perception of noise and for noise annoyance in relation to A-weighted SPLs. The risk of annoyance was enhanced among respondents who could see at least one turbine from their dwelling and among those living in a rural in comparison with a suburban area. Noise from wind turbines was

  18. Human response to wind turbine noise - perception, annoyance and moderating factors

    International Nuclear Information System (INIS)

    Pedersen, Eja

    2007-05-01

    The aims of this thesis were to describe and gain an understanding of how people who live in the vicinity of wind turbines are affected by wind turbine noise, and how individual, situational and visual factors, as well as sound properties, moderate the response. Methods A cross-sectional study was carried out in a flat, mainly rural area in Sweden, with the objective to estimate the prevalence of noise annoyance and to examine the dose-response relationship between A-weighted sound pressure levels (SPLs) and perception of and annoyance with wind turbine noise. Subjective responses were obtained through a questionnaire (n = 513; response rate: 68%) and outdoor, A-weighted SPLs were calculated for each respondent. To gain a deeper understanding of the observed noise annoyance, 15 people living in an area were interviewed using open-ended questions. The interviews were analysed using the comparative method of Grounded Theory (GT). An additional cross-sectional study, mainly exploring the influence of individual and situational factors, was carried out in seven areas in Sweden that differed with regard to terrain (flat or complex) and degree of urbanization (n = 765; response rate: 58%). To further explore the impact of visual factors, data from the two cross-sectional studies were tested with structural equation modelling. A proposed model of the influence of visual attitude on noise annoyance, also comprising the influence of noise level and general attitude, was tested among respondents who could see wind turbines versus respondents who could not see wind turbines from their dwelling, and respondents living in flat versus complex terrain. Dose-response relationships were found both for perception of noise and for noise annoyance in relation to A-weighted SPLs. The risk of annoyance was enhanced among respondents who could see at least one turbine from their dwelling and among those living in a rural in comparison with a suburban area. Noise from wind turbines was

  19. Effects of amplitude modulation on perception of wind turbine noise

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Ki Seop; Lee, Soo Gab; Gwak, Doo Young [Dept. of Mechanical and Aerospace Engineering, Seoul National University, Seoul (Korea, Republic of); Seong, Yeol Wan [Ammunition Engineering Team, Defense Agency for Technology and Quality, Daejeon (Korea, Republic of); Lee, Seung Hoon [Aerodynamics Research Team, Korea Aerospace Research Institute, Daejeon (Korea, Republic of); Hong, Ji Young [Transportation Environmental Research Team, Green Transport and Logistics Institute, Korea Railroad Research Institute, Uiwang (Korea, Republic of)

    2016-10-15

    Wind turbine noise is considered to be easily detectable and highly annoying at relatively lower sound levels than other noise sources. Many previous studies attributed this characteristic to amplitude modulation. However, it is unclear whether amplitude modulation is the main cause of these properties of wind turbine noise. Therefore, the aim of the current study is to identify the relationship between amplitude modulation and these two properties of wind turbine noise. For this investigation, two experiments were conducted. In the first experiment, 12 participants determined the detection thresholds of six target sounds in the presence of background noise. In the second experiment, 12 participants matched the loudness of modified sounds without amplitude modulation to that of target sounds with amplitude modulation. The results showed that the detection threshold was lowered as the modulation depth increased; additionally, sounds with amplitude modulation had higher subjective loudness than those without amplitude modulation.

  20. Effects of amplitude modulation on perception of wind turbine noise

    International Nuclear Information System (INIS)

    Yoon, Ki Seop; Lee, Soo Gab; Gwak, Doo Young; Seong, Yeol Wan; Lee, Seung Hoon; Hong, Ji Young

    2016-01-01

    Wind turbine noise is considered to be easily detectable and highly annoying at relatively lower sound levels than other noise sources. Many previous studies attributed this characteristic to amplitude modulation. However, it is unclear whether amplitude modulation is the main cause of these properties of wind turbine noise. Therefore, the aim of the current study is to identify the relationship between amplitude modulation and these two properties of wind turbine noise. For this investigation, two experiments were conducted. In the first experiment, 12 participants determined the detection thresholds of six target sounds in the presence of background noise. In the second experiment, 12 participants matched the loudness of modified sounds without amplitude modulation to that of target sounds with amplitude modulation. The results showed that the detection threshold was lowered as the modulation depth increased; additionally, sounds with amplitude modulation had higher subjective loudness than those without amplitude modulation

  1. Projected contributions of future wind farm development to community noise and annoyance levels in Ontario, Canada

    International Nuclear Information System (INIS)

    Whitfield Aslund, Melissa L.; Ollson, Christopher A.; Knopper, Loren D.

    2013-01-01

    Wind turbines produce sound during their operation; therefore, jurisdictions around the world have developed regulations regarding the placement of electricity generating wind farms with the intent of preventing unacceptable levels of ‘community noise’ in their vicinity. However, as survey results indicate that the relationship between wind turbine noise and annoyance may differ from noise-annoyance relationships for other common noise sources (e.g., rail, traffic), there are concerns that the application of general noise guidelines for wind turbines may lead to unacceptably high levels of annoyance in communities. In this study, previously published survey results that quantified wind turbine noise and self-reported annoyance were applied to the predicted noise levels (from turbines and transformers) for over 8000 receptors in the vicinity of 13 planned wind power developments in the province of Ontario, Canada. The results of this analysis indicate that the current wind turbine noise restrictions in Ontario will limit community exposure to wind turbine related noise such that levels of annoyance are unlikely to exceed previously established background levels of noise-related annoyance from other common noise sources. This provides valuable context that should be considered by policy-makers when evaluating the potential impacts of wind turbine noise on the community. -- highlights: •Wind turbine noise-annoyance relationship used to predict annoyance in Ontario. •Noise annoyance predicted to be <8% for non-participants <1 km from turbines. •Predicted levels of wind turbine noise annoyance similar to that from traffic noise. •Wind turbine noise annoyance not expected to exceed existing background levels

  2. Low-frequency noise from large wind turbines.

    Science.gov (United States)

    Møller, Henrik; Pedersen, Christian Sejer

    2011-06-01

    As wind turbines get larger, worries have emerged that the turbine noise would move down in frequency and that the low-frequency noise would cause annoyance for the neighbors. The noise emission from 48 wind turbines with nominal electric power up to 3.6 MW is analyzed and discussed. The relative amount of low-frequency noise is higher for large turbines (2.3-3.6 MW) than for small turbines (≤ 2 MW), and the difference is statistically significant. The difference can also be expressed as a downward shift of the spectrum of approximately one-third of an octave. A further shift of similar size is suggested for future turbines in the 10-MW range. Due to the air absorption, the higher low-frequency content becomes even more pronounced, when sound pressure levels in relevant neighbor distances are considered. Even when A-weighted levels are considered, a substantial part of the noise is at low frequencies, and for several of the investigated large turbines, the one-third-octave band with the highest level is at or below 250 Hz. It is thus beyond any doubt that the low-frequency part of the spectrum plays an important role in the noise at the neighbors. © 2011 Acoustical Society of America

  3. Noise measurement at wind power plants; Geraeuschmessung an Windenergieanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Schoene, Ralph [Cirrus Research plc, Frankfurt am Main (Germany)

    2012-09-15

    Wind energy is a supporting pillar of the energy transition. For further expansion, it is important to reduce prejudices, for example by measurements as precise as possible and assessments of the often unobjectively discussed noise emissions. These measurements are based on instruments which can analyze and measure low-frequency sound.

  4. Accelerometer North Finding System Based on the Wavelet Packet De-noising Algorithm and Filtering Circuit

    Directory of Open Access Journals (Sweden)

    LU Yongle

    2014-07-01

    Full Text Available This paper demonstrates a method and system for north finding with a low-cost piezoelectricity accelerometer based on the Coriolis acceleration principle. The proposed setup is based on the choice of an accelerometer with residual noise of 35 ng•Hz-1/2. The plane of the north finding system is aligned parallel to the local level, which helps to eliminate the effect of plane error. The Coriolis acceleration caused by the earth’s rotation and the acceleration’s instantaneous velocity is much weaker than the g-sensitivity acceleration. To get a high accuracy and a shorter time for north finding system, in this paper, the Filtering Circuit and the wavelet packet de-nosing algorithm are used as the following. First, the hardware is designed as the alternating currents across by filtering circuit, so the DC will be isolated and the weak AC signal will be amplified. The DC is interfering signal generated by the earth's gravity. Then, we have used a wavelet packet to filter the signal which has been done through the filtering circuit. Finally, compare the north finding results measured by wavelet packet filtering with those measured by a low-pass filter. Wavelet filter de-noise data shows that wavelet packet filtering and wavelet filter measurement have high accuracy. Wavelet Packet filtering has stronger ability to remove burst noise and higher engineering environment adaptability than that of Wavelet filtering. Experimental results prove the effectiveness and project implementation of the accelerometer north finding method based on wavelet packet de-noising algorithm.

  5. Anechoic wind tunnel tests on high-speed train bogie aerodynamic noise

    OpenAIRE

    Latorre Iglesias, E.; Thompson, D.; Smith, M.; Kitagawa, T.; Yamazaki, N.

    2016-01-01

    Aerodynamic noise becomes a significant noise source at speeds normally reached by high-speed trains. The train bogies are identified as important sources of aerodynamic noise. Due to the difficulty to assess this noise source carrying out field tests, wind tunnel tests offer many advantages. Tests were performed in the large-scale low-noise anechoic wind tunnel at Maibara, Japan, using a 1/7 scale train car and bogie model for a range of flow speeds between 50, 76, 89 and 100 m/s. The depend...

  6. Improved Noise Minimum Statistics Estimation Algorithm for Using in a Speech-Passing Noise-Rejecting Headset

    Directory of Open Access Journals (Sweden)

    Seyedtabaee Saeed

    2010-01-01

    Full Text Available This paper deals with configuration of an algorithm to be used in a speech-passing angle grinder noise-canceling headset. Angle grinder noise is annoying and interrupts ordinary oral communication. Meaning that, low SNR noisy condition is ahead. Since variation in angle grinder working condition changes noise statistics, the noise will be nonstationary with possible jumps in its power. Studies are conducted for picking an appropriate algorithm. A modified version of the well-known spectral subtraction shows superior performance against alternate methods. Noise estimation is calculated through a multi-band fast adapting scheme. The algorithm is adapted very quickly to the non-stationary noise environment while inflecting minimum musical noise and speech distortion on the processed signal. Objective and subjective measures illustrating the performance of the proposed method are introduced.

  7. Effect of Wind Farm Noise on Local Residents' Decision to Adopt Mitigation Measures.

    Science.gov (United States)

    Botelho, Anabela; Arezes, Pedro; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M Costa

    2017-07-11

    Wind turbines' noise is frequently pointed out as the reason for local communities' objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes' noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people's decision to adopt mitigating measures, independently of the reported annoyance.

  8. Effect of Wind Farm Noise on Local Residents’ Decision to Adopt Mitigation Measures

    Science.gov (United States)

    Botelho, Anabela; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M. Costa

    2017-01-01

    Wind turbines’ noise is frequently pointed out as the reason for local communities’ objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes’ noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people’s decision to adopt mitigating measures, independently of the reported annoyance. PMID:28696404

  9. On practical challenges of decomposition-based hybrid forecasting algorithms for wind speed and solar irradiation

    International Nuclear Information System (INIS)

    Wang, Yamin; Wu, Lei

    2016-01-01

    This paper presents a comprehensive analysis on practical challenges of empirical mode decomposition (EMD) based algorithms on wind speed and solar irradiation forecasts that have been largely neglected in literature, and proposes an alternative approach to mitigate such challenges. Specifically, the challenges are: (1) Decomposed sub-series are very sensitive to the original time series data. That is, sub-series of the new time series, consisting of the original one plus a limit number of new data samples, may significantly differ from those used in training forecasting models. In turn, forecasting models established by original sub-series may not be suitable for newly decomposed sub-series and have to be trained more frequently; and (2) Key environmental factors usually play a critical role in non-decomposition based methods for forecasting wind speed and solar irradiation. However, it is difficult to incorporate such critical environmental factors into forecasting models of individual decomposed sub-series, because the correlation between the original data and environmental factors is lost after decomposition. Numerical case studies on wind speed and solar irradiation forecasting show that the performance of existing EMD-based forecasting methods could be worse than the non-decomposition based forecasting model, and are not effective in practical cases. Finally, the approximated forecasting model based on EMD is proposed to mitigate the challenges and achieve better forecasting results than existing EMD-based forecasting algorithms and the non-decomposition based forecasting models on practical wind speed and solar irradiation forecasting cases. - Highlights: • Two challenges of existing EMD-based forecasting methods are discussed. • Significant changes of sub-series in each step of the rolling forecast procedure. • Difficulties in incorporating environmental factors into sub-series forecasting models. • The approximated forecasting method is proposed to

  10. Robust Cyclic MUSIC Algorithm for Finding Directions in Impulsive Noise Environment

    Directory of Open Access Journals (Sweden)

    Sen Li

    2017-01-01

    Full Text Available This paper addresses the issue of direction finding of a cyclostationary signal under impulsive noise environments modeled by α-stable distribution. Since α-stable distribution does not have finite second-order statistics, the conventional cyclic correlation-based signal-selective direction finding algorithms do not work effectively. To resolve this problem, we define two robust cyclic correlation functions which are derived from robust statistics property of the correntropy and the nonlinear transformation, respectively. The MUSIC algorithm with the robust cyclic correlation matrix of the received signals of arrays is then used to estimate the direction of cyclostationary signal in the presence of impulsive noise. The computer simulation results demonstrate that the two proposed robust cyclic correlation-based algorithms outperform the conventional cyclic correlation and the fractional lower order cyclic correlation based methods.

  11. Solving the wind farm layout optimization problem using random search algorithm

    DEFF Research Database (Denmark)

    Feng, Ju; Shen, Wen Zhong

    2015-01-01

    , in which better results than the genetic algorithm (GA) and the old version of the RS algorithm are obtained. Second it is applied to the Horns Rev 1 WF, and the optimized layouts obtain a higher power production than its original layout, both for the real scenario and for two constructed scenarios......Wind farm (WF) layout optimization is to find the optimal positions of wind turbines (WTs) inside a WF, so as to maximize and/or minimize a single objective or multiple objectives, while satisfying certain constraints. In this work, a random search (RS) algorithm based on continuous formulation....... In this application, it is also found that in order to get consistent and reliable optimization results, up to 360 or more sectors for wind direction have to be used. Finally, considering the inevitable inter-annual variations in the wind conditions, the robustness of the optimized layouts against wind condition...

  12. Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines.

    Science.gov (United States)

    Ma, Ping; Lien, Fue-Sang; Yee, Eugene

    2017-01-01

    This paper develops a computational acoustic beamforming (CAB) methodology for identification of sources of small wind turbine noise. This methodology is validated using the case of the NACA 0012 airfoil trailing edge noise. For this validation case, the predicted acoustic maps were in excellent conformance with the results of the measurements obtained from the acoustic beamforming experiment. Following this validation study, the CAB methodology was applied to the identification of noise sources generated by a commercial small wind turbine. The simulated acoustic maps revealed that the blade tower interaction and the wind turbine nacelle were the two primary mechanisms for sound generation for this small wind turbine at frequencies between 100 and 630 Hz.

  13. A neuro-fuzzy controlling algorithm for wind turbine

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Li [Tampere Univ. of Technology (Finland); Eriksson, J T [Tampere Univ. of Technology (Finland)

    1996-12-31

    The wind turbine control system is stochastic and nonlinear, offering a demanding field for different control methods. An improved and efficient controller will have great impact on the cost-effectiveness of the technology. In this article, a design method for a self-organizing fuzzy controller is discussed, which combines two popular computational intelligence techniques, neural networks and fuzzy logic. Based on acquisited dynamic parameters of the wind, it can effectively predict wind changes in speed and direction. Maximum power can always be extracted from the kinetic energy of the wind. Based on the stimulating experiments applying nonlinear dynamics to a `Variable Speed Fixed Angle` wind turbine, it is demonstrated that the proposed control model 3rd learning algorithm provide a predictable, stable and accurate performance. The robustness of the controller to system parameter variations and measurement disturbances is also discussed. (author)

  14. A neuro-fuzzy controlling algorithm for wind turbine

    Energy Technology Data Exchange (ETDEWEB)

    Li Lin [Tampere Univ. of Technology (Finland); Eriksson, J.T. [Tampere Univ. of Technology (Finland)

    1995-12-31

    The wind turbine control system is stochastic and nonlinear, offering a demanding field for different control methods. An improved and efficient controller will have great impact on the cost-effectiveness of the technology. In this article, a design method for a self-organizing fuzzy controller is discussed, which combines two popular computational intelligence techniques, neural networks and fuzzy logic. Based on acquisited dynamic parameters of the wind, it can effectively predict wind changes in speed and direction. Maximum power can always be extracted from the kinetic energy of the wind. Based on the stimulating experiments applying nonlinear dynamics to a `Variable Speed Fixed Angle` wind turbine, it is demonstrated that the proposed control model 3rd learning algorithm provide a predictable, stable and accurate performance. The robustness of the controller to system parameter variations and measurement disturbances is also discussed. (author)

  15. The sound of high winds. The effect of atmospheric stability on wind turbine sound and microphone noise

    International Nuclear Information System (INIS)

    Van den Berg, G.P.

    2006-01-01

    In this thesis issues are raised concerning wind turbine noise and its relationship to altitude dependent wind velocity. The following issues are investigated: what is the influence of atmospheric stability on the speed and sound power of a wind turbine?; what is the influence of atmospheric stability on the character of wind turbine sound?; how widespread is the impact of atmospheric stability on wind turbine performance: is it relevant for new wind turbine projects; how can noise prediction take this stability into account?; what can be done to deal with the resultant higher impact of wind turbine sound? Apart from these directly wind turbine related issues, a final aim was to address a measurement problem: how does wind on a microphone affect the measurement of the ambient sound level?

  16. Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2015-01-01

    Full Text Available This paper develops an effectively intelligent model to forecast short-term wind speed series. A hybrid forecasting technique is proposed based on recurrence plot (RP and optimized support vector regression (SVR. Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast. To understand the wind system, the wind speed series is analyzed using RP. Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms. Those optimized algorithms are genetic algorithm (GA, particle swarm optimization algorithm (PSO, and cuckoo optimization algorithm (COA. Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test. The experimental results show that (1 analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2 the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3 the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.

  17. Comparative study of adaptive-noise-cancellation algorithms for intrusion detection systems

    International Nuclear Information System (INIS)

    Claassen, J.P.; Patterson, M.M.

    1981-01-01

    Some intrusion detection systems are susceptible to nonstationary noise resulting in frequent nuisance alarms and poor detection when the noise is present. Adaptive inverse filtering for single channel systems and adaptive noise cancellation for two channel systems have both demonstrated good potential in removing correlated noise components prior detection. For such noise susceptible systems the suitability of a noise reduction algorithm must be established in a trade-off study weighing algorithm complexity against performance. The performance characteristics of several distinct classes of algorithms are established through comparative computer studies using real signals. The relative merits of the different algorithms are discussed in the light of the nature of intruder and noise signals

  18. Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula

    International Nuclear Information System (INIS)

    Mera, David; Cotos, José M.; Varela-Pet, José; Garcia-Pineda, Oscar

    2012-01-01

    Highlights: ► We present an adaptive thresholding algorithm to segment oil spills. ► The segmentation algorithm is based on SAR images and wind field estimations. ► A Database of oil spill confirmations was used for the development of the algorithm. ► Wind field estimations have demonstrated to be useful for filtering look-alikes. ► Parallel programming has been successfully used to minimize processing time. - Abstract: Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean’s surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.

  19. An analysis of low frequency noise from large wind turbines

    DEFF Research Database (Denmark)

    Pedersen, Christian Sejer; Møller, Henrik

    2010-01-01

    As wind turbines get larger, worries have emerged, that the noise emitted by the turbines would move down in frequency, and that the contents of low-frequency noise would be enough to cause significant annoyance for the neighbors. The sound emission from 48 wind turbines with nominal electric power......-third-octave-band spectra shows that the relative noise emission is higher in the 63-250 Hz frequency range from turbines above 2 MW than from smaller turbines. The observations confirm a downward shift of the spectrum....

  20. Investigation of Diesel’s Residual Noise on Predictive Vehicles Noise Cancelling using LMS Adaptive Algorithm

    Science.gov (United States)

    Arttini Dwi Prasetyowati, Sri; Susanto, Adhi; Widihastuti, Ida

    2017-04-01

    Every noise problems require different solution. In this research, the noise that must be cancelled comes from roadway. Least Mean Square (LMS) adaptive is one of the algorithm that can be used to cancel that noise. Residual noise always appears and could not be erased completely. This research aims to know the characteristic of residual noise from vehicle’s noise and analysis so that it is no longer appearing as a problem. LMS algorithm was used to predict the vehicle’s noise and minimize the error. The distribution of the residual noise could be observed to determine the specificity of the residual noise. The statistic of the residual noise close to normal distribution with = 0,0435, = 1,13 and the autocorrelation of the residual noise forming impulse. As a conclusion the residual noise is insignificant.

  1. Mitigating Wind Induced Noise in Outdoor Microphone Signals Using a Singular Spectral Subspace Method

    Directory of Open Access Journals (Sweden)

    Omar Eldwaik

    2018-01-01

    Full Text Available Wind induced noise is one of the major concerns of outdoor acoustic signal acquisition. It affects many field measurement and audio recording scenarios. Filtering such noise is known to be difficult due to its broadband and time varying nature. In this paper, a new method to mitigate wind induced noise in microphone signals is developed. Instead of applying filtering techniques, wind induced noise is statistically separated from wanted signals in a singular spectral subspace. The paper is presented in the context of handling microphone signals acquired outdoor for acoustic sensing and environmental noise monitoring or soundscapes sampling. The method includes two complementary stages, namely decomposition and reconstruction. The first stage decomposes mixed signals in eigen-subspaces, selects and groups the principal components according to their contributions to wind noise and wanted signals in the singular spectrum domain. The second stage reconstructs the signals in the time domain, resulting in the separation of wind noise and wanted signals. Results show that microphone wind noise is separable in the singular spectrum domain evidenced by the weighted correlation. The new method might be generalized to other outdoor sound acquisition applications.

  2. Evaluation of annoyance from the wind turbine noise: A pilot study

    Directory of Open Access Journals (Sweden)

    Małgorzata Pawlaczyk-Łuszczyńska

    2014-07-01

    Full Text Available Objectives: The overall aim of this study was to evaluate the perception of and annoyance due to the noise from wind turbines in populated areas of Poland. Material and Methods: The study group comprised 156 subjects. All subjects were asked to fill in a questionnaire developed to enable evaluation of their living conditions, including prevalence of annoyance due to the noise from wind turbines and the self-assessment of physical health and well-being. In addition, current mental health status of the respondents was assessed using Goldberg General Health Questionnaire GHQ-12. For areas where the respondents lived, A-weighted sound pressure levels (SPLs were calculated as the sum of the contributions from the wind power plants in the specific area. Results: It has been shown that the wind turbine noise at the calculated A-weigh­ted SPL of 30-48 dB was noticed outdoors by 60.3% of the respondents. This noise was perceived as annoying outdoors by 33.3% of the respondents, while indoors by 20.5% of them. The odds ratio of being annoyed outdoors by the wind turbine noise increased along with increasing SPLs (OR = 2.1; 95% CI: 1.22-3.62. The subjects' attitude to wind turbines in general and sensitivity to landscape littering was found to have significant impact on the perceived annoyance. About 63% of variance in outdoors annoyance assessment might be explained by the noise level, general attitude to wind turbines and sensitivity to landscape littering. Conclusions: Before firm conclusions can be drawn further studies are needed, including a larger number of respondents with different living environments (i.e., dissimilar terrain, different urbanization and road traffic intensity.

  3. False-nearest-neighbors algorithm and noise-corrupted time series

    International Nuclear Information System (INIS)

    Rhodes, C.; Morari, M.

    1997-01-01

    The false-nearest-neighbors (FNN) algorithm was originally developed to determine the embedding dimension for autonomous time series. For noise-free computer-generated time series, the algorithm does a good job in predicting the embedding dimension. However, the problem of predicting the embedding dimension when the time-series data are corrupted by noise was not fully examined in the original studies of the FNN algorithm. Here it is shown that with large data sets, even small amounts of noise can lead to incorrect prediction of the embedding dimension. Surprisingly, as the length of the time series analyzed by FNN grows larger, the cause of incorrect prediction becomes more pronounced. An analysis of the effect of noise on the FNN algorithm and a solution for dealing with the effects of noise are given here. Some results on the theoretically correct choice of the FNN threshold are also presented. copyright 1997 The American Physical Society

  4. Development of a wind farm noise propagation prediction model - project progress to date

    International Nuclear Information System (INIS)

    Robinson, P.; Bullmore, A.; Bass, J.; Sloth, E.

    1998-01-01

    This paper describes a twelve month measurement campaign which is part of a European project (CEC Project JOR3-CT95-0051) with the aim to substantially reduce the uncertainties involved in predicting environmentally radiated noise levels from wind farms (1). This will be achieved by comparing noise levels measure at varying distances from single and multiple sources over differing complexities of terrain with those predicted using a number of currently adopted sound propagation models. Specific objectives within the project are to: establish the important parameters controlling the propagation of wind farm noise to the far field; develop a planning tool for predicting wind farm noise emission levels under practically encountered conditions; place confidence limits on the upper and lower bounds of the noise levels predicted, thus enabling developers to quantify the risk whether noise emission from wind farms will cause nuisance to nearby residents. (Author)

  5. Reduction of Background Noise in the NASA Ames 40- by 80-Foot Wind Tunnel

    Science.gov (United States)

    Jaeger, Stephen M.; Allen, Christopher S.; Soderman, Paul T.; Olson, Larry E. (Technical Monitor)

    1995-01-01

    Background noise in both open-jet and closed wind tunnels adversely affects the signal-to-noise ratio of acoustic measurements. To measure the noise of increasingly quieter aircraft models, the background noise will have to be reduced by physical means or through signal processing. In a closed wind tunnel, such as the NASA Ames 40- by 80- Foot Wind Tunnel, the principle background noise sources can be classified as: (1) fan drive noise; (2) microphone self-noise; (3) aerodynamically induced noise from test-dependent hardware such as model struts and junctions; and (4) noise from the test section walls and vane set. This paper describes the steps taken to minimize the influence of each of these background noise sources in the 40 x 80.

  6. A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Zhang, Chu; Zhou, Jianzhong; Li, Chaoshun; Fu, Wenlong; Peng, Tian

    2017-01-01

    Highlights: • A novel hybrid approach is proposed for wind speed forecasting. • The variational mode decomposition (VMD) is optimized to decompose the original wind speed series. • The input matrix and parameters of ELM are optimized simultaneously by using a hybrid BSA. • Results show that OVMD-HBSA-ELM achieves better performance in terms of prediction accuracy. - Abstract: Reliable wind speed forecasting is essential for wind power integration in wind power generation system. The purpose of paper is to develop a novel hybrid model for short-term wind speed forecasting and demonstrates its efficiency. In the proposed model, a compound structure of extreme learning machine (ELM) based on feature selection and parameter optimization using hybrid backtracking search algorithm (HBSA) is employed as the predictor. The real-valued BSA (RBSA) is exploited to search for the optimal combination of weights and bias of ELM while the binary-valued BSA (BBSA) is exploited as a feature selection method applying on the candidate inputs predefined by partial autocorrelation function (PACF) values to reconstruct the input-matrix. Due to the volatility and randomness of wind speed signal, an optimized variational mode decomposition (OVMD) is employed to eliminate the redundant noises. The parameters of the proposed OVMD are determined according to the center frequencies of the decomposed modes and the residual evaluation index (REI). The wind speed signal is decomposed into a few modes via OVMD. The aggregation of the forecasting results of these modes constructs the final forecasting result of the proposed model. The proposed hybrid model has been applied on the mean half-hour wind speed observation data from two wind farms in Inner Mongolia, China and 10-min wind speed data from the Sotavento Galicia wind farm are studied as an additional case. Parallel experiments have been designed to compare with the proposed model. Results obtained from this study indicate that the

  7. Comparison of measured and predicted airfoil self-noise with application to wind turbine noise reduction

    International Nuclear Information System (INIS)

    Dassen, T.; Parchen, R.; Guidati, G.; Wagner, S.; Kang, S.; Khodak, A.E.

    1998-01-01

    In the ongoing JOULE-III project 'Development of Design Tools for Reduced Aerodynamic Noise Wind Turbines (DRAW)', prediction codes for inflow-turbulence (IT) noise and turbulent boundary layer trailing-edge (TE) noise, are developed and validated. It is shown that the differences in IT noise radiation between airfoils having a different shape, are correctly predicted. The first, preliminary comparison made between predicted and measured TE noise spectra yields satisfactory results. 17 refs

  8. Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

    Science.gov (United States)

    Azarpour, Masoumeh; Enzner, Gerald

    2017-12-01

    Binaural noise reduction, with applications for instance in hearing aids, has been a very significant challenge. This task relates to the optimal utilization of the available microphone signals for the estimation of the ambient noise characteristics and for the optimal filtering algorithm to separate the desired speech from the noise. The additional requirements of low computational complexity and low latency further complicate the design. A particular challenge results from the desired reconstruction of binaural speech input with spatial cue preservation. The latter essentially diminishes the utility of multiple-input/single-output filter-and-sum techniques such as beamforming. In this paper, we propose a comprehensive and effective signal processing configuration with which most of the aforementioned criteria can be met suitably. This relates especially to the requirement of efficient online adaptive processing for noise estimation and optimal filtering while preserving the binaural cues. Regarding noise estimation, we consider three different architectures: interaural (ITF), cross-relation (CR), and principal-component (PCA) target blocking. An objective comparison with two other noise PSD estimation algorithms demonstrates the superiority of the blocking-based noise estimators, especially the CR-based and ITF-based blocking architectures. Moreover, we present a new noise reduction filter based on minimum mean-square error (MMSE), which belongs to the class of common gain filters, hence being rigorous in terms of spatial cue preservation but also efficient and competitive for the acoustic noise reduction task. A formal real-time subjective listening test procedure is also developed in this paper. The proposed listening test enables a real-time assessment of the proposed computationally efficient noise reduction algorithms in a realistic acoustic environment, e.g., considering time-varying room impulse responses and the Lombard effect. The listening test outcome

  9. Coupling of an aeroacoustic model and a parabolic equation code for long range wind turbine noise propagation

    Science.gov (United States)

    Cotté, B.

    2018-05-01

    This study proposes to couple a source model based on Amiet's theory and a parabolic equation code in order to model wind turbine noise emission and propagation in an inhomogeneous atmosphere. Two broadband noise generation mechanisms are considered, namely trailing edge noise and turbulent inflow noise. The effects of wind shear and atmospheric turbulence are taken into account using the Monin-Obukhov similarity theory. The coupling approach, based on the backpropagation method to preserve the directivity of the aeroacoustic sources, is validated by comparison with an analytical solution for the propagation over a finite impedance ground in a homogeneous atmosphere. The influence of refraction effects is then analyzed for different directions of propagation. The spectrum modification related to the ground effect and the presence of a shadow zone for upwind receivers are emphasized. The validity of the point source approximation that is often used in wind turbine noise propagation models is finally assessed. This approximation exaggerates the interference dips in the spectra, and is not able to correctly predict the amplitude modulation.

  10. A semi-learning algorithm for noise rejection: an fNIRS study on ADHD children

    Science.gov (United States)

    Sutoko, Stephanie; Funane, Tsukasa; Katura, Takusige; Sato, Hiroki; Kiguchi, Masashi; Maki, Atsushi; Monden, Yukifumi; Nagashima, Masako; Yamagata, Takanori; Dan, Ippeita

    2017-02-01

    In pediatrics studies, the quality of functional near infrared spectroscopy (fNIRS) signals is often reduced by motion artifacts. These artifacts likely mislead brain functionality analysis, causing false discoveries. While noise correction methods and their performance have been investigated, these methods require several parameter assumptions that apparently result in noise overfitting. In contrast, the rejection of noisy signals serves as a preferable method because it maintains the originality of the signal waveform. Here, we describe a semi-learning algorithm to detect and eliminate noisy signals. The algorithm dynamically adjusts noise detection according to the predetermined noise criteria, which are spikes, unusual activation values (averaged amplitude signals within the brain activation period), and high activation variances (among trials). Criteria were sequentially organized in the algorithm and orderly assessed signals based on each criterion. By initially setting an acceptable rejection rate, particular criteria causing excessive data rejections are neglected, whereas others with tolerable rejections practically eliminate noises. fNIRS data measured during the attention response paradigm (oddball task) in children with attention deficit/hyperactivity disorder (ADHD) were utilized to evaluate and optimize the algorithm's performance. This algorithm successfully substituted the visual noise identification done in the previous studies and consistently found significantly lower activation of the right prefrontal and parietal cortices in ADHD patients than in typical developing children. Thus, we conclude that the semi-learning algorithm confers more objective and standardized judgment for noise rejection and presents a promising alternative to visual noise rejection

  11. Design of low noise wind turbine blades using Betz and Joukowski concepts

    DEFF Research Database (Denmark)

    Shen, Wen Zhong; Hrgovan, Iva; Okulov, Valery

    2014-01-01

    This paper presents the aerodynamic design of low noise wind turbine blades using Betz and Joukowski concepts. The aerodynamic model is based on Blade Element Momentum theory whereas the aeroacoustic prediction model is based on the BPM model. The investigation is started with a 3MW baseline...

  12. Noise from wind turbines. Guideline from the Environmental Protection Agency no. 1, 2012; Stoej fra vindmoeller

    Energy Technology Data Exchange (ETDEWEB)

    2012-07-01

    Wind turbines erected in Denmark, both on land and offshore, must observe noise limits in accordance with the Statutory Order no. 1284 of 15 December 2011. The noise limits apply to collective noise and are set for both weak winds, when noise is found to be most annoying, and stronger winds. The noise limits do not mean that noise is inaudible. They have been laid down to ensure that no significant disturbance is experienced. As most complaints from citizens are related to wind turbines on land and as the local governments are the controlling authorities, the present guideline is aimed at the local governments' administration of wind turbines. (LN)

  13. Effect of Wind Turbine Noise on Workers' Sleep Disorder: A Case Study of Manjil Wind Farm in Northern Iran

    Science.gov (United States)

    Abbasi, Milad; Monnazzam, Mohammad Reza; Zakerian, Sayedabbolfazl; Yousefzadeh, Arsalan

    2015-04-01

    Noise from wind turbines is one of the most important factors affecting the health, welfare, and human sleep. This research was carried out to study the effect of wind turbine noise on workers' sleep disorder. For this, Manjil Wind Farm, because of the greater number of staff and turbines than other wind farms in Iran, was chosen as case study. A total number of 53 participants took part in this survey. They were classified into three groups of mechanics, security, and official. In this study, daytime sleepiness data of workers were gathered using Epworth Sleepiness Scales (ESS) was used to determine the level of daytime sleepiness among the workers. The 8-h equivalent sound level (LAeq,8h) was measured to determine the individuals' exposure at each occupational group. Finally, the effect of sound, age, and workers' experience on individuals' sleep disorder was analyzed through multiple regression analysis in the R software. The results showed that there was a positive and significant relationship between age, workers' experience, equivalent sound level, and the level of sleep disorder. When age is constant, sleep disorder will increase by 26% as per each 1 dB increase in equivalent sound level. In situations where equivalent sound level is constant, an increase of 17% in sleep disorder is occurred as per each year of work experience. Because of the difference in sound exposure in different occupational groups. The effect of noise in repairing group was about 6.5 times of official group and also 3.4 times of the security group. Sleep disorder effect caused by wind turbine noise in the security group is almost two times more than the official group. Unlike most studies on wind turbine noise that address the sleep disorder among inhabitants nearby wind farms, this study, for the first time in the world, examines the impact of wind turbine noise on sleep disorder of workers who are more closer to wind turbines and exposed to higher levels of noise. So despite all the

  14. Consistent modelling of wind turbine noise propagation from source to receiver.

    Science.gov (United States)

    Barlas, Emre; Zhu, Wei Jun; Shen, Wen Zhong; Dag, Kaya O; Moriarty, Patrick

    2017-11-01

    The unsteady nature of wind turbine noise is a major reason for annoyance. The variation of far-field sound pressure levels is not only caused by the continuous change in wind turbine noise source levels but also by the unsteady flow field and the ground characteristics between the turbine and receiver. To take these phenomena into account, a consistent numerical technique that models the sound propagation from the source to receiver is developed. Large eddy simulation with an actuator line technique is employed for the flow modelling and the corresponding flow fields are used to simulate sound generation and propagation. The local blade relative velocity, angle of attack, and turbulence characteristics are input to the sound generation model. Time-dependent blade locations and the velocity between the noise source and receiver are considered within a quasi-3D propagation model. Long-range noise propagation of a 5 MW wind turbine is investigated. Sound pressure level time series evaluated at the source time are studied for varying wind speeds, surface roughness, and ground impedances within a 2000 m radius from the turbine.

  15. Hard decoding algorithm for optimizing thresholds under general Markovian noise

    Science.gov (United States)

    Chamberland, Christopher; Wallman, Joel; Beale, Stefanie; Laflamme, Raymond

    2017-04-01

    Quantum error correction is instrumental in protecting quantum systems from noise in quantum computing and communication settings. Pauli channels can be efficiently simulated and threshold values for Pauli error rates under a variety of error-correcting codes have been obtained. However, realistic quantum systems can undergo noise processes that differ significantly from Pauli noise. In this paper, we present an efficient hard decoding algorithm for optimizing thresholds and lowering failure rates of an error-correcting code under general completely positive and trace-preserving (i.e., Markovian) noise. We use our hard decoding algorithm to study the performance of several error-correcting codes under various non-Pauli noise models by computing threshold values and failure rates for these codes. We compare the performance of our hard decoding algorithm to decoders optimized for depolarizing noise and show improvements in thresholds and reductions in failure rates by several orders of magnitude. Our hard decoding algorithm can also be adapted to take advantage of a code's non-Pauli transversal gates to further suppress noise. For example, we show that using the transversal gates of the 5-qubit code allows arbitrary rotations around certain axes to be perfectly corrected. Furthermore, we show that Pauli twirling can increase or decrease the threshold depending upon the code properties. Lastly, we show that even if the physical noise model differs slightly from the hypothesized noise model used to determine an optimized decoder, failure rates can still be reduced by applying our hard decoding algorithm.

  16. Active Noise Control Using Modified FsLMS and Hybrid PSOFF Algorithm

    Directory of Open Access Journals (Sweden)

    Ranjan Walia

    2018-04-01

    Full Text Available Active noise control is an efficient technique for noise cancellation of the system, which has been defined in this paper with the aid of Modified Filtered-s Least Mean Square (MFsLMS algorithm. The Hybrid Particle Swarm Optimization and Firefly (HPSOFF algorithm are used to identify the stability factor of the MFsLMS algorithm. The computational difficulty of the modified algorithm is reduced when compared with the original Filtered-s Least Mean Square (FsLMS algorithm. The noise sources are removed from the signal and it is compared with the existing FsLMS algorithm. The performance of the system is established with the normalized mean square error for two different types of noises. The proposed method has also been compared with the existing algorithms for the same purposes.

  17. A combined aeroelastic-aeroacoustic model for wind turbine noise: Verification and analysis of field measurements

    DEFF Research Database (Denmark)

    Bertagnolio, Franck; Aagaard Madsen, Helge; Fischer, Andreas

    2017-01-01

    In this paper, semi-empirical engineering models for the three main wind turbine aerodynamic noise sources, namely, turbulent inflow, trailing edge and stall noise, are introduced. They are implemented into the in-house aeroelastic code HAWC2 commonly used for wind turbine load calculations...... and design. The results of the combined aeroelastic and aeroacoustic model are compared with field noise measurements of a 500kW wind turbine. Model and experimental data are in fairly good agreement in terms of noise levels and directivity. The combined model allows separating the various noise sources...... and highlights a number of mechanisms that are difficult to differentiate when only the overall noise from a wind turbine is measured....

  18. Objective and subjective rating of tonal noise radiated from UK wind farms: Pt. 2

    International Nuclear Information System (INIS)

    1996-01-01

    This final report provides data on the assessment of tonal noise radiation from wind turbines in the United Kingdom. Both objective and subjective assessments of the noise pollution from various wind farms are incorporated in the study. Previous subjective tests are verified here using a larger subject and sample size compared to the initial study. The study also aims to produce an objective automatic tonal assessment procedure which identifies tones and broad band masking noise in wind farm radiated noise spectra. (UK)

  19. Automatic bearing fault diagnosis of permanent magnet synchronous generators in wind turbines subjected to noise interference

    Science.gov (United States)

    Guo, Jun; Lu, Siliang; Zhai, Chao; He, Qingbo

    2018-02-01

    An automatic bearing fault diagnosis method is proposed for permanent magnet synchronous generators (PMSGs), which are widely installed in wind turbines subjected to low rotating speeds, speed fluctuations, and electrical device noise interferences. The mechanical rotating angle curve is first extracted from the phase current of a PMSG by sequentially applying a series of algorithms. The synchronous sampled vibration signal of the fault bearing is then resampled in the angular domain according to the obtained rotating phase information. Considering that the resampled vibration signal is still overwhelmed by heavy background noise, an adaptive stochastic resonance filter is applied to the resampled signal to enhance the fault indicator and facilitate bearing fault identification. Two types of fault bearings with different fault sizes in a PMSG test rig are subjected to experiments to test the effectiveness of the proposed method. The proposed method is fully automated and thus shows potential for convenient, highly efficient and in situ bearing fault diagnosis for wind turbines subjected to harsh environments.

  20. Short-Term Wind Speed Forecasting Using the Data Processing Approach and the Support Vector Machine Model Optimized by the Improved Cuckoo Search Parameter Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Chen Wang

    2016-01-01

    Full Text Available Power systems could be at risk when the power-grid collapse accident occurs. As a clean and renewable resource, wind energy plays an increasingly vital role in reducing air pollution and wind power generation becomes an important way to produce electrical power. Therefore, accurate wind power and wind speed forecasting are in need. In this research, a novel short-term wind speed forecasting portfolio has been proposed using the following three procedures: (I data preprocessing: apart from the regular normalization preprocessing, the data are preprocessed through empirical model decomposition (EMD, which reduces the effect of noise on the wind speed data; (II artificially intelligent parameter optimization introduction: the unknown parameters in the support vector machine (SVM model are optimized by the cuckoo search (CS algorithm; (III parameter optimization approach modification: an improved parameter optimization approach, called the SDCS model, based on the CS algorithm and the steepest descent (SD method is proposed. The comparison results show that the simple and effective portfolio EMD-SDCS-SVM produces promising predictions and has better performance than the individual forecasting components, with very small root mean squared errors and mean absolute percentage errors.

  1. Wind turbines. Unsteady aerodynamics and inflow noise

    Energy Technology Data Exchange (ETDEWEB)

    Riget Broe, B.

    2009-12-15

    Aerodynamical noise from wind turbines due to atmospheric turbulence has the highest emphasis in semi-empirical models. However it is an open question whether inflow noise has a high emphasis. This illustrates the need to investigate and improve the semi-empirical model for noise due to atmospheric turbulence. Three different aerodynamical models are investigated in order to estimate the lift fluctuations due to unsteady aerodynamics. Two of these models are investigated to find the unsteady lift distribution or pressure difference as function of chordwise position on the aerofoil. An acoustic model is investigated using a model for the lift distribution as input. The two models for lift distribution are used in the acoustic model. One of the models for lift distribution is for completely anisotropic turbulence and the other for perfectly isotropic turbulence, and so is also the corresponding models for the lift fluctuations derived from the models for lift distribution. The models for lift distribution and lift are compared with pressure data which are obtained by microphones placed flush with the surface of an aerofoil. The pressure data are from two experiments in a wind tunnel, one experiment with a NACA0015 profile and a second with a NACA63415 profile. The turbulence is measured by a triple wired hotwire instrument in the experiment with a NACA0015 profile. Comparison of the aerodynamical models with data shows that the models capture the general characteristics of the measurements, but the data are hampered by background noise from the fan propellers in the wind tunnel. The measurements are in between the completely anisotropic turbulent model and the perfectly isotropic turbulent model. This indicates that the models capture the aerodynamics well. Thus the measurements suggest that the noise due to atmospheric turbulence can be described and modeled by the two models for lift distribution. It was not possible to test the acoustical model by the measurements

  2. Effect of blade flutter and electrical loading on small wind turbine noise

    Science.gov (United States)

    The effect of blade flutter and electrical loading on the noise level of two different size wind turbines was investigated at the Conservation and Production Research Laboratory (CPRL) near Bushland, TX. Noise and performance data were collected on two blade designs tested on a wind turbine rated a...

  3. Coordinated Control for Flywheel Energy Storage Matrix Systems for Wind Farm Based on Charging/Discharging Ratio Consensus Algorithms

    DEFF Research Database (Denmark)

    Cao, Qian; Song, Y. D.; Guerrero, Josep M.

    2016-01-01

    This paper proposes a distributed algorithm for coordination of flywheel energy storage matrix system (FESMS) cooperated with wind farm. A simple and distributed ratio consensus algorithm is proposed to solve FESMS dispatch problem. The algorithm is based on average consensus for both undirected...... and unbalanced directed graphs. Average consensus is guaranteed in unbalanced digraphs by updating the weight matrix with both its row sums and column sums being 1. Simulation examples illustrate the effectiveness of the proposed control method....

  4. Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems.

    Science.gov (United States)

    Xu, Jingjiang; Song, Shaozhen; Li, Yuandong; Wang, Ruikang K

    2017-12-19

    Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

  5. Infrasound and low frequency noise from wind turbines: exposure and health effects

    Energy Technology Data Exchange (ETDEWEB)

    Bolin, Karl [Marcus Wallenberg Laboratory, Department of Aeronautical and Vehicle Engineering, Kungliga Tekniska Hoegskolan (Sweden); Bluhm, Goesta; Nilsson, Mats E [Institute of Environmental Medicine, Karolinska Institutet (Sweden); Eriksson, Gabriella, E-mail: kbolin@kth.se [Swedish National Road and Transport Research Institute and Linkoeping University (Sweden)

    2011-07-15

    Wind turbines emit low frequency noise (LFN) and large turbines generally generate more LFN than small turbines. The dominant source of LFN is the interaction between incoming turbulence and the blades. Measurements suggest that indoor levels of LFN in dwellings typically are within recommended guideline values, provided that the outdoor level does not exceed corresponding guidelines for facade exposure. Three cross-sectional questionnaire studies show that annoyance from wind turbine noise is related to the immission level, but several explanations other than low frequency noise are probable. A statistically significant association between noise levels and self-reported sleep disturbance was found in two of the three studies. It has been suggested that LFN from wind turbines causes other, and more serious, health problems, but empirical support for these claims is lacking.

  6. Noise from wind power plants. A study in anticipation of the recommendation from the Swedish Environmental Protection Agency

    International Nuclear Information System (INIS)

    Almgren, Martin

    2006-03-01

    Noise from wind turbines are today treated as industrial noise sources according to the guidelines for external industry noise set by Naturvaardsverket (the Swedish Environmental Protection Agency) in RR 1978:5. A praxis has been established with recommended limit 40 dBA equivalent continuous sound pressure level outside dwellings day, evening and night. Naturvaardsverket is planning new guidelines specific for wind turbine noise. A draft was presented at an information meeting 13th May 2005. Special requirements, which in some cases may be far-reaching, are planned for wind turbines. The purpose of this investigation is to illustrate the fairness of the planned requirements. Application of the recommended prediction model for sound propagation above a sea surface in the draft of Naturvaardsverket may lead to serious consequences for the planning of wind power plants near the coast. Research with measurements on sound propagation above water is at present made by the Royal Institute of Technology in Kalmarsund in Sweden. The results of these measurements, which probably will be completed during the spring 2006, should be waited for before a prediction model is recommended. If the model would be valid for sound propagation from wind turbines at sea, there should be some reports on complaint on noise from offshore based wind power plants. We have not been able to locate such complaints in Sweden (Bockstigen), in Denmark (Middelgrunden, Nystedts havmoellepark and Horns rev) or in the Netherlands. For Middelgrund and Nysted, the sound level calculated with Naturvaardsverkets model at 4,5 km and 7 km respectively is around 48 dBA. According to Swedish studies, such a level is annoying to many people. Two methods to set out limits for wind turbine noise are used internationally. In the first an absolute limit for the equivalent continuous sound pressure level is set. In the other, the sound pressure level is related to the background noise level. Naturvaardsverket is

  7. Transform Domain Robust Variable Step Size Griffiths' Adaptive Algorithm for Noise Cancellation in ECG

    Science.gov (United States)

    Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.

    2011-12-01

    The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.

  8. A generalized leaky FxLMS algorithm for tuning the waterbed effect of feedback active noise control systems

    Science.gov (United States)

    Wu, Lifu; Qiu, Xiaojun; Guo, Yecai

    2018-06-01

    To tune the noise amplification in the feedback system caused by the waterbed effect effectively, an adaptive algorithm is proposed in this paper by replacing the scalar leaky factor of the leaky FxLMS algorithm with a real symmetric Toeplitz matrix. The elements in the matrix are calculated explicitly according to the noise amplification constraints, which are defined based on a simple but efficient method. Simulations in an ANC headphone application demonstrate that the proposed algorithm can adjust the frequency band of noise amplification more effectively than the FxLMS algorithm and the leaky FxLMS algorithm.

  9. Design of low noise airfoil with high aerodynamic performance for use on small wind turbines

    Institute of Scientific and Technical Information of China (English)

    Taehyung; KIM; Seungmin; LEE; Hogeon; KIM; Soogab; LEE

    2010-01-01

    Wind power is one of the most reliable renewable energy sources and internationally installed capacity is increasing radically every year.Although wind power has been favored by the public in general,the problem with the impact of wind turbine noise on people living in the vicinity of the turbines has been increased.Low noise wind turbine design is becoming more and more important as noise is spreading more adverse effect of wind turbine to public.This paper demonstrates the design of 10 kW class wind turbines,each of three blades,a rotor diameter 6.4 m,a rated rotating speed 200 r/min and a rated wind speed 10 m/s.The optimized airfoil is dedicated for the 75% spanwise position because the dominant source of a wind turbine blade is trailing edge noise from the outer 25% of the blade.Numerical computations are performed for incompressible flow and for Mach number at 0.145 and for Reynolds numbers at 1.02×106 with a lift performance,which is resistant to surface contamination and turbulence intensity.The objectives in the design process are to reduce noise emission,while sustaining high aerodynamic efficiency.Dominant broadband noise sources are predicted by semi-empirical formulas composed of the groundwork by Brooks et al.and Lowson associated with typical wind turbine operation conditions.During the airfoil redesign process,the aerodynamic performance is analyzed to reduce the wind turbine power loss.The results obtained from the design process show that the design method is capable of designing airfoils with reduced noise using a commercial 10 kW class wind turbine blade airfoil as a basis.Therefore,the new optimized airfoil showing 2.9 dB reductions of total sound pressure level(SPL) and higher aerodynamic performance are achieved.

  10. Wind Turbine Generator System Acoustic Noise Test Report for the ARE 442 Wind Turbine

    Energy Technology Data Exchange (ETDEWEB)

    Huskey, A.; van Dam, J.

    2010-11-01

    This test was conducted on the ARE 442 as part of the U.S. Department of Energy's (DOE's) Independent Testing project. This project was established to help reduce the barriers of wind energy expansion by providing independent testing results for small turbines. In total, five turbines are being tested at the National Wind Technology Center (NWTC) as a part of this project. Acoustic noise testing is one of up to five tests that may be performed on the turbines, including duration, safety and function, power performance, and power quality tests. The acoustic noise test was conducted to the IEC 61400-11 Edition 2.1.

  11. Swimming Behavior of Roach (Rutilus rutilus) and Three-spined Stickleback (Gasterosteus aculeatus) in Response to Wind Power Noise and Single-tone Frequencies

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Mathias H.; Dock-Aakerman, Emily; Ubral-Hedenberg, Ramona; Oehman, Marcus C. (Dept. of Zoology, Stockholm Univ., Stockholm (Sweden)); Sigray, Peter (Dept. of Underwater Research, Swedish Defense Research Agency, Stockholm (Sweden))

    2007-12-15

    There is an environmental concern of how fish may be influenced by the developments of wind power offshore installations (20-23). In this study, two different species of fish were exposed to single-tone frequencies and sound generated by an offshore wind power plant. Both species reacted to the wind power noise which indicate that the noise may cause stress. However, fish have been noticed to habituate to sound and to associate with windmills at sea. This study was a small scale experiment. For a comprehensive understanding on how fish respond to wind power noise, additional studies are needed involving more species and large scale laboratory and field experiments based on detailed measurements of the noise generated from wind power plants

  12. Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, J.; Chowdhury, S.; Messac, A.; Hodge, B. M.

    2013-08-01

    This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.

  13. Trailing edge noise model applied to wind turbine airfoils

    Energy Technology Data Exchange (ETDEWEB)

    Bertagnolio, F.

    2008-01-15

    The aim of this work is firstly to provide a quick introduction to the theory of noise generation that are relevant to wind turbine technology with focus on trailing edge noise. Secondly, the socalled TNO trailing edge noise model developed by Parchen [1] is described in more details. The model is tested and validated by comparing with other results from the literature. Finally, this model is used in the optimization process of two reference airfoils in order to reduce their noise signature: the RISOE-B1-18 and the S809 airfoils. (au)

  14. Performance Analysis of Blind Subspace-Based Signature Estimation Algorithms for DS-CDMA Systems with Unknown Correlated Noise

    Science.gov (United States)

    Zarifi, Keyvan; Gershman, Alex B.

    2006-12-01

    We analyze the performance of two popular blind subspace-based signature waveform estimation techniques proposed by Wang and Poor and Buzzi and Poor for direct-sequence code division multiple-access (DS-CDMA) systems with unknown correlated noise. Using the first-order perturbation theory, analytical expressions for the mean-square error (MSE) of these algorithms are derived. We also obtain simple high SNR approximations of the MSE expressions which explicitly clarify how the performance of these techniques depends on the environmental parameters and how it is related to that of the conventional techniques that are based on the standard white noise assumption. Numerical examples further verify the consistency of the obtained analytical results with simulation results.

  15. Random Valued Impulse Noise Removal Using Region Based Detection Approach

    Directory of Open Access Journals (Sweden)

    S. Banerjee

    2017-12-01

    Full Text Available Removal of random valued noisy pixel is extremely challenging when the noise density is above 50%. The existing filters are generally not capable of eliminating such noise when density is above 70%. In this paper a region wise density based detection algorithm for random valued impulse noise has been proposed. On the basis of the intensity values, the pixels of a particular window are sorted and then stored into four regions. The higher density based region is considered for stepwise detection of noisy pixels. As a result of this detection scheme a maximum of 75% of noisy pixels can be detected. For this purpose this paper proposes a unique noise removal algorithm. It was experimentally proved that the proposed algorithm not only performs exceptionally when it comes to visual qualitative judgment of standard images but also this filter combination outsmarts the existing algorithm in terms of MSE, PSNR and SSIM comparison even up to 70% noise density level.

  16. Optimisation of electrical system for offshore wind farms via genetic algorithm

    DEFF Research Database (Denmark)

    Chen, Zhe; Zhao, Menghua; Blaabjerg, Frede

    2009-01-01

    An optimisation platform based on genetic algorithm (GA) is presented, where the main components of a wind farm and key technical specifications are used as input parameters and the electrical system design of the wind farm is optimised in terms of both production cost and system reliability....... The power losses, wind power production, initial investment and maintenance costs are considered in the production cost. The availability of components and network redundancy are included in the reliability evaluation. The method of coding an electrical system to a binary string, which is processed by GA......, is developed. Different GA techniques are investigated based on a real example offshore wind farm. This optimisation platform has been demonstrated as a powerful tool for offshore wind farm design and evaluation....

  17. A Shearlet-based algorithm for quantum noise removal in low-dose CT images

    Science.gov (United States)

    Zhang, Aguan; Jiang, Huiqin; Ma, Ling; Liu, Yumin; Yang, Xiaopeng

    2016-03-01

    Low-dose CT (LDCT) scanning is a potential way to reduce the radiation exposure of X-ray in the population. It is necessary to improve the quality of low-dose CT images. In this paper, we propose an effective algorithm for quantum noise removal in LDCT images using shearlet transform. Because the quantum noise can be simulated by Poisson process, we first transform the quantum noise by using anscombe variance stabilizing transform (VST), producing an approximately Gaussian noise with unitary variance. Second, the non-noise shearlet coefficients are obtained by adaptive hard-threshold processing in shearlet domain. Third, we reconstruct the de-noised image using the inverse shearlet transform. Finally, an anscombe inverse transform is applied to the de-noised image, which can produce the improved image. The main contribution is to combine the anscombe VST with the shearlet transform. By this way, edge coefficients and noise coefficients can be separated from high frequency sub-bands effectively. A number of experiments are performed over some LDCT images by using the proposed method. Both quantitative and visual results show that the proposed method can effectively reduce the quantum noise while enhancing the subtle details. It has certain value in clinical application.

  18. An Adaptive Filtering Algorithm Based on Genetic Algorithm-Backpropagation Network

    Directory of Open Access Journals (Sweden)

    Kai Hu

    2013-01-01

    Full Text Available A new image filtering algorithm is proposed. GA-BPN algorithm uses genetic algorithm (GA to decide weights in a back propagation neural network (BPN. It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-BPN to do image noise filter researching work. Firstly, this paper uses training samples to train GA-BPN as the noise detector. Then, we utilize the well-trained GA-BPN to recognize noise pixels in target image. And at last, an adaptive weighted average algorithm is used to recover noise pixels recognized by GA-BPN. Experiment data shows that this algorithm has better performance than other filters.

  19. Enhancements to AERMOD's building downwash algorithms based on wind-tunnel and Embedded-LES modeling

    Science.gov (United States)

    Monbureau, E. M.; Heist, D. K.; Perry, S. G.; Brouwer, L. H.; Foroutan, H.; Tang, W.

    2018-04-01

    Knowing the fate of effluent from an industrial stack is important for assessing its impact on human health. AERMOD is one of several Gaussian plume models containing algorithms to evaluate the effect of buildings on the movement of the effluent from a stack. The goal of this study is to improve AERMOD's ability to accurately model important and complex building downwash scenarios by incorporating knowledge gained from a recently completed series of wind tunnel studies and complementary large eddy simulations of flow and dispersion around simple structures for a variety of building dimensions, stack locations, stack heights, and wind angles. This study presents three modifications to the building downwash algorithm in AERMOD that improve the physical basis and internal consistency of the model, and one modification to AERMOD's building pre-processor to better represent elongated buildings in oblique winds. These modifications are demonstrated to improve the ability of AERMOD to model observed ground-level concentrations in the vicinity of a building for the variety of conditions examined in the wind tunnel and numerical studies.

  20. Robust frequency diversity based algorithm for clutter noise reduction of ultrasonic signals using multiple sub-spectrum phase coherence

    Energy Technology Data Exchange (ETDEWEB)

    Gongzhang, R.; Xiao, B.; Lardner, T.; Gachagan, A. [Centre for Ultrasonic Engineering, University of Strathclyde, Glasgow, G1 1XW (United Kingdom); Li, M. [School of Engineering, University of Glasgow, Glasgow, G12 8QQ (United Kingdom)

    2014-02-18

    This paper presents a robust frequency diversity based algorithm for clutter reduction in ultrasonic A-scan waveforms. The performance of conventional spectral-temporal techniques like Split Spectrum Processing (SSP) is highly dependent on the parameter selection, especially when the signal to noise ratio (SNR) is low. Although spatial beamforming offers noise reduction with less sensitivity to parameter variation, phased array techniques are not always available. The proposed algorithm first selects an ascending series of frequency bands. A signal is reconstructed for each selected band in which a defect is present when all frequency components are in uniform sign. Combining all reconstructed signals through averaging gives a probability profile of potential defect position. To facilitate data collection and validate the proposed algorithm, Full Matrix Capture is applied on the austenitic steel and high nickel alloy (HNA) samples with 5MHz transducer arrays. When processing A-scan signals with unrefined parameters, the proposed algorithm enhances SNR by 20dB for both samples and consequently, defects are more visible in B-scan images created from the large amount of A-scan traces. Importantly, the proposed algorithm is considered robust, while SSP is shown to fail on the austenitic steel data and achieves less SNR enhancement on the HNA data.

  1. Image Denoising Algorithm Combined with SGK Dictionary Learning and Principal Component Analysis Noise Estimation

    Directory of Open Access Journals (Sweden)

    Wenjing Zhao

    2018-01-01

    Full Text Available SGK (sequential generalization of K-means dictionary learning denoising algorithm has the characteristics of fast denoising speed and excellent denoising performance. However, the noise standard deviation must be known in advance when using SGK algorithm to process the image. This paper presents a denoising algorithm combined with SGK dictionary learning and the principal component analysis (PCA noise estimation. At first, the noise standard deviation of the image is estimated by using the PCA noise estimation algorithm. And then it is used for SGK dictionary learning algorithm. Experimental results show the following: (1 The SGK algorithm has the best denoising performance compared with the other three dictionary learning algorithms. (2 The SGK algorithm combined with PCA is superior to the SGK algorithm combined with other noise estimation algorithms. (3 Compared with the original SGK algorithm, the proposed algorithm has higher PSNR and better denoising performance.

  2. Hybrid Genetic Algorithm Fuzzy-Based Control Schemes for Small Power System with High-Penetration Wind Farms

    Directory of Open Access Journals (Sweden)

    Mohammed Elsayed Lotfy

    2018-03-01

    Full Text Available Wind is a clean, abundant, and inexhaustible source of energy. However, wind power is not constant, as windmill output is proportional to the cube of wind speed. As a result, the generated power of wind turbine generators (WTGs fluctuates significantly. Power fluctuation leads to frequency deviation and voltage flicker inside the system. This paper presents a new methodology for controlling system frequency and power. Two decentralized fuzzy logic-based control schemes with a high-penetration non-storage wind–diesel system are studied. First, one is implemented in the governor of conventional generators to damp frequency oscillation, while the other is applied to control the pitch angle system of wind turbines to smooth wind output power fluctuations and enhance the power system performance. A genetic algorithm (GA is employed to tune and optimize the membership function parameters of the fuzzy logic controllers to obtain optimal performance. The effectiveness of the suggested controllers is validated by time domain simulation for the standard IEEE nine-bus three-generator test system, including three wind farms. The robustness of the power system is checked under normal and faulty operating conditions.

  3. Multi-objective hybrid PSO-APO algorithm based security constrained optimal power flow with wind and thermal generators

    Directory of Open Access Journals (Sweden)

    Kiran Teeparthi

    2017-04-01

    Full Text Available In this paper, a new low level with teamwork heterogeneous hybrid particle swarm optimization and artificial physics optimization (HPSO-APO algorithm is proposed to solve the multi-objective security constrained optimal power flow (MO-SCOPF problem. Being engaged with the environmental and total production cost concerns, wind energy is highly penetrating to the main grid. The total production cost, active power losses and security index are considered as the objective functions. These are simultaneously optimized using the proposed algorithm for base case and contingency cases. Though PSO algorithm exhibits good convergence characteristic, fails to give near optimal solution. On the other hand, the APO algorithm shows the capability of improving diversity in search space and also to reach a near global optimum point, whereas, APO is prone to premature convergence. The proposed hybrid HPSO-APO algorithm combines both individual algorithm strengths, to get balance between global and local search capability. The APO algorithm is improving diversity in the search space of the PSO algorithm. The hybrid optimization algorithm is employed to alleviate the line overloads by generator rescheduling during contingencies. The standard IEEE 30-bus and Indian 75-bus practical test systems are considered to evaluate the robustness of the proposed method. The simulation results reveal that the proposed HPSO-APO method is more efficient and robust than the standard PSO and APO methods in terms of getting diverse Pareto optimal solutions. Hence, the proposed hybrid method can be used for the large interconnected power system to solve MO-SCOPF problem with integration of wind and thermal generators.

  4. Quality Control Algorithms for the Kennedy Space Center 50-Megahertz Doppler Radar Wind Profiler Winds Database

    Science.gov (United States)

    Barbre, Robert E., Jr.

    2012-01-01

    This paper presents the process used by the Marshall Space Flight Center Natural Environments Branch (EV44) to quality control (QC) data from the Kennedy Space Center's 50-MHz Doppler Radar Wind Profiler for use in vehicle wind loads and steering commands. The database has been built to mitigate limitations of using the currently archived databases from weather balloons. The DRWP database contains wind measurements from approximately 2.7-18.6 km altitude at roughly five minute intervals for the August 1997 to December 2009 period of record, and the extensive QC process was designed to remove spurious data from various forms of atmospheric and non-atmospheric artifacts. The QC process is largely based on DRWP literature, but two new algorithms have been developed to remove data contaminated by convection and excessive first guess propagations from the Median Filter First Guess Algorithm. In addition to describing the automated and manual QC process in detail, this paper describes the extent of the data retained. Roughly 58% of all possible wind observations exist in the database, with approximately 100 times as many complete profile sets existing relative to the EV44 balloon databases. This increased sample of near-continuous wind profile measurements may help increase launch availability by reducing the uncertainty of wind changes during launch countdown

  5. Aero-acoustic Computations of Wind Turbines

    DEFF Research Database (Denmark)

    Shen, Wen Zhong; Michelsen, Jess; Sørensen, Jens Nørkær

    2002-01-01

    A numerical algorithm for acoustic noise generation is extended to 3D flows. The approach involves two parts comprising a viscous incompressible flow part and an inviscid acoustic part. In order to simulate noise generated from a wind turbine, the incompressible and acoustic equations are written...... in polar coordinates. The developed algorithm is combined with a so-called actuator-line technique in which the loading is distributed along lines representing the blade forces. Computations are carried out for the 500kW Nordtank wind turbine equipped with three LM19 blades. ©2001 The American Institute...

  6. A multi-frame particle tracking algorithm robust against input noise

    International Nuclear Information System (INIS)

    Li, Dongning; Zhang, Yuanhui; Sun, Yigang; Yan, Wei

    2008-01-01

    The performance of a particle tracking algorithm which detects particle trajectories from discretely recorded particle positions could be substantially hindered by the input noise. In this paper, a particle tracking algorithm is developed which is robust against input noise. This algorithm employs the regression method instead of the extrapolation method usually employed by existing algorithms to predict future particle positions. If a trajectory cannot be linked to a particle at a frame, the algorithm can still proceed by trying to find a candidate at the next frame. The connectivity of tracked trajectories is inspected to remove the false ones. The algorithm is validated with synthetic data. The result shows that the algorithm is superior to traditional algorithms in the aspect of tracking long trajectories

  7. Noise annoyances from wind power: Survey of the population living close to a wind power plant. Final report: Part 3 Main study

    International Nuclear Information System (INIS)

    Pedersen, Eja; Persson-Waye, K.

    2002-02-01

    To evaluate the occurrence of annoyance from wind turbines, a study was performed in Laholm in May 2000. The aim was to obtain dose response relationships between calculated sound levels and noise annoyance and appropriate sound description as well as analysing the influence of other variables on noise annoyance. A questionnaire survey was performed in 6 areas comprising 16 wind turbines, of which 14 had an effect of 600 kW. The purpose of the study was masked. Among questions on living conditions in the countryside, questions directly related to wind turbines were included. The study population (n=518) comprised one randomly selected subject between the ages of 18 to 75 years in each household living within a calculated wind turbine sound level of 25 to 40 dBA. The response rate was 68.7% (n=356). Calculated distributions of A-weighted sound level were performed for each area and plotted on geographical maps in 2.5 dBA steps. Each dwelling could thus be given a sound level within an interval of 2.5 dBA. The most frequently occurring source of noise annoyance was noise from rotor blades. The proportions of respondents annoyed by noise increased with calculated sound level. Among respondents exposed to sound levels of 35.0-37.5 dBA, 43% responded themselves to be rather or much annoyed. A-weighted sound level was only one variable explaining annoyance. Annoyance was correlated to a larger extent by the intrusiveness of the sound character swishing. Noise annoyance was interrelated to the respondents' opinion of the visual impact of wind turbines, while attitude towards wind power in general had no greater influence. Disturbance of spoilt view was reported to a similar degree as noise disturbance. Further investigations are needed to clarify factors of importance for the disturbance of view. All the wind turbines in the study had constant rotation speed. The greater wind turbines that are now erected often have variable speed, which may lead to a sound comprising

  8. Calculation of wind turbine mechanical noise transmitted through the wings

    International Nuclear Information System (INIS)

    Vinther, S.; Kristensen, E.; Johansen, S.; Dam Madsen, K.

    2001-10-01

    A method for calculation of transmission noise radiated from the wind turbine blades has been established. The method is based on a numerical model describing the transmission of vibrations from the gear through the main shaft to the blades. In this project 1 MW and 2 MW wind turbines from BONUS Energy A/S are used as test cases. The numerical model offers the possibility of optimising the transmission system to avoid coincidence between gear excitation frequencies and natural frequencies of the blades. The optimisation can be reached by altering stiffness, mass and damping values for the different elements of the model. The numerical model needs experimental validation and supplementary determination of sound radiation factors for the blades. Therefore, a series of test methods have been developed and tried out. In a test rig for wind turbine, blades dynamic characteristicts and sound radiation factors for the blades were determined. On a 2 MW turbine tests were carried out during normal operation of the turbine. The shaft between the generator and the gearbox was excited in torsion by a hydraulic torsion exciter, and simultaneous response measurements of vibrations on one of the blades were made to estimate frequency response functions between gear and discrete points on the blade. The individual parts of the method have been tested, and the method showed out to supply valuable information about the different means for minimising radiation of transmission noise from the wind turbine blades. In future optimisation of the method, emphasis will be concentrated on the experimental validation provided by measurements on the operating wind turbine to provide a more certain validation of the numerical model. (au)

  9. A new hybrid metaheuristic algorithm for wind farm micrositing

    International Nuclear Information System (INIS)

    Massan, S.U.R.; Wagan, A.I.; Shaikh, M.M.

    2017-01-01

    This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic Algorithm) for the solution of the WTO (Wind Turbine Optimization) problem. It is well documented that turbines located behind one another face a power loss due to the obstruction of the wind due to wake loss. It is required to reduce this wake loss by the effective placement of turbines using a new HMA. This HMA is derived from the two basic algorithms i.e. DEA (Differential Evolution Algorithm) and the FA (Firefly Algorithm). The function of optimization is undertaken on the N.O. Jensen model. The blending of DEA and FA into HMA are discussed and the new algorithm HMA is implemented maximize power and minimize the cost in a WTO problem. The results by HMA have been compared with GA (Genetic Algorithm) used in some previous studies. The successfully calculated total power produced and cost per unit turbine for a wind farm by using HMA and its comparison with past approaches using single algorithms have shown that there is a significant advantage of using the HMA as compared to the use of single algorithms. The first time implementation of a new algorithm by blending two single algorithms is a significant step towards learning the behavior of algorithms and their added advantages by using them together. (author)

  10. A New Hybrid Metaheuristic Algorithm for Wind Farm Micrositing

    Directory of Open Access Journals (Sweden)

    SHAFIQ-UR-REHMAN MASSAN

    2017-07-01

    Full Text Available This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic Algorithm for the solution of the WTO (Wind Turbine Optimization problem. It is well documented that turbines located behind one another face a power loss due to the obstruction of the wind due to wake loss. It is required to reduce this wake loss by the effective placement of turbines using a new HMA. This HMA is derived from the two basic algorithms i.e. DEA (Differential Evolution Algorithm and the FA (Firefly Algorithm. The function of optimization is undertaken on the N.O. Jensen model. The blending of DEA and FA into HMA are discussed and the new algorithm HMA is implemented maximize power and minimize the cost in a WTO problem. The results by HMA have been compared with GA (Genetic Algorithm used in some previous studies. The successfully calculated total power produced and cost per unit turbine for a wind farm by using HMA and its comparison with past approaches using single algorithms have shown that there is a significant advantage of using the HMA as compared to the use of single algorithms. The first time implementation of a new algorithm by blending two single algorithms is a significant step towards learning the behavior of algorithms and their added advantages by using them together.

  11. Optimization design of wind turbine drive train based on Matlab genetic algorithm toolbox

    Science.gov (United States)

    Li, R. N.; Liu, X.; Liu, S. J.

    2013-12-01

    In order to ensure the high efficiency of the whole flexible drive train of the front-end speed adjusting wind turbine, the working principle of the main part of the drive train is analyzed. As critical parameters, rotating speed ratios of three planetary gear trains are selected as the research subject. The mathematical model of the torque converter speed ratio is established based on these three critical variable quantity, and the effect of key parameters on the efficiency of hydraulic mechanical transmission is analyzed. Based on the torque balance and the energy balance, refer to hydraulic mechanical transmission characteristics, the transmission efficiency expression of the whole drive train is established. The fitness function and constraint functions are established respectively based on the drive train transmission efficiency and the torque converter rotating speed ratio range. And the optimization calculation is carried out by using MATLAB genetic algorithm toolbox. The optimization method and results provide an optimization program for exact match of wind turbine rotor, gearbox, hydraulic mechanical transmission, hydraulic torque converter and synchronous generator, ensure that the drive train work with a high efficiency, and give a reference for the selection of the torque converter and hydraulic mechanical transmission.

  12. Optimization design of wind turbine drive train based on Matlab genetic algorithm toolbox

    International Nuclear Information System (INIS)

    Li, R N; Liu, X; Liu, S J

    2013-01-01

    In order to ensure the high efficiency of the whole flexible drive train of the front-end speed adjusting wind turbine, the working principle of the main part of the drive train is analyzed. As critical parameters, rotating speed ratios of three planetary gear trains are selected as the research subject. The mathematical model of the torque converter speed ratio is established based on these three critical variable quantity, and the effect of key parameters on the efficiency of hydraulic mechanical transmission is analyzed. Based on the torque balance and the energy balance, refer to hydraulic mechanical transmission characteristics, the transmission efficiency expression of the whole drive train is established. The fitness function and constraint functions are established respectively based on the drive train transmission efficiency and the torque converter rotating speed ratio range. And the optimization calculation is carried out by using MATLAB genetic algorithm toolbox. The optimization method and results provide an optimization program for exact match of wind turbine rotor, gearbox, hydraulic mechanical transmission, hydraulic torque converter and synchronous generator, ensure that the drive train work with a high efficiency, and give a reference for the selection of the torque converter and hydraulic mechanical transmission

  13. Comparison and application of wind retrieval algorithms for small unmanned aerial systems

    Science.gov (United States)

    Bonin, T. A.; Chilson, P. B.; Zielke, B. S.; Klein, P. M.; Leeman, J. R.

    2013-07-01

    Recently, there has been an increase in use of Unmanned Aerial Systems (UASs) as platforms for conducting fundamental and applied research in the lower atmosphere due to their relatively low cost and ability to collect samples with high spatial and temporal resolution. Concurrent with this development comes the need for accurate instrumentation and measurement methods suitable for small meteorological UASs. Moreover, the instrumentation to be integrated into such platforms must be small and lightweight. Whereas thermodynamic variables can be easily measured using well-aspirated sensors onboard, it is much more challenging to accurately measure the wind with a UAS. Several algorithms have been developed that incorporate GPS observations as a means of estimating the horizontal wind vector, with each algorithm exhibiting its own particular strengths and weaknesses. In the present study, the performance of three such GPS-based wind-retrieval algorithms has been investigated and compared with wind estimates from rawinsonde and sodar observations. Each of the algorithms considered agreed well with the wind measurements from sounding and sodar data. Through the integration of UAS-retrieved profiles of thermodynamic and kinematic parameters, one can investigate the static and dynamic stability of the atmosphere and relate them to the state of the boundary layer across a variety of times and locations, which might be difficult to access using conventional instrumentation.

  14. Development and comparisons of wind retrieval algorithms for small unmanned aerial systems

    Science.gov (United States)

    Bonin, T. A.; Chilson, P. B.; Zielke, B. S.; Klein, P. M.; Leeman, J. R.

    2012-12-01

    Recently, there has been an increase in use of Unmanned Aerial Systems (UASs) as platforms for conducting fundamental and applied research in the lower atmosphere due to their relatively low cost and ability to collect samples with high spatial and temporal resolution. Concurrent with this development comes the need for accurate instrumentation and measurement methods suitable for small meteorological UASs. Moreover, the instrumentation to be integrated into such platforms must be small and lightweight. Whereas thermodynamic variables can be easily measured using well aspirated sensors onboard, it is much more challenging to accurately measure the wind with a UAS. Several algorithms have been developed that incorporate GPS observations as a means of estimating the horizontal wind vector, with each algorithm exhibiting its own particular strengths and weaknesses. In the present study, the performance of three such GPS-based wind-retrieval algorithms has been investigated and compared with wind estimates from rawinsonde and sodar observations. Each of the algorithms considered agreed well with the wind measurements from sounding and sodar data. Through the integration of UAS-retrieved profiles of thermodynamic and kinematic parameters, one can investigate the static and dynamic stability of the atmosphere and relate them to the state of the boundary layer across a variety of times and locations, which might be difficult to access using conventional instrumentation.

  15. Measurements of noise immission from wind turbines at receptor locations: Use of a vertical microphone board to improve the signal-to-noise ratio

    International Nuclear Information System (INIS)

    Fegeant, Olivier

    1999-01-01

    The growing interest in wind energy has increased the need of accuracy in wind turbine noise immission measurements and thus, the need of new measurement techniques. This paper shows that mounting the microphone on a vertical board improves the signal-to-noise ratio over the whole frequency range compared to the free microphone technique. Indeed, the wind turbine is perceived two times noisier by the microphone due to the signal reflection by the board while, in addition, the wind noise is reduced. Furthermore, the board shielding effect allows the measurements to be carried out in the presence of reflecting surfaces such as building facades

  16. Aerodynamic noise characterization of a full-scale wind turbine through high-frequency surface pressure measurements

    DEFF Research Database (Denmark)

    Bertagnolio, Franck; Aagaard Madsen, Helge; Bak, Christian

    2015-01-01

    The aim of this work is to investigate and characterize the high-frequency surface pressure fluctuations on a full-scale wind turbine blade and in particular the influence of the atmospheric turbulence. As these fluctuations are highly correlated to the sources of both turbulent inflow noise...... and trailing edge noise, recognized to be the two main sources of noise from wind turbines, this work contributes to a more detailed insight into noise from wind turbines. The study comprises analysis and interpretation of measurement data that were acquired during an experimental campaign involving a 2 MW...... wind turbine with a 80 m diameter rotor as well as measurements of an airfoil section tested in a wind tunnel. The turbine was extensively equipped in order to monitor the local inflow onto the rotating blades. Further a section of the 38 m long blade was instrumented with 50 microphones flush...

  17. Consistent modelling of wind turbine noise propagation from source to receiver

    DEFF Research Database (Denmark)

    Barlas, Emre; Zhu, Wei Jun; Shen, Wen Zhong

    2017-01-01

    The unsteady nature of wind turbine noise is a major reason for annoyance. The variation of far-field sound pressure levels is not only caused by the continuous change in wind turbine noise source levels but also by the unsteady flow field and the ground characteristics between the turbine...... propagation of a 5 MW wind turbine is investigated. Sound pressure level time series evaluated at the source time are studied for varying wind speeds, surface roughness, and ground impedances within a 2000 m radius from the turbine....... and receiver. To take these phenomena into account, a consistent numerical technique that models the sound propagation from the source to receiver is developed. Large eddy simulation with an actuator line technique is employed for the flow modelling and the corresponding flow fields are used to simulate sound...

  18. Response to noise from modern wind farms in The Netherlands

    NARCIS (Netherlands)

    Pedersen, Eja; van den Berg, Frits; Bakker, Roel; Bouma, J.

    The increasing number and size of wind farms call for more data on human response to wind turbine noise, so that a generalized dose-response relationship can be modeled and possible adverse health effects avoided. This paper reports the results of a 2007 field study in The Netherlands with 725

  19. Noise elimination algorithm for modal analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bao, X. X., E-mail: baoxingxian@upc.edu.cn [Department of Naval Architecture and Ocean Engineering, China University of Petroleum (East China), Qingdao 266580 (China); Li, C. L. [Key Laboratory of Marine Geology and Environment, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071 (China); Xiong, C. B. [The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061 (China)

    2015-07-27

    Modal analysis is an ongoing interdisciplinary physical issue. Modal parameters estimation is applied to determine the dynamic characteristics of structures under vibration excitation. Modal analysis is more challenging for the measured vibration response signals are contaminated with noise. This study develops a mathematical algorithm of structured low rank approximation combined with the complex exponential method to estimate the modal parameters. Physical experiments using a steel cantilever beam with ten accelerometers mounted, excited by an impulse load, demonstrate that this method can significantly eliminate noise from measured signals and accurately identify the modal frequencies and damping ratios. This study provides a fundamental mechanism of noise elimination using structured low rank approximation in physical fields.

  20. Wind noise within and across behind-the-ear and miniature behind-the-ear hearing aids.

    Science.gov (United States)

    Zakis, Justin A; Hawkins, Daniel J

    2015-10-01

    Previous studies investigated wind noise with Behind-The-Ear (BTE) hearing aids, but not the more common mini-BTE style of device, which typically has a smaller shell and microphones located more deeply behind the pinna. The current study investigated wind-noise levels across one BTE and two mini-BTE devices, and between the front and rear omni-directional microphones within devices. Levels were measured at two wind speeds (3 and 6 m/s) and 36 wind azimuths (10° increments). The pattern of wind-noise level versus azimuth was similar across mini-BTE devices, and differed for the BTE device. However, mean levels were markedly different across mini-BTE devices, and could be higher, lower, or similar to those of the BTE device. For within-device level differences, the pattern and mean across azimuth were similar across mini-BTE devices, and differed for the BTE device. Wind noise had the potential to slightly or severely reduce speech intelligibility at 3 or 6 m/s, respectively, across all devices.

  1. Algorithmic-Reducibility = Renormalization-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') Replacing CRUTCHES!!!: Gauss Modular/Clock-Arithmetic Congruences = Signal X Noise PRODUCTS..

    Science.gov (United States)

    Siegel, J.; Siegel, Edward Carl-Ludwig

    2011-03-01

    Cook-Levin computational-"complexity"(C-C) algorithmic-equivalence reduction-theorem reducibility equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited with Gauss modular/clock-arithmetic/model congruences = signal X noise PRODUCT reinterpretation. Siegel-Baez FUZZYICS=CATEGORYICS(SON of ``TRIZ''): Category-Semantics(C-S) tabular list-format truth-table matrix analytics predicts and implements "noise"-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics(1987)]-Sipser[Intro. Theory Computation(1997) algorithmic C-C: "NIT-picking" to optimize optimization-problems optimally(OOPO). Versus iso-"noise" power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, this "NIT-picking" is "noise" power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-"science" algorithmic C-C models: Turing-machine, finite-state-models/automata, are identified as early-days once-workable but NOW ONLY LIMITING CRUTCHES IMPEDING latter-days new-insights!!!

  2. Droop assignment algorithm for the inertial control of a DFIG-based wind power plant for supporting the grid frequency

    DEFF Research Database (Denmark)

    Lee, Jinsik; Kang, Yong Cheol; Muljadi, Edward

    2014-01-01

    In a wind power plant (WPP) consisting of multiple wind generators (WGs), the wind speed of WGs at the downstream side decreases due to the wake effect, and thus their rotor speeds are smaller than those of the upstream WGs because of an MPPT operation. Therefore, WGs in a WPP have different amount......, while the same gains of the ROCOF loop are set for all WGs. In addition, the wake wind speed arriving at the WG is calculated by considering the wind direction and cumulative impacts of multiple shadowing. The performance of the algorithm was investigated under various wind conditions using an EMTP...... simulator. The results clearly indicate that the algorithm successfully improves the frequency nadir because WGs with higher wind speeds temporarily releases more kinetic energy....

  3. Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids.

    Science.gov (United States)

    Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker

    2012-08-01

    Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.

  4. A novel crystal-analyzer phase retrieval algorithm and its noise property.

    Science.gov (United States)

    Bao, Yuan; Wang, Yan; Li, Panyun; Wu, Zhao; Shao, Qigang; Gao, Kun; Wang, Zhili; Ju, Zaiqiang; Zhang, Kai; Yuan, Qingxi; Huang, Wanxia; Zhu, Peiping; Wu, Ziyu

    2015-05-01

    A description of the rocking curve in diffraction enhanced imaging (DEI) is presented in terms of the angular signal response function and a simple multi-information retrieval algorithm based on the cosine function fitting. A comprehensive analysis of noise properties of DEI is also given considering the noise transfer characteristic of the X-ray source. The validation has been performed with synchrotron radiation experimental data and Monte Carlo simulations based on the Geant4 toolkit combined with the refractive process of X-rays, which show good agreement with each other. Moreover, results indicate that the signal-to-noise ratios of the refraction and scattering images are about one order of magnitude better than that of the absorption image at the edges of low-Z samples. The noise penalty is drastically reduced with the increasing photon flux and visibility. Finally, this work demonstrates that the analytical method can build an interesting connection between DEI and GDPCI (grating-based differential phase contrast imaging) and is widely suitable for a variety of measurement noise in the angular signal response imaging prototype. The analysis significantly contributes to the understanding of noise characteristics of DEI images and may allow improvements to the signal-to-noise ratio in biomedical and material science imaging.

  5. Objective and subjective assessment of tonal components in noise from UK wind farm sites

    International Nuclear Information System (INIS)

    McKenzie, A.R.

    1997-01-01

    The level of any tonal components in the noise from a wind farm site can be quantified using objective analysis procedures. These procedures are, however, open to a certain amount of interpretation. an automated assessment procedure has, therefore, been developed which is appropriate to the needs of the wind turbine industry. This paper describes a study to compare the results of objective assessments carried out using this method with the results of carefully controlled subjective listening tests for samples of wind turbine noise from nine U.K. wind farm sites. (author)

  6. Deconvolution, differentiation and Fourier transformation algorithms for noise-containing data based on splines and global approximation

    NARCIS (Netherlands)

    Wormeester, Herbert; Sasse, A.G.B.M.; van Silfhout, Arend

    1988-01-01

    One of the main problems in the analysis of measured spectra is how to reduce the influence of noise in data processing. We show a deconvolution, a differentiation and a Fourier Transform algorithm that can be run on a small computer (64 K RAM) and suffer less from noise than commonly used routines.

  7. Long Range Sound Propagation over Sea: Application to Wind Turbine Noise

    Energy Technology Data Exchange (ETDEWEB)

    Boue, Matieu

    2007-12-13

    Oeland, an array of 8 microphones created an acoustical antenna directed towards the sound sources. Wind and temperature data was measured at the source location and during one measurement period (June 2005), wind and temperature profiles were also mapped in the reception area. In order to increase the signal to noise ratio different signal enhancement methods were tested including a Kalman Filter technique and periodic time-averaging. The most accurate results were obtained by combining the Kalman Filter model with a Fast Fourier Transform (FFT). Sound pressure levels as low as a few dB could be detected by using this algorithm. The final results expressed as a transmission loss ('damping in sound pressure level corrected for the atmospheric damping') between the source and the receiver, have been compared to simultaneously measured wind and temperature profiles. The transmission loss data have also been expressed as statistical distributions from which e.g. the average value can be obtained. This average, based on data for the summer period June 2005/2006, has been compared with the Swedish Environmental Protection Agency recommendation. It is found that the breaking point for cylindrical propagation is close to 700 m instead of the 200 m assumed in the recommendation. This is a significant difference and it shows that probably the Swedish recommendation uses a too small value for the expected breaking point. Of course in general the value of the breaking point can depend on the location and for which part of the year one takes the average. How large the variation can be due to such factors is today still unknown. Here only more measurements and perhaps simulations combined with the wind data base available in Sweden can provide an answer.

  8. Fault Detection of Wind Turbines with Uncertain Parameters

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Odgaard, Peter Fogh; Bak, Thomas

    2012-01-01

    on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach...... is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness...

  9. Noise and noise disturbances from wind power plants - Tests with interactive control of sound parameters for more comfortable and less perceptible sounds

    International Nuclear Information System (INIS)

    Persson-Waye, K.; Oehrstroem, E.; Bjoerkman, M.; Agge, A.

    2001-12-01

    In experimental pilot studies, a methodology has been worked out for interactively varying sound parameters in wind power plants. In the tests, 24 persons varied the center frequency of different band-widths, the frequency of a sinus-tone and the amplitude-modulation of a sinus-tone in order to create as comfortable a sound as possible. The variations build on the noise from the two wind turbines Bonus and Wind World. The variations were performed with a constant dba level. The results showed that the majority preferred a low-frequency tone (94 Hz and 115 Hz for Wind World and Bonus, respectively). The mean of the most comfortable amplitude-modulation varied between 18 and 22 Hz, depending on the ground frequency. The mean of the center-frequency for the different band-widths varied from 785 to 1104 Hz. In order to study the influence of the wind velocity on the acoustic character of the noise, a long-time measurement program has been performed. A remotely controlled system has been developed, where wind velocity, wind direction, temperature and humidity are registered simultaneously with the noise. Long-time registrations have been performed for four different wing turbines

  10. Evaluating the impact of wind turbine noise on health-related quality of life.

    Science.gov (United States)

    Shepherd, Daniel; McBride, David; Welch, David; Dirks, Kim N; Hill, Erin M

    2011-01-01

    We report a cross-sectional study comparing the health-related quality of life (HRQOL) of individuals residing in the proximity of a wind farm to those residing in a demographically matched area sufficiently displaced from wind turbines. The study employed a nonequivalent comparison group posttest-only design. Self-administered questionnaires, which included the brief version of the World Health Organization quality of life scale, were delivered to residents in two adjacent areas in semirural New Zealand. Participants were also asked to identify annoying noises, indicate their degree of noise sensitivity, and rate amenity. Statistically significant differences were noted in some HRQOL domain scores, with residents living within 2 km of a turbine installation reporting lower overall quality of life, physical quality of life, and environmental quality of life. Those exposed to turbine noise also reported significantly lower sleep quality, and rated their environment as less restful. Our data suggest that wind farm noise can negatively impact facets of HRQOL.

  11. Evaluating the impact of wind turbine noise on health-related quality of life

    Directory of Open Access Journals (Sweden)

    Daniel Shepherd

    2011-01-01

    Full Text Available We report a cross-sectional study comparing the health-related quality of life (HRQOL of individuals residing in the proximity of a wind farm to those residing in a demographically matched area sufficiently displaced from wind turbines. The study employed a nonequivalent comparison group posttest-only design. Self-administered questionnaires, which included the brief version of the World Health Organization quality of life scale, were delivered to residents in two adjacent areas in semirural New Zealand. Participants were also asked to identify annoying noises, indicate their degree of noise sensitivity, and rate amenity. Statistically significant differences were noted in some HRQOL domain scores, with residents living within 2 km of a turbine installation reporting lower overall quality of life, physical quality of life, and environmental quality of life. Those exposed to turbine noise also reported significantly lower sleep quality, and rated their environment as less restful. Our data suggest that wind farm noise can negatively impact facets of HRQOL.

  12. Comparison of single distance phase retrieval algorithms by considering different object composition and the effect of statistical and structural noise.

    Science.gov (United States)

    Chen, R C; Rigon, L; Longo, R

    2013-03-25

    Phase retrieval is a technique for extracting quantitative phase information from X-ray propagation-based phase-contrast tomography (PPCT). In this paper, the performance of different single distance phase retrieval algorithms will be investigated. The algorithms are herein called phase-attenuation duality Born Algorithm (PAD-BA), phase-attenuation duality Rytov Algorithm (PAD-RA), phase-attenuation duality Modified Bronnikov Algorithm (PAD-MBA), phase-attenuation duality Paganin algorithm (PAD-PA) and phase-attenuation duality Wu Algorithm (PAD-WA), respectively. They are all based on phase-attenuation duality property and on weak absorption of the sample and they employ only a single distance PPCT data. In this paper, they are investigated via simulated noise-free PPCT data considering the fulfillment of PAD property and weakly absorbing conditions, and with experimental PPCT data of a mixture sample containing absorbing and weakly absorbing materials, and of a polymer sample considering different degrees of statistical and structural noise. The simulation shows all algorithms can quantitatively reconstruct the 3D refractive index of a quasi-homogeneous weakly absorbing object from noise-free PPCT data. When the weakly absorbing condition is violated, the PAD-RA and PAD-PA/WA obtain better result than PAD-BA and PAD-MBA that are shown in both simulation and mixture sample results. When considering the statistical noise, the contrast-to-noise ratio values decreases as the photon number is reduced. The structural noise study shows that the result is progressively corrupted by ring-like artifacts with the increase of structural noise (i.e. phantom thickness). The PAD-RA and PAD-PA/WA gain better density resolution than the PAD-BA and PAD-MBA in both statistical and structural noise study.

  13. Measurements of Operational Wind Turbine Noise in UK Waters.

    Science.gov (United States)

    Cheesman, Samuel

    2016-01-01

    The effects of wind farm operational noise have not been addressed to the same extent as their construction methods such as piling and drilling of the foundations despite their long operational lifetimes compared with weeks of construction. The results of five postconstruction underwater sound-monitoring surveys on wind farms located throughout the waters of the British Isles are discussed. These wind farms consist of differing turbine power outputs, from 3 to 3.6 MW, and differing numbers of turbines. This work presents an overview of the results obtained and discusses both the levels and frequency components of the sound in several metrics.

  14. Aero-acoustic Computations of Wind Turbines

    DEFF Research Database (Denmark)

    Shen, Wen Zhong; Michelsen, Jess; Sørensen, Jens Nørkær

    2002-01-01

    A numerical algorithm for acoustic noise generation is extended to 3D flows. The approach involves two parts comprising a viscous incompressible flow part and an inviscid acoustic part. In order to simulate noise generated from a wind turbine, the incompressible and acoustic equations are written...

  15. An Observer-Based Controller with a LMI-Based Filter against Wind-Induced Motion for High-Rise Buildings

    Directory of Open Access Journals (Sweden)

    Chao-Jun Chen

    2017-01-01

    Full Text Available Active mass damper (AMD control system is proposed for high-rise buildings to resist a strong wind. However, negative influence of noise in sensors impedes the application of AMD systems in practice. To reduce the adverse influence of noise on AMD systems, a Kalman filter and a linear matrix inequality- (LMI- based filter are designed. Firstly, a ten-year return period fluctuating wind load is simulated by mixed autoregressive-moving average (MARMA method, and its reliability is tested by wind speed power spectrum and correlation analysis. Secondly, a designed state observer with different filters uses wind-induced acceleration responses of a high-rise building as the feedback signal that includes noise to calculate control force in this paper. Finally, these methods are applied to a numerical example of a high-rise building and an experiment of a single span four-storey steel frame. Both numerical and experimental results are presented to verify that both Kalman filter and LMI-based filter can effectively suppress noise, but only the latter can guarantee the stability of AMD parameters.

  16. Noise model based ν-support vector regression with its application to short-term wind speed forecasting.

    Science.gov (United States)

    Hu, Qinghua; Zhang, Shiguang; Xie, Zongxia; Mi, Jusheng; Wan, Jie

    2014-09-01

    Support vector regression (SVR) techniques are aimed at discovering a linear or nonlinear structure hidden in sample data. Most existing regression techniques take the assumption that the error distribution is Gaussian. However, it was observed that the noise in some real-world applications, such as wind power forecasting and direction of the arrival estimation problem, does not satisfy Gaussian distribution, but a beta distribution, Laplacian distribution, or other models. In these cases the current regression techniques are not optimal. According to the Bayesian approach, we derive a general loss function and develop a technique of the uniform model of ν-support vector regression for the general noise model (N-SVR). The Augmented Lagrange Multiplier method is introduced to solve N-SVR. Numerical experiments on artificial data sets, UCI data and short-term wind speed prediction are conducted. The results show the effectiveness of the proposed technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Optimization of Electrical System for Offshore Wind Farms via a Genetic Algorithm Approach

    DEFF Research Database (Denmark)

    Zhao, Menghua

    , and the LTC limitation of transformers, the power generation limits and the voltage operation range are considered as the constraints. The optimization method combined with probabilistic analysis is used to obtain the capacity of a given wind farm site. The OES-OWF is approached by Genetic Algorithm (GA...... to very different costs, system reliability, power quality, and power losses etc. Therefore, the optimization of electrical system design for offshore wind farms becomes more and more necessary. There are two tasks in this project: 1) the first one is to construct an algorithm for finding the capacity......). This platform is based on a knowledge database, and composed of several functional modules such as cost calculation, reliability evaluation, losses calculation, AC-DC integrated load flow algorithm etc. All these modules are based on a spreadsheet database which provides an interface for users to input...

  18. Blind signal processing algorithms under DC biased Gaussian noise

    Science.gov (United States)

    Kim, Namyong; Byun, Hyung-Gi; Lim, Jeong-Ok

    2013-05-01

    Distortions caused by the DC-biased laser input can be modeled as DC biased Gaussian noise and removing DC bias is important in the demodulation process of the electrical signal in most optical communications. In this paper, a new performance criterion and a related algorithm for unsupervised equalization are proposed for communication systems in the environment of channel distortions and DC biased Gaussian noise. The proposed criterion utilizes the Euclidean distance between the Dirac-delta function located at zero on the error axis and a probability density function of biased constant modulus errors, where constant modulus error is defined by the difference between the system out and a constant modulus calculated from the transmitted symbol points. From the results obtained from the simulation under channel models with fading and DC bias noise abruptly added to background Gaussian noise, the proposed algorithm converges rapidly even after the interruption of DC bias proving that the proposed criterion can be effectively applied to optical communication systems corrupted by channel distortions and DC bias noise.

  19. Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

    Energy Technology Data Exchange (ETDEWEB)

    Solomon, Justin, E-mail: justin.solomon@duke.edu [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Samei, Ehsan [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 and Departments of Biomedical Engineering and Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina 27705 (United States)

    2014-09-15

    Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

  20. Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

    International Nuclear Information System (INIS)

    Solomon, Justin; Samei, Ehsan

    2014-01-01

    Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

  1. Noise effect in an improved conjugate gradient algorithm to invert particle size distribution and the algorithm amendment.

    Science.gov (United States)

    Wei, Yongjie; Ge, Baozhen; Wei, Yaolin

    2009-03-20

    In general, model-independent algorithms are sensitive to noise during laser particle size measurement. An improved conjugate gradient algorithm (ICGA) that can be used to invert particle size distribution (PSD) from diffraction data is presented. By use of the ICGA to invert simulated data with multiplicative or additive noise, we determined that additive noise is the main factor that induces distorted results. Thus the ICGA is amended by introduction of an iteration step-adjusting parameter and is used experimentally on simulated data and some samples. The experimental results show that the sensitivity of the ICGA to noise is reduced and the inverted results are in accord with the real PSD.

  2. Noise immission from wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-07-01

    This report is in itself a Summary of the entire NIWT project, JOR3-CT95-0065, which consisted of a jointly EC funded collaboration between nine European partners in six Countries which ran between January 1996 and December 1997. The primary aims of the project were to investigate a number of aspects associated with more precisely quantifying the uncertainties associated with the Measurement of Acoustic Noise Immission of wind turbines. The main findings of the report are contained in the technical reports issued by partners on individual tasks. Copies of individual reports can be obtained directly from the participating partners. (author)

  3. A Background Noise Reduction Technique Using Adaptive Noise Cancellation for Microphone Arrays

    Science.gov (United States)

    Spalt, Taylor B.; Fuller, Christopher R.; Brooks, Thomas F.; Humphreys, William M., Jr.; Brooks, Thomas F.

    2011-01-01

    Background noise in wind tunnel environments poses a challenge to acoustic measurements due to possible low or negative Signal to Noise Ratios (SNRs) present in the testing environment. This paper overviews the application of time domain Adaptive Noise Cancellation (ANC) to microphone array signals with an intended application of background noise reduction in wind tunnels. An experiment was conducted to simulate background noise from a wind tunnel circuit measured by an out-of-flow microphone array in the tunnel test section. A reference microphone was used to acquire a background noise signal which interfered with the desired primary noise source signal at the array. The technique s efficacy was investigated using frequency spectra from the array microphones, array beamforming of the point source region, and subsequent deconvolution using the Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) algorithm. Comparisons were made with the conventional techniques for improving SNR of spectral and Cross-Spectral Matrix subtraction. The method was seen to recover the primary signal level in SNRs as low as -29 dB and outperform the conventional methods. A second processing approach using the center array microphone as the noise reference was investigated for more general applicability of the ANC technique. It outperformed the conventional methods at the -29 dB SNR but yielded less accurate results when coherence over the array dropped. This approach could possibly improve conventional testing methodology but must be investigated further under more realistic testing conditions.

  4. FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling.

    Science.gov (United States)

    Kim, Chang-Min; Park, Hyung-Min; Kim, Taesu; Choi, Yoon-Kyung; Lee, Soo-Young

    2003-01-01

    An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in FPGA. The chip design fully utilizes modular concept and several chips may be put together for complex applications with a large number of noise sources. Experimental results with a fabricated test board are reported for ANC only, BSS only, and simultaneous ANC/BSS, which demonstrates successful speech enhancement in real environments in real time.

  5. The effects of vision-related aspects on noise perception of wind turbines in quiet areas.

    Science.gov (United States)

    Maffei, Luigi; Iachini, Tina; Masullo, Massimiliano; Aletta, Francesco; Sorrentino, Francesco; Senese, Vincenzo Paolo; Ruotolo, Francesco

    2013-04-26

    Preserving the soundscape and geographic extension of quiet areas is a great challenge against the wide-spreading of environmental noise. The E.U. Environmental Noise Directive underlines the need to preserve quiet areas as a new aim for the management of noise in European countries. At the same time, due to their low population density, rural areas characterized by suitable wind are considered appropriate locations for installing wind farms. However, despite the fact that wind farms are represented as environmentally friendly projects, these plants are often viewed as visual and audible intruders, that spoil the landscape and generate noise. Even though the correlations are still unclear, it is obvious that visual impacts of wind farms could increase due to their size and coherence with respect to the rural/quiet environment. In this paper, by using the Immersive Virtual Reality technique, some visual and acoustical aspects of the impact of a wind farm on a sample of subjects were assessed and analyzed. The subjects were immersed in a virtual scenario that represented a situation of a typical rural outdoor scenario that they experienced at different distances from the wind turbines. The influence of the number and the colour of wind turbines on global, visual and auditory judgment were investigated. The main results showed that, regarding the number of wind turbines, the visual component has a weak effect on individual reactions, while the colour influences both visual and auditory individual reactions, although in a different way.

  6. Star point centroid algorithm based on background forecast

    Science.gov (United States)

    Wang, Jin; Zhao, Rujin; Zhu, Nan

    2014-09-01

    The calculation of star point centroid is a key step of improving star tracker measuring error. A star map photoed by APS detector includes several noises which have a great impact on veracity of calculation of star point centroid. Through analysis of characteristic of star map noise, an algorithm of calculation of star point centroid based on background forecast is presented in this paper. The experiment proves the validity of the algorithm. Comparing with classic algorithm, this algorithm not only improves veracity of calculation of star point centroid, but also does not need calibration data memory. This algorithm is applied successfully in a certain star tracker.

  7. Exposure to wind turbine noise: Perceptual responses and reported health effects.

    Science.gov (United States)

    Michaud, David S; Feder, Katya; Keith, Stephen E; Voicescu, Sonia A; Marro, Leonora; Than, John; Guay, Mireille; Denning, Allison; McGuire, D'Arcy; Bower, Tara; Lavigne, Eric; Murray, Brian J; Weiss, Shelly K; van den Berg, Frits

    2016-03-01

    Health Canada, in collaboration with Statistics Canada, and other external experts, conducted the Community Noise and Health Study to better understand the impacts of wind turbine noise (WTN) on health and well-being. A cross-sectional epidemiological study was carried out between May and September 2013 in southwestern Ontario and Prince Edward Island on 1238 randomly selected participants (606 males, 632 females) aged 18-79 years, living between 0.25 and 11.22 km from operational wind turbines. Calculated outdoor WTN levels at the dwelling reached 46 dBA. Response rate was 78.9% and did not significantly differ across sample strata. Self-reported health effects (e.g., migraines, tinnitus, dizziness, etc.), sleep disturbance, sleep disorders, quality of life, and perceived stress were not related to WTN levels. Visual and auditory perception of wind turbines as reported by respondents increased significantly with increasing WTN levels as did high annoyance toward several wind turbine features, including the following: noise, blinking lights, shadow flicker, visual impacts, and vibrations. Concern for physical safety and closing bedroom windows to reduce WTN during sleep also increased with increasing WTN levels. Other sample characteristics are discussed in relation to WTN levels. Beyond annoyance, results do not support an association between exposure to WTN up to 46 dBA and the evaluated health-related endpoints.

  8. A Novel Partial Discharge Ultra-High Frequency Signal De-Noising Method Based on a Single-Channel Blind Source Separation Algorithm

    Directory of Open Access Journals (Sweden)

    Liangliang Wei

    2018-02-01

    Full Text Available To effectively de-noise the Gaussian white noise and periodic narrow-band interference in the background noise of partial discharge ultra-high frequency (PD UHF signals in field tests, a novel de-noising method, based on a single-channel blind source separation algorithm, is proposed. Compared with traditional methods, the proposed method can effectively de-noise the noise interference, and the distortion of the de-noising PD signal is smaller. Firstly, the PD UHF signal is time-frequency analyzed by S-transform to obtain the number of source signals. Then, the single-channel detected PD signal is converted into multi-channel signals by singular value decomposition (SVD, and background noise is separated from multi-channel PD UHF signals by the joint approximate diagonalization of eigen-matrix method. At last, the source PD signal is estimated and recovered by the l1-norm minimization method. The proposed de-noising method was applied on the simulation test and field test detected signals, and the de-noising performance of the different methods was compared. The simulation and field test results demonstrate the effectiveness and correctness of the proposed method.

  9. Wind power forecast using wavelet neural network trained by improved Clonal selection algorithm

    International Nuclear Information System (INIS)

    Chitsaz, Hamed; Amjady, Nima; Zareipour, Hamidreza

    2015-01-01

    Highlights: • Presenting a Morlet wavelet neural network for wind power forecasting. • Proposing improved Clonal selection algorithm for training the model. • Applying Maximum Correntropy Criterion to evaluate the training performance. • Extensive testing of the proposed wind power forecast method on real-world data. - Abstract: With the integration of wind farms into electric power grids, an accurate wind power prediction is becoming increasingly important for the operation of these power plants. In this paper, a new forecasting engine for wind power prediction is proposed. The proposed engine has the structure of Wavelet Neural Network (WNN) with the activation functions of the hidden neurons constructed based on multi-dimensional Morlet wavelets. This forecast engine is trained by a new improved Clonal selection algorithm, which optimizes the free parameters of the WNN for wind power prediction. Furthermore, Maximum Correntropy Criterion (MCC) has been utilized instead of Mean Squared Error as the error measure in training phase of the forecasting model. The proposed wind power forecaster is tested with real-world hourly data of system level wind power generation in Alberta, Canada. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. The obtained results confirm the validity of the developed approach

  10. Noise properties of the EM algorithm. Pt. 1

    International Nuclear Information System (INIS)

    Barrett, H.H.; Wilson, D.W.; Tsui, B.M.W.

    1994-01-01

    The expectation-maximisation (EM) algorithm is an important tool for maximum-likelihood (ML) estimation and image reconstruction, especially in medical imaging. It is a non-linear iterative algorithm that attempts to find the ML estimate of the object that produced a data set. The convergence of the algorithm and other deterministic properties are well established, but relatively little is known about how noise in the data influences noise in the final reconstructed image. In this paper we present a detailed treatment of these statistical properties. The specific application we have in mind is image reconstruction in emission tomography, but the results are valid for any application of the EM algorithm in which the data set can be described by Poisson statistics. We show that the probability density function for the grey level at a pixel in the image is well approximated by a log-normal law. An expression is derived for the variance of the grey level and for pixel-to-pixel covariance. The variance increases rapidly with iteration number at first, but eventually saturates as the ML estimate is approached. Moreover, the variance at any iteration number has a factor proportional to the square of the mean image (though other factors may also depend on the mean image), so a map of the standard deviation resembles the object itself. Thus low-intensity regions of the image tend to have low noise. (author)

  11. Image segmentation algorithm based on T-junctions cues

    Science.gov (United States)

    Qian, Yanyu; Cao, Fengyun; Wang, Lu; Yang, Xuejie

    2016-03-01

    To improve the over-segmentation and over-merge phenomenon of single image segmentation algorithm,a novel approach of combing Graph-Based algorithm and T-junctions cues is proposed in this paper. First, a method by L0 gradient minimization is applied to the smoothing of the target image eliminate artifacts caused by noise and texture detail; Then, the initial over-segmentation result of the smoothing image using the graph-based algorithm; Finally, the final results via a region fusion strategy by t-junction cues. Experimental results on a variety of images verify the new approach's efficiency in eliminating artifacts caused by noise,segmentation accuracy and time complexity has been significantly improved.

  12. A Novel Combined Model Based on an Artificial Intelligence Algorithm—A Case Study on Wind Speed Forecasting in Penglai, China

    Directory of Open Access Journals (Sweden)

    Feiyu Zhang

    2016-06-01

    Full Text Available Wind speed forecasting plays a key role in wind-related engineering studies and is important in the management of wind farms. Current forecasting models based on different optimization algorithms can be adapted to various wind speed time series data. However, these methodologies cannot aggregate different hybrid forecasting methods and take advantage of the component models. To avoid these limitations, we propose a novel combined forecasting model called SSA-PSO-DWCM, i.e., particle swarm optimization (PSO determined weight coefficients model. This model consisted of three main steps: one is the decomposition of the original wind speed signals to discard the noise, the second is the parameter optimization of the forecasting method, and the last is the combination of different models in a nonlinear way. The proposed combined model is examined by forecasting the wind speed (10-min intervals of wind turbine 5 located in the Penglai region of China. The simulations reveal that the proposed combined model demonstrates a more reliable forecast than the component forecasting engines and the traditional combined method, which is based on a linear method.

  13. Cyclic pitch for the control of wind turbine noise amplitude modulation

    DEFF Research Database (Denmark)

    Bertagnolio, Franck; Aagaard Madsen, Helge; Fischer, Andreas

    2014-01-01

    Using experimental data acquired during a wind turbine measurement campaign, it is shown that amplitude modulation of aerodynamic noise can be generated by the rotating blades in conjunction with the atmospheric wind shear. As an attempt to alleviate this phenomenon, a control strategy is designed...... if such a strategy is to be implemented on an actual wind turbine, though at the expense of an increased wear and tear of the pitch control system....

  14. Optimisation of Offshore Wind Farm Cable Connection Layout Considering Levelised Production Cost Using Dynamic Minimum Spanning Tree Algorithm

    DEFF Research Database (Denmark)

    Hou, Peng; Hu, Weihao; Chen, Cong

    2016-01-01

    The approach in this paper hads been developed to optimize the cable connection layout of large scale offshore wind farms. The objective is to minimize the Levelised Production Cost (LPC) og an offshore wind farm by optimizing the cable connection configuration. Based on the minimum spanning tree...... (MST) algorithm, an improved algorithm, the Dynamic Minimum Spanning Tree (DMST) algorithm is proposed. The current carrying capacity of the cable is considered to be the main constraint and the cable sectional area is changed dynamically. An irregular shaped wind farm is chosen as the studie case...

  15. Sources and levels of background noise in the NASA Ames 40- by 80-foot wind tunnel

    Science.gov (United States)

    Soderman, Paul T.

    1988-01-01

    Background noise levels are measured in the NASA Ames Research Center 40- by 80-Foot Wind Tunnel following installation of a sound-absorbent lining on the test-section walls. Results show that the fan-drive noise dominated the empty test-section background noise at airspeeds below 120 knots. Above 120 knots, the test-section broadband background noise was dominated by wind-induced dipole noise (except at lower harmonics of fan blade-passage tones) most likely generated at the microphone or microphone support strut. Third-octave band and narrow-band spectra are presented for several fan operating conditions and test-section airspeeds. The background noise levels can be reduced by making improvements to the microphone wind screen or support strut. Empirical equations are presented relating variations of fan noise with fan speed or blade-pitch angle. An empirical expression for typical fan noise spectra is also presented. Fan motor electric power consumption is related to the noise generation. Preliminary measurements of sound absorption by the test-section lining indicate that the 152 mm thick lining will adequately absorb test-section model noise at frequencies above 300 Hz.

  16. Evaluation of wind noise in passenger car compartment in consideration of auditory masking and sound localization; Chokaku masking to hoko chikaku wo koryoshita kazekirion hyoka

    Energy Technology Data Exchange (ETDEWEB)

    Hoshino, H. [Toyota Central Research and Development Labs., Inc., Aichi (Japan); Kato, H. [Toyota Motor Corp., Aichi (Japan)

    1998-05-01

    Discussed is a method for evaluating wind noise in passenger car compartment based on human auditory characteristics. In the study, noise in the compartment of a passenger car travelling at a constant speed is collected by use of a dummy head, and the collected noise is analyzed in view of the masking effect, directional sensation produced by binaural hearing, etc. A masked spectrum of noise in the compartment of a 6-cylinder vehicle travelling at 120km/h is analyzed, and it is found that some frequency bands, especially the band centering on 300Hz, are masked by a loud noise component falling in a low frequency band of 180Hz or lower. By use of masked spectrum analysis, the level of noise that is actually audible to human ears can be calculated. The noise level thus determined by masked spectrum analysis and the noise direction determined by a binaural signal processing model are examined, and then it is found that the noise direction is clearly determined when the noise belongs in a 450Hz band or higher where wind noise prevails. On the bases of the above-mentioned results and the directional sensation produced by binaural hearing, a `binaural wind noise evaluation method` is compiled. 20 refs., 9 figs., 1 tab.

  17. Evolving aerodynamic airfoils for wind turbines through a genetic algorithm

    Science.gov (United States)

    Hernández, J. J.; Gómez, E.; Grageda, J. I.; Couder, C.; Solís, A.; Hanotel, C. L.; Ledesma, JI

    2017-01-01

    Nowadays, genetic algorithms stand out for airfoil optimisation, due to the virtues of mutation and crossing-over techniques. In this work we propose a genetic algorithm with arithmetic crossover rules. The optimisation criteria are taken to be the maximisation of both aerodynamic efficiency and lift coefficient, while minimising drag coefficient. Such algorithm shows greatly improvements in computational costs, as well as a high performance by obtaining optimised airfoils for Mexico City's specific wind conditions from generic wind turbines designed for higher Reynolds numbers, in few iterations.

  18. Improved gravitational search algorithm for unit commitment considering uncertainty of wind power

    International Nuclear Information System (INIS)

    Ji, Bin; Yuan, Xiaohui; Chen, Zhihuan; Tian, Hao

    2014-01-01

    With increasing wind farm integrations, unit commitment (UC) is more difficult to solve because of the intermittent and fluctuation nature of wind power. In this paper, scenario generation and reduction technique is applied to simulate the impacts of its uncertainty on system operation. And then a model of thermal UC problem with wind power integration (UCW) is established. Combination of quantum-inspired binary gravitational search algorithm (GSA) and scenario analysis method is proposed to solve UCW problem. Meanwhile, heuristic search strategies are used to handle the constraints of thermal unit for each scenario. In addition, a priority list of thermal units based on the weight between average full-load cost and maximal power output is utilized during the optimization process. Moreover, two UC test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method as well as the performance of the algorithm. The results are analyzed in detail, which demonstrate the model and the proposed method is practicable. The comparison with other methods clearly shows that the proposed method has higher efficiency for solving UC problems with and even without wind farm integration. - Highlights: • Impact of wind fluctuation on unit commitment problem (UCW) is investigated. • Quantum-inspired gravitational search algorithm (QBGSA) is used to optimize UC. • A new method combines QBGSA with scenario analysis is proposed to solve UCW. • Heuristic search strategies are applied to handle the constraints of the UCW. • The results verify the proposed method is feasible and efficient for handling UCW

  19. Noise propagation in iterative reconstruction algorithms with line searches

    International Nuclear Information System (INIS)

    Qi, Jinyi

    2003-01-01

    In this paper we analyze the propagation of noise in iterative image reconstruction algorithms. We derive theoretical expressions for the general form of preconditioned gradient algorithms with line searches. The results are applicable to a wide range of iterative reconstruction problems, such as emission tomography, transmission tomography, and image restoration. A unique contribution of this paper comparing to our previous work [1] is that the line search is explicitly modeled and we do not use the approximation that the gradient of the objective function is zero. As a result, the error in the estimate of noise at early iterations is significantly reduced

  20. Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

    Science.gov (United States)

    Ren, Shengwei; Zhang, Li; Zhang, Shibing

    2016-10-01

    Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

  1. Optimized Swinging Door Algorithm for Wind Power Ramp Event Detection: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Mingjian; Zhang, Jie; Florita, Anthony R.; Hodge, Bri-Mathias; Ke, Deping; Sun, Yuanzhang

    2015-08-06

    Significant wind power ramp events (WPREs) are those that influence the integration of wind power, and they are a concern to the continued reliable operation of the power grid. As wind power penetration has increased in recent years, so has the importance of wind power ramps. In this paper, an optimized swinging door algorithm (SDA) is developed to improve ramp detection performance. Wind power time series data are segmented by the original SDA, and then all significant ramps are detected and merged through a dynamic programming algorithm. An application of the optimized SDA is provided to ascertain the optimal parameter of the original SDA. Measured wind power data from the Electric Reliability Council of Texas (ERCOT) are used to evaluate the proposed optimized SDA.

  2. EUDP project 'Low noise airfoil' - Final report

    Energy Technology Data Exchange (ETDEWEB)

    Bertagnolio, F. (ed.)

    2012-06-15

    Tunnel as the high ambient noise levels largely overwhelmed the signal of interest. Finally, a new airfoil design was proposed based on a design concept including noise reduction. The new airfoil proved to perform better aerodynamically but noise reduction were not as important as expected, mainly due to the inaccuracy of the simplified flow model used in the design algorithm. (Author)

  3. RBF neural network based PI pitch controller for a class of 5-MW wind turbines using particle swarm optimization algorithm.

    Science.gov (United States)

    Poultangari, Iman; Shahnazi, Reza; Sheikhan, Mansour

    2012-09-01

    In order to control the pitch angle of blades in wind turbines, commonly the proportional and integral (PI) controller due to its simplicity and industrial usability is employed. The neural networks and evolutionary algorithms are tools that provide a suitable ground to determine the optimal PI gains. In this paper, a radial basis function (RBF) neural network based PI controller is proposed for collective pitch control (CPC) of a 5-MW wind turbine. In order to provide an optimal dataset to train the RBF neural network, particle swarm optimization (PSO) evolutionary algorithm is used. The proposed method does not need the complexities, nonlinearities and uncertainties of the system under control. The simulation results show that the proposed controller has satisfactory performance. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Precision Measurements of Wind Turbine Noise using a Large Aperture Microphone Array

    DEFF Research Database (Denmark)

    Bradley, Stuart; Mikkelsen, Torben Krogh; Hünerbein, Sabine Von

    2016-01-01

    Experiments are described with a large microphone array (40 m scale) recording wind turbine noise. The array comprised 42 purpose-designed low-noise microphones simultaneously sampled at 20 kHz. Very high quality, fast, meteorological profile data was available from nearby 80 m masts and from the...

  5. Short-term wind power prediction based on LSSVM–GSA model

    International Nuclear Information System (INIS)

    Yuan, Xiaohui; Chen, Chen; Yuan, Yanbin; Huang, Yuehua; Tan, Qingxiong

    2015-01-01

    Highlights: • A hybrid model is developed for short-term wind power prediction. • The model is based on LSSVM and gravitational search algorithm. • Gravitational search algorithm is used to optimize parameters of LSSVM. • Effect of different kernel function of LSSVM on wind power prediction is discussed. • Comparative studies show that prediction accuracy of wind power is improved. - Abstract: Wind power forecasting can improve the economical and technical integration of wind energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to forecast wind power accurately. For the purpose of utilizing wind power to the utmost extent, it is very important to make an accurate prediction of the output power of a wind farm under the premise of guaranteeing the security and the stability of the operation of the power system. In this paper, a hybrid model (LSSVM–GSA) based on the least squares support vector machine (LSSVM) and gravitational search algorithm (GSA) is proposed to forecast the short-term wind power. As the kernel function and the related parameters of the LSSVM have a great influence on the performance of the prediction model, the paper establishes LSSVM model based on different kernel functions for short-term wind power prediction. And then an optimal kernel function is determined and the parameters of the LSSVM model are optimized by using GSA. Compared with the Back Propagation (BP) neural network and support vector machine (SVM) model, the simulation results show that the hybrid LSSVM–GSA model based on exponential radial basis kernel function and GSA has higher accuracy for short-term wind power prediction. Therefore, the proposed LSSVM–GSA is a better model for short-term wind power prediction

  6. Statistical prediction of far-field wind-turbine noise, with probabilistic characterization of atmospheric stability

    DEFF Research Database (Denmark)

    Kelly, Mark C.; Barlas, Emre; Sogachev, Andrey

    2018-01-01

    Here we provide statistical low-order characterization of noise propagation from a single wind turbine, as affected by mutually interacting turbine wake and environmental conditions. This is accomplished via a probabilistic model, applied to an ensemble of atmospheric conditions based upon......; the latter solves Reynolds-Averaged Navier-Stokes equations of momentum and temperature, including the effects of stability and the ABL depth, along with the drag due to the wind turbine. Sound levels are found to be highest downwind for modestly stable conditions not atypical of mid-latitude climates...

  7. Experimental study of stochastic noise propagation in SPECT images reconstructed using the conjugate gradient algorithm.

    Science.gov (United States)

    Mariano-Goulart, D; Fourcade, M; Bernon, J L; Rossi, M; Zanca, M

    2003-01-01

    Thanks to an experimental study based on simulated and physical phantoms, the propagation of the stochastic noise in slices reconstructed using the conjugate gradient algorithm has been analysed versus iterations. After a first increase corresponding to the reconstruction of the signal, the noise stabilises before increasing linearly with iterations. The level of the plateau as well as the slope of the subsequent linear increase depends on the noise in the projection data.

  8. An Innovative Hybrid Model Based on Data Pre-Processing and Modified Optimization Algorithm and Its Application in Wind Speed Forecasting

    Directory of Open Access Journals (Sweden)

    Ping Jiang

    2017-07-01

    Full Text Available Wind speed forecasting has an unsuperseded function in the high-efficiency operation of wind farms, and is significant in wind-related engineering studies. Back-propagation (BP algorithms have been comprehensively employed to forecast time series that are nonlinear, irregular, and unstable. However, the single model usually overlooks the importance of data pre-processing and parameter optimization of the model, which results in weak forecasting performance. In this paper, a more precise and robust model that combines data pre-processing, BP neural network, and a modified artificial intelligence optimization algorithm was proposed, which succeeded in avoiding the limitations of the individual algorithm. The novel model not only improves the forecasting accuracy but also retains the advantages of the firefly algorithm (FA and overcomes the disadvantage of the FA while optimizing in the later stage. To verify the forecasting performance of the presented hybrid model, 10-min wind speed data from Penglai city, Shandong province, China, were analyzed in this study. The simulations revealed that the proposed hybrid model significantly outperforms other single metaheuristics.

  9. Wind power prediction based on genetic neural network

    Science.gov (United States)

    Zhang, Suhan

    2017-04-01

    The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

  10. An improved affine projection algorithm for active noise cancellation

    Science.gov (United States)

    Zhang, Congyan; Wang, Mingjiang; Han, Yufei; Sun, Yunzhuo

    2017-08-01

    Affine projection algorithm is a signal reuse algorithm, and it has a good convergence rate compared to other traditional adaptive filtering algorithm. There are two factors that affect the performance of the algorithm, which are step factor and the projection length. In the paper, we propose a new variable step size affine projection algorithm (VSS-APA). It dynamically changes the step size according to certain rules, so that it can get smaller steady-state error and faster convergence speed. Simulation results can prove that its performance is superior to the traditional affine projection algorithm and in the active noise control (ANC) applications, the new algorithm can get very good results.

  11. Assessment of the effects of noise and vibration from offshore wind farms on marine wildlife

    Energy Technology Data Exchange (ETDEWEB)

    Vella, G; Rushforth, I; Mason, E; Hough, A; England, R; Styles, P; Holt, T; Thorne, P

    2001-07-01

    This study involved a review of relevant studies and information on the effects of noise and vibration on marine wildlife from the construction and operation of offshore wind farms, and the identification of gaps and uncertainties in existing knowledge, recommendations for further studies to fill the gaps in knowledge, and the preparation of an inventory of planned and ongoing studies relating to the effects of offshore wind farms. The UK government's commitment to renewable energy, and the lifecycle of an offshore wind farm and potential locations are discussed. The mechanisms of noise propagation, physical noise and vibration, the use of sound by marine species such as whales and seals, the response of marine organisms to anthropogenic noise, and the colonisation of artificial reefs are examined. The behavioural response of seals and whales, the effects on fish population dynamics, and the need for further monitoring are considered.

  12. Assessment of the effects of noise and vibration from offshore wind farms on marine wildlife

    Energy Technology Data Exchange (ETDEWEB)

    Vella, G.; Rushforth, I.; Mason, E.; Hough, A.; England, R.; Styles, P.; Holt, T.; Thorne, P.

    2001-07-01

    This study involved a review of relevant studies and information on the effects of noise and vibration on marine wildlife from the construction and operation of offshore wind farms, and the identification of gaps and uncertainties in existing knowledge, recommendations for further studies to fill the gaps in knowledge, and the preparation of an inventory of planned and ongoing studies relating to the effects of offshore wind farms. The UK government's commitment to renewable energy, and the lifecycle of an offshore wind farm and potential locations are discussed. The mechanisms of noise propagation, physical noise and vibration, the use of sound by marine species such as whales and seals, the response of marine organisms to anthropogenic noise, and the colonisation of artificial reefs are examined. The behavioural response of seals and whales, the effects on fish population dynamics, and the need for further monitoring are considered.

  13. Speech Enhancement of Mobile Devices Based on the Integration of a Dual Microphone Array and a Background Noise Elimination Algorithm.

    Science.gov (United States)

    Chen, Yung-Yue

    2018-05-08

    Mobile devices are often used in our daily lives for the purposes of speech and communication. The speech quality of mobile devices is always degraded due to the environmental noises surrounding mobile device users. Regretfully, an effective background noise reduction solution cannot easily be developed for this speech enhancement problem. Due to these depicted reasons, a methodology is systematically proposed to eliminate the effects of background noises for the speech communication of mobile devices. This methodology integrates a dual microphone array with a background noise elimination algorithm. The proposed background noise elimination algorithm includes a whitening process, a speech modelling method and an H ₂ estimator. Due to the adoption of the dual microphone array, a low-cost design can be obtained for the speech enhancement of mobile devices. Practical tests have proven that this proposed method is immune to random background noises, and noiseless speech can be obtained after executing this denoise process.

  14. Speech Enhancement of Mobile Devices Based on the Integration of a Dual Microphone Array and a Background Noise Elimination Algorithm

    Directory of Open Access Journals (Sweden)

    Yung-Yue Chen

    2018-05-01

    Full Text Available Mobile devices are often used in our daily lives for the purposes of speech and communication. The speech quality of mobile devices is always degraded due to the environmental noises surrounding mobile device users. Regretfully, an effective background noise reduction solution cannot easily be developed for this speech enhancement problem. Due to these depicted reasons, a methodology is systematically proposed to eliminate the effects of background noises for the speech communication of mobile devices. This methodology integrates a dual microphone array with a background noise elimination algorithm. The proposed background noise elimination algorithm includes a whitening process, a speech modelling method and an H2 estimator. Due to the adoption of the dual microphone array, a low-cost design can be obtained for the speech enhancement of mobile devices. Practical tests have proven that this proposed method is immune to random background noises, and noiseless speech can be obtained after executing this denoise process.

  15. Location of aerodynamic noise sources from a 200 kW vertical-axis wind turbine

    Science.gov (United States)

    Ottermo, Fredric; Möllerström, Erik; Nordborg, Anders; Hylander, Jonny; Bernhoff, Hans

    2017-07-01

    Noise levels emitted from a 200 kW H-rotor vertical-axis wind turbine have been measured using a microphone array at four different positions, each at a hub-height distance from the tower. The microphone array, comprising 48 microphones in a spiral pattern, allows for directional mapping of the noise sources in the range of 500 Hz to 4 kHz. The produced images indicate that most of the noise is generated in a narrow azimuth-angle range, compatible with the location where increased turbulence is known to be present in the flow, as a result of the previous passage of a blade and its support arms. It is also shown that a semi-empirical model for inflow-turbulence noise seems to produce noise levels of the correct order of magnitude, based on the amount of turbulence that could be expected from power extraction considerations.

  16. A Hybrid Genetic Wind Driven Heuristic Optimization Algorithm for Demand Side Management in Smart Grid

    Directory of Open Access Journals (Sweden)

    Nadeem Javaid

    2017-03-01

    Full Text Available In recent years, demand side management (DSM techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks. In this paper, a heuristic algorithms-based energy management controller is designed for a residential area in a smart grid. In essence, five heuristic algorithms (the genetic algorithm (GA, the binary particle swarm optimization (BPSO algorithm, the bacterial foraging optimization algorithm (BFOA, the wind-driven optimization (WDO algorithm and our proposed hybrid genetic wind-driven (GWD algorithm are evaluated. These algorithms are used for scheduling residential loads between peak hours (PHs and off-peak hours (OPHs in a real-time pricing (RTP environment while maximizing user comfort (UC and minimizing both electricity cost and the peak to average ratio (PAR. Moreover, these algorithms are tested in two scenarios: (i scheduling the load of a single home and (ii scheduling the load of multiple homes. Simulation results show that our proposed hybrid GWD algorithm performs better than the other heuristic algorithms in terms of the selected performance metrics.

  17. Wind Turbine Acoustic Investigation: Infrasound and Low-Frequency Noise--A Case Study

    Science.gov (United States)

    Ambrose, Stephen E.; Rand, Robert W.; Krogh, Carmen M. E.

    2012-01-01

    Wind turbines produce sound that is capable of disturbing local residents and is reported to cause annoyance, sleep disturbance, and other health-related impacts. An acoustical study was conducted to investigate the presence of infrasonic and low-frequency noise emissions from wind turbines located in Falmouth, Massachusetts, USA. During the…

  18. Optimal design of minimum mean-square error noise reduction algorithms using the simulated annealing technique.

    Science.gov (United States)

    Bai, Mingsian R; Hsieh, Ping-Ju; Hur, Kur-Nan

    2009-02-01

    The performance of the minimum mean-square error noise reduction (MMSE-NR) algorithm in conjunction with time-recursive averaging (TRA) for noise estimation is found to be very sensitive to the choice of two recursion parameters. To address this problem in a more systematic manner, this paper proposes an optimization method to efficiently search the optimal parameters of the MMSE-TRA-NR algorithms. The objective function is based on a regression model, whereas the optimization process is carried out with the simulated annealing algorithm that is well suited for problems with many local optima. Another NR algorithm proposed in the paper employs linear prediction coding as a preprocessor for extracting the correlated portion of human speech. Objective and subjective tests were undertaken to compare the optimized MMSE-TRA-NR algorithm with several conventional NR algorithms. The results of subjective tests were processed by using analysis of variance to justify the statistic significance. A post hoc test, Tukey's Honestly Significant Difference, was conducted to further assess the pairwise difference between the NR algorithms.

  19. A Bi-Level Particle Swarm Optimization Algorithm for Solving Unit Commitment Problems with Wind-EVs Coordinated Dispatch

    Science.gov (United States)

    Song, Lei; Zhang, Bo

    2017-07-01

    Nowadays, the grid faces much more challenges caused by wind power and the accessing of electric vehicles (EVs). Based on the potentiality of coordinated dispatch, a model of wind-EVs coordinated dispatch was developed. Then, A bi-level particle swarm optimization algorithm for solving the model was proposed in this paper. The application of this algorithm to 10-unit test system carried out that coordinated dispatch can benefit the power system from the following aspects: (1) Reducing operating costs; (2) Improving the utilization of wind power; (3) Stabilizing the peak-valley difference.

  20. VIDEO DENOISING USING SWITCHING ADAPTIVE DECISION BASED ALGORITHM WITH ROBUST MOTION ESTIMATION TECHNIQUE

    Directory of Open Access Journals (Sweden)

    V. Jayaraj

    2010-08-01

    Full Text Available A Non-linear adaptive decision based algorithm with robust motion estimation technique is proposed for removal of impulse noise, Gaussian noise and mixed noise (impulse and Gaussian with edge and fine detail preservation in images and videos. The algorithm includes detection of corrupted pixels and the estimation of values for replacing the corrupted pixels. The main advantage of the proposed algorithm is that an appropriate filter is used for replacing the corrupted pixel based on the estimation of the noise variance present in the filtering window. This leads to reduced blurring and better fine detail preservation even at the high mixed noise density. It performs both spatial and temporal filtering for removal of the noises in the filter window of the videos. The Improved Cross Diamond Search Motion Estimation technique uses Least Median Square as a cost function, which shows improved performance than other motion estimation techniques with existing cost functions. The results show that the proposed algorithm outperforms the other algorithms in the visual point of view and in Peak Signal to Noise Ratio, Mean Square Error and Image Enhancement Factor.

  1. A homology sound-based algorithm for speech signal interference

    Science.gov (United States)

    Jiang, Yi-jiao; Chen, Hou-jin; Li, Ju-peng; Zhang, Zhan-song

    2015-12-01

    Aiming at secure analog speech communication, a homology sound-based algorithm for speech signal interference is proposed in this paper. We first split speech signal into phonetic fragments by a short-term energy method and establish an interference noise cache library with the phonetic fragments. Then we implement the homology sound interference by mixing the randomly selected interferential fragments and the original speech in real time. The computer simulation results indicated that the interference produced by this algorithm has advantages of real time, randomness, and high correlation with the original signal, comparing with the traditional noise interference methods such as white noise interference. After further studies, the proposed algorithm may be readily used in secure speech communication.

  2. An error reduction algorithm to improve lidar turbulence estimates for wind energy

    Directory of Open Access Journals (Sweden)

    J. F. Newman

    2017-02-01

    Full Text Available Remote-sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers for the measurement of wind speed and direction. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, vertically profiling lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry. In this work, a new turbulence error reduction algorithm for lidars is described. The Lidar Turbulence Error Reduction Algorithm, L-TERRA, can be applied using only data from a stand-alone vertically profiling lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of physics-based corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. The lessons learned from creating the L-TERRA model for a WINDCUBE v2 lidar can also be applied to other lidar devices. L-TERRA was tested on data from two sites in the Southern Plains region of the United States. The physics-based corrections in L-TERRA brought regression line slopes much closer to 1 at both sites and significantly reduced the sensitivity of lidar turbulence errors to atmospheric stability. The accuracy of machine

  3. Image de-noising based on mathematical morphology and multi-objective particle swarm optimization

    Science.gov (United States)

    Dou, Liyun; Xu, Dan; Chen, Hao; Liu, Yicheng

    2017-07-01

    To overcome the problem of image de-noising, an efficient image de-noising approach based on mathematical morphology and multi-objective particle swarm optimization (MOPSO) is proposed in this paper. Firstly, constructing a series and parallel compound morphology filter based on open-close (OC) operation and selecting a structural element with different sizes try best to eliminate all noise in a series link. Then, combining multi-objective particle swarm optimization (MOPSO) to solve the parameters setting of multiple structural element. Simulation result shows that our algorithm can achieve a superior performance compared with some traditional de-noising algorithm.

  4. A voting-based star identification algorithm utilizing local and global distribution

    Science.gov (United States)

    Fan, Qiaoyun; Zhong, Xuyang; Sun, Junhua

    2018-03-01

    A novel star identification algorithm based on voting scheme is presented in this paper. In the proposed algorithm, the global distribution and local distribution of sensor stars are fully utilized, and the stratified voting scheme is adopted to obtain the candidates for sensor stars. The database optimization is employed to reduce its memory requirement and improve the robustness of the proposed algorithm. The simulation shows that the proposed algorithm exhibits 99.81% identification rate with 2-pixel standard deviations of positional noises and 0.322-Mv magnitude noises. Compared with two similar algorithms, the proposed algorithm is more robust towards noise, and the average identification time and required memory is less. Furthermore, the real sky test shows that the proposed algorithm performs well on the real star images.

  5. Optimization of wind farm micro-siting for complex terrain using greedy algorithm

    International Nuclear Information System (INIS)

    Song, M.X.; Chen, K.; He, Z.Y.; Zhang, X.

    2014-01-01

    An optimization approach based on greedy algorithm for optimization of wind farm micro-siting is presented. The key of optimizing wind farm micro-siting is the fast and accurate evaluation of the wake flow interactions of wind turbines. The virtual particle model is employed for wake flow simulation of wind turbines, which makes the present method applicable for non-uniform flow fields on complex terrains. In previous bionic optimization method, within each step of the optimization process, only the power output of the turbine that is being located or relocated is considered. To aim at the overall power output of the wind farm comprehensively, a dependent region technique is introduced to improve the estimation of power output during the optimization procedure. With the technique, the wake flow influences can be reduced more efficiently during the optimization procedure. During the optimization process, the turbine that is being added will avoid being affected other turbines, and avoid affecting other turbine in the meantime. The results from the numerical calculations demonstrate that the present method is effective for wind farm micro-siting on complex terrain, and it produces better solutions in less time than the previous bionic method. - Highlights: • Greedy algorithm is applied to wind farm micro-siting problem. • The present method is effective for optimization on complex terrains. • Dependent region is suggested to improve the evaluation of wake influences. • The present method has better performance than the bionic method

  6. Optimal Allocation of Power-Electronic Interfaced Wind Turbines Using a Genetic Algorithm - Monte Carlo Hybrid Optimization Method

    DEFF Research Database (Denmark)

    Chen, Peiyuan; Siano, Pierluigi; Chen, Zhe

    2010-01-01

    determined by the wind resource and geographic conditions, the location of wind turbines in a power system network may significantly affect the distribution of power flow, power losses, etc. Furthermore, modern WTs with power-electronic interface have the capability of controlling reactive power output...... limit requirements. The method combines the Genetic Algorithm (GA), gradient-based constrained nonlinear optimization algorithm and sequential Monte Carlo simulation (MCS). The GA searches for the optimal locations and capacities of WTs. The gradient-based optimization finds the optimal power factor...... setting of WTs. The sequential MCS takes into account the stochastic behaviour of wind power generation and load. The proposed hybrid optimization method is demonstrated on an 11 kV 69-bus distribution system....

  7. ARIMA-Based Time Series Model of Stochastic Wind Power Generation

    DEFF Research Database (Denmark)

    Chen, Peiyuan; Pedersen, Troels; Bak-Jensen, Birgitte

    2010-01-01

    This paper proposes a stochastic wind power model based on an autoregressive integrated moving average (ARIMA) process. The model takes into account the nonstationarity and physical limits of stochastic wind power generation. The model is constructed based on wind power measurement of one year from...... the Nysted offshore wind farm in Denmark. The proposed limited-ARIMA (LARIMA) model introduces a limiter and characterizes the stochastic wind power generation by mean level, temporal correlation and driving noise. The model is validated against the measurement in terms of temporal correlation...... and probability distribution. The LARIMA model outperforms a first-order transition matrix based discrete Markov model in terms of temporal correlation, probability distribution and model parameter number. The proposed LARIMA model is further extended to include the monthly variation of the stochastic wind power...

  8. Virtual Reality Platform Based Simulation System of Environmental Noise Abatement Research

    Science.gov (United States)

    Yijun, Liu; Yu, Fang; Xiaoman, He; Yongyou, Wang

    The general mathematic mode of computing noise abatement is commonly used for most project planning and appraisal of environmental noise abatement projects. However, the inconvenient and impracticable mode and algorithm usually cannot meet the real world computation and testing. Therefore, a more practicable abatement mode and algorithm (multiple noise sources with multiband under sound barriers) which had been applied to VR based simulation system. That implemented the function of real-time demonstrating noise scattering condition within 3D virtual space, furthermore, with sound barriers added in 3D scene, the effectiveness of denoise by sound barriers also can be demonstrated within this system. That provides a significant solution for environmental noise abatement projects as a whole.

  9. Application of a ray theory model to the prediction of noise emissions from isolated wind turbines and wind parks

    International Nuclear Information System (INIS)

    Prospathopoulos, John M.; Voutsinas, Spyros G.

    2006-01-01

    Various propagation models have been developed to estimate the level of noise near residential areas. Predictions and measurements have proven that proper modelling of the propagation medium is of particular importance. In the present work, calculations are performed using a ray theory methodology. The ray trajectory and transport equations are derived from the linear acoustics equations for a moving medium in three dimensions. Ground and atmospheric absorption, wave refraction and diffraction and atmospheric turbulence are taken into account by introducing appropriate coefficients in the equations. In the case of a wind turbine (W/T) it is assumed that noise is produced by a point source located at the rotor centre. Given the sound power spectrum, the noise spectrum at the receiver is obtained by solving the axisymmetric propagation problem. The procedure consists of (a) finding the eigenrays, (b) calculating the energy losses along the eigenrays and (c) synthesizing the sound pressure level (SPL) by superposing the contributions of the eigenrays. In the case of a wind park the total SPL is calculated by superposing the contributions of all W/Ts. Application is made to five cases of isolated W/Ts in terrains of varying complexity. In flat or even smooth terrain the predictions agree well with the measurements. In complex terrain the predictions can be considered satisfactory, taking into account the assumption of constant wind velocity profile. Application to a wind park shows clearly the influence of the terrain on the wind velocity and consequently on the SPL. (Author)

  10. Wind Speed Forecasting Based on FEEMD and LSSVM Optimized by the Bat Algorithm

    Directory of Open Access Journals (Sweden)

    Wei Sun

    2015-06-01

    Full Text Available Affected by various environmental factors, wind speed presents high fluctuation, nonlinear and non-stationary characteristics. To evaluate wind energy properly and efficiently, this paper proposes a modified fast ensemble empirical model decomposition (FEEMD-bat algorithm (BA-least support vector machines (LSSVM (FEEMD-BA-LSSVM model combined with input selected by deep quantitative analysis. The original wind speed series are first decomposed into a limited number of intrinsic mode functions (IMFs with one residual series. Then a LSSVM is built to forecast these sub-series. In order to select input from environment variables, Cointegration and Granger causality tests are proposed to check the influence of temperature with different leading lengths. Partial correlation is applied to analyze the inner relationships between the historical speeds thus to select the LSSVM input. The parameters in LSSVM are fine-tuned by BA to ensure the generalization of LSSVM. The forecasting results suggest the hybrid approach outperforms the compared models.

  11. An improved algorithm of laser spot center detection in strong noise background

    Science.gov (United States)

    Zhang, Le; Wang, Qianqian; Cui, Xutai; Zhao, Yu; Peng, Zhong

    2018-01-01

    Laser spot center detection is demanded in many applications. The common algorithms for laser spot center detection such as centroid and Hough transform method have poor anti-interference ability and low detection accuracy in the condition of strong background noise. In this paper, firstly, the median filtering was used to remove the noise while preserving the edge details of the image. Secondly, the binarization of the laser facula image was carried out to extract target image from background. Then the morphological filtering was performed to eliminate the noise points inside and outside the spot. At last, the edge of pretreated facula image was extracted and the laser spot center was obtained by using the circle fitting method. In the foundation of the circle fitting algorithm, the improved algorithm added median filtering, morphological filtering and other processing methods. This method could effectively filter background noise through theoretical analysis and experimental verification, which enhanced the anti-interference ability of laser spot center detection and also improved the detection accuracy.

  12. Cross-Cutting Activities 2016 on Wind Turbine Noise, Summary Report

    DEFF Research Database (Denmark)

    Bertagnolio, Franck; Aagaard Madsen, Helge; Fischer, Andreas

    2017-01-01

    The goal of this report is to summarize activities that took place in year 2016 as part of the Cross-Cutting Activity on Wind Turbine Noise, self-financed by DTU Wind Energy. A short description of the background behind this project (in particular Cross-Cutting Activities conducted in year 2015......), the main objectives of the various studies and scientific achievements are reported in the introduction. Then, each Work Packages constituting this project are described in more details in the following sections....

  13. Separation of pulsar signals from noise using supervised machine learning algorithms

    Science.gov (United States)

    Bethapudi, S.; Desai, S.

    2018-04-01

    We evaluate the performance of four different machine learning (ML) algorithms: an Artificial Neural Network Multi-Layer Perceptron (ANN MLP), Adaboost, Gradient Boosting Classifier (GBC), and XGBoost, for the separation of pulsars from radio frequency interference (RFI) and other sources of noise, using a dataset obtained from the post-processing of a pulsar search pipeline. This dataset was previously used for the cross-validation of the SPINN-based machine learning engine, obtained from the reprocessing of the HTRU-S survey data (Morello et al., 2014). We have used the Synthetic Minority Over-sampling Technique (SMOTE) to deal with high-class imbalance in the dataset. We report a variety of quality scores from all four of these algorithms on both the non-SMOTE and SMOTE datasets. For all the above ML methods, we report high accuracy and G-mean for both the non-SMOTE and SMOTE cases. We study the feature importances using Adaboost, GBC, and XGBoost and also from the minimum Redundancy Maximum Relevance approach to report algorithm-agnostic feature ranking. From these methods, we find that the signal to noise of the folded profile to be the best feature. We find that all the ML algorithms report FPRs about an order of magnitude lower than the corresponding FPRs obtained in Morello et al. (2014), for the same recall value.

  14. Multiscale KF Algorithm for Strong Fractional Noise Interference Suppression in Discrete-Time UWB Systems

    Directory of Open Access Journals (Sweden)

    Liyun Su

    2011-01-01

    Full Text Available In order to suppress the interference of the strong fractional noise signal in discrete-time ultrawideband (UWB systems, this paper presents a new UWB multi-scale Kalman filter (KF algorithm for the interference suppression. This approach solves the problem of the narrowband interference (NBI as nonstationary fractional signal in UWB communication, which does not need to estimate any channel parameter. In this paper, the received sampled signal is transformed through multiscale wavelet to obtain a state transition equation and an observation equation based on the stationarity theory of wavelet coefficients in time domain. Then through the Kalman filter method, fractional signal of arbitrary scale is easily figured out. Finally, fractional noise interference is subtracted from the received signal. Performance analysis and computer simulations reveal that this algorithm is effective to reduce the strong fractional noise when the sampling rate is low.

  15. Fatigue Load Sensitivity Based Optimal Active Power Dispatch For Wind Farms

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Huang, Shaojun

    2017-01-01

    This paper proposes an optimal active power dispatch algorithm for wind farms based on Wind Turbine (WT) load sensitivity. The control objectives include tracking power references from the system operator and minimizing fatigue loads experienced by WTs. The sensitivity of WT fatigue loads to power...... sensitivity are derived, which significantly improves the computation efficiency of the local WT controller. The proposed algorithm can be implemented in different active power control schemes. Case studies were conducted with a wind farm under balance control for both low and high wind conditions...

  16. A new edge detection algorithm based on Canny idea

    Science.gov (United States)

    Feng, Yingke; Zhang, Jinmin; Wang, Siming

    2017-10-01

    The traditional Canny algorithm has poor self-adaptability threshold, and it is more sensitive to noise. In order to overcome these drawbacks, this paper proposed a new edge detection method based on Canny algorithm. Firstly, the media filtering and filtering based on the method of Euclidean distance are adopted to process it; secondly using the Frei-chen algorithm to calculate gradient amplitude; finally, using the Otsu algorithm to calculate partial gradient amplitude operation to get images of thresholds value, then find the average of all thresholds that had been calculated, half of the average is high threshold value, and the half of the high threshold value is low threshold value. Experiment results show that this new method can effectively suppress noise disturbance, keep the edge information, and also improve the edge detection accuracy.

  17. The Noise Clinic: a Blind Image Denoising Algorithm

    Directory of Open Access Journals (Sweden)

    Marc Lebrun

    2015-01-01

    Full Text Available This paper describes the complete implementation of a blind image algorithm, that takes any digital image as input. In a first step the algorithm estimates a Signal and Frequency Dependent (SFD noise model. In a second step, the image is denoised by a multiscale adaptation of the Non-local Bayes denoising method. We focus here on a careful analysis of the denoising step and present a detailed discussion of the influence of its parameters. Extensive commented tests of the blind denoising algorithm are presented, on real JPEG images and scans of old photographs.

  18. A methodology for assessment of wind turbine noise generation

    Science.gov (United States)

    Kelley, N. D.; Hemphill, R. R.; McKenna, H. E.

    1982-05-01

    An investigation of the sources of impulsive noise generated by the operation of the Mod 1 2 MW wind turbine was performed to establish criteria for assessing the noise-producing potential of other large wind turbines. Unsteady loading of the rotors was determined to be the cause of the sound pressure, which was generally below 100 Hz. Complaints originated from people in dwellings with a room with a window facing the machine. Indoor monitoring revealed pressure traces in the 31.5 Hz band with energy densities exceeding background by about 30 dB. It was concluded that the sound pressure was conveyed by the walls acting as a diaphragm. The induced vibration coupled with human body fundamental modes to produce a feeling of whole-body vibration. Spectral analyses were made of the vibration fields of the Mod 2, a 17 m Darrieus, and a Mod OA to allow comparison with the nuisance points of the Mod 1. Sound pressure levels were found at certain frequencies which would eliminate the occurrence of acoustic pollution.

  19. A Simple Sizing Algorithm for Stand-Alone PV/Wind/Battery Hybrid Microgrids

    Directory of Open Access Journals (Sweden)

    Jing Li

    2012-12-01

    Full Text Available In this paper, we develop a simple algorithm to determine the required number of generating units of wind-turbine generator and photovoltaic array, and the associated storage capacity for stand-alone hybrid microgrid. The algorithm is based on the observation that the state of charge of battery should be periodically invariant. The optimal sizing of hybrid microgrid is given in the sense that the life cycle cost of system is minimized while the given load power demand can be satisfied without load rejection. We also report a case study to show the efficacy of the developed algorithm.

  20. Detection algorithm of infrared small target based on improved SUSAN operator

    Science.gov (United States)

    Liu, Xingmiao; Wang, Shicheng; Zhao, Jing

    2010-10-01

    The methods of detecting small moving targets in infrared image sequences that contain moving nuisance objects and background noise is analyzed in this paper. A novel infrared small target detection algorithm based on improved SUSAN operator is put forward. The algorithm selects double templates for the infrared small target detection: one size is greater than the small target point size and another size is equal to the small target point size. First, the algorithm uses the big template to calculate the USAN of each pixel in the image and detect the small target, the edge of the image and isolated noise pixels; Then the algorithm uses the another template to calculate the USAN of pixels detected in the first step and improves the principles of SUSAN algorithm based on the characteristics of the small target so that the algorithm can only detect small targets and don't sensitive to the edge pixels of the image and isolated noise pixels. So the interference of the edge of the image and isolate noise points are removed and the candidate target points can be identified; At last, the target is detected by utilizing the continuity and consistency of target movement. The experimental results indicate that the improved SUSAN detection algorithm can quickly and effectively detect the infrared small targets.

  1. Review of control algorithms for offshore wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Spruce, C J; Markou, H; Leithead, W E; Dominguez Ruiz, S

    2005-07-01

    Innovative turbine control strategies could allow the improvements to cost and performance considered essential to reduce the cost of energy from offshore wind farms around the UK. This project reviewed and investigated the possibility for further development of a power control algorithm originally developed by NEG Micon Rotors Ltd for use with offshore wind turbines in the hope that more advanced algorithms would reduce the loads on, and hence the costs of, components such as the foundation/support structure, tower, blades and bedplate. Three models (simulation model, linearisation of the simulation model and control model) were produced in order to conduct the review. Application of these models produced the conclusion that the size of the latest generation of offshore wind turbines has now reached a level where performance is starting to be constrained by fundamental factors in the dynamics caused by the machine's physical size. It was also concluded that an ideal control strategy could achieve potential cost savings for the tower and support structure of 5-10% of the total cost of the turbine plus support structure. Further work to develop controllers to reduce loads in the tower and support structure is urged. The report considers non-linear simulation, the linear model, the control model, general operation of the controller, the drive train damping filter, torque control, pitch control and advanced algorithms, and makes detailed recommendations for future work.

  2. Robustness of SOC Estimation Algorithms for EV Lithium-Ion Batteries against Modeling Errors and Measurement Noise

    Directory of Open Access Journals (Sweden)

    Xue Li

    2015-01-01

    Full Text Available State of charge (SOC is one of the most important parameters in battery management system (BMS. There are numerous algorithms for SOC estimation, mostly of model-based observer/filter types such as Kalman filters, closed-loop observers, and robust observers. Modeling errors and measurement noises have critical impact on accuracy of SOC estimation in these algorithms. This paper is a comparative study of robustness of SOC estimation algorithms against modeling errors and measurement noises. By using a typical battery platform for vehicle applications with sensor noise and battery aging characterization, three popular and representative SOC estimation methods (extended Kalman filter, PI-controlled observer, and H∞ observer are compared on such robustness. The simulation and experimental results demonstrate that deterioration of SOC estimation accuracy under modeling errors resulted from aging and larger measurement noise, which is quantitatively characterized. The findings of this paper provide useful information on the following aspects: (1 how SOC estimation accuracy depends on modeling reliability and voltage measurement accuracy; (2 pros and cons of typical SOC estimators in their robustness and reliability; (3 guidelines for requirements on battery system identification and sensor selections.

  3. Four wind speed multi-step forecasting models using extreme learning machines and signal decomposing algorithms

    International Nuclear Information System (INIS)

    Liu, Hui; Tian, Hong-qi; Li, Yan-fei

    2015-01-01

    Highlights: • A hybrid architecture is proposed for the wind speed forecasting. • Four algorithms are used for the wind speed multi-scale decomposition. • The extreme learning machines are employed for the wind speed forecasting. • All the proposed hybrid models can generate the accurate results. - Abstract: Realization of accurate wind speed forecasting is important to guarantee the safety of wind power utilization. In this paper, a new hybrid forecasting architecture is proposed to realize the wind speed accurate forecasting. In this architecture, four different hybrid models are presented by combining four signal decomposing algorithms (e.g., Wavelet Decomposition/Wavelet Packet Decomposition/Empirical Mode Decomposition/Fast Ensemble Empirical Mode Decomposition) and Extreme Learning Machines. The originality of the study is to investigate the promoted percentages of the Extreme Learning Machines by those mainstream signal decomposing algorithms in the multiple step wind speed forecasting. The results of two forecasting experiments indicate that: (1) the method of Extreme Learning Machines is suitable for the wind speed forecasting; (2) by utilizing the decomposing algorithms, all the proposed hybrid algorithms have better performance than the single Extreme Learning Machines; (3) in the comparisons of the decomposing algorithms in the proposed hybrid architecture, the Fast Ensemble Empirical Mode Decomposition has the best performance in the three-step forecasting results while the Wavelet Packet Decomposition has the best performance in the one and two step forecasting results. At the same time, the Wavelet Packet Decomposition and the Fast Ensemble Empirical Mode Decomposition are better than the Wavelet Decomposition and the Empirical Mode Decomposition in all the step predictions, respectively; and (4) the proposed algorithms are effective in the wind speed accurate predictions

  4. Connection between wind turbine noise and health effects. Prepared for the National Board of Health, Denmark; Sammenhaeng mellem vindmoellestoej og helbredseffekter. Udfoert for Sundhedsstyrelsen

    Energy Technology Data Exchange (ETDEWEB)

    Holm Pedersen, T.

    2011-03-15

    The purpose of this report is, through a limited literature study, to elucidate the direct and probable indirect health effects due to wind turbine noise / vibrations / shadow effect. It is shown that the wind turbine noise's character is not substantially different from many other sources of noise in our daily lives. The sound levels are rather low, seen in relation to the sound impacts that we normally are exposed to, and that also includes low-frequency noise. Audible infrasound does not occur. Noise annoyance is the most significant effect of noise from wind turbines. The noise annoyance from wind turbines is greater than from road traffic at the same level of noise. At the noise limit of 39 dB for noise-sensitive land use one must expect that for wind turbines about 10% is highly annoying. Sleep disorders can occur. There is a sharp increase in the percentage of sleep disorders just above the noise limits. There was not found a direct correlation between stress and noise. By contrast, significant correlations between stress symptoms and noise nuisance are found. Existing studies show no significant correlations to chronic diseases, diabetes, high blood pressure and cardiovascular diseases. The literature reports on phenomenon called vibro-acoustic diseases and wind turbine syndrome, without, however, a proven causal dose-response relationship or without conducted studies where it is compared to control groups. These phenomena are not considered real for wind turbines. On the present basis, there are no demonstrated direct health effects due to wind turbine noise, though there are observed correlation between noise and stress symptoms Shadows from the rotating blades are annoying, but cannot induce epileptic attacks. (LN)

  5. Connection between wind turbine noise and health effects. Prepared for the National Board of Health, Denmark; Sammenhaeng mellem vindmoellestoej og helbredseffekter. Udfoert for Sundhedsstyrelsen

    Energy Technology Data Exchange (ETDEWEB)

    Holm Pedersen, T

    2011-03-15

    The purpose of this report is, through a limited literature study, to elucidate the direct and probable indirect health effects due to wind turbine noise / vibrations / shadow effect. It is shown that the wind turbine noise's character is not substantially different from many other sources of noise in our daily lives. The sound levels are rather low, seen in relation to the sound impacts that we normally are exposed to, and that also includes low-frequency noise. Audible infrasound does not occur. Noise annoyance is the most significant effect of noise from wind turbines. The noise annoyance from wind turbines is greater than from road traffic at the same level of noise. At the noise limit of 39 dB for noise-sensitive land use one must expect that for wind turbines about 10% is highly annoying. Sleep disorders can occur. There is a sharp increase in the percentage of sleep disorders just above the noise limits. There was not found a direct correlation between stress and noise. By contrast, significant correlations between stress symptoms and noise nuisance are found. Existing studies show no significant correlations to chronic diseases, diabetes, high blood pressure and cardiovascular diseases. The literature reports on phenomenon called vibro-acoustic diseases and wind turbine syndrome, without, however, a proven causal dose-response relationship or without conducted studies where it is compared to control groups. These phenomena are not considered real for wind turbines. On the present basis, there are no demonstrated direct health effects due to wind turbine noise, though there are observed correlation between noise and stress symptoms Shadows from the rotating blades are annoying, but cannot induce epileptic attacks. (LN)

  6. Random noise suppression of seismic data using non-local Bayes algorithm

    Science.gov (United States)

    Chang, De-Kuan; Yang, Wu-Yang; Wang, Yi-Hui; Yang, Qing; Wei, Xin-Jian; Feng, Xiao-Ying

    2018-02-01

    For random noise suppression of seismic data, we present a non-local Bayes (NL-Bayes) filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.

  7. Acoustic noise measurements on a wind turbine performed in the frame of the NIWT round robin

    International Nuclear Information System (INIS)

    Van der Borg, N.J.C.M.; Vink, P.W.

    1996-11-01

    A round robin acoustic measurement campaign has been performed by five project partners using one and the same wind turbine (WT). The measurement procedure for the round robin exercise was agreed to be in compliance with the IEA-recommended practices on WT-noise emission measurements and the measured characteristics were agreed to be the apparent sound power level and the tonality, both measured at the reference measurement position. The measurements performed by ECN resulted in an A-weighted sound power level of the TACKE TW500/37 wind turbine in Hooksiel, Germany, of 95.8 dB(A) at a wind speed of 5.5 m/s at reference conditions. The tonality assessment of the sound pressure at 50 m down wind of the turbine resulted in a difference between the maximum tone level and the masking noise level of 2.4 dB. This characterizes the noise as 'prominent'. 2 refs

  8. Effects of directional microphone and adaptive multichannel noise reduction algorithm on cochlear implant performance.

    Science.gov (United States)

    Chung, King; Zeng, Fan-Gang; Acker, Kyle N

    2006-10-01

    Although cochlear implant (CI) users have enjoyed good speech recognition in quiet, they still have difficulties understanding speech in noise. We conducted three experiments to determine whether a directional microphone and an adaptive multichannel noise reduction algorithm could enhance CI performance in noise and whether Speech Transmission Index (STI) can be used to predict CI performance in various acoustic and signal processing conditions. In Experiment I, CI users listened to speech in noise processed by 4 hearing aid settings: omni-directional microphone, omni-directional microphone plus noise reduction, directional microphone, and directional microphone plus noise reduction. The directional microphone significantly improved speech recognition in noise. Both directional microphone and noise reduction algorithm improved overall preference. In Experiment II, normal hearing individuals listened to the recorded speech produced by 4- or 8-channel CI simulations. The 8-channel simulation yielded similar speech recognition results as in Experiment I, whereas the 4-channel simulation produced no significant difference among the 4 settings. In Experiment III, we examined the relationship between STIs and speech recognition. The results suggested that STI could predict actual and simulated CI speech intelligibility with acoustic degradation and the directional microphone, but not the noise reduction algorithm. Implications for intelligibility enhancement are discussed.

  9. Cost-Effective Shaft Torque Observer for Condition Monitoring of Wind Turbines

    DEFF Research Database (Denmark)

    Perisic, Nevena; Kirkegaard, Poul Henning; Pedersen, Bo Juul

    2015-01-01

    Improvement of condition monitoring (CM) systems for wind turbines (WTs) and reduction of the cost of wind energy are possible if knowledge about the condition of different WT components is available. CM based on the WT drive train shaft torque signal can give a better understanding of the gearbox...... of the augmented Kalman filter with fading memory (AKFF) is compared with the augmented Kalman filter (AKF) using simulated data of theWT for different load conditions, measurement noise levels andWT fault scenarios. A multiple-model algorithm, based on a set of different Kalman filters, is designed for practical...

  10. High reliability - low noise radionuclide signature identification algorithms for border security applications

    Science.gov (United States)

    Lee, Sangkyu

    Illicit trafficking and smuggling of radioactive materials and special nuclear materials (SNM) are considered as one of the most important recent global nuclear threats. Monitoring the transport and safety of radioisotopes and SNM are challenging due to their weak signals and easy shielding. Great efforts worldwide are focused at developing and improving the detection technologies and algorithms, for accurate and reliable detection of radioisotopes of interest in thus better securing the borders against nuclear threats. In general, radiation portal monitors enable detection of gamma and neutron emitting radioisotopes. Passive or active interrogation techniques, present and/or under the development, are all aimed at increasing accuracy, reliability, and in shortening the time of interrogation as well as the cost of the equipment. Equally important efforts are aimed at advancing algorithms to process the imaging data in an efficient manner providing reliable "readings" of the interiors of the examined volumes of various sizes, ranging from cargos to suitcases. The main objective of this thesis is to develop two synergistic algorithms with the goal to provide highly reliable - low noise identification of radioisotope signatures. These algorithms combine analysis of passive radioactive detection technique with active interrogation imaging techniques such as gamma radiography or muon tomography. One algorithm consists of gamma spectroscopy and cosmic muon tomography, and the other algorithm is based on gamma spectroscopy and gamma radiography. The purpose of fusing two detection methodologies per algorithm is to find both heavy-Z radioisotopes and shielding materials, since radionuclides can be identified with gamma spectroscopy, and shielding materials can be detected using muon tomography or gamma radiography. These combined algorithms are created and analyzed based on numerically generated images of various cargo sizes and materials. In summary, the three detection

  11. The effect of wind turbine noise on sleep and quality of life: A systematic review and meta-analysis of observational studies.

    Science.gov (United States)

    Onakpoya, Igho J; O'Sullivan, Jack; Thompson, Matthew J; Heneghan, Carl J

    2015-09-01

    Noise generated by wind turbines has been reported to affect sleep and quality of life (QOL), but the relationship is unclear. Our objective was to explore the association between wind turbine noise, sleep disturbance and quality of life, using data from published observational studies. We searched Medline, Embase, Global Health and Google Scholar databases. No language restrictions were imposed. Hand searches of bibliography of retrieved full texts were also conducted. The reporting quality of included studies was assessed using the STROBE guidelines. Two reviewers independently determined the eligibility of studies, assessed the quality of included studies, and extracted the data. We included eight studies with a total of 2433 participants. All studies were cross-sectional, and the overall reporting quality was moderate. Meta-analysis of six studies (n=2364) revealed that the odds of being annoyed is significantly increased by wind turbine noise (OR: 4.08; 95% CI: 2.37 to 7.04; pwind turbine noise (OR: 2.94; 95% CI: 1.98 to 4.37; pwind turbine noise significantly interfered with QOL. Further, visual perception of wind turbine generators was associated with greater frequency of reported negative health effects. In conclusion, there is some evidence that exposure to wind turbine noise is associated with increased odds of annoyance and sleep problems. Individual attitudes could influence the type of response to noise from wind turbines. Experimental and observational studies investigating the relationship between wind turbine noise and health are warranted. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. The statistical prediction of offshore winds from land-based data for wind-energy applications

    DEFF Research Database (Denmark)

    Walmsley, J.L.; Barthelmie, R.J.; Burrows, W.R.

    2001-01-01

    Land-based meteorological measurements at two locations on the Danish coast are used to predict offshore wind speeds. Offshore wind-speed data are used only for developing the statistical prediction algorithms and for verification. As a first step, the two datasets were separated into nine...... percentile-based bins, with a minimum of 30 data records in each bin. Next, the records were randomly selected with approximately 70% of the data in each bin being used as a training set for development of the prediction algorithms, and the remaining 30% being reserved as a test set for evaluation purposes....... The binning procedure ensured that both training and test sets fairly represented the overall data distribution. To base the conclusions on firmer ground, five permutations of these training and test sets were created. Thus, all calculations were based on five cases, each one representing a different random...

  13. An environment-adaptive management algorithm for hearing-support devices incorporating listening situation and noise type classifiers.

    Science.gov (United States)

    Yook, Sunhyun; Nam, Kyoung Won; Kim, Heepyung; Hong, Sung Hwa; Jang, Dong Pyo; Kim, In Young

    2015-04-01

    In order to provide more consistent sound intelligibility for the hearing-impaired person, regardless of environment, it is necessary to adjust the setting of the hearing-support (HS) device to accommodate various environmental circumstances. In this study, a fully automatic HS device management algorithm that can adapt to various environmental situations is proposed; it is composed of a listening-situation classifier, a noise-type classifier, an adaptive noise-reduction algorithm, and a management algorithm that can selectively turn on/off one or more of the three basic algorithms-beamforming, noise-reduction, and feedback cancellation-and can also adjust internal gains and parameters of the wide-dynamic-range compression (WDRC) and noise-reduction (NR) algorithms in accordance with variations in environmental situations. Experimental results demonstrated that the implemented algorithms can classify both listening situation and ambient noise type situations with high accuracies (92.8-96.4% and 90.9-99.4%, respectively), and the gains and parameters of the WDRC and NR algorithms were successfully adjusted according to variations in environmental situation. The average values of signal-to-noise ratio (SNR), frequency-weighted segmental SNR, Perceptual Evaluation of Speech Quality, and mean opinion test scores of 10 normal-hearing volunteers of the adaptive multiband spectral subtraction (MBSS) algorithm were improved by 1.74 dB, 2.11 dB, 0.49, and 0.68, respectively, compared to the conventional fixed-parameter MBSS algorithm. These results indicate that the proposed environment-adaptive management algorithm can be applied to HS devices to improve sound intelligibility for hearing-impaired individuals in various acoustic environments. Copyright © 2014 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  14. Wind turbine pitch control using ICPSO-PID algorithm

    DEFF Research Database (Denmark)

    Xu, Chang; Tian, Qiangqiang; Shen, Wen Zhong

    2013-01-01

    For the traditional simplified first-order pitch-control system model, it is difficult to describe a real dynamic characteristic of a variable pitch action system, thus a complete high order mathematical model has to be developed for the pitch control of wind turbine generation (WTG). In the paper...... controller parameters quickly; and the feed-forward controller for wind speed can improve dynamics of a pitch-control system; additionally the power controller can allow a wind turbine to have a constant power output as a wind speed is over the rated one. Compared with a conventional PID, the controller...... with ICPSO-PID algorithm has a smaller overshoot, a shorter tuning time and better robustness. The design method proposed in the paper can be applied in a practical electro-hydraulic pitch control system for WTG....

  15. Optimization of Wind-Marine Hybrid Power System Configuration Based on Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    SHI Hongda; LI Linna; ZHAO Chenyu

    2017-01-01

    Multi-energy power systems can use energy generated from various sources to improve power generation reliability.This paper presents a cost-power generation model of a wind-tide-wave energy hybrid power system for use on a remote island,where the configuration is optimized using a genetic algorithm.A mixed integer programming model is used and a novel object function,including cost and power generation,is proposed to solve the boundary problem caused by existence of two goals.Using this model,the final optimized result is found to have a good fit with local resources.

  16. Review of control algorithms for offshore wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Spruce, C.J.; Markou, H.; Leithead, W.E.; Dominguez Ruiz, S.

    2005-07-01

    Innovative turbine control strategies could allow the improvements to cost and performance considered essential to reduce the cost of energy from offshore wind farms around the UK. This project reviewed and investigated the possibility for further development of a power control algorithm originally developed by NEG Micon Rotors Ltd for use with offshore wind turbines in the hope that more advanced algorithms would reduce the loads on, and hence the costs of, components such as the foundation/support structure, tower, blades and bedplate. Three models (simulation model, linearisation of the simulation model and control model) were produced in order to conduct the review. Application of these models produced the conclusion that the size of the latest generation of offshore wind turbines has now reached a level where performance is starting to be constrained by fundamental factors in the dynamics caused by the machine's physical size. It was also concluded that an ideal control strategy could achieve potential cost savings for the tower and support structure of 5-10% of the total cost of the turbine plus support structure. Further work to develop controllers to reduce loads in the tower and support structure is urged. The report considers non-linear simulation, the linear model, the control model, general operation of the controller, the drive train damping filter, torque control, pitch control and advanced algorithms, and makes detailed recommendations for future work.

  17. Wind seismic noise introduced by external infrastructure: field data and transfer mechanism

    Science.gov (United States)

    Martysevich, Pavel; Starovoyt, Yuri

    2017-04-01

    Background seismic noise generated by wind was analyzed at six co-located seismic and infrasound arrays with the use of the wind speed data. The main factors affecting the noise level were identified as (a) external structures as antenna towers for intrasite communication, vegetation and heavy solar panels fixtures, (b) borehole casing and (c) local lithology. The wind-induced seismic noise peaks in the spectra can be predicted by combination of inverted pendulum model for antenna towers and structures used to support solar panels, free- or clamped-tube resonance of the borehole casing and is dependent on the type of sedimentary upper layer. Observed resonance frequencies are in agreement with calculated clamped / free tube modes for towers and borehole casings. Improvement of the seismic data quality can be achieved by minimizing the impact of surrounding structures close to seismic boreholes. The need and the advantage of the borehole installation may vanish and appear to be even not necessary at locations with non-consolidated sediments because the impact of surrounding structures on seismic background may significantly deteriorate the installation quality and therefore the detection capability of the array. Several IMS arrays where the radio telemetry antennas are used for data delivery to the central site may benefit from the redesign of the intrasite communication system by its substitute with the fiber-optic net as less harmful engineering solution.

  18. Study of Noise Canceling Performance of Feedforward Fuzzy-Based ANC System under Non-Causal Condition

    DEFF Research Database (Denmark)

    Mojallali, Hamed; Izadi-Zamanabadi, Roozbeh; Amini, Rouzbeh

    of noise canceling performance of feed-forward fuzzy-based ANC systems for ducts under non-causal condition is presented. For this purpose, we use fuzzy filtered-x algorithm as an adaptive filter and the results are compared with classical filteredx algorithm which is employed under the same conditions......Feed-forward active noise control (ANC) systems act as adaptive systems to control and cancel undesired signals and noises. If the delay in the noise canceling subsystems increases more than the delays in the primary path, non-causal condition will occur in these systems. In this paper, study....... Analysis shows that ANC systems using fuzzy algorithm has better efficiency for noise cancellation in non-causal condition....

  19. A new IEA document for the measurement of noise immission from wind turbines at receptor locations

    International Nuclear Information System (INIS)

    Ljunggren, Sten

    1999-01-01

    A new IEA guide on acoustic noise was recently completed by an international expert group. In this guide, several practical and reliable methods for determining wind turbine noise immission at receptor locations are presented: three methods for equivalent continuous A-weighted sound pressure levels and one method for A-weighted percentiles. In the most ambitious method for equivalent sound levels, the noise is measured together with the wind speed at two locations: one at the microphone and the other at the turbine site. With this approach, the turbine levels can be corrected for background sound and the immission level can be determined at a certain target speed. Special importance is attached to the problem of correcting for background noise and to techniques for improving the signal-to-noise ratio. Thus, six methods are described which can be used in difficult situations

  20. Comparison of SeaWinds Backscatter Imaging Algorithms

    Science.gov (United States)

    Long, David G.

    2017-01-01

    This paper compares the performance and tradeoffs of various backscatter imaging algorithms for the SeaWinds scatterometer when multiple passes over a target are available. Reconstruction methods are compared with conventional gridding algorithms. In particular, the performance and tradeoffs in conventional ‘drop in the bucket’ (DIB) gridding at the intrinsic sensor resolution are compared to high-spatial-resolution imaging algorithms such as fine-resolution DIB and the scatterometer image reconstruction (SIR) that generate enhanced-resolution backscatter images. Various options for each algorithm are explored, including considering both linear and dB computation. The effects of sampling density and reconstruction quality versus time are explored. Both simulated and actual data results are considered. The results demonstrate the effectiveness of high-resolution reconstruction using SIR as well as its limitations and the limitations of DIB and fDIB. PMID:28828143

  1. The Heeger & Bergen Pyramid Based Texture Synthesis Algorithm

    Directory of Open Access Journals (Sweden)

    Thibaud Briand

    2014-11-01

    Full Text Available This contribution deals with the Heeger-Bergen pyramid-based texture analysis/synthesis algorithm. It brings a detailed explanation of the original algorithm tested on many characteristic examples. Our analysis reproduces the original results, but also brings a minor improvement concerning non-periodic textures. Inspired by visual perception theories, Heeger and Bergen proposed to characterize a texture by its first-order statistics of both its color and its responses to multiscale and multi-orientation filters, namely the steerable pyramid. The Heeger-Bergen algorithm consists in the following procedure: starting from a white noise image, histogram matchings are performed to the noise alternatively in both the image domain and steerable pyramid domain, so that the corresponding histograms match the ones of the input texture.

  2. Aerodynamic noise prediction of a Horizontal Axis Wind Turbine using Improved Delayed Detached Eddy Simulation and acoustic analogy

    International Nuclear Information System (INIS)

    Ghasemian, Masoud; Nejat, Amir

    2015-01-01

    Highlights: • The noise predictions are performed by Ffowcs Williams and Hawkings method. • There is a direct relation between the radiated noise and the wind speed. • The tonal peaks in the sound spectra match with the blade passing frequency. • The quadrupole noises have negligible effect on the low frequency noises. - Abstract: This paper presents the results of the aerodynamic and aero-acoustic prediction of the flow field around the National Renewable Energy Laboratory Phase VI wind turbine. The Improved Delayed Detached Eddy Simulation turbulence model is applied to obtain the instantaneous turbulent flow field. The noise prediction is carried out using the Ffowcs Williams and Hawkings acoustic analogy. Simulations are performed for three different inflow conditions, U = 7, 10, 15 m/s. The capability of the Improved Delayed Detached Eddy Simulation turbulence model in massive separation is verified with available experimental data for pressure coefficient. The broadband noises of the turbulent boundary layers and the tonal noises due to the blade passing frequency are predicted via flow field noise simulation. The contribution of the thickness, loading and quadrupole noises are investigated, separately. The results indicated that there is a direct relation between the strength of the radiated noise and the wind speed. Furthermore, the effect of the receiver location on the Overall Sound Pressure Level is investigated

  3. Dependence of regular background noise of VLF radiation and thunder-storm activity on solar wind proton density

    International Nuclear Information System (INIS)

    Sobolev, A.V.; Kozlov, V.I.

    1997-01-01

    Correlation of the intensity of slowly changing regular background noise within 9.7 kHz frequency in Yakutsk (L = 3) and of the solar wind density protons was determined. This result explains the reverse dependence of the intensity of the regular background noise on the solar activity, 27-day frequency, increase before and following geomagnetic storms, absence of relation with K p index of geomagnetic activity. Conclusion is made that growth of density of the solar wind protons results in increase of the regular background noise and thunderstorm activity

  4. Open noise barriers based on sonic crystals. Advances in noise control in transport infraestructures

    Energy Technology Data Exchange (ETDEWEB)

    Peiro Torres, M.P.; Redondo Pastor, J.; Bravo Plana-Sala, J.M.; Sanchez Perez, J.V.

    2016-07-01

    Noise control is an environmental problem of first magnitude nowadays. In this work, we present a new concept of acoustic screen designed to control the specific noise generated by transport infrastructures, based on new materials called sonic crystals. These materials are formed by arrangements of acoustic scatterers in air, and provide a new and different mechanism in the fight against noise from those of the classical screens. This mechanism is usually called multiple scattering and is due to their structuring in addition to their physical properties. Due to the separation between scatterers, these barriers are transparent to air and water allowing a reduction on their foundations. Tests carried out in a wind tunnel show a reduction of 42% in the overturning momentum compared to classical barriers. The acoustical performance of these barriers is shown in this work, explaining the new characteristics provided in the control of noise. Finally, an example of these barriers is presented and classified according to acoustic standardization tests. The acoustic barrier reported in this work provides a high technological solution in the field of noise control. (Author)

  5. Offshore Wind Farm Cable Connection Configuration Optimization using Dynamic Minimum Spanning Tree Algorithm

    DEFF Research Database (Denmark)

    Hou, Peng; Hu, Weihao; Chen, Zhe

    2015-01-01

    Anew approach, Dynamic Minimal Spanning Tree (DMST) algorithm, whichisbased on the MST algorithm isproposed in this paper to optimizethe cable connectionlayout for large scale offshore wind farm collection system. The current carrying capacity of the cable is considered as the main constraint....... It is amore economicalway for cable connection configurationdesignof offshore wind farm collection system....

  6. Experimental demonstration of wind turbine noise reduction through optimized airfoil shape and trailing-edge serrations

    Energy Technology Data Exchange (ETDEWEB)

    Oerlemans, S. [National Aerospace Laboratory NLR, Emmeloord (Netherlands); Schepers, J.G. [Unit Wind Energy, Energy research Centre of the Netherlands ECN, Petten (Netherlands); Guidati, G.; Wagner, S. [Institut fuer Aerodynamik und Gasdynamik IAG, Universitaet Stuttgart (Germany)

    2001-07-15

    The objective of the European project DATA (Design and Testing of Acoustically Optimized Airfoils for Wind Turbines) is a reduction of trailing-edge (TE) noise by modifying the airfoil shape and/or the application of trailing-edge serrations. This paper describes validation measurements that were performed in the DNW-LLF wind tunnel, on a model scale wind turbine with a two-bladed 4.5 m diameter rotor which was designed in the project. Measurements were done for one reference- and two acoustically optimized rotors, for varying flow conditions. The aerodynamic performance of the rotors was measured using a torque meter in the hub, and further aerodynamic information was obtained from flow visualization on the blades. The acoustic measurements were done with a 136 microphone out-of-flow acoustic array. Besides the location of the noise sources in the (stationary) rotor plane, a new acoustic processing method enabled identification of dominant noise source regions on the rotating blades. The results show dominant noise sources at the trailing-edge of the blade, close to the tip. The optimized airfoil shapes result in a significant reduction of TE noise levels with respect to the reference rotor, without loss in power production. A further reduction can be achieved by the application of trailing-edge serrations. The aerodynamic measurements are generally in good agreement with the aerodynamic predictions made during the design of the model turbine.

  7. Benchmarking the Algorithms to Detect Seasonal Signals Under Different Noise Conditions

    Science.gov (United States)

    Klos, A.; Bogusz, J.; Bos, M. S.

    2017-12-01

    Global Positioning System (GPS) position time series contain seasonal signals. Among the others, annual and semi-annual are the most powerful. Widely, these oscillations are modelled as curves with constant amplitudes, using the Weighted Least-Squares (WLS) algorithm. However, in reality, the seasonal signatures vary over time, as their geophysical causes are not constant. Different algorithms have been already used to cover this time-variability, as Wavelet Decomposition (WD), Singular Spectrum Analysis (SSA), Chebyshev Polynomial (CP) or Kalman Filter (KF). In this research, we employed 376 globally distributed GPS stations which time series contributed to the newest International Terrestrial Reference Frame (ITRF2014). We show that for c.a. 20% of stations the amplitudes of seasonal signal varies over time of more than 1.0 mm. Then, we compare the WD, SSA, CP and KF algorithms for a set of synthetic time series to quantify them under different noise conditions. We show that when variations of seasonal signals are ignored, the power-law character is biased towards flicker noise. The most reliable estimates of the variations were found to be given by SSA and KF. These methods also perform the best for other noise levels while WD, and to a lesser extend also CP, have trouble in separating the seasonal signal from the noise which leads to an underestimation in the spectral index of power-law noise of around 0.1. For real ITRF2014 GPS data we discovered, that SSA and KF are capable to model 49-84% and 77-90% of the variance of the true varying seasonal signals, respectively.

  8. Short-term nighttime wind turbine noise and cardiovascular events: A nationwide case-crossover study from Denmark.

    Science.gov (United States)

    Poulsen, Aslak Harbo; Raaschou-Nielsen, Ole; Peña, Alfredo; Hahmann, Andrea N; Nordsborg, Rikke Baastrup; Ketzel, Matthias; Brandt, Jørgen; Sørensen, Mette

    2018-05-01

    The number of people exposed to wind turbine noise (WTN) is increasing. WTN is reported as more annoying than traffic noise at similar levels. Long-term exposure to traffic noise has consistently been associated with cardiovascular disease, whereas effects of short-term exposure are much less investigated due to little day-to-day variation of e.g. road traffic noise. WTN varies considerably due to changing weather conditions allowing investigation of short-term effects of WTN on cardiovascular events. We identified all hospitalisations and deaths from stroke (16,913 cases) and myocardial infarction (MI) (17,559 cases) among Danes exposed to WTN between 1982 and 2013. We applied a time-stratified, case-crossover design. Using detailed data on wind turbine type and hourly wind data at each wind turbine, we simulated mean nighttime outdoor (10-10,000 Hz) and nighttime low frequency (LF) indoor WTN (10-160 Hz) over the 4 days preceding diagnosis and reference days. For indoor LF WTN between 10 and 15 dB(A) and above 15 dB(A), odds ratios (ORs) for MI were 1.27 (95% confidence interval (CI): 0.97-1.67; cases = 198) and 1.62 (95% CI: 0.76-3.45; cases = 21), respectively, when compared to indoor LF WTN below 5 dB(A). For stroke, corresponding ORs were 1.17 (95% CI: 0.95-1.69; cases = 166) and 2.30 (95% CI: 0.96-5.50; cases = 15). The elevated ORs above 15 dB(A) persisted across sensitivity analyses. When looking at specific lag times, noise exposure one day before MI events and three days before stroke events were associated with the highest ORs. For outdoor WTN at night, we observed both increased and decreased risk estimates. This study did not provide conclusive evidence of an association between WTN and MI or stroke. It does however suggest that indoor LF WTN at night may trigger cardiovascular events, whereas these events seemed largely unaffected by nighttime outdoor WTN. These findings need reproduction, as they were based on few cases

  9. Improved prediction of aerodynamic noise from wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Guidati, G.; Bareiss, R.; Wagner, S. [Univ. of Stuttgart, Inst. of Aerodynamics and Gasdynamics, Stuttgart (Germany)

    1997-12-31

    This paper focuses on an improved prediction model for inflow-turbulence noise which takes the true airfoil shape into account. Predictions are compared to the results of acoustic measurements on three 2D-models of 0.25 m chord. Two of the models have NACA-636xx airfoils of 12% and 18% relative thickness. The third airfoil was acoustically optimized by using the new prediction model. In the experiments the turbulence intensity of the flow was strongly increased by mounting a grid with 60 mm wide meshes and 12 mm thick rods onto the tunnel exhaust nozzle. The sound radiated from the airfoil was distinguished by the tunnel background noise by using an acoustic antenna consisting of a cross array of 36 microphones in total. An application of a standard beam-forming algorithm allows to determine how much noise is radiated from different parts of the models. This procedure normally results in a peak at the leading and trailing edge of the airfoil. The strength of the leading-edge peak is taken as the source strength for inflow-turbulence noise. (LN) 14 refs.

  10. Hydro-Thermal-Wind Generation Scheduling Considering Economic and Environmental Factors Using Heuristic Algorithms

    Directory of Open Access Journals (Sweden)

    Suresh K. Damodaran

    2018-02-01

    Full Text Available Hydro-thermal-wind generation scheduling (HTWGS with economic and environmental factors is a multi-objective complex nonlinear power system optimization problem with many equality and inequality constraints. The objective of the problem is to generate an hour-by-hour optimum schedule of hydro-thermal-wind power plants to attain the least emission of pollutants from thermal plants and a reduced generation cost of thermal and wind plants for a 24-h period, satisfying the system constraints. The paper presents a detailed framework of the HTWGS problem and proposes a modified particle swarm optimization (MPSO algorithm for evolving a solution. The competency of selected heuristic algorithms, representing different heuristic groups, viz. the binary coded genetic algorithm (BCGA, particle swarm optimization (PSO, improved harmony search (IHS, and JAYA algorithm, for searching for an optimal solution to HTWGS considering economic and environmental factors was investigated in a trial system consisting of a multi-stream cascaded system with four reservoirs, three thermal plants, and two wind plants. Appropriate mathematical models were used for representing the water discharge, generation cost, and pollutant emission of respective power plants incorporated in the system. Statistical analysis was performed to check the consistency and reliability of the proposed algorithm. The simulation results indicated that the proposed MPSO algorithm provided a better solution to the problem of HTWGS, with a reduced generation cost and the least emission, when compared with the other heuristic algorithms considered.

  11. Suppression of background noise in a transonic wind-tunnel test section

    Science.gov (United States)

    Schutzenhofer, L. A.; Howard, P. W.

    1975-01-01

    Some exploratory tests were recently performed in the transonic test section of the NASA Marshall Space Flight Center 14-in. wind tunnel to suppress the background noise. In these tests, the perforated walls of the test section were covered with fine wire screens. The screens eliminated the edge tones generated by the holes in the perforated walls and significantly reduced the tunnel background noise. The tunnel noise levels were reduced to such a degree by this simple modification at Mach numbers 0.75, 0.9, 1.1, 1.2, and 1.46 that the fluctuating pressure levels of a turbulent boundary layer could be measured on a 5-deg half-angle cone.

  12. Frequency Based Fault Detection in Wind Turbines

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2014-01-01

    In order to obtain lower cost of energy for wind turbines fault detection and accommodation is important. Expensive condition monitoring systems are often used to monitor the condition of rotating and vibrating system parts. One example is the gearbox in a wind turbine. This system is operated...... in parallel to the control system, using different computers and additional often expensive sensors. In this paper a simple filter based algorithm is proposed to detect changes in a resonance frequency in a system, exemplified with faults resulting in changes in the resonance frequency in the wind turbine...... gearbox. Only the generator speed measurement which is available in even simple wind turbine control systems is used as input. Consequently this proposed scheme does not need additional sensors and computers for monitoring the condition of the wind gearbox. The scheme is evaluated on a wide-spread wind...

  13. Measurement system for wind turbine acoustic noise assessment based on IEC standard and Qin′s model

    Institute of Scientific and Technical Information of China (English)

    Sun Lei; Qin Shuren; Bo Lin; Xu Liping; Stephan Joeckel

    2008-01-01

    A novel measurement system specially used in noise emission assessment and verification of wind turbine generator systems is presented that complies with specifications given in IEC 61400-11 to ensure the process consistency and accuracy. Theory elements of the calculation formula used for the sound power level of wind turbine have been discussed for the first time, and detailed calculation procedure of tonality and audibility integrating narrowband analysis and psychoacoustics is described. With a microphone and two PXI cards inserted into a PC, this system is designed in Qin′s model using VMIDS development system. Benefiting from the virtual instrument architecture, it′s the first time that all assessment process have been integrated into an organic whole, which gives full advantages of its efficiency, price, and facility. Mass experiments show that its assessment results accord with the ones given by MEASNET member.

  14. 'Wind turbine syndrome': fact or fiction?

    Science.gov (United States)

    Farboud, A; Crunkhorn, R; Trinidade, A

    2013-03-01

    Symptoms, including tinnitus, ear pain and vertigo, have been reported following exposure to wind turbine noise. This review addresses the effects of infrasound and low frequency noise and questions the existence of 'wind turbine syndrome'. This review is based on a search for articles published within the last 10 years, conducted using the PubMed database and Google Scholar search engine, which included in their title or abstract the terms 'wind turbine', 'infrasound' or 'low frequency noise'. There is evidence that infrasound has a physiological effect on the ear. Until this effect is fully understood, it is impossible to conclude that wind turbine noise does not cause any of the symptoms described. However, many believe that these symptoms are related largely to the stress caused by unwanted noise exposure. There is some evidence of symptoms in patients exposed to wind turbine noise. The effects of infrasound require further investigation.

  15. A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge

    2014-01-01

    Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily

  16. An Automatic K-Means Clustering Algorithm of GPS Data Combining a Novel Niche Genetic Algorithm with Noise and Density

    Directory of Open Access Journals (Sweden)

    Xiangbing Zhou

    2017-12-01

    Full Text Available Rapidly growing Global Positioning System (GPS data plays an important role in trajectory and their applications (e.g., GPS-enabled smart devices. In order to employ K-means to mine the better origins and destinations (OD behind the GPS data and overcome its shortcomings including slowness of convergence, sensitivity to initial seeds selection, and getting stuck in a local optimum, this paper proposes and focuses on a novel niche genetic algorithm (NGA with density and noise for K-means clustering (NoiseClust. In NoiseClust, an improved noise method and K-means++ are proposed to produce the initial population and capture higher quality seeds that can automatically determine the proper number of clusters, and also handle the different sizes and shapes of genes. A density-based method is presented to divide the number of niches, with its aim to maintain population diversity. Adaptive probabilities of crossover and mutation are also employed to prevent the convergence to a local optimum. Finally, the centers (the best chromosome are obtained and then fed into the K-means as initial seeds to generate even higher quality clustering results by allowing the initial seeds to readjust as needed. Experimental results based on taxi GPS data sets demonstrate that NoiseClust has high performance and effectiveness, and easily mine the city’s situations in four taxi GPS data sets.

  17. Low frequency noise from large wind turbines - updated 2011; Lavfrekvent stoej fra store vindmoeller - opdateret 2011

    Energy Technology Data Exchange (ETDEWEB)

    Moeller, H.; Sejer Pedersen, C.; Pedersen, Steffen

    2011-07-01

    The study analyzed measurements of noise from 65 wind turbines, 25 large turbines (2.3 to 3.6 MW) and 40 small ones (up to 2 MW). The large mills (2.3 to 3.6 MW) emit relatively more low frequency noise than the small ones (up to 2 MW). The difference is statistically significant for the frequency range 63-250 Hz, regardless of whether calculations are performed on all the large mills or only on new wind turbines. There are no significant differences between prototype turbines and the new mills. Because of wind noise in the measurements of the small mills, it is not possible to determine whether the difference between small and large turbines continues further down in frequency. Looking at the A-weighted sound pressure in relevant neighbor distances, the lower frequencies constitute an essential part of the noise from the large mills, and there is no doubt that the low frequency noise is both audible and annoying. When the total A-weighted sound pressure level is the same, there will on average be about 3 dB more low frequency noise from large turbines than from small ones. At large distances the noise character becomes yet more low frequency because atmospheric absorption reduces the high frequencies more than the low frequencies. Depending on the sound insulation the low frequency noise can also be annoying indoors. If the total A-weighted sound pressure level outdoors is 44 dB, the low frequency noise can be heard indoors in all the houses and for all the large turbines. The sound pressure level will in many cases exceed the indoor limit for evening night at 20 dB. (ln)

  18. An improved artificial physical optimization algorithm for dynamic dispatch of generators with valve-point effects and wind power

    International Nuclear Information System (INIS)

    Yuan, Xiaohui; Ji, Bin; Zhang, Shuangquan; Tian, Hao; Chen, Zhihuan

    2014-01-01

    Highlights: • Dynamic load economic dispatch with wind power (DLEDW) model is established. • Markov chains combined with scenario analysis method are used to predict wind power. • Chance constrained technique is used to simulate the impacts of wind forecast error. • Improved artificial physical optimization algorithm is proposed to solve DLEDW. • Heuristic search strategies are applied to handle the constraints of DLEDW. - Abstract: Wind power, a kind of promising renewable energy resource, has recently been getting more attractive because of various environmental and economic considerations. But the penetration of wind power with its fluctuation nature has made the operation of power system more intractable. To coordinate the reliability and operation cost, this paper established a stochastic model of dynamic load economic dispatch with wind integration (DLEDW). In this model, constraints such as ramping up/down capacity, prohibited operating zone are considered and effects of valve-point are taken into account. Markov chains combined with scenario analysis method is used to generate predictive values of wind power and chance constrained programming (CCP) is applied to simulate the impacts of wind power fluctuation on system operation. An improved artificial physical optimization algorithm is presented to solve the DLEDW problem. Heuristic strategies based on the priority list and stochastic simulation techniques are proposed to handle the constraints. In addition, a local chaotic mutation strategy is applied to overcome the disadvantage of premature convergence of artificial physical optimization algorithm. Two test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method and the results are compared with those of gravitational search algorithm, particle swarm optimization and standard artificial physical optimization. The simulation results demonstrate that the proposed method has a

  19. Optimal Capacitor Placement in Wind Farms by Considering Harmonics Using Discrete Lightning Search Algorithm

    Directory of Open Access Journals (Sweden)

    Reza Sirjani

    2017-09-01

    Full Text Available Currently, many wind farms exist throughout the world and, in some cases, supply a significant portion of energy to networks. However, numerous uncertainties remain with respect to the amount of energy generated by wind turbines and other sophisticated operational aspects, such as voltage and reactive power management, which requires further development and consideration. To fix the problem of poor reactive power compensation in wind farms, optimal capacitor placement has been proposed in existing wind farms as a simple and relatively inexpensive method. However, the use of induction generators, transformers, and additional capacitors represent potential problems for the harmonics of a system and therefore must be taken into account at wind farms. The optimal location and size of capacitors at buses of an 80-MW wind farm were determined according to modelled wind speed, system equivalent circuits, and harmonics in order to minimize energy losses, optimize reactive power and reduce the management costs. The discrete version of the lightning search algorithm (DLSA is a powerful and flexible nature-inspired optimization technique that was developed and implemented herein for optimal capacitor placement in wind farms. The obtained results are compared with the results of the genetic algorithm (GA and the discrete harmony search algorithm (DHSA.

  20. Pulse retrieval algorithm for interferometric frequency-resolved optical gating based on differential evolution.

    Science.gov (United States)

    Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

    2017-10-01

    A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely, differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove the robustness of the algorithm against experimental artifacts and noise. These tests show that the integrated error-correction mechanisms of the iFROG method can be successfully used to remove the effect from timing errors and spectrally varying efficiency in the detection. Moreover, the accuracy and noise resilience of the new algorithm are shown to outperform retrieval based on the generalized projections algorithm, which is widely used as the standard method in FROG retrieval. The differential evolution algorithm is further validated with experimental data, measured with unamplified three-cycle pulses from a mode-locked Ti:sapphire laser. Additionally introducing group delay dispersion in the beam path, the retrieval results show excellent agreement with independent measurements with a commercial pulse measurement device based on spectral phase interferometry for direct electric-field retrieval. Further experimental tests with strongly attenuated pulses indicate resilience of differential-evolution-based retrieval against massive measurement noise.

  1. Wind turbine underwater noise and marine mammals : implications of current knowledge and data needs

    OpenAIRE

    Madsen, P T; Wahlberg, M; Tougaard, J; Lucke, K; Tyack, Peter Lloyd

    2006-01-01

    The demand for renewable energy has led to construction of offshore wind farms with high-power turbines, and many more wind farms are being planned for the shallow waters of the world's marine habitats. The growth of offshore wind farms has raised concerns about their impact on the marine environment. Marine mammals use sound for foraging, orientation and communication and are therefore possibly susceptible to negative effects of man-made noise generated from constructing and operating large ...

  2. 77 FR 17496 - Fisheries and Habitat Conservation and Migratory Birds Programs; Final Land-Based Wind Energy...

    Science.gov (United States)

    2012-03-26

    ...] RIN 1018-AX45 Fisheries and Habitat Conservation and Migratory Birds Programs; Final Land-Based Wind...) established the Wind Turbine Guidelines Advisory Committee (Committee) under the Federal Advisory Committee... concern over certain issues such as the effects of wind turbine noise on wildlife, these issues have not...

  3. NACA0015 measurements in LM wind tunnel and turbulence generated noise

    Energy Technology Data Exchange (ETDEWEB)

    Bertagnolio, Franck

    2008-11-15

    A NACA0015 airfoil section was instrumented with an array of highfrequency microphones mounted on its surface and measured in the wind tunnel at LM Glasfiber at various inflow speeds, angles of attack, and with different turbulent inflow conditions. The aim of this work is to analyze these measurement data, including the turbulent inflow characteristics. The airfoil surface pressure data are considered in the perspective of turbulent inflow noise in order to identify the potential for using these data to validate and possibly improve associated noise models from the literature. In addition, these data are further analyzed in the context of trailing edge noise modeling which is directly related to the surface pressure fluctuations in the vicinity of the trailing edge. (au)

  4. Development of design tools for reduced aerodynamic noise wind turbines (draw)

    NARCIS (Netherlands)

    Wagner, S.; Guidati, G.; Ostertag, J.; Bareiss, R.; Wittum, G.; Huurdeman, B.; Braun, K.; Hirsch, C.; Kang, S.; Khodak, A.; Overmeire, M. van; Bladt, G.; Nienhaus, A.; Dassen, A.G.M.; Parchen, R.R.; Looijmans, K.

    1997-01-01

    The major aim of the present project was the development of new predictïon models for the aerodynamic noise generation at wind turbine blades. These models should be transferred to computer codes and should be sensitive enough to consider even small changes in the airfoil geometry. This accuracy is

  5. Application of the nonlinear time series prediction method of genetic algorithm for forecasting surface wind of point station in the South China Sea with scatterometer observations

    International Nuclear Information System (INIS)

    Zhong Jian; Dong Gang; Sun Yimei; Zhang Zhaoyang; Wu Yuqin

    2016-01-01

    The present work reports the development of nonlinear time series prediction method of genetic algorithm (GA) with singular spectrum analysis (SSA) for forecasting the surface wind of a point station in the South China Sea (SCS) with scatterometer observations. Before the nonlinear technique GA is used for forecasting the time series of surface wind, the SSA is applied to reduce the noise. The surface wind speed and surface wind components from scatterometer observations at three locations in the SCS have been used to develop and test the technique. The predictions have been compared with persistence forecasts in terms of root mean square error. The predicted surface wind with GA and SSA made up to four days (longer for some point station) in advance have been found to be significantly superior to those made by persistence model. This method can serve as a cost-effective alternate prediction technique for forecasting surface wind of a point station in the SCS basin. (paper)

  6. Fault Diagnosis of an Advanced Wind Turbine Benchmark using Interval-based ARRs and Observers

    DEFF Research Database (Denmark)

    Sardi, Hector Eloy Sanchez; Escobet, Teressa; Puig, Vicenc

    2015-01-01

    This paper proposes a model-based fault diagnosis (FD) approach for wind turbines and its application to a realistic wind turbine FD benchmark. The proposed FD approach combines the use of analytical redundancy relations (ARRs) and interval observers. Interval observers consider an unknown...... turbine and noise/parameter uncertainty bounds. Fault isolation is based on considering a set of ARRs obtained from the structural analysis of the wind turbine model and a fault signature matrix that considers the relation of ARRs and faults. The proposed FD approach has been validated on a 5-MW wind...

  7. A review of noise data collection at the central and south west wind farm in Texas

    Energy Technology Data Exchange (ETDEWEB)

    Moroz, E. [Univ. of Texas, El Paso, TX (United States)

    1996-12-31

    Evaluation of data collected over a 1-year period from a 6 MW wind farm is presented in the paper. Noise propagation prediction methods are compared with each other and with field data. Three forms of regulating noise are also compared: minimum separation distance, absolute noise limit, and relative noise limit.Relative noise limits were found to offer the most comprehensive approach to regulating noise and to allow each location to be treated independently. A hemispherical spreading model appears to be a useful planning tool. 11 refs., 4 tabs.

  8. Post commissioning noise study

    International Nuclear Information System (INIS)

    Heraud, P.

    2008-01-01

    This presentation described a wind farm post-commissioning study conducted at a wind farm owned by Helimax Energy Inc. The farm was located in a partly-forested, partly cultivated region in Quebec that featured gently rolling hills. Over 600 dwellings were located within 2 km of the wind farm, and 44 dwellings were within the wind farm's boundaries. The noise impact assessments were conducted at various points near the wind farm. The wind farm was designed using an International Standards Organization (ISO) noise propagation model and a 40 dBA to provide adequate setbacks. The study was conducted using 10 days of continuous measurements at selected points of a wind farm. Points of reception included points from 650 m to 800 m. Noise over 2 km was not thought to be contributed by the wind turbine. The nearest dwelling was 512 m from one of the farm's wind turbines. The study also considered ground factor, temperature, relative humidity, and the height of the receptors. Quebec noise level limits are 40 dBA at night, and 45 dBA during the day. Noise level limits are independent of wind speed. Measured noise contributions over 40 dBA were not observed during the measurement program. The wind turbines were only audible for 1 night out of the 30 night study period. It was concluded that the ISO noise propagation model is a reliable tool for conducting noise impact assessments. tabs., figs

  9. Edge enhancement and noise suppression for infrared image based on feature analysis

    Science.gov (United States)

    Jiang, Meng

    2018-06-01

    Infrared images are often suffering from background noise, blurred edges, few details and low signal-to-noise ratios. To improve infrared image quality, it is essential to suppress noise and enhance edges simultaneously. To realize it in this paper, we propose a novel algorithm based on feature analysis in shearlet domain. Firstly, as one of multi-scale geometric analysis (MGA), we introduce the theory and superiority of shearlet transform. Secondly, after analyzing the defects of traditional thresholding technique to suppress noise, we propose a novel feature extraction distinguishing image structures from noise well and use it to improve the traditional thresholding technique. Thirdly, with computing the correlations between neighboring shearlet coefficients, the feature attribute maps identifying the weak detail and strong edges are completed to improve the generalized unsharped masking (GUM). At last, experiment results with infrared images captured in different scenes demonstrate that the proposed algorithm suppresses noise efficiently and enhances image edges adaptively.

  10. Increasing the darkfield contrast-to-noise ratio using a deconvolution-based information retrieval algorithm in X-ray grating-based phase-contrast imaging.

    Science.gov (United States)

    Weber, Thomas; Pelzer, Georg; Bayer, Florian; Horn, Florian; Rieger, Jens; Ritter, André; Zang, Andrea; Durst, Jürgen; Anton, Gisela; Michel, Thilo

    2013-07-29

    A novel information retrieval algorithm for X-ray grating-based phase-contrast imaging based on the deconvolution of the object and the reference phase stepping curve (PSC) as proposed by Modregger et al. was investigated in this paper. We applied the method for the first time on data obtained with a polychromatic spectrum and compared the results to those, received by applying the commonly used method, based on a Fourier analysis. We confirmed the expectation, that both methods deliver the same results for the absorption and the differential phase image. For the darkfield image, a mean contrast-to-noise ratio (CNR) increase by a factor of 1.17 using the new method was found. Furthermore, the dose saving potential was estimated for the deconvolution method experimentally. It is found, that for the conventional method a dose which is higher by a factor of 1.66 is needed to obtain a similar CNR value compared to the novel method. A further analysis of the data revealed, that the improvement in CNR and dose efficiency is due to the superior background noise properties of the deconvolution method, but at the cost of comparability between measurements at different applied dose values, as the mean value becomes dependent on the photon statistics used.

  11. GPS Signal Offset Detection and Noise Strength Estimation in a Parallel Kalman Filter Algorithm

    National Research Council Canada - National Science Library

    Vanek, Barry

    1999-01-01

    .... The variance of the noise process is estimated and provided to the second algorithm, a parallel Kalman filter structure, which then adapts to changes in the real-world measurement noise strength...

  12. A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

    Science.gov (United States)

    Greenwood, Eric, II; Schmitz, Fredric H.

    2010-01-01

    A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

  13. Deep neural network and noise classification-based speech enhancement

    Science.gov (United States)

    Shi, Wenhua; Zhang, Xiongwei; Zou, Xia; Han, Wei

    2017-07-01

    In this paper, a speech enhancement method using noise classification and Deep Neural Network (DNN) was proposed. Gaussian mixture model (GMM) was employed to determine the noise type in speech-absent frames. DNN was used to model the relationship between noisy observation and clean speech. Once the noise type was determined, the corresponding DNN model was applied to enhance the noisy speech. GMM was trained with mel-frequency cepstrum coefficients (MFCC) and the parameters were estimated with an iterative expectation-maximization (EM) algorithm. Noise type was updated by spectrum entropy-based voice activity detection (VAD). Experimental results demonstrate that the proposed method could achieve better objective speech quality and smaller distortion under stationary and non-stationary conditions.

  14. Image noise reduction algorithm for digital subtraction angiography: clinical results.

    Science.gov (United States)

    Söderman, Michael; Holmin, Staffan; Andersson, Tommy; Palmgren, Charlotta; Babic, Draženko; Hoornaert, Bart

    2013-11-01

    To test the hypothesis that an image noise reduction algorithm designed for digital subtraction angiography (DSA) in interventional neuroradiology enables a reduction in the patient entrance dose by a factor of 4 while maintaining image quality. This clinical prospective study was approved by the local ethics committee, and all 20 adult patients provided informed consent. DSA was performed with the default reference DSA program, a quarter-dose DSA program with modified acquisition parameters (to reduce patient radiation dose exposure), and a real-time noise-reduction algorithm. Two consecutive biplane DSA data sets were acquired in each patient. The dose-area product (DAP) was calculated for each image and compared. A randomized, blinded, offline reading study was conducted to show noninferiority of the quarter-dose image sets. Overall, 40 samples per treatment group were necessary to acquire 80% power, which was calculated by using a one-sided α level of 2.5%. The mean DAP with the quarter-dose program was 25.3% ± 0.8 of that with the reference program. The median overall image quality scores with the reference program were 9, 13, and 12 for readers 1, 2, and 3, respectively. These scores increased slightly to 12, 15, and 12, respectively, with the quarter-dose program imaging chain. In DSA, a change in technique factors combined with a real-time noise-reduction algorithm will reduce the patient entrance dose by 75%, without a loss of image quality. RSNA, 2013

  15. Indoor noise annoyance due to 3-5 megawatt wind turbines-An exposure-response relationship.

    Science.gov (United States)

    Hongisto, Valtteri; Oliva, David; Keränen, Jukka

    2017-10-01

    The existing exposure-response relationships describing the association between wind turbine sound level and noise annoyance concern turbine sizes of 0.15-3.0 MW. The main purpose of this study was to determine a relationship concerning turbines with nominal power of 3-5 MW. A cross-sectional survey was conducted around three wind power areas in Finland. The survey involved all households within a 2 km distance from the nearest turbine. Altogether, 429 households out of 753 participated. The households were exposed to wind turbine noise having sound levels within 26.7-44.2 dB L Aeq . Standard prediction methods were applied to determine the sound level, L Aeq , in each participant's yard. The measured sound level agreed well with the predicted sound level. The exposure-response relationship was derived between L Aeq outdoors and the indoor noise annoyance. The relationship was in rather good agreement with two previous studies involving much smaller turbines (0.15-1.5 MW) under 40 dB L Aeq . The Community Tolerance Level (CTL), CTL 20  = 50 dB, was 3 dB lower than for two previous studies. Above 40 dB, a small number of participants prevented a reliable comparison to previous studies.

  16. Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

    Directory of Open Access Journals (Sweden)

    Haoran Zhao

    2018-03-01

    Full Text Available As the most efficient renewable energy source for generating electricity in a modern electricity network, wind power has the potential to realize sustainable energy supply. However, owing to its random and intermittent instincts, a high permeability of wind power into a power network demands accurate and effective wind energy prediction models. This study proposes a multi-stage intelligent algorithm for wind electric power prediction, which combines the Beveridge–Nelson (B-N decomposition approach, the Least Square Support Vector Machine (LSSVM, and a newly proposed intelligent optimization approach called the Grasshopper Optimization Algorithm (GOA. For data preprocessing, the B-N decomposition approach was employed to disintegrate the hourly wind electric power data into a deterministic trend, a cyclic term, and a random component. Then, the LSSVM optimized by the GOA (denoted GOA-LSSVM was applied to forecast the future 168 h of the deterministic trend, the cyclic term, and the stochastic component, respectively. Finally, the future hourly wind electric power values can be obtained by multiplying the forecasted values of these three trends. Through comparing the forecasting performance of this proposed method with the LSSVM, the LSSVM optimized by the Fruit-fly Optimization Algorithm (FOA-LSSVM, and the LSSVM optimized by Particle Swarm Optimization (PSO-LSSVM, it is verified that the established multi-stage approach is superior to other models and can increase the precision of wind electric power prediction effectively.

  17. An l1-TV Algorithm for Deconvolution with Salt and Pepper Noise

    Science.gov (United States)

    2009-04-01

    deblurring in the presence of impulsive noise ,” Int. J. Comput. Vision, vol. 70, no. 3, pp. 279–298, Dec. 2006. [13] A. E. Beaton and J. W. Tukey, “The...AN 1-TV ALGORITHM FOR DECONVOLUTIONWITH SALT AND PEPPER NOISE Brendt Wohlberg∗ T-7 Mathematical Modeling and Analysis Los Alamos National Laboratory...and pepper noise , but the extension of this formulation to more general prob- lems, such as deconvolution, has received little attention. We consider

  18. Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm using Particle Swarm Optimization Algorithm

    DEFF Research Database (Denmark)

    Hou, Peng; Hu, Weihao; Soltani, Mohsen

    2015-01-01

    With the increasing size of wind farm, the impact of the wake effect on wind farm energy yields become more and more evident. The arrangement of the wind turbines’ (WT) locations will influence the capital investment and contribute to the wake losses which incur the reduction of energy production....... As a consequence, the optimized placement of the wind turbines may be done by considering the wake effect as well as the components cost within the wind farm. In this paper, a mathematical model which includes the variation of both wind direction and wake deficit is proposed. The problem is formulated by using...... Levelized Production Cost (LPC) as the objective function. The optimization procedure is performed by Particle Swarm Optimization (PSO) algorithm with the purpose of maximizing the energy yields while minimizing the total investment. The simulation results indicate that the proposed method is effective...

  19. Single image super resolution algorithm based on edge interpolation in NSCT domain

    Science.gov (United States)

    Zhang, Mengqun; Zhang, Wei; He, Xinyu

    2017-11-01

    In order to preserve the texture and edge information and to improve the space resolution of single frame, a superresolution algorithm based on Contourlet (NSCT) is proposed. The original low resolution image is transformed by NSCT, and the directional sub-band coefficients of the transform domain are obtained. According to the scale factor, the high frequency sub-band coefficients are amplified by the interpolation method based on the edge direction to the desired resolution. For high frequency sub-band coefficients with noise and weak targets, Bayesian shrinkage is used to calculate the threshold value. The coefficients below the threshold are determined by the correlation among the sub-bands of the same scale to determine whether it is noise and de-noising. The anisotropic diffusion filter is used to effectively enhance the weak target in the low contrast region of the target and background. Finally, the high-frequency sub-band is amplified by the bilinear interpolation method to the desired resolution, and then combined with the high-frequency subband coefficients after de-noising and small target enhancement, the NSCT inverse transform is used to obtain the desired resolution image. In order to verify the effectiveness of the proposed algorithm, the proposed algorithm and several common image reconstruction methods are used to test the synthetic image, motion blurred image and hyperspectral image, the experimental results show that compared with the traditional single resolution algorithm, the proposed algorithm can obtain smooth edges and good texture features, and the reconstructed image structure is well preserved and the noise is suppressed to some extent.

  20. Adaptive nonlocal means filtering based on local noise level for CT denoising

    International Nuclear Information System (INIS)

    Li, Zhoubo; Trzasko, Joshua D.; Lake, David S.; Blezek, Daniel J.; Manduca, Armando; Yu, Lifeng; Fletcher, Joel G.; McCollough, Cynthia H.

    2014-01-01

    Purpose: To develop and evaluate an image-domain noise reduction method based on a modified nonlocal means (NLM) algorithm that is adaptive to local noise level of CT images and to implement this method in a time frame consistent with clinical workflow. Methods: A computationally efficient technique for local noise estimation directly from CT images was developed. A forward projection, based on a 2D fan-beam approximation, was used to generate the projection data, with a noise model incorporating the effects of the bowtie filter and automatic exposure control. The noise propagation from projection data to images was analytically derived. The analytical noise map was validated using repeated scans of a phantom. A 3D NLM denoising algorithm was modified to adapt its denoising strength locally based on this noise map. The performance of this adaptive NLM filter was evaluated in phantom studies in terms of in-plane and cross-plane high-contrast spatial resolution, noise power spectrum (NPS), subjective low-contrast spatial resolution using the American College of Radiology (ACR) accreditation phantom, and objective low-contrast spatial resolution using a channelized Hotelling model observer (CHO). Graphical processing units (GPU) implementation of this noise map calculation and the adaptive NLM filtering were developed to meet demands of clinical workflow. Adaptive NLM was piloted on lower dose scans in clinical practice. Results: The local noise level estimation matches the noise distribution determined from multiple repetitive scans of a phantom, demonstrated by small variations in the ratio map between the analytical noise map and the one calculated from repeated scans. The phantom studies demonstrated that the adaptive NLM filter can reduce noise substantially without degrading the high-contrast spatial resolution, as illustrated by modulation transfer function and slice sensitivity profile results. The NPS results show that adaptive NLM denoising preserves the

  1. Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions

    DEFF Research Database (Denmark)

    Hansen, Per Christian; Jensen, Søren Holdt

    2007-01-01

    We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... with working Matlab code and applications in speech processing....

  2. Current Background Noise Sources and Levels in the NASA Ames 40- by 80-Foot Wind Tunnel: A Status Report

    Science.gov (United States)

    Allen, Christopher S.; Jaeger, Stephen; Soderman, Paul; Koga, Dennis (Technical Monitor)

    1999-01-01

    Background noise measurements were made of the acoustic environment in the National Full-Scale Aerodynamics Complex 40- by 80-Foot Wind Tunnel (40x80) at NASA Ames Research Center. The measurements were acquired subsequent to the 40x80 Aeroacoustic Modernization Project, which was undertaken to improve the anechoic characteristics of the 40x80's closed test section as well as reduce the levels of background noise in the facility. The resulting 40x80 anechoic environment was described by Soderman et. al., and the current paper describes the resulting 40x80 background noise, discusses the sources of the noise, and draws comparisons to previous 40x80 background noise levels measurements. At low wind speeds or low frequencies, the 40x80 background noise is dominated by the fan drive system. To obtain the lowest fan drive noise for a given tunnel condition, it is possible in the 40x80 to reduce the fans' rotational speed and adjust the fans' blade pitch, as described by Schmidtz et. al. This idea is not new, but has now been operationally implemented with modifications for increased power at low rotational speeds. At low to mid-frequencies and at higher wind speeds, the dominant noise mechanism was thought to be caused by the surface interface of the previous test section floor acoustic lining. In order to reduce this noise mechanism, the new test section floor lining was designed to resist the pumping of flow in and out of the space between the grating slats required to support heavy equipment. In addition, the lining/flow interface over the entire test section was designed to be smoother and quieter than the previous design. At high wind speeds or high frequencies, the dominant source of background noise in the 40x80 is believed to be caused by the response of the in-flow microphone probes (required by the nature of the closed test section) to the fluctuations in the freestream flow. The resulting background noise levels are also different for probes of various

  3. A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

    Directory of Open Access Journals (Sweden)

    W. Lu

    2017-09-01

    Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  4. Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method

    International Nuclear Information System (INIS)

    Azizipanah-Abarghooee, Rasoul; Niknam, Taher; Roosta, Alireza; Malekpour, Ahmad Reza; Zare, Mohsen

    2012-01-01

    In this paper, wind power generators are being incorporated in the multiobjective economic emission dispatch problem which minimizes wind-thermal electrical energy cost and emissions produced by fossil-fueled power plants, simultaneously. Large integration of wind energy sources necessitates an efficient model to cope with uncertainty arising from random wind variation. Hence, a multiobjective stochastic search algorithm based on 2m point estimated method is implemented to analyze the probabilistic wind-thermal economic emission dispatch problem considering both overestimation and underestimation of available wind power. 2m point estimated method handles the system uncertainties and renders the probability density function of desired variables efficiently. Moreover, a new population-based optimization algorithm called modified teaching-learning algorithm is proposed to determine the set of non-dominated optimal solutions. During the simulation, the set of non-dominated solutions are kept in an external memory (repository). Also, a fuzzy-based clustering technique is implemented to control the size of the repository. In order to select the best compromise solution from the repository, a niching mechanism is utilized such that the population will move toward a smaller search space in the Pareto-optimal front. In order to show the efficiency and feasibility of the proposed framework, three different test systems are represented as case studies. -- Highlights: ► WPGs are being incorporated in the multiobjective economic emission dispatch problem. ► 2m PEM handles the system uncertainties. ► A MTLBO is proposed to determine the set of non-dominated (Pareto) optimal solutions. ► A fuzzy-based clustering technique is implemented to control the size of the repository.

  5. Application of genetic algorithm in electrical system optimization for offshore wind farms

    DEFF Research Database (Denmark)

    Chen, Zhe; Zhao, M.; Blaabjerg, Frede

    2008-01-01

    Genetic Algorithm (GA) has been widely used in solving optimization problem in different areas. This paper illustrates the application of GA in the electrical system design for offshore wind farms, where the main components of a wind farm and key technical specifications are used as input...

  6. Wind turbine noise reduction. An indicative cost estimation; Sanering windturbinegeluid. Een indicatieve raming van kosten

    Energy Technology Data Exchange (ETDEWEB)

    Verheijen, E.N.G.; Jabben, J.

    2011-11-15

    Since the 1st of January 2011 new rules apply for wind turbine noise. The rules include a different calculation method and different noise limits, intended for new wind turbines. In order to tackle noise annoyance from existing wind turbines the government is considering to set up a abatement operation, for which a cost estimate is given in this study. At an abatement limit of 47 decibel L{sub den} (Level day-evening-night) approximately 450 dwellings would be eligible for noise remediation. The costs of this operation are estimated at 4.9 million euro. However, in many of these cases the wind turbine is probably owned by the respective residents. It is possible that public funds for noise remediation will not be allocated to the owners of dwellings that directly profit from the turbines. If these cases are excluded, the abatement operation would cover 165 to 275 dwellings with estimated costs for remediation of 1.6 to 2.6 million euro. A tentative cost-benefit analysis suggests that noise remediation will be cost effective in most situations. This means that the benefits of reduced annoyance or sleep disturbance are in balance with the cost of remediation. Only for the small group of wind turbines that are in use for over fifteen years, remediation will not be cost effective. These wind turbines are nearing the end of their lifespan and are therefore ignored in the above estimates. [Dutch] Sinds 1 januari 2011 zijn nieuwe regels rond windturbinegeluid van kracht. Bij de nieuwe regelgeving hoort een andere berekeningsmethode en normstelling, bedoeld voor nieuw te plaatsen windturbines. Voor de aanpak van de geluidhinder door bestaande windturbines overweegt de overheid een saneringsoperatie op te zetten, waarvoor in dit onderzoek een kostenraming wordt gegeven. Bij een saneringsgrenswaarde van 47 decibel zouden ongeveer 450 woningen voor sanering in aanmerking komen. De kosten voor sanering daarvan worden geschat op 4,9 miljoen euro. Bij een groot deel van deze

  7. Practical options for selecting data-driven or physics-based prognostics algorithms with reviews

    International Nuclear Information System (INIS)

    An, Dawn; Kim, Nam H.; Choi, Joo-Ho

    2015-01-01

    This paper is to provide practical options for prognostics so that beginners can select appropriate methods for their fields of application. To achieve this goal, several popular algorithms are first reviewed in the data-driven and physics-based prognostics methods. Each algorithm’s attributes and pros and cons are analyzed in terms of model definition, model parameter estimation and ability to handle noise and bias in data. Fatigue crack growth examples are then used to illustrate the characteristics of different algorithms. In order to suggest a suitable algorithm, several studies are made based on the number of data sets, the level of noise and bias, availability of loading and physical models, and complexity of the damage growth behavior. Based on the study, it is concluded that the Gaussian process is easy and fast to implement, but works well only when the covariance function is properly defined. The neural network has the advantage in the case of large noise and complex models but only with many training data sets. The particle filter and Bayesian method are superior to the former methods because they are less affected by noise and model complexity, but work only when physical model and loading conditions are available. - Highlights: • Practical review of data-driven and physics-based prognostics are provided. • As common prognostics algorithms, NN, GP, PF and BM are introduced. • Algorithms’ attributes, pros and cons, and applicable conditions are discussed. • This will be helpful to choose the best algorithm for different applications

  8. Static economic dispatch incorporating wind farm using Flower pollination algorithm

    Directory of Open Access Journals (Sweden)

    Suresh Velamuri

    2016-09-01

    Full Text Available Renewable energy is one of the clean and cheapest forms of energy which helps in minimizing the carbon foot print. Due to the less environmental impact and economic issues integration of renewable energy sources with the existing network gained attention. In this paper, the impact of wind energy is analysed in a power system network using static economic dispatch (SED. The wind energy is integrated with the existing thermal systems. Here, the generation scheduling is optimized using Flower pollination algorithm (FPA due to its robustness in solving nonlinear problems. Integration of wind power in the existing system increases the complexity due to its stochastic nature. Weibull distribution function is used for solving the stochastic nature of wind. Scenarios without and with wind power penetration are discussed in detail. The analysis is carried out by considering the losses and installing the wind farm at different locations in the system. The proposed methodology is tested and validated on a standard IEEE 30 bus system.

  9. Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions

    DEFF Research Database (Denmark)

    Hansen, Per Christian; Jensen, Søren Holdt

    We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV and ULLIV). In addition we show how the subspace-based algorithms can be evaluated and compared by means of simple FIR filter interpretations. The algorithms are illustrated...... with working Matlab code and applications in speech processing....

  10. Design and preliminary test results at Mach 5 of an axisymmetric slotted sound shield. [for supersonic wind tunnels (noise reduction in wind tunnel nozzles)

    Science.gov (United States)

    Beckwith, I. E.; Spokowski, A. J.; Harvey, W. D.; Stainback, P. C.

    1975-01-01

    The basic theory and sound attenuation mechanisms, the design procedures, and preliminary experimental results are presented for a small axisymmetric sound shield for supersonic wind tunnels. The shield consists of an array of small diameter rods aligned nearly parallel to the entrance flow with small gaps between the rods for boundary layer suction. Results show that at the lowest test Reynolds number (based on rod diameter) of 52,000 the noise shield reduced the test section noise by about 60 percent ( or 8 db attenuation) but no attenuation was measured for the higher range of test reynolds numbers from 73,000 to 190,000. These results are below expectations based on data reported elsewhere on a flat sound shield model. The smaller attenuation from the present tests is attributed to insufficient suction at the gaps to prevent feedback of vacuum manifold noise into the shielded test flow and to insufficient suction to prevent transition of the rod boundary layers to turbulent flow at the higher Reynolds numbers. Schlieren photographs of the flow are shown.

  11. Systematic classification and identification of noise spectra using perception-based neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Racz, A.; Kiss, S. (KFKI-Atomic Energy Research Inst., Budapest (Hungary). Applied Reactor Physics Lab.)

    1994-01-01

    A general framework for the detection of gradually developing changes in a noise generating system is presented. The procedure is based on a new learning algorithm developed for neural networks with dynamically building architecture. The method has been tested by using almost a thousand noise spectra recorded from different detector types and from different detector positions. This work is part of a larger project, aimed at developing a noise diagnostic expert system. (author).

  12. A method of optimized neural network by L-M algorithm to transformer winding hot spot temperature forecasting

    Science.gov (United States)

    Wei, B. G.; Wu, X. Y.; Yao, Z. F.; Huang, H.

    2017-11-01

    Transformers are essential devices of the power system. The accurate computation of the highest temperature (HST) of a transformer’s windings is very significant, as for the HST is a fundamental parameter in controlling the load operation mode and influencing the life time of the insulation. Based on the analysis of the heat transfer processes and the thermal characteristics inside transformers, there is taken into consideration the influence of factors like the sunshine, external wind speed etc. on the oil-immersed transformers. Experimental data and the neural network are used for modeling and protesting of the HST, and furthermore, investigations are conducted on the optimization of the structure and algorithms of neutral network are conducted. Comparison is made between the measured values and calculated values by using the recommended algorithm of IEC60076 and by using the neural network algorithm proposed by the authors; comparison that shows that the value computed with the neural network algorithm approximates better the measured value than the value computed with the algorithm proposed by IEC60076.

  13. Filtered-X Affine Projection Algorithms for Active Noise Control Using Volterra Filters

    Directory of Open Access Journals (Sweden)

    Sicuranza Giovanni L

    2004-01-01

    Full Text Available We consider the use of adaptive Volterra filters, implemented in the form of multichannel filter banks, as nonlinear active noise controllers. In particular, we discuss the derivation of filtered-X affine projection algorithms for homogeneous quadratic filters. According to the multichannel approach, it is then easy to pass from these algorithms to those of a generic Volterra filter. It is shown in the paper that the AP technique offers better convergence and tracking capabilities than the classical LMS and NLMS algorithms usually applied in nonlinear active noise controllers, with a limited complexity increase. This paper extends in two ways the content of a previous contribution published in Proc. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03, Grado, Italy, June 2003. First of all, a general adaptation algorithm valid for any order of affine projections is presented. Secondly, a more complete set of experiments is reported. In particular, the effects of using multichannel filter banks with a reduced number of channels are investigated and relevant results are shown.

  14. The use of ground reflecting boards in measuring wind turbine noise

    International Nuclear Information System (INIS)

    Henderson, A.R.; Mackinnon, A.; Benson, I.M.

    1992-01-01

    This paper gives an account of an experimental programme to assess the ground microphone measurement technique which can potentially increase the accuracy, reliability and confidence in wind turbine noise emission measurements. It shows that a 1 m diameter circular board can achieve acceptable accuracy and, since it is significantly more practical to use, could readily be adopted for international standards. (author)

  15. Robust MST-Based Clustering Algorithm.

    Science.gov (United States)

    Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

    2018-06-01

    Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

  16. Optimised operation of an off-grid hybrid wind-diesel-battery system using genetic algorithm

    International Nuclear Information System (INIS)

    Gan, Leong Kit; Shek, Jonathan K.H.; Mueller, Markus A.

    2016-01-01

    Highlights: • Diesel generator’s operation is optimised in a hybrid wind-diesel-battery system. • Optimisation is performed using wind speed and load demand forecasts. • The objective is to maximise wind energy utilisation with limited battery storage. • Physical modelling approach (Simscape) is used to verify mathematical model. • Sensitivity analyses are performed with synthesised wind and load forecast errors. - Abstract: In an off-grid hybrid wind-diesel-battery system, the diesel generator is often not utilised efficiently, therefore compromising its lifetime. In particular, the general rule of thumb of running the diesel generator at more than 40% of its rated capacity is often unmet. This is due to the variation in power demand and wind speed which needs to be supplied by the diesel generator. In addition, the frequent start-stop of the diesel generator leads to additional mechanical wear and fuel wastage. This research paper proposes a novel control algorithm which optimises the operation of a diesel generator, using genetic algorithm. With a given day-ahead forecast of local renewable energy resource and load demand, it is possible to optimise the operation of a diesel generator, subjected to other pre-defined constraints. Thus, the utilisation of the renewable energy sources to supply electricity can be maximised. Usually, the optimisation studies of a hybrid system are being conducted through simple analytical modelling, coupled with a selected optimisation algorithm to seek the optimised solution. The obtained solution is not verified using a more realistic system model, for instance the physical modelling approach. This often led to the question of the applicability of such optimised operation being used in reality. In order to take a step further, model-based design using Simulink is employed in this research to perform a comparison through a physical modelling approach. The Simulink model has the capability to incorporate the electrical

  17. A triangle voting algorithm based on double feature constraints for star sensors

    Science.gov (United States)

    Fan, Qiaoyun; Zhong, Xuyang

    2018-02-01

    A novel autonomous star identification algorithm is presented in this study. In the proposed algorithm, each sensor star constructs multi-triangle with its bright neighbor stars and obtains its candidates by triangle voting process, in which the triangle is considered as the basic voting element. In order to accelerate the speed of this algorithm and reduce the required memory for star database, feature extraction is carried out to reduce the dimension of triangles and each triangle is described by its base and height. During the identification period, the voting scheme based on double feature constraints is proposed to implement triangle voting. This scheme guarantees that only the catalog star satisfying two features can vote for the sensor star, which improves the robustness towards false stars. The simulation and real star image test demonstrate that compared with the other two algorithms, the proposed algorithm is more robust towards position noise, magnitude noise and false stars.

  18. China's experimental pragmatics of "Scientific development" in wind power: Algorithmic struggles over software in wind turbines

    DEFF Research Database (Denmark)

    Kirkegaard, Julia

    2016-01-01

    . This increased focus on quality, to ensure the sustainable and scientific development of China's wind energy market, requires improved indigenous Chinese innovation capabilities in wind turbine technology. To shed light on how the turn to quality impacts upon the industry and global competition, this study......This article presents a case study on the development of China's wind power market. As China's wind industry has experienced a quality crisis, the Chinese government has intervened to steer the industry towards a turn to quality, indicating a pragmatist and experimental mode of market development...... unfold over issues associated with intellectual property rights (IPRs), certification and standardisation of software algorithms. The article concludes that the use of this STS lens makes a fresh contribution to the often path-dependent, structuralist and hierarchical China literature, offering instead...

  19. Recommendation of maximum allowable noise levels for offshore wind power systems; Empfehlung von Laermschutzwerten bei der Errichtung von Offshore-Windenergieanlagen (OWEA)

    Energy Technology Data Exchange (ETDEWEB)

    Werner, Stefanie [Umweltbundesamt, Dessau-Rosslau (Germany). Fachgebiet II 2.3

    2011-05-15

    When offshore wind farms are constructed, every single pile is hammered into the sediment by a hydraulic hammer. Noise levels at Horns Reef wind farm were in the range of 235 dB. The noise may cause damage to the auditory system of marine mammals. The Federal Environmental Office therefore recommends the definition of maximum permissible noise levels. Further, care should be taken that no marine mammals are found in the immediate vicinity of the construction site. (AKB)

  20. Wind turbines and human health

    Directory of Open Access Journals (Sweden)

    Loren eKnopper

    2014-06-01

    Full Text Available The association between wind turbines and health effects is highly debated. Some argue that reported health effects are related to wind turbine operation (electromagnetic fields (EMF, shadow flicker, audible noise, low frequency noise, infrasound. Others suggest that when turbines are sited correctly, effects are more likely attributable to a number of subjective variables that result in an annoyed/stressed state. In this review we provide a bibliographic-like summary and analysis of the science around this issue specifically in terms of noise (including audible, low frequency noise and infrasound, EMF and shadow flicker. Now there are roughly 60 scientific peer-reviewed articles on this issue. The available scientific evidence suggests that EMF, shadow flicker, low frequency noise and infrasound from wind turbines are not likely to affect human health; some studies have found that audible noise from wind turbines can be annoying to some. Annoyance may be associated with some self-reported health effects (e.g., sleep disturbance especially at sound pressure levels >40 dB(A. Because environmental noise above certain levels is a recognized factor in a number of health issues, siting restrictions have been implemented in many jurisdictions to limit noise exposure. These setbacks should help alleviate annoyance from noise. Subjective variables (attitudes and expectations are also linked to annoyance and have the potential to facilitate other health complaints via the nocebo effect. Therefore, it is possible that a segment of the population may remain annoyed (or report other health impacts even when noise limits are enforced. Based on the findings and scientific merit of the available studies, the weight of evidence suggests that when sited properly, wind turbines are not related to adverse health. Stemming from this review, we provide a number of recommended best practices for wind turbine development in the context of human health.

  1. Wind turbines and human health.

    Science.gov (United States)

    Knopper, Loren D; Ollson, Christopher A; McCallum, Lindsay C; Whitfield Aslund, Melissa L; Berger, Robert G; Souweine, Kathleen; McDaniel, Mary

    2014-01-01

    The association between wind turbines and health effects is highly debated. Some argue that reported health effects are related to wind turbine operation [electromagnetic fields (EMF), shadow flicker, audible noise, low-frequency noise, infrasound]. Others suggest that when turbines are sited correctly, effects are more likely attributable to a number of subjective variables that result in an annoyed/stressed state. In this review, we provide a bibliographic-like summary and analysis of the science around this issue specifically in terms of noise (including audible, low-frequency noise, and infrasound), EMF, and shadow flicker. Now there are roughly 60 scientific peer-reviewed articles on this issue. The available scientific evidence suggests that EMF, shadow flicker, low-frequency noise, and infrasound from wind turbines are not likely to affect human health; some studies have found that audible noise from wind turbines can be annoying to some. Annoyance may be associated with some self-reported health effects (e.g., sleep disturbance) especially at sound pressure levels >40 dB(A). Because environmental noise above certain levels is a recognized factor in a number of health issues, siting restrictions have been implemented in many jurisdictions to limit noise exposure. These setbacks should help alleviate annoyance from noise. Subjective variables (attitudes and expectations) are also linked to annoyance and have the potential to facilitate other health complaints via the nocebo effect. Therefore, it is possible that a segment of the population may remain annoyed (or report other health impacts) even when noise limits are enforced. Based on the findings and scientific merit of the available studies, the weight of evidence suggests that when sited properly, wind turbines are not related to adverse health. Stemming from this review, we provide a number of recommended best practices for wind turbine development in the context of human health.

  2. Wind Turbines and Human Health

    Science.gov (United States)

    Knopper, Loren D.; Ollson, Christopher A.; McCallum, Lindsay C.; Whitfield Aslund, Melissa L.; Berger, Robert G.; Souweine, Kathleen; McDaniel, Mary

    2014-01-01

    The association between wind turbines and health effects is highly debated. Some argue that reported health effects are related to wind turbine operation [electromagnetic fields (EMF), shadow flicker, audible noise, low-frequency noise, infrasound]. Others suggest that when turbines are sited correctly, effects are more likely attributable to a number of subjective variables that result in an annoyed/stressed state. In this review, we provide a bibliographic-like summary and analysis of the science around this issue specifically in terms of noise (including audible, low-frequency noise, and infrasound), EMF, and shadow flicker. Now there are roughly 60 scientific peer-reviewed articles on this issue. The available scientific evidence suggests that EMF, shadow flicker, low-frequency noise, and infrasound from wind turbines are not likely to affect human health; some studies have found that audible noise from wind turbines can be annoying to some. Annoyance may be associated with some self-reported health effects (e.g., sleep disturbance) especially at sound pressure levels >40 dB(A). Because environmental noise above certain levels is a recognized factor in a number of health issues, siting restrictions have been implemented in many jurisdictions to limit noise exposure. These setbacks should help alleviate annoyance from noise. Subjective variables (attitudes and expectations) are also linked to annoyance and have the potential to facilitate other health complaints via the nocebo effect. Therefore, it is possible that a segment of the population may remain annoyed (or report other health impacts) even when noise limits are enforced. Based on the findings and scientific merit of the available studies, the weight of evidence suggests that when sited properly, wind turbines are not related to adverse health. Stemming from this review, we provide a number of recommended best practices for wind turbine development in the context of human health. PMID:24995266

  3. Application of a Dynamic Fuzzy Search Algorithm to Determine Optimal Wind Plant Sizes and Locations in Iowa

    International Nuclear Information System (INIS)

    Milligan, M. R.; Factor, T.

    2001-01-01

    This paper illustrates a method for choosing the optimal mix of wind capacity at several geographically dispersed locations. The method is based on a dynamic fuzzy search algorithm that can be applied to different optimization targets. We illustrate the method using two objective functions for the optimization: maximum economic benefit and maximum reliability. We also illustrate the sensitivity of the fuzzy economic benefit solutions to small perturbations of the capacity selections at each wind site. We find that small changes in site capacity and/or location have small effects on the economic benefit provided by wind power plants. We use electric load and generator data from Iowa, along with high-quality wind-speed data collected by the Iowa Wind Energy Institute

  4. Application of a Dynamic Fuzzy Search Algorithm to Determine Optimal Wind Plant Sizes and Locations in Iowa

    Energy Technology Data Exchange (ETDEWEB)

    Milligan, M. R., National Renewable Energy Laboratory; Factor, T., Iowa Wind Energy Institute

    2001-09-21

    This paper illustrates a method for choosing the optimal mix of wind capacity at several geographically dispersed locations. The method is based on a dynamic fuzzy search algorithm that can be applied to different optimization targets. We illustrate the method using two objective functions for the optimization: maximum economic benefit and maximum reliability. We also illustrate the sensitivity of the fuzzy economic benefit solutions to small perturbations of the capacity selections at each wind site. We find that small changes in site capacity and/or location have small effects on the economic benefit provided by wind power plants. We use electric load and generator data from Iowa, along with high-quality wind-speed data collected by the Iowa Wind Energy Institute.

  5. WHO Environmental Noise Guidelines for the European Region: A Systematic Review on Environmental Noise and Annoyance

    Directory of Open Access Journals (Sweden)

    Rainer Guski

    2017-12-01

    Full Text Available Background: This paper describes a systematic review and meta-analyses on effects of environmental noise on annoyance. The noise sources include aircraft, road, and rail transportation noise as well as wind turbines and noise source combinations. Objectives: Update knowledge about effects of environmental noise on people living in the vicinity of noise sources. Methods: Eligible were published studies (2000–2014 providing comparable acoustical and social survey data including exposure-response functions between standard indicators of noise exposure and standard annoyance responses. The systematic literature search in 20 data bases resulted in 62 studies, of which 57 were used for quantitative meta-analyses. By means of questionnaires sent to the study authors, additional study data were obtained. Risk of bias was assessed by means of study characteristics for individual studies and by funnel plots to assess the risk of publication bias. Main Results: Tentative exposure-response relations for percent highly annoyed residents (%HA in relation to noise levels for aircraft, road, rail, wind turbine and noise source combinations are presented as well as meta-analyses of correlations between noise levels and annoyance raw scores, and the OR for increase of %HA with increasing noise levels. Quality of evidence was assessed using the GRADE terminology. The evidence of exposure-response relations between noise levels and %HA is moderate (aircraft and railway or low (road traffic and wind turbines. The evidence of correlations between noise levels and annoyance raw scores is high (aircraft and railway or moderate (road traffic and wind turbines. The evidence of ORs representing the %HA increase by a certain noise level increase is moderate (aircraft noise, moderate/high (road and railway traffic, and low (wind turbines. Strengths and Limitations: The strength of the evidence is seen in the large total sample size encompassing the included studies (e

  6. Static and wind tunnel near-field/far-field jet noise measurements from model scale single-flow base line and suppressor nozzles. Summary report. [conducted in the Boeing large anechoic test chamber and the NASA-Ames 40by 80-foot wind tunnel

    Science.gov (United States)

    Jaeck, C. L.

    1977-01-01

    A test program was conducted in the Boeing large anechoic test chamber and the NASA-Ames 40- by 80-foot wind tunnel to study the near- and far-field jet noise characteristics of six baseline and suppressor nozzles. Static and wind-on noise source locations were determined. A technique for extrapolating near field jet noise measurements into the far field was established. It was determined if flight effects measured in the near field are the same as those in the far field. The flight effects on the jet noise levels of the baseline and suppressor nozzles were determined. Test models included a 15.24-cm round convergent nozzle, an annular nozzle with and without ejector, a 20-lobe nozzle with and without ejector, and a 57-tube nozzle with lined ejector. The static free-field test in the anechoic chamber covered nozzle pressure ratios from 1.44 to 2.25 and jet velocities from 412 to 594 m/s at a total temperature of 844 K. The wind tunnel flight effects test repeated these nozzle test conditions with ambient velocities of 0 to 92 m/s.

  7. Time Series Analysis and Forecasting for Wind Speeds Using Support Vector Regression Coupled with Artificial Intelligent Algorithms

    Directory of Open Access Journals (Sweden)

    Ping Jiang

    2015-01-01

    Full Text Available Wind speed/power has received increasing attention around the earth due to its renewable nature as well as environmental friendliness. With the global installed wind power capacity rapidly increasing, wind industry is growing into a large-scale business. Reliable short-term wind speed forecasts play a practical and crucial role in wind energy conversion systems, such as the dynamic control of wind turbines and power system scheduling. In this paper, an intelligent hybrid model for short-term wind speed prediction is examined; the model is based on cross correlation (CC analysis and a support vector regression (SVR model that is coupled with brainstorm optimization (BSO and cuckoo search (CS algorithms, which are successfully utilized for parameter determination. The proposed hybrid models were used to forecast short-term wind speeds collected from four wind turbines located on a wind farm in China. The forecasting results demonstrate that the intelligent hybrid models outperform single models for short-term wind speed forecasting, which mainly results from the superiority of BSO and CS for parameter optimization.

  8. Fermeuse wind power project Newfoundland : noise and visual analysis studies

    Energy Technology Data Exchange (ETDEWEB)

    Henn, P.; Turgeon, J.; Heraud, P.; Belanger, S.; Dakousian, S.; Lamontagne, C.; Soares, D. [Helimax Energy Inc., Montreal, PQ (Canada); Basil, C.; Boulianne, S.; Salacup, S.; Thompson, C. [Skypower, Toronto, ON (Canada)

    2008-03-15

    This paper discussed the noise and visual analyses used to assess the potential impacts of a wind energy project on the east coast of the Avalon Peninsula near St. John's, Newfoundland. The proposed farm will be located approximately 1 km away from the town of Fermeuse, and will have an installed capacity of 27 MW from 9 turbines. The paper provided details of the consultation process conducted to determine acceptable distance and site locations for the wind turbines from the community. Stakeholders were identified during meetings, events, and discussions with local authorities. Consultations were also held with government agencies and municipal councils. A baseline acoustic environment study was conducted, and details of anticipated environmental impacts during the project's construction, operation, and decommissioning phases were presented. The visual analysis study was divided into the following landscape units: town, shoreline, forest, open land and lacustrine landscapes. The effect of the turbines on the landscapes were assessed from different viewpoints using visual simulation programs. The study showed that the visual effects of the project are not considered as significant because of the low number of turbines. It was concluded that the effect of construction on ambient noise levels is of low concern as all permanent dwellings are located at least 1 km away from the turbines. 2 refs., 4 tabs., 4 figs.

  9. Wavelet tree structure based speckle noise removal for optical coherence tomography

    Science.gov (United States)

    Yuan, Xin; Liu, Xuan; Liu, Yang

    2018-02-01

    We report a new speckle noise removal algorithm in optical coherence tomography (OCT). Though wavelet domain thresholding algorithms have demonstrated superior advantages in suppressing noise magnitude and preserving image sharpness in OCT, the wavelet tree structure has not been investigated in previous applications. In this work, we propose an adaptive wavelet thresholding algorithm via exploiting the tree structure in wavelet coefficients to remove the speckle noise in OCT images. The threshold for each wavelet band is adaptively selected following a special rule to retain the structure of the image across different wavelet layers. Our results demonstrate that the proposed algorithm outperforms conventional wavelet thresholding, with significant advantages in preserving image features.

  10. A Digital Image Denoising Algorithm Based on Gaussian Filtering and Bilateral Filtering

    Directory of Open Access Journals (Sweden)

    Piao Weiying

    2018-01-01

    Full Text Available Bilateral filtering has been applied in the area of digital image processing widely, but in the high gradient region of the image, bilateral filtering may generate staircase effect. Bilateral filtering can be regarded as one particular form of local mode filtering, according to above analysis, an mixed image de-noising algorithm is proposed based on Gaussian filter and bilateral filtering. First of all, it uses Gaussian filter to filtrate the noise image and get the reference image, then to take both the reference image and noise image as the input for range kernel function of bilateral filter. The reference image can provide the image’s low frequency information, and noise image can provide image’s high frequency information. Through the competitive experiment on both the method in this paper and traditional bilateral filtering, the experimental result showed that the mixed de-noising algorithm can effectively overcome staircase effect, and the filtrated image was more smooth, its textural features was also more close to the original image, and it can achieve higher PSNR value, but the amount of calculation of above two algorithms are basically the same.

  11. [Comfort of crew and passengers and atmospheric pressure, noise, wind speed in high-speed train of Shijiazhuang-Taiyuan passenger dedicated line].

    Science.gov (United States)

    Zhai, Yi-biao; Huo, Wei; Liu, Qiao-ying; Chen, Bao-shan; Zhang, Jin-long; Shi, Lei

    2012-11-01

    To explore the crew and passengers' comfort on the Shijiazhuang-Taiyuan passenger dedicated line and physical factors, such as air pressure, noise, wind speed. Comfort investigation of all the crew (n = 244) and passengers (n = 377) on the Shijiazhuang-Taiyuan passenger dedicated line at speed of 250 km/h and 200 km/h and the detection of the air pressure, noise and wind speed were performed in 2011. Significantly higher ratio of comfortable feeling, lower ratio of seriously discomfortable feeling were observed in crew and passengers at 200 km/h compared with those at 250 km/h (P noise in passengers at 200 km/h. No significant difference was observed in ear discomfort induced by air pressure and noise among crew, and the duration of disappearance of discomfortable feeling among passengers between 200 km/h and 250 km/h. The noise in carriages exceeded the related standard when the high-speed train passing through the tunnels. The individuals feel more comfortable at 200 km/h than 250 km/h in this line., which may be related with rapid variation of wind speed and noise when the train passes through the tunnels with high speed.

  12. Assimilation of low-level wind in a high-resolution mesoscale model using the back and forth nudging algorithm

    Directory of Open Access Journals (Sweden)

    Jean-François Mahfouf

    2012-06-01

    Full Text Available The performance of a new data assimilation algorithm called back and forth nudging (BFN is evaluated using a high-resolution numerical mesoscale model and simulated wind observations in the boundary layer. This new algorithm, of interest for the assimilation of high-frequency observations provided by ground-based active remote-sensing instruments, is straightforward to implement in a realistic atmospheric model. The convergence towards a steady-state profile can be achieved after five iterations of the BFN algorithm, and the algorithm provides an improved solution with respect to direct nudging. It is shown that the contribution of the nudging term does not dominate over other model physical and dynamical tendencies. Moreover, by running backward integrations with an adiabatic version of the model, the nudging coefficients do not need to be increased in order to stabilise the numerical equations. The ability of BFN to produce model changes upstream from the observations, in a similar way to 4-D-Var assimilation systems, is demonstrated. The capacity of the model to adjust to rapid changes in wind direction with the BFN is a first encouraging step, for example, to improve the detection and prediction of low-level wind shear phenomena through high-resolution mesoscale modelling over airports.

  13. Genetic Algorithm-Based Identification of Fractional-Order Systems

    Directory of Open Access Journals (Sweden)

    Shengxi Zhou

    2013-05-01

    Full Text Available Fractional calculus has become an increasingly popular tool for modeling the complex behaviors of physical systems from diverse domains. One of the key issues to apply fractional calculus to engineering problems is to achieve the parameter identification of fractional-order systems. A time-domain identification algorithm based on a genetic algorithm (GA is proposed in this paper. The multi-variable parameter identification is converted into a parameter optimization by applying GA to the identification of fractional-order systems. To evaluate the identification accuracy and stability, the time-domain output error considering the condition variation is designed as the fitness function for parameter optimization. The identification process is established under various noise levels and excitation levels. The effects of external excitation and the noise level on the identification accuracy are analyzed in detail. The simulation results show that the proposed method could identify the parameters of both commensurate rate and non-commensurate rate fractional-order systems from the data with noise. It is also observed that excitation signal is an important factor influencing the identification accuracy of fractional-order systems.

  14. Statistics-Based Compression of Global Wind Fields

    KAUST Repository

    Jeong, Jaehong

    2017-02-07

    Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth\\'s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

  15. Statistics-Based Compression of Global Wind Fields

    KAUST Repository

    Jeong, Jaehong; Castruccio, Stefano; Crippa, Paola; Genton, Marc G.

    2017-01-01

    Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth's orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

  16. UDE-based control of variable-speed wind turbine systems

    Science.gov (United States)

    Ren, Beibei; Wang, Yeqin; Zhong, Qing-Chang

    2017-01-01

    In this paper, the control of a PMSG (permanent magnet synchronous generator)-based variable-speed wind turbine system with a back-to-back converter is considered. The uncertainty and disturbance estimator (UDE)-based control approach is applied to the regulation of the DC-link voltage and the control of the RSC (rotor-side converter) and the GSC (grid-side converter). For the rotor-side controller, the UDE-based vector control is developed for the RSC with PMSG control to facilitate the application of the MPPT (maximum power point tracking) algorithm for the maximum wind energy capture. For the grid-side controller, the UDE-based vector control is developed to control the GSC with the power reference generated by a UDE-based DC-link voltage controller. Compared with the conventional vector control, the UDE-based vector control can achieve reliable current decoupling control with fast response. Moreover, the UDE-based DC-link voltage regulation can achieve stable DC-link voltage under model uncertainties and external disturbances, e.g. wind speed variations. The effectiveness of the proposed UDE-based control approach is demonstrated through extensive simulation studies in the presence of coupled dynamics, model uncertainties and external disturbances under varying wind speeds. The UDE-based control is able to generate more energy, e.g. by 5% for the wind profile tested.

  17. Improved Density Based Spatial Clustering of Applications of Noise Clustering Algorithm for Knowledge Discovery in Spatial Data

    Directory of Open Access Journals (Sweden)

    Arvind Sharma

    2016-01-01

    Full Text Available There are many techniques available in the field of data mining and its subfield spatial data mining is to understand relationships between data objects. Data objects related with spatial features are called spatial databases. These relationships can be used for prediction and trend detection between spatial and nonspatial objects for social and scientific reasons. A huge data set may be collected from different sources as satellite images, X-rays, medical images, traffic cameras, and GIS system. To handle this large amount of data and set relationship between them in a certain manner with certain results is our primary purpose of this paper. This paper gives a complete process to understand how spatial data is different from other kinds of data sets and how it is refined to apply to get useful results and set trends to predict geographic information system and spatial data mining process. In this paper a new improved algorithm for clustering is designed because role of clustering is very indispensable in spatial data mining process. Clustering methods are useful in various fields of human life such as GIS (Geographic Information System, GPS (Global Positioning System, weather forecasting, air traffic controller, water treatment, area selection, cost estimation, planning of rural and urban areas, remote sensing, and VLSI designing. This paper presents study of various clustering methods and algorithms and an improved algorithm of DBSCAN as IDBSCAN (Improved Density Based Spatial Clustering of Application of Noise. The algorithm is designed by addition of some important attributes which are responsible for generation of better clusters from existing data sets in comparison of other methods.

  18. Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality.

    Science.gov (United States)

    Keshavarzi, Mahmoud; Goehring, Tobias; Zakis, Justin; Turner, Richard E; Moore, Brian C J

    2018-01-01

    Despite great advances in hearing-aid technology, users still experience problems with noise in windy environments. The potential benefits of using a deep recurrent neural network (RNN) for reducing wind noise were assessed. The RNN was trained using recordings of the output of the two microphones of a behind-the-ear hearing aid in response to male and female speech at various azimuths in the presence of noise produced by wind from various azimuths with a velocity of 3 m/s, using the "clean" speech as a reference. A paired-comparison procedure was used to compare all possible combinations of three conditions for subjective intelligibility and for sound quality or comfort. The conditions were unprocessed noisy speech, noisy speech processed using the RNN, and noisy speech that was high-pass filtered (which also reduced wind noise). Eighteen native English-speaking participants were tested, nine with normal hearing and nine with mild-to-moderate hearing impairment. Frequency-dependent linear amplification was provided for the latter. Processing using the RNN was significantly preferred over no processing by both subject groups for both subjective intelligibility and sound quality, although the magnitude of the preferences was small. High-pass filtering (HPF) was not significantly preferred over no processing. Although RNN was significantly preferred over HPF only for sound quality for the hearing-impaired participants, for the results as a whole, there was a preference for RNN over HPF. Overall, the results suggest that reduction of wind noise using an RNN is possible and might have beneficial effects when used in hearing aids.

  19. Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality

    Science.gov (United States)

    Keshavarzi, Mahmoud; Goehring, Tobias; Zakis, Justin; Turner, Richard E.; Moore, Brian C. J.

    2018-01-01

    Despite great advances in hearing-aid technology, users still experience problems with noise in windy environments. The potential benefits of using a deep recurrent neural network (RNN) for reducing wind noise were assessed. The RNN was trained using recordings of the output of the two microphones of a behind-the-ear hearing aid in response to male and female speech at various azimuths in the presence of noise produced by wind from various azimuths with a velocity of 3 m/s, using the “clean” speech as a reference. A paired-comparison procedure was used to compare all possible combinations of three conditions for subjective intelligibility and for sound quality or comfort. The conditions were unprocessed noisy speech, noisy speech processed using the RNN, and noisy speech that was high-pass filtered (which also reduced wind noise). Eighteen native English-speaking participants were tested, nine with normal hearing and nine with mild-to-moderate hearing impairment. Frequency-dependent linear amplification was provided for the latter. Processing using the RNN was significantly preferred over no processing by both subject groups for both subjective intelligibility and sound quality, although the magnitude of the preferences was small. High-pass filtering (HPF) was not significantly preferred over no processing. Although RNN was significantly preferred over HPF only for sound quality for the hearing-impaired participants, for the results as a whole, there was a preference for RNN over HPF. Overall, the results suggest that reduction of wind noise using an RNN is possible and might have beneficial effects when used in hearing aids. PMID:29708061

  20. AUTOMATIC DETECTION ALGORITHM OF DYNAMIC PRESSURE PULSES IN THE SOLAR WIND

    International Nuclear Information System (INIS)

    Zuo, Pingbing; Feng, Xueshang; Wang, Yi; Xie, Yanqiong; Li, Huijun; Xu, Xiaojun

    2015-01-01

    Dynamic pressure pulses (DPPs) in the solar wind are a significant phenomenon closely related to the solar-terrestrial connection and physical processes of solar wind dynamics. In order to automatically identify DPPs from solar wind measurements, we develop a procedure with a three-step detection algorithm that is able to rapidly select DPPs from the plasma data stream and simultaneously define the transition region where large dynamic pressure variations occur and demarcate the upstream and downstream region by selecting the relatively quiet status before and after the abrupt change in dynamic pressure. To demonstrate the usefulness, efficiency, and accuracy of this procedure, we have applied it to the Wind observations from 1996 to 2008 by successfully obtaining the DPPs. The procedure can also be applied to other solar wind spacecraft observation data sets with different time resolutions

  1. Noise annoyances from wind power: Survey of the population living close to a wind power plant. Final report: Part 3 Main study; Stoerningar fraan vindkraft: undersoekning bland maenniskor boende i naerheten av vindkraftverk. Slutrapport: Del 3 Huvudstudie

    Energy Technology Data Exchange (ETDEWEB)

    Pedersen, Eja [Halmstad Univ., Halmstad (Sweden). School of Business and Engineering; Persson-Waye, K [Goeteborg Univ., Goeteborg (Sweden). Dept. of Environmental Medicine

    2002-02-01

    To evaluate the occurrence of annoyance from wind turbines, a study was performed in Laholm in May 2000. The aim was to obtain dose response relationships between calculated sound levels and noise annoyance and appropriate sound description as well as analysing the influence of other variables on noise annoyance. A questionnaire survey was performed in 6 areas comprising 16 wind turbines, of which 14 had an effect of 600 kW. The purpose of the study was masked. Among questions on living conditions in the countryside, questions directly related to wind turbines were included. The study population (n=518) comprised one randomly selected subject between the ages of 18 to 75 years in each household living within a calculated wind turbine sound level of 25 to 40 dBA. The response rate was 68.7% (n=356). Calculated distributions of A-weighted sound level were performed for each area and plotted on geographical maps in 2.5 dBA steps. Each dwelling could thus be given a sound level within an interval of 2.5 dBA. The most frequently occurring source of noise annoyance was noise from rotor blades. The proportions of respondents annoyed by noise increased with calculated sound level. Among respondents exposed to sound levels of 35.0-37.5 dBA, 43% responded themselves to be rather or much annoyed. A-weighted sound level was only one variable explaining annoyance. Annoyance was correlated to a larger extent by the intrusiveness of the sound character swishing. Noise annoyance was interrelated to the respondents' opinion of the visual impact of wind turbines, while attitude towards wind power in general had no greater influence. Disturbance of spoilt view was reported to a similar degree as noise disturbance. Further investigations are needed to clarify factors of importance for the disturbance of view. All the wind turbines in the study had constant rotation speed. The greater wind turbines that are now erected often have variable speed, which may lead to a sound comprising

  2. Multi-objective random search algorithm for simultaneously optimizing wind farm layout and number of turbines

    DEFF Research Database (Denmark)

    Feng, Ju; Shen, Wen Zhong; Xu, Chang

    2016-01-01

    A new algorithm for multi-objective wind farm layout optimization is presented. It formulates the wind turbine locations as continuous variables and is capable of optimizing the number of turbines and their locations in the wind farm simultaneously. Two objectives are considered. One is to maximi...

  3. Research on Wavelet-Based Algorithm for Image Contrast Enhancement

    Institute of Scientific and Technical Information of China (English)

    Wu Ying-qian; Du Pei-jun; Shi Peng-fei

    2004-01-01

    A novel wavelet-based algorithm for image enhancement is proposed in the paper. On the basis of multiscale analysis, the proposed algorithm solves efficiently the problem of noise over-enhancement, which commonly occurs in the traditional methods for contrast enhancement. The decomposed coefficients at same scales are processed by a nonlinear method, and the coefficients at different scales are enhanced in different degree. During the procedure, the method takes full advantage of the properties of Human visual system so as to achieve better performance. The simulations demonstrate that these characters of the proposed approach enable it to fully enhance the content in images, to efficiently alleviate the enhancement of noise and to achieve much better enhancement effect than the traditional approaches.

  4. Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

    Science.gov (United States)

    Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

    2014-09-09

    This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm

  5. Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

    Directory of Open Access Journals (Sweden)

    Lingli Cui

    2014-09-01

    Full Text Available This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and

  6. Utgrunden off-shore wind farm - Measurements of underwater noise

    International Nuclear Information System (INIS)

    Lindell, Hans

    2003-07-01

    Airicole, GE Wind Energy and SEAS/Energi E2 have initiated this project in order to achieve a better understanding on how offshore based wind farms effect the underwater noise. The main reason is to gain knowledge on how marine wildlife could be effected by this kind of installation. The measurements were performed at Utgrunden wind farm that is situated at the reef Utgrunden on the Swedish southeast coast. The farm consists of seven 1,5 MW turbines. Three hydrophones registered the underwater sound and four accelerometers the tower vibrations. The measurement campaign was conducted during a period from November 2002 to February 2003. The objectives with this project is to answer the following issues and its results are: 1. What is the character of sound from a single power station? - The turbines radiate sound mainly at a few dominating frequencies from 30 Hz up to 800 Hz. At frequencies below 3 Hz no contribution from the turbines can be detected due to the high background level from the waves and the low tower vibration level. 2. What are the sound generating mechanisms in the turbine? - Gearbox mesh frequency vibrations that are transmitted via the tower structure and radiated out to the water mainly generate the sound. Airborne blade sound is effectively dampened in the transition from air to water. 3. How does the sound attenuate with increasing distance at different frequencies? - The average attenuation per doubled distance for frequencies between 31 Hz and 722 Hz is approximately 4 dB in the measured positions. No clear frequency dependence could be found. 4. How does the sound pressure level vary with increasing wind speed? - With increasing wind speed, the sound pressure level increases and the dominating frequencies move upward due to increasing turbine rotational speed. 5. How does sound from different power stations interfere with each other and influence the over all sound image? - No clear tendencies of interference could be observed in this study

  7. Airfoil optimization for noise emission problem on small scale turbines

    Energy Technology Data Exchange (ETDEWEB)

    Gocmen, Tuhfe; Ozerdem, Baris [Mechanical Engineering Department, Yzmir Institute of Technology (Turkey)

    2011-07-01

    Wind power is a preferred natural resource and has had benefits for the energy industry and for the environment all over the world. However, noise emission from wind turbines is becoming a major concern today. This study paid close attention to small scale wind turbines close to urban areas and proposes an optimum number of six airfoils to address noise emission concerns and performance criteria. The optimization process aimed to decrease the noise emission levels and enhance the aerodynamic performance of a small scale wind turbine. This study determined the sources and the operating conditions of broadband noise emissions. A new design is presented which enhances aerodynamic performance and at the same time reduces airfoil self noise. It used popular aerodynamic functions and codes based on aero-acoustic empirical models. Through numerical computations and analyses, it is possible to derive useful improvements that can be made to commercial airfoils for small scale wind turbines.

  8. A compressed sensing based method with support refinement for impulse noise cancelation in DSL

    KAUST Repository

    Quadeer, Ahmed Abdul

    2013-06-01

    This paper presents a compressed sensing based method to suppress impulse noise in digital subscriber line (DSL). The proposed algorithm exploits the sparse nature of the impulse noise and utilizes the carriers, already available in all practical DSL systems, for its estimation and cancelation. Specifically, compressed sensing is used for a coarse estimate of the impulse position, an a priori information based maximum aposteriori probability (MAP) metric for its refinement, followed by least squares (LS) or minimum mean square error (MMSE) estimation for estimating the impulse amplitudes. Simulation results show that the proposed scheme achieves higher rate as compared to other known sparse estimation algorithms in literature. The paper also demonstrates the superior performance of the proposed scheme compared to the ITU-T G992.3 standard that utilizes RS-coding for impulse noise refinement in DSL signals. © 2013 IEEE.

  9. A novel hybrid approach for predicting wind farm power production based on wavelet transform, hybrid neural networks and imperialist competitive algorithm

    International Nuclear Information System (INIS)

    Aghajani, Afshin; Kazemzadeh, Rasool; Ebrahimi, Afshin

    2016-01-01

    Highlights: • Proposing a novel hybrid method for short-term prediction of wind farms with high accuracy. • Investigating the prediction accuracy for proposed method in comparison with other methods. • Investigating the effect of six types of parameters as input data on predictions. • Comparing results for 6 & 4 types of the input parameters – addition of pressure and air humidity. - Abstract: This paper proposes a novel hybrid approach to forecast electric power production in wind farms. Wavelet transform (WT) is employed to filter input data of wind power, while radial basis function (RBF) neural network is utilized for primary prediction. For better predictions the main forecasting engine is comprised of three multilayer perceptron (MLP) neural networks by different learning algorithms of Levenberg–Marquardt (LM), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Bayesian regularization (BR). Meta-heuristic technique Imperialist Competitive Algorithm (ICA) is used to optimize neural networks’ weightings in order to escape from local minima. In the forecast process, the real data of wind farms located in the southern part of Alberta, Canada, are used to train and test the proposed model. The data are a complete set of six meteorological and technical characteristics, including wind speed, wind power, wind direction, temperature, pressure, and air humidity. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. Results of optimizations indicate the superiority of the proposed method over the other mentioned techniques; and, forecasting error is remarkably reduced. For instance, the average normalized root mean square error (NRMSE) and average mean absolute percentage error (MAPE) are respectively 11% and 14% lower for the proposed method in 1-h-ahead forecasts over a 24-h period with six types of input than those for the best of the compared models.

  10. Multi-frequencies ECT algorithms to remove sodium noise in ISI of ferromagnetic SG tubes of FBR

    International Nuclear Information System (INIS)

    Mihalache, Ovidiu

    2012-01-01

    The paper presents developments and application of multi-frequency eddy current to be used during In-Service Inspection (ISI) of ferromagnetic steam generator (SG) tubes of Fast Breeder Reactors (FBR). Signal enhancement by means of multi-frequency ECT techniques are validated through 3D simulations of both signals and noise due to sodium forms around SG tube or SP. The purpose of such algorithms is to remove from ECT signal the electromagnetic noise resulting from sodium accumulated outside of SG tubes after SG vessel draining. Finite element method (FEM) simulations are used to analyse different sodium build-up scenarios observed experimentally, and to determine optimal multi-frequency ECT algorithms to suppress the most efficiently sodium noise. Also a new 'window multi-frequency' algorithm is applied and validated using 3-dimensional FEM simulations of SP and sodium forms. (author)

  11. Artificial bee colony algorithm for economic load dispatch with wind power energy

    Directory of Open Access Journals (Sweden)

    Safari Amin

    2016-01-01

    Full Text Available This paper presents an efficient Artificial Bee Colony (ABC algorithm for solving large scale economic load dispatch (ELD problems in power networks. To realize the ELD, the valve-point loading effect, system load demand, power losses, ramp rate limits and prohibited operation zones are considered here. Simulations were performed on four different power systems with 3, 6, 15 and 40 generating units and the results are compared with two forms of power systems, one power system is with a wind power generator and other power system is without a wind power generator. The results of this study reveal that the proposed approach is able to find appreciable ELD solutions than those of previous algorithms.

  12. Performance evaluation of PCA-based spike sorting algorithms.

    Science.gov (United States)

    Adamos, Dimitrios A; Kosmidis, Efstratios K; Theophilidis, George

    2008-09-01

    Deciphering the electrical activity of individual neurons from multi-unit noisy recordings is critical for understanding complex neural systems. A widely used spike sorting algorithm is being evaluated for single-electrode nerve trunk recordings. The algorithm is based on principal component analysis (PCA) for spike feature extraction. In the neuroscience literature it is generally assumed that the use of the first two or most commonly three principal components is sufficient. We estimate the optimum PCA-based feature space by evaluating the algorithm's performance on simulated series of action potentials. A number of modifications are made to the open source nev2lkit software to enable systematic investigation of the parameter space. We introduce a new metric to define clustering error considering over-clustering more favorable than under-clustering as proposed by experimentalists for our data. Both the program patch and the metric are available online. Correlated and white Gaussian noise processes are superimposed to account for biological and artificial jitter in the recordings. We report that the employment of more than three principal components is in general beneficial for all noise cases considered. Finally, we apply our results to experimental data and verify that the sorting process with four principal components is in agreement with a panel of electrophysiology experts.

  13. Model-based Bayesian signal extraction algorithm for peripheral nerves

    Science.gov (United States)

    Eggers, Thomas E.; Dweiri, Yazan M.; McCallum, Grant A.; Durand, Dominique M.

    2017-10-01

    Objective. Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time. Approach. To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms. Main results. The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity. Significance. HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of

  14. The Speech multi features fusion perceptual hash algorithm based on tensor decomposition

    Science.gov (United States)

    Huang, Y. B.; Fan, M. H.; Zhang, Q. Y.

    2018-03-01

    With constant progress in modern speech communication technologies, the speech data is prone to be attacked by the noise or maliciously tampered. In order to make the speech perception hash algorithm has strong robustness and high efficiency, this paper put forward a speech perception hash algorithm based on the tensor decomposition and multi features is proposed. This algorithm analyses the speech perception feature acquires each speech component wavelet packet decomposition. LPCC, LSP and ISP feature of each speech component are extracted to constitute the speech feature tensor. Speech authentication is done by generating the hash values through feature matrix quantification which use mid-value. Experimental results showing that the proposed algorithm is robust for content to maintain operations compared with similar algorithms. It is able to resist the attack of the common background noise. Also, the algorithm is highly efficiency in terms of arithmetic, and is able to meet the real-time requirements of speech communication and complete the speech authentication quickly.

  15. Active structural acoustic control of helicopter interior multifrequency noise using input-output-based hybrid control

    Science.gov (United States)

    Ma, Xunjun; Lu, Yang; Wang, Fengjiao

    2017-09-01

    This paper presents the recent advances in reduction of multifrequency noise inside helicopter cabin using an active structural acoustic control system, which is based on active gearbox struts technical approach. To attenuate the multifrequency gearbox vibrations and resulting noise, a new scheme of discrete model predictive sliding mode control has been proposed based on controlled auto-regressive moving average model. Its implementation only needs input/output data, hence a broader frequency range of controlled system is modelled and the burden on the state observer design is released. Furthermore, a new iteration form of the algorithm is designed, improving the developing efficiency and run speed. To verify the algorithm's effectiveness and self-adaptability, experiments of real-time active control are performed on a newly developed helicopter model system. The helicopter model can generate gear meshing vibration/noise similar to a real helicopter with specially designed gearbox and active struts. The algorithm's control abilities are sufficiently checked by single-input single-output and multiple-input multiple-output experiments via different feedback strategies progressively: (1) control gear meshing noise through attenuating vibrations at the key points on the transmission path, (2) directly control the gear meshing noise in the cabin using the actuators. Results confirm that the active control system is practical for cancelling multifrequency helicopter interior noise, which also weakens the frequency-modulation of the tones. For many cases, the attenuations of the measured noise exceed the level of 15 dB, with maximum reduction reaching 31 dB. Also, the control process is demonstrated to be smoother and faster.

  16. An efficient randomized algorithm for contact-based NMR backbone resonance assignment.

    Science.gov (United States)

    Kamisetty, Hetunandan; Bailey-Kellogg, Chris; Pandurangan, Gopal

    2006-01-15

    Backbone resonance assignment is a critical bottleneck in studies of protein structure, dynamics and interactions by nuclear magnetic resonance (NMR) spectroscopy. A minimalist approach to assignment, which we call 'contact-based', seeks to dramatically reduce experimental time and expense by replacing the standard suite of through-bond experiments with the through-space (nuclear Overhauser enhancement spectroscopy, NOESY) experiment. In the contact-based approach, spectral data are represented in a graph with vertices for putative residues (of unknown relation to the primary sequence) and edges for hypothesized NOESY interactions, such that observed spectral peaks could be explained if the residues were 'close enough'. Due to experimental ambiguity, several incorrect edges can be hypothesized for each spectral peak. An assignment is derived by identifying consistent patterns of edges (e.g. for alpha-helices and beta-sheets) within a graph and by mapping the vertices to the primary sequence. The key algorithmic challenge is to be able to uncover these patterns even when they are obscured by significant noise. This paper develops, analyzes and applies a novel algorithm for the identification of polytopes representing consistent patterns of edges in a corrupted NOESY graph. Our randomized algorithm aggregates simplices into polytopes and fixes inconsistencies with simple local modifications, called rotations, that maintain most of the structure already uncovered. In characterizing the effects of experimental noise, we employ an NMR-specific random graph model in proving that our algorithm gives optimal performance in expected polynomial time, even when the input graph is significantly corrupted. We confirm this analysis in simulation studies with graphs corrupted by up to 500% noise. Finally, we demonstrate the practical application of the algorithm on several experimental beta-sheet datasets. Our approach is able to eliminate a large majority of noise edges and to

  17. A Study of Wind Turbine Comprehensive Operational Assessment Model Based on EM-PCA Algorithm

    Science.gov (United States)

    Zhou, Minqiang; Xu, Bin; Zhan, Yangyan; Ren, Danyuan; Liu, Dexing

    2018-01-01

    To assess wind turbine performance accurately and provide theoretical basis for wind farm management, a hybrid assessment model based on Entropy Method and Principle Component Analysis (EM-PCA) was established, which took most factors of operational performance into consideration and reach to a comprehensive result. To verify the model, six wind turbines were chosen as the research objects, the ranking obtained by the method proposed in the paper were 4#>6#>1#>5#>2#>3#, which are completely in conformity with the theoretical ranking, which indicates that the reliability and effectiveness of the EM-PCA method are high. The method could give guidance for processing unit state comparison among different units and launching wind farm operational assessment.

  18. Empirical wind retrieval model based on SAR spectrum measurements

    Science.gov (United States)

    Panfilova, Maria; Karaev, Vladimir; Balandina, Galina; Kanevsky, Mikhail; Portabella, Marcos; Stoffelen, Ad

    ambiguity from polarimetric SAR. A criterion based on the complex correlation coefficient between the VV and VH signals sign is applied to select the wind direction. An additional quality control on the wind speed value retrieved with the spectral method is applied. Here, we use the direction obtained with the spectral method and the backscattered signal for CMOD wind speed estimate. The algorithm described above may be refined by the use of numerous SAR data and wind measurements. In the present preliminary work the first results of SAR images combined with in situ data processing are presented. Our results are compared to the results obtained using previously developed models CMOD, C-2PO for VH polarization and statistical wind retrieval approaches [1]. Acknowledgments. This work is supported by the Russian Foundation of Basic Research (grants 13-05-00852-a). [1] M. Portabella, A. Stoffelen, J. A. Johannessen, Toward an optimal inversion method for synthetic aperture radar wind retrieval, Journal of geophysical research, V. 107, N C8, 2002

  19. A real-time MTFC algorithm of space remote-sensing camera based on FPGA

    Science.gov (United States)

    Zhao, Liting; Huang, Gang; Lin, Zhe

    2018-01-01

    A real-time MTFC algorithm of space remote-sensing camera based on FPGA was designed. The algorithm can provide real-time image processing to enhance image clarity when the remote-sensing camera running on-orbit. The image restoration algorithm adopted modular design. The MTF measurement calculation module on-orbit had the function of calculating the edge extension function, line extension function, ESF difference operation, normalization MTF and MTFC parameters. The MTFC image filtering and noise suppression had the function of filtering algorithm and effectively suppressing the noise. The algorithm used System Generator to design the image processing algorithms to simplify the design structure of system and the process redesign. The image gray gradient dot sharpness edge contrast and median-high frequency were enhanced. The image SNR after recovery reduced less than 1 dB compared to the original image. The image restoration system can be widely used in various fields.

  20. Noise annoyances from wind power: Survey of the population living close to a wind power plant. Final report: Part 3 Main study; Stoerningar fraan vindkraft: undersoekning bland maenniskor boende i naerheten av vindkraftverk. Slutrapport: Del 3 Huvudstudie

    Energy Technology Data Exchange (ETDEWEB)

    Pedersen, Eja [Halmstad Univ., Halmstad (Sweden). School of Business and Engineering; Persson-Waye, K. [Goeteborg Univ., Goeteborg (Sweden). Dept. of Environmental Medicine

    2002-02-01

    To evaluate the occurrence of annoyance from wind turbines, a study was performed in Laholm in May 2000. The aim was to obtain dose response relationships between calculated sound levels and noise annoyance and appropriate sound description as well as analysing the influence of other variables on noise annoyance. A questionnaire survey was performed in 6 areas comprising 16 wind turbines, of which 14 had an effect of 600 kW. The purpose of the study was masked. Among questions on living conditions in the countryside, questions directly related to wind turbines were included. The study population (n=518) comprised one randomly selected subject between the ages of 18 to 75 years in each household living within a calculated wind turbine sound level of 25 to 40 dBA. The response rate was 68.7% (n=356). Calculated distributions of A-weighted sound level were performed for each area and plotted on geographical maps in 2.5 dBA steps. Each dwelling could thus be given a sound level within an interval of 2.5 dBA. The most frequently occurring source of noise annoyance was noise from rotor blades. The proportions of respondents annoyed by noise increased with calculated sound level. Among respondents exposed to sound levels of 35.0-37.5 dBA, 43% responded themselves to be rather or much annoyed. A-weighted sound level was only one variable explaining annoyance. Annoyance was correlated to a larger extent by the intrusiveness of the sound character swishing. Noise annoyance was interrelated to the respondents' opinion of the visual impact of wind turbines, while attitude towards wind power in general had no greater influence. Disturbance of spoilt view was reported to a similar degree as noise disturbance. Further investigations are needed to clarify factors of importance for the disturbance of view. All the wind turbines in the study had constant rotation speed. The greater wind turbines that are now erected often have variable speed, which may lead to a sound

  1. Application of a Beamforming Technique to the Measurement of Airfoil Leading Edge Noise

    Directory of Open Access Journals (Sweden)

    Thomas Geyer

    2012-01-01

    Full Text Available The present paper describes the use of microphone array technology and beamforming algorithms for the measurement and analysis of noise generated by the interaction of a turbulent flow with the leading edge of an airfoil. Experiments were performed using a setup in an aeroacoustic wind tunnel, where the turbulent inflow is provided by different grids. In order to exactly localize the aeroacoustic noise sources and, moreover, to separate airfoil leading edge noise from grid-generated noise, the selected deconvolution beamforming algorithm is extended to be used on a fully three-dimensional source region. The result of this extended beamforming are three-dimensional mappings of noise source locations. Besides acoustic measurements, the investigation of airfoil leading edge noise requires the measurement of parameters describing the incident turbulence, such as the intensity and a characteristic length scale or time scale. The method used for the determination of these parameters in the present study is explained in detail. To demonstrate the applicability of the extended beamforming algorithm and the experimental setup as a whole, the noise generated at the leading edge of airfoils made of porous materials was measured and compared to that generated at the leading edge of a common nonporous airfoil.

  2. A discrete force allocation algorithm for modelling wind turbines in computational fluid dynamics

    DEFF Research Database (Denmark)

    Réthoré, Pierre-Elouan; Sørensen, Niels N.

    2012-01-01

    at the position of the wind turbine rotor to estimate correctly the power production and the rotor loading. The method proposed in this paper solves this issue by spreading the force on the direct neighbouring cells and applying an equivalent pressure jump at the cell faces. This can potentially open......This paper describes an algorithm for allocating discrete forces in computational fluid dynamics (CFD). Discrete forces are useful in wind energy CFD. They are used as an approximation of the wind turbine blades’ action on the wind (actuator disc/line), to model forests and to model turbulent...

  3. Two LQRI based Blade Pitch Controls for Wind Turbines

    Directory of Open Access Journals (Sweden)

    Yoonsu Nam

    2012-06-01

    Full Text Available As the wind turbine size has been increasing and their mechanical components are built lighter, the reduction of the structural loads becomes a very important task of wind turbine control in addition to maximum wind power capture. In this paper, we present a separate set of collective and individual pitch control algorithms. Both pitch control algorithms use the LQR control technique with integral action (LQRI, and utilize Kalman filters to estimate system states and wind speed. Compared to previous works in this area, our pitch control algorithms can control rotor speed and blade bending moments at the same time to improve the trade-off between rotor speed regulation and load reduction, while both collective and individual pitch controls can be designed separately. Simulation results show that the proposed collective and individual pitch controllers achieve very good rotor speed regulation and significant reduction of blade bending moments.

  4. Experiences of disturbance from wind power. Final report

    International Nuclear Information System (INIS)

    Pedersen, Eja

    2002-02-01

    Wind power generates electricity at low environmental costs, but local residents sometimes have had complains. To support further development of wind farms, it is important to find out if people are annoyed and if so, in what way. This is a preliminary study that will be followed by an extensive survey in Laholm, a municipality in the South of Sweden with 44 wind power turbines. A survey based on cases of complaints in Laholm shows that outdoor noise is the most common annoyance. Others are indoor noise, shadow flicker and visual impact. Residents in one nearby location, Falkenberg, that resembles the landscape in Laholm, were interviewed. The most common source of annoyance was traffic noise. The turbines annoyed no respondent, even thought the estimated noise levels in some cases exceeded the 40-dBA limit. Also in another location outside Halmstad people that lived close to the wind turbines experienced no problems. The number of people actually indicating annoyance by wind turbines is probably fairly small. The most common annoyance is that from wind turbine noise. People who are annoyed of noise could eater be exposed to higher noise levels than estimated or of certain discomforting type of noise. Several other factors of individual nature could also affect the annoyance. These are assumed to be the general attitude towards wind power, if you are in the possession of a turbine, if you are raised in the countryside or in a city, and the general attitude towards the authorities. Following these assumptions, several hypotheses for the main survey are discussed and described

  5. 34. Meeting of Experts. Noise immission

    International Nuclear Information System (INIS)

    2001-01-01

    downwind conditions there will be a tunnel effect where the sound energy is trapped between the reflecting water surface and layers of air with high wind speed. The sound level will be highest near the ground. The same problem with tunnel effects can be observed under the water where the sound is trapped between layers of different salinity. Today there is quite few offshore wind turbines and they are relatively small. There are however plans for larger farms in many countries and the wind turbines used there will most likely be larger than land based turbines hence emitting more noise. It is however possible to modify the RPM of the wind power plants and thereby move the noise emission to higher frequencies. This would improve the situation since high frequencies are absorbed more. The group agreed that above all measurements of long range sound propagation over water is needed, especially due to the industry's unawareness of the problem. The discussion came to concentrate on how to certify the manufacturers specifications. When measuring noise emission from prototypes the conditions are often perfect and the prototypes optimised. The noise level will therefore most probably be as low as it can be for that type of turbine. An emission level of about 2-3 dB compared to more realistic conditions is quite common. There is also an ageing effect that needs to be considered; a wind turbine will often emit more noise some time after the installation. Different ways of dealing with limit violations were discussed it seems as the most common methods are fees and (partial) closure of the wind turbines. There are quite many examples of turbines that have to be closed during night or that a few turbines in a group are closed. In some countries the owner of the turbines can make an agreement with the neighbours and the local authorities to compensate the neighbours with better house insulation

  6. Improving performance of wavelet-based image denoising algorithm using complex diffusion process

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Sharifzadeh, Sara; Korhonen, Jari

    2012-01-01

    using a variety of standard images and its performance has been compared against several de-noising algorithms known from the prior art. Experimental results show that the proposed algorithm preserves the edges better and in most cases, improves the measured visual quality of the denoised images......Image enhancement and de-noising is an essential pre-processing step in many image processing algorithms. In any image de-noising algorithm, the main concern is to keep the interesting structures of the image. Such interesting structures often correspond to the discontinuities (edges...... in comparison to the existing methods known from the literature. The improvement is obtained without excessive computational cost, and the algorithm works well on a wide range of different types of noise....

  7. Ripple FPN reduced algorithm based on temporal high-pass filter and hardware implementation

    Science.gov (United States)

    Li, Yiyang; Li, Shuo; Zhang, Zhipeng; Jin, Weiqi; Wu, Lei; Jin, Minglei

    2016-11-01

    Cooled infrared detector arrays always suffer from undesired Ripple Fixed-Pattern Noise (FPN) when observe the scene of sky. The Ripple Fixed-Pattern Noise seriously affect the imaging quality of thermal imager, especially for small target detection and tracking. It is hard to eliminate the FPN by the Calibration based techniques and the current scene-based nonuniformity algorithms. In this paper, we present a modified space low-pass and temporal high-pass nonuniformity correction algorithm using adaptive time domain threshold (THP&GM). The threshold is designed to significantly reduce ghosting artifacts. We test the algorithm on real infrared in comparison to several previously published methods. This algorithm not only can effectively correct common FPN such as Stripe, but also has obviously advantage compared with the current methods in terms of detail protection and convergence speed, especially for Ripple FPN correction. Furthermore, we display our architecture with a prototype built on a Xilinx Virtex-5 XC5VLX50T field-programmable gate array (FPGA). The hardware implementation of the algorithm based on FPGA has two advantages: (1) low resources consumption, and (2) small hardware delay (less than 20 lines). The hardware has been successfully applied in actual system.

  8. J-85 jet engine noise measured in the ONERA S1 wind tunnel and extrapolated to far field

    Science.gov (United States)

    Soderman, Paul T.; Julienne, Alain; Atencio, Adolph, Jr.

    1991-01-01

    Noise from a J-85 turbojet with a conical, convergent nozzle was measured in simulated flight in the ONERA S1 Wind Tunnel. Data are presented for several flight speeds up to 130 m/sec and for radiation angles of 40 to 160 degrees relative to the upstream direction. The jet was operated with subsonic and sonic exhaust speeds. A moving microphone on a 2 m sideline was used to survey the radiated sound field in the acoustically treated, closed test section. The data were extrapolated to a 122 m sideline by means of a multiple-sideline source-location method, which was used to identify the acoustic source regions, directivity patterns, and near field effects. The source-location method is described along with its advantages and disadvantages. Results indicate that the effects of simulated flight on J-85 noise are significant. At the maximum forward speed of 130 m/sec, the peak overall sound levels in the aft quadrant were attentuated approximately 10 dB relative to sound levels of the engine operated statically. As expected, the simulated flight and static data tended to merge in the forward quadrant as the radiation angle approached 40 degrees. There is evidence that internal engine or shock noise was important in the forward quadrant. The data are compared with published predictions for flight effects on pure jet noise and internal engine noise. A new empirical prediction is presented that relates the variation of internally generated engine noise or broadband shock noise to forward speed. Measured near field noise extrapolated to far field agrees reasonably well with data from similar engines tested statically outdoors, in flyover, in a wind tunnel, and on the Bertin Aerotrain. Anomalies in the results for the forward quadrant and for angles above 140 degrees are discussed. The multiple-sideline method proved to be cumbersome in this application, and it did not resolve all of the uncertainties associated with measurements of jet noise close to the jet. The

  9. Group-SMA Algorithm Based Joint Estimation of Train Parameter and State

    Directory of Open Access Journals (Sweden)

    Wei Zheng

    2015-03-01

    Full Text Available The braking rate and train arresting operation is important in the train braking performance. It is difficult to obtain the states of the train on time because of the measurement noise and a long calculation time. A type of Group Stochastic M-algorithm (GSMA based on Rao-Blackwellization Particle Filter (RBPF algorithm and Stochastic M-algorithm (SMA is proposed in this paper. Compared with RBPF, GSMA based estimation precisions for the train braking rate and the control accelerations were improved by 78% and 62%, respectively. The calculation time of the GSMA was decreased by 70% compared with SMA.

  10. An Adaptive Noise Cancellation System Based on Linear and Widely Linear Complex Valued Least Mean Square Algorithms for Removing Electrooculography Artifacts from Electroencephalography Signals

    Directory of Open Access Journals (Sweden)

    Engin Cemal MENGÜÇ

    2018-03-01

    Full Text Available In this study, an adaptive noise cancellation (ANC system based on linear and widely linear (WL complex valued least mean square (LMS algorithms is designed for removing electrooculography (EOG artifacts from electroencephalography (EEG signals. The real valued EOG and EEG signals (Fp1 and Fp2 given in dataset are primarily expressed as a complex valued signal in the complex domain. Then, using the proposed ANC system, the EOG artifacts are eliminated in the complex domain from the EEG signals. Expression of these signals in the complex domain allows us to remove EOG artifacts from two EEG channels simultaneously. Moreover, in this study, it has been shown that the complex valued EEG signal exhibits noncircular behavior, and in the case, the WL-CLMS algorithm enhances the performance of the ANC system compared to real-valued LMS and CLMS algorithms. Simulation results support the proposed approach.

  11. Improving the Penetration of Wind Power with Dynamic Thermal Rating System, Static VAR Compensator and Multi-Objective Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Jiashen Teh

    2018-04-01

    Full Text Available The integration of renewable energy sources, especially wind energy, has been on the rise throughout power systems worldwide. Due to this relatively new introduction, the integration of wind energy is often not optimized. Moreover, owing to the technical constraints and transmission congestions of the power network, most of the wind energy has to be curtailed. Due to various factors that influence the connectivity of wind energy, this paper proposes a well-organized posterior multi-objective (MO optimization algorithm for maximizing the connections of wind energy. In this regard, the dynamic thermal rating (DTR system and the static VAR compensator (SVC have been identified as effective tools for improving the loadability of the network. The propose MO algorithm in this paper aims to minimize: (1 wind energy curtailment, (2 operation cost of the network considering all investments and operations, also known as the total social cost, and (3 SVC operation cost. The proposed MO problem was solved using the non-dominated sorting genetic algorithm (NSGA II and it was tested on the modified IEEE reliability test system (IEEE-RTS. The results demonstrate the applicability of the proposed algorithm in aiding power system enhancement planning for integrating wind energy.

  12. Underwater noise from three types of offshore wind turbines: estimation of impact zones for harbor porpoises and harbor seals.

    Science.gov (United States)

    Tougaard, Jakob; Henriksen, Oluf Damsgaard; Miller, Lee A

    2009-06-01

    Underwater noise was recorded from three different types of wind turbines in Denmark and Sweden (Middelgrunden, Vindeby, and Bockstigen-Valar) during normal operation. Wind turbine noise was only measurable above ambient noise at frequencies below 500 Hz. Total sound pressure level was in the range 109-127 dB re 1 microPa rms, measured at distances between 14 and 20 m from the foundations. The 1/3-octave noise levels were compared with audiograms of harbor seals and harbor porpoises. Maximum 1/3-octave levels were in the range 106-126 dB re 1 microPa rms. Maximum range of audibility was estimated under two extreme assumptions on transmission loss (3 and 9 dB per doubling of distance, respectively). Audibility was low for harbor porpoises extending 20-70 m from the foundation, whereas audibility for harbor seals ranged from less than 100 m to several kilometers. Behavioral reactions of porpoises to the noise appear unlikely except if they are very close to the foundations. However, behavioral reactions from seals cannot be excluded up to distances of a few hundred meters. It is unlikely that the noise reaches dangerous levels at any distance from the turbines and the noise is considered incapable of masking acoustic communication by seals and porpoises.

  13. Real-Time Wavelet-Based Coordinated Control of Hybrid Energy Storage Systems for Denoising and Flattening Wind Power Output

    Directory of Open Access Journals (Sweden)

    Tran Thai Trung

    2014-10-01

    Full Text Available Since the penetration level of wind energy is continuously increasing, the negative impact caused by the fluctuation of wind power output needs to be carefully managed. This paper proposes a novel real-time coordinated control algorithm based on a wavelet transform to mitigate both short-term and long-term fluctuations by using a hybrid energy storage system (HESS. The short-term fluctuation is eliminated by using an electric double-layer capacitor (EDLC, while the wind-HESS system output is kept constant during each 10-min period by a Ni-MH battery (NB. State-of-charge (SOC control strategies for both EDLC and NB are proposed to maintain the SOC level of storage within safe operating limits. A ramp rate limitation (RRL requirement is also considered in the proposed algorithm. The effectiveness of the proposed algorithm has been tested by using real time simulation. The simulation model of the wind-HESS system is developed in the real-time digital simulator (RTDS/RSCAD environment. The proposed algorithm is also implemented as a user defined model of the RSCAD. The simulation results demonstrate that the HESS with the proposed control algorithm can indeed assist in dealing with the variation of wind power generation. Moreover, the proposed method shows better performance in smoothing out the fluctuation and managing the SOC of battery and EDLC than the simple moving average (SMA based method.

  14. An Improved Iris Recognition Algorithm Based on Hybrid Feature and ELM

    Science.gov (United States)

    Wang, Juan

    2018-03-01

    The iris image is easily polluted by noise and uneven light. This paper proposed an improved extreme learning machine (ELM) based iris recognition algorithm with hybrid feature. 2D-Gabor filters and GLCM is employed to generate a multi-granularity hybrid feature vector. 2D-Gabor filter and GLCM feature work for capturing low-intermediate frequency and high frequency texture information, respectively. Finally, we utilize extreme learning machine for iris recognition. Experimental results reveal our proposed ELM based multi-granularity iris recognition algorithm (ELM-MGIR) has higher accuracy of 99.86%, and lower EER of 0.12% under the premise of real-time performance. The proposed ELM-MGIR algorithm outperforms other mainstream iris recognition algorithms.

  15. Optimization of PV/Wind/Battery stand-alone system, using hybrid FPA/SA algorithm and CFD simulation, case study: Tehran

    International Nuclear Information System (INIS)

    Tahani, Mojtaba; Babayan, Narek; Pouyaei, Arman

    2015-01-01

    Highlights: • The utilization of an optimized Hybrid PV/Wind/Battery system has been studied. • The proposed system has been studied for a building in Tehran. • A novel hybrid optimization method, namely FPA/SA has been proposed. • The impact of inclined part of the roof on wind velocity is studied by CFD. • LPSP and Payback time were considered as objective functions in this study. - Abstract: Renewable energy hybrid systems are a promising technology toward sustainable and clean development. Due to stochastic behavior of renewable energy sources, optimization of their convertors has great importance for increasing system’s reliability and efficiency and also in order to decrease the costs. In this research study, it was aimed to study the utilization of an optimized hybrid PV/Wind/Battery system for a three story building, with an inclined surface on the edge of its roof, located in Tehran, capital of Iran. For this purpose, a new evolutionary based optimization technique, namely hybrid FPA/SA algorithm was developed, in order to maximize system’s reliability and minimize system’s costs. The new algorithm combines the approaches which are utilized in Flower Pollination Algorithm (FPA) and Simulated Annealing (SA) algorithm. The developed algorithm was validated using popular benchmark functions. Moreover the influence of PV panels tilt angle (which is equal to the slope of inclined part of the roof) is studied on the wind speed by using computational fluid dynamics (CFD) simulation. The outputs of CFD simulations are utilized as inputs for modeling wind turbine performance. The Loss of Power Supply Probability (LPSP) and Payback time are considered as objective functions, and PV panel tilt angle, number of PV panels and number of batteries are selected as decision variables. The results showed that if the tilt angle for PV panels is set equal to 30° and the number of PV panels is selected equal to 11 the fastest payback time which is 12 years and

  16. Novel precision enhancement algorithm with reduced image noise in cosmic muon tomography applications

    Directory of Open Access Journals (Sweden)

    Lee Sangkyu

    2016-01-01

    Full Text Available In this paper, we present a new algorithm that improves muon-based generated tomography images with increased precision and reduced image noise applicable to the detection of nuclear materials. Cosmic muon tomography is an interrogation-based imaging technique that, over the last decade, has been frequently employed for the detection of high-Z materials. This technique exploits a magnitude of cosmic muon scattering angles in order to construct an image. The scattering angles of the muons striking the geometry of interest are non-uniform, as cosmic muons vary in energy. The randomness of the scattering angles leads to significant noise in the muon tomography image. GEANT4 is used to numerically create data on the momenta and positions of scattered muons in a predefined geometry that includes high-Z materials. The numerically generated information is then processed with the point of closest approach reconstruction method to construct a muon tomography image; statistical filters are then developed to refine the point of closest approach reconstructed images. The filtered images exhibit reduced noise and enhanced precision when attempting to identify the presence of high-Z materials. The average precision from the point of closest approach reconstruction method is 13 %; for the integrated method, 88 %. The filtered image, therefore, results in a seven-fold improvement in precision compared to the point of closest approach reconstructed image.

  17. Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Sihem SLATNIA

    2011-01-01

    Full Text Available We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA for a range of tasks,extracting edges in a given gray or colour image, noise filtering applied to black-white image. This is the best set of local rules determine the future state of CA in an asynchronous way. The Genetic Algorithm (GA is applied to search the best CA rules that can realize the best edge detection and noise filtering.

  18. Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Okba Kazar

    2011-01-01

    Full Text Available We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA for a range of tasks, extracting edges in a given gray or colour image, noise filtering applied to black-white image. This is the best set of local rules determine the future state of CA in an asynchronous way. The Genetic Algorithm (GA is applied to search the best CA rules that can realize the best edge detection and noise filtering.

  19. Design and validation of the high performance and low noise CQU-DTU-LN1 airfoils

    DEFF Research Database (Denmark)

    Cheng, Jiangtao; Zhu, Wei Jun; Fischer, Andreas

    2014-01-01

    with the blade element momentum theory, the viscous-inviscid XFOIL code and an airfoil self-noise prediction model, an optimization algorithm has been developed for designing the high performance and low noise CQU-DTU-LN1 series of airfoils with targets of maximum power coefficient and low noise emission...... emission between the CQU-DTU-LN118 airfoil and the National Advisory Committee for Aeronautics (NACA) 64618 airfoil, which is used in modern wind turbine blades, are carried out. Copyright © 2013 John Wiley & Sons, Ltd....

  20. Experimental and theoretical characterization of acoustic noise from a 7.6 m diameter yaw controlled teetered rotor wind turbine

    Energy Technology Data Exchange (ETDEWEB)

    Moroz, E. [Univ. of Texas at El Paso, Dept. of Mechanical and Industrial Engineering, El Paso, TX (United States)

    1997-12-31

    An experimental investigation into the acoustic noise from a small (7.6 m diameter) teetered rotor wind turbine, set at various yaw angles up to 90 degrees of yaw, was conducted. The results revealed a 1/3 octave spectra which was dominated by a broad peak in the higher frequency range, at all yaw angles investigated. This prompted a theoretical investigation to reveal the mechanisms producing the dominant feature in the experimentally obtained noise spectra and resulted in the development of a wind turbine aerodynamic noise prediction coce, WTNOISE. The location near busy roads and the relatively rough terrain of the wind test site caused difficulties in obtaining useful noise spectral information below 500Hz. However, sufficiently good data was obtained above 500Hz to clearly show a dominant `hump` in the spectrum, centered between 3000 and 4000Hz. Although the local Reynolds number for the blade elements was around 500,000 and one might expect Laminar flow over a significant portion of the blade, the data did not match the noise spectra predicted when Laminar flow was assumed. Given the relatively poor surface quality of the rotor blades and the high turbulence of the test site it was therefore assumed that the boundary layer on the blade may have tripped relatively early and that the turbulent flow setting should be used. This assumption led to a much better correlation between experiment and predictions. The WTNOISE code indicated that the broad peak in the spectrum was most likely caused by trailing edge bluntness noise. Unfortunately time did not allow for modifications to the trailing edge to be investigated. (au)

  1. Ensemble empirical mode decomposition based fluorescence spectral noise reduction for low concentration PAHs

    Science.gov (United States)

    Wang, Shu-tao; Yang, Xue-ying; Kong, De-ming; Wang, Yu-tian

    2017-11-01

    A new noise reduction method based on ensemble empirical mode decomposition (EEMD) is proposed to improve the detection effect for fluorescence spectra. Polycyclic aromatic hydrocarbons (PAHs) pollutants, as a kind of important current environmental pollution source, are highly oncogenic. Using the fluorescence spectroscopy method, the PAHs pollutants can be detected. However, instrument will produce noise in the experiment. Weak fluorescent signals can be affected by noise, so we propose a way to denoise and improve the detection effect. Firstly, we use fluorescence spectrometer to detect PAHs to obtain fluorescence spectra. Subsequently, noises are reduced by EEMD algorithm. Finally, the experiment results show the proposed method is feasible.

  2. Economic dispatch optimization algorithm based on particle diffusion

    International Nuclear Information System (INIS)

    Han, Li; Romero, Carlos E.; Yao, Zheng

    2015-01-01

    Highlights: • A dispatch model that considers fuel, emissions control and wind power cost is built. • An optimization algorithm named diffusion particle optimization (DPO) is proposed. • DPO was used to analyze the impact of wind power risk and emissions on dispatch. - Abstract: Due to the widespread installation of emissions control equipment in fossil fuel-fired power plants, the cost of emissions control needs to be considered, together with the plant fuel cost, in providing economic power dispatch of those units to the grid. On the other hand, while using wind power decreases the overall power generation cost for the power grid, it poses a risk to a traditional grid, because of its inherent stochastic characteristics. Therefore, an economic dispatch optimization model needs to consider all of the fuel cost, emissions control cost and wind power cost for each of the generating unit conforming the fleet that meets the required grid power demand. In this study, an optimization algorithm referred as diffusion particle optimization (DPO) is proposed to solve such complex optimization problem. In this algorithm, Brownian motion theory is used to guide the movement of particles so that the particles can search for an optimal solution over the entire definition region. Several benchmark functions and power grid system data were used to test the performance of DPO, and compared to traditional algorithms used for economic dispatch optimization, such as, particle swarm optimization and artificial bee colony algorithm. It was found that DPO has less probability to be trapped in local optimums. According to results of different power systems DPO was able to find economic dispatch solutions with lower costs. DPO was also used to analyze the impact of wind power risk and fossil unit emissions coefficients on power dispatch. The result are encouraging for the use of DPO as a dynamic tool for economic dispatch of the power grid.

  3. Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Qin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krishnan, Venkat K [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cui, Mingjian [University of Texas at Dallas; Feng, Cong [University of Texas at Dallas; Wang, Zhenke [University of Texas at Dallas; Zhang, Jie [University of Texas at Dallas

    2018-02-01

    Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

  4. Placement Optimization of Wind Farm Based on Niche Genetic Algorithm%基于小生境遗传算法的风电场布局优化

    Institute of Scientific and Technical Information of China (English)

    田琳琳; 赵宁; 钟伟; 胡偶

    2011-01-01

    The placement of wind turbines in a wind farm is optimized based on niche genetic algorithm. Two simplified oncoming flow models of the unidirectional uniform wind and the non-uniform wind are considered with variable wind directions. In order to predict a more realistic power produced by the wind farm, the modified Jensen wake model is employed to investigate the behavior of wake interactions among the wind turbines. The niche genetic algorithm is used in optimization to minimize the cost of en-ergy (COE). In addition to optimal configurations, the results include number of turbines, total power output, objective functions and efficiency of output power for each configuration. Compared with earlier studies, the present work provides more improved results, and it is suitable for the optimization of the wind turbine placement in wind farms.%基于小生境遗传算法对风电场内风力机机组的布局进行优化.在优化过程中,考虑等风速同风向和变风速变风向两种简化的入流模式,采用修正的Jensen尾流模型模拟机组之间尾流的相互干扰效应,以单位发电量所消耗的成本最低为目标,使用小生境遗传算法优化风电场机组的排布.文中给出了优化后的风电场布局轮廓图、风电场机组台数、总发电量、目标函数值以及风电场的效率.通过与以前的相关研究对比分析,表明本文的方法取得了较优的结果,可为将来真实风场的风力机排布提供参考依据.

  5. Noise-based logic hyperspace with the superposition of 2 states in a single wire

    Science.gov (United States)

    Kish, Laszlo B.; Khatri, Sunil; Sethuraman, Swaminathan

    2009-05-01

    In the introductory paper [L.B. Kish, Phys. Lett. A 373 (2009) 911], about noise-based logic, we showed how simple superpositions of single logic basis vectors can be achieved in a single wire. The superposition components were the N orthogonal logic basis vectors. Supposing that the different logic values have “on/off” states only, the resultant discrete superposition state represents a single number with N bit accuracy in a single wire, where N is the number of orthogonal logic vectors in the base. In the present Letter, we show that the logic hyperspace (product) vectors defined in the introductory paper can be generalized to provide the discrete superposition of 2 orthogonal system states. This is equivalent to a multi-valued logic system with 2 logic values per wire. This is a similar situation to quantum informatics with N qubits, and hence we introduce the notion of noise-bit. This system has major differences compared to quantum informatics. The noise-based logic system is deterministic and each superposition element is instantly accessible with the high digital accuracy, via a real hardware parallelism, without decoherence and error correction, and without the requirement of repeating the logic operation many times to extract the probabilistic information. Moreover, the states in noise-based logic do not have to be normalized, and non-unitary operations can also be used. As an example, we introduce a string search algorithm which is O(√{M}) times faster than Grover's quantum algorithm (where M is the number of string entries), while it has the same hardware complexity class as the quantum algorithm.

  6. Simulation of modified hybrid noise reduction algorithm to enhance the speech quality

    International Nuclear Information System (INIS)

    Waqas, A.; Muhammad, T.; Jamal, H.

    2013-01-01

    Speech is the most essential method of correspondence of humankind. Cell telephony, portable hearing assistants and, hands free are specific provisions in this respect. The performance of these communication devices could be affected because of distortions which might augment them. There are two essential sorts of distortions that might be recognized, specifically: convolutive and additive noises. These mutilations contaminate the clean speech and make it unsatisfactory to human audiences i.e. perceptual value and intelligibility of speech signal diminishes. The objective of speech upgrade systems is to enhance the quality and understandability of speech to make it more satisfactory to audiences. This paper recommends a modified hybrid approach for single channel devices to process the noisy signals considering only the effect of background noises. It is a mixture of pre-processing relative spectral amplitude (RASTA) filter, which is approximated by a straight forward 4th order band-pass filter, and conventional minimum mean square error short time spectral amplitude (MMSE STSA85) estimator. To analyze the performance of the algorithm an objective parameter called Perceptual estimation of speech quality (PESQ) is measured. The results show that the modified algorithm performs well to remove the background noises. SIMULINK implementation is also performed and its profile report has been generated to observe the execution time. (author)

  7. Fault Diagnosis System of Wind Turbine Generator Based on Petri Net

    Science.gov (United States)

    Zhang, Han

    Petri net is an important tool for discrete event dynamic systems modeling and analysis. And it has great ability to handle concurrent phenomena and non-deterministic phenomena. Currently Petri nets used in wind turbine fault diagnosis have not participated in the actual system. This article will combine the existing fuzzy Petri net algorithms; build wind turbine control system simulation based on Siemens S7-1200 PLC, while making matlab gui interface for migration of the system to different platforms.

  8. Optimal placement of horizontal - and vertical - axis wind turbines in a wind farm for maximum power generation using a genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xiaomin; Agarwal, Ramesh [Department of Mechanical Engineering & Materials Science, Washington University in St. Louis, Jolley Hall, Campus Box 1185, One Brookings Drive, St. Louis, Missouri, 63130 (United States)

    2012-07-01

    In this paper, we consider the Wind Farm layout optimization problem using a genetic algorithm. Both the Horizontal –Axis Wind Turbines (HAWT) and Vertical-Axis Wind Turbines (VAWT) are considered. The goal of the optimization problem is to optimally position the turbines within the wind farm such that the wake effects are minimized and the power production is maximized. The reasonably accurate modeling of the turbine wake is critical in determination of the optimal layout of the turbines and the power generated. For HAWT, two wake models are considered; both are found to give similar answers. For VAWT, a very simple wake model is employed.

  9. Reduction of background noise induced by wind tunnel jet exit vanes

    Science.gov (United States)

    Martin, R. M.; Brooks, T. F.; Hoad, D. R.

    1985-01-01

    The NASA-Langley 4 x 7 m wind tunnel develops low frequency flow pulsations at certain velocity ranges during open throat mode operation, affecting the aerodynamics of the flow and degrading the resulting model test data. Triangular vanes attached to the trailing edge of flat steel rails, mounted 10 cm from the inside of the jet exit walls, have been used to reduce this effect; attention is presently given to methods used to reduce the inherent noise generation of the vanes while retaining their pulsation reduction features.

  10. Planetary Seismology : Lander- and Wind-Induced Seismic Signals

    Science.gov (United States)

    Lorenz, Ralph

    2016-10-01

    Seismic measurements are of interest for future geophysical exploration of ocean worlds such as Europa or Titan, as well as Venus, Mars and the Moon. Even when a seismometer is deployed away from a lander (as in the case of Apollo) lander-generated disturbances are apparent. Such signatures may be usefully diagnostic of lander operations (at least for outreach), and may serve as seismic excitation for near-field propagation studies. The introduction of these 'spurious' events may also influence the performance of event detection and data compression algorithms.Examples of signatures in the Viking 2 seismometer record of lander mechanism operations are presented. The coherence of Viking seismometer noise levels and wind forcing is well-established : some detailed examples are examined. Wind noise is likely to be significant on future Mars missions such as InSight, as well as on Titan and Venus.

  11. THE APPROACHING TRAIN DETECTION ALGORITHM

    OpenAIRE

    S. V. Bibikov

    2015-01-01

    The paper deals with detection algorithm for rail vibroacoustic waves caused by approaching train on the background of increased noise. The urgency of algorithm development for train detection in view of increased rail noise, when railway lines are close to roads or road intersections is justified. The algorithm is based on the method of weak signals detection in a noisy environment. The information statistics ultimate expression is adjusted. We present the results of algorithm research and t...

  12. The recommendations of the noise working group

    International Nuclear Information System (INIS)

    Legerton, M.L.

    1997-01-01

    In 1993 the DTI set up a Working Group to define a framework which can be used to measure and rate the noise from wind turbines. The final report of the Noise Working Group is now available for publication. The advice on the setting of noise limits for wind farms is largely unaltered from the preliminary recommendations presented at the 17th BWEA Annual Conference [1]. This paper recaps on those recommendations and provides additional information on the measurement procedures to be used with the recommendations on noise limits. The paper describes the measurement of the existing background noise climate on which the limits are based and the procedure to be used for the measurement of turbine noise levels in the investigation of complaints. The noise limits are rated noise levels in that they can include a penalty for tones present in the noise. The level of penalty depends upon the audibility of the tone and measurement procedure for determining audibility and the associated penalty system are also described. (author)

  13. Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

    Science.gov (United States)

    Hsiao, Y. R.; Tsai, C.

    2017-12-01

    As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

  14. A comparative evaluation of adaptive noise cancellation algorithms for minimizing motion artifacts in a forehead-mounted wearable pulse oximeter.

    Science.gov (United States)

    Comtois, Gary; Mendelson, Yitzhak; Ramuka, Piyush

    2007-01-01

    Wearable physiological monitoring using a pulse oximeter would enable field medics to monitor multiple injuries simultaneously, thereby prioritizing medical intervention when resources are limited. However, a primary factor limiting the accuracy of pulse oximetry is poor signal-to-noise ratio since photoplethysmographic (PPG) signals, from which arterial oxygen saturation (SpO2) and heart rate (HR) measurements are derived, are compromised by movement artifacts. This study was undertaken to quantify SpO2 and HR errors induced by certain motion artifacts utilizing accelerometry-based adaptive noise cancellation (ANC). Since the fingers are generally more vulnerable to motion artifacts, measurements were performed using a custom forehead-mounted wearable pulse oximeter developed for real-time remote physiological monitoring and triage applications. This study revealed that processing motion-corrupted PPG signals by least mean squares (LMS) and recursive least squares (RLS) algorithms can be effective to reduce SpO2 and HR errors during jogging, but the degree of improvement depends on filter order. Although both algorithms produced similar improvements, implementing the adaptive LMS algorithm is advantageous since it requires significantly less operations.

  15. Low-dose multiple-information retrieval algorithm for X-ray grating-based imaging

    International Nuclear Information System (INIS)

    Wang Zhentian; Huang Zhifeng; Chen Zhiqiang; Zhang Li; Jiang Xiaolei; Kang Kejun; Yin Hongxia; Wang Zhenchang; Stampanoni, Marco

    2011-01-01

    The present work proposes a low dose information retrieval algorithm for X-ray grating-based multiple-information imaging (GB-MII) method, which can retrieve the attenuation, refraction and scattering information of samples by only three images. This algorithm aims at reducing the exposure time and the doses delivered to the sample. The multiple-information retrieval problem in GB-MII is solved by transforming a nonlinear equations set to a linear equations and adopting the nature of the trigonometric functions. The proposed algorithm is validated by experiments both on conventional X-ray source and synchrotron X-ray source, and compared with the traditional multiple-image-based retrieval algorithm. The experimental results show that our algorithm is comparable with the traditional retrieval algorithm and especially suitable for high Signal-to-Noise system.

  16. Favorable noise uniformity properties of Fourier-based interpolation and reconstruction approaches in single-slice helical computed tomography

    International Nuclear Information System (INIS)

    La Riviere, Patrick J.; Pan Xiaochuan

    2002-01-01

    Volumes reconstructed by standard methods from single-slice helical computed tomography (CT) data have been shown to have noise levels that are highly nonuniform relative to those in conventional CT. These noise nonuniformities can affect low-contrast object detectability and have also been identified as the cause of the zebra artifacts that plague maximum intensity projection (MIP) images of such volumes. While these spatially variant noise levels have their root in the peculiarities of the helical scan geometry, there is also a strong dependence on the interpolation and reconstruction algorithms employed. In this paper, we seek to develop image reconstruction strategies that eliminate or reduce, at its source, the nonuniformity of noise levels in helical CT relative to that in conventional CT. We pursue two approaches, independently and in concert. We argue, and verify, that Fourier-based longitudinal interpolation approaches lead to more uniform noise ratios than do the standard 360LI and 180LI approaches. We also demonstrate that a Fourier-based fan-to-parallel rebinning algorithm, used as an alternative to fanbeam filtered backprojection for slice reconstruction, also leads to more uniform noise ratios, even when making use of the 180LI and 360LI interpolation approaches

  17. A class of kernel based real-time elastography algorithms.

    Science.gov (United States)

    Kibria, Md Golam; Hasan, Md Kamrul

    2015-08-01

    In this paper, a novel real-time kernel-based and gradient-based Phase Root Seeking (PRS) algorithm for ultrasound elastography is proposed. The signal-to-noise ratio of the strain image resulting from this method is improved by minimizing the cross-correlation discrepancy between the pre- and post-compression radio frequency signals with an adaptive temporal stretching method and employing built-in smoothing through an exponentially weighted neighborhood kernel in the displacement calculation. Unlike conventional PRS algorithms, displacement due to tissue compression is estimated from the root of the weighted average of the zero-lag cross-correlation phases of the pair of corresponding analytic pre- and post-compression windows in the neighborhood kernel. In addition to the proposed one, the other time- and frequency-domain elastography algorithms (Ara et al., 2013; Hussain et al., 2012; Hasan et al., 2012) proposed by our group are also implemented in real-time using Java where the computations are serially executed or parallely executed in multiple processors with efficient memory management. Simulation results using finite element modeling simulation phantom show that the proposed method significantly improves the strain image quality in terms of elastographic signal-to-noise ratio (SNRe), elastographic contrast-to-noise ratio (CNRe) and mean structural similarity (MSSIM) for strains as high as 4% as compared to other reported techniques in the literature. Strain images obtained for the experimental phantom as well as in vivo breast data of malignant or benign masses also show the efficacy of our proposed method over the other reported techniques in the literature. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. Performance comparison of weighted sum-minimum mean square error and virtual signal-to-interference plus noise ratio algorithms in simulated and measured channels

    DEFF Research Database (Denmark)

    Rahimi, Maryam; Nielsen, Jesper Ødum; Pedersen, Troels

    2014-01-01

    A comparison in data achievement between two well-known algorithms with simulated and real measured data is presented. The algorithms maximise the data rate in cooperative base stations (BS) multiple-input-single-output scenario. Weighted sum-minimum mean square error algorithm could be used...... in multiple-input-multiple-output scenarios, but it has lower performance than virtual signal-to-interference plus noise ratio algorithm in theory and practice. A real measurement environment consisting of two BS and two users have been studied to evaluate the simulation results....

  19. Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones

    Directory of Open Access Journals (Sweden)

    Qiulong Yang

    2018-01-01

    Full Text Available Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP and Volunteer Observation System (VOS were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line

  20. Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones

    Science.gov (United States)

    Yang, Qiulong; Yang, Kunde; Cao, Ran; Duan, Shunli

    2018-01-01

    Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP) and Volunteer Observation System (VOS) were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line array deployed near

  1. Restoration for Noise Removal in Quantum Images

    Science.gov (United States)

    Liu, Kai; Zhang, Yi; Lu, Kai; Wang, Xiaoping

    2017-09-01

    Quantum computation has become increasingly attractive in the past few decades due to its extraordinary performance. As a result, some studies focusing on image representation and processing via quantum mechanics have been done. However, few of them have considered the quantum operations for images restoration. To address this problem, three noise removal algorithms are proposed in this paper based on the novel enhanced quantum representation model, oriented to two kinds of noise pollution (Salt-and-Pepper noise and Gaussian noise). For the first algorithm Q-Mean, it is designed to remove the Salt-and-Pepper noise. The noise points are extracted through comparisons with the adjacent pixel values, after which the restoration operation is finished by mean filtering. As for the second method Q-Gauss, a special mask is applied to weaken the Gaussian noise pollution. The third algorithm Q-Adapt is effective for the source image containing unknown noise. The type of noise can be judged through the quantum statistic operations for the color value of the whole image, and then different noise removal algorithms are used to conduct image restoration respectively. Performance analysis reveals that our methods can offer high restoration quality and achieve significant speedup through inherent parallelism of quantum computation.

  2. Noise and noise disturbances from wind power plants - Tests with interactive control of sound parameters for more comfortable and less perceptible sounds; Buller och bullerstoerningar fraan vindkraftverk - Foersoek med interaktiv styrning av ljudparametrar foer behagligare och mindre maerkbara ljud

    Energy Technology Data Exchange (ETDEWEB)

    Persson-Waye, K.; Oehrstroem, E.; Bjoerkman, M.; Agge, A. [Goeteborg Univ. (Sweden). Dept. of Environmental Medicine

    2001-12-01

    In experimental pilot studies, a methodology has been worked out for interactively varying sound parameters in wind power plants. In the tests, 24 persons varied the center frequency of different band-widths, the frequency of a sinus-tone and the amplitude-modulation of a sinus-tone in order to create as comfortable a sound as possible. The variations build on the noise from the two wind turbines Bonus and Wind World. The variations were performed with a constant dba level. The results showed that the majority preferred a low-frequency tone (94 Hz and 115 Hz for Wind World and Bonus, respectively). The mean of the most comfortable amplitude-modulation varied between 18 and 22 Hz, depending on the ground frequency. The mean of the center-frequency for the different band-widths varied from 785 to 1104 Hz. In order to study the influence of the wind velocity on the acoustic character of the noise, a long-time measurement program has been performed. A remotely controlled system has been developed, where wind velocity, wind direction, temperature and humidity are registered simultaneously with the noise. Long-time registrations have been performed for four different wing turbines.

  3. Research on machine learning framework based on random forest algorithm

    Science.gov (United States)

    Ren, Qiong; Cheng, Hui; Han, Hai

    2017-03-01

    With the continuous development of machine learning, industry and academia have released a lot of machine learning frameworks based on distributed computing platform, and have been widely used. However, the existing framework of machine learning is limited by the limitations of machine learning algorithm itself, such as the choice of parameters and the interference of noises, the high using threshold and so on. This paper introduces the research background of machine learning framework, and combined with the commonly used random forest algorithm in machine learning classification algorithm, puts forward the research objectives and content, proposes an improved adaptive random forest algorithm (referred to as ARF), and on the basis of ARF, designs and implements the machine learning framework.

  4. A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data.

    Science.gov (United States)

    Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

    2017-06-01

    Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

  5. A numerically stable, finite memory, fast array recursive least squares algorithm for broadband active noise control

    NARCIS (Netherlands)

    van Ophem, S.; Berkhoff, Arthur P.

    2016-01-01

    For broadband active noise control applications with a rapidly changing primary path, it is desirable to find algorithms with a rapid convergence, a fast tracking performance, and a low computational cost. Recently, a promising algorithm has been presented, called the fast-array Kalman filter, which

  6. A comparison of regression algorithms for wind speed forecasting at Alexander Bay

    CSIR Research Space (South Africa)

    Botha, Nicolene

    2016-12-01

    Full Text Available to forecast 1 to 24 hours ahead, in hourly intervals. Predictions are performed on a wind speed time series with three machine learning regression algorithms, namely support vector regression, ordinary least squares and Bayesian ridge regression. The resulting...

  7. Fuzzy logic based variable speed wind generation system

    Energy Technology Data Exchange (ETDEWEB)

    Simoes, M.G. [Sao Paulo Univ., SP (Brazil). Escola Politecnica. PMC - Mecatronica; Bose, B.K. [Tennessee Univ., Knoxville, TN (United States). Dept. of Electrical Engineering; Spiegel, Ronal J. [Environmental Protection Agency, Research Triangle Park, NC (United States). Air and Energy Engineering Research Lab.

    1996-12-31

    This work demonstrates the successful application of fuzzy logic to enhance the performance and control of a variable speed wind generation system. A maximum power point tracker control is performed with three fuzzy controllers, without wind velocity measurement, and robust to wind vortex and turbine torque ripple. A squirrel cage induction generator feeds the power to a double-sided PWM converter system which pumps the power to a utility grid or supplies to an autonomous system. The fuzzy logic controller FLC-1 searches on-line the generator speed so that the aerodynamic efficiency of the wind turbine is optimized. A second fuzzy controller FLC-2 programs the machine flux by on-line search so as to optimize the machine-converter system wind vortex. Detailed analysis and simulation studies were performed for development of the control strategy and fuzzy algorithms, and a DSP TMS320C30 based hardware with C control software was built for the performance evaluation of a laboratory experimental set-up. The theoretical development was fully validated and the system is ready to be reproduced in a higher power installation. (author) 7 refs., 3 figs., 1 tab.

  8. Airborne Doppler Wind Lidar Post Data Processing Software DAPS-LV

    Science.gov (United States)

    Beyon, Jeffrey Y. (Inventor); Koch, Grady J. (Inventor); Kavaya, Michael J. (Inventor)

    2015-01-01

    Systems, methods, and devices of the present invention enable post processing of airborne Doppler wind LIDAR data. In an embodiment, airborne Doppler wind LIDAR data software written in LabVIEW may be provided and may run two versions of different airborne wind profiling algorithms. A first algorithm may be the Airborne Wind Profiling Algorithm for Doppler Wind LIDAR ("APOLO") using airborne wind LIDAR data from two orthogonal directions to estimate wind parameters, and a second algorithm may be a five direction based method using pseudo inverse functions to estimate wind parameters. The various embodiments may enable wind profiles to be compared using different algorithms, may enable wind profile data for long haul color displays to be generated, may display long haul color displays, and/or may enable archiving of data at user-selectable altitudes over a long observation period for data distribution and population.

  9. Wind Turbine Acoustics

    Science.gov (United States)

    Hubbard, Harvey H.; Shepherd, Kevin P.

    2009-01-01

    Wind turbine generators, ranging in size from a few kilowatts to several megawatts, are producing electricity both singly and in wind power stations that encompass hundreds of machines. Many installations are in uninhabited areas far from established residences, and therefore there are no apparent environmental impacts in terms of noise. There is, however, the potential for situations in which the radiated noise can be heard by residents of adjacent neighborhoods, particularly those neighborhoods with low ambient noise levels. A widely publicized incident of this nature occurred with the operation of the experimental Mod-1 2-MW wind turbine, which is described in detail elsewhere. Pioneering studies which were conducted at the Mod-1 site on the causes and remedies of noise from wind turbines form the foundation of much of the technology described in this chapter.

  10. High-speed MRF-based segmentation algorithm using pixonal images

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Hassanpour, H.; Naimi, H. M.

    2013-01-01

    Segmentation is one of the most complicated procedures in the image processing that has important role in the image analysis. In this paper, an improved pixon-based method for image segmentation is proposed. In proposed algorithm, complex partial differential equations (PDEs) is used as a kernel...... function to make pixonal image. Using this kernel function causes noise on images to reduce and an image not to be over-segment when the pixon-based method is used. Utilising the PDE-based method leads to elimination of some unnecessary details and results in a fewer pixon number, faster performance...... and more robustness against unwanted environmental noises. As the next step, the appropriate pixons are extracted and eventually, we segment the image with the use of a Markov random field. The experimental results indicate that the proposed pixon-based approach has a reduced computational load...

  11. Noise-immune complex correlation for optical coherence angiography based on standard and Jones matrix optical coherence tomography.

    Science.gov (United States)

    Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Miura, Masahiro; Yasuno, Yoshiaki

    2016-04-01

    This paper describes a complex correlation mapping algorithm for optical coherence angiography (cmOCA). The proposed algorithm avoids the signal-to-noise ratio dependence and exhibits low noise in vasculature imaging. The complex correlation coefficient of the signals, rather than that of the measured data are estimated, and two-step averaging is introduced. Algorithms of motion artifact removal based on non perfusing tissue detection using correlation are developed. The algorithms are implemented with Jones-matrix OCT. Simultaneous imaging of pigmented tissue and vasculature is also achieved using degree of polarization uniformity imaging with cmOCA. An application of cmOCA to in vivo posterior human eyes is presented to demonstrate that high-contrast images of patients' eyes can be obtained.

  12. Noise-immune complex correlation for optical coherence angiography based on standard and Jones matrix optical coherence tomography

    Science.gov (United States)

    Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Miura, Masahiro; Yasuno, Yoshiaki

    2016-01-01

    This paper describes a complex correlation mapping algorithm for optical coherence angiography (cmOCA). The proposed algorithm avoids the signal-to-noise ratio dependence and exhibits low noise in vasculature imaging. The complex correlation coefficient of the signals, rather than that of the measured data are estimated, and two-step averaging is introduced. Algorithms of motion artifact removal based on non perfusing tissue detection using correlation are developed. The algorithms are implemented with Jones-matrix OCT. Simultaneous imaging of pigmented tissue and vasculature is also achieved using degree of polarization uniformity imaging with cmOCA. An application of cmOCA to in vivo posterior human eyes is presented to demonstrate that high-contrast images of patients’ eyes can be obtained. PMID:27446673

  13. Application of Machine Learning Algorithms to the Study of Noise Artifacts in Gravitational-Wave Data

    Science.gov (United States)

    Biswas, Rahul; Blackburn, Lindy L.; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Young-Min, Kim; Le Bigot, Eric-Olivier; Lee, Chang-Hwan; hide

    2014-01-01

    The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitationalwave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across multiple detectors is non-negligible. Furthermore, non-Gaussian noise artifacts typically dominate over the background contributed from stationary noise. These "glitches" can easily be confused for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational-waves. We apply Machine Learning Algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Terrestrial noise sources may manifest characteristic disturbances in these auxiliary channels, inducing non-trivial correlations with glitches in the gravitational-wave data. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well-suited. We demonstrate the feasibility and applicability of three very different MLAs: Artificial Neural Networks, Support Vector Machines, and Random Forests. These classifiers identify and remove a substantial fraction of the glitches present in two very different data sets: four weeks of LIGO's fourth science run and one week of LIGO's sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth science run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar limiting performance, suggesting that most of the useful information currently contained in the auxiliary channel parameters we extract

  14. A Survey of Blue-Noise Sampling and Its Applications

    KAUST Repository

    Yan, Dongming; Guo, Jian-Wei; Wang, Bin; Zhang, Xiao-Peng; Wonka, Peter

    2015-01-01

    In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.

  15. A Survey of Blue-Noise Sampling and Its Applications

    KAUST Repository

    Yan, Dongming

    2015-05-05

    In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.

  16. Scenario-based stochastic optimal operation of wind, photovoltaic, pump-storage hybrid system in frequency- based pricing

    International Nuclear Information System (INIS)

    Zare Oskouei, Morteza; Sadeghi Yazdankhah, Ahmad

    2015-01-01

    Highlights: • Two-stage objective function is proposed for optimization problem. • Hourly-based optimal contractual agreement is calculated. • Scenario-based stochastic optimization problem is solved. • Improvement of system frequency by utilizing PSH unit. - Abstract: This paper proposes the operating strategy of a micro grid connected wind farm, photovoltaic and pump-storage hybrid system. The strategy consists of two stages. In the first stage, the optimal hourly contractual agreement is determined. The second stage corresponds to maximizing its profit by adapting energy management strategy of wind and photovoltaic in coordination with optimum operating schedule of storage device under frequency based pricing for a day ahead electricity market. The pump-storage hydro plant is utilized to minimize unscheduled interchange flow and maximize the system benefit by participating in frequency control based on energy price. Because of uncertainties in power generation of renewable sources and market prices, generation scheduling is modeled by a stochastic optimization problem. Uncertainties of parameters are modeled by scenario generation and scenario reduction method. A powerful optimization algorithm is proposed using by General Algebraic Modeling System (GAMS)/CPLEX. In order to verify the efficiency of the method, the algorithm is applied to various scenarios with different wind and photovoltaic power productions in a day ahead electricity market. The numerical results demonstrate the effectiveness of the proposed approach.

  17. Random Vibration and Dynamic Analysis of a Planetary Gear Train in a Wind Turbine

    Directory of Open Access Journals (Sweden)

    Jianming Yang

    2016-01-01

    Full Text Available Premature failure of gearboxes is a big challenge facing the wind power industry. It highly depends on fully understanding the embedded dynamics to solve this problem. To this end, this paper investigates the random vibration and dynamics of planetary gear trains (PGTs in wind turbines under the excitation of wind turbulence. The turbulence is represented by the Von Karmon spectrum and implemented by passing white noise through a 2nd-order shaping filter. Then, extra equations are formed and added to the original governing equations of motion. With this augmented equation set, a recursive numerical algorithm based on stochastic Newmark scheme is applied to solve for the statistics of the responses starting from initial conditions. After simulation, the variances of the vibration responses and the dynamic meshing forces at gear meshes are obtained.

  18. Noise-based logic hyperspace with the superposition of 2N states in a single wire

    International Nuclear Information System (INIS)

    Kish, Laszlo B.; Khatri, Sunil; Sethuraman, Swaminathan

    2009-01-01

    In the introductory paper [L.B. Kish, Phys. Lett. A 373 (2009) 911], about noise-based logic, we showed how simple superpositions of single logic basis vectors can be achieved in a single wire. The superposition components were the N orthogonal logic basis vectors. Supposing that the different logic values have 'on/off' states only, the resultant discrete superposition state represents a single number with N bit accuracy in a single wire, where N is the number of orthogonal logic vectors in the base. In the present Letter, we show that the logic hyperspace (product) vectors defined in the introductory paper can be generalized to provide the discrete superposition of 2 N orthogonal system states. This is equivalent to a multi-valued logic system with 2 2 N logic values per wire. This is a similar situation to quantum informatics with N qubits, and hence we introduce the notion of noise-bit. This system has major differences compared to quantum informatics. The noise-based logic system is deterministic and each superposition element is instantly accessible with the high digital accuracy, via a real hardware parallelism, without decoherence and error correction, and without the requirement of repeating the logic operation many times to extract the probabilistic information. Moreover, the states in noise-based logic do not have to be normalized, and non-unitary operations can also be used. As an example, we introduce a string search algorithm which is O(√(M)) times faster than Grover's quantum algorithm (where M is the number of string entries), while it has the same hardware complexity class as the quantum algorithm.

  19. Comparison study of noise reduction algorithms in dual energy chest digital tomosynthesis

    Science.gov (United States)

    Lee, D.; Kim, Y.-S.; Choi, S.; Lee, H.; Choi, S.; Kim, H.-J.

    2018-04-01

    Dual energy chest digital tomosynthesis (CDT) is a recently developed medical technique that takes advantage of both tomosynthesis and dual energy X-ray images. However, quantum noise, which occurs in dual energy X-ray images, strongly interferes with diagnosis in various clinical situations. Therefore, noise reduction is necessary in dual energy CDT. In this study, noise-compensating algorithms, including a simple smoothing of high-energy images (SSH) and anti-correlated noise reduction (ACNR), were evaluated in a CDT system. We used a newly developed prototype CDT system and anthropomorphic chest phantom for experimental studies. The resulting images demonstrated that dual energy CDT can selectively image anatomical structures, such as bone and soft tissue. Among the resulting images, those acquired with ACNR showed the best image quality. Both coefficient of variation and contrast to noise ratio (CNR) were the highest in ACNR among the three different dual energy techniques, and the CNR of bone was significantly improved compared to the reconstructed images acquired at a single energy. This study demonstrated the clinical value of dual energy CDT and quantitatively showed that ACNR is the most suitable among the three developed dual energy techniques, including standard log subtraction, SSH, and ACNR.

  20. Optimum Parameters of a Tuned Liquid Column Damper in a Wind Turbine Subject to Stochastic Load

    Science.gov (United States)

    Alkmim, M. H.; de Morais, M. V. G.; Fabro, A. T.

    2017-12-01

    Parameter optimization for tuned liquid column dampers (TLCD), a class of passive structural control, have been previously proposed in the literature for reducing vibration in wind turbines, and several other applications. However, most of the available work consider the wind excitation as either a deterministic harmonic load or random load with white noise spectra. In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of undamped primary system under white noise excitation by comparing with result from the literature. Finally, it is shown that different wind profiles can significantly affect the optimum TLCD parameters.

  1. Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation

    Science.gov (United States)

    Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.

    2012-01-01

    Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.

  2. Improved Relay Node Placement Algorithm for Wireless Sensor Networks Application in Wind Farm

    DEFF Research Database (Denmark)

    Chen, Qinyin; Hu, Y.; Chen, Zhe

    2013-01-01

    -tolerance. Each wind turbine has a potentially large number of data points needing to be monitored and collected, as farms continue to increase in scale; distances between turbines can reach several hundred meters. Optimal placement of relays in a large farm requires an efficient algorithmic solution. A relay...... node placement algorithm is proposed in this paper to approximate the optimal position for relays connecting each turbine. However, constraints are then required to prevent relay nodes being overloaded in 3-dimensions. The algorithm is extended to 3-dimensional Euclidean space for this optimal relay...

  3. Effects of Wind Turbine Noise on Self-Reported and Objective Measures of Sleep.

    Science.gov (United States)

    Michaud, David S; Feder, Katya; Keith, Stephen E; Voicescu, Sonia A; Marro, Leonora; Than, John; Guay, Mireille; Denning, Allison; Murray, Brian J; Weiss, Shelly K; Villeneuve, Paul J; van den Berg, Frits; Bower, Tara

    2016-01-01

    To investigate the association between self-reported and objective measures of sleep and wind turbine noise (WTN) exposure. The Community Noise and Health Study, a cross-sectional epidemiological study, included an in-house computer-assisted interview and sleep pattern monitoring over a 7 d period. Outdoor WTN levels were calculated following international standards for conditions that typically approximate the highest long-term average levels at each dwelling. Study data were collected between May and September 2013 from adults, aged 18-79 y (606 males, 632 females) randomly selected from each household and living between 0.25 and 11.22 kilometers from operational wind turbines in two Canadian provinces. Self-reported sleep quality over the past 30 d was assessed using the Pittsburgh Sleep Quality Index. Additional questions assessed the prevalence of diagnosed sleep disorders and the magnitude of sleep disturbance over the previous year. Objective measures for sleep latency, sleep efficiency, total sleep time, rate of awakening bouts, and wake duration after sleep onset were recorded using the wrist worn Actiwatch2® from a subsample of 654 participants (289 males, 365 females) for a total of 3,772 sleep nights. Participant response rate for the interview was 78.9%. Outdoor WTN levels reached 46 dB(A) with an arithmetic mean of 35.6 and a standard deviation of 7.4. Self-reported and objectively measured sleep outcomes consistently revealed no apparent pattern or statistically significant relationship to WTN levels. However, sleep was significantly influenced by other factors, including, but not limited to, the use of sleep medication, other health conditions (including sleep disorders), caffeine consumption, and annoyance with blinking lights on wind turbines. Study results do not support an association between exposure to outdoor WTN up to 46 dB(A) and an increase in the prevalence of disturbed sleep. Conclusions are based on WTN levels averaged over 1 y and, in

  4. Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Qin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krishnan, Venkat K [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cui, Mingjian [Univ. of Texas-Dallas, Richardson, TX (United States); Feng, Cong [Univ. of Texas-Dallas, Richardson, TX (United States); Wang, Zhenke [Univ. of Texas-Dallas, Richardson, TX (United States); Zhang, Jie [Univ. of Texas-Dallas, Richardson, TX (United States)

    2017-08-31

    Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

  5. Multiscale Distance Coherence Vector Algorithm for Content-Based Image Retrieval

    Science.gov (United States)

    Jiexian, Zeng; Xiupeng, Liu

    2014-01-01

    Multiscale distance coherence vector algorithm for content-based image retrieval (CBIR) is proposed due to the same descriptor with different shapes and the shortcomings of antinoise performance of the distance coherence vector algorithm. By this algorithm, the image contour curve is evolved by Gaussian function first, and then the distance coherence vector is, respectively, extracted from the contour of the original image and evolved images. Multiscale distance coherence vector was obtained by reasonable weight distribution of the distance coherence vectors of evolved images contour. This algorithm not only is invariable to translation, rotation, and scaling transformation but also has good performance of antinoise. The experiment results show us that the algorithm has a higher recall rate and precision rate for the retrieval of images polluted by noise. PMID:24883416

  6. Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm

    International Nuclear Information System (INIS)

    Zhou, Jianzhong; Lu, Peng; Li, Yuanzheng; Wang, Chao; Yuan, Liu; Mo, Li

    2016-01-01

    Highlights: • HTWCS system is established while considering uncertainty of wind power. • An enhanced multi-objective bee colony optimization algorithm is proposed. • Some heuristic repairing strategies are designed to handle various constraints. • HTWCS problem with economic/environment objectives is solved by EMOBCO. - Abstract: This paper presents a short-term economic/environmental hydro-thermal-wind complementary scheduling (HTWCS) system considering uncertainty of wind power, as well as various complicated non-linear constraints. HTWCS system is formulated as a multi-objective optimization problem to optimize conflictive objectives, i.e., economic and environmental criteria. Then an enhanced multi-objective bee colony optimization algorithm (EMOBCO) is proposed to solve this problem, which adopts Elite archive set, adaptive mutation/selection mechanism and local searching strategy to improve global searching ability of standard bee colony optimization (BCO). Especially, a novel constraints-repairing strategy with compressing decision space and a violation-adjustment method are used to handle various hydraulic and electric constraints. Finally, a daily scheduling simulation case of hydro-thermal-wind system is conducted to verify feasibility and effectiveness of the proposed EMOBCO in solving HTWCS problem. The simulation results indicate that the proposed EMOBCO can provide lower economic cost and smaller pollutant emission than other method established recently while considering various complex constraints in HTWCS problem.

  7. Chemical Source Localization Fusing Concentration Information in the Presence of Chemical Background Noise.

    Science.gov (United States)

    Pomareda, Víctor; Magrans, Rudys; Jiménez-Soto, Juan M; Martínez, Dani; Tresánchez, Marcel; Burgués, Javier; Palacín, Jordi; Marco, Santiago

    2017-04-20

    We present the estimation of a likelihood map for the location of the source of a chemical plume dispersed under atmospheric turbulence under uniform wind conditions. The main contribution of this work is to extend previous proposals based on Bayesian inference with binary detections to the use of concentration information while at the same time being robust against the presence of background chemical noise. For that, the algorithm builds a background model with robust statistics measurements to assess the posterior probability that a given chemical concentration reading comes from the background or from a source emitting at a distance with a specific release rate. In addition, our algorithm allows multiple mobile gas sensors to be used. Ten realistic simulations and ten real data experiments are used for evaluation purposes. For the simulations, we have supposed that sensors are mounted on cars which do not have among its main tasks navigating toward the source. To collect the real dataset, a special arena with induced wind is built, and an autonomous vehicle equipped with several sensors, including a photo ionization detector (PID) for sensing chemical concentration, is used. Simulation results show that our algorithm, provides a better estimation of the source location even for a low background level that benefits the performance of binary version. The improvement is clear for the synthetic data while for real data the estimation is only slightly better, probably because our exploration arena is not able to provide uniform wind conditions. Finally, an estimation of the computational cost of the algorithmic proposal is presented.

  8. Structure-Based Low-Rank Model With Graph Nuclear Norm Regularization for Noise Removal.

    Science.gov (United States)

    Ge, Qi; Jing, Xiao-Yuan; Wu, Fei; Wei, Zhi-Hui; Xiao, Liang; Shao, Wen-Ze; Yue, Dong; Li, Hai-Bo

    2017-07-01

    Nonlocal image representation methods, including group-based sparse coding and block-matching 3-D filtering, have shown their great performance in application to low-level tasks. The nonlocal prior is extracted from each group consisting of patches with similar intensities. Grouping patches based on intensity similarity, however, gives rise to disturbance and inaccuracy in estimation of the true images. To address this problem, we propose a structure-based low-rank model with graph nuclear norm regularization. We exploit the local manifold structure inside a patch and group the patches by the distance metric of manifold structure. With the manifold structure information, a graph nuclear norm regularization is established and incorporated into a low-rank approximation model. We then prove that the graph-based regularization is equivalent to a weighted nuclear norm and the proposed model can be solved by a weighted singular-value thresholding algorithm. Extensive experiments on additive white Gaussian noise removal and mixed noise removal demonstrate that the proposed method achieves a better performance than several state-of-the-art algorithms.

  9. Sound wave contours around wind turbine arrays

    International Nuclear Information System (INIS)

    Van Beek, A.; Van Blokland, G.J.

    1993-02-01

    Noise pollution is an important factor in selecting suitable sites for wind turbines in order to realize 1000 MW of wind power as planned by the Dutch government for the year 2000. Therefore an accurate assessment of wind turbine noise is important. The amount of noise pollution from a wind turbine depends on the wind conditions. An existing standard method to assess wind turbine noise is supplemented and adjusted. In the first part of the investigation the method was developed and applied for a solitary sound source. In the second part attention is paid to the use of the method for wind turbine arrays. It appears that the adjusted method results in a shift of the contours of the permitted noise level. In general the contours are 15-25% closer to the wind farm, which means that the minimal permitted distance between houses and wind turbine arrays can be reduced. 14 figs., 1 tab., 4 appendices, 7 refs

  10. Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

    Directory of Open Access Journals (Sweden)

    Quanzhen Huang

    2017-01-01

    Full Text Available Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

  11. A Parametric Genetic Algorithm Approach to Assess Complementary Options of Large Scale Wind-solar Coupling

    Institute of Scientific and Technical Information of China (English)

    Tim; Mareda; Ludovic; Gaudard; Franco; Romerio

    2017-01-01

    The transitional path towards a highly renewable power system based on wind and solar energy sources is investigated considering their intermittent and spatially distributed characteristics. Using an extensive weather-driven simulation of hourly power mismatches between generation and load, we explore the interplay between geographical resource complementarity and energy storage strategies. Solar and wind resources are considered at variable spatial scales across Europe and related to the Swiss load curve, which serve as a typical demand side reference. The optimal spatial distribution of renewable units is further assessed through a parameterized optimization method based on a genetic algorithm. It allows us to explore systematically the effective potential of combined integration strategies depending on the sizing of the system, with a focus on how overall performance is affected by the definition of network boundaries. Upper bounds on integration schemes are provided considering both renewable penetration and needed reserve power capacity. The quantitative trade-off between grid extension, storage and optimal wind-solar mix is highlighted.This paper also brings insights on how optimal geographical distribution of renewable units evolves as a function of renewable penetration and grid extent.

  12. Nonlinear Rayleigh wave inversion based on the shuffled frog-leaping algorithm

    Science.gov (United States)

    Sun, Cheng-Yu; Wang, Yan-Yan; Wu, Dun-Shi; Qin, Xiao-Jun

    2017-12-01

    At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear global optimization problem. In order to alleviate the risk of falling into a local optimal solution, this paper introduces a new global optimization method, the shuffle frog-leaping algorithm (SFLA), into the Rayleigh wave dispersion-curve inversion process. SFLA is a swarm-intelligence-based algorithm that simulates a group of frogs searching for food. It uses a few parameters, achieves rapid convergence, and is capability of effective global searching. In order to test the reliability and calculation performance of SFLA, noise-free and noisy synthetic datasets were inverted. We conducted a comparative analysis with other established algorithms using the noise-free dataset, and then tested the ability of SFLA to cope with data noise. Finally, we inverted a real-world example to examine the applicability of SFLA. Results from both synthetic and field data demonstrated the effectiveness of SFLA in the interpretation of Rayleigh wave dispersion curves. We found that SFLA is superior to the established methods in terms of both reliability and computational efficiency, so it offers great potential to improve our ability to solve geophysical inversion problems.

  13. Pulse Retrieval Algorithm for Interferometric Frequency-Resolved Optical Gating Based on Differential Evolution

    OpenAIRE

    Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

    2017-01-01

    A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove robustness of the algorithm against experimental artifacts and noise. These tests show that the i...

  14. An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Kai Hu

    2015-01-01

    Full Text Available Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR.

  15. V/STOL Rotary Propulsor Noise Prediction Model Update and Evaluation.

    Science.gov (United States)

    1979-12-01

    Noise as Observed on and Jacques the Bertin Aerotrain July 1976 JSV 54(2) 3) Hoch, Berthelot Use of the Bertin Aerotrain for the Investigation July 1976...Atencio G.E. X376-B Jots 2 Drevet, et al Aerotrain - G.E. J85 9 Jaeck Wind Tunnel - G.E. J85 Nozzles 13 Pacbian, et al Wind Tunnel Model Jet 23 Brooks...Calculat6d Full-Scale Jet Noise Data Base Item 2. - This paper presents measurements made of the noise from a J85 engine installed on the Aerotrain . Data

  16. A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data

    Science.gov (United States)

    Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

    2017-06-01

    Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

  17. Impulsive noise removal from color video with morphological filtering

    Science.gov (United States)

    Ruchay, Alexey; Kober, Vitaly

    2017-09-01

    This paper deals with impulse noise removal from color video. The proposed noise removal algorithm employs a switching filtering for denoising of color video; that is, detection of corrupted pixels by means of a novel morphological filtering followed by removal of the detected pixels on the base of estimation of uncorrupted pixels in the previous scenes. With the help of computer simulation we show that the proposed algorithm is able to well remove impulse noise in color video. The performance of the proposed algorithm is compared in terms of image restoration metrics with that of common successful algorithms.

  18. Wind Tunnel Measurements at LM Wind Power

    DEFF Research Database (Denmark)

    Bertagnolio, Franck

    2012-01-01

    This section presents the results obtained during the experimental campaign that was conducted in the wind tunnel at LM Wind Power in Lunderskov from August 16th to 26th, 2010. The goal of this study is to validate the so-called TNO trailing edge noise model through measurements of the boundary...... layer turbulence characteristics and the far-field noise generated by the acoustic scattering of the turbulent boundary layer vorticies as they convect past the trailing edge. This campaign was conducted with a NACA0015 airfoil section that was placed in the wind tunnel section. It is equipped with high...

  19. Model/data comparison of typhoon-generated noise

    International Nuclear Information System (INIS)

    Wang Jing-Yan; Li Feng-Hua

    2016-01-01

    Ocean noise recorded during a typhoon can be used to monitor the typhoon and investigate the mechanism of the wind-generated noise. An analytical expression for the typhoon-generated noise intensity is derived as a function of wind speed. A “bi-peak” structure was observed in an experiment during which typhoon-generated noise was recorded. Wind speed dependence and frequency dependence were also observed in the frequency range of 100 Hz–1000 Hz. The model/data comparison shows that results of the present model of 500 Hz and 1000 Hz are in reasonable agreement with the experimental data, and the typhoon-generated noise intensity has a dependence on frequency and a power-law dependence on wind speed. (special topic)

  20. Fitting a circular distribution based on nonnegative trigonometric sums for wind direction in Malaysia

    Science.gov (United States)

    Masseran, Nurulkamal; Razali, Ahmad Mahir; Ibrahim, Kamarulzaman; Zaharim, Azami; Sopian, Kamaruzzaman

    2015-02-01

    Wind direction has a substantial effect on the environment and human lives. As examples, the wind direction influences the dispersion of particulate matter in the air and affects the construction of engineering structures, such as towers, bridges, and tall buildings. Therefore, a statistical analysis of the wind direction provides important information about the wind regime at a particular location. In addition, knowledge of the wind direction and wind speed can be used to derive information about the energy potential. This study investigated the characteristics of the wind regime of Mersing, Malaysia. A circular distribution based on Nonnegative Trigonometric Sums (NNTS) was fitted to a histogram of the average hourly wind direction data. The Newton-like manifold algorithm was used to estimate the parameter of each component of the NNTS model. Next, the suitability of each NNTS model was judged based on a graphical representation and Akaike's Information Criteria. The study found that the NNTS model with six or more components was able to fit the wind directional data for the Mersing station.

  1. A CAMAC based real-time noise analysis system for nuclear reactors

    International Nuclear Information System (INIS)

    Ciftcioglu, O.

    1987-01-01

    A CAMAC based real-time noise analysis system was designed for the TRIGA MARK II nuclear reactor at the Institute for Nuclear Energy, Istanbul. The input analog signals obtained from the radiation detectors are introduced to the system through CAMAC interface. The signals coverted into digital form are processed by a PDP-11 computer. The fast data processing based on auto/cross power spectral density computations is carried out by means of assembly written FFT algorithms in real-time and the spectra obtained are displayed on a CAMAC driven display system as an additional monitoring device. The system has the advantage of being software programmable and controlled by a CAMAC system so that it is operated under porgram control for reactor surveillance, anomaly detection and diagnosis. The system can also be used for the identification of nonstationary operational characteristics of the reactor in long term by comparing the noise power spectra with the corresponding reference noise patterns prepared in advance. (orig.)

  2. Integrative modeling and novel particle swarm-based optimal design of wind farms

    Science.gov (United States)

    Chowdhury, Souma

    allowing simultaneous optimization of the type and the location of the turbines. Layout optimization (using UWFLO) of a hypothetical 25-turbine commercial-scale wind farm provides a remarkable 4.4% increase in capacity factor compared to a conventional array layout. A further 2% increase in capacity factor is accomplished when the types of turbines are also optimally selected. The scope of turbine selection and placement however depends on the land configuration and the nameplate capacity of the farm. Such dependencies are not clearly defined in the existing literature. We develop response surface-based models, which implicitly employ UWFLO, to quantify and analyze the roles of these other crucial design factors in optimal wind farm planning. The wind pattern at a site can vary significantly from year to year, which is not adequately captured by conventional wind distribution models. The resulting ill-predictability of the annual distribution of wind conditions introduces significant uncertainties in the estimated energy output of the wind farm. A new method is developed to characterize these wind resource uncertainties and model the propagation of these uncertainties into the estimated farm output. The overall wind pattern/regime also varies from one region to another, which demands turbines with capabilities uniquely suited for different wind regimes. Using the UWFLO method, we model the performance potential of currently available turbines for different wind regimes, and quantify their feature-based expected market suitability. Such models can initiate an understanding of the product variation that current turbine manufacturers should pursue, to adequately satisfy the needs of the naturally diverse wind energy market. The wind farm design problems formulated in this dissertation involve highly multimodal objective and constraint functions and a large number of continuous and discrete variables. An effective modification of the PSO algorithm is developed to address such

  3. Stochastic Dynamic AC Optimal Power Flow Based on a Multivariate Short-Term Wind Power Scenario Forecasting Model

    Directory of Open Access Journals (Sweden)

    Wenlei Bai

    2017-12-01

    Full Text Available The deterministic methods generally used to solve DC optimal power flow (OPF do not fully capture the uncertainty information in wind power, and thus their solutions could be suboptimal. However, the stochastic dynamic AC OPF problem can be used to find an optimal solution by fully capturing the uncertainty information of wind power. That uncertainty information of future wind power can be well represented by the short-term future wind power scenarios that are forecasted using the generalized dynamic factor model (GDFM—a novel multivariate statistical wind power forecasting model. Furthermore, the GDFM can accurately represent the spatial and temporal correlations among wind farms through the multivariate stochastic process. Fully capturing the uncertainty information in the spatially and temporally correlated GDFM scenarios can lead to a better AC OPF solution under a high penetration level of wind power. Since the GDFM is a factor analysis based model, the computational time can also be reduced. In order to further reduce the computational time, a modified artificial bee colony (ABC algorithm is used to solve the AC OPF problem based on the GDFM forecasting scenarios. Using the modified ABC algorithm based on the GDFM forecasting scenarios has resulted in better AC OPF’ solutions on an IEEE 118-bus system at every hour for 24 h.

  4. Spatial planning of wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-01-01

    This paper proposes guidelines for spatial planning for wind power, based on experience with spatial planning in Belgium, Denmark, France and the Netherlands. In addition experiences from Germany and Ireland have been used. This guidelines quotes all decisive criteria for successful implementation of wind energy: landscape integration, stakeholders involvement, noise and distance from buildings. (author)

  5. An Improved Fast Compressive Tracking Algorithm Based on Online Random Forest Classifier

    Directory of Open Access Journals (Sweden)

    Xiong Jintao

    2016-01-01

    Full Text Available The fast compressive tracking (FCT algorithm is a simple and efficient algorithm, which is proposed in recent years. But, it is difficult to deal with the factors such as occlusion, appearance changes, pose variation, etc in processing. The reasons are that, Firstly, even if the naive Bayes classifier is fast in training, it is not robust concerning the noise. Secondly, the parameters are required to vary with the unique environment for accurate tracking. In this paper, we propose an improved fast compressive tracking algorithm based on online random forest (FCT-ORF for robust visual tracking. Firstly, we combine ideas with the adaptive compressive sensing theory regarding the weighted random projection to exploit both local and discriminative information of the object. The second reason is the online random forest classifier for online tracking which is demonstrated with more robust to the noise adaptively and high computational efficiency. The experimental results show that the algorithm we have proposed has a better performance in the field of occlusion, appearance changes, and pose variation than the fast compressive tracking algorithm’s contribution.

  6. A Noise Reduction Preprocessor for Mobile Voice Communication

    Directory of Open Access Journals (Sweden)

    Rainer Martin

    2004-07-01

    Full Text Available We describe a speech enhancement algorithm which leads to significant quality and intelligibility improvements when used as a preprocessor to a low bit rate speech coder. This algorithm was developed in conjunction with the mixed excitation linear prediction (MELP coder which, by itself, is highly susceptible to environmental noise. The paper presents novel as well as known speech and noise estimation techniques and combines them into a highly effective speech enhancement system. The algorithm is based on short-time spectral amplitude estimation, soft-decision gain modification, tracking of the a priori probability of speech absence, and minimum statistics noise power estimation. Special emphasis is placed on enhancing the performance of the preprocessor in nonstationary noise environments.

  7. Computational Aerodynamics and Aeroacoustics for Wind Turbines

    DEFF Research Database (Denmark)

    Shen, Wen Zhong

    and applied to laminar flows. An aero-acoustic formulation for turbulent flows was in [15] developed for Large Eddy Simulation (LES), Unsteady Reynolds Averaged Navier-Stokes Simulation (URANS) and Detached Eddy Simulation (DES). In [16] a collocated grid / finite volume method for aero-acoustic computations...... with Computational Aero-Acoustics (CAA). With the spread of wind turbines near urban areas, there is an increasing need for accurate predictions of aerodynamically generated noise. Indeed, noise has become one of the most important issues for further development of wind power, and the ability of controlling...... and aero-acoustics of wind turbines. The papers are written in the period from 1997 to 2008 and numbered according to the list in page v. The work consists of two parts: an aerodynamic part based on Computational Fluid Dynamics and an aero-acoustic part based on Computational Aero Acoustics for wind...

  8. Iterative Observer-based Estimation Algorithms for Steady-State Elliptic Partial Differential Equation Systems

    KAUST Repository

    Majeed, Muhammad Usman

    2017-07-19

    Steady-state elliptic partial differential equations (PDEs) are frequently used to model a diverse range of physical phenomena. The source and boundary data estimation problems for such PDE systems are of prime interest in various engineering disciplines including biomedical engineering, mechanics of materials and earth sciences. Almost all existing solution strategies for such problems can be broadly classified as optimization-based techniques, which are computationally heavy especially when the problems are formulated on higher dimensional space domains. However, in this dissertation, feedback based state estimation algorithms, known as state observers, are developed to solve such steady-state problems using one of the space variables as time-like. In this regard, first, an iterative observer algorithm is developed that sweeps over regular-shaped domains and solves boundary estimation problems for steady-state Laplace equation. It is well-known that source and boundary estimation problems for the elliptic PDEs are highly sensitive to noise in the data. For this, an optimal iterative observer algorithm, which is a robust counterpart of the iterative observer, is presented to tackle the ill-posedness due to noise. The iterative observer algorithm and the optimal iterative algorithm are then used to solve source localization and estimation problems for Poisson equation for noise-free and noisy data cases respectively. Next, a divide and conquer approach is developed for three-dimensional domains with two congruent parallel surfaces to solve the boundary and the source data estimation problems for the steady-state Laplace and Poisson kind of systems respectively. Theoretical results are shown using a functional analysis framework, and consistent numerical simulation results are presented for several test cases using finite difference discretization schemes.

  9. Cook-Levin Theorem Algorithmic-Reducibility/Completeness = Wilson Renormalization-(Semi)-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') REPLACING CRUTCHES!!!: Models: Turing-machine, finite-state-models, finite-automata

    Science.gov (United States)

    Young, Frederic; Siegel, Edward

    Cook-Levin theorem theorem algorithmic computational-complexity(C-C) algorithmic-equivalence reducibility/completeness equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited via Siegel FUZZYICS =CATEGORYICS = ANALOGYICS =PRAGMATYICS/CATEGORY-SEMANTICS ONTOLOGY COGNITION ANALYTICS-Aristotle ``square-of-opposition'' tabular list-format truth-table matrix analytics predicts and implements ''noise''-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics (1987)]-Sipser[Intro.Thy. Computation(`97)] algorithmic C-C: ''NIT-picking''(!!!), to optimize optimization-problems optimally(OOPO). Versus iso-''noise'' power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, ''NIT-picking'' is ''noise'' power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-''science''/SEANCE algorithmic C-C models: Turing-machine, finite-state-models, finite-automata,..., discrete-maths graph-theory equivalence to physics Feynman-diagrams are identified as early-days once-workable valid but limiting IMPEDING CRUTCHES(!!!), ONLY IMPEDE latter-days new-insights!!!

  10. Imaging reconstruction based on improved wavelet denoising combined with parallel-beam filtered back-projection algorithm

    Science.gov (United States)

    Ren, Zhong; Liu, Guodong; Huang, Zhen

    2012-11-01

    The image reconstruction is a key step in medical imaging (MI) and its algorithm's performance determinates the quality and resolution of reconstructed image. Although some algorithms have been used, filter back-projection (FBP) algorithm is still the classical and commonly-used algorithm in clinical MI. In FBP algorithm, filtering of original projection data is a key step in order to overcome artifact of the reconstructed image. Since simple using of classical filters, such as Shepp-Logan (SL), Ram-Lak (RL) filter have some drawbacks and limitations in practice, especially for the projection data polluted by non-stationary random noises. So, an improved wavelet denoising combined with parallel-beam FBP algorithm is used to enhance the quality of reconstructed image in this paper. In the experiments, the reconstructed effects were compared between the improved wavelet denoising and others (directly FBP, mean filter combined FBP and median filter combined FBP method). To determine the optimum reconstruction effect, different algorithms, and different wavelet bases combined with three filters were respectively test. Experimental results show the reconstruction effect of improved FBP algorithm is better than that of others. Comparing the results of different algorithms based on two evaluation standards i.e. mean-square error (MSE), peak-to-peak signal-noise ratio (PSNR), it was found that the reconstructed effects of the improved FBP based on db2 and Hanning filter at decomposition scale 2 was best, its MSE value was less and the PSNR value was higher than others. Therefore, this improved FBP algorithm has potential value in the medical imaging.

  11. A Combined Energy Management Algorithm for Wind Turbine/Battery Hybrid System

    Science.gov (United States)

    Altin, Necmi; Eyimaya, Süleyman Emre

    2018-03-01

    From an energy management standpoint, natural phenomena such as solar irradiation and wind speed are uncontrolled variables, so the correlation between the energy generated by renewable energy sources and energy demand cannot always be predicted. For this reason, energy storage systems are used to provide more efficient renewable energy systems. In these systems, energy management systems are used to control the energy storage system and establish a balance between the generated power and the power demand. In addition, especially in wind turbines, rapidly varying wind speeds cause wind power fluctuations, which threaten the power system stability, especially at high power levels. Energy storage systems are also used to mitigate the power fluctuations and sustain the power system's stability. In these systems, another controller which controls the energy storage system power to mitigate power fluctuations is required. These two controllers are different from each other. In this study, a combined energy management algorithm is proposed which can perform both as an energy control system and a power fluctuation mitigation system. The proposed controller is tested with wind energy conversion system modeled in MATLAB/Simulink. Simulation results show that the proposed controller acts as an energy management system while, at the same time, mitigating power fluctuations.

  12. A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video

    Directory of Open Access Journals (Sweden)

    Zhang Liangpei

    2007-01-01

    Full Text Available Super-resolution (SR reconstruction technique is capable of producing a high-resolution image from a sequence of low-resolution images. In this paper, we study an efficient SR algorithm for digital video. To effectively deal with the intractable problems in SR video reconstruction, such as inevitable motion estimation errors, noise, blurring, missing regions, and compression artifacts, the total variation (TV regularization is employed in the reconstruction model. We use the fixed-point iteration method and preconditioning techniques to efficiently solve the associated nonlinear Euler-Lagrange equations of the corresponding variational problem in SR. The proposed algorithm has been tested in several cases of motion and degradation. It is also compared with the Laplacian regularization-based SR algorithm and other TV-based SR algorithms. Experimental results are presented to illustrate the effectiveness of the proposed algorithm.

  13. Preliminary recommendations of the Noise Working Group

    International Nuclear Information System (INIS)

    Legerton, M.L.

    1995-01-01

    In 1993 the DTI set up a Working Group largely consisting of independent experts on wind turbine noise. The main objectives of the Working Group were to define a framework which can be used to measure and rate the noise from wind turbines and to provide indicative noise levels thought to offer a reasonable degree of protection to wind farm neighbours and encourage best practice in turbine design and wind farm siting and layout. This paper presents the preliminary recommendations of the Working Group. (Author)

  14. A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power

    International Nuclear Information System (INIS)

    Liao, Gwo-Ching

    2011-01-01

    An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm (CQGA). In addition to the detailed models of economic dispatch introduction and their associated constraints, the wind power effect is also included in this paper. The chaotic quantum genetic algorithm used to solve the economic dispatch process and discussed with real scenarios used for the simulation tests. After comparing the proposed algorithm with several other algorithms commonly used to solve optimization problems, the results show that the proposed algorithm is able to find the optimal solution quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time). At the end, the impact to the total cost savings for power generation after adding (or not adding) wind power generation is also discussed. The actual implementation results prove that the proposed algorithm is economical, fast and practical. They are quite valuable for further research. -- Research highlights: → Quantum Genetic Algorithm can effectively improve the global search ability. → It can achieve the real objective of the global optimal solutions. → The CPU computation time is less than that other algorithms adopted in this paper.

  15. Noise-based logic hyperspace with the superposition of 2{sup N} states in a single wire

    Energy Technology Data Exchange (ETDEWEB)

    Kish, Laszlo B. [Texas A and M University, Department of Electrical and Computer Engineering, College Station, TX 77843-3128 (United States)], E-mail: laszlo.kish@ece.tamu.edu; Khatri, Sunil; Sethuraman, Swaminathan [Texas A and M University, Department of Electrical and Computer Engineering, College Station, TX 77843-3128 (United States)

    2009-05-11

    In the introductory paper [L.B. Kish, Phys. Lett. A 373 (2009) 911], about noise-based logic, we showed how simple superpositions of single logic basis vectors can be achieved in a single wire. The superposition components were the N orthogonal logic basis vectors. Supposing that the different logic values have 'on/off' states only, the resultant discrete superposition state represents a single number with N bit accuracy in a single wire, where N is the number of orthogonal logic vectors in the base. In the present Letter, we show that the logic hyperspace (product) vectors defined in the introductory paper can be generalized to provide the discrete superposition of 2{sup N} orthogonal system states. This is equivalent to a multi-valued logic system with 2{sup 2{sup N}} logic values per wire. This is a similar situation to quantum informatics with N qubits, and hence we introduce the notion of noise-bit. This system has major differences compared to quantum informatics. The noise-based logic system is deterministic and each superposition element is instantly accessible with the high digital accuracy, via a real hardware parallelism, without decoherence and error correction, and without the requirement of repeating the logic operation many times to extract the probabilistic information. Moreover, the states in noise-based logic do not have to be normalized, and non-unitary operations can also be used. As an example, we introduce a string search algorithm which is O({radical}(M)) times faster than Grover's quantum algorithm (where M is the number of string entries), while it has the same hardware complexity class as the quantum algorithm.

  16. Research on correction algorithm of laser positioning system based on four quadrant detector

    Science.gov (United States)

    Gao, Qingsong; Meng, Xiangyong; Qian, Weixian; Cai, Guixia

    2018-02-01

    This paper first introduces the basic principle of the four quadrant detector, and a set of laser positioning experiment system is built based on the four quadrant detector. Four quadrant laser positioning system in the actual application, not only exist interference of background light and detector dark current noise, and the influence of random noise, system stability, spot equivalent error can't be ignored, so it is very important to system calibration and correction. This paper analyzes the various factors of system positioning error, and then propose an algorithm for correcting the system error, the results of simulation and experiment show that the modified algorithm can improve the effect of system error on positioning and improve the positioning accuracy.

  17. Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

    International Nuclear Information System (INIS)

    Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.

    2014-01-01

    Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem

  18. Gearbox Fatigue Load Estimation for Condition Monitoring of Wind Turbines

    DEFF Research Database (Denmark)

    Perisic, Nevena; Pedersen, Bo Juul; Kirkegaard, Poul Henning

    2012-01-01

    control and data acquisition (SCADA) system. Estimated loads can be further used for prediction of remaining operating lifetime of turbine components, detection of high stress level or fault detection. An augmented Kalman filter is chosen as the fatigue load estimator because its characteristics well suit......The focus of the paper is on a design of a fatigue load estimator for predictive condition monitoring systems (CMS) of wind turbines. In order to avoid high-price measurement equipment required for direct load measuring, an indirect approach is suggested using only measurements from supervisory...... for the real time application. This paper presents results of the estimation of the gearbox fatigue load, often called shaft torque, using simulated data of wind turbine. Noise sensitivity of the algorithm is investigated by assuming different levels of measurement noise. Shaft torque estimations are compared...

  19. A review on computational fluid dynamic simulation techniques for Darrieus vertical axis wind turbines

    International Nuclear Information System (INIS)

    Ghasemian, Masoud; Ashrafi, Z. Najafian; Sedaghat, Ahmad

    2017-01-01

    Highlights: • A review on CFD simulation technique for Darrieus wind turbines is provided. • Recommendations and guidelines toward reliable and accurate simulations are presented. • Different progresses in CFD simulation of Darrieus wind turbines are addressed. - Abstract: The global warming threats, the presence of policies on support of renewable energies, and the desire for clean smart cities are the major drives for most recent researches on developing small wind turbines in urban environments. VAWTs (vertical axis wind turbines) are most appealing for energy harvesting in the urban environment. This is attributed due to structural simplicity, wind direction independency, no yaw mechanism required, withstand high turbulence winds, cost effectiveness, easier maintenance, and lower noise emission of VAWTs. This paper reviews recent published works on CFD (computational fluid dynamic) simulations of Darrieus VAWTs. Recommendations and guidelines are presented for turbulence modeling, spatial and temporal discretization, numerical schemes and algorithms, and computational domain size. The operating and geometrical parameters such as tip speed ratio, wind speed, solidity, blade number and blade shapes are fully investigated. The purpose is to address different progresses in simulations areas such as blade profile modification and optimization, wind turbine performance augmentation using guide vanes, wind turbine wake interaction in wind farms, wind turbine aerodynamic noise reduction, dynamic stall control, self-starting characteristics, and effects of unsteady and skewed wind conditions.

  20. Genetic algorithm-based improved DOA estimation using fourth-order cumulants

    Science.gov (United States)

    Ahmed, Ammar; Tufail, Muhammad

    2017-05-01

    Genetic algorithm (GA)-based direction of arrival (DOA) estimation is proposed using fourth-order cumulants (FOC) and ESPRIT principle which results in Multiple Invariance Cumulant ESPRIT algorithm. In the existing FOC ESPRIT formulations, only one invariance is utilised to estimate DOAs. The unused multiple invariances (MIs) must be exploited simultaneously in order to improve the estimation accuracy. In this paper, a fitness function based on a carefully designed cumulant matrix is developed which incorporates MIs present in the sensor array. Better DOA estimation can be achieved by minimising this fitness function. Moreover, the effectiveness of Newton's method as well as GA for this optimisation problem has been illustrated. Simulation results show that the proposed algorithm provides improved estimation accuracy compared to existing algorithms, especially in the case of low SNR, less number of snapshots, closely spaced sources and high signal and noise correlation. Moreover, it is observed that the optimisation using Newton's method is more likely to converge to false local optima resulting in erroneous results. However, GA-based optimisation has been found attractive due to its global optimisation capability.