Biometric identification with high frequency electrocardiogram: Unregistered user refusal method and performance evaluation.

Science.gov (United States)

Kyoso, Masaki

2015-08-01

As a new modality for biometric identification, electrocardiogram-based identification technique has been developed. We proposed a technique with high frequency component of electrocardiogram (HFECG) in QRS segment. In this report, an unregistered user refusal algorithm was combined with the artificial neural network based waveform classifier. The refusal function was realized by simple thresholding technique. HFECGs from twenty collaborators were used for supervised learning. Twenty HFECGs from the same collaborators were tested and false acceptance rate (FAR) and false rejection rate (FRR) were evaluated. Ten HFECGs from other collaborators were also tested to find unregistered user refusal performance. The results show that FAR and FRR in the registrants can be kept within 1%, however, unregistered user refusal performance was not acceptable under the same condition.

Identification Method of Mud Shale Fractures Base on Wavelet Transform

Science.gov (United States)

Xia, Weixu; Lai, Fuqiang; Luo, Han

2018-01-01

In recent years, inspired by seismic analysis technology, a new method for analysing mud shale fractures oil and gas reservoirs by logging properties has emerged. By extracting the high frequency attribute of the wavelet transform in the logging attribute, the formation information hidden in the logging signal is extracted, identified the fractures that are not recognized by conventional logging and in the identified fracture segment to show the “cycle jump”, “high value”, “spike” and other response effect is more obvious. Finally formed a complete wavelet denoising method and wavelet high frequency identification fracture method.

Damage detection in multi-span beams based on the analysis of frequency changes

International Nuclear Information System (INIS)

Gillich, G R; Ntakpe, J L; Praisach, Z I; Mimis, M C; Abdel Wahab, M

2017-01-01

Crack identification in multi-span beams is performed to determine whether the structure is healthy or not. Among all crack identification methods, these based on measured natural frequency changes present the advantage of simplicity and easy to use in practical engineering. To accurately identify the cracks characteristics for multi-span beam structure, a mathematical model is established, which can predict frequency changes for any boundary conditions, the intermediate supports being hinges. This relation is based on the modal strain energy concept. Since frequency changes are relative small, to obtain natural frequencies with high resolution, a signal processing algorithm based on superposing of numerous spectra is also proposed, which overcomes the disadvantage of Fast Fourier Transform in the aspect of frequency resolution. Based on above-mentioned mathematical model and signal processing algorithm, the method of identifying cracks on multi-span beams is presented. To verify the accuracy of this identification method, experimental examples are conducted on a two-span structure. The results demonstrate that the method proposed in this paper can accurately identify the crack position and depth. (paper)

Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID

Directory of Open Access Journals (Sweden)

Ardhyanti Mita Nugraha Joanna

2018-01-01

Full Text Available Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP. This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID)

Science.gov (United States)

Nugraha, Joanna Ardhyanti Mita; Suryono; Suseno, dan Jatmiko Endro

2018-02-01

Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID) as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP). This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

Frequency response function-based explicit framework for dynamic identification in human-structure systems

Science.gov (United States)

Wei, Xiaojun; Živanović, Stana

2018-05-01

The aim of this paper is to propose a novel theoretical framework for dynamic identification in a structure occupied by a single human. The framework enables the prediction of the dynamics of the human-structure system from the known properties of the individual system components, the identification of human body dynamics from the known dynamics of the empty structure and the human-structure system and the identification of the properties of the structure from the known dynamics of the human and the human-structure system. The novelty of the proposed framework is the provision of closed-form solutions in terms of frequency response functions obtained by curve fitting measured data. The advantages of the framework over existing methods are that there is neither need for nonlinear optimisation nor need for spatial/modal models of the empty structure and the human-structure system. In addition, the second-order perturbation method is employed to quantify the effect of uncertainties in human body dynamics on the dynamic identification of the empty structure and the human-structure system. The explicit formulation makes the method computationally efficient and straightforward to use. A series of numerical examples and experiments are provided to illustrate the working of the method.

Power system low frequency oscillation monitoring and analysis based on multi-signal online identification

Institute of Scientific and Technical Information of China (English)

无

2010-01-01

The advance in the wide-area measurement system (WAMS) is driving the power system to the trend of wide-area monitoring and control.The Prony method is usually used for low frequency oscillation online identification.However,the identified amplitude and phase information is not sufficiently used.In this paper,the amplitude is adopted to detect the occurrence of the oscillation and to obtain the mode observability of the sites.The phase is adopted to identify the oscillation generator grouping and to obtain the mode shapes.The time varying characteristics of low frequency oscillations are studied.The behaviors and the characters of low frequency oscillations are displayed by dynamic visual techniques.Demonstrations on the "11.9" low frequency oscillation of the Guizhou Power Grid substantiate the feasibility and the validation of the proposed methods.

A Support Vector Machine-Based Gender Identification Using Speech Signal

Science.gov (United States)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

Metamodel-based inverse method for parameter identification: elastic-plastic damage model

Science.gov (United States)

Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

2017-04-01

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

A new frequency matching technique for FRF-based model updating

Science.gov (United States)

Yang, Xiuming; Guo, Xinglin; Ouyang, Huajiang; Li, Dongsheng

2017-05-01

Frequency Response Function (FRF) residues have been widely used to update Finite Element models. They are a kind of original measurement information and have the advantages of rich data and no extraction errors, etc. However, like other sensitivity-based methods, an FRF-based identification method also needs to face the ill-conditioning problem which is even more serious since the sensitivity of the FRF in the vicinity of a resonance is much greater than elsewhere. Furthermore, for a given frequency measurement, directly using a theoretical FRF at a frequency may lead to a huge difference between the theoretical FRF and the corresponding experimental FRF which finally results in larger effects of measurement errors and damping. Hence in the solution process, correct selection of the appropriate frequency to get the theoretical FRF in every iteration in the sensitivity-based approach is an effective way to improve the robustness of an FRF-based algorithm. A primary tool for right frequency selection based on the correlation of FRFs is the Frequency Domain Assurance Criterion. This paper presents a new frequency selection method which directly finds the frequency that minimizes the difference of the order of magnitude between the theoretical and experimental FRFs. A simulated truss structure is used to compare the performance of different frequency selection methods. For the sake of reality, it is assumed that not all the degrees of freedom (DoFs) are available for measurement. The minimum number of DoFs required in each approach to correctly update the analytical model is regarded as the right identification standard.

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.

Radio Frequency Identification

Indian Academy of Sciences (India)

Radio Frequency Identification (RFID) has been around sinceearly 2000. Its use has currently become commonplace as thecost of RFID tags has rapidly decreased. RFID tags have alsobecome more 'intelligent' with the incorporation of processorsand sensors in them. They are widely used now in manyinnovative ways.

Frequency characteristic measurement of a fiber optic gyroscope using a correlation spectrum analysis method based on a pseudo-random sequence

International Nuclear Information System (INIS)

Li, Yang; Chen, Xingfan; Liu, Cheng

2015-01-01

The frequency characteristic is an important indicator of a system’s dynamic performance. The identification of a fiber optic gyroscope (FOG)’s frequency characteristic using a correlation spectrum analysis method based on a pseudo-random sequence is proposed. Taking the angle vibrator as the source of the test rotation stimulation and a pseudo-random sequence as the test signal, the frequency characteristic of a FOG is calculated according to the power spectral density of the rotation rate signal and the cross-power spectral density of the FOG’s output signal and rotation rate signal. A theoretical simulation is done to confirm the validity of this method. An experiment system is built and the test results indicate that the measurement error of the normalized amplitude–frequency response is less than 0.01, that the error of the phase–frequency response is less than 0.3 rad, and the overall measurement accuracy is superior to the traditional frequency-sweep method. By using this method, the FOG’s amplitude–frequency response and phase–frequency response can be measured simultaneously, quickly, accurately, and with a high frequency resolution. The described method meets the requirements of engineering applications. (paper)

In-situ identification of marine organisms using high frequency, wideband ultrasound

DEFF Research Database (Denmark)

Pham, An Hoai

methods. Conventional acoustical methods use frequencies in the range of 10 to 500 kHz and give reasonable estimations of size distribution, if the species is known, but can only significantly support the determination of the actual species, if there are only a few known species available. It is expected...... that higher frequencies and broader bandwidths than used until now will give more information useful for fish species identification. The objective of this Ph.D. study has been to develop a method to investigate the possibility of in-situ identification of fish with high-frequency, wideband ultrasound...... and the fish bodies. The frequencies are 2, 3.5, and 6 MHz. The angles are -30°, -15°, 0°, 15°, and 30°. The results show that even though there are variations, a scan of the ultrasound backscatter along a fish of a specific species contains patterns that are characteristic for that species. This is true...

Novel structural flexibility identification in narrow frequency bands

International Nuclear Information System (INIS)

Zhang, J; Moon, F L

2012-01-01

A ‘Sub-PolyMAX’ method is proposed in this paper not only for estimating modal parameters, but also for identifying structural flexibility by processing the impact test data in narrow frequency bands. The traditional PolyMAX method obtains denominator polynomial coefficients by minimizing the least square (LS) errors of frequency response function (FRF) estimates over the whole frequency range, but FRF peaks in different structural modes may have different levels of magnitude, which leads to the modal parameters identified for the modes with small FRF peaks being inaccurate. In contrast, the proposed Sub-PolyMAX method implements the LS solver in each subspace of the whole frequency range separately; thus the results identified from a narrow frequency band are not affected by FRF data in other frequency bands. In performing structural identification in narrow frequency bands, not in the whole frequency space, the proposed method has the following merits: (1) it produces accurate modal parameters, even for the modes with very small FRF peaks; (2) it significantly reduces computation cost by reducing the number of frequency lines and the model order in each LS implementation; (3) it accurately identifies structural flexibility from impact test data, from which structural deflection under any static load can be predicted. Numerical and laboratory examples are investigated to verify the effectiveness of the proposed method. (paper)

Radio frequency identification and time-driven activity based costing:RFID-TDABC application in warehousing

OpenAIRE

Bahr, Witold; Price, Brian J

2016-01-01

Purpose: This paper extends the use of Radio Frequency Identification (RFID) data for accounting of warehouse costs and services. Time Driven Activity Based Costing (TDABC) methodology is enhanced with the real-time collected RFID data about duration of warehouse activities. This allows warehouse managers to have accurate and instant calculations of costs. The RFID enhanced TDABC (RFID-TDABC) is proposed as a novel application of the RFID technology. Research Approach: Application of RFID-TDA...

Key Concept Identification: A Comprehensive Analysis of Frequency and Topical Graph-Based Approaches

Directory of Open Access Journals (Sweden)

Muhammad Aman

2018-05-01

Full Text Available Automatic key concept extraction from text is the main challenging task in information extraction, information retrieval and digital libraries, ontology learning, and text analysis. The statistical frequency and topical graph-based ranking are the two kinds of potentially powerful and leading unsupervised approaches in this area, devised to address the problem. To utilize the potential of these approaches and improve key concept identification, a comprehensive performance analysis of these approaches on datasets from different domains is needed. The objective of the study presented in this paper is to perform a comprehensive empirical analysis of selected frequency and topical graph-based algorithms for key concept extraction on three different datasets, to identify the major sources of error in these approaches. For experimental analysis, we have selected TF-IDF, KP-Miner and TopicRank. Three major sources of error, i.e., frequency errors, syntactical errors and semantical errors, and the factors that contribute to these errors are identified. Analysis of the results reveals that performance of the selected approaches is significantly degraded by these errors. These findings can help us develop an intelligent solution for key concept extraction in the future.

Method for Assessing Grid Frequency Deviation Due to Wind Power Fluctuation Based on “Time-Frequency Transformation”

DEFF Research Database (Denmark)

Jin, Lin; Yuan-zhang, Sun; Sørensen, Poul Ejnar

2012-01-01

published studies are based entirely on deterministic methodology. This paper presents a novel assessment method based on Time-Frequency Transformation to overcome shortcomings of existing methods. The main contribution of the paper is to propose a stochastic process simulation model which is a better...... alternative of the existing dynamic frequency deviation simulation model. In this way, the method takes the stochastic wind power fluctuation into full account so as to give a quantitative risk assessment of grid frequency deviation to grid operators, even without using any dynamic simulation tool. The case...

Identification Male Fertility Through Abnormalities Sperm Based Morphology (Teratospermia) using Invariant Moment Method

Science.gov (United States)

Syahputra, M. F.; Chairani, R.; Seniman; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Erliana, C. I.; Andayani, U.

2018-03-01

Sperm morphology is still a standard laboratory analysis in diagnosing infertility in men. Manually identification of sperm form is still not accurate, the difficulty in seeing the form of the invisible sperm from the digital microscope image is often a weakness in the process of identification and takes a long time. Therefore, male fertility identification application system is needed Through sperm abnormalities based on sperm morphology (teratospermia). The method used is invariant moment method. This study uses 15 data testing and 20 data training sperm image. That the process of male fertility identification through sperm abnormalities based on sperm morphology (teratospermia) has an accuracy rate of 80.77%. Use of time to process Identification of male fertility through sperm abnormalities Based on sperm morphology (teratospermia) during 0.4369 seconds.

Frequency scanning-based stability analysis method for grid-connected inverter system

DEFF Research Database (Denmark)

Wang, Yanbo; Wang, Xiongfei; Blaabjerg, Frede

2017-01-01

This paper proposes a frequency scanning-based impedance analysis for stability assessment of grid-connected inverter system, which is able to perform stability assessment without using system mathematical models and inherit the superior feature of impedance-based stability criterion with conside......This paper proposes a frequency scanning-based impedance analysis for stability assessment of grid-connected inverter system, which is able to perform stability assessment without using system mathematical models and inherit the superior feature of impedance-based stability criterion...... with consideration of the inverter nonlinearities. Small current disturbance is injected into grid-connected inverter system in a particular frequency range, and the impedance is computed according to the harmonic-frequency response using Fourier analysis, and then the stability is predicted on the basis...... of the impedance stability criterion. The stability issues of grid-connected inverters with grid-current feedback and the converter-current feedback are addressed using the proposed method. The results obtained from simulation and experiments validate the effectiveness of the method. The frequency scanning...

MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.

Science.gov (United States)

Tuta, Jure; Juric, Matjaz B

2018-03-24

This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method

Directory of Open Access Journals (Sweden)

Jure Tuta

2018-03-01

Full Text Available This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method, a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.. Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

[Study of biometric identification of heart sound base on Mel-Frequency cepstrum coefficient].

Science.gov (United States)

Chen, Wei; Zhao, Yihua; Lei, Sheng; Zhao, Zikai; Pan, Min

2012-12-01

Heart sound is a physiological parameter with individual characteristics generated by heart beat. To do the individual classification and recognition, in this paper, we present our study of using wavelet transform in the signal denoising, with the Mel-Frequency cepstrum coefficients (MFCC) as the feature parameters, and propose a research of reducing the dimensionality through principal components analysis (PCA). We have done the preliminary study to test the feasibility of biometric identification method using heart sound. The results showed that under the selected experimental conditions, the system could reach a 90% recognition rate. This study can provide a reference for further research.

System Identification A Frequency Domain Approach

CERN Document Server

Pintelon, Rik

2012-01-01

System identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and the designing of any electrical systems, they are vital in the fields of electrical, mechanical, civil, and chemical engineering. Focusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach. It high??lights many of the important steps in the identi

Gender Identification Using High-Frequency Speech Energy: Effects of Increasing the Low-Frequency Limit.

Science.gov (United States)

Donai, Jeremy J; Halbritter, Rachel M

The purpose of this study was to investigate the ability of normal-hearing listeners to use high-frequency energy for gender identification from naturally produced speech signals. Two experiments were conducted using a repeated-measures design. Experiment 1 investigated the effects of increasing high-pass filter cutoff (i.e., increasing the low-frequency spectral limit) on gender identification from naturally produced vowel segments. Experiment 2 studied the effects of increasing high-pass filter cutoff on gender identification from naturally produced sentences. Confidence ratings for the gender identification task were also obtained for both experiments. Listeners in experiment 1 were capable of extracting talker gender information at levels significantly above chance from vowel segments high-pass filtered up to 8.5 kHz. Listeners in experiment 2 also performed above chance on the gender identification task from sentences high-pass filtered up to 12 kHz. Cumulatively, the results of both experiments provide evidence that normal-hearing listeners can utilize information from the very high-frequency region (above 4 to 5 kHz) of the speech signal for talker gender identification. These findings are at variance with current assumptions regarding the perceptual information regarding talker gender within this frequency region. The current results also corroborate and extend previous studies of the use of high-frequency speech energy for perceptual tasks. These findings have potential implications for the study of information contained within the high-frequency region of the speech spectrum and the role this region may play in navigating the auditory scene, particularly when the low-frequency portion of the spectrum is masked by environmental noise sources or for listeners with substantial hearing loss in the low-frequency region and better hearing sensitivity in the high-frequency region (i.e., reverse slope hearing loss).

System Identification Methods for Aircraft Flight Control Development and Validation

Science.gov (United States)

1995-10-01

System-identification methods compose a mathematical model, or series of models, : from measurements of inputs and outputs of dynamic systems. This paper : discusses the use of frequency-domain system-identification methods for the : development and ...

Identification methods for structural health monitoring

CERN Document Server

Papadimitriou, Costas

2016-01-01

The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method). Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.

Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model

Directory of Open Access Journals (Sweden)

Yazid Edwar

2014-07-01

Full Text Available This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA. The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement.

Optimum Identification Method of Sorting Green Household Waste

Directory of Open Access Journals (Sweden)

Daud Mohd Hisam

2016-01-01

Full Text Available This project is related to design of sorting facility for reducing, reusing, recycling green waste material, and in particular to invent an automatic system to distinguish household waste in order to separate them from the main waste stream. The project focuses on thorough analysis of the properties of green household waste. The method of identification is using capacitive sensor where the characteristic data taken on three different sensor drive frequency. Three types of material have been chosen as a medium of this research, to be separated using the selected method. Based on capacitance characteristics and its ability to penetrate green object, optimum identification method is expected to be recognized in this project. The output capacitance sensor is in analogue value. The results demonstrate that the information from the sensor is enough to recognize the materials that have been selected.

Radar Emission Sources Identification Based on Hierarchical Agglomerative Clustering for Large Data Sets

Directory of Open Access Journals (Sweden)

Janusz Dudczyk

2016-01-01

Full Text Available More advanced recognition methods, which may recognize particular copies of radars of the same type, are called identification. The identification process of radar devices is a more specialized task which requires methods based on the analysis of distinctive features. These features are distinguished from the signals coming from the identified devices. Such a process is called Specific Emitter Identification (SEI. The identification of radar emission sources with the use of classic techniques based on the statistical analysis of basic measurable parameters of a signal such as Radio Frequency, Amplitude, Pulse Width, or Pulse Repetition Interval is not sufficient for SEI problems. This paper presents the method of hierarchical data clustering which is used in the process of radar identification. The Hierarchical Agglomerative Clustering Algorithm (HACA based on Generalized Agglomerative Scheme (GAS implemented and used in the research method is parameterized; therefore, it is possible to compare the results. The results of clustering are presented in dendrograms in this paper. The received results of grouping and identification based on HACA are compared with other SEI methods in order to assess the degree of their usefulness and effectiveness for systems of ESM/ELINT class.

Passive ultra high frequency radio frequency identification systems for single-item identification in food supply chains

Directory of Open Access Journals (Sweden)

Paolo Barge

2017-02-01

Full Text Available In the food industry, composition, size, and shape of items are much less regular than in other commodities sectors. In addition, a wide variety of packaging, composed by different materials, is employed. As material, size and shape of items to which the tag should be attached strongly influence the minimum power requested for tag functioning, performance improvements can be achieved only selecting suitable radio frequency (RF identifiers for the specific combination of food product and packaging. When dealing with logistics units, the dynamic reading of a vast number of tags could originate simultaneous broadcasting of signals (tag-to-tag collisions that could affect reading rates and the overall reliability of the identification procedure. This paper reports the results of an analysis of the reading performance of ultra high frequency radio frequency identification systems for multiple static and dynamic electronic identification of food packed products in controlled conditions. Products were considered when arranged on a logistics pallet. The effects on reading rate of different factors, among which the product type, the gate configuration, the field polarisation, the power output of the RF reader, the interrogation protocol configuration as well as the transit speed, the number of tags and their interactions were statistically analysed and compared.

Process identification method based on the Z transformation; Methode d'identification de processus par la transformation en Z

Energy Technology Data Exchange (ETDEWEB)

Zwingelstein, G [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1968-07-01

A simple method is described for identifying the transfer function of a linear retard-less system, based on the inversion of the Z transformation of the transmittance using a computer. It is assumed in this study that the signals at the entrance and at the exit of the circuit considered are of the deterministic type. The study includes: the theoretical principle of the inversion of the Z transformation, details about programming simulation, and identification of filters whose degrees vary from the first to the fifth order. (authors) [French] On decrit une methode simple d'identification de fonction de transfert d'un systeme lineaire sans retard, qui repose sur l'inversion de la transformee en Z de la transmittance a l'aide d'un calculateur. On suppose dans cette etude, que les signaux a l'entree et a la sortie du circuit considere sont de type deterministe. L'etude comporte: le principe theorique de l'inversion de la transformation en Z, les details de la programmation, la simulation et l'identification de filtres dont le degre varie du premier au cinquieme ordre. (auteurs)

A highly precise frequency-based method for estimating the tension of an inclined cable with unknown boundary conditions

Science.gov (United States)

Ma, Lin

2017-11-01

This paper develops a method for precisely determining the tension of an inclined cable with unknown boundary conditions. First, the nonlinear motion equation of an inclined cable is derived, and a numerical model of the motion of the cable is proposed using the finite difference method. The proposed numerical model includes the sag-extensibility, flexural stiffness, inclination angle and rotational stiffness at two ends of the cable. Second, the influence of the dynamic parameters of the cable on its frequencies is discussed in detail, and a method for precisely determining the tension of an inclined cable is proposed based on the derivatives of the eigenvalues of the matrices. Finally, a multiparameter identification method is developed that can simultaneously identify multiple parameters, including the rotational stiffness at two ends. This scheme is applicable to inclined cables with varying sag, varying flexural stiffness and unknown boundary conditions. Numerical examples indicate that the method provides good precision. Because the parameters of cables other than tension (e.g., the flexural stiffness and rotational stiffness at the ends) are not accurately known in practical engineering, the multiparameter identification method could further improve the accuracy of cable tension measurements.

Nuclear material enrichment identification method based on cross-correlation and high order spectra

International Nuclear Information System (INIS)

Yang Fan; Wei Biao; Feng Peng; Mi Deling; Ren Yong

2013-01-01

In order to enhance the sensitivity of nuclear material identification system (NMIS) against the change of nuclear material enrichment, the principle of high order statistic feature is introduced and applied to traditional NMIS. We present a new enrichment identification method based on cross-correlation and high order spectrum algorithm. By applying the identification method to NMIS, the 3D graphs with nuclear material character are presented and can be used as new signatures to identify the enrichment of nuclear materials. The simulation result shows that the identification method could suppress the background noises, electronic system noises, and improve the sensitivity against enrichment change to exponential order with no system structure modification. (authors)

The PLR-DTW method for ECG based biometric identification.

Science.gov (United States)

Shen, Jun; Bao, Shu-Di; Yang, Li-Cai; Li, Ye

2011-01-01

There has been a surge of research on electrocardiogram (ECG) signal based biometric for person identification. Though most of the existing studies claimed that ECG signal is unique to an individual and can be a viable biometric, one of the main difficulties for real-world applications of ECG biometric is the accuracy performance. To address this problem, this study proposes a PLR-DTW method for ECG biometric, where the Piecewise Linear Representation (PLR) is used to keep important information of an ECG signal segment while reduce the data dimension at the same time if necessary, and the Dynamic Time Warping (DTW) is used for similarity measures between two signal segments. The performance evaluation was carried out on three ECG databases, and the existing method using wavelet coefficients, which was proved to have good accuracy performance, was selected for comparison. The analysis results show that the PLR-DTW method achieves an accuracy rate of 100% for identification, while the one using wavelet coefficients achieved only around 93%.

Islanding Detection of Synchronous Machine-Based DGs using Average Frequency Based Index

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M. Bakhshi

2013-06-01

Full Text Available Identification of intentional and unintentional islanding situations of dispersed generators (DGs is one of the most important protection concerns in power systems. Considering safety and reliability problems of distribution networks, an exact diagnosis index is required to discriminate the loss of the main network from the existing parallel operation. Hence, this paper introduces a new islanding detection method for synchronous machine–based DGs. This method uses the average value of the generator frequency to calculate a new detection index. The proposed method is an effective supplement of the over/under frequency protection (OFP/UFP system. The analytical equations and simulation results are used to assess the performance of the proposed method under various scenarios such as different types of faults, load changes and capacitor bank switching. To show the effectiveness of the proposed method, it is compared with the performance of both ROCOF and ROCOFOP methods.

FPGA Implementation for GMM-Based Speaker Identification

Directory of Open Access Journals (Sweden)

Phaklen EhKan

2011-01-01

Full Text Available In today's society, highly accurate personal identification systems are required. Passwords or pin numbers can be forgotten or forged and are no longer considered to offer a high level of security. The use of biological features, biometrics, is becoming widely accepted as the next level for security systems. Biometric-based speaker identification is a method of identifying persons from their voice. Speaker-specific characteristics exist in speech signals due to different speakers having different resonances of the vocal tract. These differences can be exploited by extracting feature vectors such as Mel-Frequency Cepstral Coefficients (MFCCs from the speech signal. A well-known statistical modelling process, the Gaussian Mixture Model (GMM, then models the distribution of each speaker's MFCCs in a multidimensional acoustic space. The GMM-based speaker identification system has features that make it promising for hardware acceleration. This paper describes the hardware implementation for classification of a text-independent GMM-based speaker identification system. The aim was to produce a system that can perform simultaneous identification of large numbers of voice streams in real time. This has important potential applications in security and in automated call centre applications. A speedup factor of ninety was achieved compared to a software implementation on a standard PC.

A New Method of Reliability Evaluation Based on Wavelet Information Entropy for Equipment Condition Identification

International Nuclear Information System (INIS)

He, Z J; Zhang, X L; Chen, X F

2012-01-01

Aiming at reliability evaluation of condition identification of mechanical equipment, it is necessary to analyze condition monitoring information. A new method of reliability evaluation based on wavelet information entropy extracted from vibration signals of mechanical equipment is proposed. The method is quite different from traditional reliability evaluation models that are dependent on probability statistics analysis of large number sample data. The vibration signals of mechanical equipment were analyzed by means of second generation wavelet package (SGWP). We take relative energy in each frequency band of decomposed signal that equals a percentage of the whole signal energy as probability. Normalized information entropy (IE) is obtained based on the relative energy to describe uncertainty of a system instead of probability. The reliability degree is transformed by the normalized wavelet information entropy. A successful application has been achieved to evaluate the assembled quality reliability for a kind of dismountable disk-drum aero-engine. The reliability degree indicates the assembled quality satisfactorily.

An Automatic Parameter Identification Method for a PMSM Drive with LC-Filter

DEFF Research Database (Denmark)

Bech, Michael Møller; Christensen, Jeppe Haals; Weber, Magnus L.

2016-01-01

of the PMSM fed through an LC-filter. Based on the measured current response, model parameters for both the filter (L, R, C) and the PMSM (L and R) are estimated: First, the frequency response of the system is estimated using Welch Modified Periodogram method and then an optimization algorithm is used to find...... the parameters in an analytical reference model that minimize the model error. To demonstrate the practical feasibility of the method, a fully functional drive including an embedded real-time controller has been built. In addition to modulation, data acquisition and control the whole parameter identification...... method is also implemented on the real-time controller. Based on laboratory experiments on a 22 kW drive, it is concluded that the embedded identification method can estimate the five parameters in less than ten seconds....

Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT

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Cunsuo Pang

2016-09-01

Full Text Available This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method, is effective in reducing the computation load. A multi-order STFRFT time-frequency algorithm is also developed that makes use of the time-frequency feature of each micro-Doppler component signal. This algorithm improves the estimation accuracy of time-frequency curve fitting through multi-order matching. Finally, experiment data were used to demonstrate STFRFT’s performance in micro-Doppler time-frequency analysis. The results validated the higher estimate accuracy of the proposed algorithm. It may be applied to an LFM (Linear frequency modulated pulse radar, SAR (Synthetic aperture radar, or ISAR (Inverse synthetic aperture radar, for improving the probability of target recognition.

Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT.

Science.gov (United States)

Pang, Cunsuo; Han, Yan; Hou, Huiling; Liu, Shengheng; Zhang, Nan

2016-09-24

This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT) for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method, is effective in reducing the computation load. A multi-order STFRFT time-frequency algorithm is also developed that makes use of the time-frequency feature of each micro-Doppler component signal. This algorithm improves the estimation accuracy of time-frequency curve fitting through multi-order matching. Finally, experiment data were used to demonstrate STFRFT's performance in micro-Doppler time-frequency analysis. The results validated the higher estimate accuracy of the proposed algorithm. It may be applied to an LFM (Linear frequency modulated) pulse radar, SAR (Synthetic aperture radar), or ISAR (Inverse synthetic aperture radar), for improving the probability of target recognition.

A lithology identification method for continental shale oil reservoir based on BP neural network

Science.gov (United States)

Han, Luo; Fuqiang, Lai; Zheng, Dong; Weixu, Xia

2018-06-01

The Dongying Depression and Jiyang Depression of the Bohai Bay Basin consist of continental sedimentary facies with a variable sedimentary environment and the shale layer system has a variety of lithologies and strong heterogeneity. It is difficult to accurately identify the lithologies with traditional lithology identification methods. The back propagation (BP) neural network was used to predict the lithology of continental shale oil reservoirs. Based on the rock slice identification, x-ray diffraction bulk rock mineral analysis, scanning electron microscope analysis, and the data of well logging and logging, the lithology was divided with carbonate, clay and felsic as end-member minerals. According to the core-electrical relationship, the frequency histogram was then used to calculate the logging response range of each lithology. The lithology-sensitive curves selected from 23 logging curves (GR, AC, CNL, DEN, etc) were chosen as the input variables. Finally, the BP neural network training model was established to predict the lithology. The lithology in the study area can be divided into four types: mudstone, lime mudstone, lime oil-mudstone, and lime argillaceous oil-shale. The logging responses of lithology were complicated and characterized by the low values of four indicators and medium values of two indicators. By comparing the number of hidden nodes and the number of training times, we found that the number of 15 hidden nodes and 1000 times of training yielded the best training results. The optimal neural network training model was established based on the above results. The lithology prediction results of BP neural network of well XX-1 showed that the accuracy rate was over 80%, indicating that the method was suitable for lithology identification of continental shale stratigraphy. The study provided the basis for the reservoir quality and oily evaluation of continental shale reservoirs and was of great significance to shale oil and gas exploration.

The development of small-scale mechanization means positioning algorithm using radio frequency identification technology in industrial plants

Science.gov (United States)

Astafiev, A.; Orlov, A.; Privezencev, D.

2018-01-01

The article is devoted to the development of technology and software for the construction of positioning and control systems for small mechanization in industrial plants based on radio frequency identification methods, which will be the basis for creating highly efficient intelligent systems for controlling the product movement in industrial enterprises. The main standards that are applied in the field of product movement control automation and radio frequency identification are considered. The article reviews modern publications and automation systems for the control of product movement developed by domestic and foreign manufacturers. It describes the developed algorithm for positioning of small-scale mechanization means in an industrial enterprise. Experimental studies in laboratory and production conditions have been conducted and described in the article.

Identification of Natural Frequency of Low Rise Building on Soft Ground Profile using Ambient Vibration Method

Science.gov (United States)

Kamarudin, A. F.; Zainal Abidin, M. H.; Mokhatar, S. N.; Daud, M. E.; Ibrahim, A.; Ibrahim, Z.; Noh, M. S. Md

2018-04-01

Natural frequency is the rate at which a body to vibrate or oscillate. Application of ambient vibration (AV) excitation is widely used nowadays as the input motion for building predominant frequency, fo, and ground fundamental frequency, Fo, prediction due to simple, fast, non-destructive, simple handling operation and reliable result. However, it must be emphasized and caution to isolate these frequencies (fo and Fo) from spurious frequencies of site-structure effects especially to low rise building on soft ground deposit. In this study, identification of fo and Fo by using AV measurements were performed on ground and 4-storey primary school reinforced concrete (RC) building at Sekolah Kebangsaan (SK) Sg. Tongkang, Rengit, Johor using 1 Hz of tri-axial seismometer sensor. Overlapping spectra between Fourier Amplitude Spectra (FAS) from and Horizontal to Vertical Spectra Ratio (HVSR) were used to distinguish respective frequencies of building and ground natural frequencies. Three dominant frequencies were identified from the FAS curves at 1.91 Hz, 1.98 Hz and 2.79 Hz in longitudinal (East West-EW), transverse (North South-NS) and vertical (UD) directions. It is expected the building has deformed in translational mode based on the first peak frequency by respective NS and EW components of FAS spectrum. Vertical frequency identified from the horizontal spectrums, might induces to the potential of rocking effect experienced by the school building. Meanwhile, single peak HVSR spectrum at low ground fundamental frequency concentrated at 0.93 Hz indicates to the existence deep contrast of soft deposit. Strong interaction between ground and building at similar frequency (0.93 Hz) observed from the FAS curves on the highest floor has shown the building to behave as a dependent unit against ground response as one rigid mass.

Identification of material properties of orthotropic composite plate using experimental frequency response function data

Science.gov (United States)

Tam, Jun Hui; Ong, Zhi Chao; Ismail, Zubaidah; Ang, Bee Chin; Khoo, Shin Yee

2018-05-01

The demand for composite materials is increasing due to their great superiority in material properties, e.g., lightweight, high strength and high corrosion resistance. As a result, the invention of composite materials of diverse properties is becoming prevalent, and thus, leading to the development of material identification methods for composite materials. Conventional identification methods are destructive, time-consuming and costly. Therefore, an accurate identification approach is proposed to circumvent these drawbacks, involving the use of Frequency Response Function (FRF) error function defined by the correlation discrepancy between experimental and Finite-Element generated FRFs. A square E-glass epoxy composite plate is investigated under several different configurations of boundary conditions. It is notable that the experimental FRFs are used as the correlation reference, such that, during computation, the predicted FRFs are continuously updated with reference to the experimental FRFs until achieving a solution. The final identified elastic properties, namely in-plane elastic moduli, Ex and Ey, in-plane shear modulus, Gxy, and major Poisson's ratio, vxy of the composite plate are subsequently compared to the benchmark parameters as well as with those obtained using modal-based approach. As compared to the modal-based approach, the proposed method is found to have yielded relatively better results. This can be explained by the direct employment of raw data in the proposed method that avoids errors that might incur during the stage of modal extraction.

Wavelet-Based Frequency Response Function: Comparative Study of Input Excitation

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K. Dziedziech

2014-01-01

Full Text Available Time-variant systems can be found in many areas of engineering. It is widely accepted that the classical Fourier-based methods are not suitable for the analysis and identification of such systems. The time-variant frequency response function—based on the continuous wavelet transform—is used in this paper for the analysis of time-variant systems. The focus is on the comparative study of various broadband input excitations. The performance of the method is tested using simulated data from a simple MDOF system and experimental data from a frame-like structure.

Adaptive operational modal identification for slow linear time-varying structures based on frozen-in coefficient method and limited memory recursive principal component analysis

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Wang, Cheng; Guan, Wei; Wang, J. Y.; Zhong, Bineng; Lai, Xiongming; Chen, Yewang; Xiang, Liang

2018-02-01

To adaptively identify the transient modal parameters for linear weakly damped structures with slow time-varying characteristics under unmeasured stationary random ambient loads, this paper proposes a novel operational modal analysis (OMA) method based on the frozen-in coefficient method and limited memory recursive principal component analysis (LMRPCA). In the modal coordinate, the random vibration response signals of mechanical weakly damped structures can be decomposed into the inner product of modal shapes and modal responses, from which the natural frequencies and damping ratios can be well acquired by single-degree-of-freedom (SDOF) identification approach such as FFT. Hence, for the OMA method based on principal component analysis (PCA), it becomes very crucial to examine the relation between the transformational matrix and the modal shapes matrix, to find the association between the principal components (PCs) matrix and the modal responses matrix, and to turn the operational modal parameter identification problem into PCA of the stationary random vibration response signals of weakly damped mechanical structures. Based on the theory of "time-freezing", the method of frozen-in coefficient, and the assumption of "short time invariant" and "quasistationary", the non-stationary random response signals of the weakly damped and slow linear time-varying structures (LTV) can approximately be seen as the stationary random response time series of weakly damped and linear time invariant structures (LTI) in a short interval. Thus, the adaptive identification of time-varying operational modal parameters is turned into decompositing the PCs of stationary random vibration response signals subsection of weakly damped mechanical structures after choosing an appropriate limited memory window. Finally, a three-degree-of-freedom (DOF) structure with weakly damped and slow time-varying mass is presented to illustrate this method of identification. Results show that the LMRPCA

The PolyMAX Frequency-Domain Method: A New Standard for Modal Parameter Estimation?

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Bart Peeters

2004-01-01

Full Text Available Recently, a new non-iterative frequency-domain parameter estimation method was proposed. It is based on a (weighted least-squares approach and uses multiple-input-multiple-output frequency response functions as primary data. This so-called “PolyMAX” or polyreference least-squares complex frequency-domain method can be implemented in a very similar way as the industry standard polyreference (time-domain least-squares complex exponential method: in a first step a stabilisation diagram is constructed containing frequency, damping and participation information. Next, the mode shapes are found in a second least-squares step, based on the user selection of stable poles. One of the specific advantages of the technique lies in the very stable identification of the system poles and participation factors as a function of the specified system order, leading to easy-to-interpret stabilisation diagrams. This implies a potential for automating the method and to apply it to “difficult” estimation cases such as high-order and/or highly damped systems with large modal overlap. Some real-life automotive and aerospace case studies are discussed. PolyMAX is compared with classical methods concerning stability, accuracy of the estimated modal parameters and quality of the frequency response function synthesis.

Active Magnetic Bearings Stiffness and Damping Identification from Frequency Characteristics of Control System

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Chaowu Jin

2016-01-01

Full Text Available At present, the stiffness and damping identification for active magnetic bearings (AMBs are still in the stage of theoretical analysis. The theoretical analysis indicates that if the mechanical structure and system parameters are determined, AMBs stiffness and damping are only related to frequency characteristic of control system, ignoring operating condition. More importantly, few verification methods are proposed. Considering the shortcomings of the theoretical identification, this paper obtains these coefficients from the experiment by using the magnetic bearing as a sine exciter. The identification results show that AMBs stiffness and damping have a great relationship with the control system and rotating speed. Specifically, at low rotating speed, the stiffness and damping can be obtained from the rotor static suspension by adding the same excitation frequency. However, at high speed, different from the static suspension situation, the AMBs supporting coefficients are not only related to the frequency characteristics of control system, but also related to the system operating conditions.

Damage Detection Based on Cross-Term Extraction from Bilinear Time-Frequency Distributions

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Ma Yuchao

2014-01-01

Full Text Available Abundant damage information is implicated in the bilinear time-frequency distribution of structural dynamic signals, which could provide effective support for structural damage identification. Signal time-frequency analysis methods are reviewed, and the characters of linear time-frequency distribution and bilinear time-frequency distribution typically represented by the Wigner-Ville distribution are compared. The existence of the cross-term and its application in structural damage detection are demonstrated. A method of extracting the dominant term is proposed, which combines the short-time Fourier spectrum and Wigner-Ville distribution; then two-dimensional time-frequency transformation matrix is constructed and the complete cross-term is extracted finally. The distribution character of which could be applied to the structural damage identification. Through theoretical analysis, model experiment and numerical simulation of the girder structure, the change rate of cross-term amplitude is validated to identify the damage location and degree. The effectiveness of the cross-term of bilinear time-frequency distribution for damage detection is confirmed and the analytical method of damage identification used in structural engineering is available.

Rotor Resistance Online Identification of Vector Controlled Induction Motor Based on Neural Network

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Bo Fan

2014-01-01

Full Text Available Rotor resistance identification has been well recognized as one of the most critical factors affecting the theoretical study and applications of AC motor’s control for high performance variable frequency speed adjustment. This paper proposes a novel model for rotor resistance parameters identification based on Elman neural networks. Elman recurrent neural network is capable of performing nonlinear function approximation and possesses the ability of time-variable characteristic adaptation. Those influencing factors of specified parameter are analyzed, respectively, and various work states are covered to ensure the completeness of the training samples. Through signal preprocessing on samples and training dataset, different input parameters identifications with one network are compared and analyzed. The trained Elman neural network, applied in the identification model, is able to efficiently predict the rotor resistance in high accuracy. The simulation and experimental results show that the proposed method owns extensive adaptability and performs very well in its application to vector controlled induction motor. This identification method is able to enhance the performance of induction motor’s variable-frequency speed regulation.

The Diffusion and Impact of Radio Frequency Identification in Supply Chains: A Multi-Method Approach

Science.gov (United States)

Wu, Xiaoran

2012-01-01

As a promising and emerging technology for supply chain management, Radio Frequency Identification (RFID) is a new alternative to existing tracking technologies and also allows a range of internal control and supply chain coordination. RFID has generated a significant amount of interest and activities from both practitioners and researchers in…

Process identification method based on the Z transformation

International Nuclear Information System (INIS)

Zwingelstein, G.

1968-01-01

A simple method is described for identifying the transfer function of a linear retard-less system, based on the inversion of the Z transformation of the transmittance using a computer. It is assumed in this study that the signals at the entrance and at the exit of the circuit considered are of the deterministic type. The study includes: the theoretical principle of the inversion of the Z transformation, details about programming simulation, and identification of filters whose degrees vary from the first to the fifth order. (authors) [fr

Face identification with frequency domain matched filtering in mobile environments

Science.gov (United States)

Lee, Dong-Su; Woo, Yong-Hyun; Yeom, Seokwon; Kim, Shin-Hwan

2012-06-01

Face identification at a distance is very challenging since captured images are often degraded by blur and noise. Furthermore, the computational resources and memory are often limited in the mobile environments. Thus, it is very challenging to develop a real-time face identification system on the mobile device. This paper discusses face identification based on frequency domain matched filtering in the mobile environments. Face identification is performed by the linear or phase-only matched filter and sequential verification stages. The candidate window regions are decided by the major peaks of the linear or phase-only matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering test, which verify color and shape information of the candidate regions in order to remove false alarms. All algorithms are built on the mobile device using Android platform. The preliminary results show that face identification of East Asian people can be performed successfully in the mobile environments.

Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System

Directory of Open Access Journals (Sweden)

Minghong She

2018-01-01

Full Text Available For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. By using the same projection of related data in time offset set and LQ decomposition, the multiplication operation of projection is achieved and dynamics estimation of the unknown equipment system model is obtained. Consequently, we have solved the problem of biased estimation caused when the open-loop subspace identification algorithm is applied to the closed-loop identification. A simulation example is given to show the effectiveness of the proposed approach. In final, the practicability of the identification algorithm is verified by hardware test of UAV servo system in real environment.

Rule Based Expert System for Monitoring Real Time Drug Supply in Hospital Using Radio Frequency Identification Technology

Science.gov (United States)

Driandanu, Galih; Surarso, Bayu; Suryono

2018-02-01

A radio frequency identification (RFID) has obtained increasing attention with the emergence of various applications. This study aims to examine the implementation of rule based expert system supported by RFID technology into a monitoring information system of drug supply in a hospital. This research facilitates in monitoring the real time drug supply by using data sample from the hospital pharmacy. This system able to identify and count the number of drug and provide warning and report in real time. the conclusion is the rule based expert system and RFID technology can facilitate the performance in monitoring the drug supply quickly and precisely.

Mathematical correlation of modal parameter identification methods via system realization theory

Science.gov (United States)

Juang, J. N.

1986-01-01

A unified approach is introduced using system realization theory to derive and correlate modal parameter identification methods for flexible structures. Several different time-domain and frequency-domain methods are analyzed and treated. A basic mathematical foundation is presented which provides insight into the field of modal parameter identification for comparison and evaluation. The relation among various existing methods is established and discussed. This report serves as a starting point to stimulate additional research towards the unification of the many possible approaches for modal parameter identification.

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

Science.gov (United States)

Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

48 CFR 552.211-92 - Radio Frequency Identification (RFID) using passive tags.

Science.gov (United States)

2010-10-01

... Identification (RFID) using passive tags. 552.211-92 Section 552.211-92 Federal Acquisition Regulations System... Provisions and Clauses 552.211-92 Radio Frequency Identification (RFID) using passive tags. As prescribed in 511.204(b)(11), insert the following clause: Radio Frequency Identification (RFID) Using Passive Tags...

Applications of wind generation for power system frequency control, inter-area oscillations damping and parameter identification

Science.gov (United States)

Wilches-Bernal, Felipe

Power systems around the world are experiencing a continued increase in wind generation as part of their energy mix. Because of its power electronics interface, wind energy conversion systems interact differently with the grid than conventional generation. These facts are changing the traditional dynamics that regulate power system behavior and call for a re-examination of traditional problems encountered in power systems like frequency response, inter-area oscillations and parameter identification. To address this need, realistic models for wind generation are necessary. The dissertation implements such models in a MATLAB-based flexible environment suited for power system research. The dissertation continues with an analysis of the frequency response of a test power system dependent mainly on a mode referred to as the frequency regulation mode. Using this test system it is shown that its frequency regulation capability is reduced with wind penetration levels of 25% and above. A controller for wind generation to restore the frequency response of the system is then presented. The proposed controller requires the WTG to operate in a deloaded mode, a condition that is obtained through pitching the wind turbine blades. Time simulations at wind penetration levels of 25% and 50% are performed to demonstrate the effectiveness of the proposed controller. Next, the dissertation evaluates how the inter-area oscillation of a two-machine power system is affected by wind integration. The assessment is performed based on the positioning of the WTG, the level of wind penetration, and the loading condition of the system. It is determined that integrating wind reduces the damping of the inter-area mode of the system when performed in an area that imports power. For this worst-case scenario, the dissertation proposes two controllers for wind generation to improve the damping of the inter-area mode. The first controller uses frequency as feedback signal for the active power control

Diagnosis and Model Based Identification of a Coupling Misalignment

Directory of Open Access Journals (Sweden)

P. Pennacchi

2005-01-01

Full Text Available This paper is focused on the application of two different diagnostic techniques aimed to identify the most important faults in rotating machinery as well as on the simulation and prediction of the frequency response of rotating machines. The application of the two diagnostics techniques, the orbit shape analysis and the model based identification in the frequency domain, is described by means of an experimental case study that concerns a gas turbine-generator unit of a small power plant whose rotor-train was affected by an angular misalignment in a flexible coupling, caused by a wrong machine assembling. The fault type is identified by means of the orbit shape analysis, then the equivalent bending moments, which enable the shaft experimental vibrations to be simulated, have been identified using a model based identification method. These excitations have been used to predict the machine vibrations in a large rotating speed range inside which no monitoring data were available. To the best of the authors' knowledge, this is the first case of identification of coupling misalignment and prediction of the consequent machine behaviour in an actual size rotating machinery. The successful results obtained emphasise the usefulness of integrating common condition monitoring techniques with diagnostic strategies.

The Tracking Resonance Frequency Method for Photoacoustic Measurements Based on the Phase Response

Science.gov (United States)

Suchenek, Mariusz

2017-04-01

One of the major issues in the use of the resonant photoacoustic cell is the resonance frequency of the cell. The frequency is not stable, and its changes depend mostly on temperature and gas mixture. This paper presents a new method for tracking resonance frequency, where both the amplitude and phase are calculated from the input samples. The stimulating frequency can be adjusted to the resonance frequency of the cell based on the phase. This method was implemented using a digital measurement system with an analog to digital converter, field programmable gate array (FPGA) and a microcontroller. The resonance frequency was changed by the injection of carbon dioxide into the cell. A theoretical description and experimental results are also presented.

Structural system identification based on variational mode decomposition

Science.gov (United States)

Bagheri, Abdollah; Ozbulut, Osman E.; Harris, Devin K.

2018-03-01

In this paper, a new structural identification method is proposed to identify the modal properties of engineering structures based on dynamic response decomposition using the variational mode decomposition (VMD). The VMD approach is a decomposition algorithm that has been developed as a means to overcome some of the drawbacks and limitations of the empirical mode decomposition method. The VMD-based modal identification algorithm decomposes the acceleration signal into a series of distinct modal responses and their respective center frequencies, such that when combined their cumulative modal responses reproduce the original acceleration response. The decaying amplitude of the extracted modal responses is then used to identify the modal damping ratios using a linear fitting function on modal response data. Finally, after extracting modal responses from available sensors, the mode shape vector for each of the decomposed modes in the system is identified from all obtained modal response data. To demonstrate the efficiency of the algorithm, a series of numerical, laboratory, and field case studies were evaluated. The laboratory case study utilized the vibration response of a three-story shear frame, whereas the field study leveraged the ambient vibration response of a pedestrian bridge to characterize the modal properties of the structure. The modal properties of the shear frame were computed using analytical approach for a comparison with the experimental modal frequencies. Results from these case studies demonstrated that the proposed method is efficient and accurate in identifying modal data of the structures.

A Novel L-Shape Ultra Wideband Chipless Radio-Frequency Identification Tag

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Khaled Issa

2017-01-01

Full Text Available A novel compact dual-polarized-spectral-signature-based chipless radio-frequency identification (RFID tag is presented. Specifically, an L-shape resonator-based structure is optimized to have different spectral signatures in both horizontal and vertical polarizations, in order to double the encoding capacity. Resonators’ slot width and the space between closely placed resonators are also optimized to enhance the mutual coupling, thereby helping in achieving high-data encoding density. The proposed RFID tag operates over 5 GHz to 10 GHz frequency band. As a proof of concept, three different 18-bit dual-polarized RFID tags are simulated, fabricated, and tested in an anechoic chamber environment. The measurement data show reasonable agreement with the simulation results, with respect to resonators’ frequency positions, null depth, and their bandwidth over the operational spectrum.

Parametric and Non-Parametric Vibration-Based Structural Identification Under Earthquake Excitation

Science.gov (United States)

Pentaris, Fragkiskos P.; Fouskitakis, George N.

2014-05-01

The problem of modal identification in civil structures is of crucial importance, and thus has been receiving increasing attention in recent years. Vibration-based methods are quite promising as they are capable of identifying the structure's global characteristics, they are relatively easy to implement and they tend to be time effective and less expensive than most alternatives [1]. This paper focuses on the off-line structural/modal identification of civil (concrete) structures subjected to low-level earthquake excitations, under which, they remain within their linear operating regime. Earthquakes and their details are recorded and provided by the seismological network of Crete [2], which 'monitors' the broad region of south Hellenic arc, an active seismic region which functions as a natural laboratory for earthquake engineering of this kind. A sufficient number of seismic events are analyzed in order to reveal the modal characteristics of the structures under study, that consist of the two concrete buildings of the School of Applied Sciences, Technological Education Institute of Crete, located in Chania, Crete, Hellas. Both buildings are equipped with high-sensitivity and accuracy seismographs - providing acceleration measurements - established at the basement (structure's foundation) presently considered as the ground's acceleration (excitation) and at all levels (ground floor, 1st floor, 2nd floor and terrace). Further details regarding the instrumentation setup and data acquisition may be found in [3]. The present study invokes stochastic, both non-parametric (frequency-based) and parametric methods for structural/modal identification (natural frequencies and/or damping ratios). Non-parametric methods include Welch-based spectrum and Frequency response Function (FrF) estimation, while parametric methods, include AutoRegressive (AR), AutoRegressive with eXogeneous input (ARX) and Autoregressive Moving-Average with eXogeneous input (ARMAX) models[4, 5

Location identification of closed crack based on Duffing oscillator transient transition

Science.gov (United States)

Liu, Xiaofeng; Bo, Lin; Liu, Yaolu; Zhao, Youxuan; Zhang, Jun; Deng, Mingxi; Hu, Ning

2018-02-01

The existence of a closed micro-crack in plates can be detected by using the nonlinear harmonic characteristics of the Lamb wave. However, its location identification is difficult. By considering the transient nonlinear Lamb under the noise interference, we proposed a location identification method for the closed crack based on the quantitative measurement of Duffing oscillator transient transfer in the phase space. The sliding short-time window was used to create a window truncation of to-be-detected signal. And then, the periodic extension processing for transient nonlinear Lamb wave was performed to ensure that the Duffing oscillator has adequate response time to reach a steady state. The transient autocorrelation method was used to reduce the occurrence of missed harmonic detection due to the random variable phase of nonlinear Lamb wave. Moreover, to overcome the deficiency in the quantitative analysis of Duffing system state by phase trajectory diagram and eliminate the misjudgment caused by harmonic frequency component contained in broadband noise, logic operation method of oscillator state transition function based on circular zone partition was adopted to establish the mapping relation between the oscillator transition state and the nonlinear harmonic time domain information. Final state transition discriminant function of Duffing oscillator was used as basis for identifying the reflected and transmitted harmonics from the crack. Chirplet time-frequency analysis was conducted to identify the mode of generated harmonics and determine the propagation speed. Through these steps, accurate position identification of the closed crack was achieved.

Joint DOA and Fundamental Frequency Estimation Methods based on 2-D Filtering

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt

2010-01-01

of the fundamental frequency and the DOA of spatio-temporarily sampled periodic signals. The first and simplest method is based on the 2-D periodogram, whereas the second method is a generalization of the 2-D Capon method. In the experimental part, both qualitative and quantitative measurements show that the proposed...

Study of Biometric Identification Method Based on Naked Footprint

Directory of Open Access Journals (Sweden)

Raji Rafiu King

2013-10-01

Full Text Available The scale of deployment of biometric identity-verification systems has recently seen an enormous increase owing to the need for more secure and reliable way of identifying people. Footprint identification which can be defined as the measurement of footprint features for recognizing the identity of a user has surfaced recently. This study is based on a biometric personal identification method using static footprint features viz. friction ridge / texture and foot shape / silhouette. To begin with, naked footprints of users are captured; images then undergo pre processing followed by the extraction of two features; shape using Gradient Vector Flow （GVF） snake model and minutiae extraction respectively. Matching is then effected based on these two features followed by a fusion of these two results for either a reject or accept decision. Our shape matching feature is based on cosine similarity while the texture one is based on miniature score matching. The results from our research establish that the naked footprint is a credible biometric feature as two barefoot impressions of an individual match perfectly while that of two different persons shows a great deal of dissimilarity. Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Doi: 10.12777/ijse.5.2.29-35 How to cite this article: King

An automatic method to determine cutoff frequency based on image power spectrum

International Nuclear Information System (INIS)

Beis, J.S.; Vancouver Hospital and Health Sciences Center, British Columbia; Celler, A.; Barney, J.S.

1995-01-01

The authors present an algorithm for automatically choosing filter cutoff frequency (F c ) using the power spectrum of the projections. The method is based on the assumption that the expectation of the image power spectrum is the sum of the expectation of the blurred object power spectrum (dominant at low frequencies) plus a constant value due to Poisson noise. By considering the discrete components of the noise-dominated high-frequency spectrum as a Gaussian distribution N(μ,σ), the Student t-test determines F c as the highest frequency for which the image frequency components are unlikely to be drawn from N (μ,σ). The method is general and can be applied to any filter. In this work, the authors tested the approach using the Metz restoration filter on simulated, phantom, and patient data with good results. Quantitative performance of the technique was evaluated by plotting recovery coefficient (RC) versus NMSE of reconstructed images

Identification of fractional order systems using modulating functions method

KAUST Repository

Liu, Dayan

2013-06-01

The modulating functions method has been used for the identification of linear and nonlinear systems. In this paper, we generalize this method to the on-line identification of fractional order systems based on the Riemann-Liouville fractional derivatives. First, a new fractional integration by parts formula involving the fractional derivative of a modulating function is given. Then, we apply this formula to a fractional order system, for which the fractional derivatives of the input and the output can be transferred into the ones of the modulating functions. By choosing a set of modulating functions, a linear system of algebraic equations is obtained. Hence, the unknown parameters of a fractional order system can be estimated by solving a linear system. Using this method, we do not need any initial values which are usually unknown and not equal to zero. Also we do not need to estimate the fractional derivatives of noisy output. Moreover, it is shown that the proposed estimators are robust against high frequency sinusoidal noises and the ones due to a class of stochastic processes. Finally, the efficiency and the stability of the proposed method is confirmed by some numerical simulations.

Comments on Frequency Swept Rotating Input Perturbation Techniques and Identification of the Fluid Force Models in Rotor/bearing/seal Systems and Fluid Handling Machines

Science.gov (United States)

Muszynska, Agnes; Bently, Donald E.

1991-01-01

Perturbation techniques used for identification of rotating system dynamic characteristics are described. A comparison between two periodic frequency-swept perturbation methods applied in identification of fluid forces of rotating machines is presented. The description of the fluid force model identified by inputting circular periodic frequency-swept force is given. This model is based on the existence and strength of the circumferential flow, most often generated by the shaft rotation. The application of the fluid force model in rotor dynamic analysis is presented. It is shown that the rotor stability is an entire rotating system property. Some areas for further research are discussed.

Implementasi Rule Based Expert Systems untuk Realtime Monitoring Penyelesaian Perkara Pidana Menggunakan Teknologi Radio Frequency Identification

Directory of Open Access Journals (Sweden)

Mar Fuah

2017-05-01

Full Text Available One of the problems in the criminal case completions is that the difficulty of making decision to estimate when the settlement of the case file will be fulfilled. It is caused by the number of case files handled and detention time changing. Therefore, the fast and accurate information is needed. The research aims to develop a monitoring system tracking and tracking of scheduling rules using Rule Based Expert Systems method with 17 rules, and supported by Radio Frequency Identification technology (RFID in the form of computer applications. Based on the output of the system, an analysis is performed in the criminal case settlement process with a set of IF-THEN rules. The RFID reader read the data of case files through radio wave signals emitted by the antenna toward active-Tag attached in the criminal case file. The system is designed to monitor the tracking and tracing of RFID-based scheduling rules in realtime way that was built in the form of computer application in accordance with the system design. This study results in no failure in reading active tags by the RFID reader to detect criminal case files that had been examined. There were many case files handled in three different location, they were the constabulary, prosecutor, and judges of district court and RFID was able to identify them simultaneously. So, RFID supports the implementation of Rule Based Expert Systems very much for realtime monitoring in criminal case accomplishment.

A Dissipation Gap Method for full-field measurement-based identification of elasto-plastic material parameters

KAUST Repository

Blaysat, Benoît

2012-05-18

Using enriched data such as displacement fields obtained from digital image correlation is a pathway to the local identification of material parameters. Up to now, most of the identification techniques for nonlinear models are based on Finite Element Updating Methods. This article explains how an appropriate use of the Dissipation Gap Method can help in this context and be an interesting alternative to these classical techniques. The Dissipation Gap Methods rely on the concept of error in dissipation that has been used mainly for the verification of finite element simulations. We provide here an original application of these founding developments to the identification of material parameters for nonlinear behaviors. The proposed technique and especially the main technical keypoint of building the admissible fields are described in detail. The approach is then illustrated through the identification of heterogeneous isotropic elasto-plastic properties. The basic numerical features highlighted through these simple examples demonstrate this approach to be a promising tool for nonlinear identification. © 2012 John Wiley & Sons, Ltd.

Biometric and Emotion Identification: An ECG Compression Based Method.

Science.gov (United States)

Brás, Susana; Ferreira, Jacqueline H T; Soares, Sandra C; Pinho, Armando J

2018-01-01

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

Radio Frequency Identification (RFID) in medical environment: Gaussian Derivative Frequency Modulation (GDFM) as a novel modulation technique with minimal interference properties.

Science.gov (United States)

Rieche, Marie; Komenský, Tomás; Husar, Peter

2011-01-01

Radio Frequency Identification (RFID) systems in healthcare facilitate the possibility of contact-free identification and tracking of patients, medical equipment and medication. Thereby, patient safety will be improved and costs as well as medication errors will be reduced considerably. However, the application of RFID and other wireless communication systems has the potential to cause harmful electromagnetic disturbances on sensitive medical devices. This risk mainly depends on the transmission power and the method of data communication. In this contribution we point out the reasons for such incidents and give proposals to overcome these problems. Therefore a novel modulation and transmission technique called Gaussian Derivative Frequency Modulation (GDFM) is developed. Moreover, we carry out measurements to show the inteference properties of different modulation schemes in comparison to our GDFM.

An Islanding Detection Method by Using Frequency Positive Feedback Based on FLL for Single-Phase Microgrid

DEFF Research Database (Denmark)

Sun, Qinfei; Guerrero, Josep M.; Jing, Tianjun

2017-01-01

An active islanding detection method based on Frequency-Locked Loop (FLL) for constant power controlled inverter in single-phase microgrid is proposed. This method generates a phase shift comparing the instantaneous frequency obtained from FLL unit with the nominal frequency to modify the reference...

Application of Story-wise Shear Building Identification Method to Actual Ambient Vibration

Directory of Open Access Journals (Sweden)

Kohei eFujita

2015-02-01

Full Text Available A sophisticated and smart story stiffness System Identification (SI method for a shear building model is applied to a full-scale building frame subjected to micro-tremors. The advantageous and novel feature is that not only the modal parameters, such as natural frequencies and damping ratios, but also the physical model parameters, such as story stiffnesses and damping coefficients, can be identified using micro-tremors. While the building responses to earthquake ground motions are necessary in the previous SI method, it is shown in this paper that the micro-tremor measurements in a full-scale 5 story building frame can be used for identification within the same framework. The SI using micro-tremor measurements leads to the enhanced usability of the previously proposed story-wise shear building identification method. The degree of ARX models and cut-off frequencies of band-pass filter are determined to derive reliable results.

Health condition identification of multi-stage planetary gearboxes using a mRVM-based method

Science.gov (United States)

Lei, Yaguo; Liu, Zongyao; Wu, Xionghui; Li, Naipeng; Chen, Wu; Lin, Jing

2015-08-01

Multi-stage planetary gearboxes are widely applied in aerospace, automotive and heavy industries. Their key components, such as gears and bearings, can easily suffer from damage due to tough working environment. Health condition identification of planetary gearboxes aims to prevent accidents and save costs. This paper proposes a method based on multiclass relevance vector machine (mRVM) to identify health condition of multi-stage planetary gearboxes. In this method, a mRVM algorithm is adopted as a classifier, and two features, i.e. accumulative amplitudes of carrier orders (AACO) and energy ratio based on difference spectra (ERDS), are used as the input of the classifier to classify different health conditions of multi-stage planetary gearboxes. To test the proposed method, seven health conditions of a two-stage planetary gearbox are considered and vibration data is acquired from the planetary gearbox under different motor speeds and loading conditions. The results of three tests based on different data show that the proposed method obtains an improved identification performance and robustness compared with the existing method.

Spectral and spectral-frequency methods of investigating atmosphereless bodies of the Solar system

International Nuclear Information System (INIS)

Busarev, Vladimir V; Prokof'eva-Mikhailovskaya, Valentina V; Bochkov, Valerii V

2007-01-01

A method of reflectance spectrophotometry of atmosphereless bodies of the Solar system, its specificity, and the means of eliminating basic spectral noise are considered. As a development, joining the method of reflectance spectrophotometry with the frequency analysis of observational data series is proposed. The combined spectral-frequency method allows identification of formations with distinctive spectral features, and estimations of their sizes and distribution on the surface of atmospherelss celestial bodies. As applied to investigations of asteroids 21 Lutetia and 4 Vesta, the spectral frequency method has given us the possibility of obtaining fundamentally new information about minor planets. (instruments and methods of investigation)

Biometric and Emotion Identification: An ECG Compression Based Method

Directory of Open Access Journals (Sweden)

Susana Brás

2018-04-01

Full Text Available We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG. The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1 conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2 conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3 identification of the ECG record class, using a 1-NN (nearest neighbor classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

Biometric and Emotion Identification: An ECG Compression Based Method

Science.gov (United States)

Brás, Susana; Ferreira, Jacqueline H. T.; Soares, Sandra C.; Pinho, Armando J.

2018-01-01

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model. PMID:29670564

A frequency domain radar interferometric imaging (FII) technique based on high-resolution methods

Science.gov (United States)

Luce, H.; Yamamoto, M.; Fukao, S.; Helal, D.; Crochet, M.

2001-01-01

In the present work, we propose a frequency-domain interferometric imaging (FII) technique for a better knowledge of the vertical distribution of the atmospheric scatterers detected by MST radars. This is an extension of the dual frequency-domain interferometry (FDI) technique to multiple frequencies. Its objective is to reduce the ambiguity (resulting from the use of only two adjacent frequencies), inherent with the FDI technique. Different methods, commonly used in antenna array processing, are first described within the context of application to the FII technique. These methods are the Fourier-based imaging, the Capon's and the singular value decomposition method used with the MUSIC algorithm. Some preliminary simulations and tests performed on data collected with the middle and upper atmosphere (MU) radar (Shigaraki, Japan) are also presented. This work is a first step in the developments of the FII technique which seems to be very promising.

Study on Fault Diagnosis of Rolling Bearing Based on Time-Frequency Generalized Dimension

Directory of Open Access Journals (Sweden)

Yu Yuan

2015-01-01

Full Text Available The condition monitoring technology and fault diagnosis technology of mechanical equipment played an important role in the modern engineering. Rolling bearing is the most common component of mechanical equipment which sustains and transfers the load. Therefore, fault diagnosis of rolling bearings has great significance. Fractal theory provides an effective method to describe the complexity and irregularity of the vibration signals of rolling bearings. In this paper a novel multifractal fault diagnosis approach based on time-frequency domain signals was proposed. The method and numerical algorithm of Multi-fractal analysis in time-frequency domain were provided. According to grid type J and order parameter q in algorithm, the value range of J and the cut-off condition of q were optimized based on the effect on the dimension calculation. Simulation experiments demonstrated that the effective signal identification could be complete by multifractal method in time-frequency domain, which is related to the factors such as signal energy and distribution. And the further fault diagnosis experiments of bearings showed that the multifractal method in time-frequency domain can complete the fault diagnosis, such as the fault judgment and fault types. And the fault detection can be done in the early stage of fault. Therefore, the multifractal method in time-frequency domain used in fault diagnosis of bearing is a practicable method.

Wireless Hydrogen Smart Sensor Based on Pt/Graphene-Immobilized Radio-Frequency Identification Tag.

Science.gov (United States)

Lee, Jun Seop; Oh, Jungkyun; Jun, Jaemoon; Jang, Jyongsik

2015-08-25

Hydrogen, a clean-burning fuel, is of key importance to various industrial applications, including fuel cells and the aerospace and automotive industries. However, hydrogen gas is odorless, colorless, and highly flammable; thus, appropriate safety protocol implementation and monitoring are essential. Highly sensitive hydrogen-gas leak detection and surveillance systems are needed; additionally, the ability to monitor large areas (e.g., cities) via wireless networks is becoming increasingly important. In this report, we introduce a radio frequency identification (RFID)-based wireless smart-sensor system, composed of a Pt-decorated reduced graphene oxide (Pt_rGO)-immobilized RFID sensor tag and an RFID-reader antenna-connected network analyzer to detect hydrogen gas. The Pt_rGOs, produced using a simple chemical reduction process, were immobilized on an antenna pattern in the sensor tag through spin coating. The resulting Pt_rGO-based RFID sensor tag exhibited a high sensitivity to hydrogen gas at unprecedentedly low concentrations (1 ppm), with wireless communication between the sensor tag and RFID-reader antenna. The wireless sensor tag demonstrated flexibility and a long lifetime due to the strong immobilization of Pt_rGOs on the substrate and battery-independent operation during hydrogen sensing, respectively.

Time-domain modeling for shielding effectiveness of materials against electromagnetic pulse based on system identification

International Nuclear Information System (INIS)

Chen, Xiang; Chen, Yong Guang; Wei, Ming; Hu, Xiao Feng

2013-01-01

Shielding effectiveness (SE) of materials against electromagnetic pulse (EMP) cannot be well estimated by traditional test method of SE of materials which only consider the amplitude-frequency characteristic of materials, but ignore the phase-frequency ones. In order to solve this problem, the model of SE of materials against EMP was established based on system identification (SI) method with time-domain linear cosine frequency sweep signal. The feasibility of the method in this paper was examined depending on infinite planar material and the simulation research of coaxial test method and windowed semi-anechoic box of materials. The results show that the amplitude-frequency and phase-frequency information of each frequency can be fully extracted with this method. SE of materials against strong EMP can be evaluated with time-domain low field strength (voltage) of cosine frequency sweep signal. And SE of materials against a variety EMP will be predicted by the model.

A Novel Coupled State/Input/Parameter Identification Method for Linear Structural Systems

Directory of Open Access Journals (Sweden)

Zhimin Wan

2018-01-01

Full Text Available In many engineering applications, unknown states, inputs, and parameters exist in the structures. However, most methods require one or two of these variables to be known in order to identify the other(s. Recently, the authors have proposed a method called EGDF for coupled state/input/parameter identification for nonlinear system in state space. However, the EGDF method based solely on acceleration measurements is found to be unstable, which can cause the drift of the identified inputs and displacements. Although some regularization methods can be adopted for solving the problem, they are not suitable for joint input-state identification in real time. In this paper, a strategy of data fusion of displacement and acceleration measurements is used to avoid the low-frequency drift in the identified inputs and structural displacements for linear structural systems. Two numerical examples about a plane truss and a single-stage isolation system are conducted to verify the effectiveness of the proposed modified EGDF algorithm.

Use of Time-Frequency Analysis and Neural Networks for Mode Identification in a Wireless Software-Defined Radio Approach

Directory of Open Access Journals (Sweden)

Matteo Gandetto

2004-09-01

Full Text Available The use of time-frequency distributions is proposed as a nonlinear signal processing technique that is combined with a pattern recognition approach to identify superimposed transmission modes in a reconfigurable wireless terminal based on software-defined radio techniques. In particular, a software-defined radio receiver is described aiming at the identification of two coexistent communication modes: frequency hopping code division multiple access and direct sequence code division multiple access. As a case study, two standards, based on the previous modes and operating in the same band (industrial, scientific, and medical, are considered: IEEE WLAN 802.11b (direct sequence and Bluetooth (frequency hopping. Neural classifiers are used to obtain identification results. A comparison between two different neural classifiers is made in terms of relative error frequency.

A time-frequency analysis method to obtain stable estimates of magnetotelluric response function based on Hilbert-Huang transform

Science.gov (United States)

Cai, Jianhua

2017-05-01

The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.

Extraction of artificial boundary frequencies for damage identification

Energy Technology Data Exchange (ETDEWEB)

Mao Lei; Lu Yong, E-mail: yong.lu@ed.ac.uk [Institute for Infrastructure and Environment, Joint Research Institute for Civil and Environmental Engineering (ERP), School of Engineering, University of Edinburgh, The Kings Buildings, Edinburgh EH9 3JL (United Kingdom)

2011-07-19

This paper introduces some recent progress in a study which is aimed at incorporating the so-called artificial boundary condition (ABC) frequencies for damage identification. The ABC frequencies are those corresponding to the natural frequencies of the system with additional pin supports, but may be extracted from specially configured incomplete frequency response function matrix of the original structure without the need of physically imposing the additional supports. A particular focus of this paper is placed on the actual extraction of such frequencies from physical experiments and the associated data processing and analysis. Results will demonstrate that it is possible to extract the first few ABC frequencies for a variety of boundary conditions with 1-2 artificial pin supports in a beam or a slab structure.

Extraction of artificial boundary frequencies for damage identification

International Nuclear Information System (INIS)

Mao Lei; Lu Yong

2011-01-01

This paper introduces some recent progress in a study which is aimed at incorporating the so-called artificial boundary condition (ABC) frequencies for damage identification. The ABC frequencies are those corresponding to the natural frequencies of the system with additional pin supports, but may be extracted from specially configured incomplete frequency response function matrix of the original structure without the need of physically imposing the additional supports. A particular focus of this paper is placed on the actual extraction of such frequencies from physical experiments and the associated data processing and analysis. Results will demonstrate that it is possible to extract the first few ABC frequencies for a variety of boundary conditions with 1-2 artificial pin supports in a beam or a slab structure.

A Time-Space Domain Information Fusion Method for Specific Emitter Identification Based on Dempster-Shafer Evidence Theory.

Science.gov (United States)

Jiang, Wen; Cao, Ying; Yang, Lin; He, Zichang

2017-08-28

Specific emitter identification plays an important role in contemporary military affairs. However, most of the existing specific emitter identification methods haven't taken into account the processing of uncertain information. Therefore, this paper proposes a time-space domain information fusion method based on Dempster-Shafer evidence theory, which has the ability to deal with uncertain information in the process of specific emitter identification. In this paper, radars will generate a group of evidence respectively based on the information they obtained, and our main task is to fuse the multiple groups of evidence to get a reasonable result. Within the framework of recursive centralized fusion model, the proposed method incorporates a correlation coefficient, which measures the relevance between evidence and a quantum mechanical approach, which is based on the parameters of radar itself. The simulation results of an illustrative example demonstrate that the proposed method can effectively deal with uncertain information and get a reasonable recognition result.

A frequency domain global parameter estimation method for multiple reference frequency response measurements

Science.gov (United States)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

A method of using the matrix Auto-Regressive Moving Average (ARMA) model in the Laplace domain for multiple-reference global parameter identification is presented. This method is particularly applicable to the area of modal analysis where high modal density exists. The method is also applicable when multiple reference frequency response functions are used to characterise linear systems. In order to facilitate the mathematical solution, the Forsythe orthogonal polynomial is used to reduce the ill-conditioning of the formulated equations and to decouple the normal matrix into two reduced matrix blocks. A Complex Mode Indicator Function (CMIF) is introduced, which can be used to determine the proper order of the rational polynomials.

Applications of hybrid time-frequency methods in nonlinear structural dynamics

International Nuclear Information System (INIS)

Politopoulos, I.; Piteau, Ph.; Borsoi, L.; Antunes, J.

2014-01-01

This paper presents a study on methods which may be used to compute the nonlinear response of systems whose linear properties are determined in the frequency or Laplace domain. Typically, this kind of situation may arise in soil-structure and fluid-structure interaction problems. In particular three methods are investigated: (a) the hybrid time-frequency method, (b) the computation of the convolution integral which requires an inverse Fourier or Laplace transform of the system's transfer function, and (c) the identification of an equivalent system defined in the time domain which may be solved with classical time integration methods. These methods are illustrated by their application to some simple, one degree of freedom, non-linear systems and their advantages and drawbacks are highlighted. (authors)

Discrete frequency identification using the HP 5451B Fourier analyser

International Nuclear Information System (INIS)

Holland, L.; Barry, P.

1977-01-01

The frequency analysis by the HP5451B discrete frequency Fourier analyser is studied. The advantages of cross correlation analysis to identify discrete frequencies in a background noise are discussed in conjuction with the elimination of aliasing and wraparound error. Discrete frequency identification is illustrated by a series of graphs giving the results of analysing 'electrical' and 'acoustical' white noise and sinusoidal signals [pt

Power system frequency estimation based on an orthogonal decomposition method

Science.gov (United States)

Lee, Chih-Hung; Tsai, Men-Shen

2018-06-01

In recent years, several frequency estimation techniques have been proposed by which to estimate the frequency variations in power systems. In order to properly identify power quality issues under asynchronously-sampled signals that are contaminated with noise, flicker, and harmonic and inter-harmonic components, a good frequency estimator that is able to estimate the frequency as well as the rate of frequency changes precisely is needed. However, accurately estimating the fundamental frequency becomes a very difficult task without a priori information about the sampling frequency. In this paper, a better frequency evaluation scheme for power systems is proposed. This method employs a reconstruction technique in combination with orthogonal filters, which may maintain the required frequency characteristics of the orthogonal filters and improve the overall efficiency of power system monitoring through two-stage sliding discrete Fourier transforms. The results showed that this method can accurately estimate the power system frequency under different conditions, including asynchronously sampled signals contaminated by noise, flicker, and harmonic and inter-harmonic components. The proposed approach also provides high computational efficiency.

A Rapid Identification Method for Calamine Using Near-Infrared Spectroscopy Based on Multi-Reference Correlation Coefficient Method and Back Propagation Artificial Neural Network.

Science.gov (United States)

Sun, Yangbo; Chen, Long; Huang, Bisheng; Chen, Keli

2017-07-01

As a mineral, the traditional Chinese medicine calamine has a similar shape to many other minerals. Investigations of commercially available calamine samples have shown that there are many fake and inferior calamine goods sold on the market. The conventional identification method for calamine is complicated, therefore as a result of the large scale of calamine samples, a rapid identification method is needed. To establish a qualitative model using near-infrared (NIR) spectroscopy for rapid identification of various calamine samples, large quantities of calamine samples including crude products, counterfeits and processed products were collected and correctly identified using the physicochemical and powder X-ray diffraction method. The NIR spectroscopy method was used to analyze these samples by combining the multi-reference correlation coefficient (MRCC) method and the error back propagation artificial neural network algorithm (BP-ANN), so as to realize the qualitative identification of calamine samples. The accuracy rate of the model based on NIR and MRCC methods was 85%; in addition, the model, which took comprehensive multiple factors into consideration, can be used to identify crude calamine products, its counterfeits and processed products. Furthermore, by in-putting the correlation coefficients of multiple references as the spectral feature data of samples into BP-ANN, a BP-ANN model of qualitative identification was established, of which the accuracy rate was increased to 95%. The MRCC method can be used as a NIR-based method in the process of BP-ANN modeling.

78 FR 19311 - Certain Radio Frequency Identification (“RFID”) Products And Components Thereof; Institution of...

Science.gov (United States)

2013-03-29

... Identification (``RFID'') Products And Components Thereof; Institution of Investigation Pursuant to 19 U.S.C... sale within the United States after importation of certain radio frequency identification (``RFID... after importation of certain radio frequency identification (``RFID'') products and components thereof...

Integral methods in low-frequency electromagnetics

CERN Document Server

Solin, Pavel; Karban, Pavel; Ulrych, Bohus

2009-01-01

A modern presentation of integral methods in low-frequency electromagnetics This book provides state-of-the-art knowledge on integral methods in low-frequency electromagnetics. Blending theory with numerous examples, it introduces key aspects of the integral methods used in engineering as a powerful alternative to PDE-based models. Readers will get complete coverage of: The electromagnetic field and its basic characteristics An overview of solution methods Solutions of electromagnetic fields by integral expressions Integral and integrodifferential methods

Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method

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Beata Palczynska

2017-05-01

Full Text Available The measurements of electromagnetic field emissions, performed on board a vessel have showed that, in this specific environment, a high level of non-stationary magnetic fields (MFs is observed. The adaptive time-frequency method can be used successfully to analyze this type of measured signal. It allows one to specify the time interval in which the individual frequency components of the signal occur. In this paper, the method of identification of non-stationary MF sources based on the matching pursuit (MP algorithm is presented. It consists of the decomposition of an examined time-waveform into the linear expansion of chirplet atoms and the analysis of the matrix of their parameters. The main feature of the proposed method is the modification of the chirplet’s matrix in a way that atoms, whose normalized energies are lower than a certain threshold, will be rejected. On the time-frequency planes of the spectrograms, obtained separately for each remaining chirlpet, it can clearly identify the time-frequency structures appearing in the examined signal. The choice of a threshold defines the computing speed and precision of the performed analysis. The method was implemented in the virtual application and used for processing real data, obtained from measurements of time-vary MF emissions onboard a ship.

High-frequency combination coding-based steady-state visual evoked potential for brain computer interface

Energy Technology Data Exchange (ETDEWEB)

Zhang, Feng; Zhang, Xin; Xie, Jun; Li, Yeping; Han, Chengcheng; Lili, Li; Wang, Jing [School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049 (China); Xu, Guang-Hua [School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049 (China); State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an 710054 (China)

2015-03-10

This study presents a new steady-state visual evoked potential (SSVEP) paradigm for brain computer interface (BCI) systems. The goal of this study is to increase the number of targets using fewer stimulation high frequencies, with diminishing subject’s fatigue and reducing the risk of photosensitive epileptic seizures. The new paradigm is High-Frequency Combination Coding-Based High-Frequency Steady-State Visual Evoked Potential (HFCC-SSVEP).Firstly, we studied SSVEP high frequency(beyond 25 Hz)response of SSVEP, whose paradigm is presented on the LED. The SNR (Signal to Noise Ratio) of high frequency(beyond 40 Hz) response is very low, which is been unable to be distinguished through the traditional analysis method; Secondly we investigated the HFCC-SSVEP response (beyond 25 Hz) for 3 frequencies (25Hz, 33.33Hz, and 40Hz), HFCC-SSVEP produces n{sup n} with n high stimulation frequencies through Frequence Combination Code. Further, Animproved Hilbert-huang transform (IHHT)-based variable frequency EEG feature extraction method and a local spectrum extreme target identification algorithmare adopted to extract time-frequency feature of the proposed HFCC-SSVEP response.Linear predictions and fixed sifting (iterating) 10 time is used to overcome the shortage of end effect and stopping criterion,generalized zero-crossing (GZC) is used to compute the instantaneous frequency of the proposed SSVEP respondent signals, the improved HHT-based feature extraction method for the proposed SSVEP paradigm in this study increases recognition efficiency, so as to improve ITR and to increase the stability of the BCI system. what is more, SSVEPs evoked by high-frequency stimuli (beyond 25Hz) minimally diminish subject’s fatigue and prevent safety hazards linked to photo-induced epileptic seizures, So as to ensure the system efficiency and undamaging.This study tests three subjects in order to verify the feasibility of the proposed method.

High-frequency combination coding-based steady-state visual evoked potential for brain computer interface

International Nuclear Information System (INIS)

Zhang, Feng; Zhang, Xin; Xie, Jun; Li, Yeping; Han, Chengcheng; Lili, Li; Wang, Jing; Xu, Guang-Hua

2015-01-01

This study presents a new steady-state visual evoked potential (SSVEP) paradigm for brain computer interface (BCI) systems. The goal of this study is to increase the number of targets using fewer stimulation high frequencies, with diminishing subject’s fatigue and reducing the risk of photosensitive epileptic seizures. The new paradigm is High-Frequency Combination Coding-Based High-Frequency Steady-State Visual Evoked Potential (HFCC-SSVEP).Firstly, we studied SSVEP high frequency(beyond 25 Hz)response of SSVEP, whose paradigm is presented on the LED. The SNR (Signal to Noise Ratio) of high frequency(beyond 40 Hz) response is very low, which is been unable to be distinguished through the traditional analysis method; Secondly we investigated the HFCC-SSVEP response (beyond 25 Hz) for 3 frequencies (25Hz, 33.33Hz, and 40Hz), HFCC-SSVEP produces n n with n high stimulation frequencies through Frequence Combination Code. Further, Animproved Hilbert-huang transform (IHHT)-based variable frequency EEG feature extraction method and a local spectrum extreme target identification algorithmare adopted to extract time-frequency feature of the proposed HFCC-SSVEP response.Linear predictions and fixed sifting (iterating) 10 time is used to overcome the shortage of end effect and stopping criterion,generalized zero-crossing (GZC) is used to compute the instantaneous frequency of the proposed SSVEP respondent signals, the improved HHT-based feature extraction method for the proposed SSVEP paradigm in this study increases recognition efficiency, so as to improve ITR and to increase the stability of the BCI system. what is more, SSVEPs evoked by high-frequency stimuli (beyond 25Hz) minimally diminish subject’s fatigue and prevent safety hazards linked to photo-induced epileptic seizures, So as to ensure the system efficiency and undamaging.This study tests three subjects in order to verify the feasibility of the proposed method

Frequency and mode identification of γ Doradus from photometric and spectroscopic observations*

Science.gov (United States)

Brunsden, E.; Pollard, K. R.; Wright, D. J.; De Cat, P.; Cottrell, P. L.

2018-04-01

The prototype star for the γ Doradus class of pulsating variables was studied employing photometric and spectroscopic observations to determine the frequencies and modes of pulsation. The four frequencies found are self-consistent between the observation types and almost identical to those found in previous studies (1.3641 d-1, 1.8783 d-1, 1.4742 d-1, and 1.3209 d-1). Three of the frequencies are classified as l, m = (1, 1) pulsations and the other is ambiguous between l, m = (2, 0) and (2, -2) modes. Two frequencies are shown to be stable over 20 yr since their first identification. The agreement in ground-based work makes this star an excellent calibrator between high-precision photometry and spectroscopy with the upcoming TESS observations and a potential standard for continued asteroseismic modelling.

Method of Increasing Identification Accuracy under Experimental Tests of Dynamic Objects

Directory of Open Access Journals (Sweden)

Y. N. Pavlov

2015-01-01

Full Text Available The work concerns a problem of increasing identification accuracy of linear dynamic systems on the basis of experimental data obtained by applying test signals to the system.The work is aimed at considering a possibility to use the experimentally obtained hodograph counting to determine parameters of this system in a specific context of the linear dynamic system of the second order.An offer was to use a method of harmonious linearization and a described cut method.The type of frequency transfer function of the identified system was assumed as known.It was supposed that when obtaining the frequency characteristics of a real system there are disturbances interfering with experiment as a result of which points of experimentally received hodograph are random displaced.An identification problem solution was searched in a class of the hodograph set by the system model, which had the same type of frequency transfer function, as the type of frequency transfer function of the identified system.The unknown coefficients of frequency transfer function of the system model were searched through minimizing a proximity criterion (measure of the experimentally received hodograph of the system and of the system model hodograph over the entire aggregate of points. One of the authors described this criterion in the earlier publication.The solution to a problem of nonlinear dynamic system identification by the frequency hodograph was reduced to the solution of the system of equations of the rather unknown linear parameters of frequency transfer function of the system model.The program to simulate a process of the pseudo-experimental data, containing random errors, and determine parameters of this system is developed for a dynamic system of the second order.A conducted computing experiment is conducted to estimate an error at which the offered algorithm defines the values of parameters of this system.

Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles.

Science.gov (United States)

Bisgin, Halil; Bera, Tanmay; Ding, Hongjian; Semey, Howard G; Wu, Leihong; Liu, Zhichao; Barnes, Amy E; Langley, Darryl A; Pava-Ripoll, Monica; Vyas, Himansu J; Tong, Weida; Xu, Joshua

2018-04-25

Insect pests, such as pantry beetles, are often associated with food contaminations and public health risks. Machine learning has the potential to provide a more accurate and efficient solution in detecting their presence in food products, which is currently done manually. In our previous research, we demonstrated such feasibility where Artificial Neural Network (ANN) based pattern recognition techniques could be implemented for species identification in the context of food safety. In this study, we present a Support Vector Machine (SVM) model which improved the average accuracy up to 85%. Contrary to this, the ANN method yielded ~80% accuracy after extensive parameter optimization. Both methods showed excellent genus level identification, but SVM showed slightly better accuracy  for most species. Highly accurate species level identification remains a challenge, especially in distinguishing between species from the same genus which may require improvements in both imaging and machine learning techniques. In summary, our work does illustrate a new SVM based technique and provides a good comparison with the ANN model in our context. We believe such insights will pave better way forward for the application of machine learning towards species identification and food safety.

Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier.

Science.gov (United States)

Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Rao, A R

2016-11-05

DNA barcoding is a molecular diagnostic method that allows automated and accurate identification of species based on a short and standardized fragment of DNA. To this end, an attempt has been made in this study to develop a computational approach for identifying the species by comparing its barcode with the barcode sequence of known species present in the reference library. Each barcode sequence was first mapped onto a numeric feature vector based on k-mer frequencies and then Random forest methodology was employed on the transformed dataset for species identification. The proposed approach outperformed similarity-based, tree-based, diagnostic-based approaches and found comparable with existing supervised learning based approaches in terms of species identification success rate, while compared using real and simulated datasets. Based on the proposed approach, an online web interface SPIDBAR has also been developed and made freely available at http://cabgrid.res.in:8080/spidbar/ for species identification by the taxonomists. Copyright © 2016 Elsevier B.V. All rights reserved.

Reliability and applications of statistical methods based on oligonucleotide frequencies in bacterial and archaeal genomes

DEFF Research Database (Denmark)

Bohlin, J; Skjerve, E; Ussery, David

2008-01-01

with here are mainly used to examine similarities between archaeal and bacterial DNA from different genomes. These methods compare observed genomic frequencies of fixed-sized oligonucleotides with expected values, which can be determined by genomic nucleotide content, smaller oligonucleotide frequencies......, or be based on specific statistical distributions. Advantages with these statistical methods include measurements of phylogenetic relationship with relatively small pieces of DNA sampled from almost anywhere within genomes, detection of foreign/conserved DNA, and homology searches. Our aim was to explore...... the reliability and best suited applications for some popular methods, which include relative oligonucleotide frequencies (ROF), di- to hexanucleotide zero'th order Markov methods (ZOM) and 2.order Markov chain Method (MCM). Tests were performed on distant homology searches with large DNA sequences, detection...

A Comfort-Aware Energy Efficient HVAC System Based on the Subspace Identification Method

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O. Tsakiridis

2016-01-01

Full Text Available A proactive heating method is presented aiming at reducing the energy consumption in a HVAC system while maintaining the thermal comfort of the occupants. The proposed technique fuses time predictions for the zones’ temperatures, based on a deterministic subspace identification method, and zones’ occupancy predictions, based on a mobility model, in a decision scheme that is capable of regulating the balance between the total energy consumed and the total discomfort cost. Simulation results for various occupation-mobility models demonstrate the efficiency of the proposed technique.

Proposed Sandia frequency shift for anti-islanding detection method based on artificial immune system

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A.Y. Hatata

2018-03-01

Full Text Available Sandia frequency shift (SFS is one of the active anti-islanding detection methods that depend on frequency drift to detect an islanding condition for inverter-based distributed generation. The non-detection zone (NDZ of the SFS method depends to a great extent on its parameters. Improper adjusting of these parameters may result in failure of the method. This paper presents a proposed artificial immune system (AIS-based technique to obtain optimal parameters of SFS anti-islanding detection method. The immune system is highly distributed, highly adaptive, and self-organizing in nature, maintains a memory of past encounters, and has the ability to continually learn about new encounters. The proposed method generates less total harmonic distortion (THD than the conventional SFS, which results in faster island detection and better non-detection zone. The performance of the proposed method is derived analytically and simulated using Matlab/Simulink. Two case studies are used to verify the proposed method. The first case includes a photovoltaic (PV connected to grid and the second includes a wind turbine connected to grid. The deduced optimized parameter setting helps to achieve the “non-islanding inverter” as well as least potential adverse impact on power quality. Keywords: Anti-islanding detection, Sandia frequency shift (SFS, Non-detection zone (NDZ, Total harmonic distortion (THD, Artificial immune system (AIS, Clonal selection algorithm

A noise level prediction method based on electro-mechanical frequency response function for capacitors.

Science.gov (United States)

Zhu, Lingyu; Ji, Shengchang; Shen, Qi; Liu, Yuan; Li, Jinyu; Liu, Hao

2013-01-01

The capacitors in high-voltage direct-current (HVDC) converter stations radiate a lot of audible noise which can reach higher than 100 dB. The existing noise level prediction methods are not satisfying enough. In this paper, a new noise level prediction method is proposed based on a frequency response function considering both electrical and mechanical characteristics of capacitors. The electro-mechanical frequency response function (EMFRF) is defined as the frequency domain quotient of the vibration response and the squared capacitor voltage, and it is obtained from impulse current experiment. Under given excitations, the vibration response of the capacitor tank is the product of EMFRF and the square of the given capacitor voltage in frequency domain, and the radiated audible noise is calculated by structure acoustic coupling formulas. The noise level under the same excitations is also measured in laboratory, and the results are compared with the prediction. The comparison proves that the noise prediction method is effective.

A Kriging Model Based Finite Element Model Updating Method for Damage Detection

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Xiuming Yang

2017-10-01

Full Text Available Model updating is an effective means of damage identification and surrogate modeling has attracted considerable attention for saving computational cost in finite element (FE model updating, especially for large-scale structures. In this context, a surrogate model of frequency is normally constructed for damage identification, while the frequency response function (FRF is rarely used as it usually changes dramatically with updating parameters. This paper presents a new surrogate model based model updating method taking advantage of the measured FRFs. The Frequency Domain Assurance Criterion (FDAC is used to build the objective function, whose nonlinear response surface is constructed by the Kriging model. Then, the efficient global optimization (EGO algorithm is introduced to get the model updating results. The proposed method has good accuracy and robustness, which have been verified by a numerical simulation of a cantilever and experimental test data of a laboratory three-story structure.

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

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Yang Zhang

2016-10-01

Full Text Available Ultra-wideband (UWB radar has been widely used for detecting human physiological signals (respiration, movement, etc. in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc., the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

Science.gov (United States)

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-10-27

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

Comprehensive evaluation of SNP identification with the Restriction Enzyme-based Reduced Representation Library (RRL method

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Du Ye

2012-02-01

Full Text Available Abstract Background Restriction Enzyme-based Reduced Representation Library (RRL method represents a relatively feasible and flexible strategy used for Single Nucleotide Polymorphism (SNP identification in different species. It has remarkable advantage of reducing the complexity of the genome by orders of magnitude. However, comprehensive evaluation for actual efficacy of SNP identification by this method is still unavailable. Results In order to evaluate the efficacy of Restriction Enzyme-based RRL method, we selected Tsp 45I enzyme which covers 266 Mb flanking region of the enzyme recognition site according to in silico simulation on human reference genome, then we sequenced YH RRL after Tsp 45I treatment and obtained reads of which 80.8% were mapped to target region with an 20-fold average coverage, about 96.8% of target region was covered by at least one read and 257 K SNPs were identified in the region using SOAPsnp software. Compared with whole genome resequencing data, we observed false discovery rate (FDR of 13.95% and false negative rate (FNR of 25.90%. The concordance rate of homozygote loci was over 99.8%, but that of heterozygote were only 92.56%. Repeat sequences and bases quality were proved to have a great effect on the accuracy of SNP calling, SNPs in recognition sites contributed evidently to the high FNR and the low concordance rate of heterozygote. Our results indicated that repeat masking and high stringent filter criteria could significantly decrease both FDR and FNR. Conclusions This study demonstrates that Restriction Enzyme-based RRL method was effective for SNP identification. The results highlight the important role of bias and the method-derived defects represented in this method and emphasize the special attentions noteworthy.

A time and frequency synchronization method for CO-OFDM based on CMA equalizers

Science.gov (United States)

Ren, Kaixuan; Li, Xiang; Huang, Tianye; Cheng, Zhuo; Chen, Bingwei; Wu, Xu; Fu, Songnian; Ping, Perry Shum

2018-06-01

In this paper, an efficient time and frequency synchronization method based on a new training symbol structure is proposed for polarization division multiplexing (PDM) coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. The coarse timing synchronization is achieved by exploiting the correlation property of the first training symbol, and the fine timing synchronization is accomplished by using the time-domain symmetric conjugate of the second training symbol. Furthermore, based on these training symbols, a constant modulus algorithm (CMA) is proposed for carrier frequency offset (CFO) estimation. Theoretical analysis and simulation results indicate that the algorithm has the advantages of robustness to poor optical signal-to-noise ratio (OSNR) and chromatic dispersion (CD). The frequency offset estimation range can achieve [ -Nsc/2 ΔfN , + Nsc/2 ΔfN ] GHz with the mean normalized estimation error below 12 × 10-3 even under the condition of OSNR as low as 10 dB.

The Detection of Subsynchronous Oscillation in HVDC Based on the Stochastic Subspace Identification Method

Directory of Open Access Journals (Sweden)

Chen Shi

2014-01-01

Full Text Available Subsynchronous oscillation (SSO usually caused by series compensation, power system stabilizer (PSS, high voltage direct current transmission (HVDC and other power electronic equipment, which will affect the safe operation of generator shafting even the system. It is very important to identify the modal parameters of SSO to take effective control strategies as well. Since the identification accuracy of traditional methods are not high enough, the stochastic subspace identification (SSI method is proposed to improve the identification accuracy of subsynchronous oscillation modal. The stochastic subspace identification method was compared with the other two methods on subsynchronous oscillation IEEE benchmark model and Xiang-Shang HVDC system model, the simulation results show that the stochastic subspace identification method has the advantages of high identification precision, high operation efficiency and strong ability of anti-noise.

An Estimation Method for number of carrier frequency

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Xiong Peng

2015-01-01

Full Text Available This paper proposes a method that utilizes AR model power spectrum estimation based on Burg algorithm to estimate the number of carrier frequency in single pulse. In the modern electronic and information warfare, the pulse signal form of radar is complex and changeable, among which single pulse with multi-carrier frequencies is the most typical one, such as the frequency shift keying (FSK signal, the frequency shift keying with linear frequency (FSK-LFM hybrid modulation signal and the frequency shift keying with bi-phase shift keying (FSK-BPSK hybrid modulation signal. In view of this kind of single pulse which has multi-carrier frequencies, this paper adopts a method which transforms the complex signal into AR model, then takes power spectrum based on Burg algorithm to show the effect. Experimental results show that the estimation method still can determine the number of carrier frequencies accurately even when the signal noise ratio (SNR is very low.

Moving force identification based on modified preconditioned conjugate gradient method

Science.gov (United States)

Chen, Zhen; Chan, Tommy H. T.; Nguyen, Andy

2018-06-01

This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The method aims to obtain more accurate and more efficient identification results from the responses of bridge deck caused by vehicles passing by, which are known to be sensitive to ill-posed problems that exist in the inverse problem. A simply supported beam model with biaxial time-varying forces is used to generate numerical simulations with various analysis scenarios to assess the effectiveness of the method. Evaluation results show that regularization matrix L and number of iterations j are very important influence factors to identification accuracy and noise immunity of M-PCG. Compared with the conventional counterpart SVD embedded in the time domain method (TDM) and the standard form of CG, the M-PCG with proper regularization matrix has many advantages such as better adaptability and more robust to ill-posed problems. More importantly, it is shown that the average optimal numbers of iterations of M-PCG can be reduced by more than 70% compared with PCG and this apparently makes M-PCG a preferred choice for field MFI applications.

Soil-structure interaction analysis of NPP containments: substructure and frequency domain methods

International Nuclear Information System (INIS)

Venancio-Filho, F.; Almeida, M.C.F.; Ferreira, W.G.; De Barros, F.C.P.

1997-01-01

Substructure and frequency domain methods for soil-structure interaction are addressed in this paper. After a brief description of mathematical models for the soil and of excitation, the equations for dynamic soil-structure interaction are developed for a rigid surface foundation and for an embedded foundation. The equations for the frequency domain analysis of MDOF systems are provided. An example of soil-structure interaction analysis with frequency-dependent soil properties is given and examples of identification of foundation impedance functions and soil properties are presented. (orig.)

ITPI: Initial Transcription Process-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

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Baixia Zhang

2016-01-01

Full Text Available Identification of bioactive components is an important area of research in traditional Chinese medicine (TCM formula. The reported identification methods only consider the interaction between the components and the target proteins, which is not sufficient to explain the influence of TCM on the gene expression. Here, we propose the Initial Transcription Process-based Identification (ITPI method for the discovery of bioactive components that influence transcription factors (TFs. In this method, genome-wide chip detection technology was used to identify differentially expressed genes (DEGs. The TFs of DEGs were derived from GeneCards. The components influencing the TFs were derived from STITCH. The bioactive components in the formula were identified by evaluating the molecular similarity between the components in formula and the components that influence the TF of DEGs. Using the formula of Tian-Zhu-San (TZS as an example, the reliability and limitation of ITPI were examined and 16 bioactive components that influence TFs were identified.

Maximum-likelihood methods for array processing based on time-frequency distributions

Science.gov (United States)

Zhang, Yimin; Mu, Weifeng; Amin, Moeness G.

1999-11-01

This paper proposes a novel time-frequency maximum likelihood (t-f ML) method for direction-of-arrival (DOA) estimation for non- stationary signals, and compares this method with conventional maximum likelihood DOA estimation techniques. Time-frequency distributions localize the signal power in the time-frequency domain, and as such enhance the effective SNR, leading to improved DOA estimation. The localization of signals with different t-f signatures permits the division of the time-frequency domain into smaller regions, each contains fewer signals than those incident on the array. The reduction of the number of signals within different time-frequency regions not only reduces the required number of sensors, but also decreases the computational load in multi- dimensional optimizations. Compared to the recently proposed time- frequency MUSIC (t-f MUSIC), the proposed t-f ML method can be applied in coherent environments, without the need to perform any type of preprocessing that is subject to both array geometry and array aperture.

Radio frequency identification and its application in e-commerce

OpenAIRE

Bahr, Witold; Price, Brian J

2016-01-01

This chapter presents Radio Frequency Identification (RFID), which is one of the Automatic Identification and Data Capture (AIDC) technologies (Wamba and Boeck, 2008) and discusses the application of RFID in E-Commerce. Firstly RFID is defined and the tag and reader components of the RFID system are explained. Then historical context of RFID is briefly discussed. Next, RFID is contrasted with other AIDC technologies, especially the use of barcodes which are commonly applied in E-Commerce. Las...

Building Modern Vibration Diagnostics Systems Based on the Frequency-Time Transformations of A Measured Signal

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Yasoveev Vasikh

2016-01-01

Full Text Available Basic methods of analysis of vibration transducers signals were reviewed. Continuous wavelet transform, being a time-frequency transform, was found to be an advanced mathematical tool for analysis of vibration signals. Experimental studies revealed obvious changes in the continuous wavelet transform spectrum depending on the existing defects. A method for detection and identification of technological violations based on the analysis of CWT spectrum components and normalized correlation coefficient was suggested. In accordance with the suggested method software for vibration diagnostics was developed.

A comparative assessment of different frequency based damage detection in unidirectional composite plates using MFC sensors

Science.gov (United States)

de Medeiros, Ricardo; Sartorato, Murilo; Vandepitte, Dirk; Tita, Volnei

2016-11-01

The basic concept of the vibration based damage identification methods is that the dynamic behaviour of a structure can change if damage occurs. Damage in a structure can alter the structural integrity, and therefore, the physical properties like stiffness, mass and/or damping may change. The dynamic behaviour of a structure is a function of these physical properties and will, therefore, directly be affected by the damage. The dynamic behaviour can be described in terms of time, frequency and modal domain parameters. The changes in these parameters (or properties derived from these parameters) are used as indicators of damage. Hence, this work has two main objectives. The first one is to provide an overview of the structural vibration based damage identification methods. For this purpose, a fundamental description of the structural vibration based damage identification problem is given, followed by a short literature overview of the damage features, which are commonly addressed. The second objective is to create a damage identification method for detection of the damage in composite structures. To aid in this process, two basic principles are discussed, namely the effect of the potential damage case on the dynamic behaviour, and the consequences involved with the information reduction in the signal processing. Modal properties from the structural dynamic output response are obtained. In addition, experimental and computational results are presented for the application of modal analysis techniques applied to composite specimens with and without damage. The excitation of the structures is performed using an impact hammer and, for measuring the output data, accelerometers as well as piezoelectric sensors. Finite element models are developed by shell elements, and numerical results are compared to experimental data, showing good correlation for the response of the specimens in some specific frequency range. Finally, FRFs are analysed using suitable metrics, including a

Improvement of Frequency Domain Output Only Modal Identification from the Application of the Random Decrement Technique

DEFF Research Database (Denmark)

Rodrigues, J.; Brincker, Rune; Andersen, P.

2004-01-01

This paper explores the idea of estimating the spectral densities as the Fourier transform of the random decrement functions for the application of frequency domain output-only modal identification methods. The gains in relation to the usual procedure of computing the spectral densities directly...

Mode Identification of Guided Ultrasonic Wave using Time- Frequency Algorithm

International Nuclear Information System (INIS)

Yoon, Byung Sik; Yang, Seung Han; Cho, Yong Sang; Kim, Yong Sik; Lee, Hee Jong

2007-01-01

The ultrasonic guided waves are waves whose propagation characteristics depend on structural thickness and shape such as those in plates, tubes, rods, and embedded layers. If the angle of incidence or the frequency of sound is adjusted properly, the reflected and refracted energy within the structure will constructively interfere, thereby launching the guided wave. Because these waves penetrate the entire thickness of the tube and propagate parallel to the surface, a large portion of the material can be examined from a single transducer location. The guided ultrasonic wave has various merits like above. But various kind of modes are propagating through the entire thickness, so we don't know the which mode is received. Most of applications are limited from mode selection and mode identification. So the mode identification is very important process for guided ultrasonic inspection application. In this study, various time-frequency analysis methodologies are developed and compared for mode identification tool of guided ultrasonic signal. For this study, a high power tone-burst ultrasonic system set up for the generation and receive of guided waves. And artificial notches were fabricated on the Aluminum plate for the experiment on the mode identification

The Exploration of Radio Frequency Identification (RFID) Application in the Retail Industry: Based on Wal-Mart, Tesco and Sainsburys Case Studies Analysis

OpenAIRE

Gao, Yucheng

2010-01-01

The purpose of this research is to show how radio frequency identification (RFID) benefits supply chain management and explore what difficulties will face by using this technology. It is based on the analysis of three real companies (Wal-Mart, Tesco and Sainsburys) to track how real organizations deploy RFID technology in their company, what problems they face and how operators plan strategies to overcome these difficulties. Furthermore, this research also indicates recommendations and soluti...

Magnetic nanoparticles colourization by a mixing-frequency method

International Nuclear Information System (INIS)

Tu, Liang; Wu, Kai; Klein, Todd; Wang, Jian-Ping

2014-01-01

Brownian and Néel relaxation of magnetic nanoparticles (MNPs) can be characterized by a highly sensitive mixing-frequency method using a search-coil based detection system. The unique magnetic properties of MNPs have been used for biomarkers detection. In this paper, we present a theory and implement an experimental detection scheme using the mixing-frequency method to identify different MNPs simultaneously. A low-frequency sinusoidal magnetic field is applied to saturate the MNPs periodically. A high-frequency sinusoidal magnetic field is then applied to generate mixing-frequency signals that are highly specific to the magnetization of MNPs. The spectra of each MNP can be defined as the complex magnetization of the MNPs over the field frequency. The magnetic spectra of various MNPs and magnetic beads have been characterized and compared. The differences between the MNPs spectra enable us to identify the individual MNPs at the same time. A test has been done to verify the ratio of two different MNPs in mixed samples based on the proposed theory. The experimental results show that the mixing-frequency method is a promising method for MNPs colourization. (paper)

Gear-box fault detection using time-frequency based methods

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2015-01-01

Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors...... in the gear-box resonance frequency can be detected. Two different time–frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen–Loeve basis. Both of them detect the gear-box fault with an acceptable detection delay of maximum 100s, which...... is neglectable compared with the fault developing time....

A novel method for accurate needle-tip identification in trans-rectal ultrasound-based high-dose-rate prostate brachytherapy.

Science.gov (United States)

Zheng, Dandan; Todor, Dorin A

2011-01-01

In real-time trans-rectal ultrasound (TRUS)-based high-dose-rate prostate brachytherapy, the accurate identification of needle-tip position is critical for treatment planning and delivery. Currently, needle-tip identification on ultrasound images can be subject to large uncertainty and errors because of ultrasound image quality and imaging artifacts. To address this problem, we developed a method based on physical measurements with simple and practical implementation to improve the accuracy and robustness of needle-tip identification. Our method uses measurements of the residual needle length and an off-line pre-established coordinate transformation factor, to calculate the needle-tip position on the TRUS images. The transformation factor was established through a one-time systematic set of measurements of the probe and template holder positions, applicable to all patients. To compare the accuracy and robustness of the proposed method and the conventional method (ultrasound detection), based on the gold-standard X-ray fluoroscopy, extensive measurements were conducted in water and gel phantoms. In water phantom, our method showed an average tip-detection accuracy of 0.7 mm compared with 1.6 mm of the conventional method. In gel phantom (more realistic and tissue-like), our method maintained its level of accuracy while the uncertainty of the conventional method was 3.4mm on average with maximum values of over 10mm because of imaging artifacts. A novel method based on simple physical measurements was developed to accurately detect the needle-tip position for TRUS-based high-dose-rate prostate brachytherapy. The method demonstrated much improved accuracy and robustness over the conventional method. Copyright © 2011 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Bearing faults identification and resonant band demodulation based on wavelet de-noising methods and envelope analysis

Science.gov (United States)

Abdelrhman, Ahmed M.; Sei Kien, Yong; Salman Leong, M.; Meng Hee, Lim; Al-Obaidi, Salah M. Ali

2017-07-01

The vibration signals produced by rotating machinery contain useful information for condition monitoring and fault diagnosis. Fault severities assessment is a challenging task. Wavelet Transform (WT) as a multivariate analysis tool is able to compromise between the time and frequency information in the signals and served as a de-noising method. The CWT scaling function gives different resolutions to the discretely signals such as very fine resolution at lower scale but coarser resolution at a higher scale. However, the computational cost increased as it needs to produce different signal resolutions. DWT has better low computation cost as the dilation function allowed the signals to be decomposed through a tree of low and high pass filters and no further analysing the high-frequency components. In this paper, a method for bearing faults identification is presented by combing Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT) with envelope analysis for bearing fault diagnosis. The experimental data was sampled by Case Western Reserve University. The analysis result showed that the proposed method is effective in bearing faults detection, identify the exact fault’s location and severity assessment especially for the inner race and outer race faults.

The Influence of High-Frequency Envelope Information on Low-Frequency Vowel Identification in Noise.

Directory of Open Access Journals (Sweden)

Wiebke Schubotz

Full Text Available Vowel identification in noise using consonant-vowel-consonant (CVC logatomes was used to investigate a possible interplay of speech information from different frequency regions. It was hypothesized that the periodicity conveyed by the temporal envelope of a high frequency stimulus can enhance the use of the information carried by auditory channels in the low-frequency region that share the same periodicity. It was further hypothesized that this acts as a strobe-like mechanism and would increase the signal-to-noise ratio for the voiced parts of the CVCs. In a first experiment, different high-frequency cues were provided to test this hypothesis, whereas a second experiment examined more closely the role of amplitude modulations and intact phase information within the high-frequency region (4-8 kHz. CVCs were either natural or vocoded speech (both limited to a low-pass cutoff-frequency of 2.5 kHz and were presented in stationary 3-kHz low-pass filtered masking noise. The experimental results did not support the hypothesized use of periodicity information for aiding low-frequency perception.

The Influence of High-Frequency Envelope Information on Low-Frequency Vowel Identification in Noise.

Science.gov (United States)

Schubotz, Wiebke; Brand, Thomas; Kollmeier, Birger; Ewert, Stephan D

2016-01-01

Vowel identification in noise using consonant-vowel-consonant (CVC) logatomes was used to investigate a possible interplay of speech information from different frequency regions. It was hypothesized that the periodicity conveyed by the temporal envelope of a high frequency stimulus can enhance the use of the information carried by auditory channels in the low-frequency region that share the same periodicity. It was further hypothesized that this acts as a strobe-like mechanism and would increase the signal-to-noise ratio for the voiced parts of the CVCs. In a first experiment, different high-frequency cues were provided to test this hypothesis, whereas a second experiment examined more closely the role of amplitude modulations and intact phase information within the high-frequency region (4-8 kHz). CVCs were either natural or vocoded speech (both limited to a low-pass cutoff-frequency of 2.5 kHz) and were presented in stationary 3-kHz low-pass filtered masking noise. The experimental results did not support the hypothesized use of periodicity information for aiding low-frequency perception.

Fuel number identification method and device

International Nuclear Information System (INIS)

Doi, Takami; Seno, Makoto; Kikuchi, Takashi; Sakamoto, Hiromi; Takahashi, Masaki; Tanaka, Keiji.

1997-01-01

The present invention provides a method of and a device for automatically identifying fuel numbers impressed on fuel assemblies disposed in a fuel reprocessing facility, power plant and a reactor core at a high speed and at a high identification rate. Namely, three or more character images are photographed for one fuel assembly as an object of the identification under different illumination conditions. As a result, different character images by the number of the illumination directions can be obtained for identical impressed characters. Learning on a neural network system is applied to the images of all of the characters impressed on the fuel assembly obtained under illumination of predetermined directions. Then, result of the identification by the number of the illumination directions can be obtained for each of the characters as an object of the identification. As a result, since the result of the identification is determined based on a theory of decision of majority, highly automatic identification can be realized. (I.S.)

Gait Correlation Analysis Based Human Identification

Directory of Open Access Journals (Sweden)

Jinyan Chen

2014-01-01

Full Text Available Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x, vertical axis (y, and temporal axis (t. By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features’ dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance.

Blind system identification of two-thermocouple sensor based on cross-relation method

Science.gov (United States)

Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

2018-03-01

In dynamic temperature measurement, the dynamic characteristics of the sensor affect the accuracy of the measurement results. Thermocouples are widely used for temperature measurement in harsh conditions due to their low cost, robustness, and reliability, but because of the presence of the thermal inertia, there is a dynamic error in the dynamic temperature measurement. In order to eliminate the dynamic error, two-thermocouple sensor was used to measure dynamic gas temperature in constant velocity flow environments in this paper. Blind system identification of two-thermocouple sensor based on a cross-relation method was carried out. Particle swarm optimization algorithm was used to estimate time constants of two thermocouples and compared with the grid based search method. The method was validated on the experimental equipment built by using high temperature furnace, and the input dynamic temperature was reconstructed by using the output data of the thermocouple with small time constant.

Portraits of Benvenuto Cellini and Anthropological Methods of Their Identification

Science.gov (United States)

Nasobin, Oleg

2016-01-01

Modern methods of biometric identification are increasingly applied in order to attribute works of art. They are based on developments in the 19th century anthropological methods. So, this article describes how the successional anthropological methods were applied for the identification of Benvenuto Cellini's portraits. Objective comparison of…

RFID explained a primer on radio frequency identification technologies

CERN Document Server

Want, Roy

2006-01-01

This lecture provides an introduction to Radio Frequency Identification (RFID), a technology enabling automatic identification of objects at a distance without requiring line-of-sight. Electronic tagging can be divided into technologies that have a power source (active tags), and those that are powered by the tag interrogation signal (passive tags); the focus here is on passive tags. An overview of the principles of the technology divides passive tags into devices that use either near field or far field coupling to communicate with a tag reader. The strengths and weaknesses of the approaches a

Vibro-acoustic modulation–based damage identification in a composite skin–stiffener structure

NARCIS (Netherlands)

Ooijevaar, T.H.; Rogge, M.D.; Loendersloot, Richard; Warnet, Laurent; Akkerman, Remko; Tinga, Tiedo

2016-01-01

Vibro-acoustic modulation–based damage identification relies on the modulation of a high-frequency carrier signal by an intenser low-frequency vibration signal due to damage-induced structural nonlinearities. A time domain analysis of the vibro-acoustic modulation phenomena was presented at multiple

Brain-computer interface based on intermodulation frequency

Science.gov (United States)

Chen, Xiaogang; Chen, Zhikai; Gao, Shangkai; Gao, Xiaorong

2013-12-01

Objective. Most recent steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems have used a single frequency for each target, so that a large number of targets require a large number of stimulus frequencies and therefore a wider frequency band. However, human beings show good SSVEP responses only in a limited range of frequencies. Furthermore, this issue is especially problematic if the SSVEP-based BCI takes a PC monitor as a stimulator, which is only capable of generating a limited range of frequencies. To mitigate this issue, this study presents an innovative coding method for SSVEP-based BCI by means of intermodulation frequencies. Approach. Simultaneous modulations of stimulus luminance and color at different frequencies were utilized to induce intermodulation frequencies. Luminance flickered at relatively large frequency (10, 12, 15 Hz), while color alternated at low frequency (0.5, 1 Hz). An attractive feature of the proposed method was that it would substantially increase the number of targets at a single flickering frequency by altering color modulated frequencies. Based on this method, the BCI system presented in this study realized eight targets merely using three flickering frequencies. Main results. The online results obtained from 15 subjects (14 healthy and 1 with stroke) revealed that an average classification accuracy of 93.83% and information transfer rate (ITR) of 33.80 bit min-1 were achieved using our proposed SSVEP-based BCI system. Specifically, 5 out of the 15 subjects exhibited an ITR of 40.00 bit min-1 with a classification accuracy of 100%. Significance. These results suggested that intermodulation frequencies could be adopted as steady responses in BCI, for which our system could be used as a practical BCI system.

Modal Identification from Ambient Responses using Frequency Domain Decomposition

DEFF Research Database (Denmark)

Brincker, Rune; Zhang, L.; Andersen, P.

2000-01-01

In this paper a new frequency domain technique is introduced for the modal identification from ambient responses, ie. in the case where the modal parameters must be estimated without knowing the input exciting the system. By its user friendliness the technique is closely related to the classical ...

EGC: a time-frequency augmented template-based method for gravitational wave burst search in ground-based interferometers

International Nuclear Information System (INIS)

Clapson, Andre-Claude; Barsuglia, Matteo; Bizouard, Marie-Anne; Brisson, Violette; Cavalier, Fabien; Davier, Michel; Hello, Patrice; Leroy, Nicolas; Varvella, Monica

2008-01-01

The detection of burst-type events in the output of ground gravitational wave detectors is particularly challenging. The potential variety of astrophysical waveforms, as proposed by simulations and analytic studies in general relativity and the discrimination of actual signals from instrumental noise both are critical issues. Robust methods that achieve reasonable detection performances over a wide range of signals are required. We present here a hybrid burst-detection pipeline related to time-frequency transforms while based on matched filtering to provide robustness against noise characteristics. Studies on simulated noise show that the algorithm has a detection efficiency similar to other methods over very different waveforms and particularly good timing even for low amplitude signals: no bias for most tested waveforms and an average accuracy of 1.1 ms (down to 0.1 ms in the best case). Time-frequency-type parameters, useful for event classification, are also derived for noise spectral densities unfavourable to standard time-frequency algorithms

EGC: a time-frequency augmented template-based method for gravitational wave burst search in ground-based interferometers

Energy Technology Data Exchange (ETDEWEB)

Clapson, Andre-Claude; Barsuglia, Matteo; Bizouard, Marie-Anne; Brisson, Violette; Cavalier, Fabien; Davier, Michel; Hello, Patrice; Leroy, Nicolas; Varvella, Monica [LAL, Universite Paris-Sud 11, BP 34, 91898 Orsay (France)

2008-02-07

The detection of burst-type events in the output of ground gravitational wave detectors is particularly challenging. The potential variety of astrophysical waveforms, as proposed by simulations and analytic studies in general relativity and the discrimination of actual signals from instrumental noise both are critical issues. Robust methods that achieve reasonable detection performances over a wide range of signals are required. We present here a hybrid burst-detection pipeline related to time-frequency transforms while based on matched filtering to provide robustness against noise characteristics. Studies on simulated noise show that the algorithm has a detection efficiency similar to other methods over very different waveforms and particularly good timing even for low amplitude signals: no bias for most tested waveforms and an average accuracy of 1.1 ms (down to 0.1 ms in the best case). Time-frequency-type parameters, useful for event classification, are also derived for noise spectral densities unfavourable to standard time-frequency algorithms.

Resting State EEG-based biometrics for individual identification using convolutional neural networks.

Science.gov (United States)

Lan Ma; Minett, James W; Blu, Thierry; Wang, William S-Y

2015-08-01

Biometrics is a growing field, which permits identification of individuals by means of unique physical features. Electroencephalography (EEG)-based biometrics utilizes the small intra-personal differences and large inter-personal differences between individuals' brainwave patterns. In the past, such methods have used features derived from manually-designed procedures for this purpose. Another possibility is to use convolutional neural networks (CNN) to automatically extract an individual's best and most unique neural features and conduct classification, using EEG data derived from both Resting State with Open Eyes (REO) and Resting State with Closed Eyes (REC). Results indicate that this CNN-based joint-optimized EEG-based Biometric System yields a high degree of accuracy of identification (88%) for 10-class classification. Furthermore, rich inter-personal difference can be found using a very low frequency band (0-2Hz). Additionally, results suggest that the temporal portions over which subjects can be individualized is less than 200 ms.

Radio Frequency Identification (RFID technology and patient safety

Directory of Open Access Journals (Sweden)

Sima Ajami

2013-01-01

Full Text Available Background: Radio frequency identification (RFID systems have been successfully applied in areas of manufacturing, supply chain, agriculture, transportation, healthcare, and services to name a few. However, the different advantages and disadvantages expressed in various studies of the challenges facing the technology of the use of the RFID technology have been met with skepticism by managers of healthcare organizations. The aim of this study was to express and display the role of RFID technology in improving patient safety and increasing the impact of it in healthcare. Materials and Methods: This study was non-systematical review, which the literature search was conducted with the help of libraries, books, conference proceedings, PubMed databases and also search engines available at Google, Google scholar in which published between 2004 and 2013 during Febuary 2013. We employed the following keywords and their combinations; RFID, healthcare, patient safety, medical errors, and medication errors in the searching areas of title, keywords, abstract, and full text. Results: The preliminary search resulted in 68 articles. After a careful analysis of the content of each paper, a total of 33 papers was selected based on their relevancy. Conclusion: We should integrate RFID with hospital information systems (HIS and electronic health records (EHRs and support it by clinical decision support systems (CDSS, it facilitates processes and reduce medical, medication and diagnosis errors.

Radio Frequency Identification (RFID) technology and patient safety

Science.gov (United States)

Ajami, Sima; Rajabzadeh, Ahmad

2013-01-01

Background: Radio frequency identification (RFID) systems have been successfully applied in areas of manufacturing, supply chain, agriculture, transportation, healthcare, and services to name a few. However, the different advantages and disadvantages expressed in various studies of the challenges facing the technology of the use of the RFID technology have been met with skepticism by managers of healthcare organizations. The aim of this study was to express and display the role of RFID technology in improving patient safety and increasing the impact of it in healthcare. Materials and Methods: This study was non-systematical review, which the literature search was conducted with the help of libraries, books, conference proceedings, PubMed databases and also search engines available at Google, Google scholar in which published between 2004 and 2013 during Febuary 2013. We employed the following keywords and their combinations; RFID, healthcare, patient safety, medical errors, and medication errors in the searching areas of title, keywords, abstract, and full text. Results: The preliminary search resulted in 68 articles. After a careful analysis of the content of each paper, a total of 33 papers was selected based on their relevancy. Conclusion: We should integrate RFID with hospital information systems (HIS) and electronic health records (EHRs) and support it by clinical decision support systems (CDSS), it facilitates processes and reduce medical, medication and diagnosis errors. PMID:24381626

Modal Identification from Ambient Responses Using Frequency Domain Decomposition

DEFF Research Database (Denmark)

Brincker, Rune; Zhang, Lingmi; Andersen, Palle

2000-01-01

In this paper a new frequency domain technique is introduced for the modal identification from ambient responses, i.e. in the case where the modal parameters must be estimated without knowing the input exciting the system. By its user friendliness the technique is closely related to the classical...

Model Optimization Identification Method Based on Closed-loop Operation Data and Process Characteristics Parameters

Directory of Open Access Journals (Sweden)

Zhiqiang GENG

2014-01-01

Full Text Available Output noise is strongly related to input in closed-loop control system, which makes model identification of closed-loop difficult, even unidentified in practice. The forward channel model is chosen to isolate disturbance from the output noise to input, and identified by optimization the dynamic characteristics of the process based on closed-loop operation data. The characteristics parameters of the process, such as dead time and time constant, are calculated and estimated based on the PI/PID controller parameters and closed-loop process input/output data. And those characteristics parameters are adopted to define the search space of the optimization identification algorithm. PSO-SQP optimization algorithm is applied to integrate the global search ability of PSO with the local search ability of SQP to identify the model parameters of forward channel. The validity of proposed method has been verified by the simulation. The practicability is checked with the PI/PID controller parameter turning based on identified forward channel model.

Identification method of non-reflective faults based on index distribution of optical fibers.

Science.gov (United States)

Lee, Wonkyoung; Myong, Seung Il; Lee, Jyung Chan; Lee, Sangsoo

2014-01-13

This paper investigates an identification method of non-reflective faults based on index distribution of optical fibers. The method identifies not only reflective faults but also non-reflective faults caused by tilted fiber-cut, lateral connector-misalignment, fiber-bend, and temperature variation. We analyze the reason why wavelength dependence of the fiber-bend is opposite to that of the lateral connector-misalignment, and the effect of loss due to temperature variation on OTDR waveforms through simulation and experimental results. This method can be realized by only upgrade of fault-analysis software without the hardware change, it is, therefore, competitive and cost-effective in passive optical networks.

How can radio frequency identification technology impact nursing practice?

Science.gov (United States)

Billingsley, Luanne; Wyld, David

2014-12-01

Radio frequency identification (RFID) technology can save nurses time, improve quality of care, en hance patient and staff safety, and decrease costs. However, without a better understanding of these systems and their benefits to patients and hospitals, nurses may be slower to recommend, implement, or adopt RFID technology into practice.

Dynamic biometric identification from multiple views using the GLBP-TOP method.

Science.gov (United States)

Wang, Yu; Shen, Xuanjing; Chen, Haipeng; Zhai, Yujie

2014-01-01

To realize effective and rapid dynamic biometric identification with low computational complexity, a video-based facial texture program that extracts local binary patterns from three orthogonal planes in the frequency domain of the Gabor transform (GLBP-TOP) was proposed. Firstly, each normalized face was transformed by Gabor wavelet to get the enhanced Gabor magnitude map, and then the LBP-TOP operator was applied to the maps to extract video texture. Finally, weighted Chi square statistics based on the Fisher Criterion were used to realize the identification. The proposed algorithm was proved effective through the biometric experiments using the Honda/UCSD database, and was robust against changes of illumination and expressions.

Radio Frequency Identification (RFID): its usage and libraries

OpenAIRE

Rafiq, Muhammad

2004-01-01

Radio Frequency Identification (RFID) is one of the most exciting technologies that revolutionize the working practices by increasing efficiencies, and improving profitability. The article provides details about RFID, its components, how it works, and its usage in different sectors i.e. retail sales and supply chains, livestock industry, courier services, military and prisons, automobiles and logistics, entertainment industry, publishing industry, wireless transaction, and, especially, in...

Speaker gender identification based on majority vote classifiers

Science.gov (United States)

Mezghani, Eya; Charfeddine, Maha; Nicolas, Henri; Ben Amar, Chokri

2017-03-01

Speaker gender identification is considered among the most important tools in several multimedia applications namely in automatic speech recognition, interactive voice response systems and audio browsing systems. Gender identification systems performance is closely linked to the selected feature set and the employed classification model. Typical techniques are based on selecting the best performing classification method or searching optimum tuning of one classifier parameters through experimentation. In this paper, we consider a relevant and rich set of features involving pitch, MFCCs as well as other temporal and frequency-domain descriptors. Five classification models including decision tree, discriminant analysis, nave Bayes, support vector machine and k-nearest neighbor was experimented. The three best perming classifiers among the five ones will contribute by majority voting between their scores. Experimentations were performed on three different datasets spoken in three languages: English, German and Arabic in order to validate language independency of the proposed scheme. Results confirm that the presented system has reached a satisfying accuracy rate and promising classification performance thanks to the discriminating abilities and diversity of the used features combined with mid-level statistics.

Authentication of Radio Frequency Identification Devices Using Electronic Characteristics

Science.gov (United States)

Chinnappa Gounder Periaswamy, Senthilkumar

2010-01-01

Radio frequency identification (RFID) tags are low-cost devices that are used to uniquely identify the objects to which they are attached. Due to the low cost and size that is driving the technology, a tag has limited computational capabilities and resources. This limitation makes the implementation of conventional security protocols to prevent…

Development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification

Science.gov (United States)

Astafiev, A.; Orlov, A.; Privezencev, D.

2018-01-01

The article is devoted to the development of technology and software for the construction of positioning and control systems in industrial plants based on aggregation to determine the current storage area using computer vision and radiofrequency identification. It describes the developed of the project of hardware for industrial products positioning system in the territory of a plant on the basis of radio-frequency grid. It describes the development of the project of hardware for industrial products positioning system in the plant on the basis of computer vision methods. It describes the development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification. Experimental studies in laboratory and production conditions have been conducted and described in the article.

Fundamental Frequency Estimation using Polynomial Rooting of a Subspace-Based Method

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt

2010-01-01

improvements compared to HMUSIC. First, by using the proposed method we can obtain an estimate of the fundamental frequency without doing a grid search like in HMUSIC. This is due to that the fundamental frequency is estimated as the argument of the root lying closest to the unit circle. Second, we obtain...... a higher spectral resolution compared to HMUSIC which is a property of polynomial rooting methods. Our simulation results show that the proposed method is applicable to real-life signals, and that we in most cases obtain a higher spectral resolution than HMUSIC....

IDENTIFICATION OF LANDSLIDES SUSCEPTIBILITY IN THE DOBRIC CATCHMENT AREA USING THE FREQUENCY RATE MODEL

Directory of Open Access Journals (Sweden)

ROXANA VĂIDEAN

2013-11-01

Full Text Available The landslides susceptibility of the Dobric catchment area (Ilişua river. The territorial geomorfological investigation focuses mainly on the analysis of the present situation, as context of future events occurrence. The previous evolutionary context is secondary in place due also to the particular attention it has received so far. The significance of the knowledge regarding the present events and their evolution is explicit in the attempt to mitigate their impact on the built area and on the resources. The identification of areas characterized by maximum susceptibility in the landslides occurrence is absolutely necessary. The method which makes the identification of these areas possible is none other than the method considering the conditional factors, as well as the spatial distribution of the events that have already occurred. In this regard, the use of the frequency rate model is considered to be ideal.

A virtual closed loop method for closed loop identification

NARCIS (Netherlands)

Agüero, J.C.; Goodwin, G.C.; Hof, Van den P.M.J.

2011-01-01

Indirect methods for the identification of linear plant models on the basis of closed loop data are based on the use of (reconstructed) input signals that are uncorrelated with the noise. This generally requires exact (linear) controller knowledge. On the other hand, direct identification requires

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

Science.gov (United States)

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

Frequency-Domain Maximum-Likelihood Estimation of High-Voltage Pulse Transformer Model Parameters

CERN Document Server

Aguglia, D; Martins, C.D.A.

2014-01-01

This paper presents an offline frequency-domain nonlinear and stochastic identification method for equivalent model parameter estimation of high-voltage pulse transformers. Such kinds of transformers are widely used in the pulsed-power domain, and the difficulty in deriving pulsed-power converter optimal control strategies is directly linked to the accuracy of the equivalent circuit parameters. These components require models which take into account electric fields energies represented by stray capacitance in the equivalent circuit. These capacitive elements must be accurately identified, since they greatly influence the general converter performances. A nonlinear frequency-based identification method, based on maximum-likelihood estimation, is presented, and a sensitivity analysis of the best experimental test to be considered is carried out. The procedure takes into account magnetic saturation and skin effects occurring in the windings during the frequency tests. The presented method is validated by experim...

Two-dimensional PCA-based human gait identification

Science.gov (United States)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

Security risks associated with radio frequency identification in medical environments.

Science.gov (United States)

Hawrylak, Peter J; Schimke, Nakeisha; Hale, John; Papa, Mauricio

2012-12-01

Radio frequency identification (RFID) is a form of wireless communication that is used to identify assets and people. RFID has significant benefits to the medical environment. However, serious security threats are present in RFID systems that must be addressed in a medical environment. Of particular interest are threats to patient privacy and safety based on interception of messages, interruption of communication, modification of data, and fabrication of messages and devices. This paper presents an overview of these security threats present in RFID systems in a medical environment and provides guidance on potential solutions to these threats. This paper provides a roadmap for researchers and implementers to address the security issues facing RFID in the medical space.

Crack identification based on synthetic artificial intelligent technique

International Nuclear Information System (INIS)

Shim, Mun Bo; Suh, Myung Won

2001-01-01

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising

New Waste Beverage Cans Identification Method

Directory of Open Access Journals (Sweden)

Firmansyah Burlian

2016-05-01

Full Text Available The primary emphasis of this work is on the development of a new waste beverage cans identification method for automated beverage cans sorting systems known as the SVS system. The method described involved window-based subdivision of the image into X-cells, construction of X-candidate template for N-cells, calculation of matching scores of reference templates for the N-cells image, and application of matching score to identify the grade of the object. The SVS system performance for correct beverage cans grade identification is 95.17% with estimated throughput of 21,600 objects per hour with a conveyor belt width of 18˝. The weight of the throughput depends on the size and type of the objects.

Crack identification method in beam-like structures using changes in experimentally measured frequencies and Particle Swarm Optimization

Science.gov (United States)

Khatir, Samir; Dekemele, Kevin; Loccufier, Mia; Khatir, Tawfiq; Abdel Wahab, Magd

2018-02-01

In this paper, a technique is presented for the detection and localization of an open crack in beam-like structures using experimentally measured natural frequencies and the Particle Swarm Optimization (PSO) method. The technique considers the variation in local flexibility near the crack. The natural frequencies of a cracked beam are determined experimentally and numerically using the Finite Element Method (FEM). The optimization algorithm is programmed in MATLAB. The algorithm is used to estimate the location and severity of a crack by minimizing the differences between measured and calculated frequencies. The method is verified using experimentally measured data on a cantilever steel beam. The Fourier transform is adopted to improve the frequency resolution. The results demonstrate the good accuracy of the proposed technique.

Nuclear Magnetic Resonance Spectroscopy-Based Identification of Yeast.

Science.gov (United States)

Himmelreich, Uwe; Sorrell, Tania C; Daniel, Heide-Marie

2017-01-01

Rapid and robust high-throughput identification of environmental, industrial, or clinical yeast isolates is important whenever relatively large numbers of samples need to be processed in a cost-efficient way. Nuclear magnetic resonance (NMR) spectroscopy generates complex data based on metabolite profiles, chemical composition and possibly on medium consumption, which can not only be used for the assessment of metabolic pathways but also for accurate identification of yeast down to the subspecies level. Initial results on NMR based yeast identification where comparable with conventional and DNA-based identification. Potential advantages of NMR spectroscopy in mycological laboratories include not only accurate identification but also the potential of automated sample delivery, automated analysis using computer-based methods, rapid turnaround time, high throughput, and low running costs.We describe here the sample preparation, data acquisition and analysis for NMR-based yeast identification. In addition, a roadmap for the development of classification strategies is given that will result in the acquisition of a database and analysis algorithms for yeast identification in different environments.

Identification of characteristic frequencies of damaged railway tracks using field hammer test measurements

Science.gov (United States)

Oregui, M.; Li, Z.; Dollevoet, R.

2015-03-01

In this paper, the feasibility of the Frequency Response Function (FRF)-based statistical method to identify the characteristic frequencies of railway track defects is studied. The method compares a damaged track state to a healthy state based on non-destructive field hammer test measurements. First, a study is carried out to investigate the repeatability of hammer tests in railway tracks. By changing the excitation and measurement locations it is shown that the variability introduced by the test process is negligible. Second, following the concepts of control charts employed in process monitoring, a method to define an approximate healthy state is introduced by using hammer test measurements at locations without visual damage. Then, the feasibility study includes an investigation into squats (i.e. a major type of rail surface defect) of varying severity. The identified frequency ranges related to squats agree with those found in an extensively validated vehicle-borne detection system. Therefore, the FRF-based statistical method in combination with the non-destructive hammer test measurements has the potential to be employed to identify the characteristic frequencies of damaged conditions in railway tracks in the frequency range of 300-3000 Hz.

Musical Instrument Identification using Multiscale Mel-frequency Cepstral Coefficients

DEFF Research Database (Denmark)

Sturm, Bob L.; Morvidone, Marcela; Daudet, Laurent

2010-01-01

We investigate the benefits of evaluating Mel-frequency cepstral coefficients (MFCCs) over several time scales in the context of automatic musical instrument identification for signals that are monophonic but derived from real musical settings. We define several sets of features derived from MFCC...... multiscale decompositions perform significantly better than features computed using a single time-resolution....

Improved system blind identification based on second-order ...

Indian Academy of Sciences (India)

An improved system blind identification method based on second- order cyclostationary statistics and the properties of group delay, has been ... In the last decade, there has been considerable research on achieving blind identification.

A simulation tool for radio frequency identification construction supply chains

NARCIS (Netherlands)

Gassel, van F.J.M.; Jansen, G.; Zavadskas, E.K.; Kaklauskas, A.; Skibniewski, M.J.

2008-01-01

Radio Frequency IDentification (RFID) technology is being used more and more in the construction industry. RFID tags and peripheral equipment are becoming cheaper and more suitable for application in the supply chain. However, it is difficult for contractors to estimate the costs and benefits of

Substructure identification for shear structures: cross-power spectral density method

International Nuclear Information System (INIS)

Zhang, Dongyu; Johnson, Erik A

2012-01-01

In this paper, a substructure identification method for shear structures is proposed. A shear structure is divided into many small substructures; utilizing the dynamic equilibrium of a one-floor substructure, an inductive identification problem is formulated, using the cross-power spectral densities between structural floor accelerations and a reference response, to estimate the parameters of that one story. Repeating this procedure, all story parameters of the shear structure are identified from top to bottom recursively. An identification error analysis is performed for the proposed substructure method, revealing how uncertain factors (e.g. measurement noise) in the identification process affect the identification accuracy. According to the error analysis, a smart reference selection rule is designed to choose the optimal reference response that further enhances the identification accuracy. Moreover, based on the identification error analysis, explicit formulae are developed to calculate the variances of the parameter identification errors. A ten-story shear structure is used to illustrate the effectiveness of the proposed substructure method. The simulation results show that the method, combined with the reference selection rule, can very accurately identify structural parameters despite large measurement noise. Furthermore, the proposed formulae provide good predictions for the variances of the parameter identification errors, which are vital for providing accurate warnings of structural damage. (paper)

Risk assessment of chemicals in food and diet: Hazard identification by methods of animal-based toxicology

DEFF Research Database (Denmark)

Barlow, S. M.; Greig, J. B.; Bridges, J. W.

2002-01-01

the current state of the science of risk assessment of chemicals in food and diet, by consideration of the four stages of risk assessment, that is. hazard identification. hazard characterisation, exposure assessment and risk characterisation. The contribution of animal-based methods in toxicology to hazard......, on hazard identification for food chemicals, such as new measurement techniques, the use of transgenic animals, assessment of hormone balance and the possibilities for conducting studies in which common human diseases have been modelled. is also considered. (C) 2002 ILSI. Published by Elsevier Science Ltd....... All rights reserved....

A Kalman-based Fundamental Frequency Estimation Algorithm

DEFF Research Database (Denmark)

Shi, Liming; Nielsen, Jesper Kjær; Jensen, Jesper Rindom

2017-01-01

Fundamental frequency estimation is an important task in speech and audio analysis. Harmonic model-based methods typically have superior estimation accuracy. However, such methods usually as- sume that the fundamental frequency and amplitudes are station- ary over a short time frame. In this pape...

Roll-to-Roll Screen Printed Radio Frequency Identification Transponder Antennas for Vehicle Tracking Systems

Science.gov (United States)

Zichner, Ralf; Baumann, Reinhard R.

2013-05-01

Vehicle tracking systems based on ultra high frequency (UHF) radio frequency identification (RFID) technology are already introduced to control the access to car parks and corporate premises. For this field of application so-called Windshield RFID transponder labels are used, which are applied to the inside of the windshield. State of the art for manufacturing these transponder antennas is the traditional lithography/etching approach. Furthermore the performance of these transponders is limited to a reading distance of approximately 5 m which results in car speed limit of 5 km/h for identification. However, to achieve improved performance compared to existing all-purpose transponders and a dramatic cost reduction, an optimized antenna design is needed which takes into account the special dielectric and in particular metallic car environment of the tag and an roll-to-roll (R2R) printing manufacturing process. In this paper we focus on the development of a customized UHF RFID transponder antenna design, which is adopted for vehicle geometry as well as R2R screen printing manufacturing processes.

Radio Frequency Identification (RFID) technology and patient safety

OpenAIRE

Ajami, Sima; Rajabzadeh, Ahmad

2013-01-01

Background: Radio frequency identification (RFID) systems have been successfully applied in areas of manufacturing, supply chain, agriculture, transportation, healthcare, and services to name a few. However, the different advantages and disadvantages expressed in various studies of the challenges facing the technology of the use of the RFID technology have been met with skepticism by managers of healthcare organizations. The aim of this study was to express and display the role of RFID techno...

Method of transient identification based on a possibilistic approach, optimized by genetic algorithm

International Nuclear Information System (INIS)

Almeida, Jose Carlos Soares de

2001-02-01

This work develops a method for transient identification based on a possible approach, optimized by Genetic Algorithm to optimize the number of the centroids of the classes that represent the transients. The basic idea of the proposed method is to optimize the partition of the search space, generating subsets in the classes within a partition, defined as subclasses, whose centroids are able to distinguish the classes with the maximum correct classifications. The interpretation of the subclasses as fuzzy sets and the possible approach provided a heuristic to establish influence zones of the centroids, allowing to achieve the 'don't know' answer for unknown transients, that is, outside the training set. (author)

Modal Identification of Output-Only Systems using Frequency Domain Decomposition

DEFF Research Database (Denmark)

Brincker, Rune; Zhang, L.; Andersen, P.

2000-01-01

In this paper a new frequency domain technique is introduced for the modal identification from ambient responses, ie. in the case where the modal parameters must be estimated without knowing the input exciting the system. By its user friendliness the technique is closely related to the classical ...

A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares

Directory of Open Access Journals (Sweden)

Zizhou Lao

2018-05-01

Full Text Available For model-based state of charge (SOC estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing the estimation error to increase. Constantly updating model parameters during battery operation, also known as online parameter identification, can effectively solve this problem. In this paper, a lithium-ion battery is modeled using the Thevenin model. A variable forgetting factor (VFF strategy is introduced to improve forgetting factor recursive least squares (FFRLS to variable forgetting factor recursive least squares (VFF-RLS. A novel method based on VFF-RLS for the online identification of the Thevenin model is proposed. Experiments verified that VFF-RLS gives more stable online parameter identification results than FFRLS. Combined with an unscented Kalman filter (UKF algorithm, a joint algorithm named VFF-RLS-UKF is proposed for SOC estimation. In a variable-temperature environment, a battery SOC estimation experiment was performed using the joint algorithm. The average error of the SOC estimation was as low as 0.595% in some experiments. Experiments showed that VFF-RLS can effectively track the changes in model parameters. The joint algorithm improved the SOC estimation accuracy compared to the method with the fixed forgetting factor.

Measuring the drinking behaviour of individual pigs housed in group using radio frequency identification (RFID).

Science.gov (United States)

Maselyne, J; Adriaens, I; Huybrechts, T; De Ketelaere, B; Millet, S; Vangeyte, J; Van Nuffel, A; Saeys, W

2016-09-01

Changes in the drinking behaviour of pigs may indicate health, welfare or productivity problems. Automated monitoring and analysis of drinking behaviour could allow problems to be detected, thus improving farm productivity. A high frequency radio frequency identification (HF RFID) system was designed to register the drinking behaviour of individual pigs. HF RFID antennas were placed around four nipple drinkers and connected to a reader via a multiplexer. A total of 55 growing-finishing pigs were fitted with radio frequency identification (RFID) ear tags, one in each ear. RFID-based drinking visits were created from the RFID registrations using a bout criterion and a minimum and maximum duration criterion. The HF RFID system was successfully validated by comparing RFID-based visits with visual observations and flow meter measurements based on visit overlap. Sensitivity was at least 92%, specificity 93%, precision 90% and accuracy 93%. RFID-based drinking duration had a high correlation with observed drinking duration (R 2=0.88) and water usage (R 2=0.71). The number of registrations after applying the visit criteria had an even higher correlation with the same two variables (R 2=0.90 and 0.75, respectively). There was also a correlation between number of RFID visits and number of observed visits (R 2=0.84). The system provides good quality information about the drinking behaviour of individual pigs. As health or other problems affect the pigs' drinking behaviour, analysis of the RFID data could allow problems to be detected and signalled to the farmer. This information can help to improve the productivity and economics of the farm as well as the health and welfare of the pigs.

Bearing performance degradation assessment based on time-frequency code features and SOM network

International Nuclear Information System (INIS)

Zhang, Yan; Tang, Baoping; Han, Yan; Deng, Lei

2017-01-01

Bearing performance degradation assessment and prognostics are extremely important in supporting maintenance decision and guaranteeing the system’s reliability. To achieve this goal, this paper proposes a novel feature extraction method for the degradation assessment and prognostics of bearings. Features of time-frequency codes (TFCs) are extracted from the time-frequency distribution using a hybrid procedure based on short-time Fourier transform (STFT) and non-negative matrix factorization (NMF) theory. An alternative way to design the health indicator is investigated by quantifying the similarity between feature vectors using a self-organizing map (SOM) network. On the basis of this idea, a new health indicator called time-frequency code quantification error (TFCQE) is proposed to assess the performance degradation of the bearing. This indicator is constructed based on the bearing real-time behavior and the SOM model that is previously trained with only the TFC vectors under the normal condition. Vibration signals collected from the bearing run-to-failure tests are used to validate the developed method. The comparison results demonstrate the superiority of the proposed TFCQE indicator over many other traditional features in terms of feature quality metrics, incipient degradation identification and achieving accurate prediction. Highlights • Time-frequency codes are extracted to reflect the signals’ characteristics. • SOM network served as a tool to quantify the similarity between feature vectors. • A new health indicator is proposed to demonstrate the whole stage of degradation development. • The method is useful for extracting the degradation features and detecting the incipient degradation. • The superiority of the proposed method is verified using experimental data. (paper)

Methods for tornado frequency calculation of nuclear power plant

International Nuclear Information System (INIS)

Liu Haibin; Li Lin

2012-01-01

In order to take probabilistic safety assessment of nuclear power plant tornado attack event, a method to calculate tornado frequency of nuclear power plant is introduced based on HAD 101/10 and NUREG/CR-4839 references. This method can consider history tornado frequency of the plant area, construction dimension, intensity various along with tornado path and area distribution and so on and calculate the frequency of different scale tornado. (authors)

Review of Radio Frequency Identification and Wireless Technology for Structural Health Monitoring

Energy Technology Data Exchange (ETDEWEB)

Dhital, Dipesh; Chia, Chen Ciang; Lee, Jung Ryul [Chonbuk National University, Jeonju (Korea, Republic of); Park, Chan Yik [Aeronautical Technology Directorate, Agency for Defense Development, Daejeon (Korea, Republic of)

2010-06-15

Radio frequency identification(RFID) combined with wireless technology has good potential for structural health monitoring(SHM). We describe several advantages of RFID and wireless technologies for SHM, and review SHM examples with working principles, design and technical details for damage detection, heat exposure monitoring, force/strain sensing, and corrosion detection in concrete, steel, carbon fiber reinforced polymer(CFRP), and other materials. Various sensors combined with wireless communication are also discussed. These methodologies can be readily developed, implemented, and customized. There are some technical difficulties, but solutions are being addressed. Lastly, a surface acoustic wave-based RFID system is presented, and possible future trends of SHM based on RFID and wireless technology are presented

Review of Radio Frequency Identification and Wireless Technology for Structural Health Monitoring

International Nuclear Information System (INIS)

Dhital, Dipesh; Chia, Chen Ciang; Lee, Jung Ryul; Park, Chan Yik

2010-01-01

Radio frequency identification(RFID) combined with wireless technology has good potential for structural health monitoring(SHM). We describe several advantages of RFID and wireless technologies for SHM, and review SHM examples with working principles, design and technical details for damage detection, heat exposure monitoring, force/strain sensing, and corrosion detection in concrete, steel, carbon fiber reinforced polymer(CFRP), and other materials. Various sensors combined with wireless communication are also discussed. These methodologies can be readily developed, implemented, and customized. There are some technical difficulties, but solutions are being addressed. Lastly, a surface acoustic wave-based RFID system is presented, and possible future trends of SHM based on RFID and wireless technology are presented

Probability of identification: a statistical model for the validation of qualitative botanical identification methods.

Science.gov (United States)

LaBudde, Robert A; Harnly, James M

2012-01-01

A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.

Libraries for spectrum identification: Method of normalized coordinates versus linear correlation

International Nuclear Information System (INIS)

Ferrero, A.; Lucena, P.; Herrera, R.G.; Dona, A.; Fernandez-Reyes, R.; Laserna, J.J.

2008-01-01

In this work it is proposed that an easy solution based directly on linear algebra in order to obtain the relation between a spectrum and a spectrum base. This solution is based on the algebraic determination of an unknown spectrum coordinates with respect to a spectral library base. The identification capacity comparison between this algebraic method and the linear correlation method has been shown using experimental spectra of polymers. Unlike the linear correlation (where the presence of impurities may decrease the discrimination capacity), this method allows to detect quantitatively the existence of a mixture of several substances in a sample and, consequently, to beer in mind impurities for improving the identification

A direct method for soil-structure interaction analysis based on frequency-dependent soil masses

International Nuclear Information System (INIS)

Danisch, R.; Delinic, K.; Marti, J.; Trbojevic, V.M.

1993-01-01

In a soil-structure interaction analysis, the soil, as a subsystem of the global vibrating system, exerts a strong influence on the response of the nuclear reactor building to the earthquake excitation. The volume of resources required for dealing with the soil have led to a number of different types of frequency-domain solutions, most of them based on the impedance function approach. These procedures require coupling the soil to the lumped-mass finite-element model of the reactor building. In most practical cases, the global vibrating system is analysed in the time domain (i.e. modal time history, linear or non-linear direct time-integration). Hence, it follows that the frequency domain solution for soil must be converted to an 'equivalent' soil model in the time domain. Over the past three decades, different approaches have been developed and used for earthquake analysis of nuclear power plants. In some cases, difficulties experienced in modelling the soil have affected the methods of global analysis, thus leading to approaches like the substructuring technique, e.g. 3-step method. In the practical applications, the limitations of each specific method must be taken into account in order to avoid unrealistic results. The aim of this paper is to present the recent development on an equivalent SDOF system for soil including frequency-dependent soil masses. The method will be compared with the classical 3-step method. (author)

Gearbox fault diagnosis based on time-frequency domain synchronous averaging and feature extraction technique

Science.gov (United States)

Zhang, Shengli; Tang, Jiong

2016-04-01

Gearbox is one of the most vulnerable subsystems in wind turbines. Its healthy status significantly affects the efficiency and function of the entire system. Vibration based fault diagnosis methods are prevalently applied nowadays. However, vibration signals are always contaminated by noise that comes from data acquisition errors, structure geometric errors, operation errors, etc. As a result, it is difficult to identify potential gear failures directly from vibration signals, especially for the early stage faults. This paper utilizes synchronous averaging technique in time-frequency domain to remove the non-synchronous noise and enhance the fault related time-frequency features. The enhanced time-frequency information is further employed in gear fault classification and identification through feature extraction algorithms including Kernel Principal Component Analysis (KPCA), Multilinear Principal Component Analysis (MPCA), and Locally Linear Embedding (LLE). Results show that the LLE approach is the most effective to classify and identify different gear faults.

Contribution of low-frequency harmonics to Mandarin Chinese tone identification in quiet and six-talker babble background.

Science.gov (United States)

Liu, Chang; Azimi, Behnam; Bhandary, Moulesh; Hu, Yi

2014-01-01

The goal of this study was to investigate Mandarin Chinese tone identification in quiet and multi-talker babble conditions for normal-hearing listeners. Tone identification was measured with speech stimuli and stimuli with low and/or high harmonics that were embedded in three Mandarin vowels with two fundamental frequencies. There were six types of stimuli: all harmonics (All), low harmonics (Low), high harmonics (High), and the first (H1), second (H2), and third (H3) harmonic. Results showed that, for quiet conditions, individual harmonics carried frequency contour information well enough for tone identification with high accuracy; however, in noisy conditions, tone identification with individual low harmonics (e.g., H1, H2, and H3) was significantly lower than that with the Low, High, and All harmonics. Moreover, tone identification with individual harmonics in noise was lower for a low F0 than for a high F0, and was also dependent on vowel category. Tone identification with individual low-frequency harmonics was accounted for by local signal-to-noise ratios, indicating that audibility of harmonics in noise may play a primary role in tone identification.

Radio frequency identification applications in hospital environments.

Science.gov (United States)

Wicks, Angela M; Visich, John K; Li, Suhong

2006-01-01

Radio frequency identification (RFID) technology has recently begun to receive increased interest from practitioners and academicians. This interest is driven by mandates from major retailers such as Wal-Mart, Target and Metro Group, and the United States Department of Defense, in order to increase the efficiency and visibility of material and information flows in the supply chain. However, supply chain managers do not have a monopoly on the deployment of RFID. In this article, the authors discuss the potential benefits, the areas of applications, the implementation challenges, and the corresponding strategies of RFID in hospital environments.

A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems

Science.gov (United States)

Liu, Zuolin; Xu, Jian

2018-04-01

In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.

Long range ultra-high frequency (UHF) radio frequency identification (RFID) antenna design

Science.gov (United States)

Reynolds, Nathan D.

There is an ever-increasing demand for radio frequency identification (RFID) tags that are passive, long range, and mountable on multiple surfaces. Currently, RFID technology is utilized in numerous applications such as supply chain management, access control, and public transportation. With the combination of sensory systems in recent years, the applications of RFID technology have been extended beyond tracking and identifying. This extension includes applications such as environmental monitoring and healthcare applications. The available sensory systems usually operate in the medium or high frequency bands and have a low read range. However, the range limitations of these systems are being overcome by the development of RFID sensors focused on utilizing tags in the ultra-high frequency (UHF) band. Generally, RFID tags have to be mounted to the object that is being identified. Often the objects requiring identification are metallic. The inherent properties of metallic objects have substantial effects on nearby electromagnetic radiation; therefore, the operation of the tag antenna is affected when mounted on a metallic surface. This outlines one of the most challenging problems for RFID systems today: the optimization of tag antenna performance in a complex environment. In this research, a novel UHF RFID tag antenna, which has a low profile, long range, and is mountable on metallic surfaces, is designed analytically and simulated using a 3-D electromagnetic simulator, ANSYS HFSS. A microstrip patch antenna is selected as the antenna structure, as patch antennas are low profile and suitable for mounting on metallic surfaces. Matching and theoretical models of the microstrip patch antenna are investigated. Once matching and theory of a microstrip patch antenna is thoroughly understood, a unique design technique using electromagnetic band gap (EBG) structures is explored. This research shows that the utilization of an EBG structure in the patch antenna design yields

Research on Automotive Dynamic Weighing Method Based on Piezoelectric Sensor

Directory of Open Access Journals (Sweden)

Zhang Wei

2017-01-01

Full Text Available In order to effectively measure the dynamic axle load of vehicles in motion, the dynamic weighing method of vehicles based on piezoelectric sensor was studied. Firstly, the influencing factors of the measurement accuracy in the dynamic weighing process were analyzed systematically, and the impacts of road irregularities and dynamic weighing system vibration on measurement error were discussed. On the basis of the analysis, the arithmetic mean filter method was used in the software algorithm to filter out the periodic interference added in the sensor signal, the most suitable n value was selected to get the better filtering result by simulation comparison. Then, the dynamic axle load calculation model of high speed vehicles was studied deeply, based on the theoretical response curve of the sensor, the dynamic axle load calculation method based on frequency reconstruction was established according to actual measurement signals of sensors and the analysis from time domain and frequency domain, also the least square method was used to realize the identification of temperature correction coefficient. A large amount of data that covered the usual vehicle weighing range was collected by experiment. The results show that the dynamic weighing signal system identification error all controlled within 10% at the same temperature and 60% of the vehicle data error can be controlled within 7%. The temperature correction coefficient and the correction formula at different temperatures ranges are well adapted to ensure that the vehicle temperature error at different temperatures can also be controlled within 10% and 70% of the vehicle data error within 7%. Furthermore, the weighing results remain stable regardless of the speed of the vehicle which meets the requirements for high-speed dynamic weighing.

Probabilistic structural damage identification based on vibration data

International Nuclear Information System (INIS)

Hao, H.; Xia, Y.

2001-01-01

Vibration-based methods are being rapidly developed and applied to detect structural damage in civil, mechanical and aerospace engineering communities in the last two decades. But uncertainties existing in the structural model and measured vibration data might lead to unreliable results. This paper will present some recent research results to tackle the above mentioned uncertainty problems. By assuming each of the FE model parameters and measured vibration data as a normally distributed random variable, a probabilistic damage detection procedure is developed based on perturbation method and validated by Monte Carlo simulation technique. With this technique, the damage probability of each structural element can be determined. The method developed has been verified by applying it to identify the damages of laboratory tested structures. It was proven that, as compared to the deterministic damage identification method, the present method can not only reduce the possibility of false identification, but also give the identification results in terms of probability. which is deemed more realistic and practical in detecting possible damages in a structure. It has also been found that the modal data included in damage identification analysis have a great influence on the identification results. With a sensitivity study, an optimal measurement set for damage detection is determined. This set includes the optimal measurement locations and the most appropriate modes that should be used in the damage identification analysis. Numerical results indicated that if the optimal set determined in a pre-analysis is used in the damage detection better results will be achieved. (author)

Triple-Frequency GPS Precise Point Positioning Ambiguity Resolution Using Dual-Frequency Based IGS Precise Clock Products

Directory of Open Access Journals (Sweden)

Fei Liu

2017-01-01

Full Text Available With the availability of the third civil signal in the Global Positioning System, triple-frequency Precise Point Positioning ambiguity resolution methods have drawn increasing attention due to significantly reduced convergence time. However, the corresponding triple-frequency based precise clock products are not widely available and adopted by applications. Currently, most precise products are generated based on ionosphere-free combination of dual-frequency L1/L2 signals, which however are not consistent with the triple-frequency ionosphere-free carrier-phase measurements, resulting in inaccurate positioning and unstable float ambiguities. In this study, a GPS triple-frequency PPP ambiguity resolution method is developed using the widely used dual-frequency based clock products. In this method, the interfrequency clock biases between the triple-frequency and dual-frequency ionosphere-free carrier-phase measurements are first estimated and then applied to triple-frequency ionosphere-free carrier-phase measurements to obtain stable float ambiguities. After this, the wide-lane L2/L5 and wide-lane L1/L2 integer property of ambiguities are recovered by estimating the satellite fractional cycle biases. A test using a sparse network is conducted to verify the effectiveness of the method. The results show that the ambiguity resolution can be achieved in minutes even tens of seconds and the positioning accuracy is in decimeter level.

Person re-identification using height-based gait in colour depth camera

NARCIS (Netherlands)

John, V.; Englebienne, G.; Kröse, B.

2013-01-01

We address the problem of person re-identification in colour-depth camera using the height temporal information of people. Our proposed gait-based feature corresponds to the frequency response of the height temporal information. We demonstrate that the discriminative periodic motion associated with

Synchronous machine parameter identification in frequency and time domain

Directory of Open Access Journals (Sweden)

Hasni M.

2007-01-01

Full Text Available This paper presents the results of a frequency and time-domain identification procedure to estimate the linear parameters of a salient-pole synchronous machine at standstill. The objective of this study is to use several input signals to identify the model structure and parameters of a salient-pole synchronous machine from standstill test data. The procedure consists to define, to conduct the standstill tests and also to identify the model structure. The signals used for identification are the different excitation voltages at standstill and the flowing current in different windings. We estimate the parameters of operational impedances, or in other words the reactance and the time constants. The tests were carried out on synchronous machine of 1.5 kVA 380V 1500 rpm.

Thermal-Diffusivity-Based Frequency References in Standard CMOS

NARCIS (Netherlands)

Kashmiri, S.M.

2012-01-01

In recent years, a lot of research has been devoted to the realization of accurate integrated frequency references. A thermal-diffusivity-based (TD) frequency reference provides an alternative method of on-chip frequency generation in standard CMOS technology. A frequency-locked loop locks the

A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and identification-decoupled strategy.

Science.gov (United States)

Wang, Hongbin; Zhang, Yongqian; Gui, Shuqi; Zhang, Yong; Lu, Fuping; Deng, Yulin

2017-08-15

Comparisons across large numbers of samples are frequently necessary in quantitative proteomics. Many quantitative methods used in proteomics are based on stable isotope labeling, but most of these are only useful for comparing two samples. For up to eight samples, the iTRAQ labeling technique can be used. For greater numbers of samples, the label-free method has been used, but this method was criticized for low reproducibility and accuracy. An ingenious strategy has been introduced, comparing each sample against a 18 O-labeled reference sample that was created by pooling equal amounts of all samples. However, it is necessary to use proportion-known protein mixtures to investigate and evaluate this new strategy. Another problem for comparative proteomics of multiple samples is the poor coincidence and reproducibility in protein identification results across samples. In present study, a method combining 18 O-reference strategy and a quantitation and identification-decoupled strategy was investigated with proportion-known protein mixtures. The results obviously demonstrated that the 18 O-reference strategy had greater accuracy and reliability than other previously used comparison methods based on transferring comparison or label-free strategies. By the decoupling strategy, the quantification data acquired by LC-MS and the identification data acquired by LC-MS/MS are matched and correlated to identify differential expressed proteins, according to retention time and accurate mass. This strategy made protein identification possible for all samples using a single pooled sample, and therefore gave a good reproducibility in protein identification across multiple samples, and allowed for optimizing peptide identification separately so as to identify more proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

Search-based model identification of smart-structure damage

Science.gov (United States)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

[Identification of special quality eggs with NIR spectroscopy technology based on symbol entropy feature extraction method].

Science.gov (United States)

Zhao, Yong; Hong, Wen-Xue

2011-11-01

Fast, nondestructive and accurate identification of special quality eggs is an urgent problem. The present paper proposed a new feature extraction method based on symbol entropy to identify near infrared spectroscopy of special quality eggs. The authors selected normal eggs, free range eggs, selenium-enriched eggs and zinc-enriched eggs as research objects and measured the near-infrared diffuse reflectance spectra in the range of 12 000-4 000 cm(-1). Raw spectra were symbolically represented with aggregation approximation algorithm and symbolic entropy was extracted as feature vector. An error-correcting output codes multiclass support vector machine classifier was designed to identify the spectrum. Symbolic entropy feature is robust when parameter changed and the highest recognition rate reaches up to 100%. The results show that the identification method of special quality eggs using near-infrared is feasible and the symbol entropy can be used as a new feature extraction method of near-infrared spectra.

A general theory on frequency and time-frequency analysis of irregularly sampled time series based on projection methods - Part 1: Frequency analysis

Science.gov (United States)

Lenoir, Guillaume; Crucifix, Michel

2018-03-01

We develop a general framework for the frequency analysis of irregularly sampled time series. It is based on the Lomb-Scargle periodogram, but extended to algebraic operators accounting for the presence of a polynomial trend in the model for the data, in addition to a periodic component and a background noise. Special care is devoted to the correlation between the trend and the periodic component. This new periodogram is then cast into the Welch overlapping segment averaging (WOSA) method in order to reduce its variance. We also design a test of significance for the WOSA periodogram, against the background noise. The model for the background noise is a stationary Gaussian continuous autoregressive-moving-average (CARMA) process, more general than the classical Gaussian white or red noise processes. CARMA parameters are estimated following a Bayesian framework. We provide algorithms that compute the confidence levels for the WOSA periodogram and fully take into account the uncertainty in the CARMA noise parameters. Alternatively, a theory using point estimates of CARMA parameters provides analytical confidence levels for the WOSA periodogram, which are more accurate than Markov chain Monte Carlo (MCMC) confidence levels and, below some threshold for the number of data points, less costly in computing time. We then estimate the amplitude of the periodic component with least-squares methods, and derive an approximate proportionality between the squared amplitude and the periodogram. This proportionality leads to a new extension for the periodogram: the weighted WOSA periodogram, which we recommend for most frequency analyses with irregularly sampled data. The estimated signal amplitude also permits filtering in a frequency band. Our results generalise and unify methods developed in the fields of geosciences, engineering, astronomy and astrophysics. They also constitute the starting point for an extension to the continuous wavelet transform developed in a companion

New hybrid frequency reuse method for packet loss minimization in LTE network.

Science.gov (United States)

Ali, Nora A; El-Dakroury, Mohamed A; El-Soudani, Magdi; ElSayed, Hany M; Daoud, Ramez M; Amer, Hassanein H

2015-11-01

This paper investigates the problem of inter-cell interference (ICI) in Long Term Evolution (LTE) mobile systems, which is one of the main problems that causes loss of packets between the base station and the mobile station. Recently, different frequency reuse methods, such as soft and fractional frequency reuse, have been introduced in order to mitigate this type of interference. In this paper, minimizing the packet loss between the base station and the mobile station is the main concern. Soft Frequency Reuse (SFR), which is the most popular frequency reuse method, is examined and the amount of packet loss is measured. In order to reduce packet loss, a new hybrid frequency reuse method is implemented. In this method, each cell occupies the same bandwidth of the SFR, but the total system bandwidth is greater than in SFR. This will provide the new method with a lot of new sub-carriers from the neighboring cells to reduce the ICI which represents a big problem in many applications and causes a lot of packets loss. It is found that the new hybrid frequency reuse method has noticeable improvement in the amount of packet loss compared to SFR method in the different frequency bands. Traffic congestion management in Intelligent Transportation system (ITS) is one of the important applications that is affected by the packet loss due to the large amount of traffic that is exchanged between the base station and the mobile node. Therefore, it is used as a studied application for the proposed frequency reuse method and the improvement in the amount of packet loss reached 49.4% in some frequency bands using the new hybrid frequency reuse method.

Elasticity analysis by MR elastography using the instantaneous frequency method

International Nuclear Information System (INIS)

Oshiro, Osamu; Suga, Mikio; Minato, Kotaro; Okamoto, Jun; Takizawa, Osamu; Matsuda, Tetsuya; Komori, Masaru; Takahashi, Takashi

2000-01-01

This paper describes a calculation method for estimating the elasticity of human organs using magnetic resonance elastography (MRE) images. The method is based on the instantaneous frequency method, which is very sensitive to noise. Therefore, the proposed method also incorporates a noise-reduction function. In the instantaneous frequency method, Fourier transform is applied to the measurement signal. Then, inverse Fourier transform is performed after the negative frequency component is set to zero. In the proposed method, noise is reduced by processing in which the positive higher frequency component is also set to zero before inverse Fourier transform is performed. First, we conducted a simulation study and confirmed the applicability of this method and the noise reduction function. Next, we carried out a phantom experiment and demonstrated that elasticity images could be generated, with the gray level corresponding to the local frequency in MRE images. (author)

Damage identification method for continuous girder bridges based on spatially-distributed long-gauge strain sensing under moving loads

Science.gov (United States)

Wu, Bitao; Wu, Gang; Yang, Caiqian; He, Yi

2018-05-01

A novel damage identification method for concrete continuous girder bridges based on spatially-distributed long-gauge strain sensing is presented in this paper. First, the variation regularity of the long-gauge strain influence line of continuous girder bridges which changes with the location of vehicles on the bridge is studied. According to this variation regularity, a calculation method for the distribution regularity of the area of long-gauge strain history is investigated. Second, a numerical simulation of damage identification based on the distribution regularity of the area of long-gauge strain history is conducted, and the results indicate that this method is effective for identifying damage and is not affected by the speed, axle number and weight of vehicles. Finally, a real bridge test on a highway is conducted, and the experimental results also show that this method is very effective for identifying damage in continuous girder bridges, and the local element stiffness distribution regularity can be revealed at the same time. This identified information is useful for maintaining of continuous girder bridges on highways.

On the orthogonalised reverse path method for nonlinear system identification

Science.gov (United States)

Muhamad, P.; Sims, N. D.; Worden, K.

2012-09-01

The problem of obtaining the underlying linear dynamic compliance matrix in the presence of nonlinearities in a general multi-degree-of-freedom (MDOF) system can be solved using the conditioned reverse path (CRP) method introduced by Richards and Singh (1998 Journal of Sound and Vibration, 213(4): pp. 673-708). The CRP method also provides a means of identifying the coefficients of any nonlinear terms which can be specified a priori in the candidate equations of motion. Although the CRP has proved extremely useful in the context of nonlinear system identification, it has a number of small issues associated with it. One of these issues is the fact that the nonlinear coefficients are actually returned in the form of spectra which need to be averaged over frequency in order to generate parameter estimates. The parameter spectra are typically polluted by artefacts from the identification of the underlying linear system which manifest themselves at the resonance and anti-resonance frequencies. A further problem is associated with the fact that the parameter estimates are extracted in a recursive fashion which leads to an accumulation of errors. The first minor objective of this paper is to suggest ways to alleviate these problems without major modification to the algorithm. The results are demonstrated on numerically-simulated responses from MDOF systems. In the second part of the paper, a more radical suggestion is made, to replace the conditioned spectral analysis (which is the basis of the CRP method) with an alternative time domain decorrelation method. The suggested approach - the orthogonalised reverse path (ORP) method - is illustrated here using data from simulated single-degree-of-freedom (SDOF) and MDOF systems.

Low velocity target detection based on time-frequency image for high frequency ground wave radar

Institute of Scientific and Technical Information of China (English)

YAN Songhua; WU Shicai; WEN Biyang

2007-01-01

The Doppler spectral broadening resulted from non-stationary movement of target and radio-frequency interference will decrease the veracity of target detection by high frequency ground wave(HEGW)radar.By displaying the change of signal energy on two dimensional time-frequency images based on time-frequency analysis,a new mathematical morphology method to distinguish target from nonlinear time-frequency curves is presented.The analyzed results from the measured data verify that with this new method the target can be detected correctly from wide Doppler spectrum.

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

Science.gov (United States)

Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

2018-02-01

Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to

Compact printed two dipole array antenna with a high front-back ratio for ultra-high-frequency radio-frequency identification handheld reader applications

DEFF Research Database (Denmark)

Liu, Qi; Zhang, Shuai; He, Sailing

2015-01-01

A printed two-dipole array antenna with a high front-back ratio is proposed for ultra-high-frequency (UHF) radio-frequency identification handheld readers. The proposed antenna is a parasitic dual-element array with the ends of both elements folded back towards each other for additional coupling....

A PCR-based method for identification of bifidobacteria from the human alimentary tract at the species level

NARCIS (Netherlands)

Venema, K.; Maathuis, A.J.H.

2003-01-01

A polymerase chain reaction (PCR)-based method was developed for the identification of isolates of Bifidobacterium at the species level. Using two Bifidobacterium-specific primers directed against the 16S ribosomal gene (Bif164 and Bif662), a PCR product was obtained from the type strains of 12

Implanting inequality: empirical evidence of social and ethical risks of implantable radio-frequency identification (RFID) devices.

Science.gov (United States)

Monahan, Torin; Fisher, Jill A

2010-10-01

The aim of this study was to assess empirically the social and ethical risks associated with implantable radio-frequency identification (RFID) devices. Qualitative research included observational studies in twenty-three U.S. hospitals that have implemented new patient identification systems and eighty semi-structured interviews about the social and ethical implications of new patient identification systems, including RFID implants. The study identified three primary social and ethical risks associated with RFID implants: (i) unfair prioritization of patients based on their participation in the system, (ii) diminished trust of patients by care providers, and (iii) endangerment of patients who misunderstand the capabilities of the systems. RFID implants may aggravate inequalities in access to care without any clear health benefits. This research underscores the importance of critically evaluating new healthcare technologies from the perspective of both normative ethics and empirical ethics.

The frequency-independent control method for distributed generation systems

DEFF Research Database (Denmark)

Naderi, Siamak; Pouresmaeil, Edris; Gao, Wenzhong David

2012-01-01

In this paper a novel frequency-independent control method suitable for distributed generation (DG) is presented. This strategy is derived based on the . abc/. αβ transformation and . abc/. dq transformation of the ac system variables. The active and reactive currents injected by the DG are contr......In this paper a novel frequency-independent control method suitable for distributed generation (DG) is presented. This strategy is derived based on the . abc/. αβ transformation and . abc/. dq transformation of the ac system variables. The active and reactive currents injected by the DG...

Overcoming Inter-Subject Variability in BCI Using EEG-Based Identification

Directory of Open Access Journals (Sweden)

J. Stastny

2014-04-01

Full Text Available The high dependency of the Brain Computer Interface (BCI system performance on the BCI user is a well-known issue of many BCI devices. This contribution presents a new way to overcome this problem using a synergy between a BCI device and an EEG-based biometric algorithm. Using the biometric algorithm, the BCI device automatically identifies its current user and adapts parameters of the classification process and of the BCI protocol to maximize the BCI performance. In addition to this we present an algorithm for EEG-based identification designed to be resistant to variations in EEG recordings between sessions, which is also demonstrated by an experiment with an EEG database containing two sessions recorded one year apart. Further, our algorithm is designed to be compatible with our movement-related BCI device and the evaluation of the algorithm performance took place under conditions of a standard BCI experiment. Estimation of the mu rhythm fundamental frequency using the Frequency Zooming AR modeling is used for EEG feature extraction followed by a classifier based on the regularized Mahalanobis distance. An average subject identification score of 96 % is achieved.

Hob Identification Methods

Directory of Open Access Journals (Sweden)

Andrzej Piotrowski

2018-03-01

Full Text Available In industrial practice, hobs are manufactured and used. The problem boils down to the identification of a hob with defining its profile, which depends on many design and technological parameters (such as the grinding wheel size, profile, type and positioning during machining. This makes the basis for the correct execution and sharpening of the tool. The accuracy of the hob determines the quality of gear wheel teeth being shaped. The article presents the hob identification methods that are possible to be used in industrial and laboratory practice.

A Semiactive and Adaptive Hybrid Control System for a Tracked Vehicle Hydropneumatic Suspension Based on Disturbance Identification

Directory of Open Access Journals (Sweden)

Shousong Han

2017-01-01

Full Text Available The riding conditions for a high-speed tracked vehicle are quite complex. To enhance the adaptability of suspension systems to different riding conditions, a semiactive and self-adaptive hybrid control strategy based on disturbance velocity and frequency identification was proposed. A mathematical model of the semiactive, self-adaptive hybrid suspension control system, along with a performance evaluation function, was established. Based on a two-degree-of-freedom (DOF suspension system, the kinematic relations and frequency zero-crossing detection method were defined, and expressions for the disturbance velocity and disturbance frequency of the road were obtained. Optimal scheduling of the semiactive hybrid damping control gain (csky, cground, chybrid and self-adaptive control gain (cv under different disturbances were realized by exploiting the particle swarm multiobjective optimization algorithm. An experimental study using a carefully designed test rig was performed under a number of typical riding conditions of tracked vehicles, and the results showed that the proposed control strategy is capable of accurately recognizing different disturbances, shifting between control modes (semiactive/self-adaptive, and scheduling the damping control gain according to the disturbance identification outcomes; hence, the proposed strategy could achieve a good trade-off between ride comfort and ride safety and efficiently increase the overall performance of the suspension under various riding conditions.

A topological method for vortex identification in turbulent flows

Energy Technology Data Exchange (ETDEWEB)

Zhong, Qiang; Chen, Huai; Li, Danxun [State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084 (China); Chen, Qigang, E-mail: lidx@mail.tsinghua.edu.cn [School of Civil Engineering, Beijing Jiaotong University, Beijing 100044 (China)

2017-02-15

We present a novel vortex identification method based on structured vorticity ( ω {sub s}) of the direction field of flow (velocity vectors set to unit magnitude). As a direct measure of streamline curvature is insensitive to vortex strength, ω {sub s} is effective in detecting vortices of various strengths. The effectiveness has been tested against both analytical flows (pure shear flow, Oseen vortex flow, strong outward spiraling motion, straining flow, Taylor–Green flow) and experimental flows (closed cavity flow, closed and open channel flow). Comparison of the new method with the swirling-strength method indicates that the new method shows promise as being a simple and effective criterion for vortex identification. (paper)

Noncontact blood species identification method based on spatially resolved near-infrared transmission spectroscopy

Science.gov (United States)

Zhang, Linna; Sun, Meixiu; Wang, Zhennan; Li, Hongxiao; Li, Yingxin; Li, Gang; Lin, Ling

2017-09-01

The inspection and identification of whole blood are crucially significant for import-export ports and inspection and quarantine departments. In our previous research, we proved Near-Infrared diffuse transmitted spectroscopy method was potential for noninvasively identifying three blood species, including macaque, human and mouse, with samples measured in the cuvettes. However, in open sampling cases, inspectors may be endangered by virulence factors in blood samples. In this paper, we explored the noncontact measurement for classification, with blood samples measured in the vacuum blood vessels. Spatially resolved near-infrared spectroscopy was used to improve the prediction accuracy. Results showed that the prediction accuracy of the model built with nine detection points was more than 90% in identification between all five species, including chicken, goat, macaque, pig and rat, far better than the performance of the model built with single-point spectra. The results fully supported the idea that spatially resolved near-infrared spectroscopy method can improve the prediction ability, and demonstrated the feasibility of this method for noncontact blood species identification in practical applications.

Y-STR frequency surveying method

DEFF Research Database (Denmark)

Willuweit, Sascha; Caliebe, Amke; Andersen, Mikkel Meyer

2011-01-01

Reasonable formalized methods to estimate the frequencies of DNA profiles generated from lineage markers have been proposed in the past years and were discussed in the forensic community. Recently, collections of population data on the frequencies of variations in Y chromosomal STR profiles have...... reached a new quality with the establishment of the comprehensive neatly quality-controlled reference database YHRD. Grounded on such unrivalled empirical material from hundreds of populations studies the core assumption of the Haplotype Frequency Surveying Method originally described 10 years ago can...... be tested and improved. Here we provide new approaches to calculate the parameters used in the frequency surveying method: a maximum likelihood estimation of the regression parameters (r1, r2, s1 and s2) and a revised Frequency Surveying framework with variable binning and a database preprocessing to take...

Spectroscopic pulsational frequency identification and mode determination of γ Doradus star HD 12901

Science.gov (United States)

Brunsden, E.; Pollard, K. R.; Cottrell, P. L.; Wright, D. J.; De Cat, P.

2012-12-01

Using multisite spectroscopic data collected from three sites, the frequencies and pulsational modes of the γ Doradus star HD 12901 were identified. A total of six frequencies in the range 1-2 d-1 were observed, their identifications supported by multiple line-profile measurement techniques and previously published photometry. Five frequencies were of sufficient signal-to-noise ratio for mode identification, and all five displayed similar three-bump standard deviation profiles which were fitted well with (l,m) = (1,1) modes. These fits had reduced χ2 values of less than 18. We propose that this star is an excellent candidate to test models of non-radially pulsating γ Doradus stars as a result of the presence of multiple (1,1) modes. This paper includes data taken at the Mount John University Observatory of the University of Canterbury (New Zealand), the McDonald Observatory of the University of Texas at Austin (Texas, USA) and the European Southern Observatory at La Silla (Chile).

The impact of parameter identification methods on drug therapy control in an intensive care unit

NARCIS (Netherlands)

Hann, C.E.; Chase, J.G.; Ypma, M.F.; Elfring, J.; Nor, N.H.M.; Lawrence, P.; Shaw, G.M.

2008-01-01

This paper investigates the impact of fast parameter identification methods, which do not require any forward simulations, on model-based glucose control, using retrospective data in the Christchurch Hospital Intensive Care Unit. The integral-based identification method has been previously

A fuzzy logic-based damage identification method for simply-supported bridge using modal shape ratios

Directory of Open Access Journals (Sweden)

Hanbing Liu

2012-08-01

Full Text Available A fuzzy logic system (FLS is established for damage identification of simply supported bridge. A novel damage indicator is developed based on ratios of mode shape components between before and after damage. Numerical simulation of a simply-supported bridge is presented to demonstrate the memory, inference and anti-noise ability of the proposed method. The bridge is divided into eight elements and nine nodes, the damage indicator vector at characteristic nodes is used as the input measurement of FLS. Results reveal that FLS can detect damage of training patterns with an accuracy of 100%. Aiming at other test patterns, the FLS also possesses favorable inference ability, the identification accuracy for single damage location is up to 93.75%. Tests with noise simulated data show that the FLS possesses favorable anti-noise ability.

Travel path and transport mode identification method using ''less-frequently-detected'' position data

International Nuclear Information System (INIS)

Shimizu, T; Yamaguchi, T; Ai, H; Katagiri, Y; Kawase, J

2014-01-01

This study aims to seek method on travel path and transport mode identification in case positions of travellers are detected in low frequency. The survey in which ten test travellers with GPS logger move around Tokyo city centre was conducted. Travel path datasets of each traveller in which position data are selected every five minutes are processed from our survey data. Coverage index analysis based on the buffer analysis using GIS software is conducted. The condition and possibility to identify a path and a transport mode used are discussed

Research on Damage Identification of Bridge Based on Digital Image Measurement

Science.gov (United States)

Liang, Yingjing; Huan, Shi; Tao, Weijun

2017-12-01

In recent years, the number of the damage bridge due to excessive deformation gradually increased, which caused significant property damage and casualties. Hence health monitoring and the damage detection of the bridge structure based on the deflection measurement are particularly important. The current conventional deflection measurement methods, such as total station, connected pipe, GPS, etc., have many shortcomings as low efficiency, heavy workload, low degree of automation, operating frequency and working time constrained. GPS has a low accuracy in the vertical displacement measurement and cannot meet the dynamic measured requirements of the current bridge engineering. This paper presents a bridge health monitoring and damage detection technology based on digital image measurement method in which the measurement accuracy is sub-millimeter level and can achieve the 24-hour automatic non-destructive monitoring for the deflection. It can be concluded from this paper that it is feasible to use digital image measurement method for identification of the damage in the bridge structure, because it has been validated by the theoretical analysis, the laboratory model and the application of the real bridge.

An identification method for damping ratio in rotor systems

Science.gov (United States)

Wang, Weimin; Li, Qihang; Gao, Jinji; Yao, Jianfei; Allaire, Paul

2016-02-01

Centrifugal compressor testing with magnetic bearing excitations is the last step to assure the compressor rotordynamic stability in the designed operating conditions. To meet the challenges of stability evaluation, a new method combining the rational polynomials method (RPM) with the weighted instrumental variables (WIV) estimator to fit the directional frequency response function (dFRF) is presented. Numerical simulation results show that the method suggested in this paper can identify the damping ratio of the first forward and backward modes with high accuracy, even in a severe noise environment. Experimental tests were conducted to study the effect of different bearing configurations on the stability of rotor. Furthermore, two example centrifugal compressors (a nine-stage straight-through and a six-stage back-to-back) were employed to verify the feasibility of identification method in industrial configurations as well.

FRF based position controller design through system identification for A hydraulic cylinder

Energy Technology Data Exchange (ETDEWEB)

Seo, Hyoung Kyu; Kim, Dong Hwan [Dept. of Mechanical Design and Robot Engineering, Seoul National University of Science and Technology, Seoul (Korea, Republic of); Park, Jong Won [Reliability Assessment Center, Korea Institute of Machinery and Materials, Daejeon (Korea, Republic of)

2015-11-15

In this study, we have focused on the design of a controller and an operating program for the operation of the hydraulic actuators used in a shaker. To control the motion of the shaker accurately, the position of each hydraulic cylinder should be controlled precisely even under an uncertain environment. For this purpose, we have suggested a control algorithm using an FRF (frequency response function) based control which senses the behavior of the actuator in advance, calculates a transfer function through the system identification method, and provides the final control input. The experimental results on the performance of this system were compared with that of a simple PID control algorithm.

A Bayesian statistical method for particle identification in shower counters

International Nuclear Information System (INIS)

Takashimizu, N.; Kimura, A.; Shibata, A.; Sasaki, T.

2004-01-01

We report an attempt on identifying particles using a Bayesian statistical method. We have developed the mathematical model and software for this purpose. We tried to identify electrons and charged pions in shower counters using this method. We designed an ideal shower counter and studied the efficiency of identification using Monte Carlo simulation based on Geant4. Without having any other information, e.g. charges of particles which are given by tracking detectors, we have achieved 95% identifications of both particles

Applications of radio frequency identification systems in the mining industry

Energy Technology Data Exchange (ETDEWEB)

Hind, D [Davis Derby Limited (United Kingdom)

1994-12-31

The paper describes the application of Radio Frequency Identification (RFID) systems in the mining industry for both surface and underground mines. The history of the RFID system, types available, the transponder, and the various techniques used are described and compared. The design and certification of a system for use in a hazardous area are described, noting the hazard of inadvertent detonator ignition. 2 refs.

Development of evaluation method for software hazard identification techniques

International Nuclear Information System (INIS)

Huang, H. W.; Chen, M. H.; Shih, C.; Yih, S.; Kuo, C. T.; Wang, L. H.; Yu, Y. C.; Chen, C. W.

2006-01-01

This research evaluated the applicable software hazard identification techniques nowadays, such as, Preliminary Hazard Analysis (PHA), Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Markov chain modeling, Dynamic Flow-graph Methodology (DFM), and simulation-based model analysis; and then determined indexes in view of their characteristics, which include dynamic capability, completeness, achievability, detail, signal/noise ratio, complexity, and implementation cost. By this proposed method, the analysts can evaluate various software hazard identification combinations for specific purpose. According to the case study results, the traditional PHA + FMEA + FTA (with failure rate) + Markov chain modeling (with transfer rate) combination is not competitive due to the dilemma for obtaining acceptable software failure rates. However, the systematic architecture of FTA and Markov chain modeling is still valuable for realizing the software fault structure. The system centric techniques, such as DFM and simulation-based model-analysis, show the advantage on dynamic capability, achievability, detail, signal/noise ratio. However, their disadvantages are the completeness complexity and implementation cost. This evaluation method can be a platform to reach common consensus for the stakeholders. Following the evolution of software hazard identification techniques, the evaluation results could be changed. However, the insight of software hazard identification techniques is much more important than the numbers obtained by the evaluation. (authors)

Physically based method for measuring suspended-sediment concentration and grain size using multi-frequency arrays of acoustic-doppler profilers

Science.gov (United States)

Topping, David J.; Wright, Scott A.; Griffiths, Ronald; Dean, David

2014-01-01

As the result of a 12-year program of sediment-transport research and field testing on the Colorado River (6 stations in UT and AZ), Yampa River (2 stations in CO), Little Snake River (1 station in CO), Green River (1 station in CO and 2 stations in UT), and Rio Grande (2 stations in TX), we have developed a physically based method for measuring suspended-sediment concentration and grain size at 15-minute intervals using multifrequency arrays of acoustic-Doppler profilers. This multi-frequency method is able to achieve much higher accuracies than single-frequency acoustic methods because it allows removal of the influence of changes in grain size on acoustic backscatter. The method proceeds as follows. (1) Acoustic attenuation at each frequency is related to the concentration of silt and clay with a known grain-size distribution in a river cross section using physical samples and theory. (2) The combination of acoustic backscatter and attenuation at each frequency is uniquely related to the concentration of sand (with a known reference grain-size distribution) and the concentration of silt and clay (with a known reference grain-size distribution) in a river cross section using physical samples and theory. (3) Comparison of the suspended-sand concentrations measured at each frequency using this approach then allows theory-based calculation of the median grain size of the suspended sand and final correction of the suspended-sand concentration to compensate for the influence of changing grain size on backscatter. Although this method of measuring suspended-sediment concentration is somewhat less accurate than using conventional samplers in either the EDI or EWI methods, it is much more accurate than estimating suspended-sediment concentrations using calibrated pump measurements or single-frequency acoustics. Though the EDI and EWI methods provide the most accurate measurements of suspended-sediment concentration, these measurements are labor-intensive, expensive, and

A NOVEL WRAPPING CURVELET TRANSFORMATION BASED ANGULAR TEXTURE PATTERN (WCTATP EXTRACTION METHOD FOR WEED IDENTIFICATION

Directory of Open Access Journals (Sweden)

D. Ashok Kumar

2016-02-01

Full Text Available Apparently weed is a major menace in crop production as it competes with crop for nutrients, moisture, space and light which resulting in poor growth and development of the crop and finally yield. Yield loss accounts for even more than 70% when crops are frown under unweeded condition with severe weed infestation. Weed management is the most significant process in the agricultural applications to improve the crop productivity rate and reduce the herbicide application cost. Existing weed detection techniques does not yield better performance due to the complex background, illumination variation and crop and weed overlapping in the agricultural field image. Hence, there arises a need for the development of effective weed identification technique. To overcome this drawback, this paper proposes a novel Wrapping Curvelet Transformation Based Angular Texture Pattern Extraction Method (WCTATP for weed identification. In our proposed work, Global Histogram Equalization (GHE is used improve the quality of the image and Adaptive Median Filter (AMF is used for filtering the impulse noise from the image. Plant image identification is performed using green pixel extraction and k-means clustering. Wrapping Curvelet transform is applied to the plant image. Feature extraction is performed to extract the angular texture pattern of the plant image. Particle Swarm Optimization (PSO based Differential Evolution Feature Selection (DEFS approach is applied to select the optimal features. Then, the selected features are learned and passed through an RVM based classifier to find out the weed. Edge detection and contouring is performed to identify the weed in the plant image. The Fuzzy rule-based approach is applied to detect the low, medium and high levels of the weed patchiness. From the experimental results, it is clearly observed that the accuracy of the proposed approach is higher than the existing Support Vector Machine (SVM based approaches. The proposed approach

Nonparametric identification of nonlinear dynamic systems using a synchronisation-based method

Science.gov (United States)

Kenderi, Gábor; Fidlin, Alexander

2014-12-01

The present study proposes an identification method for highly nonlinear mechanical systems that does not require a priori knowledge of the underlying nonlinearities to reconstruct arbitrary restoring force surfaces between degrees of freedom. This approach is based on the master-slave synchronisation between a dynamic model of the system as the slave and the real system as the master using measurements of the latter. As the model synchronises to the measurements, it becomes an observer of the real system. The optimal observer algorithm in a least-squares sense is given by the Kalman filter. Using the well-known state augmentation technique, the Kalman filter can be turned into a dual state and parameter estimator to identify parameters of a priori characterised nonlinearities. The paper proposes an extension of this technique towards nonparametric identification. A general system model is introduced by describing the restoring forces as bilateral spring-dampers with time-variant coefficients, which are estimated as augmented states. The estimation procedure is followed by an a posteriori statistical analysis to reconstruct noise-free restoring force characteristics using the estimated states and their estimated variances. Observability is provided using only one measured mechanical quantity per degree of freedom, which makes this approach less demanding in the number of necessary measurement signals compared with truly nonparametric solutions, which typically require displacement, velocity and acceleration signals. Additionally, due to the statistical rigour of the procedure, it successfully addresses signals corrupted by significant measurement noise. In the present paper, the method is described in detail, which is followed by numerical examples of one degree of freedom (1DoF) and 2DoF mechanical systems with strong nonlinearities of vibro-impact type to demonstrate the effectiveness of the proposed technique.

A Review of Frequency Response Analysis Methods for Power Transformer Diagnostics

Directory of Open Access Journals (Sweden)

Saleh Alsuhaibani

2016-10-01

Full Text Available Power transformers play a critical role in electric power networks. Such transformers can suffer failures due to multiple stresses and aging. Thus, assessment of condition and diagnostic techniques are of great importance for improving power network reliability and service continuity. Several techniques are available to diagnose the faults within the power transformer. Frequency response analysis (FRA method is a powerful technique for diagnosing transformer winding deformation and several other types of problems that are caused during manufacture, transportation, installation and/or service life. This paper provides a comprehensive review on FRA methods and their applications in diagnostics and fault identification for power transformers. The paper discusses theory and applications of FRA methods as well as various issues and challenges faced in the application of this method.

A New High Frequency Injection Method Based on Duty Cycle Shifting without Maximum Voltage Magnitude Loss

DEFF Research Database (Denmark)

Wang, Dong; Lu, Kaiyuan; Rasmussen, Peter Omand

2015-01-01

The conventional high frequency signal injection method is to superimpose a high frequency voltage signal to the commanded stator voltage before space vector modulation. Therefore, the magnitude of the voltage used for machine torque production is limited. In this paper, a new high frequency...... amplitude. This may be utilized to develop new position estimation algorithm without involving the inductance in the medium to high speed range. As an application example, a developed inductance independent position estimation algorithm using the proposed high frequency injection method is applied to drive...... injection method, in which high frequency signal is generated by shifting the duty cycle between two neighboring switching periods, is proposed. This method allows injecting a high frequency signal at half of the switching frequency without the necessity to sacrifice the machine fundamental voltage...

Optimization of measurement methods for a multi-frequency electromagnetic field from mobile phone base station using broadband EMF meter

Directory of Open Access Journals (Sweden)

Paweł Bieńkowski

2015-10-01

Full Text Available Background: This paper presents the characteristics of the mobile phone base station (BS as an electromagnetic field (EMF source. The most common system configurations with their construction are described. The parameters of radiated EMF in the context of the access to methods and other parameters of the radio transmission are discussed. Attention was also paid to antennas that are used in this technology. Material and Methods: The influence of individual components of a multi-frequency EMF, most commonly found in the BS surroundings, on the resultant EMF strength value indicated by popular broadband EMF meters was analyzed. The examples of metrological characteristics of the most common EMF probes and 2 measurement scenarios of the multisystem base station, with and without microwave relays, are shown. Results: The presented method for measuring the multi-frequency EMF using 2 broadband probes allows for the significant minimization of measurement uncertainty. Equations and formulas that can be used to calculate the actual EMF intensity from multi-frequency sources are shown. They have been verified in the laboratory conditions on a specific standard setup as well as in real conditions in a survey of the existing base station with microwave relays. Conclusions: Presented measurement methodology of multi-frequency EMF from BS with microwave relays, validated both in laboratory and real conditions. It has been proven that the described measurement methodology is the optimal approach to the evaluation of EMF exposure in BS surrounding. Alternative approaches with much greater uncertainty (precaution method or more complex measuring procedure (sources exclusion method are also presented. Med Pr 2015;66(5:701–712

Radio Frequency Identification (RFID) in healthcare: a literature review.

Science.gov (United States)

Kolokathi, Aikaterini; Rallis, Panagiotis

2013-01-01

Creating and maintaining a safe and high-quality health care environment is of great importance for global community. New technologies and their applications can help us achieve this goal. Radio-Frequency Identification (RIFD) technology is considered one of those technologies and even today there are some interesting deployments in the health industry. As a result, this work aims to present the basic idea behind RFID solutions, problems that can be addressed with the adoption of RFID and the benefits of relative applications.

Fast LCMV-based Methods for Fundamental Frequency Estimation

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Glentis, George-Othon; Christensen, Mads Græsbøll

2013-01-01

peaks and require matrix inversions for each point in the search grid. In this paper, we therefore consider fast implementations of LCMV-based fundamental frequency estimators, exploiting the estimators' inherently low displacement rank of the used Toeplitz-like data covariance matrices, using...... with several orders of magnitude, but, as we show, further computational savings can be obtained by the adoption of an approximative IAA-based data covariance matrix estimator, reminiscent of the recently proposed Quasi-Newton IAA technique. Furthermore, it is shown how the considered pitch estimators can...... as such either the classic time domain averaging covariance matrix estimator, or, if aiming for an increased spectral resolution, the covariance matrix resulting from the application of the recent iterative adaptive approach (IAA). The proposed exact implementations reduce the required computational complexity...

Spectral element method for elastic and acoustic waves in frequency domain

Energy Technology Data Exchange (ETDEWEB)

Shi, Linlin; Zhou, Yuanguo; Wang, Jia-Min; Zhuang, Mingwei [Institute of Electromagnetics and Acoustics, and Department of Electronic Science, Xiamen, 361005 (China); Liu, Na, E-mail: liuna@xmu.edu.cn [Institute of Electromagnetics and Acoustics, and Department of Electronic Science, Xiamen, 361005 (China); Liu, Qing Huo, E-mail: qhliu@duke.edu [Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27708 (United States)

2016-12-15

Numerical techniques in time domain are widespread in seismic and acoustic modeling. In some applications, however, frequency-domain techniques can be advantageous over the time-domain approach when narrow band results are desired, especially if multiple sources can be handled more conveniently in the frequency domain. Moreover, the medium attenuation effects can be more accurately and conveniently modeled in the frequency domain. In this paper, we present a spectral-element method (SEM) in frequency domain to simulate elastic and acoustic waves in anisotropic, heterogeneous, and lossy media. The SEM is based upon the finite-element framework and has exponential convergence because of the use of GLL basis functions. The anisotropic perfectly matched layer is employed to truncate the boundary for unbounded problems. Compared with the conventional finite-element method, the number of unknowns in the SEM is significantly reduced, and higher order accuracy is obtained due to its spectral accuracy. To account for the acoustic-solid interaction, the domain decomposition method (DDM) based upon the discontinuous Galerkin spectral-element method is proposed. Numerical experiments show the proposed method can be an efficient alternative for accurate calculation of elastic and acoustic waves in frequency domain.

An improved phase-locked loop method for automatic resonance frequency tracing based on static capacitance broadband compensation for a high-power ultrasonic transducer.

Science.gov (United States)

Dong, Hui-juan; Wu, Jian; Zhang, Guang-yu; Wu, Han-fu

2012-02-01

The phase-locked loop (PLL) method is widely used for automatic resonance frequency tracing (ARFT) of high-power ultrasonic transducers, which are usually vibrating systems with high mechanical quality factor (Qm). However, a heavily-loaded transducer usually has a low Qm because the load has a large mechanical loss. In this paper, a series of theoretical analyses is carried out to detail why the traditional PLL method could cause serious frequency tracing problems, including loss of lock, antiresonance frequency tracing, and large tracing errors. The authors propose an improved ARFT method based on static capacitance broadband compensation (SCBC), which is able to address these problems. Experiments using a generator based on the novel method were carried out using crude oil as the transducer load. The results obtained have demonstrated the effectiveness of the novel method, compared with the conventional PLL method, in terms of improved tracing accuracy (±9 Hz) and immunity to antiresonance frequency tracing and loss of lock.

Applications of radio frequency identification systems in the mining industry

Energy Technology Data Exchange (ETDEWEB)

Hind, D J [Davis Derby Ltd., Derby (United Kingdom)

1994-01-01

Radio Frequency Identification Systems (RFID) are one of the automatic data capture technologies taking over from bar codes and magnetic swipe cards in many applications involving automatic hands free operation in arduous environments. RFID systems are based on the use of miniature radio transponders carrying encoded electronic data that is used to uniquely identify the identity of transponders. The paper reviews the types of system available and compares the various techniques involved in the different systems. The various types of transponder are described including the latest state of the art passive read/write high performance types. The problems involved in designing and certifying a system for use in hazardous areas are described, with particular reference to the problems of inadvertent detonator ignition by radio systems. Applications of RFID systems in the mining industry are described, covering applications both on the surface and underground. 1 ref., 10 figs.

Identification of Histamine H3 Receptor Ligands Using a New Crystal Structure Fragment-based Method

DEFF Research Database (Denmark)

Frandsen, Ida Osborn; Boesgaard, Michael W; Fidom, Kimberley

2017-01-01

Virtual screening offers an efficient alternative to high-throughput screening in the identification of pharmacological tools and lead compounds. Virtual screening is typically based on the matching of target structures or ligand pharmacophores to commercial or in-house compound catalogues....... The complete pharmacophore fragment library is freely available through the GPCR database, GPCRdb, allowing the successful application herein to be repeated for most of the 285 class A GPCR targets. The method could also easily be adapted to other protein families....

Description of an identification method of thermocouple time constant based on application of recursive numerical filtering to temperature fluctuation

International Nuclear Information System (INIS)

Bernardin, B.; Le Guillou, G.; Parcy, JP.

1981-04-01

Usual spectral methods, based on temperature fluctuation analysis, aiming at thermocouple time constant identification are using an equipment too much sophisticated for on-line application. It is shown that numerical filtering is optimal for this application, the equipment is simpler than for spectral methods and less samples of signals are needed for the same accuracy. The method is described and a parametric study was performed using a temperature noise simulator [fr

State of charge estimation of lithium-ion batteries based on an improved parameter identification method

International Nuclear Information System (INIS)

Xia, Bizhong; Chen, Chaoren; Tian, Yong; Wang, Mingwang; Sun, Wei; Xu, Zhihui

2015-01-01

The SOC (state of charge) is the most important index of the battery management systems. However, it cannot be measured directly with sensors and must be estimated with mathematical techniques. An accurate battery model is crucial to exactly estimate the SOC. In order to improve the model accuracy, this paper presents an improved parameter identification method. Firstly, the concept of polarization depth is proposed based on the analysis of polarization characteristics of the lithium-ion batteries. Then, the nonlinear least square technique is applied to determine the model parameters according to data collected from pulsed discharge experiments. The results show that the proposed method can reduce the model error as compared with the conventional approach. Furthermore, a nonlinear observer presented in the previous work is utilized to verify the validity of the proposed parameter identification method in SOC estimation. Finally, experiments with different levels of discharge current are carried out to investigate the influence of polarization depth on SOC estimation. Experimental results show that the proposed method can improve the SOC estimation accuracy as compared with the conventional approach, especially under the conditions of large discharge current. - Highlights: • The polarization characteristics of lithium-ion batteries are analyzed. • The concept of polarization depth is proposed to improve model accuracy. • A nonlinear least square technique is applied to determine the model parameters. • A nonlinear observer is used as the SOC estimation algorithm. • The validity of the proposed method is verified by experimental results.

Multi-cracks identification based on the nonlinear vibration response of beams subjected to moving harmonic load

Directory of Open Access Journals (Sweden)

Chouiyakh H.

2016-01-01

Full Text Available The aim of this work is to investigate the nonlinear forced vibration of beams containing an arbitrary number of cracks and to perform a multi-crack identification procedure based on the obtained signals. Cracks are assumed to be open and modelled trough rotational springs linking two adjacent sub-beams. Forced vibration analysis is performed by a developed time differential quadrature method. The obtained nonlinear vibration responses are analyzed by Huang Hilbert Transform. The instantaneous frequency is used as damage index tool for cracks detection.

[Identification of Candida dubliniensis strains using heat tolerance tests, morphological characteristics and molecular methods].

Science.gov (United States)

Arikan, Sevtap; Darka, Ozge; Hasçelik, Gülşen; Günalp, Ayfer

2003-01-01

Described in 1995, Candida dubliniensis is a novel Candida species closely related to Candida albicans due primarily to its ability to produce germ tube and chlamydospores. Given these phenotypic similarities between the two species, C. dubliniensis cannot be readily distinguished from Candida albicans by routine laboratory work-up. We explored the frequency of isolation of C. dubliniensis among 213 strains previously defined as C. albicans based on their ability to produce germ tube. The test isolates were initially examined for their morphological features on cornmeal tween 80 agar, inability to grow at 45 degrees C, and the biochemical assimilation profile (ID 32C system, bioMerieux, France). Among all, 2 (0.9%) of the isolates were identified as C. dubliniensis based on the production of numerous chlamydospores in chains on cornmeal tween 80 agar and the lack of growth at 45 degrees C. The assimilation profile of these isolates was found to be in accordance with this identification. In an effort to confirm the identification, polymerase chain reaction (PCR) studies were carried out by using the C. dubliniensis specific primer set, DUBF and DUBR. Both of the isolates yielded C. dubliniensis-specific 288 base pair amplification products, confirming the previous identification obtained with the initial screening tests. The isolates were found to be susceptible to fluconazole and itraconazole, and generated amphotericin B minimal inhibitory concentrations of 0.5-1 microgram/ml by NCCLS M27-A2 microdilution method. These data suggest that the isolation rate of C. dubliniensis among our clinical isolates is low. The morphological features on cornmeal tween 80 agar and the lack of ability to grow at 45 degrees C appear as reliable, cheap, and practical screening tests in initial identification of C. dubliniensis among germ tube-producing Candida strains.

Identification system for chemical warfare agents with PGNAA method

International Nuclear Information System (INIS)

Wang Bairong; Yin Guanghua; Yang Zhongpin

2007-01-01

The principle and the experimental commanding of Chemical warfare Agents Identification with PGNAA method are discussed in this paper. The choosing of detector, neutron source and the data processing method are detailed. Finally, a set of experimental instruments composed of Cf-232 and BGO detector is developed based on this theory discussed above. (authors)

[Optimization of measurement methods for a multi-frequency electromagnetic field from mobile phone base station using broadband EMF meter].

Science.gov (United States)

Bieńkowski, Paweł; Cała, Paweł; Zubrzak, Bartłomiej

2015-01-01

This paper presents the characteristics of the mobile phone base station (BS) as an electromagnetic field (EMF) source. The most common system configurations with their construction are described. The parameters of radiated EMF in the context of the access to methods and other parameters of the radio transmission are discussed. Attention was also paid to antennas that are used in this technology. The influence of individual components of a multi-frequency EMF, most commonly found in the BS surroundings, on the resultant EMF strength value indicated by popular broadband EMF meters was analyzed. The examples of metrological characteristics of the most common EMF probes and 2 measurement scenarios of the multisystem base station, with and without microwave relays, are shown. The presented method for measuring the multi-frequency EMF using 2 broadband probes allows for the significant minimization of measurement uncertainty. Equations and formulas that can be used to calculate the actual EMF intensity from multi-frequency sources are shown. They have been verified in the laboratory conditions on a specific standard setup as well as in real conditions in a survey of the existing base station with microwave relays. Presented measurement methodology of multi-frequency EMF from BS with microwave relays, validated both in laboratory and real conditions. It has been proven that the described measurement methodology is the optimal approach to the evaluation of EMF exposure in BS surrounding. Alternative approaches with much greater uncertainty (precaution method) or more complex measuring procedure (sources exclusion method) are also presented). This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

A Systematic Identification Method for Thermodynamic Property Modelling

DEFF Research Database (Denmark)

Ana Perederic, Olivia; Cunico, Larissa; Sarup, Bent

2017-01-01

In this work, a systematic identification method for thermodynamic property modelling is proposed. The aim of the method is to improve the quality of phase equilibria prediction by group contribution based property prediction models. The method is applied to lipid systems where the Original UNIFAC...... model is used. Using the proposed method for estimating the interaction parameters using only VLE data, a better phase equilibria prediction for both VLE and SLE was obtained. The results were validated and compared with the original model performance...

Stimulus variability and the phonetic relevance hypothesis: effects of variability in speaking style, fundamental frequency, and speaking rate on spoken word identification.

Science.gov (United States)

Sommers, Mitchell S; Barcroft, Joe

2006-04-01

Three experiments were conducted to examine the effects of trial-to-trial variations in speaking style, fundamental frequency, and speaking rate on identification of spoken words. In addition, the experiments investigated whether any effects of stimulus variability would be modulated by phonetic confusability (i.e., lexical difficulty). In Experiment 1, trial-to-trial variations in speaking style reduced the overall identification performance compared with conditions containing no speaking-style variability. In addition, the effects of variability were greater for phonetically confusable words than for phonetically distinct words. In Experiment 2, variations in fundamental frequency were found to have no significant effects on spoken word identification and did not interact with lexical difficulty. In Experiment 3, two different methods for varying speaking rate were found to have equivalent negative effects on spoken word recognition and similar interactions with lexical difficulty. Overall, the findings are consistent with a phonetic-relevance hypothesis, in which accommodating sources of acoustic-phonetic variability that affect phonetically relevant properties of speech signals can impair spoken word identification. In contrast, variability in parameters of the speech signal that do not affect phonetically relevant properties are not expected to affect overall identification performance. Implications of these findings for the nature and development of lexical representations are discussed.

Applications of radio frequency identification systems in underground mining

Energy Technology Data Exchange (ETDEWEB)

Knights, P F; Kairouz, J; Daneshmend, L K; Pathak, J [McGill University, Montreal, PQ (Canada). Canadian Centre for Automation and Robotics in Mining

1994-12-31

The paper describes the application of Radio Frequency Identification (RFID) systems in underground hardrock mines. The operating principles and some of the applications of RDIF systems are described. The system operates by the exchange of information between transponder tags and an antenna and controller device. The suitability of RFID systems for process control, inventory control, materials handling, control of access, security, and transportation in underground coal and hardrock mines is discussed. An ore tonnage tracking system is under development that uses RDIF transponder tags to locate vehicles in an underground mine. 6 refs., 4 figs.

Interchange Recognition Method Based on CNN

Directory of Open Access Journals (Sweden)

HE Haiwei

2018-03-01

Full Text Available The identification and classification of interchange structures in OSM data can provide important information for the construction of multi-scale model, navigation and location services, congestion analysis, etc. The traditional method of interchange identification relies on the low-level characteristics of artificial design, and cannot distinguish the complex interchange structure with interference section effectively. In this paper, a new method based on convolutional neural network for identification of the interchange is proposed. The method combines vector data with raster image, and uses neural network to learn the fuzzy characteristics of the interchange, and classifies the complex interchange structure in OSM. Experiments show that this method has strong anti-interference, and has achieved good results in the classification of complex interchange shape, and there is room for further improvement with the expansion of the case base and the optimization of neural network model.

Parameter Identification of Ship Maneuvering Models Using Recursive Least Square Method Based on Support Vector Machines

Directory of Open Access Journals (Sweden)

Man Zhu

2017-03-01

Full Text Available Determination of ship maneuvering models is a tough task of ship maneuverability prediction. Among several prime approaches of estimating ship maneuvering models, system identification combined with the full-scale or free- running model test is preferred. In this contribution, real-time system identification programs using recursive identification method, such as the recursive least square method (RLS, are exerted for on-line identification of ship maneuvering models. However, this method seriously depends on the objects of study and initial values of identified parameters. To overcome this, an intelligent technology, i.e., support vector machines (SVM, is firstly used to estimate initial values of the identified parameters with finite samples. As real measured motion data of the Mariner class ship always involve noise from sensors and external disturbances, the zigzag simulation test data include a substantial quantity of Gaussian white noise. Wavelet method and empirical mode decomposition (EMD are used to filter the data corrupted by noise, respectively. The choice of the sample number for SVM to decide initial values of identified parameters is extensively discussed and analyzed. With de-noised motion data as input-output training samples, parameters of ship maneuvering models are estimated using RLS and SVM-RLS, respectively. The comparison between identification results and true values of parameters demonstrates that both the identified ship maneuvering models from RLS and SVM-RLS have reasonable agreements with simulated motions of the ship, and the increment of the sample for SVM positively affects the identification results. Furthermore, SVM-RLS using data de-noised by EMD shows the highest accuracy and best convergence.

Time-Frequency Distribution of Music based on Sparse Wavelet Packet Representations

DEFF Research Database (Denmark)

Endelt, Line Ørtoft

We introduce a new method for generating time-frequency distributions, which is particularly useful for the analysis of music signals. The method presented here is based on $\\ell1$ sparse representations of music signals in a redundant wavelet packet dictionary. The representations are found using...... the minimization methods basis pursuit and best orthogonal basis. Visualizations of the time-frequency distribution are constructed based on a simplified energy distribution in the wavelet packet decomposition. The time-frequency distributions emphasizes structured musical content, including non-stationary content...

[A accurate identification method for Chinese materia medica--systematic identification of Chinese materia medica].

Science.gov (United States)

Wang, Xue-Yong; Liao, Cai-Li; Liu, Si-Qi; Liu, Chun-Sheng; Shao, Ai-Juan; Huang, Lu-Qi

2013-05-01

This paper put forward a more accurate identification method for identification of Chinese materia medica (CMM), the systematic identification of Chinese materia medica (SICMM) , which might solve difficulties in CMM identification used the ordinary traditional ways. Concepts, mechanisms and methods of SICMM were systematically introduced and possibility was proved by experiments. The establishment of SICMM will solve problems in identification of Chinese materia medica not only in phenotypic characters like the mnorphous, microstructure, chemical constituents, but also further discovery evolution and classification of species, subspecies and population in medical plants. The establishment of SICMM will improve the development of identification of CMM and create a more extensive study space.

Village Building Identification Based on Ensemble Convolutional Neural Networks

Science.gov (United States)

Guo, Zhiling; Chen, Qi; Xu, Yongwei; Shibasaki, Ryosuke; Shao, Xiaowei

2017-01-01

In this study, we present the Ensemble Convolutional Neural Network (ECNN), an elaborate CNN frame formulated based on ensembling state-of-the-art CNN models, to identify village buildings from open high-resolution remote sensing (HRRS) images. First, to optimize and mine the capability of CNN for village mapping and to ensure compatibility with our classification targets, a few state-of-the-art models were carefully optimized and enhanced based on a series of rigorous analyses and evaluations. Second, rather than directly implementing building identification by using these models, we exploited most of their advantages by ensembling their feature extractor parts into a stronger model called ECNN based on the multiscale feature learning method. Finally, the generated ECNN was applied to a pixel-level classification frame to implement object identification. The proposed method can serve as a viable tool for village building identification with high accuracy and efficiency. The experimental results obtained from the test area in Savannakhet province, Laos, prove that the proposed ECNN model significantly outperforms existing methods, improving overall accuracy from 96.64% to 99.26%, and kappa from 0.57 to 0.86. PMID:29084154

Individual feature identification method for nuclear accident emergency decision-making

International Nuclear Information System (INIS)

Chen Yingfeng; Wang Jianlong; Lin Xiaoling; Yang Yongxin; Lu Xincheng

2014-01-01

According to the individual feature identification method and combining with the characteristics of nuclear accident emergency decision-making, the evaluation index system of the nuclear accident emergency decision-making was determined on the basis of investigation and analysis. The effectiveness of the nuclear accident emergency decision-making was evaluated based on the individual standards by solving the individual features of the individual standard identification decisions. The case study shows that the optimization result is reasonable, objective and reliable, and it can provide an effective analysis method and decision-making support for optimization of nuclear accident emergency protective measures. (authors)

Identification method for gas-liquid two-phase flow regime based on singular value decomposition and least square support vector machine

International Nuclear Information System (INIS)

Sun Bin; Zhou Yunlong; Zhao Peng; Guan Yuebo

2007-01-01

Aiming at the non-stationary characteristics of differential pressure fluctuation signals of gas-liquid two-phase flow, and the slow convergence of learning and liability of dropping into local minima for BP neural networks, flow regime identification method based on Singular Value Decomposition (SVD) and Least Square Support Vector Machine (LS-SVM) is presented. First of all, the Empirical Mode Decomposition (EMD) method is used to decompose the differential pressure fluctuation signals of gas-liquid two-phase flow into a number of stationary Intrinsic Mode Functions (IMFs) components from which the initial feature vector matrix is formed. By applying the singular vale decomposition technique to the initial feature vector matrixes, the singular values are obtained. Finally, the singular values serve as the flow regime characteristic vector to be LS-SVM classifier and flow regimes are identified by the output of the classifier. The identification result of four typical flow regimes of air-water two-phase flow in horizontal pipe has shown that this method achieves a higher identification rate. (authors)

Hazard identification based on plant functional modelling

International Nuclear Information System (INIS)

Rasmussen, B.; Whetton, C.

1993-10-01

A major objective of the present work is to provide means for representing a process plant as a socio-technical system, so as to allow hazard identification at a high level. The method includes technical, human and organisational aspects and is intended to be used for plant level hazard identification so as to identify critical areas and the need for further analysis using existing methods. The first part of the method is the preparation of a plant functional model where a set of plant functions link together hardware, software, operations, work organisation and other safety related aspects of the plant. The basic principle of the functional modelling is that any aspect of the plant can be represented by an object (in the sense that this term is used in computer science) based upon an Intent (or goal); associated with each Intent are Methods, by which the Intent is realized, and Constraints, which limit the Intent. The Methods and Constraints can themselves be treated as objects and decomposed into lower-level Intents (hence the procedure is known as functional decomposition) so giving rise to a hierarchical, object-oriented structure. The plant level hazard identification is carried out on the plant functional model using the Concept Hazard Analysis method. In this, the user will be supported by checklists and keywords and the analysis is structured by pre-defined worksheets. The preparation of the plant functional model and the performance of the hazard identification can be carried out manually or with computer support. (au) (4 tabs., 10 ills., 7 refs.)

Designing waveforms for temporal encoding using a frequency sampling method

DEFF Research Database (Denmark)

Gran, Fredrik; Jensen, Jørgen Arendt

2007-01-01

was compared to a linear frequency modulated signal with amplitude tapering, previously used in clinical studies for synthetic transmit aperture imaging. The latter had a relatively flat spectrum which implied that the waveform tried to excite all frequencies including ones with low amplification. The proposed......In this paper a method for designing waveforms for temporal encoding in medical ultrasound imaging is described. The method is based on least squares optimization and is used to design nonlinear frequency modulated signals for synthetic transmit aperture imaging. By using the proposed design method...... waveform, on the other hand, was designed so that only frequencies where the transducer had a large amplification were excited. Hereby, unnecessary heating of the transducer could be avoided and the signal-tonoise ratio could be increased. The experimental ultrasound scanner RASMUS was used to evaluate...

Frequency domain methods applied to forecasting electricity markets

International Nuclear Information System (INIS)

Trapero, Juan R.; Pedregal, Diego J.

2009-01-01

The changes taking place in electricity markets during the last two decades have produced an increased interest in the problem of forecasting, either load demand or prices. Many forecasting methodologies are available in the literature nowadays with mixed conclusions about which method is most convenient. This paper focuses on the modeling of electricity market time series sampled hourly in order to produce short-term (1 to 24 h ahead) forecasts. The main features of the system are that (1) models are of an Unobserved Component class that allow for signal extraction of trend, diurnal, weekly and irregular components; (2) its application is automatic, in the sense that there is no need for human intervention via any sort of identification stage; (3) the models are estimated in the frequency domain; and (4) the robustness of the method makes possible its direct use on both load demand and price time series. The approach is thoroughly tested on the PJM interconnection market and the results improve on classical ARIMA models. (author)

The constitutive compatibility method for identification of material parameters based on full-field measurements

KAUST Repository

Moussawi, Ali

2013-10-01

We revisit here the concept of the constitutive relation error for the identification of elastic material parameters based on image correlation. An additional concept, so called constitutive compatibility of stress, is introduced defining a subspace of the classical space of statically admissible stresses. The key idea is to define stresses as compatible with the observed deformation field through the chosen class of constitutive equation. This makes possible the uncoupling of the identification of stress from the identification of the material parameters. As a result, the global cost of the identification is strongly reduced. This uncoupling also leads to parametrized solutions in cases where the solution is non-unique as demonstrated on 2D numerical examples. © 2013 Elsevier B.V.

Star identification methods, techniques and algorithms

CERN Document Server

Zhang, Guangjun

2017-01-01

This book summarizes the research advances in star identification that the author’s team has made over the past 10 years, systematically introducing the principles of star identification, general methods, key techniques and practicable algorithms. It also offers examples of hardware implementation and performance evaluation for the star identification algorithms. Star identification is the key step for celestial navigation and greatly improves the performance of star sensors, and as such the book include the fundamentals of star sensors and celestial navigation, the processing of the star catalog and star images, star identification using modified triangle algorithms, star identification using star patterns and using neural networks, rapid star tracking using star matching between adjacent frames, as well as implementation hardware and using performance tests for star identification. It is not only valuable as a reference book for star sensor designers and researchers working in pattern recognition and othe...

3D ear identification based on sparse representation.

Directory of Open Access Journals (Sweden)

Lin Zhang

Full Text Available Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm.

A sensitivity function-based conjugate gradient method for optical tomography with the frequency-domain equation of radiative transfer

International Nuclear Information System (INIS)

Kim, Hyun Keol; Charette, Andre

2007-01-01

The Sensitivity Function-based Conjugate Gradient Method (SFCGM) is described. This method is used to solve the inverse problems of function estimation, such as the local maps of absorption and scattering coefficients, as applied to optical tomography for biomedical imaging. A highly scattering, absorbing, non-reflecting, non-emitting medium is considered here and simultaneous reconstructions of absorption and scattering coefficients inside the test medium are achieved with the proposed optimization technique, by using the exit intensity measured at boundary surfaces. The forward problem is solved with a discrete-ordinates finite-difference method on the framework of the frequency-domain full equation of radiative transfer. The modulation frequency is set to 600 MHz and the frequency data, obtained with the source modulation, is used as the input data. The inversion results demonstrate that the SFCGM can retrieve simultaneously the spatial distributions of optical properties inside the medium within a reasonable accuracy, by significantly reducing a cross-talk between inter-parameters. It is also observed that the closer-to-detector objects are better retrieved

Radio Frequency Identification (RFID) technology and patient safety.

Science.gov (United States)

Ajami, Sima; Rajabzadeh, Ahmad

2013-09-01

Radio frequency identification (RFID) systems have been successfully applied in areas of manufacturing, supply chain, agriculture, transportation, healthcare, and services to name a few. However, the different advantages and disadvantages expressed in various studies of the challenges facing the technology of the use of the RFID technology have been met with skepticism by managers of healthcare organizations. The aim of this study was to express and display the role of RFID technology in improving patient safety and increasing the impact of it in healthcare. This study was non-systematical review, which the literature search was conducted with the help of libraries, books, conference proceedings, PubMed databases and also search engines available at Google, Google scholar in which published between 2004 and 2013 during Febuary 2013. We employed the following keywords and their combinations; RFID, healthcare, patient safety, medical errors, and medication errors in the searching areas of title, keywords, abstract, and full text. The preliminary search resulted in 68 articles. After a careful analysis of the content of each paper, a total of 33 papers was selected based on their relevancy. We should integrate RFID with hospital information systems (HIS) and electronic health records (EHRs) and support it by clinical decision support systems (CDSS), it facilitates processes and reduce medical, medication and diagnosis errors.

Genetic Algorithm-Based Identification of Fractional-Order Systems

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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.

Microcantilver-based DNA hybridization sensors for Salmonella identification

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Carlo Ricciardi

2012-02-01

Full Text Available The detection of pathogenic microorganisms in foods remains a challenging since the safety of foodstuffs has to be ensured by the food producing companies. Conventional methods for the detection and identification of bacteria mainly rely on specific microbiological and biochemical identification. Biomolecular methods, are commonly used as a support for traditional techniques, thanks to their high sensitivity, specificity and not excessive costs. However, new methods like biosensors for example, can be an exciting alternative to the more traditional tecniques for the detection of pathogens in food. In this study we report Salmonella enterica serotype Enteritidis DNA detection through a novel class of label-free biosensors: microcantilevers (MCs. In general, MCs can operate as a microbalance and is used to detect the mass of the entities anchored to the cantilever surface using the decrease in the resonant frequency. We use DNA hybridization as model reaction system and for this reason, specific single stranded probe DNA of the pathogen and three different DNA targets (single-stranded complementary DNA, PCR product and serial dilutions of DNA extracted from S. Enteritidis strains were applied. Two protocols were reported in order to allow the probe immobilization on cantilever surface: i MC surface was functionalized with 3-aminopropyltriethoxysilane and glutaraldehyde and an amino-modified DNA probe was used; ii gold-coated sensors and thiolated DNA probes were used in order to generate a covalent bonding (Th-Au. For the first one, measures after hybridization with the PCR product showed related frequency shift 10 times higher than hybridization with complementary probe and detectable signals were obtained at the concentrations of 103 and 106 cfu/mL after hybridization with bacterial DNA. There are currently optimizations of the second protocol, where preliminary results have shown to be more uniform and therefore more precise within each of the

Frequency-Dependent FDTD Algorithm Using Newmark’s Method

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Bing Wei

2014-01-01

Full Text Available According to the characteristics of the polarizability in frequency domain of three common models of dispersive media, the relation between the polarization vector and electric field intensity is converted into a time domain differential equation of second order with the polarization vector by using the conversion from frequency to time domain. Newmark βγ difference method is employed to solve this equation. The electric field intensity to polarizability recursion is derived, and the electric flux to electric field intensity recursion is obtained by constitutive relation. Then FDTD iterative computation in time domain of electric and magnetic field components in dispersive medium is completed. By analyzing the solution stability of the above differential equation using central difference method, it is proved that this method has more advantages in the selection of time step. Theoretical analyses and numerical results demonstrate that this method is a general algorithm and it has advantages of higher accuracy and stability over the algorithms based on central difference method.

Research of Electrical Conductivity Measurement System for Mine Bursting Water Based on Dual Frequency Method

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Zhou Mengran

2016-01-01

Full Text Available This paper presents a double frequency conductivity measurement method for measuring mine bursting water, to solve the capacitance effect of the conductivity sensor itself has the help. The core controller of the system is the single chip microcomputer ATMEGA128. This paper introduces the basic principle of the measurement of the existing problems and the dual frequency measurement method, and then introduces and analyzes the hardware. To test and analyze the collected data, the double frequency method is found to have good stability and accuracy in the measurement of the electrical conductivity of mine inrush water. It is proved that the method and the system design of the hardware circuit can accurately measure the electric conductivity of the mine inrush water source.

Low-frequency Periodic Error Identification and Compensation for Star Tracker Attitude Measurement

Institute of Scientific and Technical Information of China (English)

WANG Jiongqi; XIONG Kai; ZHOU Haiyin

2012-01-01

The low-frequency periodic error of star tracker is one of the most critical problems for high-accuracy satellite attitude determination.In this paper an approach is proposed to identify and compensate the low-frequency periodic error for star tracker in attitude measurement.The analytical expression between the estimated gyro drift and the low-frequency periodic error of star tracker is derived firstly.And then the low-frequency periodic error,which can be expressed by Fourier series,is identified by the frequency spectrum of the estimated gyro drift according to the solution of the first step.Furthermore,the compensated model of the low-frequency periodic error is established based on the identified parameters to improve the attitude determination accuracy.Finally,promising simulated experimental results demonstrate the validity and effectiveness of the proposed method.The periodic error for attitude determination is eliminated basically and the estimation precision is improved greatly.

Adding Personality to Gifted Identification: Relationships among Traditional and Personality-Based Constructs

Science.gov (United States)

Carman, Carol A.

2011-01-01

One of the underutilized tools in gifted identification is personality-based measures. A multiple confirmatory factor analysis was utilized to examine the relationships between traditional identification methods and personality-based measures. The pattern of correlations indicated this model could be measuring two constructs, one related to…

A Method for Estimating BeiDou Inter-frequency Satellite Clock Bias

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LI Haojun

2016-02-01

Full Text Available A new method for estimating the BeiDou inter-frequency satellite clock bias is proposed, considering the shortage of the current methods. The constant and variable parts of the inter-frequency satellite clock bias are considered in the new method. The data from 10 observation stations are processed to validate the new method. The characterizations of the BeiDou inter-frequency satellite clock bias are also analyzed using the computed results. The results of the BeiDou inter-frequency satellite clock bias indicate that it is stable in the short term. The estimated BeiDou inter-frequency satellite clock bias results are molded. The model results show that the 10 parameters of model for each satellite can express the BeiDou inter-frequency satellite clock bias well and the accuracy reaches cm level. When the model parameters of the first day are used to compute the BeiDou inter-frequency satellite clock bias of the second day, the accuracy also reaches cm level. Based on the stability and modeling, a strategy for the BeiDou satellite clock service is presented to provide the reference of our BeiDou.

An Optimal Image-Based Method for Identification of Acoustic Emission (AE) Sources in Plate-Like Structures Using a Lead Zirconium Titanate (PZT) Sensor Array

Science.gov (United States)

Zhou, Li

2018-01-01

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method. PMID:29466310

An Optimal Image-Based Method for Identification of Acoustic Emission (AE) Sources in Plate-Like Structures Using a Lead Zirconium Titanate (PZT) Sensor Array.

Science.gov (United States)

Yan, Gang; Zhou, Li

2018-02-21

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method.

Frequency Analysis of Wing-Rotor System Considering Flexibility in Capsule Based on High-Accurate Method

Science.gov (United States)

Zhang, Xiayang; Zhu, Ming; Zhao, Meijuan; Wu, Zhe

2018-05-01

Based on a typical wing-rotor thrust model on the airship, the dynamic influence of the gyroscopic effects from the tip rotor acting on the overall coupled system has been analyzed. Meanwhile, the flexibility at the capsule boundary has been studied, as well. Hamilton's principle is employed to derive the general governing equations and the numerical Rayleigh-Ritz method is finally chosen in actual frequency computations. A new set of shape functions are put forward and verified which take most of the couplings among dimensions into account. The parameter studies are also conducted to make deep investigations. The results demonstrate that the inherent frequencies are significantly affected by the rotor speed and the flexible capsule condition. When rotor revolves, the modal shapes have reached into complex states and the components of each mode will change with the increment of rotor speed. The flexibility will also greatly reduce the entire frequencies compared with the rigid case. It is also demonstrated that the inherent property will be significantly affected by the mounting geometry, rotor inertia, the structural stiffness, and rotor speed.

Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms.

Science.gov (United States)

Liu, Rensong; Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

2017-01-01

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K -nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance.

Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms

Science.gov (United States)

Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

2017-01-01

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K-nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance. PMID:28874909

Study on The Extended Range Weather Forecast of Low Frequency Signal Based on Period Analysis Method

Science.gov (United States)

Li, X.

2016-12-01

Although many studies have explored the MJO and its application for weather forecasting, low-frequency oscillation has been insufficiently studied for the extend range weather forecasting over middle and high latitudes. In China, low-frequency synoptic map is a useful tool for meteorological operation department to forecast extend range weather. It is therefore necessary to develop objective methods to serve the need for finding low-frequency signal, interpretation and application of this signal in the extend range weather forecasting. In this paper, method of Butterworth band pass filter was applied to get low-frequency height field at 500hPa from 1980 to 2014 by using NCEP/NCAR daily grid data. Then period analysis and optimal subset regression methods were used to process the low frequency data of 150 days before the first forecast day and extend the low frequency signal of 500hPa low-frequency high field to future 30 days in the global from June to August during 2011-2014. Finally, the results were test. The main results are as follows: (1) In general, the fitting effect of low frequency signals of 500hPa low-frequency height field by period analysis in the northern hemisphere was better than that in the southern hemisphere, and was better in the low latitudes than that in the high latitudes. The fitting accuracy gradually reduced with the increase of forecast time length, which tended to be stable during the late forecasting period. (2) The fitting effects over the 6 key regions in China showed that except filtering result over Xinjiang area in the first 10 days and 30 days, filtering results over the other 5 key regions throughout the whole period have passed reliability test with level more than 95%. (3) The center and scope of low and high low frequency systems can be fitted well by using the methods mentioned above, which is consist with the corresponding use of the low-frequency synoptic map for the prediction of the extended period. Application of the

Analysis of low-dimensional radio-frequency impedance-based cardio-synchronous waveforms for biometric authentication.

Science.gov (United States)

Venugopalan, Shreyas; Savvides, Marios; Griofa, Marc O; Cohen, Ken

2014-08-01

Over the past two decades, there have been a lot of advances in the field of pattern analyses for biomedical signals, which have helped in both medical diagnoses and in furthering our understanding of the human body. A relatively recent area of interest is the utility of biomedical signals in the field of biometrics, i.e., for user identification. Seminal work in this domain has already been done using electrocardiograph (ECG) signals. In this paper, we discuss our ongoing work in using a relatively recent modality of biomedical signals-a cardio-synchronous waveform measured using a Radio-Frequency Impedance-Interrogation (RFII) device for the purpose of user identification. Compared to an ECG setup, this device is noninvasive and measurements can be obtained easily and quickly. Here, we discuss the feasibility of reducing the dimensions of these signals by projecting onto various subspaces while still preserving interuser discriminating information. We compare the classification performance using classical dimensionality reduction methods such as principal component analysis (PCA), independent component analysis (ICA), random projections, with more recent techniques such as K-SVD-based dictionary learning. We also report the reconstruction accuracies in these subspaces. Our results show that the dimensionality of the measured signals can be reduced by 60 fold while maintaining high user identification rates.

A identification system for chemical warfare agents with PGNAA method

International Nuclear Information System (INIS)

Wang Bairong; Yin Guanghua; Yang Zhongping

2006-01-01

The principle and the experimental commanding of Chemical warfare Agents Identification with PGNAA method are discussed in this paper. The choosing of Detector, neutron source and the data processing method are detailed. Finally, a set of experimental instruments composed of Cf-232 and BGO detector is developed based on the theory discussed above. (authors)

Increased situation awareness in major incidents-radio frequency identification (RFID) technique: a promising tool.

Science.gov (United States)

Jokela, Jorma; Rådestad, Monica; Gryth, Dan; Nilsson, Helené; Rüter, Anders; Svensson, Leif; Harkke, Ville; Luoto, Markku; Castrén, Maaret

2012-02-01

In mass-casualty situations, communications and information management to improve situational awareness is a major challenge for responders. In this study, the feasibility of a prototype system that utilizes commercially available, low-cost components, including Radio Frequency Identification (RFID) and mobile phone technology, was tested in two simulated mass-casualty incidents. The feasibility and the direct benefits of the system were evaluated in two simulated mass-casualty situations: one in Finland involving a passenger ship accident resulting in multiple drowning/hypothermia patients, and another at a major airport in Sweden using an aircraft crash scenario. Both simulations involved multiple agencies and functioned as test settings for comparing the disaster management's situational awareness with and without using the RFID-based system. Triage documentation was done using both an RFID-based system, which automatically sent the data to the Medical Command, and a traditional method using paper triage tags. The situational awareness was measured by comparing the availability of up-to date information at different points in the care chain using both systems. Information regarding the numbers and status or triage classification of the casualties was available approximately one hour earlier using the RFID system compared to the data obtained using the traditional method. The tested prototype system was quick, stable, and easy to use, and proved to work seamlessly even in harsh field conditions. It surpassed the paper-based system in all respects except simplicity of use. It also improved the general view of the mass-casualty situations, and enhanced medical emergency readiness in a multi-organizational medical setting. The tested technology is feasible in a mass-casualty incident; further development and testing should take place.

Identification techniques for phenomenological models of hysteresis based on the conjugate gradient method

International Nuclear Information System (INIS)

Andrei, Petru; Oniciuc, Liviu; Stancu, Alexandru; Stoleriu, Laurentiu

2007-01-01

An identification technique for the parameters of phenomenological models of hysteresis is presented. The basic idea of our technique is to set up a system of equations for the parameters of the model as a function of known quantities on the major or minor hysteresis loops (e.g. coercive force, susceptibilities at various points, remanence), or other magnetization curves. This system of equations can be either over or underspecified and is solved by using the conjugate gradient method. Numerical results related to the identification of parameters in the Energetic, Jiles-Atherton, and Preisach models are presented

Tokamak plasma shape identification based on the boundary integral equations

International Nuclear Information System (INIS)

Kurihara, Kenichi; Kimura, Toyoaki

1992-05-01

A necessary condition for tokamak plasma shape identification is discussed and a new identification method is proposed in this article. This method is based on the boundary integral equations governing a vacuum region around a plasma with only the measurement of either magnetic fluxes or magnetic flux intensities. It can identify various plasmas with low to high ellipticities with the precision determined by the number of the magnetic sensors. This method is applicable to real-time control and visualization using a 'table-look-up' procedure. (author)

Fuel number identification method and device therefor

International Nuclear Information System (INIS)

Doi, Takami; Seno, Makoto; Tanaka, Keiji

1998-01-01

The present invention provides a method of and a device for automatically identifying the number on the upper surface of a fuel of a fuel assembly in a PWR type reactor. Namely, the number on the upper surface of the fuel assembly of the PWR is not arranged in a row, but indent letters are dispersed to predetermined positions of the surface to be indented. Accordingly, the identification of letters is difficult. In the present invention, the letters are identified by the following procedures. Procedure (1): the letters are detected while having a corner portion of the upper surface of a fuel assembly where the number is indented as characteristic points. A procedure (2): a letter region is determined to a relative position based on the characteristic points while determining indent letters having the same direction as one group. A procedure (3): a letter identification treatment is applied to the letter images in the above-mentioned letter region to identify them. A neural network is used for the letter identification treatment. (N.H.)

Identification of the corporate values of an enterprise: theory, approaches, methodic

Directory of Open Access Journals (Sweden)

Kozlov Vladimir Aleksandrovich

2015-07-01

Full Text Available This article focuses on research and composition of the instrument to identify the corporate values of the enterprise and practical activities to support them. The first part based on theoretical evidence of essence and correlation between notions of ‘Corporate culture’ and ‘Corporate values’. The method of corporate values identification, based on indirect approach, is proposed and the examples are provided. The results of implemented project for corporate values identification at industrial enterprise are presented. For further support the tasks and activities for corporate values management are proposed.

Weak Defect Identification for Centrifugal Compressor Blade Crack Based on Pressure Sensors and Genetic Algorithm.

Science.gov (United States)

Li, Hongkun; He, Changbo; Malekian, Reza; Li, Zhixiong

2018-04-19

The Centrifugal compressor is a piece of key equipment for petrochemical factories. As the core component of a compressor, the blades suffer periodic vibration and flow induced excitation mechanism, which will lead to the occurrence of crack defect. Moreover, the induced blade defect usually has a serious impact on the normal operation of compressors and the safety of operators. Therefore, an effective blade crack identification method is particularly important for the reliable operation of compressors. Conventional non-destructive testing and evaluation (NDT&E) methods can detect the blade defect effectively, however, the compressors should shut down during the testing process which is time-consuming and costly. In addition, it can be known these methods are not suitable for the long-term on-line condition monitoring and cannot identify the blade defect in time. Therefore, the effective on-line condition monitoring and weak defect identification method should be further studied and proposed. Considering the blade vibration information is difficult to measure directly, pressure sensors mounted on the casing are used to sample airflow pressure pulsation signal on-line near the rotating impeller for the purpose of monitoring the blade condition indirectly in this paper. A big problem is that the blade abnormal vibration amplitude induced by the crack is always small and this feature information will be much weaker in the pressure signal. Therefore, it is usually difficult to identify blade defect characteristic frequency embedded in pressure pulsation signal by general signal processing methods due to the weakness of the feature information and the interference of strong noise. In this paper, continuous wavelet transform (CWT) is used to pre-process the sampled signal first. Then, the method of bistable stochastic resonance (SR) based on Woods-Saxon and Gaussian (WSG) potential is applied to enhance the weak characteristic frequency contained in the pressure

Development of corrosion condition sensing and monitoring system using radio-frequency identification devices (RFID) : progress report 2

Energy Technology Data Exchange (ETDEWEB)

Gu, G.P.; Li, J.; Liu, P.; Bibby, D.; Zheng, W.; Lo, J. [Natural Resources Canada, Ottawa, ON (Canada). CANMET Materials Technology Laboratory

2008-12-15

The development of a corrosion severity monitoring system that used radio-frequency identification device (RIFD) technology was discussed. A corrosion monitoring sensor was integrated with a tag modified to partially block the radio frequency signal. The metallic coating caused a frequency shift of the device's reader antenna in order to allow for the accurate characterization of metal coatings. Communications between the tag and the reader were re-established as the corrosion process gradually deteriorated the coating. The method was tested experimentally with 3 RFID systems using both active and passive tags were assembled. A passive tag was covered in aluminum foil. Results of the experiment showed that the metallic coating interfered with RFID signals. A cold-spray technology was used to coat tags with metal alloys. The surface morphology of the coatings was tested to determine optimum coating parameters. Further studies are being conducted to develop software for the technology. 4 refs., 11 figs.

Frequency-Wavenumber (FK)-Based Data Selection in High-Frequency Passive Surface Wave Survey

Science.gov (United States)

Cheng, Feng; Xia, Jianghai; Xu, Zongbo; Hu, Yue; Mi, Binbin

2018-04-01

Passive surface wave methods have gained much attention from geophysical and civil engineering communities because of the limited application of traditional seismic surveys in highly populated urban areas. Considering that they can provide high-frequency phase velocity information up to several tens of Hz, the active surface wave survey would be omitted and the amount of field work could be dramatically reduced. However, the measured dispersion energy image in the passive surface wave survey would usually be polluted by a type of "crossed" artifacts at high frequencies. It is common in the bidirectional noise distribution case with a linear receiver array deployed along roads or railways. We review several frequently used passive surface wave methods and derive the underlying physics for the existence of the "crossed" artifacts. We prove that the "crossed" artifacts would cross the true surface wave energy at fixed points in the f-v domain and propose a FK-based data selection technique to attenuate the artifacts in order to retrieve the high-frequency information. Numerical tests further demonstrate the existence of the "crossed" artifacts and indicate that the well-known wave field separation method, FK filter, does not work for the selection of directional noise data. Real-world applications manifest the feasibility of the proposed FK-based technique to improve passive surface wave methods by a priori data selection. Finally, we discuss the applicability of our approach.

Frequency-Wavenumber (FK)-Based Data Selection in High-Frequency Passive Surface Wave Survey

Science.gov (United States)

Cheng, Feng; Xia, Jianghai; Xu, Zongbo; Hu, Yue; Mi, Binbin

2018-07-01

Passive surface wave methods have gained much attention from geophysical and civil engineering communities because of the limited application of traditional seismic surveys in highly populated urban areas. Considering that they can provide high-frequency phase velocity information up to several tens of Hz, the active surface wave survey would be omitted and the amount of field work could be dramatically reduced. However, the measured dispersion energy image in the passive surface wave survey would usually be polluted by a type of "crossed" artifacts at high frequencies. It is common in the bidirectional noise distribution case with a linear receiver array deployed along roads or railways. We review several frequently used passive surface wave methods and derive the underlying physics for the existence of the "crossed" artifacts. We prove that the "crossed" artifacts would cross the true surface wave energy at fixed points in the f- v domain and propose a FK-based data selection technique to attenuate the artifacts in order to retrieve the high-frequency information. Numerical tests further demonstrate the existence of the "crossed" artifacts and indicate that the well-known wave field separation method, FK filter, does not work for the selection of directional noise data. Real-world applications manifest the feasibility of the proposed FK-based technique to improve passive surface wave methods by a priori data selection. Finally, we discuss the applicability of our approach.

Evaluating current automatic de-identification methods with Veteran’s health administration clinical documents

Directory of Open Access Journals (Sweden)

Ferrández Oscar

2012-07-01

Full Text Available Abstract Background The increased use and adoption of Electronic Health Records (EHR causes a tremendous growth in digital information useful for clinicians, researchers and many other operational purposes. However, this information is rich in Protected Health Information (PHI, which severely restricts its access and possible uses. A number of investigators have developed methods for automatically de-identifying EHR documents by removing PHI, as specified in the Health Insurance Portability and Accountability Act “Safe Harbor” method. This study focuses on the evaluation of existing automated text de-identification methods and tools, as applied to Veterans Health Administration (VHA clinical documents, to assess which methods perform better with each category of PHI found in our clinical notes; and when new methods are needed to improve performance. Methods We installed and evaluated five text de-identification systems “out-of-the-box” using a corpus of VHA clinical documents. The systems based on machine learning methods were trained with the 2006 i2b2 de-identification corpora and evaluated with our VHA corpus, and also evaluated with a ten-fold cross-validation experiment using our VHA corpus. We counted exact, partial, and fully contained matches with reference annotations, considering each PHI type separately, or only one unique ‘PHI’ category. Performance of the systems was assessed using recall (equivalent to sensitivity and precision (equivalent to positive predictive value metrics, as well as the F2-measure. Results Overall, systems based on rules and pattern matching achieved better recall, and precision was always better with systems based on machine learning approaches. The highest “out-of-the-box” F2-measure was 67% for partial matches; the best precision and recall were 95% and 78%, respectively. Finally, the ten-fold cross validation experiment allowed for an increase of the F2-measure to 79% with partial matches

A touch probe method of operating an implantable RFID tag for orthopedic implant identification.

Science.gov (United States)

Liu, Xiaoyu; Berger, J Lee; Ogirala, Ajay; Mickle, Marlin H

2013-06-01

The major problem in operating an implantable radio-frequency identification (RFID) tag embedded on an orthopedic implant is low efficiency because of metallic interference. To improve the efficiency, this paper proposes a method of operating an implantable passive RFID tag using a touch probe at 13.56 MHz. This technology relies on the electric field interaction between two pairs of electrodes, one being a part of the touch probe placed on the surface of tissue and the other being a part of the tag installed under the tissue. Compared with using a conventional RFID antenna such as a loop antenna, this method has a better performance in the near field operation range to reduce interference with the orthopedic implant. Properly matching the touch probe and the tag to the tissue and the implant reduces signal attenuation and increases the overall system efficiency. The experiments have shown that this method has a great performance in the near field transcutaneous operation and can be used for orthopedic implant identification.

Identification of Nonlinear Dynamic Systems Possessing Some Non-linearities

Directory of Open Access Journals (Sweden)

Y. N. Pavlov

2015-01-01

Full Text Available The subject of this work is the problem of identification of nonlinear dynamic systems based on the experimental data obtained by applying test signals to the system. The goal is to determinate coefficients of differential equations of systems by experimental frequency hodographs and separate similar, but different, in essence, forces: dissipative forces with the square of the first derivative in the motion equations and dissipative force from the action of dry friction. There was a proposal to use the harmonic linearization method to approximate each of the nonlinearity of "quadratic friction" and "dry friction" by linear friction with the appropriate harmonic linearization coefficient.Assume that a frequency transfer function of the identified system has a known form. Assume as well that there are disturbances while obtaining frequency characteristics of the realworld system. As a result, the points of experimentally obtained hodograph move randomly. Searching for solution of the identification problem was in the hodograph class, specified by the system model, which has the form of the frequency transfer function the same as the form of the frequency transfer function of the system identified. Minimizing a proximity criterion (measure of the experimentally obtained system hodograph and the system hodograph model for all the experimental points described and previously published by one of the authors allowed searching for the unknown coefficients of the frequenc ransfer function of the system model. The paper shows the possibility to identify a nonlinear dynamic system with multiple nonlinearities, obtained on the experimental samples of the frequency system hodograph. The proposed algorithm allows to select the nonlinearity of the type "quadratic friction" and "dry friction", i.e. also in the case where the nonlinearity is dependent on the same dynamic parameter, in particular, on the derivative of the system output value. For the dynamic

Quantitative electromechanical impedance method for nondestructive testing based on a piezoelectric bimorph cantilever

International Nuclear Information System (INIS)

Fu, Ji; Tan, Chi; Li, Faxin

2015-01-01

The electromechanical impedance (EMI) method, which holds great promise in structural health monitoring (SHM), is usually treated as a qualitative method. In this work, we proposed a quantitative EMI method based on a piezoelectric bimorph cantilever using the sample’s local contact stiffness (LCS) as the identification parameter for nondestructive testing (NDT). Firstly, the equivalent circuit of the contact vibration system was established and the analytical relationship between the cantilever’s contact resonance frequency and the LCS was obtained. As the LCS is sensitive to typical defects such as voids and delamination, the proposed EMI method can then be used for NDT. To verify the equivalent circuit model, two piezoelectric bimorph cantilevers were fabricated and their free resonance frequencies were measured and compared with theoretical predictions. It was found that the stiff cantilever’s EMI can be well predicted by the equivalent circuit model while the soft cantilever’s cannot. Then, both cantilevers were assembled into a homemade NDT system using a three-axis motorized stage for LCS scanning. Testing results on a specimen with a prefabricated defect showed that the defect could be clearly reproduced in the LCS image, indicating the validity of the quantitative EMI method for NDT. It was found that the single-frequency mode of the EMI method can also be used for NDT, which is faster but not quantitative. Finally, several issues relating to the practical application of the NDT method were discussed. The proposed EMI-based NDT method offers a simple and rapid solution for damage evaluation in engineering structures and may also shed some light on EMI-based SHM. (paper)

Rydberg-atom based radio-frequency electrometry using frequency modulation spectroscopy in room temperature vapor cells.

Science.gov (United States)

Kumar, Santosh; Fan, Haoquan; Kübler, Harald; Jahangiri, Akbar J; Shaffer, James P

2017-04-17

Rydberg atom-based electrometry enables traceable electric field measurements with high sensitivity over a large frequency range, from gigahertz to terahertz. Such measurements are particularly useful for the calibration of radio frequency and terahertz devices, as well as other applications like near field imaging of electric fields. We utilize frequency modulated spectroscopy with active control of residual amplitude modulation to improve the signal to noise ratio of the optical readout of Rydberg atom-based radio frequency electrometry. Matched filtering of the signal is also implemented. Although we have reached similarly, high sensitivity with other read-out methods, frequency modulated spectroscopy is advantageous because it is well-suited for building a compact, portable sensor. In the current experiment, ∼3 µV cm-1 Hz-1/2 sensitivity is achieved and is found to be photon shot noise limited.

Model reduction and frequency residuals for a robust estimation of nonlinearities in subspace identification

Science.gov (United States)

De Filippis, G.; Noël, J. P.; Kerschen, G.; Soria, L.; Stephan, C.

2017-09-01

The introduction of the frequency-domain nonlinear subspace identification (FNSI) method in 2013 constitutes one in a series of recent attempts toward developing a realistic, first-generation framework applicable to complex structures. If this method showed promising capabilities when applied to academic structures, it is still confronted with a number of limitations which needs to be addressed. In particular, the removal of nonphysical poles in the identified nonlinear models is a distinct challenge. In the present paper, it is proposed as a first contribution to operate directly on the identified state-space matrices to carry out spurious pole removal. A modal-space decomposition of the state and output matrices is examined to discriminate genuine from numerical poles, prior to estimating the extended input and feedthrough matrices. The final state-space model thus contains physical information only and naturally leads to nonlinear coefficients free of spurious variations. Besides spurious variations due to nonphysical poles, vibration modes lying outside the frequency band of interest may also produce drifts of the nonlinear coefficients. The second contribution of the paper is to include residual terms, accounting for the existence of these modes. The proposed improved FNSI methodology is validated numerically and experimentally using a full-scale structure, the Morane-Saulnier Paris aircraft.

A DTI-based model for TMS using the independent impedance method with frequency-dependent tissue parameters

Science.gov (United States)

De Geeter, N.; Crevecoeur, G.; Dupré, L.; Van Hecke, W.; Leemans, A.

2012-04-01

Accurate simulations on detailed realistic head models are necessary to gain a better understanding of the response to transcranial magnetic stimulation (TMS). Hitherto, head models with simplified geometries and constant isotropic material properties are often used, whereas some biological tissues have anisotropic characteristics which vary naturally with frequency. Moreover, most computational methods do not take the tissue permittivity into account. Therefore, we calculate the electromagnetic behaviour due to TMS in a head model with realistic geometry and where realistic dispersive anisotropic tissue properties are incorporated, based on T1-weighted and diffusion-weighted magnetic resonance images. This paper studies the impact of tissue anisotropy, permittivity and frequency dependence, using the anisotropic independent impedance method. The results show that anisotropy yields differences up to 32% and 19% of the maximum induced currents and electric field, respectively. Neglecting the permittivity values leads to a decrease of about 72% and 24% of the maximum currents and field, respectively. Implementing the dispersive effects of biological tissues results in a difference of 6% of the maximum currents. The cerebral voxels show limited sensitivity of the induced electric field to changes in conductivity and permittivity, whereas the field varies approximately linearly with frequency. These findings illustrate the importance of including each of the above parameters in the model and confirm the need for accuracy in the applied patient-specific method, which can be used in computer-assisted TMS.

Dynamic RCS Simulation of a Missile Target Group Based on the High-frequency Asymptotic Method

Directory of Open Access Journals (Sweden)

Zhao Tao

2014-04-01

Full Text Available To simulate dynamic Radar Cross Section (RCS of missile target group, an efficient RCS prediction approach is proposed based on the high-frequency asymptotic theory. The minimal energy trajectory and coordinate transformation is used to get trajectories of the missile, decoys and roll booster, and establish the dynamic scene for the separate procedure of the target group, and the dynamic RCS including specular reflection, edge diffraction and multi-reflection from the target group are obtained by Physical Optics (PO, Equivalent Edge Currents (EEC and Shooting-and-Bouncing Ray (SBR methods. Compared with the dynamic RCS result with the common interpolation method, the proposed method is consistent with the common method when the targets in the scene are far away from each other and each target is not sheltered by others in the incident direction. When the target group is densely distributed and the shelter effect can not be neglected, the interpolation method is extremely difficult to realize, whereas the proposed method is successful.

RareVar: A Framework for Detecting Low-Frequency Single-Nucleotide Variants.

Science.gov (United States)

Hao, Yangyang; Xuei, Xiaoling; Li, Lang; Nakshatri, Harikrishna; Edenberg, Howard J; Liu, Yunlong

2017-07-01

Accurate identification of low-frequency somatic point mutations in tumor samples has important clinical utilities. Although high-throughput sequencing technology enables capturing such variants while sequencing primary tumor samples, our ability for accurate detection is compromised when the variant frequency is close to the sequencer error rate. Most current experimental and bioinformatic strategies target mutations with ≥5% allele frequency, which limits our ability to understand the cancer etiology and tumor evolution. We present an experimental and computational modeling framework, RareVar, to reliably identify low-frequency single-nucleotide variants from high-throughput sequencing data under standard experimental protocols. RareVar protocol includes a benchmark design by pooling DNAs from already sequenced individuals at various concentrations to target variants at desired frequencies, 0.5%-3% in our case. By applying a generalized, linear model-based, position-specific error model, followed by machine-learning-based variant calibration, our approach outperforms existing methods. Our method can be applied on most capture and sequencing platforms without modifying the experimental protocol.

Vortex Tube Modeling Using the System Identification Method

Energy Technology Data Exchange (ETDEWEB)

Han, Jaeyoung; Jeong, Jiwoong; Yu, Sangseok [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Im, Seokyeon [Tongmyong Univ., Busan (Korea, Republic of)

2017-05-15

In this study, vortex tube system model is developed to predict the temperature of the hot and the cold sides. The vortex tube model is developed based on the system identification method, and the model utilized in this work to design the vortex tube is ARX type (Auto-Regressive with eXtra inputs). The derived polynomial model is validated against experimental data to verify the overall model accuracy. It is also shown that the derived model passes the stability test. It is confirmed that the derived model closely mimics the physical behavior of the vortex tube from both the static and dynamic numerical experiments by changing the angles of the low-temperature side throttle valve, clearly showing temperature separation. These results imply that the system identification based modeling can be a promising approach for the prediction of complex physical systems, including the vortex tube.

Neural network based electron identification in the ZEUS calorimeter

International Nuclear Information System (INIS)

Abramowicz, H.; Caldwell, A.; Sinkus, R.

1995-01-01

We present an electron identification algorithm based on a neural network approach applied to the ZEUS uranium calorimeter. The study is motivated by the need to select deep inelastic, neutral current, electron proton interactions characterized by the presence of a scattered electron in the final state. The performance of the algorithm is compared to an electron identification method based on a classical probabilistic approach. By means of a principle component analysis the improvement in the performance is traced back to the number of variables used in the neural network approach. (orig.)

Multi-frequency exciting and spectrogram-based ECT method

CERN Document Server

Chady, T

2000-01-01

The purpose of this paper is to experimentally demonstrate advantages of a multi-frequency ECT system. In this system, a precise crack imaging was achieved by using spectrograms obtained from an eddy-current probe multi-frequency response. A complex signal containing selected sinusoidal components was used as an excitation. The results of measurements for various test specimens are presented.

Applications of radio frequency identification systems in the mining industry

Energy Technology Data Exchange (ETDEWEB)

Hind, D J [Davis Derby Ltd., Derby (United Kingdom)

1995-07-01

Radio Frequency Identification Systems (RFID) are one of the automatic data capture technologies taking over from bar codes and magnetic swipe cards in many applications involving automatic hands free operation in arduous environments. RFID systems are based on the use of miniature radio transponders carrying encoded electronic data that is used to uniquely identify the identity of transponders. This paper reviews the types of system available and compares the various techniques involved in the different systems. The various types of transponder are described including the latest state of the art passive read/write high performance types. A review of the history of RFID systems in the mining industry is also given in the paper. The problems involved in designing and certifying a system for use in hazardous areas are also described, with particular reference to the problems of inadvertent detonator ignition by radio systems. Applications of RFID systems in the mining industry are described in considerable detail, covering applications both on the surface and underground. 1 ref., 12 figs., 1 tab.

Identification of natural images and computer-generated graphics based on statistical and textural features.

Science.gov (United States)

Peng, Fei; Li, Jiao-ting; Long, Min

2015-03-01

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

Rapid identification of ascomycetous yeasts from clinical specimens by a molecular method based on flow cytometry and comparison with identifications from phenotypic assays.

Science.gov (United States)

Page, Brent T; Shields, Christine E; Merz, William G; Kurtzman, Cletus P

2006-09-01

This study was designed to compare the identification of ascomycetous yeasts recovered from clinical specimens by using phenotypic assays (PA) and a molecular flow cytometric (FC) method. Large-subunit rRNA domains 1 and 2 (D1/D2) gene sequence analysis was also performed and served as the reference for correct strain identification. A panel of 88 clinical isolates was tested that included representatives of nine commonly encountered species and six infrequently encountered species. The PA included germ tube production, fermentation of seven carbohydrates, morphology on corn meal agar, urease and phenoloxidase activities, and carbohydrate assimilation tests when needed. The FC method (Luminex) employed species-specific oligonucleotides attached to polystyrene beads, which were hybridized with D1/D2 amplicons from the unidentified isolates. The PA identified 81 of 88 strains correctly but misidentified 4 of Candida dubliniensis, 1 of C. bovina, 1 of C. palmioleophila, and 1 of C. bracarensis. The FC method correctly identified 79 of 88 strains and did not misidentify any isolate but did not identify nine isolates because oligonucleotide probes were not available in the current library. The FC assay takes approximately 5 h, whereas the PA takes from 2 h to 5 days for identification. In conclusion, PA did well with the commonly encountered species, was not accurate for uncommon species, and takes significantly longer than the FC method. These data strongly support the potential of FC technology for rapid and accurate identification of medically important yeasts. With the introduction of new antifungals, rapid, accurate identification of pathogenic yeasts is more important than ever for guiding antifungal chemotherapy.

High-resolution mid-IR spectrometer based on frequency upconversion

DEFF Research Database (Denmark)

Hu, Qi; Dam, Jeppe Seidelin; Pedersen, Christian

2012-01-01

We demonstrate a novel approach for high-resolution spectroscopy based on frequency upconversion and postfiltering by means of a scanning Fabryx2013;Perot interferometer. The system is based on sum-frequency mixing, shifting the spectral content from the mid-infrared to the near-visible region al......-frequency 1064xA0;nm laser. We investigate water vapor emission lines from a butane burner and compare the measured results to model data. The presented method we suggest to be used for real-time monitoring of specific gas lines and reference signals....

Communications device identification methods, communications methods, wireless communications readers, wireless communications systems, and articles of manufacture

Science.gov (United States)

Steele, Kerry D [Kennewick, WA; Anderson, Gordon A [Benton City, WA; Gilbert, Ronald W [Morgan Hill, CA

2011-02-01

Communications device identification methods, communications methods, wireless communications readers, wireless communications systems, and articles of manufacture are described. In one aspect, a communications device identification method includes providing identification information regarding a group of wireless identification devices within a wireless communications range of a reader, using the provided identification information, selecting one of a plurality of different search procedures for identifying unidentified ones of the wireless identification devices within the wireless communications range, and identifying at least some of the unidentified ones of the wireless identification devices using the selected one of the search procedures.

Multiple independent identification decisions: a method of calibrating eyewitness identifications.

Science.gov (United States)

Pryke, Sean; Lindsay, R C L; Dysart, Jennifer E; Dupuis, Paul

2004-02-01

Two experiments (N = 147 and N = 90) explored the use of multiple independent lineups to identify a target seen live. In Experiment 1, simultaneous face, body, and sequential voice lineups were used. In Experiment 2, sequential face, body, voice, and clothing lineups were used. Both studies demonstrated that multiple identifications (by the same witness) from independent lineups of different features are highly diagnostic of suspect guilt (G. L. Wells & R. C. L. Lindsay, 1980). The number of suspect and foil selections from multiple independent lineups provides a powerful method of calibrating the accuracy of eyewitness identification. Implications for use of current methods are discussed. ((c) 2004 APA, all rights reserved)

Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

Directory of Open Access Journals (Sweden)

Xiaoming Xi

2013-07-01

Full Text Available Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT, which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

[Identification of Dens Draconis and Os Draconis by XRD method].

Science.gov (United States)

Chen, Guang-Yun; Wu, Qi-Nan; Shen, Bei; Chen, Rong

2012-04-01

To establish an XRD method for evaluating the quality of Os Draconis and Dens Draconis and applying in judgement of the counterfeit. Dens Draconis, Os Draconis and the counterfeit of Os Draconis were analyzed by XRD. Their diffraction patterns were clustered analysis and evaluated their similarity degree. Established the analytical method of Dens Draconis and Os Draconis basing the features fingerprint information of the 10 common peaks by XRD pattern. Obtained the XRD pattern of the counterfeit of Os Draconis. The similarity degree of separate sources of Dens Draconis was high,while the similarity degree of separate sources of Os Draconis was significant different from each other. This method can be used for identification and evaluation of Os Draconis and Dens Draconis. It also can be used for identification the counterfeit of Os Draconis effectively.

Mastering system identification in 100 exercises

CERN Document Server

Schoukens, J; Rolain, Yves

2012-01-01

"This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring complex theoretical knowledge. The contents encompass state-of-the-art system identification methods, with both time and frequency domain system identification methods covered, including the pros and cons of each. Each chapter features MATLAB exercises, discussions of the exercises, accompanying MATLAB downloads, and larger projects that serve as potential assignments in this learn-by-doing resource"--

Systems and methods for process and user driven dynamic voltage and frequency scaling

Science.gov (United States)

Mallik, Arindam [Evanston, IL; Lin, Bin [Hillsboro, OR; Memik, Gokhan [Evanston, IL; Dinda, Peter [Evanston, IL; Dick, Robert [Evanston, IL

2011-03-22

Certain embodiments of the present invention provide a method for power management including determining at least one of an operating frequency and an operating voltage for a processor and configuring the processor based on the determined at least one of the operating frequency and the operating voltage. The operating frequency is determined based at least in part on direct user input. The operating voltage is determined based at least in part on an individual profile for processor.

Medical equipment management through the use of radio frequency identification (RFID)

OpenAIRE

Sanchez, Joaquin A.; Nixon, Richard A.; Chávez, Sergio

2004-01-01

MBA Professional Report Approved for public release, distribution is unlimited The purpose of this MBA project is to identify the potential value of Radio Frequency Identification (RFID) use in the management of medical equipment at Naval Medical Center San Diego (NMCSD). In doing so, our project seeks to derive potential benefits through the use of RFID technology by comparing a group of medical equipment items that are tracked within NMCSD. The project includes a discussion of additio...

Response-only method for damage detection of beam-like structures using high accuracy frequencies with auxiliary mass spatial probing

Science.gov (United States)

Zhong, Shuncong; Oyadiji, S. Olutunde; Ding, Kang

2008-04-01

This paper proposes a new approach based on auxiliary mass spatial probing using spectral centre correction method (SCCM), to provide a simple solution for damage detection by just using the response time history of beam-like structures. The natural frequencies of a damaged beam with a traversing auxiliary mass change due to change in the inertia of the beam as the auxiliary mass is traversed along the beam, as well as the point-to-point variations in the flexibility of the beam. Therefore the auxiliary mass can enhance the effects of the crack on the dynamics of the beam and, therefore, facilitate the identification and location of damage in the beam. That is, the auxiliary mass can be used to probe the dynamic characteristic of the beam by traversing the mass from one end of the beam to the other. However, it is impossible to obtain accurate modal frequencies by the direct operation of the fast Fourier transform (FFT) of the response data of the structure because the frequency spectrum can be only calculated from limited sampled time data which results in the well-known leakage effect. SCCM is identical to the energy centrobaric correction method (ECCM) which is a practical and effective method used in rotating mechanical fault diagnosis and which resolves the shortcoming of FFT and can provide high accuracy estimate of frequency, amplitude and phase. In the present work, the modal responses of damaged simply supported beams with auxiliary mass are computed using the finite element method (FEM). The graphical plots of the natural frequencies calculated by SCCM versus axial location of auxiliary mass are obtained. However, it is difficult to locate the crack directly from the curve of natural frequencies. A simple and fast method, the derivatives of natural frequency curve, is proposed in the paper which can provide crack information for damage detection of beam-like structures. The efficiency and practicability of the proposed method is illustrated via numerical

A Novel Frequency Measurement Method Suitable for a Large Frequency Ratio Condition

Institute of Scientific and Technical Information of China (English)

ZHOU Wei; XUAN Zong-Qiang; YU Jian-Guo; WANG Hai; ZHOU Hui; LI Zhi-Qi

2004-01-01

@@ As for the obstacles to direct comparison between superhigh and lower frequencies, we accomplish the accurate comparison between low and microwave frequencies with the 105 ratios of the operating frequencies on the basis of phase comparison between the signals whose frequencies are related by an arbitrary integer. This method is simple and accurate, and will be widely used as a special frequency comparison approach.

Improving multiple-point-based a priori models for inverse problems by combining Sequential Simulation with the Frequency Matching Method

DEFF Research Database (Denmark)

Cordua, Knud Skou; Hansen, Thomas Mejer; Lange, Katrine

In order to move beyond simplified covariance based a priori models, which are typically used for inverse problems, more complex multiple-point-based a priori models have to be considered. By means of marginal probability distributions ‘learned’ from a training image, sequential simulation has...... proven to be an efficient way of obtaining multiple realizations that honor the same multiple-point statistics as the training image. The frequency matching method provides an alternative way of formulating multiple-point-based a priori models. In this strategy the pattern frequency distributions (i.......e. marginals) of the training image and a subsurface model are matched in order to obtain a solution with the same multiple-point statistics as the training image. Sequential Gibbs sampling is a simulation strategy that provides an efficient way of applying sequential simulation based algorithms as a priori...

Hermitian Mindlin Plate Wavelet Finite Element Method for Load Identification

Directory of Open Access Journals (Sweden)

Xiaofeng Xue

2016-01-01

Full Text Available A new Hermitian Mindlin plate wavelet element is proposed. The two-dimensional Hermitian cubic spline interpolation wavelet is substituted into finite element functions to construct frequency response function (FRF. It uses a system’s FRF and response spectrums to calculate load spectrums and then derives loads in the time domain via the inverse fast Fourier transform. By simulating different excitation cases, Hermitian cubic spline wavelets on the interval (HCSWI finite elements are used to reverse load identification in the Mindlin plate. The singular value decomposition (SVD method is adopted to solve the ill-posed inverse problem. Compared with ANSYS results, HCSWI Mindlin plate element can accurately identify the applied load. Numerical results show that the algorithm of HCSWI Mindlin plate element is effective. The accuracy of HCSWI can be verified by comparing the FRF of HCSWI and ANSYS elements with the experiment data. The experiment proves that the load identification of HCSWI Mindlin plate is effective and precise by using the FRF and response spectrums to calculate the loads.

Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism

Directory of Open Access Journals (Sweden)

Tae-Hyoung Kim

2017-01-01

Full Text Available This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems. To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established. A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail. Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed. This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process. This is one of the distinguishing features of the proposed method. The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria. Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.

Nonstationary Hydrological Frequency Analysis: Theoretical Methods and Application Challenges

Science.gov (United States)

Xiong, L.

2014-12-01

Because of its great implications in the design and operation of hydraulic structures under changing environments (either climate change or anthropogenic changes), nonstationary hydrological frequency analysis has become so important and essential. Two important achievements have been made in methods. Without adhering to the consistency assumption in the traditional hydrological frequency analysis, the time-varying probability distribution of any hydrological variable can be established by linking the distribution parameters to some covariates such as time or physical variables with the help of some powerful tools like the Generalized Additive Model of Location, Scale and Shape (GAMLSS). With the help of copulas, the multivariate nonstationary hydrological frequency analysis has also become feasible. However, applications of the nonstationary hydrological frequency formula to the design and operation of hydraulic structures for coping with the impacts of changing environments in practice is still faced with many challenges. First, the nonstationary hydrological frequency formulae with time as covariate could only be extrapolated for a very short time period beyond the latest observation time, because such kind of formulae is not physically constrained and the extrapolated outcomes could be unrealistic. There are two physically reasonable methods that can be used for changing environments, one is to directly link the quantiles or the distribution parameters to some measureable physical factors, and the other is to use the derived probability distributions based on hydrological processes. However, both methods are with a certain degree of uncertainty. For the design and operation of hydraulic structures under changing environments, it is recommended that design results of both stationary and nonstationary methods be presented together and compared with each other, to help us understand the potential risks of each method.

Liquid identification by Hilbert spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Lyatti, M; Divin, Y; Poppe, U; Urban, K, E-mail: M.Lyatti@fz-juelich.d, E-mail: Y.Divin@fz-juelich.d [Forschungszentrum Juelich, 52425 Juelich (Germany)

2009-11-15

Fast and reliable identification of liquids is of great importance in, for example, security, biology and the beverage industry. An unambiguous identification of liquids can be made by electromagnetic measurements of their dielectric functions in the frequency range of their main dispersions, but this frequency range, from a few GHz to a few THz, is not covered by any conventional spectroscopy. We have developed a concept of liquid identification based on our new Hilbert spectroscopy and high- T{sub c} Josephson junctions, which can operate at the intermediate range from microwaves to THz frequencies. A demonstration setup has been developed consisting of a polychromatic radiation source and a compact Hilbert spectrometer integrated in a Stirling cryocooler. Reflection polychromatic spectra of various bottled liquids have been measured at the spectral range of 15-300 GHz with total scanning time down to 0.2 s and identification of liquids has been demonstrated.

Liquid identification by Hilbert spectroscopy

Science.gov (United States)

Lyatti, M.; Divin, Y.; Poppe, U.; Urban, K.

2009-11-01

Fast and reliable identification of liquids is of great importance in, for example, security, biology and the beverage industry. An unambiguous identification of liquids can be made by electromagnetic measurements of their dielectric functions in the frequency range of their main dispersions, but this frequency range, from a few GHz to a few THz, is not covered by any conventional spectroscopy. We have developed a concept of liquid identification based on our new Hilbert spectroscopy and high- Tc Josephson junctions, which can operate at the intermediate range from microwaves to THz frequencies. A demonstration setup has been developed consisting of a polychromatic radiation source and a compact Hilbert spectrometer integrated in a Stirling cryocooler. Reflection polychromatic spectra of various bottled liquids have been measured at the spectral range of 15-300 GHz with total scanning time down to 0.2 s and identification of liquids has been demonstrated.

Liquid identification by Hilbert spectroscopy

International Nuclear Information System (INIS)

Lyatti, M; Divin, Y; Poppe, U; Urban, K

2009-01-01

Fast and reliable identification of liquids is of great importance in, for example, security, biology and the beverage industry. An unambiguous identification of liquids can be made by electromagnetic measurements of their dielectric functions in the frequency range of their main dispersions, but this frequency range, from a few GHz to a few THz, is not covered by any conventional spectroscopy. We have developed a concept of liquid identification based on our new Hilbert spectroscopy and high- T c Josephson junctions, which can operate at the intermediate range from microwaves to THz frequencies. A demonstration setup has been developed consisting of a polychromatic radiation source and a compact Hilbert spectrometer integrated in a Stirling cryocooler. Reflection polychromatic spectra of various bottled liquids have been measured at the spectral range of 15-300 GHz with total scanning time down to 0.2 s and identification of liquids has been demonstrated.

Radar network communication through sensing of frequency hopping

Science.gov (United States)

Dowla, Farid; Nekoogar, Faranak

2013-05-28

In one embodiment, a radar communication system includes a plurality of radars having a communication range and being capable of operating at a sensing frequency and a reporting frequency, wherein the reporting frequency is different than the sensing frequency, each radar is adapted for operating at the sensing frequency until an event is detected, each radar in the plurality of radars has an identification/location frequency for reporting information different from the sensing frequency, a first radar of the radars which senses the event sends a reporting frequency corresponding to its identification/location frequency when the event is detected, and all other radars in the plurality of radars switch their reporting frequencies to match the reporting frequency of the first radar upon detecting the reporting frequency switch of a radar within the communication range. In another embodiment, a method is presented for communicating information in a radar system.

A High-Spin Rate Measurement Method for Projectiles Using a Magnetoresistive Sensor Based on Time-Frequency Domain Analysis.

Science.gov (United States)

Shang, Jianyu; Deng, Zhihong; Fu, Mengyin; Wang, Shunting

2016-06-16

Traditional artillery guidance can significantly improve the attack accuracy and overall combat efficiency of projectiles, which makes it more adaptable to the information warfare of the future. Obviously, the accurate measurement of artillery spin rate, which has long been regarded as a daunting task, is the basis of precise guidance and control. Magnetoresistive (MR) sensors can be applied to spin rate measurement, especially in the high-spin and high-g projectile launch environment. In this paper, based on the theory of a MR sensor measuring spin rate, the mathematical relationship model between the frequency of MR sensor output and projectile spin rate was established through a fundamental derivation. By analyzing the characteristics of MR sensor output whose frequency varies with time, this paper proposed the Chirp z-Transform (CZT) time-frequency (TF) domain analysis method based on the rolling window of a Blackman window function (BCZT) which can accurately extract the projectile spin rate. To put it into practice, BCZT was applied to measure the spin rate of 155 mm artillery projectile. After extracting the spin rate, the impact that launch rotational angular velocity and aspect angle have on the extraction accuracy of the spin rate was analyzed. Simulation results show that the BCZT TF domain analysis method can effectively and accurately measure the projectile spin rate, especially in a high-spin and high-g projectile launch environment.

Identification of Hidden Failures in Process Control Systems Based on the HMG Method

DEFF Research Database (Denmark)

Jalashgar, Atoosa

1998-01-01

cause the systems to become overloaded and even unstable, if they remain hidden. The method uses a particular terminology to contribute to the identification of system properties, including goals, functions, and the capabilities. All identified knowledge about the system is then represented by using...... a tailored combination of two function-oriented methods, Multilevel Flow Modelling (MFM) and Goal Tree-Success Tree (GTST). The features of the method, called Hybrid MFM-GTST, are described and demonstrated by using an example of a process control system. (C) 1998 John Wiley & Sons, Inc....

Identification method of gas-liquid two-phase flow regime based on image wavelet packet information entropy and genetic neural network

International Nuclear Information System (INIS)

Zhou Yunlong; Chen Fei; Sun Bin

2008-01-01

Based on the characteristic that wavelet packet transform image can be decomposed by different scales, a flow regime identification method based on image wavelet packet information entropy feature and genetic neural network was proposed. Gas-liquid two-phase flow images were captured by digital high speed video systems in horizontal pipe. The information entropy feature from transformation coefficients were extracted using image processing techniques and multi-resolution analysis. The genetic neural network was trained using those eigenvectors, which was reduced by the principal component analysis, as flow regime samples, and the flow regime intelligent identification was realized. The test result showed that image wavelet packet information entropy feature could excellently reflect the difference between seven typical flow regimes, and the genetic neural network with genetic algorithm and BP algorithm merits were with the characteristics of fast convergence for simulation and avoidance of local minimum. The recognition possibility of the network could reach up to about 100%, and a new and effective method was presented for on-line flow regime. (authors)

Functional screen printed radio frequency identification tags on flexible substrates, facilitating low-cost and integrated point-of-care diagnostics

CSIR Research Space (South Africa)

Smith, Suzanne

2018-05-01

Full Text Available This work explores the practical functionality of ultra-high frequency (UHF) radio frequency identification (RFID) tags screen printed onto various low-cost, flexible substrates. The need for integrated and automated low-cost point...

[Identification of mycobacteria to the species level by molecular methods in the Public Health Laboratory of Bogotá, Colombia].

Science.gov (United States)

Hernández-Toloza, Johana Esther; Rincón-Serrano, María de Pilar; Celis-Bustos, Yamile Adriana; Aguillón, Claudia Inés

2016-01-01

Global epidemiology of non-tuberculous mycobacteria (NTM) is unknown due to the fact that notification is not required in many countries, however the number of infection reports and outbreaks caused by NTM suggest a significant increase in the last years. Traditionally, mycobacteria identification is made through biochemical profiles which allow to differentiate M. tuberculosis from NTM, and in some cases the mycobacteria species. Nevertheless, these methods are technically cumbersome and time consuming. On the other hand, the introduction of methods based on molecular biology has improved the laboratory diagnosis of NTM. To establish the NTM frequency in positive cultures for acid-fast bacilli (AAFB) which were sent to Laboratorio de Salud Pública de Bogotá over a 12 month period. A total of 100 positive cultures for acid-fast bacilli from public and private hospitals from Bogotá were identified by both biochemical methods and the molecular methods PRA (PCR-restriction enzyme analysis) and multiplex-PCR. Furthermore, low prevalence mycobacteria species and non-interpretable results were confirmed by 16SrDNA sequentiation analysis. Identification using the PRA method showed NMT occurrence in 11% of cultures. In addition, this molecular methodology allowed to detect the occurrence of more than one mycobacteria in 4% of the cultures. Interestingly, a new M. kubicae pattern of PCR-restriction analysis is reported in our study. Using a mycobacteria identification algorithm, which includes the molecular method PRA, improves the diagnostic power of conventional methods and could help to advance both NTM epidemiology knowledge and mycobacteriosis control. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

HOC Based Blind Identification of Hydroturbine Shaft Volterra System

Directory of Open Access Journals (Sweden)

Bing Bai

2017-01-01

Full Text Available In order to identify the quadratic Volterra system simplified from the hydroturbine shaft system, a blind identification method based on the third-order cumulants and a reversely recursive method are proposed. The input sequence of the system under consideration is an unobservable independent identically distributed (i.i.d., zero-mean and non-Gaussian stationary signal, and the observed signals are the superposition of the system output signal and Gaussian noise. To calculate the third-order moment of the output signal, a computer loop judgment method is put forward to determine the coefficient. When using optimization method to identify the time domain kernels, we combined the traditional optimization algorithm (direct search method with genetic algorithm (GA and constituted the hybrid genetic algorithm (HGA. Finally, according to the prototype observation signal and the time domain kernel parameters obtained from identification, the input signal of the system can be gained recursively. To test the proposed method, three numerical experiments and engineering application have been carried out. The results show that the method is applicable to the blind identification of the hydroturbine shaft system and has strong universality; the input signal obtained by the reversely recursive method can be approximately taken as the random excitation acted on the runner of the hydroturbine shaft system.

Candida colonization and species identification by two methods in NICU newborn

Directory of Open Access Journals (Sweden)

Narges Sadat Taherzadeh

2016-02-01

Full Text Available Background: Over the last two decades invasive candidiasis has become an increasing problem in neonatal intensive care units (NICUs. Colonization of skin and mucous membranes with Candida spp. is important factor in the pathogenesis of neonatal infection and several colonized sites are major risk factors evoking higher frequencies of progression to invasive candidiasis. The aim of this study was to detect Candida colonization in NICU patients. Methods: This cross-sectional study was conducted on 93 neonates in NICUs at Imam Khomeini and Children Medical Center Hospitals in Tehran. Cutaneous and mucous membrane samples obtained at first, third, and seventh days of patients’ stay in NICUs during nine months from August 2013 to May 2014. The samples were primarily cultured on CHROMagar Candida medium. The cultured media were incubated at 35°C for 48h and evaluated based on colony color produced on CHROMagar Candida. In addition, isolated colonies were cultured on Corn Meal Agar medium supplemented with tween 80 for identification of Candida spp. based on their morphology. Finally, polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP method was performed for definite identification of isolated species. Results: Colonization by Candida spp. was occurred in 20.43% of neonates. Fifteen and four patients colonized with one and two different Candida spp., respectively. Isolated Candida spp. identified as; C. parapsilosis (n: 10, C. albicans (n: 7, C. tropicalis (n: 3, C. guilliermondii (n: 2, and C. krusei (n: 1. In present study non-albicans Candia species were dominant (69.56% and C. parapsilosis was the most frequent isolate (43.47%. Using Fisher's exact test, the correlation between fungal colonization with low birth weight, low gestational age, and duration of hospital stay was found to be statistically significant (P=0.003. Conclusion: The results of this study imply to the candida species colonization of neonates

An improved wavelet-Galerkin method for dynamic response reconstruction and parameter identification of shear-type frames

Science.gov (United States)

Bu, Haifeng; Wang, Dansheng; Zhou, Pin; Zhu, Hongping

2018-04-01

An improved wavelet-Galerkin (IWG) method based on the Daubechies wavelet is proposed for reconstructing the dynamic responses of shear structures. The proposed method flexibly manages wavelet resolution level according to excitation, thereby avoiding the weakness of the wavelet-Galerkin multiresolution analysis (WGMA) method in terms of resolution and the requirement of external excitation. IWG is implemented by this work in certain case studies, involving single- and n-degree-of-freedom frame structures subjected to a determined discrete excitation. Results demonstrate that IWG performs better than WGMA in terms of accuracy and computation efficiency. Furthermore, a new method for parameter identification based on IWG and an optimization algorithm are also developed for shear frame structures, and a simultaneous identification of structural parameters and excitation is implemented. Numerical results demonstrate that the proposed identification method is effective for shear frame structures.

Modulation format identification enabled by the digital frequency-offset loading technique for hitless coherent transceiver.

Science.gov (United States)

Fu, Songnian; Xu, Zuying; Lu, Jianing; Jiang, Hexun; Wu, Qiong; Hu, Zhouyi; Tang, Ming; Liu, Deming; Chan, Calvin Chun-Kit

2018-03-19

We propose a blind and fast modulation format identification (MFI) enabled by the digital frequency-offset (FO) loading technique for hitless coherent transceiver. Since modulation format information is encoded to the FO distribution during digital signal processing (DSP) at the transmitter side (Tx), we can use the fast Fourier transformation based FO estimation (FFT-FOE) method to obtain the FO distribution of individual data block after constant modulus algorithm (CMA) pre-equalization at the receiver side, in order to realize non-data-aided (NDA) and fast MFI. The obtained FO can be also used for subsequent FO compensation (FOC), without additional complexity. We numerically investigate and experimentally verify the proposed MFI with high accuracy and fast format switching among 28 Gbaud dual-polarization (DP)-4/8/16/64QAM, time domain hybrid-4/16QAM, and set partitioning (SP)-128QAM. In particular, the proposed MFI brings no performance degradation, in term of tolerance of amplified spontaneous emission (ASE) noise, laser linewidth, and fiber nonlinearity. Finally, a hitless coherent transceiver enabled by the proposed MFI with switching-block of only 2048 symbols is demonstrated over 1500 km standard single mode fiber (SSMF) transmission.

Identification methods of irradiated food

International Nuclear Information System (INIS)

Raffi, J.J.

1991-01-01

After a general review of the different possible methods, the stress is put upon the ones close to application: electron spin resonance, thermoluminescence and method of lipids. The problem of the specificity of each method is discussed (proof or presumption): they are then placed in the context of the programme of identification of irradiated foods just co-organized by the author with the Community Bureau of Reference (CEC) [fr

Electromagnetic interference from radio frequency identification inducing potentially hazardous incidents in critical care medical equipment

NARCIS (Netherlands)

Togt, R. van der; Lieshout, E.J. van; Hensbroek, R.; Beinat, E.; Binnekade, J.M.; Bakker, P.J.M.

2008-01-01

Context: Health care applications of autoidentification technologies, such as radio frequency identification (RFID), have been proposed to improve patient safety and also the tracking and tracing of medical equipment. However, electromagnetic interference (EMI) by RFID on medical devices has never

The identification method of the nuclear fragments in emulsions

International Nuclear Information System (INIS)

Jipa, Alexandru; Ocheseanu, Silvia; Caramarcu, Costin; Calin, Marius; Constantin, Florin; Stan, Emil

2003-01-01

The visualization detectors have been successfully used from the beginning of the study of the relativistic nuclear collisions. One of these detectors used in such experiments is the nuclear emulsion. To increase the speed of the passage from pictures to experimental data different methods and tools have been proposed during the time. For identifying the nuclear fragments obtained in the relativistic radioactive beams multiple layers of nuclear emulsions have been exposed in experiments performed at the Synchrophasotron from the JINR Dubna (BECQUEREL Collaboration). The nuclear fragments have been identified using PAVICOM scanning and measuring system. In the present work an identification method based on a real time image processing machine and a reconstruction algorithm based on special conformal transforms is proposed. The results obtained by this method are compared with those obtained using PAVICOM device. Because in this study only pictures have been used, not initial nuclear emulsions, some difficulties in the identification of the nuclear fragments with higher polar angles can appear. Generally, comparable results have been obtained. The authors thank Dr. Pavel Zarubin from JINR Dubna, Laboratory of High Energy Physics, and Dr. Maria Haiduc, Institute of Space Sciences Bucharest-Magurele, for the pictures of the nuclear emulsions exposed in these experiments. (authors)

An FEM-based AI approach to model parameter identification for low vibration modes of wind turbine composite rotor blades

Science.gov (United States)

Navadeh, N.; Goroshko, I. O.; Zhuk, Y. A.; Fallah, A. S.

2017-11-01

An approach to construction of a beam-type simplified model of a horizontal axis wind turbine composite blade based on the finite element method is proposed. The model allows effective and accurate description of low vibration bending modes taking into account the effects of coupling between flapwise and lead-lag modes of vibration transpiring due to the non-uniform distribution of twist angle in the blade geometry along its length. The identification of model parameters is carried out on the basis of modal data obtained by more detailed finite element simulations and subsequent adoption of the 'DIRECT' optimisation algorithm. Stable identification results were obtained using absolute deviations in frequencies and in modal displacements in the objective function and additional a priori information (boundedness and monotony) on the solution properties.

Flextensional fiber Bragg grating-based accelerometer for low frequency vibration measurement

Institute of Scientific and Technical Information of China (English)

Jinghua Zhang; Xueguang Qiao; Manli Hu; Zhongyao Feng; Hong Gao; Yang Yang; Rui Zhou

2011-01-01

@@ The intelligent structural health monitoring method,which uses a fiber Bragg grating(FBG)sensor,is a new approach in the field of civil engineering.However,it lacks a reliable FBG-based accelerometer for taking structural low frequency vibration measurements.In this letter,a flextensional FBG-based accelerometer is proposed and demonstrated.The experimental results indicate that the natural frequency of the developed accelerometer is 16.7 Hz,with a high sensitivity of 410.7 pm/g.In addition,it has a broad and flat response over low frequencies ranging from 1 to 10 Hz.The natural frequency and sensitivity of the accelerometer can be tuned by adding mass to tailor the sensor performance to specific applications.Experimental results are presented to demonstrate the good performance of the proposed FBG-based accelerometer.These results show that the proposed accelerometer is satisfactory for low frequency vibration measurements.%The intelligent structural health monitoring method, which uses a fiber Bragg grating {FBG} sensor, ie a new approach in the field of civil engineering. However, it lacks a reliable FBG-based accelerometer for taking structural low frequency vibration measurements. In this letter, a flextensional FBG-based accelerometer is proposed and demonstrated. The experimental results indicate that the natural frequency of the developed accelerometer is 16.7 Hz, with a high sensitivity of 410.7 pm/g. In addition, it has a broad and flat response over low frequencies ranging from 1 to 10 Hz. The natural frequency and sensitivity of the accelerometer can be tuned by adding mass to tailor the sensor performance to specific applications. Experimental results are presented to demonstrate the good performance of the proposed FBG-based accelerometer. These results show that the proposed accelerometer is satisfactory for low frequency vibration measurements.

Power System Oscillation Modes Identifications: Guidelines for Applying TLS-ESPRIT Method

Science.gov (United States)

Gajjar, Gopal R.; Soman, Shreevardhan

2013-05-01

Fast measurements of power system quantities available through wide-area measurement systems enables direct observations for power system electromechanical oscillations. But the raw observations data need to be processed to obtain the quantitative measures required to make any inference regarding the power system state. A detailed discussion is presented for the theory behind the general problem of oscillatory mode indentification. This paper presents some results on oscillation mode identification applied to a wide-area frequency measurements system. Guidelines for selection of parametes for obtaining most reliable results from the applied method are provided. Finally, some results on real measurements are presented with our inference on them.

Robust parameterization of time-frequency characteristics for recognition of musical genres of Mexican culture

Science.gov (United States)

Pérez Rosas, Osvaldo G.; Rivera Martínez, José L.; Maldonado Cano, Luis A.; López Rodríguez, Mario; Amaya Reyes, Laura M.; Cano Martínez, Elizabeth; García Vázquez, Mireya S.; Ramírez Acosta, Alejandro A.

2017-09-01

The automatic identification and classification of musical genres based on the sound similarities to form musical textures, it is a very active investigation area. In this context it has been created recognition systems of musical genres, formed by time-frequency characteristics extraction methods and by classification methods. The selection of this methods are important for a good development in the recognition systems. In this article they are proposed the Mel-Frequency Cepstral Coefficients (MFCC) methods as a characteristic extractor and Support Vector Machines (SVM) as a classifier for our system. The stablished parameters of the MFCC method in the system by our time-frequency analysis, represents the gamma of Mexican culture musical genres in this article. For the precision of a classification system of musical genres it is necessary that the descriptors represent the correct spectrum of each gender; to achieve this we must realize a correct parametrization of the MFCC like the one we present in this article. With the system developed we get satisfactory detection results, where the least identification percentage of musical genres was 66.67% and the one with the most precision was 100%.

Adoption of radio-frequency identification to establish traceability in Taiwanese eel exported to the Japanese market.

Science.gov (United States)

Jeng, Shu-Ching; Wu, Chun-Lung; Yang, I-Da

2013-01-01

Eel culture and export to the Japanese market is an important industry in Taiwan; however, the average amount produced by each farm is small. Eels from different farms might be mixed before export, making it difficult to determine which farm is responsible for eels containing drug residues. Therefore, the Taiwanese government uses a two-stage procedure of inspection and accreditation for validating the use of good practice in aquaculture farming. Nevertheless, it is still difficult to trace any farm that has produced eels containing drug residues. Radio-frequency identification has the potential to establish traceability in eel products. Here we suggest that Japanese eel importers should insist on the use of radio-frequency identification by Taiwanese eel exporters to enable verification of the safety of eel products being exported to the Japanese market.

Joint Spatio-Temporal Filtering Methods for DOA and Fundamental Frequency Estimation

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Benesty, Jacob

2015-01-01

some attention in the community and is quite promising for several applications. The proposed methods are based on optimal, adaptive filters that leave the desired signal, having a certain DOA and fundamental frequency, undistorted and suppress everything else. The filtering methods simultaneously...... operate in space and time, whereby it is possible resolve cases that are otherwise problematic for pitch estimators or DOA estimators based on beamforming. Several special cases and improvements are considered, including a method for estimating the covariance matrix based on the recently proposed...

A Sensitive and Specific PCR Based Method for Identification of Cryptosporidium Sp. Using New Primers from 18S Ribosomal RNA

Directory of Open Access Journals (Sweden)

M Heydarnezhadi

2011-09-01

Full Text Available Background: The main goal of the present study was to develop a new sensitive and specific PCR based method for Identification of Cryptosporidium sp. using novel primers from 18S ribosomal RNA. Cryptosporidi­osis in high-risk host groups particularly in neonates and immuno-compromised individuals may result in death. To the best of our knowledge this is the first study regarding develop a new PCR based method to diagnose the cryptosporidiosis in Iran.Methods: A total of 850 human fecal samples from patients clinically suspected to cryptosporidiosis and 100 healthy and diarrheic cattle stool specimens were collected. The simplified formol-ether concentration method was carried out for all samples. They were then examined microscopically by modified Ziehl-Neel­sen staining method. Total DNA was extracted by QIA amp DNA stool mini kit was carried out by using designed prim­ers.Results: Twenty nine cases of cryptosporidiosis infection in human and 30 samples from cattle microscopi­cally were posi­tive. The described primary and nested PCR method could detect all Cryptospori­dium positive samples from human and cattle. Regards to suspected negative samples in pri­mary PCR examination, the Nested PCR could ap­prove two more positive results. Furthermore, Nested PCR analysis was able to detect one more case which was nega­tive in both microscopically examination and primary PCR. Specificity of the test was 100%. Sensitivity of Nested PCR in comparison to our gold standard; microscopy after Ridley concentration modified ziehl-Neelsen, was 100 %.Conclusion: Our developed PCR based method by using new primers devised from 18S ribosomal RNA revealed the ability for identification of the Cryptosporidium species such as C. parvum and C. huminis with high specificity and sensitivity.

IDENTIFICATION OF THE main HONEY CROPS BASED on remote sensing data

Directory of Open Access Journals (Sweden)

A. Moskalenko

2017-05-01

Full Text Available Possibilities of bee forage identification and mapping based on multispectral images Landsat 8 have been shown in the research. The satellite images can be used to determine areas of crops that are resource for nectar and pollen such as sunflower, buckwheat and corn. Identifying bee forages was based on methods of supervised classification such as minimum distance to means, the linear discriminant analysis, the maximum likelihood, the parallelepiped and the k-nearest neighbors. The accuracy of classification methods of remote sensing data for identification of pollen and nectars cultures was compared. The method of maximum likelihood showed the best results for buckwheat and good one for corn and sunflower fields by 13/07/2016. Also this method showed good result for corn and sunflower fields, and poor result for identification of buckwheat fields by 29/07/2016. The stage of flowering plants is the most important period of cropgrowth phase for beekeeping because it is the periodof formation of pollen and nectar. Therefore identification of bee forage has been analyzed vegetation period from germination to flowering. Images of Landsat 8 (sensor OLI by 26/05/2016, 27/06/2016, 13/07/2016 and 29/07/2016 have been used in the research. The optimum period of remote sensing data for identification agricultural crops of bee forage has been determined. Buckwheat fields can be identified more effective in mid-July. Corn fields can be determined at the end of July. Sunflowers can be identified well as before flowering as during flowering.

Identification of process dynamics. Stability monitoring in BWR type reactors

International Nuclear Information System (INIS)

Abrahamsson, P.; Hallgren, P.

1991-06-01

Identification of process dynamics is used for stability monitoring in nuclear reactors (Boiling Water Reactor). This report treats the problem of estimating a damping factor and a resonance frequency from the neutron flux as measured in the reactor. A new parametric online method for identification is derived and presented, and is shown to meet the requirements of stability monitoring. The technique for estimating the process parameters is based on a recursive lattice filter algorithm. The problem of time varying parameters and offset, as well as offline experiments and signal processing are treated. All parts are implemented in a realtime program, using the language C. In comparison with earlier identifications, the new way of estimating the damping factor is shown to work well. Estimates of both the damping factor and the resonance frequency show a stable and reliable behavior. Future development and improvements are also indicated. (au)

Order Tracking Based on Robust Peak Search Instantaneous Frequency Estimation

International Nuclear Information System (INIS)

Gao, Y; Guo, Y; Chi, Y L; Qin, S R

2006-01-01

Order tracking plays an important role in non-stationary vibration analysis of rotating machinery, especially to run-up or coast down. An instantaneous frequency estimation (IFE) based order tracking of rotating machinery is introduced. In which, a peak search algorithms of spectrogram of time-frequency analysis is employed to obtain IFE of vibrations. An improvement to peak search is proposed, which can avoid strong non-order components or noises disturbing to the peak search work. Compared with traditional methods of order tracking, IFE based order tracking is simplified in application and only software depended. Testing testify the validity of the method. This method is an effective supplement to traditional methods, and the application in condition monitoring and diagnosis of rotating machinery is imaginable

radio frequency based radio frequency based water level monitor

African Journals Online (AJOL)

eobe

ABSTRACT. This paper elucidates a radio frequency (RF) based transmission and reception system used to remotely monitor and .... range the wireless can cover but in this prototype, it ... power supply to the system, the sensed water level is.

Identification of provenance rocks based on EPMA analyses of heavy minerals

Science.gov (United States)

Shimizu, M.; Sano, N.; Ueki, T.; Yonaga, Y.; Yasue, K. I.; Masakazu, N.

2017-12-01

Information on mountain building is significant in the field of geological disposal of high-level radioactive waste, because this affects long-term stability in groundwater flow system. Provenance analysis is one of effective approaches for understanding building process of mountains. Chemical compositions of heavy minerals, as well as their chronological data, can be an index for identification of provenance rocks. The accurate identification requires the measurement of as many grains as possible. In order to achieve an efficient provenance analysis, we developed a method for quick identification of heavy minerals using an Electron Probe Micro Analyzer (EPMA). In this method, heavy mineral grains extracted from a sample were aligned on a glass slide and mounted in a resin. Concentration of 28 elements was measured for 300-500 grains per sample using EPMA. To measure as many grains as possible, we prioritized swiftness of measurement over precision, configuring measurement time of about 3.5 minutes for each grain. Identification of heavy minerals was based on their chemical composition. We developed a Microsoft® Excel® spread sheet input criteria of mineral identification using a typical range of chemical compositions for each mineral. The grains of 110 wt.% total were rejected. The criteria of mineral identification were revised through the comparison between mineral identification by optical microscopy and chemical compositions of grains classified as "unknown minerals". Provenance rocks can be identified based on abundance ratio of identified minerals. If no significant difference of the abundance ratio was found among source rocks, chemical composition of specific minerals was used as another index. This method was applied to the sediments of some regions in Japan where provenance rocks had lithological variations but similar formation ages. Consequently, the provenance rocks were identified based on chemical compositions of heavy minerals resistant to

Impulse response identification with deterministic inputs using non-parametric methods

International Nuclear Information System (INIS)

Bhargava, U.K.; Kashyap, R.L.; Goodman, D.M.

1985-01-01

This paper addresses the problem of impulse response identification using non-parametric methods. Although the techniques developed herein apply to the truncated, untruncated, and the circulant models, we focus on the truncated model which is useful in certain applications. Two methods of impulse response identification will be presented. The first is based on the minimization of the C/sub L/ Statistic, which is an estimate of the mean-square prediction error; the second is a Bayesian approach. For both of these methods, we consider the effects of using both the identity matrix and the Laplacian matrix as weights on the energy in the impulse response. In addition, we present a method for estimating the effective length of the impulse response. Estimating the length is particularly important in the truncated case. Finally, we develop a method for estimating the noise variance at the output. Often, prior information on the noise variance is not available, and a good estimate is crucial to the success of estimating the impulse response with a nonparametric technique

The constitutive compatibility method for identification of material parameters based on full-field measurements

KAUST Repository

Moussawi, Ali; Lubineau, Gilles; Florentin, É ric; Blaysat, Benoî t

2013-01-01

We revisit here the concept of the constitutive relation error for the identification of elastic material parameters based on image correlation. An additional concept, so called constitutive compatibility of stress, is introduced defining a subspace

Dynamic Parameter Identification of Hydrodynamic Bearing-Rotor System

Directory of Open Access Journals (Sweden)

Zhiqiang Song

2015-01-01

Full Text Available A new method called modal parameter genetic time domain identification was employed to study the characteristics of the bearing-rotor system. A multifrequency signal decomposition technology to identify the main components of the measured signal and reject the image mode produced by noise has been used. The first- and second-order natural frequency and damping ratios of the shaft system are identified. Furthermore, because of the deficiency of the traditional least square method, a new genetic identification method to identify the bearing dynamic characteristic parameters has been proposed. The method has been effective albeit with few testing points and operation cases. The derivation of oil-film dynamic coefficients could also provide a basis for shaft system natural vibration characteristic and vibration response analysis. Using the identified dynamic coefficients as the supporting condition, the shaft system modal characteristics were studied. The calculated first- and second-order natural frequencies match quite well those obtained from the modal parameter identification. It was proved that the modal parameter and physical parameter identification methods utilized in this paper are reasonable.

Quasidynamic emergency analysis, identification and control of power system frequency perturbations

Energy Technology Data Exchange (ETDEWEB)

Jovanovic, S M [Nikola Tesla Institute, Belgrade (YU)

1990-07-01

There are several possible operating states of a power system. These are the normal operating state (both secure and insecure), the emergency state, the extreme emergency state and the restorative state. The system enters the emergency operating state if any of the operating constraints are violated. Emergency analysis attempts to compute in real time the violations of these constraints and the new (successive) disturbances which arise from the initial ones. The paper presents a quasidynamic approach to emergency state analysis, identification and control of power system frequency perturbations. A quasidynamic model is derived by simplifying the conventional long-term dynamics model of power systems in the time interval 0-5 s. The quasidynamic model is algebraic in nature, but the time variable t is incorporated into the model and is used to describe the part of the system dynamics that is of interest in the specified time interval. The paper proposes an on-line computer emergency control strategy based on the above quasidynamic model. Finally, a numerical example is given for the Yugoslav power system. (author).

Identification of hydrologic and geochemical pathways using high frequency sampling, REE aqueous sampling and soil characterization at Koiliaris Critical Zone Observatory, Crete

Energy Technology Data Exchange (ETDEWEB)

Moraetis, Daniel, E-mail: moraetis@mred.tuc.gr [Department of Environmental Engineering, Technical University of Crete, 73100 Chania (Greece); Stamati, Fotini; Kotronakis, Manolis; Fragia, Tasoula; Paranychnianakis, Nikolaos; Nikolaidis, Nikolaos P. [Department of Environmental Engineering, Technical University of Crete, 73100 Chania (Greece)

2011-06-15

Highlights: > Identification of hydrological and geochemical pathways within a complex watershed. > Water increased N-NO{sub 3} concentration and E.C. values during flash flood events. > Soil degradation and impact on water infiltration within the Koiliaris watershed. > Analysis of Rare Earth Elements in water bodies for identification of karstic water. - Abstract: Koiliaris River watershed is a Critical Zone Observatory that represents severely degraded soils due to intensive agricultural activities and biophysical factors. It has typical Mediterranean soils under the imminent threat of desertification which is expected to intensify due to projected climate change. High frequency hydro-chemical monitoring with targeted sampling for Rare Earth Elements (REE) analysis of different water bodies and geochemical characterization of soils were used for the identification of hydrologic and geochemical pathways. The high frequency monitoring of water chemical data highlighted the chemical alterations of water in Koiliaris River during flash flood events. Soil physical and chemical characterization surveys were used to identify erodibility patterns within the watershed and the influence of soils on surface and ground water chemistry. The methodology presented can be used to identify the impacts of degraded soils to surface and ground water quality as well as in the design of methods to minimize the impacts of land use practices.

New logarithmic technique of diffusivity identification using the flash method; Nouvelle technique logarithmique d`identification de la diffusivite par la methode flash

Energy Technology Data Exchange (ETDEWEB)

Thermitus, M.A.; Laurent, M. [Institut National des Sciences Appliquees (INSA), 69 - Villeurbanne (France)

1997-12-31

Using a logarithmic transformation, the thermogram of a flash experiment can be interpreted as the sum of the adiabatic model solution with a term representative of the losses. Two methods based on this transformation are proposed in this study. They are based on the identification of a parameter that depends on the thickness of the sample and on its diffusivity and not on the experimental conditions. They allow to identify the diffusivity with a high precision even for materials with a low conductivity at high temperatures. (J.S.) 12 refs.

Method for Walking Gait Identification in a Lower Extremity Exoskeleton Based on C4.5 Decision Tree Algorithm

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Qing Guo

2015-04-01

Full Text Available A gait identification method for a lower extremity exoskeleton is presented in order to identify the gait sub-phases in human-machine coordinated motion. First, a sensor layout for the exoskeleton is introduced. Taking the difference between human lower limb motion and human-machine coordinated motion into account, the walking gait is divided into five sub-phases, which are ‘double standing’, ‘right leg swing and left leg stance’, ‘double stance with right leg front and left leg back’, ‘right leg stance and left leg swing’, and ‘double stance with left leg front and right leg back’. The sensors include shoe pressure sensors, knee encoders, and thigh and calf gyroscopes, and are used to measure the contact force of the foot, and the knee joint angle and its angular velocity. Then, five sub-phases of walking gait are identified by a C4.5 decision tree algorithm according to the data fusion of the sensors' information. Based on the simulation results for the gait division, identification accuracy can be guaranteed by the proposed algorithm. Through the exoskeleton control experiment, a division of five sub-phases for the human-machine coordinated walk is proposed. The experimental results verify this gait division and identification method. They can make hydraulic cylinders retract ahead of time and improve the maximal walking velocity when the exoskeleton follows the person's motion.

Reduction of low frequency vibration of truck driver and seating system through system parameter identification, sensitivity analysis and active control

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Wang, Xu; Bi, Fengrong; Du, Haiping

2018-05-01

This paper aims to develop an 5-degree-of-freedom driver and seating system model for optimal vibration control. A new method for identification of the driver seating system parameters from experimental vibration measurement has been developed. The parameter sensitivity analysis has been conducted considering the random excitation frequency and system parameter uncertainty. The most and least sensitive system parameters for the transmissibility ratio have been identified. The optimised PID controllers have been developed to reduce the driver's body vibration.

Research on frequency control strategy of interconnected region based on fuzzy PID

Science.gov (United States)

Zhang, Yan; Li, Chunlan

2018-05-01

In order to improve the frequency control performance of the interconnected power grid, overcome the problems of poor robustness and slow adjustment of traditional regulation, the paper puts forward a frequency control method based on fuzzy PID. The method takes the frequency deviation and tie-line deviation of each area as the control objective, takes the regional frequency deviation and its deviation as input, and uses fuzzy mathematics theory, adjusts PID control parameters online. By establishing the regional frequency control model of water-fire complementary power generation in MATLAB, the regional frequency control strategy is given, and three control modes (TBC-FTC, FTC-FTC, FFC-FTC) are simulated and analyzed. The simulation and experimental results show that, this method has better control performance compared with the traditional regional frequency regulation.

Precise material identification method based on a photon counting technique with correction of the beam hardening effect in X-ray spectra

International Nuclear Information System (INIS)

Kimoto, Natsumi; Hayashi, Hiroaki; Asahara, Takashi; Mihara, Yoshiki; Kanazawa, Yuki; Yamakawa, Tsutomu; Yamamoto, Shuichiro; Yamasaki, Masashi; Okada, Masahiro

2017-01-01

The aim of our study is to develop a novel material identification method based on a photon counting technique, in which the incident and penetrating X-ray spectra are analyzed. Dividing a 40 kV X-ray spectra into two energy regions, the corresponding linear attenuation coefficients are derived. We can identify the materials precisely using the relationship between atomic number and linear attenuation coefficient through the correction of the beam hardening effect of the X-ray spectra. - Highlights: • We propose a precise material identification method to be used as a photon counting system. • Beam hardening correction is important, even when the analysis is applied to the short energy regions in the X-ray spectrum. • Experiments using a single probe-type CdTe detector were performed, and Monte Carlo simulation was also carried out. • We described the applicability of our method for clinical diagnostic X-ray imaging in the near future.

Identification of the Parameters of the Instantaneous Point Pollution Source in the Azov Sea Based on the Adjoint Method

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V.S. Kochergin

2017-02-01

Full Text Available The passive admixture transport model in the Azov Sea is considered. The problem of cartelistic impulse local source identification at the sea surface based on adjoint method is solving by integration of independent series of adjoint tasks. Simultaneous solution of this problem at the parallel mode is realized by the aforementioned approach. The efficiency of the algorithm optimal value power of source search agreed with the data measurements is shown in the test example. The measurement data assimilation algorithm in the passive admixture transfer model is implemented applying variational methods of filtration for optimal estimate retrieval. The retrieval is carried out by means of the method of adjoint equations and solving of linear systems. On the basis of the variational filtration method of data assimilation, the optimal estimate retrieval algorithm for pollution source power identification is constructed. In application of the algorithm, the integration of the main, linked and adjoint problems is implemented. Integration problems are solved using TVD approximations. For the application of the procedure, the Azov current fields and turbulent diffusion coefficients are obtained using the sigma coordinate ocean model (POM under the eastern wind stress conditions being dominant at the observed time period. Furthermore, the results can be used to perform numerical data assimilation on loads of suspended matter.

Construction Project Performance Improvement through Radio Frequency Identification Technology Application on a Project Supply Chain

Science.gov (United States)

Wang, Heng

2017-01-01

Construction project productivity typically lags other industries and it has been the focus of numerous studies in order to improve the project performance. This research investigated the application of Radio Frequency Identification (RFID) technology on construction projects' supply chain and determined that RFID technology can improve the…

[Biometric identification method for ECG based on the piecewise linear representation (PLR) and dynamic time warping (DTW)].

Science.gov (United States)

Yang, Licai; Shen, Jun; Bao, Shudi; Wei, Shoushui

2013-10-01

To treat the problem of identification performance and the complexity of the algorithm, we proposed a piecewise linear representation and dynamic time warping (PLR-DTW) method for ECG biometric identification. Firstly we detected R peaks to get the heartbeats after denoising preprocessing. Then we used the PLR method to keep important information of an ECG signal segment while reducing the data dimension at the same time. The improved DTW method was used for similarity measurements between the test data and the templates. The performance evaluation was carried out on the two ECG databases: PTB and MIT-BIH. The analystic results showed that compared to the discrete wavelet transform method, the proposed PLR-DTW method achieved a higher accuracy rate which is nearly 8% of rising, and saved about 30% operation time, and this demonstrated that the proposed method could provide a better performance.

Simulation and Experimental Investigation of Structural Dynamic Frequency Characteristics Control

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Bing Li

2012-04-01

Full Text Available In general, mechanical equipment such as cars, airplanes, and machine tools all operate with constant frequency characteristics. These constant working characteristics should be controlled if the dynamic performance of the equipment demands improvement or the dynamic characteristics is intended to change with different working conditions. Active control is a stable and beneficial method for this, but current active control methods mainly focus on vibration control for reducing the vibration amplitudes in the time domain or frequency domain. In this paper, a new method of dynamic frequency characteristics active control (DFCAC is presented for a flat plate, which can not only accomplish vibration control but also arbitrarily change the dynamic characteristics of the equipment. The proposed DFCAC algorithm is based on a neural network including two parts of the identification implement and the controller. The effectiveness of the DFCAC method is verified by several simulation and experiments, which provide desirable results.

Frequency-domain method for separating signal and noise