WorldWideScience

Sample records for automated fault extraction

  1. Automated fault extraction and classification using 3-D seismic data for the Ekofisk field development

    Energy Technology Data Exchange (ETDEWEB)

    Signer, C.; Nickel, M.; Randen, T.; Saeter, T.; Soenneland, H.H.

    1998-12-31

    Mapping of fractures is important for the prediction of fluid flow in many reservoir types. The fluid flow depends mainly on the efficiency of the reservoir seals. Improved spatial mapping of the open and closed fracture systems will allow a better prediction of the fluid flow pattern. The primary objectives of this paper is to present fracture characterization at the reservoir scale combined with seismic facies mapping. The complexity of the giant Ekofisk field on the Norwegian continental shelf provides an ideal framework for testing the validity and the applicability of an automated seismic fault and fracture detection and mapping tool. The mapping of the faults can be based on seismic attribute grids, which means that attribute-responses related to faults are extracted along key horizons which were interpreted in the reservoir interval. 3 refs., 3 figs.

  2. Automated extraction of faults and porous reservoir bodies. Examples from the Vallhall Field

    Energy Technology Data Exchange (ETDEWEB)

    Barkved, Olav Inge; Whitman, Doug; Kunz, Tim

    1998-12-31

    The Norwegian Vahall field is located 250 km South-West of Stavanger. The production is primarily from the highly porous and fractured chalk, the Tor formation. Fractures, evidently play a significant role in enhancing flow properties as well as production rates, are significantly higher than expected from matrix permeability alone. The fractures are primarily tectonically induced and related to faulting. Syn-depositional faulting is believed to be a controlling factor on reservoir thickness variations observed across the field. Due to the low acoustic contrast and weak appearance of the highly porous chalk, direct evidence of faulting in well bore logs is limited. The seismic data quality in the most central area of the field is very poor due to tertiary gas charging, but in the flank area of the field, the quality is excellent. 1 ref., 5 figs.

  3. Automated Water Extraction Index

    DEFF Research Database (Denmark)

    Feyisa, Gudina Legese; Meilby, Henrik; Fensholt, Rasmus

    2014-01-01

    of various sorts of environmental noise and at the same time offers a stable threshold value. Thus we introduced a new Automated Water Extraction Index (AWEI) improving classification accuracy in areas that include shadow and dark surfaces that other classification methods often fail to classify correctly...

  4. Alternative validation practice of an automated faulting measurement method.

    Science.gov (United States)

    2010-03-08

    A number of states have adopted profiler based systems to automatically measure faulting, : in jointed concrete pavements. However, little published work exists which documents the : validation process used for such automated faulting systems. This p...

  5. Automated vehicle for railway track fault detection

    Science.gov (United States)

    Bhushan, M.; Sujay, S.; Tushar, B.; Chitra, P.

    2017-11-01

    For the safety reasons, railroad tracks need to be inspected on a regular basis for detecting physical defects or design non compliances. Such track defects and non compliances, if not detected in a certain interval of time, may eventually lead to severe consequences such as train derailments. Inspection must happen twice weekly by a human inspector to maintain safety standards as there are hundreds and thousands of miles of railroad track. But in such type of manual inspection, there are many drawbacks that may result in the poor inspection of the track, due to which accidents may cause in future. So to avoid such errors and severe accidents, this automated system is designed.Such a concept would surely introduce automation in the field of inspection process of railway track and can help to avoid mishaps and severe accidents due to faults in the track.

  6. Automated Fault Detection for DIII-D Tokamak Experiments

    Energy Technology Data Exchange (ETDEWEB)

    Walker, M.L.; Scoville, J.T.; Johnson, R.D.; Hyatt, A.W.; Lee, J.

    1999-11-01

    An automated fault detection software system has been developed and was used during 1999 DIII-D plasma operations. The Fault Identification and Communication System (FICS) executes automatically after every plasma discharge to check dozens of subsystems for proper operation and communicates the test results to the tokamak operator. This system is now used routinely during DIII-D operations and has led to an increase in tokamak productivity.

  7. Display interface concepts for automated fault diagnosis

    Science.gov (United States)

    Palmer, Michael T.

    1989-01-01

    An effort which investigated concepts for displaying dynamic system status and fault history (propagation) information to the flight crew is described. This investigation was performed by developing several candidate display formats and then conducting comprehension tests to determine those characteristics that made one format preferable to another for presenting this type of information. Twelve subjects participated. Flash tests, or limited time exposure tests, were used to determine the subjects' comprehension of the information presented in the display formats. It was concluded from the results of the comprehension tests that pictographs were more comprehensible than both block diagrams and text for presenting dynamic system status and fault history information, and that pictographs were preferred over both block diagrams and text. It was also concluded that the addition of this type of information in the cockpit would help the crew remain aware of the status of their aircraft.

  8. Automated DNA extraction from pollen in honey.

    Science.gov (United States)

    Guertler, Patrick; Eicheldinger, Adelina; Muschler, Paul; Goerlich, Ottmar; Busch, Ulrich

    2014-04-15

    In recent years, honey has become subject of DNA analysis due to potential risks evoked by microorganisms, allergens or genetically modified organisms. However, so far, only a few DNA extraction procedures are available, mostly time-consuming and laborious. Therefore, we developed an automated DNA extraction method from pollen in honey based on a CTAB buffer-based DNA extraction using the Maxwell 16 instrument and the Maxwell 16 FFS Nucleic Acid Extraction System, Custom-Kit. We altered several components and extraction parameters and compared the optimised method with a manual CTAB buffer-based DNA isolation method. The automated DNA extraction was faster and resulted in higher DNA yield and sufficient DNA purity. Real-time PCR results obtained after automated DNA extraction are comparable to results after manual DNA extraction. No PCR inhibition was observed. The applicability of this method was further successfully confirmed by analysis of different routine honey samples. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Automated extraction of DNA from clothing

    DEFF Research Database (Denmark)

    Stangegaard, Michael; Hjort, Benjamin Benn; Nøhr Hansen, Thomas

    2011-01-01

    Presence of PCR inhibitors in extracted DNA may interfere with the subsequent quantification and short tandem repeat (STR) reactions used in forensic genetic DNA typing. We have compared three automated DNA extraction methods based on magnetic beads with a manual method with the aim of reducing...... the amount of PCR inhibitors in the DNA extracts and increasing the proportion of reportable DNA profiles....

  10. A data-driven multiplicative fault diagnosis approach for automation processes.

    Science.gov (United States)

    Hao, Haiyang; Zhang, Kai; Ding, Steven X; Chen, Zhiwen; Lei, Yaguo

    2014-09-01

    This paper presents a new data-driven method for diagnosing multiplicative key performance degradation in automation processes. Different from the well-established additive fault diagnosis approaches, the proposed method aims at identifying those low-level components which increase the variability of process variables and cause performance degradation. Based on process data, features of multiplicative fault are extracted. To identify the root cause, the impact of fault on each process variable is evaluated in the sense of contribution to performance degradation. Then, a numerical example is used to illustrate the functionalities of the method and Monte-Carlo simulation is performed to demonstrate the effectiveness from the statistical viewpoint. Finally, to show the practical applicability, a case study on the Tennessee Eastman process is presented. Copyright © 2013. Published by Elsevier Ltd.

  11. Fault Features Extraction and Identification based Rolling Bearing Fault Diagnosis

    International Nuclear Information System (INIS)

    Qin, B; Sun, G D; Zhang L Y; Wang J G; HU, J

    2017-01-01

    For the fault classification model based on extreme learning machine (ELM), the diagnosis accuracy and stability of rolling bearing is greatly influenced by a critical parameter, which is the number of nodes in hidden layer of ELM. An adaptive adjustment strategy is proposed based on vibrational mode decomposition, permutation entropy, and nuclear kernel extreme learning machine to determine the tunable parameter. First, the vibration signals are measured and then decomposed into different fault feature models based on variation mode decomposition. Then, fault feature of each model is formed to a high dimensional feature vector set based on permutation entropy. Second, the ELM output function is expressed by the inner product of Gauss kernel function to adaptively determine the number of hidden layer nodes. Finally, the high dimension feature vector set is used as the input to establish the kernel ELM rolling bearing fault classification model, and the classification and identification of different fault states of rolling bearings are carried out. In comparison with the fault classification methods based on support vector machine and ELM, the experimental results show that the proposed method has higher classification accuracy and better generalization ability. (paper)

  12. Automatic fault extraction using a modified ant-colony algorithm

    International Nuclear Information System (INIS)

    Zhao, Junsheng; Sun, Sam Zandong

    2013-01-01

    The basis of automatic fault extraction is seismic attributes, such as the coherence cube which is always used to identify a fault by the minimum value. The biggest challenge in automatic fault extraction is noise, including that of seismic data. However, a fault has a better spatial continuity in certain direction, which makes it quite different from noise. Considering this characteristic, a modified ant-colony algorithm is introduced into automatic fault identification and tracking, where the gradient direction and direction consistency are used as constraints. Numerical model test results show that this method is feasible and effective in automatic fault extraction and noise suppression. The application of field data further illustrates its validity and superiority. (paper)

  13. Fault tolerant strategies for automated operation of nuclear reactors

    International Nuclear Information System (INIS)

    Berkan, R.C.; Tsoukalas, L.

    1991-01-01

    This paper introduces an automatic control system incorporating a number of verification, validation, and command generation tasks with-in a fault-tolerant architecture. The integrated system utilizes recent methods of artificial intelligence such as neural networks and fuzzy logic control. Furthermore, advanced signal processing and nonlinear control methods are also included in the design. The primary goal is to create an on-line capability to validate signals, analyze plant performance, and verify the consistency of commands before control decisions are finalized. The application of this approach to the automated startup of the Experimental Breeder Reactor-II (EBR-II) is performed using a validated nonlinear model. The simulation results show that the advanced concepts have the potential to improve plant availability andsafety

  14. Acceleration of Automated HI Source Extraction

    Science.gov (United States)

    Badenhorst, S. J.; Blyth, S.; Kuttel, M. M.

    2013-10-01

    We aim to enable fast automated extraction of neutral hydrogen (HI) sources from large survey data sets. This requires both handling the large files (>5 TB) to be produced by next-generation interferometers and acceleration of the source extraction algorithm. We develop an efficient multithreaded implementation of the A'Trous wavelet reconstruction algorithm, which we evaluate against the serial implementation in the DUCHAMP package. We also evaluate three memory management libraries (Mmap, Boost and Stxxl) that enable processing of data files too large to fit into main memory, to establish which provides the best performance.

  15. PCA Fault Feature Extraction in Complex Electric Power Systems

    Directory of Open Access Journals (Sweden)

    ZHANG, J.

    2010-08-01

    Full Text Available Electric power system is one of the most complex artificial systems in the world. The complexity is determined by its characteristics about constitution, configuration, operation, organization, etc. The fault in electric power system cannot be completely avoided. When electric power system operates from normal state to failure or abnormal, its electric quantities (current, voltage and angles, etc. may change significantly. Our researches indicate that the variable with the biggest coefficient in principal component usually corresponds to the fault. Therefore, utilizing real-time measurements of phasor measurement unit, based on principal components analysis technology, we have extracted successfully the distinct features of fault component. Of course, because of the complexity of different types of faults in electric power system, there still exists enormous problems need a close and intensive study.

  16. Operations management system advanced automation: Fault detection isolation and recovery prototyping

    Science.gov (United States)

    Hanson, Matt

    1990-01-01

    The purpose of this project is to address the global fault detection, isolation and recovery (FDIR) requirements for Operation's Management System (OMS) automation within the Space Station Freedom program. This shall be accomplished by developing a selected FDIR prototype for the Space Station Freedom distributed processing systems. The prototype shall be based on advanced automation methodologies in addition to traditional software methods to meet the requirements for automation. A secondary objective is to expand the scope of the prototyping to encompass multiple aspects of station-wide fault management (SWFM) as discussed in OMS requirements documentation.

  17. Automated Fluid Feature Extraction from Transient Simulations

    Science.gov (United States)

    Haimes, Robert

    2000-01-01

    In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense.

  18. Statistical Feature Extraction for Fault Locations in Nonintrusive Fault Detection of Low Voltage Distribution Systems

    Directory of Open Access Journals (Sweden)

    Hsueh-Hsien Chang

    2017-04-01

    Full Text Available This paper proposes statistical feature extraction methods combined with artificial intelligence (AI approaches for fault locations in non-intrusive single-line-to-ground fault (SLGF detection of low voltage distribution systems. The input features of the AI algorithms are extracted using statistical moment transformation for reducing the dimensions of the power signature inputs measured by using non-intrusive fault monitoring (NIFM techniques. The data required to develop the network are generated by simulating SLGF using the Electromagnetic Transient Program (EMTP in a test system. To enhance the identification accuracy, these features after normalization are given to AI algorithms for presenting and evaluating in this paper. Different AI techniques are then utilized to compare which identification algorithms are suitable to diagnose the SLGF for various power signatures in a NIFM system. The simulation results show that the proposed method is effective and can identify the fault locations by using non-intrusive monitoring techniques for low voltage distribution systems.

  19. FADES: A tool for automated fault analysis of complex systems

    International Nuclear Information System (INIS)

    Wood, C.

    1990-01-01

    FADES is an Expert System for performing fault analyses on complex connected systems. By using a graphical editor to draw components and link them together the FADES system allows the analyst to describe a given system. The knowledge base created is used to qualitatively simulate the system behaviour. By inducing all possible component failures in the system and determining their effects, a set of facts is built up. These facts are then used to create Fault Trees, or FMEA tables. The facts may also be used for explanation effects and to generate diagnostic rules allowing system instrumentation to be optimised. The prototype system has been built and tested and is preently undergoing testing by users. All comments from these trials will be used to tailor the system to the requirements of the user so that the end product performs the exact task required

  20. Automated Feature Extraction from Hyperspectral Imagery, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed activities will result in the development of a novel hyperspectral feature-extraction toolkit that will provide a simple, automated, and accurate...

  1. Component-based modeling of systems for automated fault tree generation

    International Nuclear Information System (INIS)

    Majdara, Aref; Wakabayashi, Toshio

    2009-01-01

    One of the challenges in the field of automated fault tree construction is to find an efficient modeling approach that can support modeling of different types of systems without ignoring any necessary details. In this paper, we are going to represent a new system of modeling approach for computer-aided fault tree generation. In this method, every system model is composed of some components and different types of flows propagating through them. Each component has a function table that describes its input-output relations. For the components having different operational states, there is also a state transition table. Each component can communicate with other components in the system only through its inputs and outputs. A trace-back algorithm is proposed that can be applied to the system model to generate the required fault trees. The system modeling approach and the fault tree construction algorithm are applied to a fire sprinkler system and the results are presented

  2. PLAT: An Automated Fault and Behavioural Anomaly Detection Tool for PLC Controlled Manufacturing Systems

    Directory of Open Access Journals (Sweden)

    Arup Ghosh

    2016-01-01

    Full Text Available Operational faults and behavioural anomalies associated with PLC control processes take place often in a manufacturing system. Real time identification of these operational faults and behavioural anomalies is necessary in the manufacturing industry. In this paper, we present an automated tool, called PLC Log-Data Analysis Tool (PLAT that can detect them by using log-data records of the PLC signals. PLAT automatically creates a nominal model of the PLC control process and employs a novel hash table based indexing and searching scheme to satisfy those purposes. Our experiments show that PLAT is significantly fast, provides real time identification of operational faults and behavioural anomalies, and can execute within a small memory footprint. In addition, PLAT can easily handle a large manufacturing system with a reasonable computing configuration and can be installed in parallel to the data logging system to identify operational faults and behavioural anomalies effectively.

  3. Sensor fault-tolerant control for gear-shifting engaging process of automated manual transmission

    Science.gov (United States)

    Li, Liang; He, Kai; Wang, Xiangyu; Liu, Yahui

    2018-01-01

    Angular displacement sensor on the actuator of automated manual transmission (AMT) is sensitive to fault, and the sensor fault will disturb its normal control, which affects the entire gear-shifting process of AMT and results in awful riding comfort. In order to solve this problem, this paper proposes a method of fault-tolerant control for AMT gear-shifting engaging process. By using the measured current of actuator motor and angular displacement of actuator, the gear-shifting engaging load torque table is built and updated before the occurrence of the sensor fault. Meanwhile, residual between estimated and measured angular displacements is used to detect the sensor fault. Once the residual exceeds a determined fault threshold, the sensor fault is detected. Then, switch control is triggered, and the current observer and load torque table estimates an actual gear-shifting position to replace the measured one to continue controlling the gear-shifting process. Numerical and experiment tests are carried out to evaluate the reliability and feasibility of proposed methods, and the results show that the performance of estimation and control is satisfactory.

  4. Automated feature extraction and classification from image sources

    Science.gov (United States)

    ,

    1995-01-01

    The U.S. Department of the Interior, U.S. Geological Survey (USGS), and Unisys Corporation have completed a cooperative research and development agreement (CRADA) to explore automated feature extraction and classification from image sources. The CRADA helped the USGS define the spectral and spatial resolution characteristics of airborne and satellite imaging sensors necessary to meet base cartographic and land use and land cover feature classification requirements and help develop future automated geographic and cartographic data production capabilities. The USGS is seeking a new commercial partner to continue automated feature extraction and classification research and development.

  5. Automated Generation of Fault Management Artifacts from a Simple System Model

    Science.gov (United States)

    Kennedy, Andrew K.; Day, John C.

    2013-01-01

    Our understanding of off-nominal behavior - failure modes and fault propagation - in complex systems is often based purely on engineering intuition; specific cases are assessed in an ad hoc fashion as a (fallible) fault management engineer sees fit. This work is an attempt to provide a more rigorous approach to this understanding and assessment by automating the creation of a fault management artifact, the Failure Modes and Effects Analysis (FMEA) through querying a representation of the system in a SysML model. This work builds off the previous development of an off-nominal behavior model for the upcoming Soil Moisture Active-Passive (SMAP) mission at the Jet Propulsion Laboratory. We further developed the previous system model to more fully incorporate the ideas of State Analysis, and it was restructured in an organizational hierarchy that models the system as layers of control systems while also incorporating the concept of "design authority". We present software that was developed to traverse the elements and relationships in this model to automatically construct an FMEA spreadsheet. We further discuss extending this model to automatically generate other typical fault management artifacts, such as Fault Trees, to efficiently portray system behavior, and depend less on the intuition of fault management engineers to ensure complete examination of off-nominal behavior.

  6. Deep Fault Recognizer: An Integrated Model to Denoise and Extract Features for Fault Diagnosis in Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Xiaojie Guo

    2016-12-01

    Full Text Available Fault diagnosis in rotating machinery is significant to avoid serious accidents; thus, an accurate and timely diagnosis method is necessary. With the breakthrough in deep learning algorithm, some intelligent methods, such as deep belief network (DBN and deep convolution neural network (DCNN, have been developed with satisfactory performances to conduct machinery fault diagnosis. However, only a few of these methods consider properly dealing with noises that exist in practical situations and the denoising methods are in need of extensive professional experiences. Accordingly, rethinking the fault diagnosis method based on deep architectures is essential. Hence, this study proposes an automatic denoising and feature extraction method that inherently considers spatial and temporal correlations. In this study, an integrated deep fault recognizer model based on the stacked denoising autoencoder (SDAE is applied to both denoise random noises in the raw signals and represent fault features in fault pattern diagnosis for both bearing rolling fault and gearbox fault, and trained in a greedy layer-wise fashion. Finally, the experimental validation demonstrates that the proposed method has better diagnosis accuracy than DBN, particularly in the existing situation of noises with superiority of approximately 7% in fault diagnosis accuracy.

  7. Automated tissue dissociation for rapid extraction of viable cells

    OpenAIRE

    McBeth, Christine; Gutermuth, Angela; Ochs, Jelena; Sharon, Andre; Sauer-Budge, Alexis F.

    2017-01-01

    Viable cells from healthy tissues are a rich resource in high demand for many next-generation therapeutics and regenerative medicine applications. Cell extraction from the dense connective matrix of most tissues is a labor-intensive task and high variability makes cGMP compliance difficult. To reduce costs and ensure greater reproducibility, automated tissue dissociators compatible with robotic liquid handling systems are required. Here we demonstrate the utility of our automated tissue disso...

  8. Automated valve fault detection based on acoustic emission parameters and support vector machine

    Directory of Open Access Journals (Sweden)

    Salah M. Ali

    2018-03-01

    Full Text Available Reciprocating compressors are one of the most used types of compressors with wide applications in industry. The most common failure in reciprocating compressors is always related to the valves. Therefore, a reliable condition monitoring method is required to avoid the unplanned shutdown in this category of machines. Acoustic emission (AE technique is one of the effective recent methods in the field of valve condition monitoring. However, a major challenge is related to the analysis of AE signal which perhaps only depends on the experience and knowledge of technicians. This paper proposes automated fault detection method using support vector machine (SVM and AE parameters in an attempt to reduce human intervention in the process. Experiments were conducted on a single stage reciprocating air compressor by combining healthy and faulty valve conditions to acquire the AE signals. Valve functioning was identified through AE waveform analysis. SVM faults detection model was subsequently devised and validated based on training and testing samples respectively. The results demonstrated automatic valve fault detection model with accuracy exceeding 98%. It is believed that valve faults can be detected efficiently without human intervention by employing the proposed model for a single stage reciprocating compressor. Keywords: Condition monitoring, Faults detection, Signal analysis, Acoustic emission, Support vector machine

  9. An automated and simple method for brain MR image extraction

    Directory of Open Access Journals (Sweden)

    Zhu Zixin

    2011-09-01

    Full Text Available Abstract Background The extraction of brain tissue from magnetic resonance head images, is an important image processing step for the analyses of neuroimage data. The authors have developed an automated and simple brain extraction method using an improved geometric active contour model. Methods The method uses an improved geometric active contour model which can not only solve the boundary leakage problem but also is less sensitive to intensity inhomogeneity. The method defines the initial function as a binary level set function to improve computational efficiency. The method is applied to both our data and Internet brain MR data provided by the Internet Brain Segmentation Repository. Results The results obtained from our method are compared with manual segmentation results using multiple indices. In addition, the method is compared to two popular methods, Brain extraction tool and Model-based Level Set. Conclusions The proposed method can provide automated and accurate brain extraction result with high efficiency.

  10. An Effective Fault Feature Extraction Method for Gas Turbine Generator System Diagnosis

    Directory of Open Access Journals (Sweden)

    Jian-Hua Zhong

    2016-01-01

    Full Text Available Fault diagnosis is very important to maintain the operation of a gas turbine generator system (GTGS in power plants, where any abnormal situations will interrupt the electricity supply. The fault diagnosis of the GTGS faces the main challenge that the acquired data, vibration or sound signals, contain a great deal of redundant information which extends the fault identification time and degrades the diagnostic accuracy. To improve the diagnostic performance in the GTGS, an effective fault feature extraction framework is proposed to solve the problem of the signal disorder and redundant information in the acquired signal. The proposed framework combines feature extraction with a general machine learning method, support vector machine (SVM, to implement an intelligent fault diagnosis. The feature extraction method adopts wavelet packet transform and time-domain statistical features to extract the features of faults from the vibration signal. To further reduce the redundant information in extracted features, kernel principal component analysis is applied in this study. Experimental results indicate that the proposed feature extracted technique is an effective method to extract the useful features of faults, resulting in improvement of the performance of fault diagnosis for the GTGS.

  11. Automated vasculature extraction from placenta images

    Science.gov (United States)

    Almoussa, Nizar; Dutra, Brittany; Lampe, Bryce; Getreuer, Pascal; Wittman, Todd; Salafia, Carolyn; Vese, Luminita

    2011-03-01

    Recent research in perinatal pathology argues that analyzing properties of the placenta may reveal important information on how certain diseases progress. One important property is the structure of the placental blood vessels, which supply a fetus with all of its oxygen and nutrition. An essential step in the analysis of the vascular network pattern is the extraction of the blood vessels, which has only been done manually through a costly and time-consuming process. There is no existing method to automatically detect placental blood vessels; in addition, the large variation in the shape, color, and texture of the placenta makes it difficult to apply standard edge-detection algorithms. We describe a method to automatically detect and extract blood vessels from a given image by using image processing techniques and neural networks. We evaluate several local features for every pixel, in addition to a novel modification to an existing road detector. Pixels belonging to blood vessel regions have recognizable responses; hence, we use an artificial neural network to identify the pattern of blood vessels. A set of images where blood vessels are manually highlighted is used to train the network. We then apply the neural network to recognize blood vessels in new images. The network is effective in capturing the most prominent vascular structures of the placenta.

  12. Automated Image Registration Using Morphological Region of Interest Feature Extraction

    Science.gov (United States)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2005-01-01

    With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

  13. Applications of the Automated SMAC Modal Parameter Extraction Package

    International Nuclear Information System (INIS)

    MAYES, RANDALL L.; DORRELL, LARRY R.; KLENKE, SCOTT E.

    1999-01-01

    An algorithm known as SMAC (Synthesize Modes And Correlate), based on principles of modal filtering, has been in development for a few years. The new capabilities of the automated version are demonstrated on test data from a complex shell/payload system. Examples of extractions from impact and shaker data are shown. The automated algorithm extracts 30 to 50 modes in the bandwidth from each column of the frequency response function matrix. Examples of the synthesized Mode Indicator Functions (MIFs) compared with the actual MIFs show the accuracy of the technique. A data set for one input and 170 accelerometer outputs can typically be reduced in an hour. Application to a test with some complex modes is also demonstrated

  14. Vibration Feature Extraction and Analysis for Fault Diagnosis of Rotating Machinery-A Literature Survey

    OpenAIRE

    Saleem Riaz; Hassan Elahi; Kashif Javaid; Tufail Shahzad

    2017-01-01

    Safety, reliability, efficiency and performance of rotating machinery in all industrial applications are the main concerns. Rotating machines are widely used in various industrial applications. Condition monitoring and fault diagnosis of rotating machinery faults are very important and often complex and labor-intensive. Feature extraction techniques play a vital role for a reliable, effective and efficient feature extraction for the diagnosis of rotating machinery. Therefore, deve...

  15. Fault Tolerant Control System Design Using Automated Methods from Risk Analysis

    DEFF Research Database (Denmark)

    Blanke, M.

    Fault tolerant controls have the ability to be resilient to simple faults in control loop components.......Fault tolerant controls have the ability to be resilient to simple faults in control loop components....

  16. Automated extraction of radiation dose information for CT examinations.

    Science.gov (United States)

    Cook, Tessa S; Zimmerman, Stefan; Maidment, Andrew D A; Kim, Woojin; Boonn, William W

    2010-11-01

    Exposure to radiation as a result of medical imaging is currently in the spotlight, receiving attention from Congress as well as the lay press. Although scanner manufacturers are moving toward including effective dose information in the Digital Imaging and Communications in Medicine headers of imaging studies, there is a vast repository of retrospective CT data at every imaging center that stores dose information in an image-based dose sheet. As such, it is difficult for imaging centers to participate in the ACR's Dose Index Registry. The authors have designed an automated extraction system to query their PACS archive and parse CT examinations to extract the dose information stored in each dose sheet. First, an open-source optical character recognition program processes each dose sheet and converts the information to American Standard Code for Information Interchange (ASCII) text. Each text file is parsed, and radiation dose information is extracted and stored in a database which can be queried using an existing pathology and radiology enterprise search tool. Using this automated extraction pipeline, it is possible to perform dose analysis on the >800,000 CT examinations in the PACS archive and generate dose reports for all of these patients. It is also possible to more effectively educate technologists, radiologists, and referring physicians about exposure to radiation from CT by generating report cards for interpreted and performed studies. The automated extraction pipeline enables compliance with the ACR's reporting guidelines and greater awareness of radiation dose to patients, thus resulting in improved patient care and management. Copyright © 2010 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  17. Vibration Feature Extraction and Analysis for Fault Diagnosis of Rotating Machinery-A Literature Survey

    Directory of Open Access Journals (Sweden)

    Saleem Riaz

    2017-02-01

    Full Text Available Safety, reliability, efficiency and performance of rotating machinery in all industrial applications are the main concerns. Rotating machines are widely used in various industrial applications. Condition monitoring and fault diagnosis of rotating machinery faults are very important and often complex and labor-intensive. Feature extraction techniques play a vital role for a reliable, effective and efficient feature extraction for the diagnosis of rotating machinery. Therefore, developing effective bearing fault diagnostic method using different fault features at different steps becomes more attractive. Bearings are widely used in medical applications, food processing industries, semi-conductor industries, paper making industries and aircraft components. This paper review has demonstrated that the latest reviews applied to rotating machinery on the available a variety of vibration feature extraction. Generally literature is classified into two main groups: frequency domain, time frequency analysis. However, fault detection and diagnosis of rotating machine vibration signal processing methods to present their own limitations. In practice, most healthy ingredients faulty vibration signal from background noise and mechanical vibration signals are buried. This paper also reviews that how the advanced signal processing methods, empirical mode decomposition and interference cancellation algorithm has been investigated and developed. The condition for rotating machines based rehabilitation, prevent failures increase the availability and reduce the cost of maintenance is becoming necessary too. Rotating machine fault detection and diagnostics in developing algorithms signal processing based on a key problem is the fault feature extraction or quantification. Currently, vibration signal, fault detection and diagnosis of rotating machinery based techniques most widely used techniques. Furthermore, the researchers are widely interested to make automatic

  18. Critical Evaluation of Validation Rules Automated Extraction from Data

    Directory of Open Access Journals (Sweden)

    David Pejcoch

    2014-10-01

    Full Text Available The goal of this article is to critically evaluate a possibility of automatic extraction of such kind of rules which could be later used within a Data Quality Management process for validation of records newly incoming to Information System. For practical demonstration the 4FT-Miner procedure implemented in LISpMiner System was chosen. A motivation for this task is the potential simplification of projects focused on Data Quality Management. Initially, this article is going to critically evaluate a possibility of fully automated extraction with the aim to identify strengths and weaknesses of this approach in comparison to its alternative, when at least some a priori knowledge is available. As a result of practical implementation, this article provides design of recommended process which would be used as a guideline for future projects. Also the question of how to store and maintain extracted rules and how to integrate them with existing tools supporting Data Quality Management is discussed

  19. Arduino-based automation of a DNA extraction system.

    Science.gov (United States)

    Kim, Kyung-Won; Lee, Mi-So; Ryu, Mun-Ho; Kim, Jong-Won

    2015-01-01

    There have been many studies to detect infectious diseases with the molecular genetic method. This study presents an automation process for a DNA extraction system based on microfluidics and magnetic bead, which is part of a portable molecular genetic test system. This DNA extraction system consists of a cartridge with chambers, syringes, four linear stepper actuators, and a rotary stepper actuator. The actuators provide a sequence of steps in the DNA extraction process, such as transporting, mixing, and washing for the gene specimen, magnetic bead, and reagent solutions. The proposed automation system consists of a PC-based host application and an Arduino-based controller. The host application compiles a G code sequence file and interfaces with the controller to execute the compiled sequence. The controller executes stepper motor axis motion, time delay, and input-output manipulation. It drives the stepper motor with an open library, which provides a smooth linear acceleration profile. The controller also provides a homing sequence to establish the motor's reference position, and hard limit checking to prevent any over-travelling. The proposed system was implemented and its functionality was investigated, especially regarding positioning accuracy and velocity profile.

  20. 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.

  1. A New Method for Weak Fault Feature Extraction Based on Improved MED

    Directory of Open Access Journals (Sweden)

    Junlin Li

    2018-01-01

    Full Text Available Because of the characteristics of weak signal and strong noise, the low-speed vibration signal fault feature extraction has been a hot spot and difficult problem in the field of equipment fault diagnosis. Moreover, the traditional minimum entropy deconvolution (MED method has been proved to be used to detect such fault signals. The MED uses objective function method to design the filter coefficient, and the appropriate threshold value should be set in the calculation process to achieve the optimal iteration effect. It should be pointed out that the improper setting of the threshold will cause the target function to be recalculated, and the resulting error will eventually affect the distortion of the target function in the background of strong noise. This paper presents an improved MED based method of fault feature extraction from rolling bearing vibration signals that originate in high noise environments. The method uses the shuffled frog leaping algorithm (SFLA, finds the set of optimal filter coefficients, and eventually avoids the artificial error influence of selecting threshold parameter. Therefore, the fault bearing under the two rotating speeds of 60 rpm and 70 rpm is selected for verification with typical low-speed fault bearing as the research object; the results show that SFLA-MED extracts more obvious bearings and has a higher signal-to-noise ratio than the prior MED method.

  2. Automated extraction of chemical structure information from digital raster images

    Science.gov (United States)

    Park, Jungkap; Rosania, Gus R; Shedden, Kerby A; Nguyen, Mandee; Lyu, Naesung; Saitou, Kazuhiro

    2009-01-01

    Background To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links to scientific research

  3. Automated extraction of chemical structure information from digital raster images

    Directory of Open Access Journals (Sweden)

    Shedden Kerby A

    2009-02-01

    Full Text Available Abstract Background To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links

  4. Diesel Engine Valve Clearance Fault Diagnosis Based on Features Extraction Techniques and FastICA-SVM

    Science.gov (United States)

    Jing, Ya-Bing; Liu, Chang-Wen; Bi, Feng-Rong; Bi, Xiao-Yang; Wang, Xia; Shao, Kang

    2017-07-01

    Numerous vibration-based techniques are rarely used in diesel engines fault diagnosis in a direct way, due to the surface vibration signals of diesel engines with the complex non-stationary and nonlinear time-varying features. To investigate the fault diagnosis of diesel engines, fractal correlation dimension, wavelet energy and entropy as features reflecting the diesel engine fault fractal and energy characteristics are extracted from the decomposed signals through analyzing vibration acceleration signals derived from the cylinder head in seven different states of valve train. An intelligent fault detector FastICA-SVM is applied for diesel engine fault diagnosis and classification. The results demonstrate that FastICA-SVM achieves higher classification accuracy and makes better generalization performance in small samples recognition. Besides, the fractal correlation dimension and wavelet energy and entropy as the special features of diesel engine vibration signal are considered as input vectors of classifier FastICA-SVM and could produce the excellent classification results. The proposed methodology improves the accuracy of feature extraction and the fault diagnosis of diesel engines.

  5. Automatic extraction of faults and fractal analysis from remote sensing data

    Directory of Open Access Journals (Sweden)

    R. Gloaguen

    2007-01-01

    Full Text Available Object-based classification is a promising technique for image classification. Unlike pixel-based methods, which only use the measured radiometric values, the object-based techniques can also use shape and context information of scene textures. These extra degrees of freedom provided by the objects allow the automatic identification of geological structures. In this article, we present an evaluation of object-based classification in the context of extraction of geological faults. Digital elevation models and radar data of an area near Lake Magadi (Kenya have been processed. We then determine the statistics of the fault populations. The fractal dimensions of fault dimensions are similar to fractal dimensions directly measured on remote sensing images of the study area using power spectra (PSD and variograms. These methods allow unbiased statistics of faults and help us to understand the evolution of the fault systems in extensional domains. Furthermore, the direct analysis of image texture is a good indicator of the fault statistics and allows us to classify the intensity and type of deformation. We propose that extensional fault networks can be modeled by iterative function system (IFS.

  6. Automated Extraction of Family History Information from Clinical Notes

    Science.gov (United States)

    Bill, Robert; Pakhomov, Serguei; Chen, Elizabeth S.; Winden, Tamara J.; Carter, Elizabeth W.; Melton, Genevieve B.

    2014-01-01

    Despite increased functionality for obtaining family history in a structured format within electronic health record systems, clinical notes often still contain this information. We developed and evaluated an Unstructured Information Management Application (UIMA)-based natural language processing (NLP) module for automated extraction of family history information with functionality for identifying statements, observations (e.g., disease or procedure), relative or side of family with attributes (i.e., vital status, age of diagnosis, certainty, and negation), and predication (“indicator phrases”), the latter of which was used to establish relationships between observations and family member. The family history NLP system demonstrated F-scores of 66.9, 92.4, 82.9, 57.3, 97.7, and 61.9 for detection of family history statements, family member identification, observation identification, negation identification, vital status, and overall extraction of the predications between family members and observations, respectively. While the system performed well for detection of family history statements and predication constituents, further work is needed to improve extraction of certainty and temporal modifications. PMID:25954443

  7. Automated extraction, labelling and analysis of the coronary vasculature from arteriograms

    NARCIS (Netherlands)

    Dumay, A.C.M.; Gerbrands, J.J.; Reiber, J.H.C.

    1996-01-01

    For clinical decision-making and documentation purposes we have developed techniques to extract, label and analyze the coronary vasculature from arteriograms in an automated, quantitative manner. Advanced image processing techniques were applied to extract and analyze the vasculatures from

  8. Text Mining approaches for automated literature knowledge extraction and representation.

    Science.gov (United States)

    Nuzzo, Angelo; Mulas, Francesca; Gabetta, Matteo; Arbustini, Eloisa; Zupan, Blaz; Larizza, Cristiana; Bellazzi, Riccardo

    2010-01-01

    Due to the overwhelming volume of published scientific papers, information tools for automated literature analysis are essential to support current biomedical research. We have developed a knowledge extraction tool to help researcher in discovering useful information which can support their reasoning process. The tool is composed of a search engine based on Text Mining and Natural Language Processing techniques, and an analysis module which process the search results in order to build annotation similarity networks. We tested our approach on the available knowledge about the genetic mechanism of cardiac diseases, where the target is to find both known and possible hypothetical relations between specific candidate genes and the trait of interest. We show that the system i) is able to effectively retrieve medical concepts and genes and ii) plays a relevant role assisting researchers in the formulation and evaluation of novel literature-based hypotheses.

  9. Multiple Fault Diagnosis Research on Motors in Aluminum Electrolytic Based on ICA Feature Extraction

    Directory of Open Access Journals (Sweden)

    Jiejia Li

    2014-08-01

    Full Text Available Motors as the actuator in the aluminum electrolysis process, mainly used for control the lifting of the anode to control the cell voltage, make the electrolytic tank keep in the best condition, once the motors failed, slot voltage will be out of control. This paper study on the fault of the motors in the process of aluminum electrolysis. In this paper adopts the EMD algorithm for various stator current signal data preprocessing, it has high adaptive decomposition ability and good ability, and then use the ICA algorithm extract feature of the current which has been denied. The extracted features input to the rough neural network for fault diagnosis and classification and gives the results of fault diagnosis. Through the simulation and analysis verify the feasibility and superiority of this model.

  10. Extraction of polychlorinated biphenyls from soils by automated focused microwave-assisted Soxhlet extraction.

    Science.gov (United States)

    Luque-García, J L; de Castro, Luque

    2003-05-23

    The application of a new focused microwave-assisted Soxhlet extractor for the extraction of polychlorinated biphenyls from differently aged soils is here presented. The new extractor overcomes the disadvantages of previous devices based on the same principle and enables a fully automated extraction of two samples simultaneously. The variables affecting the extraction step (namely, power of irradiation, irradiation time, extractant volume, extractant composition and number of extraction cycles) have been optimized using experimental design methodology. The optimized method has also been applied to a certified reference material (CRM910-050 "real" contaminated soil) for quality assurance validation. Quantification of the target compounds has been performed by GC with ion-trap MS. The mass spectrometer was operated in the electron-ionization mode, with selected-ion monitoring at m/z 152, 186, 292, 326 and 498. The results obtained have demonstrated that this approach is as efficient as conventional Soxhlet but with a drastic reduction of both extraction time (70 min vs. 24 h for the "real" contaminated soil) and organic solvent disposal, as 75-80% of the extractant is recycled.

  11. An Enhancement Deep Feature Extraction Method for Bearing Fault Diagnosis Based on Kernel Function and Autoencoder

    Directory of Open Access Journals (Sweden)

    Fengtao Wang

    2018-01-01

    Full Text Available Rotating machinery vibration signals are nonstationary and nonlinear under complicated operating conditions. It is meaningful to extract optimal features from raw signal and provide accurate fault diagnosis results. In order to resolve the nonlinear problem, an enhancement deep feature extraction method based on Gaussian radial basis kernel function and autoencoder (AE is proposed. Firstly, kernel function is employed to enhance the feature learning capability, and a new AE is designed termed kernel AE (KAE. Subsequently, a deep neural network is constructed with one KAE and multiple AEs to extract inherent features layer by layer. Finally, softmax is adopted as the classifier to accurately identify different bearing faults, and error backpropagation algorithm is used to fine-tune the model parameters. Aircraft engine intershaft bearing vibration data are used to verify the method. The results confirm that the proposed method has a better feature extraction capability, requires fewer iterations, and has a higher accuracy than standard methods using a stacked AE.

  12. Average combination difference morphological filters for fault feature extraction of bearing

    Science.gov (United States)

    Lv, Jingxiang; Yu, Jianbo

    2018-02-01

    In order to extract impulse components from vibration signals with much noise and harmonics, a new morphological filter called average combination difference morphological filter (ACDIF) is proposed in this paper. ACDIF constructs firstly several new combination difference (CDIF) operators, and then integrates the best two CDIFs as the final morphological filter. This design scheme enables ACIDF to extract positive and negative impacts existing in vibration signals to enhance accuracy of bearing fault diagnosis. The length of structure element (SE) that affects the performance of ACDIF is determined adaptively by a new indicator called Teager energy kurtosis (TEK). TEK further improves the effectiveness of ACDIF for fault feature extraction. Experimental results on the simulation and bearing vibration signals demonstrate that ACDIF can effectively suppress noise and extract periodic impulses from bearing vibration signals.

  13. Analysis of the relationship of automatically and manually extracted lineaments from DEM and geologically mapped tectonic faults around the Main Ethiopian Rift and the Ethiopian Highlands, Ethiopia

    Directory of Open Access Journals (Sweden)

    Michal Kusák

    2017-02-01

    Full Text Available The paper deals with the functions that automatically extract lineaments from the 90 m Shuttle Radar Topographic Mission (SRTM of Digital Elevation Model (DEM (Consortium for Spatial Information 2014 in the software ArcGIS 10.1 and PCI Geomatica. They were performed for the Main Ethiopian Rift and the Ethiopian Highlands (transregional scale 1,060,000 km2, which are one of the tectonically most active areas in the world. The values of input parameters – the RADI (filter radius value, GTHR (edge gradient threshold, LTHR (curve length, FTHR (line fitting error, ATHR (angular difference, and the DTHR (linked distance threshold – and their influence on the final shape and number of lineaments are discussed. A map of automated extracted lineaments was created and compared with 1 the tectonic faults on the geological map by Geological Survey of Ethiopia (Mangesha et al. 1996 and 2 the lineaments based on visual interpretation by the author from the same data set. The predominant azimuth of lineaments is similar to the azimuth of the faults on the geological map. The comparison of lineaments by automated visualization in GIS and visual interpretation of lineaments carried out by the authors around the Jemma River Basin (regional scale 16,000 km2 proved that both sets of lineaments are of the same NE–SW azimuth, which is the orientation of the rift. However, lineaments mapping by automated visualization in GIS identifies a larger number of shorter lineaments than lineaments created by visual interpretation.

  14. Automated fault diagnosis in nonlinear multivariable systems using a learning methodology.

    Science.gov (United States)

    Trunov, A B; Polycarpou, M M

    2000-01-01

    The paper presents a robust fault diagnosis scheme for detecting and approximating state and output faults occurring in a class of nonlinear multiinput-multioutput dynamical systems. Changes in the system dynamics due to a fault are modeled as nonlinear functions of the control input and measured output variables. Both state and output faults can be modeled as slowly developing (incipient) or abrupt, with each component of the state/output fault vector being represented by a separate time profile. The robust fault diagnosis scheme utilizes on-line approximators and adaptive nonlinear filtering techniques to obtain estimates of the fault functions. Robustness with respect to modeling uncertainties, fault sensitivity and stability properties of the learning scheme are rigorously derived and the theoretical results are illustrated by a simulation example of a fourth-order satellite model.

  15. Automated Extraction of Substance Use Information from Clinical Texts.

    Science.gov (United States)

    Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

    2015-01-01

    Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

  16. Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Jia Uddin

    2014-01-01

    Full Text Available This paper proposes a method for the reliable fault detection and classification of induction motors using two-dimensional (2D texture features and a multiclass support vector machine (MCSVM. The proposed model first converts time-domain vibration signals to 2D gray images, resulting in texture patterns (or repetitive patterns, and extracts these texture features by generating the dominant neighborhood structure (DNS map. The principal component analysis (PCA is then used for the purpose of dimensionality reduction of the high-dimensional feature vector including the extracted texture features due to the fact that the high-dimensional feature vector can degrade classification performance, and this paper configures an effective feature vector including discriminative fault features for diagnosis. Finally, the proposed approach utilizes the one-against-all (OAA multiclass support vector machines (MCSVMs to identify induction motor failures. In this study, the Gaussian radial basis function kernel cooperates with OAA MCSVMs to deal with nonlinear fault features. Experimental results demonstrate that the proposed approach outperforms three state-of-the-art fault diagnosis algorithms in terms of fault classification accuracy, yielding an average classification accuracy of 100% even in noisy environments.

  17. 28-day extended-duration orbiter automated fault detection, isolation, and recovery concept definition and proof-of-concept development

    Science.gov (United States)

    Rejai, B.; Zeilingold, D.; Rehagen, S.

    1992-01-01

    This paper describes concept definition and proof-of-concept development of an automated on-board fault detection, isolation, and reconfiguration (FDIR) system for the extended-duration orbiter (EDO). The EDO is a modified Shuttle orbiter that can perform 16- to 28-day missions. The design of EDO FDIR requires automating existing orbiter FDIR procedures while minimizing changes to existing hardware and software. Automation will be achieved by extensive use of expert system technology. Two software architectures, a fully distributed one and a hierarchical failure-driven one, were identified. The hierarchical failure-driven approach was selected for proof-of-concept development. Prototypes were developed for the power reactant storage and distribution and fuel cells subsystems to recognize, isolate, and provide reconfiguration instructions for a limited number of malfunctions.

  18. Natural Environment Modeling and Fault-Diagnosis for Automated Agricultural Vehicle

    DEFF Research Database (Denmark)

    Blas, Morten Rufus; Blanke, Mogens

    2008-01-01

    This paper presents results for an automatic navigation system for agricultural vehicles. The system uses stereo-vision, inertial sensors and GPS. Special emphasis has been placed on modeling the natural environment in conjunction with a fault-tolerant navigation system. The results are exemplified...... by an agricultural vehicle following cut grass (swath). It is demonstrated how faults in the system can be detected and diagnosed using state of the art techniques from fault-tolerant literature. Results in performing fault-diagnosis and fault accomodation are presented using real data....

  19. Manifold Learning with Self-Organizing Mapping for Feature Extraction of Nonlinear Faults in Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Lin Liang

    2015-01-01

    Full Text Available A new method for extracting the low-dimensional feature automatically with self-organization mapping manifold is proposed for the detection of rotating mechanical nonlinear faults (such as rubbing, pedestal looseness. Under the phase space reconstructed by single vibration signal, the self-organization mapping (SOM with expectation maximization iteration algorithm is used to divide the local neighborhoods adaptively without manual intervention. After that, the local tangent space alignment algorithm is adopted to compress the high-dimensional phase space into low-dimensional feature space. The proposed method takes advantages of the manifold learning in low-dimensional feature extraction and adaptive neighborhood construction of SOM and can extract intrinsic fault features of interest in two dimensional projection space. To evaluate the performance of the proposed method, the Lorenz system was simulated and rotation machinery with nonlinear faults was obtained for test purposes. Compared with the holospectrum approaches, the results reveal that the proposed method is superior in identifying faults and effective for rotating machinery condition monitoring.

  20. Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

    International Nuclear Information System (INIS)

    Wang, M; Hu, N Q; Qin, G J

    2011-01-01

    In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

  1. Evaluation of Four Automated Protocols for Extraction of DNA from FTA Cards

    DEFF Research Database (Denmark)

    Stangegaard, Michael; Børsting, Claus; Ferrero-Miliani, Laura

    2013-01-01

    Extraction of DNA using magnetic bead-based techniques on automated DNA extraction instruments provides a fast, reliable, and reproducible method for DNA extraction from various matrices. Here, we have compared the yield and quality of DNA extracted from FTA cards using four automated extraction...... protocols on three different instruments. The extraction processes were repeated up to six times with the same pieces of FTA cards. The sample material on the FTA cards was either blood or buccal cells. With the QIAamp DNA Investigator and QIAsymphony DNA Investigator kits, it was possible to extract DNA...... from the FTA cards in all six rounds of extractions in sufficient amount and quality to obtain complete short tandem repeat (STR) profiles on a QIAcube and a QIAsymphony SP. With the PrepFiler Express kit, almost all the extractable DNA was extracted in the first two rounds of extractions. Furthermore...

  2. GNAR-GARCH model and its application in feature extraction for rolling bearing fault diagnosis

    Science.gov (United States)

    Ma, Jiaxin; Xu, Feiyun; Huang, Kai; Huang, Ren

    2017-09-01

    Given its simplicity of modeling and sensitivity to condition variations, time series model is widely used in feature extraction to realize fault classification and diagnosis. However, nonlinear and nonstationary characteristics common in fault signals of rolling bearing bring challenges to the diagnosis. In this paper, a hybrid model, the combination of a general expression for linear and nonlinear autoregressive (GNAR) model and a generalized autoregressive conditional heteroscedasticity (GARCH) model, (i.e., GNAR-GARCH), is proposed and applied to rolling bearing fault diagnosis. An exact expression of GNAR-GARCH model is given. Maximum likelihood method is used for parameter estimation and modified Akaike Information Criterion is adopted for structure identification of GNAR-GARCH model. The main advantage of this novel model over other models is that the combination makes the model suitable for nonlinear and nonstationary signals. It is verified with statistical tests that contain comparisons among the different time series models. Finally, GNAR-GARCH model is applied to fault diagnosis by modeling mechanical vibration signals including simulation and real data. With the parameters estimated and taken as feature vectors, k-nearest neighbor algorithm is utilized to realize the classification of fault status. The results show that GNAR-GARCH model exhibits higher accuracy and better performance than do other models.

  3. Anti-aliasing lifting scheme for mechanical vibration fault feature extraction

    Science.gov (United States)

    Bao, Wen; Zhou, Rui; Yang, Jianguo; Yu, Daren; Li, Ning

    2009-07-01

    A troublesome problem in application of wavelet transform for mechanical vibration fault feature extraction is frequency aliasing. In this paper, an anti-aliasing lifting scheme is proposed to solve this problem. With this method, the input signal is firstly transformed by a redundant lifting scheme to avoid the aliasing caused by split and merge operations. Then the resultant coefficients and their single subband reconstructed signals are further processed to remove the aliasing caused by the unideal frequency property of lifting filters based on the fast Fourier transform (FFT) technique. Because the aliasing in each subband signal is eliminated, the ratio of signal to noise (SNR) is improved. The anti-aliasing lifting scheme is applied to analyze a practical vibration signal measured from a faulty ball bearing and testing results confirm that the proposed method is effective for extracting weak fault feature from a complex background. The proposed method is also applied to the fault diagnosis of valve trains in different working conditions on a gasoline engine. The experimental results show that using the features extracted from the anti-aliasing lifting scheme for classification can obtain a higher accuracy than using those extracted from the lifting scheme and the redundant lifting scheme.

  4. Feature extraction of kernel regress reconstruction for fault diagnosis based on self-organizing manifold learning

    Science.gov (United States)

    Chen, Xiaoguang; Liang, Lin; Xu, Guanghua; Liu, Dan

    2013-09-01

    The feature space extracted from vibration signals with various faults is often nonlinear and of high dimension. Currently, nonlinear dimensionality reduction methods are available for extracting low-dimensional embeddings, such as manifold learning. However, these methods are all based on manual intervention, which have some shortages in stability, and suppressing the disturbance noise. To extract features automatically, a manifold learning method with self-organization mapping is introduced for the first time. Under the non-uniform sample distribution reconstructed by the phase space, the expectation maximization(EM) iteration algorithm is used to divide the local neighborhoods adaptively without manual intervention. After that, the local tangent space alignment(LTSA) algorithm is adopted to compress the high-dimensional phase space into a more truthful low-dimensional representation. Finally, the signal is reconstructed by the kernel regression. Several typical states include the Lorenz system, engine fault with piston pin defect, and bearing fault with outer-race defect are analyzed. Compared with the LTSA and continuous wavelet transform, the results show that the background noise can be fully restrained and the entire periodic repetition of impact components is well separated and identified. A new way to automatically and precisely extract the impulsive components from mechanical signals is proposed.

  5. Integrating angle-frequency domain synchronous averaging technique with feature extraction for gear fault diagnosis

    Science.gov (United States)

    Zhang, Shengli; Tang, J.

    2018-01-01

    Gear fault diagnosis relies heavily on the scrutiny of vibration responses measured. In reality, gear vibration signals are noisy and dominated by meshing frequencies as well as their harmonics, which oftentimes overlay the fault related components. Moreover, many gear transmission systems, e.g., those in wind turbines, constantly operate under non-stationary conditions. To reduce the influences of non-synchronous components and noise, a fault signature enhancement method that is built upon angle-frequency domain synchronous averaging is developed in this paper. Instead of being averaged in the time domain, the signals are processed in the angle-frequency domain to solve the issue of phase shifts between signal segments due to uncertainties caused by clearances, input disturbances, and sampling errors, etc. The enhanced results are then analyzed through feature extraction algorithms to identify the most distinct features for fault classification and identification. Specifically, Kernel Principal Component Analysis (KPCA) targeting at nonlinearity, Multilinear Principal Component Analysis (MPCA) targeting at high dimensionality, and Locally Linear Embedding (LLE) targeting at local similarity among the enhanced data are employed and compared to yield insights. Numerical and experimental investigations are performed, and the results reveal the effectiveness of angle-frequency domain synchronous averaging in enabling feature extraction and classification.

  6. Automated Fault Diagnostics, Prognostics, and Recovery in Spacecraft Power Systems, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Fault detection and isolation (FDI) in spacecraft's electrical power system (EPS) has always received special attention. However, the power systems health management...

  7. Automated concept and relationship extraction for the semi-automated ontology management (SEAM) system.

    Science.gov (United States)

    Doing-Harris, Kristina; Livnat, Yarden; Meystre, Stephane

    2015-01-01

    We develop medical-specialty specific ontologies that contain the settled science and common term usage. We leverage current practices in information and relationship extraction to streamline the ontology development process. Our system combines different text types with information and relationship extraction techniques in a low overhead modifiable system. Our SEmi-Automated ontology Maintenance (SEAM) system features a natural language processing pipeline for information extraction. Synonym and hierarchical groups are identified using corpus-based semantics and lexico-syntactic patterns. The semantic vectors we use are term frequency by inverse document frequency and context vectors. Clinical documents contain the terms we want in an ontology. They also contain idiosyncratic usage and are unlikely to contain the linguistic constructs associated with synonym and hierarchy identification. By including both clinical and biomedical texts, SEAM can recommend terms from those appearing in both document types. The set of recommended terms is then used to filter the synonyms and hierarchical relationships extracted from the biomedical corpus. We demonstrate the generality of the system across three use cases: ontologies for acute changes in mental status, Medically Unexplained Syndromes, and echocardiogram summary statements. Across the three uses cases, we held the number of recommended terms relatively constant by changing SEAM's parameters. Experts seem to find more than 300 recommended terms to be overwhelming. The approval rate of recommended terms increased as the number and specificity of clinical documents in the corpus increased. It was 60% when there were 199 clinical documents that were not specific to the ontology domain and 90% when there were 2879 documents very specific to the target domain. We found that fewer than 100 recommended synonym groups were also preferred. Approval rates for synonym recommendations remained low varying from 43% to 25% as the

  8. Automated video feature extraction : workshop summary report October 10-11 2012.

    Science.gov (United States)

    2012-12-01

    This report summarizes a 2-day workshop on automated video feature extraction. Discussion focused on the Naturalistic Driving : Study, funded by the second Strategic Highway Research Program, and also involved the companion roadway inventory dataset....

  9. Ecological interface design : supporting fault diagnosis of automated advice in a supervisory air traffic control task

    NARCIS (Netherlands)

    Borst, C.; Bijsterbosch, V.A.; van Paassen, M.M.; Mulder, M.

    2017-01-01

    Future air traffic control will have to rely on more advanced automation to support human controllers in their job of safely handling increased traffic volumes. A prerequisite for the success of such automation is that the data driving it are reliable. Current technology, however, still warrants

  10. Bearing fault diagnosis under unknown time-varying rotational speed conditions via multiple time-frequency curve extraction

    Science.gov (United States)

    Huang, Huan; Baddour, Natalie; Liang, Ming

    2018-02-01

    Under normal operating conditions, bearings often run under time-varying rotational speed conditions. Under such circumstances, the bearing vibrational signal is non-stationary, which renders ineffective the techniques used for bearing fault diagnosis under constant running conditions. One of the conventional methods of bearing fault diagnosis under time-varying speed conditions is resampling the non-stationary signal to a stationary signal via order tracking with the measured variable speed. With the resampled signal, the methods available for constant condition cases are thus applicable. However, the accuracy of the order tracking is often inadequate and the time-varying speed is sometimes not measurable. Thus, resampling-free methods are of interest for bearing fault diagnosis under time-varying rotational speed for use without tachometers. With the development of time-frequency analysis, the time-varying fault character manifests as curves in the time-frequency domain. By extracting the Instantaneous Fault Characteristic Frequency (IFCF) from the Time-Frequency Representation (TFR) and converting the IFCF, its harmonics, and the Instantaneous Shaft Rotational Frequency (ISRF) into straight lines, the bearing fault can be detected and diagnosed without resampling. However, so far, the extraction of the IFCF for bearing fault diagnosis is mostly based on the assumption that at each moment the IFCF has the highest amplitude in the TFR, which is not always true. Hence, a more reliable T-F curve extraction approach should be investigated. Moreover, if the T-F curves including the IFCF, its harmonic, and the ISRF can be all extracted from the TFR directly, no extra processing is needed for fault diagnosis. Therefore, this paper proposes an algorithm for multiple T-F curve extraction from the TFR based on a fast path optimization which is more reliable for T-F curve extraction. Then, a new procedure for bearing fault diagnosis under unknown time-varying speed

  11. Extraction of repetitive transients with frequency domain multipoint kurtosis for bearing fault diagnosis

    Science.gov (United States)

    Liao, Yuhe; Sun, Peng; Wang, Baoxiang; Qu, Lei

    2018-05-01

    The appearance of repetitive transients in a vibration signal is one typical feature of faulty rolling element bearings. However, accurate extraction of these fault-related characteristic components has always been a challenging task, especially when there is interference from large amplitude impulsive noises. A frequency domain multipoint kurtosis (FDMK)-based fault diagnosis method is proposed in this paper. The multipoint kurtosis is redefined in the frequency domain and the computational accuracy is improved. An envelope autocorrelation function is also presented to estimate the fault characteristic frequency, which is used to set the frequency hunting zone of the FDMK. Then, the FDMK, instead of kurtosis, is utilized to generate a fast kurtogram and only the optimal band with maximum FDMK value is selected for envelope analysis. Negative interference from both large amplitude impulsive noise and shaft rotational speed related harmonic components are therefore greatly reduced. The analysis results of simulation and experimental data verify the capability and feasibility of this FDMK-based method

  12. Sparse representation based on local time-frequency template matching for bearing transient fault feature extraction

    Science.gov (United States)

    He, Qingbo; Ding, Xiaoxi

    2016-05-01

    The transients caused by the localized fault are important measurement information for bearing fault diagnosis. Thus it is crucial to extract the transients from the bearing vibration or acoustic signals that are always corrupted by a large amount of background noise. In this paper, an iterative transient feature extraction approach is proposed based on time-frequency (TF) domain sparse representation. The approach is realized by presenting a new method, called local TF template matching. In this method, the TF atoms are constructed based on the TF distribution (TFD) of the Morlet wavelet bases and local TF templates are formulated from the TF atoms for the matching process. The instantaneous frequency (IF) ridge calculated from the TFD of an analyzed signal provides the frequency parameter values for the TF atoms as well as an effective template matching path on the TF plane. In each iteration, local TF templates are employed to do correlation with the TFD of the analyzed signal along the IF ridge tube for identifying the optimum parameters of transient wavelet model. With this iterative procedure, transients can be extracted in the TF domain from measured signals one by one. The final signal can be synthesized by combining the extracted TF atoms and the phase of the raw signal. The local TF template matching builds an effective TF matching-based sparse representation approach with the merit of satisfying the native pulse waveform structure of transients. The effectiveness of the proposed method is verified by practical defective bearing signals. Comparison results also show that the proposed method is superior to traditional methods in transient feature extraction.

  13. Disposable and removable nucleic acid extraction and purification cartridges for automated flow-through systems

    Science.gov (United States)

    Regan, John Frederick

    2014-09-09

    Removable cartridges are used on automated flow-through systems for the purpose of extracting and purifying genetic material from complex matrices. Different types of cartridges are paired with specific automated protocols to concentrate, extract, and purifying pathogenic or human genetic material. Their flow-through nature allows large quantities sample to be processed. Matrices may be filtered using size exclusion and/or affinity filters to concentrate the pathogen of interest. Lysed material is ultimately passed through a filter to remove the insoluble material before the soluble genetic material is delivered past a silica-like membrane that binds the genetic material, where it is washed, dried, and eluted. Cartridges are inserted into the housing areas of flow-through automated instruments, which are equipped with sensors to ensure proper placement and usage of the cartridges. Properly inserted cartridges create fluid- and air-tight seals with the flow lines of an automated instrument.

  14. Evaluation of four automated protocols for extraction of DNA from FTA cards.

    Science.gov (United States)

    Stangegaard, Michael; Børsting, Claus; Ferrero-Miliani, Laura; Frank-Hansen, Rune; Poulsen, Lena; Hansen, Anders J; Morling, Niels

    2013-10-01

    Extraction of DNA using magnetic bead-based techniques on automated DNA extraction instruments provides a fast, reliable, and reproducible method for DNA extraction from various matrices. Here, we have compared the yield and quality of DNA extracted from FTA cards using four automated extraction protocols on three different instruments. The extraction processes were repeated up to six times with the same pieces of FTA cards. The sample material on the FTA cards was either blood or buccal cells. With the QIAamp DNA Investigator and QIAsymphony DNA Investigator kits, it was possible to extract DNA from the FTA cards in all six rounds of extractions in sufficient amount and quality to obtain complete short tandem repeat (STR) profiles on a QIAcube and a QIAsymphony SP. With the PrepFiler Express kit, almost all the extractable DNA was extracted in the first two rounds of extractions. Furthermore, we demonstrated that it was possible to successfully extract sufficient DNA for STR profiling from previously processed FTA card pieces that had been stored at 4 °C for up to 1 year. This showed that rare or precious FTA card samples may be saved for future analyses even though some DNA was already extracted from the FTA cards.

  15. Automated serial extraction of DNA and RNA from biobanked tissue specimens

    OpenAIRE

    Mathot, Lucy; Wallin, Monica; Sjöblom, Tobias

    2013-01-01

    Background: With increasing biobanking of biological samples, methods for large scale extraction of nucleic acids are in demand. The lack of such techniques designed for extraction from tissues results in a bottleneck in downstream genetic analyses, particularly in the field of cancer research. We have developed an automated procedure for tissue homogenization and extraction of DNA and RNA into separate fractions from the same frozen tissue specimen. A purpose developed magnetic bead based te...

  16. Automated serial extraction of DNA and RNA from biobanked tissue specimens.

    Science.gov (United States)

    Mathot, Lucy; Wallin, Monica; Sjöblom, Tobias

    2013-08-19

    With increasing biobanking of biological samples, methods for large scale extraction of nucleic acids are in demand. The lack of such techniques designed for extraction from tissues results in a bottleneck in downstream genetic analyses, particularly in the field of cancer research. We have developed an automated procedure for tissue homogenization and extraction of DNA and RNA into separate fractions from the same frozen tissue specimen. A purpose developed magnetic bead based technology to serially extract both DNA and RNA from tissues was automated on a Tecan Freedom Evo robotic workstation. 864 fresh-frozen human normal and tumor tissue samples from breast and colon were serially extracted in batches of 96 samples. Yields and quality of DNA and RNA were determined. The DNA was evaluated in several downstream analyses, and the stability of RNA was determined after 9 months of storage. The extracted DNA performed consistently well in processes including PCR-based STR analysis, HaloPlex selection and deep sequencing on an Illumina platform, and gene copy number analysis using microarrays. The RNA has performed well in RT-PCR analyses and maintains integrity upon storage. The technology described here enables the processing of many tissue samples simultaneously with a high quality product and a time and cost reduction for the user. This reduces the sample preparation bottleneck in cancer research. The open automation format also enables integration with upstream and downstream devices for automated sample quantitation or storage.

  17. The evaluation of a concept for a Canadian-made automated multipurpose materials extraction facility

    Science.gov (United States)

    Kleinberg, H.

    Long-term habitation of space will eventually require use of off-Earth resources to reduce long-term program costs and risks to personnel and equipment due to launch from Earth. Extraction of oxygen from lunar soil is a prime example. Processes currently under study for such activities focus on the extraction of only one element / chemical from one type of soil on one world, and they produce large amounts of waste material. This paper presents the results of an examination by Spar Aerospace of a plasma separation concept as part of a materials extraction facility that might be used in space. Such a process has the far-reaching potential for extracting any or all of the elements available in soil samples, extraction of oxygen from lunar soil being the near-term application. Plasma separation has the potential for a 100 percent yield of extracted elements from input samples, and the versatility to be used on many non-terrestrial sites for the extraction of available elemental resources. The development of new materials extraction processes for each world would thus be eliminated. Such a facility could also reduce the generation of waste products by decomposing soil samples into pure, stable elements. Robotics, automation, and a plasma separation facility could be used to gather, prepare, process, separate, collect and ship the available chemical elements. The following topics are discussed: automated soil-gathering using robotics; automated soil pre-processing; plasma dissociation and separation of soil, and collection of sorted elements in an automated process; containment of gases, storage of pure elements, metals; and automated shipment of materials to a manned base, or pick-up site.

  18. Automated fault detection and classification of etch systems using modular neural networks

    Science.gov (United States)

    Hong, Sang J.; May, Gary S.; Yamartino, John; Skumanich, Andrew

    2004-04-01

    Modular neural networks (MNNs) are investigated as a tool for modeling process behavior and fault detection and classification (FDC) using tool data in plasma etching. Principal component analysis (PCA) is initially employed to reduce the dimensionality of the voluminous multivariate tool data and to establish relationships between the acquired data and the process state. MNNs are subsequently used to identify anomalous process behavior. A gradient-based fuzzy C-means clustering algorithm is implemented to enhance MNN performance. MNNs for eleven individual steps of etch runs are trained with data acquired from baseline, control (acceptable), and perturbed (unacceptable) runs, and then tested with data not used for training. In the fault identification phase, a 0% of false alarm rate for the control runs is achieved.

  19. Basic methods for automated fault detection and energy data validation in existing district heating systems

    OpenAIRE

    Sandin, Fredrik; Gustafsson, Jonas; Delsing, Jerker; Eklund, Robert

    2012-01-01

    Fault detection and diagnostics (FDD) of district heating substations (DHS) are important activities because malfunctioning components can lead to incorrect billing and waste of energy. Although FDD has been an activate research area for nearly two decades, only a few simple tools are commonly deployed in the district energy industry. Some of the methods proposed in the literature are promising, but their complexity may prevent broader application. Other methods require sensor data that are n...

  20. Fully Automated Electro Membrane Extraction Autosampler for LC-MS Systems Allowing Soft Extractions for High-Throughput Applications

    DEFF Research Database (Denmark)

    Fuchs, David; Pedersen-Bjergaard, Stig; Jensen, Henrik

    2016-01-01

    was optimized for soft extraction of analytes and high sample throughput. Further, it was demonstrated that by flushing the EME-syringe with acidic wash buffer and reverting the applied electric potential, carry-over between samples can be reduced to below 1%. Performance of the system was characterized (RSD......, a complete analytical workflow of purification, separation, and analysis of sample could be achieved within only 5.5 min. With the developed system large sequences of samples could be analyzed in a completely automated manner. This high degree of automation makes the developed EME-autosampler a powerful tool...

  1. Feature Extraction and Selection Strategies for Automated Target Recognition

    Science.gov (United States)

    Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

    2010-01-01

    Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

  2. Automating Information Extraction from 3-D Scan Data

    National Research Council Canada - National Science Library

    Bradtmiller, Bruce

    1998-01-01

    ... and 7.2, newly developed software for extracting body measurements from 3-D scans. Investigators used traditional methods to measure 123 male and female subjects for 21 dimensions associated with the sizing and design of military clothing...

  3. Adaptive Redundant Lifting Wavelet Transform Based on Fitting for Fault Feature Extraction of Roller Bearings

    Directory of Open Access Journals (Sweden)

    Huaqing Wang

    2012-03-01

    Full Text Available A least square method based on data fitting is proposed to construct a new lifting wavelet, together with the nonlinear idea and redundant algorithm, the adaptive redundant lifting transform based on fitting is firstly stated in this paper. By variable combination selections of basis function, sample number and dimension of basis function, a total of nine wavelets with different characteristics are constructed, which are respectively adopted to perform redundant lifting wavelet transforms on low-frequency approximate signals at each layer. Then the normalized lP norms of the new node-signal obtained through decomposition are calculated to adaptively determine the optimal wavelet for the decomposed approximate signal. Next, the original signal is taken for subsection power spectrum analysis to choose the node-signal for single branch reconstruction and demodulation. Experiment signals and engineering signals are respectively used to verify the above method and the results show that bearing faults can be diagnosed more effectively by the method presented here than by both spectrum analysis and demodulation analysis. Meanwhile, compared with the symmetrical wavelets constructed with Lagrange interpolation algorithm, the asymmetrical wavelets constructed based on data fitting are more suitable in feature extraction of fault signal of roller bearings.

  4. Automated extraction of DNA and PCR setup using a Tecan Freedom EVO® liquid handler

    DEFF Research Database (Denmark)

    Frøslev, Tobias Guldberg; Hansen, Anders Johannes; Stangegaard, Michael

    2009-01-01

    We have implemented and validated automated protocols for DNA extraction and PCR setup using a Tecan Freedom EVO® liquid handler mounted with the TeMagS magnetic separation device. The methods were validated for accredited, forensic genetic work according to ISO 17025 using the Qiagen Mag...

  5. Repetitive transient extraction for machinery fault diagnosis using multiscale fractional order entropy infogram

    Science.gov (United States)

    Xu, Xuefang; Qiao, Zijian; Lei, Yaguo

    2018-03-01

    The presence of repetitive transients in vibration signals is a typical symptom of local faults of rotating machinery. Infogram was developed to extract the repetitive transients from vibration signals based on Shannon entropy. Unfortunately, the Shannon entropy is maximized for random processes and unable to quantify the repetitive transients buried in heavy random noise. In addition, the vibration signals always contain multiple intrinsic oscillatory modes due to interaction and coupling effects between machine components. Under this circumstance, high values of Shannon entropy appear in several frequency bands or high value of Shannon entropy doesn't appear in the optimal frequency band, and the infogram becomes difficult to interpret. Thus, it also becomes difficult to select the optimal frequency band for extracting the repetitive transients from the whole frequency bands. To solve these problems, multiscale fractional order entropy (MSFE) infogram is proposed in this paper. With the help of MSFE infogram, the complexity and nonlinear signatures of the vibration signals can be evaluated by quantifying spectral entropy over a range of scales in fractional domain. Moreover, the similarity tolerance of MSFE infogram is helpful for assessing the regularity of signals. A simulation and two experiments concerning a locomotive bearing and a wind turbine gear are used to validate the MSFE infogram. The results demonstrate that the MSFE infogram is more robust to the heavy noise than infogram and the high value is able to only appear in the optimal frequency band for the repetitive transient extraction.

  6. Towards automated support for extraction of reusable components

    Science.gov (United States)

    Abd-El-hafiz, S. K.; Basili, Victor R.; Caldiera, Gianluigi

    1992-01-01

    A cost effective introduction of software reuse techniques requires the reuse of existing software developed in many cases without aiming at reusability. This paper discusses the problems related to the analysis and reengineering of existing software in order to reuse it. We introduce a process model for component extraction and focus on the problem of analyzing and qualifying software components which are candidates for reuse. A prototype tool for supporting the extraction of reusable components is presented. One of the components of this tool aids in understanding programs and is based on the functional model of correctness. It can assist software engineers in the process of finding correct formal specifications for programs. A detailed description of this component and an example to demonstrate a possible operational scenario are given.

  7. Automated extraction protocol for quantification of SARS-Coronavirus RNA in serum: an evaluation study

    Directory of Open Access Journals (Sweden)

    Lui Wing-bong

    2006-02-01

    Full Text Available Abstract Background We have previously developed a test for the diagnosis and prognostic assessment of the severe acute respiratory syndrome (SARS based on the detection of the SARS-coronavirus RNA in serum by real-time quantitative reverse transcriptase polymerase chain reaction (RT-PCR. In this study, we evaluated the feasibility of automating the serum RNA extraction procedure in order to increase the throughput of the assay. Methods An automated nucleic acid extraction platform using the MagNA Pure LC instrument (Roche Diagnostics was evaluated. We developed a modified protocol in compliance with the recommended biosafety guidelines from the World Health Organization based on the use of the MagNA Pure total nucleic acid large volume isolation kit for the extraction of SARS-coronavirus RNA. The modified protocol was compared with a column-based extraction kit (QIAamp viral RNA mini kit, Qiagen for quantitative performance, analytical sensitivity and precision. Results The newly developed automated protocol was shown to be free from carry-over contamination and have comparable performance with other standard protocols and kits designed for the MagNA Pure LC instrument. However, the automated method was found to be less sensitive, less precise and led to consistently lower serum SARS-coronavirus concentrations when compared with the column-based extraction method. Conclusion As the diagnostic efficiency and prognostic value of the serum SARS-CoV RNA RT-PCR test is critically associated with the analytical sensitivity and quantitative performance contributed both by the RNA extraction and RT-PCR components of the test, we recommend the use of the column-based manual RNA extraction method.

  8. Automated extraction of metastatic liver cancer regions from abdominal contrast CT images

    International Nuclear Information System (INIS)

    Yamakawa, Junki; Matsubara, Hiroaki; Kimura, Shouta; Hasegawa, Junichi; Shinozaki, Kenji; Nawano, Shigeru

    2010-01-01

    In this paper, automated extraction of metastatic liver cancer regions from abdominal contrast X-ray CT images is investigated. Because even in Japan, cases of metastatic liver cancers are increased due to recent Europeanization and/or Americanization of Japanese eating habits, development of a system for computer aided diagnosis of them is strongly expected. Our automated extraction procedure consists of following four steps; liver region extraction, density transformation for enhancement of cancer regions, segmentation for obtaining candidate cancer regions, and reduction of false positives by shape feature. Parameter values used in each step of the procedure are decided based on density and shape features of typical metastatic liver cancers. In experiments using practical 20 cases of metastatic liver tumors, it is shown that 56% of true cancers can be detected successfully from CT images by the proposed procedure. (author)

  9. Automated extraction of lexical meanings from Polish corpora: potentialities and limitations

    Directory of Open Access Journals (Sweden)

    Maciej Piasecki

    2015-11-01

    Full Text Available Automated extraction of lexical meanings from Polish corpora: potentialities and limitations Large corpora are often consulted by linguists as a knowledge source with respect to lexicon, morphology or syntax. However, there are also several methods of automated extraction of semantic properties of language units from corpora. In the paper we focus on emerging potentialities of these methods, as well as on their identified limitations. Evidence that can be collected from corpora is confronted with the existing models of formalised description of lexical meanings. Two basic paradigms of lexical semantics extraction are briefly described. Their properties are analysed on the basis of several experiments performed on Polish corpora. Several potential applications of the methods, including a system supporting expansion of a Polish wordnet, are discussed. Finally, perspectives on the potential further development are discussed.

  10. Highly efficient automated extraction of DNA from old and contemporary skeletal remains.

    Science.gov (United States)

    Zupanič Pajnič, Irena; Debska, Magdalena; Gornjak Pogorelc, Barbara; Vodopivec Mohorčič, Katja; Balažic, Jože; Zupanc, Tomaž; Štefanič, Borut; Geršak, Ksenija

    2016-01-01

    We optimised the automated extraction of DNA from old and contemporary skeletal remains using the AutoMate Express system and the PrepFiler BTA kit. 24 Contemporary and 25 old skeletal remains from WWII were analysed. For each skeleton, extraction using only 0.05 g of powder was performed according to the manufacturer's recommendations (no demineralisation - ND method). Since only 32% of full profiles were obtained from aged and 58% from contemporary casework skeletons, the extraction protocol was modified to acquire higher quality DNA and genomic DNA was obtained after full demineralisation (FD method). The nuclear DNA of the samples was quantified using the Investigator Quantiplex kit and STR typing was performed using the NGM kit to evaluate the performance of tested extraction methods. In the aged DNA samples, 64% of full profiles were obtained using the FD method. For the contemporary skeletal remains the performance of the ND method was closer to the FD method compared to the old skeletons, giving 58% of full profiles with the ND method and 71% of full profiles using the FD method. The extraction of DNA from only 0.05 g of bone or tooth powder using the AutoMate Express has proven highly successful in the recovery of DNA from old and contemporary skeletons, especially with the modified FD method. We believe that the results obtained will contribute to the possibilities of using automated devices for extracting DNA from skeletal remains, which would shorten the procedures for obtaining high-quality DNA from skeletons in forensic laboratories. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  11. Active learning: a step towards automating medical concept extraction.

    Science.gov (United States)

    Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

    2016-03-01

    This paper presents an automatic, active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort and (2) the robustness of incremental active learning framework across different selection criteria and data sets are determined. The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional random fields as the supervised method, and least confidence and information density as 2 selection criteria for active learning framework were used. The effect of incremental learning vs standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. The following 2 clinical data sets were used for evaluation: the Informatics for Integrating Biology and the Bedside/Veteran Affairs (i2b2/VA) 2010 natural language processing challenge and the Shared Annotated Resources/Conference and Labs of the Evaluation Forum (ShARe/CLEF) 2013 eHealth Evaluation Lab. The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared with the random sampling baseline, the saving is at least doubled. Incremental active learning is a promising approach for building effective and robust medical concept extraction models while significantly reducing the burden of manual annotation. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  12. Automated extraction of avian influenza virus for rapid detection using real-time RT-PCR.

    Science.gov (United States)

    Tewari, Deepanker; Zellers, Corey; Acland, Helen; Pedersen, Janice C

    2007-10-01

    Highly pathogenic H5N1 avian influenza (AI) poses a grave risk to human health. An important aspect of influenza control is rapid diagnosis. This study describes the efficiency of AI-RNA extraction utilizing silica-based magnetic beads with robotics and its detection with an influenza A matrix gene real-time RT-PCR from tracheal swabs, and compares it to virus isolation and manual spin column extractions. Analytical sensitivity was assessed by performing dilution analysis and detection of H2N2 AI viral RNA. Diagnostic sensitivity and specificity was assessed by analyzing tracheal swabs collected from H7N2 infected and uninfected chickens. Both manual and robotic extractions detected AI virus at 1log(10)EID(50)/ml. Diagnostic sensitivity and specificity of matrix gene detection with the automated extraction method for chicken tracheal swab specimens was similar to that of virus isolation and the manual extraction method. There were only three discordant results among 212 tested specimens. The main advantages of automated robotic viral nucleic acid extraction are high throughput processing; hands-free operation; and reduction in human and technical error. This study demonstrates successful detection of influenza A virus with magnetic beads utilizing the Qiagen MagAttract cell kit on a BioRobot M48 platform.

  13. Automated renal histopathology: digital extraction and quantification of renal pathology

    Science.gov (United States)

    Sarder, Pinaki; Ginley, Brandon; Tomaszewski, John E.

    2016-03-01

    The branch of pathology concerned with excess blood serum proteins being excreted in the urine pays particular attention to the glomerulus, a small intertwined bunch of capillaries located at the beginning of the nephron. Normal glomeruli allow moderate amount of blood proteins to be filtered; proteinuric glomeruli allow large amount of blood proteins to be filtered. Diagnosis of proteinuric diseases requires time intensive manual examination of the structural compartments of the glomerulus from renal biopsies. Pathological examination includes cellularity of individual compartments, Bowman's and luminal space segmentation, cellular morphology, glomerular volume, capillary morphology, and more. Long examination times may lead to increased diagnosis time and/or lead to reduced precision of the diagnostic process. Automatic quantification holds strong potential to reduce renal diagnostic time. We have developed a computational pipeline capable of automatically segmenting relevant features from renal biopsies. Our method first segments glomerular compartments from renal biopsies by isolating regions with high nuclear density. Gabor texture segmentation is used to accurately define glomerular boundaries. Bowman's and luminal spaces are segmented using morphological operators. Nuclei structures are segmented using color deconvolution, morphological processing, and bottleneck detection. Average computation time of feature extraction for a typical biopsy, comprising of ~12 glomeruli, is ˜69 s using an Intel(R) Core(TM) i7-4790 CPU, and is ~65X faster than manual processing. Using images from rat renal tissue samples, automatic glomerular structural feature estimation was reproducibly demonstrated for 15 biopsy images, which contained 148 individual glomeruli images. The proposed method holds immense potential to enhance information available while making clinical diagnoses.

  14. Extraction of prostatic lumina and automated recognition for prostatic calculus image using PCA-SVM.

    Science.gov (United States)

    Wang, Zhuocai; Xu, Xiangmin; Ding, Xiaojun; Xiao, Hui; Huang, Yusheng; Liu, Jian; Xing, Xiaofen; Wang, Hua; Liao, D Joshua

    2011-01-01

    Identification of prostatic calculi is an important basis for determining the tissue origin. Computation-assistant diagnosis of prostatic calculi may have promising potential but is currently still less studied. We studied the extraction of prostatic lumina and automated recognition for calculus images. Extraction of lumina from prostate histology images was based on local entropy and Otsu threshold recognition using PCA-SVM and based on the texture features of prostatic calculus. The SVM classifier showed an average time 0.1432 second, an average training accuracy of 100%, an average test accuracy of 93.12%, a sensitivity of 87.74%, and a specificity of 94.82%. We concluded that the algorithm, based on texture features and PCA-SVM, can recognize the concentric structure and visualized features easily. Therefore, this method is effective for the automated recognition of prostatic calculi.

  15. Automated DNA extraction from genetically modified maize using aminosilane-modified bacterial magnetic particles.

    Science.gov (United States)

    Ota, Hiroyuki; Lim, Tae-Kyu; Tanaka, Tsuyoshi; Yoshino, Tomoko; Harada, Manabu; Matsunaga, Tadashi

    2006-09-18

    A novel, automated system, PNE-1080, equipped with eight automated pestle units and a spectrophotometer was developed for genomic DNA extraction from maize using aminosilane-modified bacterial magnetic particles (BMPs). The use of aminosilane-modified BMPs allowed highly accurate DNA recovery. The (A(260)-A(320)):(A(280)-A(320)) ratio of the extracted DNA was 1.9+/-0.1. The DNA quality was sufficiently pure for PCR analysis. The PNE-1080 offered rapid assay completion (30 min) with high accuracy. Furthermore, the results of real-time PCR confirmed that our proposed method permitted the accurate determination of genetically modified DNA composition and correlated well with results obtained by conventional cetyltrimethylammonium bromide (CTAB)-based methods.

  16. Extraction of Prostatic Lumina and Automated Recognition for Prostatic Calculus Image Using PCA-SVM

    Science.gov (United States)

    Wang, Zhuocai; Xu, Xiangmin; Ding, Xiaojun; Xiao, Hui; Huang, Yusheng; Liu, Jian; Xing, Xiaofen; Wang, Hua; Liao, D. Joshua

    2011-01-01

    Identification of prostatic calculi is an important basis for determining the tissue origin. Computation-assistant diagnosis of prostatic calculi may have promising potential but is currently still less studied. We studied the extraction of prostatic lumina and automated recognition for calculus images. Extraction of lumina from prostate histology images was based on local entropy and Otsu threshold recognition using PCA-SVM and based on the texture features of prostatic calculus. The SVM classifier showed an average time 0.1432 second, an average training accuracy of 100%, an average test accuracy of 93.12%, a sensitivity of 87.74%, and a specificity of 94.82%. We concluded that the algorithm, based on texture features and PCA-SVM, can recognize the concentric structure and visualized features easily. Therefore, this method is effective for the automated recognition of prostatic calculi. PMID:21461364

  17. Automated extraction of DNA from biological stains on fabric from crime cases. A comparison of a manual and three automated methods

    DEFF Research Database (Denmark)

    Stangegaard, Michael; Hjort, Benjamin B; Hansen, Thomas N

    2013-01-01

    The presence of PCR inhibitors in extracted DNA may interfere with the subsequent quantification and short tandem repeat (STR) reactions used in forensic genetic DNA typing. DNA extraction from fabric for forensic genetic purposes may be challenging due to the occasional presence of PCR inhibitors...... that may be co-extracted with the DNA. Using 120 forensic trace evidence samples consisting of various types of fabric, we compared three automated DNA extraction methods based on magnetic beads (PrepFiler Express Forensic DNA Extraction Kit on an AutoMate Express, QIAsyphony DNA Investigator kit either...... with the sample pre-treatment recommended by Qiagen or an in-house optimized sample pre-treatment on a QIAsymphony SP) and one manual method (Chelex) with the aim of reducing the amount of PCR inhibitors in the DNA extracts and increasing the proportion of reportable STR-profiles. A total of 480 samples were...

  18. Evaluation of an automated protocol for efficient and reliable DNA extraction of dietary samples.

    Science.gov (United States)

    Wallinger, Corinna; Staudacher, Karin; Sint, Daniela; Thalinger, Bettina; Oehm, Johannes; Juen, Anita; Traugott, Michael

    2017-08-01

    Molecular techniques have become an important tool to empirically assess feeding interactions. The increased usage of next-generation sequencing approaches has stressed the need of fast DNA extraction that does not compromise DNA quality. Dietary samples here pose a particular challenge, as these demand high-quality DNA extraction procedures for obtaining the minute quantities of short-fragmented food DNA. Automatic high-throughput procedures significantly decrease time and costs and allow for standardization of extracting total DNA. However, these approaches have not yet been evaluated for dietary samples. We tested the efficiency of an automatic DNA extraction platform and a traditional CTAB protocol, employing a variety of dietary samples including invertebrate whole-body extracts as well as invertebrate and vertebrate gut content samples and feces. Extraction efficacy was quantified using the proportions of successful PCR amplifications of both total and prey DNA, and cost was estimated in terms of time and material expense. For extraction of total DNA, the automated platform performed better for both invertebrate and vertebrate samples. This was also true for prey detection in vertebrate samples. For the dietary analysis in invertebrates, there is still room for improvement when using the high-throughput system for optimal DNA yields. Overall, the automated DNA extraction system turned out as a promising alternative to labor-intensive, low-throughput manual extraction methods such as CTAB. It is opening up the opportunity for an extensive use of this cost-efficient and innovative methodology at low contamination risk also in trophic ecology.

  19. A Novel Characteristic Frequency Bands Extraction Method for Automatic Bearing Fault Diagnosis Based on Hilbert Huang Transform.

    Science.gov (United States)

    Yu, Xiao; Ding, Enjie; Chen, Chunxu; Liu, Xiaoming; Li, Li

    2015-11-03

    Because roller element bearings (REBs) failures cause unexpected machinery breakdowns, their fault diagnosis has attracted considerable research attention. Established fault feature extraction methods focus on statistical characteristics of the vibration signal, which is an approach that loses sight of the continuous waveform features. Considering this weakness, this article proposes a novel feature extraction method for frequency bands, named Window Marginal Spectrum Clustering (WMSC) to select salient features from the marginal spectrum of vibration signals by Hilbert-Huang Transform (HHT). In WMSC, a sliding window is used to divide an entire HHT marginal spectrum (HMS) into window spectrums, following which Rand Index (RI) criterion of clustering method is used to evaluate each window. The windows returning higher RI values are selected to construct characteristic frequency bands (CFBs). Next, a hybrid REBs fault diagnosis is constructed, termed by its elements, HHT-WMSC-SVM (support vector machines). The effectiveness of HHT-WMSC-SVM is validated by running series of experiments on REBs defect datasets from the Bearing Data Center of Case Western Reserve University (CWRU). The said test results evidence three major advantages of the novel method. First, the fault classification accuracy of the HHT-WMSC-SVM model is higher than that of HHT-SVM and ST-SVM, which is a method that combines statistical characteristics with SVM. Second, with Gauss white noise added to the original REBs defect dataset, the HHT-WMSC-SVM model maintains high classification accuracy, while the classification accuracy of ST-SVM and HHT-SVM models are significantly reduced. Third, fault classification accuracy by HHT-WMSC-SVM can exceed 95% under a Pmin range of 500-800 and a m range of 50-300 for REBs defect dataset, adding Gauss white noise at Signal Noise Ratio (SNR) = 5. Experimental results indicate that the proposed WMSC method yields a high REBs fault classification accuracy and a

  20. Evaluation of automated nucleic acid extraction methods for virus detection in a multicenter comparative trial

    DEFF Research Database (Denmark)

    Rasmussen, Thomas Bruun; Uttenthal, Åse; Hakhverdyan, M.

    2009-01-01

    between the results obtained for the different automated extraction platforms. In particular, the limit of detection was identical for 9/12 and 8/12 best performing robots (using dilutions of BVDV infected-serum and cell culture material, respectively), which was similar to a manual extraction method used...... for comparison. The remaining equipment and protocols used were less sensitive, in an extreme case for serum, by a factor of 1000. There was no evidence for cross-contamination of RNA template in any of the negative samples included in these panels. These results are not intended to replace local optimisation...

  1. Application and evaluation of automated methods to extract neuroanatomical connectivity statements from free text.

    Science.gov (United States)

    French, Leon; Lane, Suzanne; Xu, Lydia; Siu, Celia; Kwok, Cathy; Chen, Yiqi; Krebs, Claudia; Pavlidis, Paul

    2012-11-15

    Automated annotation of neuroanatomical connectivity statements from the neuroscience literature would enable accessible and large-scale connectivity resources. Unfortunately, the connectivity findings are not formally encoded and occur as natural language text. This hinders aggregation, indexing, searching and integration of the reports. We annotated a set of 1377 abstracts for connectivity relations to facilitate automated extraction of connectivity relationships from neuroscience literature. We tested several baseline measures based on co-occurrence and lexical rules. We compare results from seven machine learning methods adapted from the protein interaction extraction domain that employ part-of-speech, dependency and syntax features. Co-occurrence based methods provided high recall with weak precision. The shallow linguistic kernel recalled 70.1% of the sentence-level connectivity statements at 50.3% precision. Owing to its speed and simplicity, we applied the shallow linguistic kernel to a large set of new abstracts. To evaluate the results, we compared 2688 extracted connections with the Brain Architecture Management System (an existing database of rat connectivity). The extracted connections were connected in the Brain Architecture Management System at a rate of 63.5%, compared with 51.1% for co-occurring brain region pairs. We found that precision increases with the recency and frequency of the extracted relationships. The source code, evaluations, documentation and other supplementary materials are available at http://www.chibi.ubc.ca/WhiteText. paul@chibi.ubc.ca. Supplementary data are available at Bioinformatics Online.

  2. A novel wavelet-based feature extraction from common mode currents for fault location in a residential DC microgrid

    DEFF Research Database (Denmark)

    Beheshtaein, Siavash; Yu, Junyang; Cuzner, Rob

    2017-01-01

    DC community and residential microgrids are recognized as effective means for electrification of remote areas as a result of monumental efforts in many parts of the world — most significantly in India — but also through similar efforts in Nepal, Cameroon, New Guinea and Nigeria. So far modular ap...... and proposes methodologies for extracting specific information about the location and type of fault using wavelets. The sensing hardware, sampling rates and processing requirements that are needed are also presented....

  3. Feature Extraction Method for High Impedance Ground Fault Localization in Radial Power Distribution Networks

    DEFF Research Database (Denmark)

    Jensen, Kåre Jean; Munk, Steen M.; Sørensen, John Aasted

    1998-01-01

    of three phase voltages and currents. The method consists of a feature extractor, based on a grid description of the feeder by impulse responses, and a neural network for ground fault localization. The emphasis of this paper is the feature extractor, and the detection of the time instance of a ground fault...

  4. Automated Device for Asynchronous Extraction of RNA, DNA, or Protein Biomarkers from Surrogate Patient Samples.

    Science.gov (United States)

    Bitting, Anna L; Bordelon, Hali; Baglia, Mark L; Davis, Keersten M; Creecy, Amy E; Short, Philip A; Albert, Laura E; Karhade, Aditya V; Wright, David W; Haselton, Frederick R; Adams, Nicholas M

    2016-12-01

    Many biomarker-based diagnostic methods are inhibited by nontarget molecules in patient samples, necessitating biomarker extraction before detection. We have developed a simple device that purifies RNA, DNA, or protein biomarkers from complex biological samples without robotics or fluid pumping. The device design is based on functionalized magnetic beads, which capture biomarkers and remove background biomolecules by magnetically transferring the beads through processing solutions arrayed within small-diameter tubing. The process was automated by wrapping the tubing around a disc-like cassette and rotating it past a magnet using a programmable motor. This device recovered biomarkers at ~80% of the operator-dependent extraction method published previously. The device was validated by extracting biomarkers from a panel of surrogate patient samples containing clinically relevant concentrations of (1) influenza A RNA in nasal swabs, (2) Escherichia coli DNA in urine, (3) Mycobacterium tuberculosis DNA in sputum, and (4) Plasmodium falciparum protein and DNA in blood. The device successfully extracted each biomarker type from samples representing low levels of clinically relevant infectivity (i.e., 7.3 copies/µL of influenza A RNA, 405 copies/µL of E. coli DNA, 0.22 copies/µL of TB DNA, 167 copies/µL of malaria parasite DNA, and 2.7 pM of malaria parasite protein). © 2015 Society for Laboratory Automation and Screening.

  5. Bearing Fault Diagnosis Based on Multiscale Permutation Entropy and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Jian-Jiun Ding

    2012-07-01

    Full Text Available Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, multiscale permutation entropy (MPE was introduced for feature extraction from faulty bearing vibration signals. After extracting feature vectors by MPE, the support vector machine (SVM was applied to automate the fault diagnosis procedure. Simulation results demonstrated that the proposed method is a very powerful algorithm for bearing fault diagnosis and has much better performance than the methods based on single scale permutation entropy (PE and multiscale entropy (MSE.

  6. Automated extraction of natural drainage density patterns for the conterminous United States through high performance computing

    Science.gov (United States)

    Stanislawski, Larry V.; Falgout, Jeff T.; Buttenfield, Barbara P.

    2015-01-01

    Hydrographic networks form an important data foundation for cartographic base mapping and for hydrologic analysis. Drainage density patterns for these networks can be derived to characterize local landscape, bedrock and climate conditions, and further inform hydrologic and geomorphological analysis by indicating areas where too few headwater channels have been extracted. But natural drainage density patterns are not consistently available in existing hydrographic data for the United States because compilation and capture criteria historically varied, along with climate, during the period of data collection over the various terrain types throughout the country. This paper demonstrates an automated workflow that is being tested in a high-performance computing environment by the U.S. Geological Survey (USGS) to map natural drainage density patterns at the 1:24,000-scale (24K) for the conterminous United States. Hydrographic network drainage patterns may be extracted from elevation data to guide corrections for existing hydrographic network data. The paper describes three stages in this workflow including data pre-processing, natural channel extraction, and generation of drainage density patterns from extracted channels. The workflow is concurrently implemented by executing procedures on multiple subbasin watersheds within the U.S. National Hydrography Dataset (NHD). Pre-processing defines parameters that are needed for the extraction process. Extraction proceeds in standard fashion: filling sinks, developing flow direction and weighted flow accumulation rasters. Drainage channels with assigned Strahler stream order are extracted within a subbasin and simplified. Drainage density patterns are then estimated with 100-meter resolution and subsequently smoothed with a low-pass filter. The extraction process is found to be of better quality in higher slope terrains. Concurrent processing through the high performance computing environment is shown to facilitate and refine

  7. Accelerated solvent extraction (ASE) - a fast and automated technique with low solvent consumption for the extraction of solid samples (T12)

    International Nuclear Information System (INIS)

    Hoefler, F.

    2002-01-01

    Full text: Accelerated solvent extraction (ASE) is a modern extraction technique that significantly streamlines sample preparation. A common organic solvent as well as water is used as extraction solvent at elevated temperature and pressure to increase extraction speed and efficiency. The entire extraction process is fully automated and performed within 15 minutes with a solvent consumption of 18 ml for a 10 g sample. For many matrices and for a variety of solutes, ASE has proven to be equivalent or superior to sonication, Soxhlet, and reflux extraction techniques while requiring less time, solvent and labor. First ASE has been applied for the extraction of environmental hazards from solid matrices. Within a very short time ASE was approved by the U.S. EPA for the extraction of BNAs, PAHs, PCBs, pesticides, herbicides, TPH, and dioxins from solid samples in method 3545. Especially for the extraction of dioxins the extraction time with ASE is reduced to 20 minutes in comparison to 18 h using Soxhlet. In food analysis ASE is used for the extraction of pesticide and mycotoxin residues from fruits and vegetables, the fat determination and extraction of vitamins. Time consuming and solvent intensive methods for the extraction of additives from polymers as well as for the extraction of marker compounds from herbal supplements can be performed with higher efficiencies using ASE. For the analysis of chemical weapons the extraction process and sample clean-up including derivatization can be automated and combined with GC-MS using an online ASE-APEC-GC system. (author)

  8. Establishing a novel automated magnetic bead-based method for the extraction of DNA from a variety of forensic samples.

    Science.gov (United States)

    Witt, Sebastian; Neumann, Jan; Zierdt, Holger; Gébel, Gabriella; Röscheisen, Christiane

    2012-09-01

    Automated systems have been increasingly utilized for DNA extraction by many forensic laboratories to handle growing numbers of forensic casework samples while minimizing the risk of human errors and assuring high reproducibility. The step towards automation however is not easy: The automated extraction method has to be very versatile to reliably prepare high yields of pure genomic DNA from a broad variety of sample types on different carrier materials. To prevent possible cross-contamination of samples or the loss of DNA, the components of the kit have to be designed in a way that allows for the automated handling of the samples with no manual intervention necessary. DNA extraction using paramagnetic particles coated with a DNA-binding surface is predestined for an automated approach. For this study, we tested different DNA extraction kits using DNA-binding paramagnetic particles with regard to DNA yield and handling by a Freedom EVO(®)150 extraction robot (Tecan) equipped with a Te-MagS magnetic separator. Among others, the extraction kits tested were the ChargeSwitch(®)Forensic DNA Purification Kit (Invitrogen), the PrepFiler™Automated Forensic DNA Extraction Kit (Applied Biosystems) and NucleoMag™96 Trace (Macherey-Nagel). After an extensive test phase, we established a novel magnetic bead extraction method based upon the NucleoMag™ extraction kit (Macherey-Nagel). The new method is readily automatable and produces high yields of DNA from different sample types (blood, saliva, sperm, contact stains) on various substrates (filter paper, swabs, cigarette butts) with no evidence of a loss of magnetic beads or sample cross-contamination. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  9. Doping control in Japan. An automated extraction procedure for the doping test.

    Science.gov (United States)

    Nakajima, T.; Matsumoto, T.

    1976-01-01

    Horse racing in Japan consists of two systems, the National (10 racecourses) and the Regional public racing (32 racecourses) having about 2,500 racing meetings in total per year. Urine or saliva samples for dope testing are collected by the officials from thw winner, second and third, and transported to the laboratory in a frozen state. In 1975, 76, 117 samples were analyzed by this laboratory. The laboratory provides the following four methods of analysis, which are variously combined by request. (1) Method for detection of drugs extracted by chloroform from alkalinized sample. (2) Methods for detection of camphor and its derivatives. (3) Method for detection of barbiturates. (4) Method for detection of ethanol. These methods consist of screening, mainly by thin layer chromatography and confirmatory tests using ultra violet spectrophotometry, gas chromatography and mass spectrometry combined with gas chromatography. In the screening test of doping drugs, alkalinized samples are extracted with chloroform. In order to automate the extraction procedure, the authors contrived a new automatic extractor. They also devised a means of pH adjustment of horse urine by using buffer solution and an efficient mechanism of evaporation of organic solvent. Analytical data obtained by the automatic extractor are presented in this paper. In 1972, we started research work to automate the extraction procedure in method (1) above, and the Automatic Extractor has been in use in routine work since last July. One hundred and twnety samples per hour are extracted automatically by three automatic extractors. The analytical data using this apparatus is presented below. PMID:1000163

  10. Automated CO2 extraction from air for clumped isotope analysis in the atmo- and biosphere

    Science.gov (United States)

    Hofmann, Magdalena; Ziegler, Martin; Pons, Thijs; Lourens, Lucas; Röckmann, Thomas

    2015-04-01

    The conventional stable isotope ratios 13C/12C and 18O/16O in atmospheric CO2 are a powerful tool for unraveling the global carbon cycle. In recent years, it has been suggested that the abundance of the very rare isotopologue 13C18O16O on m/z 47 might be a promising tracer to complement conventional stable isotope analysis of atmospheric CO2 [Affek and Eiler, 2006; Affek et al. 2007; Eiler and Schauble, 2004; Yeung et al., 2009]. Here we present an automated analytical system that is designed for clumped isotope analysis of atmo- and biospheric CO2. The carbon dioxide gas is quantitatively extracted from about 1.5L of air (ATP). The automated stainless steel extraction and purification line consists of three main components: (i) a drying unit (a magnesium perchlorate unit and a cryogenic water trap), (ii) two CO2 traps cooled with liquid nitrogen [Werner et al., 2001] and (iii) a GC column packed with Porapak Q that can be cooled with liquid nitrogen to -30°C during purification and heated up to 230°C in-between two extraction runs. After CO2 extraction and purification, the CO2 is automatically transferred to the mass spectrometer. Mass spectrometric analysis of the 13C18O16O abundance is carried out in dual inlet mode on a MAT 253 mass spectrometer. Each analysis generally consists of 80 change-over-cycles. Three additional Faraday cups were added to the mass spectrometer for simultaneous analysis of the mass-to-charge ratios 44, 45, 46, 47, 48 and 49. The reproducibility for δ13C, δ18O and Δ47 for repeated CO2 extractions from air is in the range of 0.11o (SD), 0.18o (SD) and 0.02 (SD)o respectively. This automated CO2 extraction and purification system will be used to analyse the clumped isotopic signature in atmospheric CO2 (tall tower, Cabauw, Netherlands) and to study the clumped isotopic fractionation during photosynthesis (leaf chamber experiments) and soil respiration. References Affek, H. P., Xu, X. & Eiler, J. M., Geochim. Cosmochim. Acta 71, 5033

  11. Semi-automated set-up for exhaustive micro-electromembrane extractions of basic drugs from biological fluids

    Czech Academy of Sciences Publication Activity Database

    Dvořák, Miloš; Seip, K. F.; Pedersen-Bjergaard, S.; Kubáň, Pavel

    2018-01-01

    Roč. 1005, APR (2018), s. 34-42 ISSN 0003-2670 R&D Projects: GA ČR(CZ) GA16-09135S Institutional support: RVO:68081715 Keywords : electromembrane extraction * exhaustive extraction * automation Subject RIV: CB - Analytical Chemistry, Separation OBOR OECD: Analytical chemistry Impact factor: 4.950, year: 2016

  12. Strategies for Medical Data Extraction and Presentation Part 3: Automated Context- and User-Specific Data Extraction.

    Science.gov (United States)

    Reiner, Bruce

    2015-08-01

    In current medical practice, data extraction is limited by a number of factors including lack of information system integration, manual workflow, excessive workloads, and lack of standardized databases. The combined limitations result in clinically important data often being overlooked, which can adversely affect clinical outcomes through the introduction of medical error, diminished diagnostic confidence, excessive utilization of medical services, and delays in diagnosis and treatment planning. Current technology development is largely inflexible and static in nature, which adversely affects functionality and usage among the diverse and heterogeneous population of end users. In order to address existing limitations in medical data extraction, alternative technology development strategies need to be considered which incorporate the creation of end user profile groups (to account for occupational differences among end users), customization options (accounting for individual end user needs and preferences), and context specificity of data (taking into account both the task being performed and data subject matter). Creation of the proposed context- and user-specific data extraction and presentation templates offers a number of theoretical benefits including automation and improved workflow, completeness in data search, ability to track and verify data sources, creation of computerized decision support and learning tools, and establishment of data-driven best practice guidelines.

  13. Automation of lidar-based hydrologic feature extraction workflows using GIS

    Science.gov (United States)

    Borlongan, Noel Jerome B.; de la Cruz, Roel M.; Olfindo, Nestor T.; Perez, Anjillyn Mae C.

    2016-10-01

    With the advent of LiDAR technology, higher resolution datasets become available for use in different remote sensing and GIS applications. One significant application of LiDAR datasets in the Philippines is in resource features extraction. Feature extraction using LiDAR datasets require complex and repetitive workflows which can take a lot of time for researchers through manual execution and supervision. The Development of the Philippine Hydrologic Dataset for Watersheds from LiDAR Surveys (PHD), a project under the Nationwide Detailed Resources Assessment Using LiDAR (Phil-LiDAR 2) program, created a set of scripts, the PHD Toolkit, to automate its processes and workflows necessary for hydrologic features extraction specifically Streams and Drainages, Irrigation Network, and Inland Wetlands, using LiDAR Datasets. These scripts are created in Python and can be added in the ArcGIS® environment as a toolbox. The toolkit is currently being used as an aid for the researchers in hydrologic feature extraction by simplifying the workflows, eliminating human errors when providing the inputs, and providing quick and easy-to-use tools for repetitive tasks. This paper discusses the actual implementation of different workflows developed by Phil-LiDAR 2 Project 4 in Streams, Irrigation Network and Inland Wetlands extraction.

  14. Automated Extraction of 3D Trees from Mobile LiDAR Point Clouds

    Directory of Open Access Journals (Sweden)

    Y. Yu

    2014-06-01

    Full Text Available This paper presents an automated algorithm for extracting 3D trees directly from 3D mobile light detection and ranging (LiDAR data. To reduce both computational and spatial complexities, ground points are first filtered out from a raw 3D point cloud via blockbased elevation filtering. Off-ground points are then grouped into clusters representing individual objects through Euclidean distance clustering and voxel-based normalized cut segmentation. Finally, a model-driven method is proposed to achieve the extraction of 3D trees based on a pairwise 3D shape descriptor. The proposed algorithm is tested using a set of mobile LiDAR point clouds acquired by a RIEGL VMX-450 system. The results demonstrate the feasibility and effectiveness of the proposed algorithm.

  15. CHANNEL MORPHOLOGY TOOL (CMT): A GIS-BASED AUTOMATED EXTRACTION MODEL FOR CHANNEL GEOMETRY

    Energy Technology Data Exchange (ETDEWEB)

    JUDI, DAVID [Los Alamos National Laboratory; KALYANAPU, ALFRED [Los Alamos National Laboratory; MCPHERSON, TIMOTHY [Los Alamos National Laboratory; BERSCHEID, ALAN [Los Alamos National Laboratory

    2007-01-17

    This paper describes an automated Channel Morphology Tool (CMT) developed in ArcGIS 9.1 environment. The CMT creates cross-sections along a stream centerline and uses a digital elevation model (DEM) to create station points with elevations along each of the cross-sections. The generated cross-sections may then be exported into a hydraulic model. Along with the rapid cross-section generation the CMT also eliminates any cross-section overlaps that might occur due to the sinuosity of the channels using the Cross-section Overlap Correction Algorithm (COCoA). The CMT was tested by extracting cross-sections from a 5-m DEM for a 50-km channel length in Houston, Texas. The extracted cross-sections were compared directly with surveyed cross-sections in terms of the cross-section area. Results indicated that the CMT-generated cross-sections satisfactorily matched the surveyed data.

  16. Automated extraction of reported statistical analyses: towards a logical representation of clinical trial literature.

    Science.gov (United States)

    Hsu, William; Speier, William; Taira, Ricky K

    2012-01-01

    Randomized controlled trials are an important source of evidence for guiding clinical decisions when treating a patient. However, given the large number of studies and their variability in quality, determining how to summarize reported results and formalize them as part of practice guidelines continues to be a challenge. We have developed a set of information extraction and annotation tools to automate the identification of key information from papers related to the hypothesis, sample size, statistical test, confidence interval, significance level, and conclusions. We adapted the Automated Sequence Annotation Pipeline to map extracted phrases to relevant knowledge sources. We trained and tested our system on a corpus of 42 full-text articles related to chemotherapy of non-small cell lung cancer. On our test set of 7 papers, we obtained an overall precision of 86%, recall of 78%, and an F-score of 0.82 for classifying sentences. This work represents our efforts towards utilizing this information for quality assessment, meta-analysis, and modeling.

  17. Automated quality control of forced oscillation measurements: respiratory artifact detection with advanced feature extraction.

    Science.gov (United States)

    Pham, Thuy T; Leong, Philip H W; Robinson, Paul D; Gutzler, Thomas; Jee, Adelle S; King, Gregory G; Thamrin, Cindy

    2017-10-01

    The forced oscillation technique (FOT) can provide unique and clinically relevant lung function information with little cooperation with subjects. However, FOT has higher variability than spirometry, possibly because strategies for quality control and reducing artifacts in FOT measurements have yet to be standardized or validated. Many quality control procedures rely on either simple statistical filters or subjective evaluation by a human operator. In this study, we propose an automated artifact removal approach based on the resistance against flow profile, applied to complete breaths. We report results obtained from data recorded from children and adults, with and without asthma. Our proposed method has 76% agreement with a human operator for the adult data set and 79% for the pediatric data set. Furthermore, we assessed the variability of respiratory resistance measured by FOT using within-session variation (wCV) and between-session variation (bCV). In the asthmatic adults test data set, our method was again similar to that of the manual operator for wCV (6.5 vs. 6.9%) and significantly improved bCV (8.2 vs. 8.9%). Our combined automated breath removal approach based on advanced feature extraction offers better or equivalent quality control of FOT measurements compared with an expert operator and computationally more intensive methods in terms of accuracy and reducing intrasubject variability. NEW & NOTEWORTHY The forced oscillation technique (FOT) is gaining wider acceptance for clinical testing; however, strategies for quality control are still highly variable and require a high level of subjectivity. We propose an automated, complete breath approach for removal of respiratory artifacts from FOT measurements, using feature extraction and an interquartile range filter. Our approach offers better or equivalent performance compared with an expert operator, in terms of accuracy and reducing intrasubject variability. Copyright © 2017 the American Physiological

  18. A modular computational framework for automated peak extraction from ion mobility spectra.

    Science.gov (United States)

    D'Addario, Marianna; Kopczynski, Dominik; Baumbach, Jörg Ingo; Rahmann, Sven

    2014-01-22

    An ion mobility (IM) spectrometer coupled with a multi-capillary column (MCC) measures volatile organic compounds (VOCs) in the air or in exhaled breath. This technique is utilized in several biotechnological and medical applications. Each peak in an MCC/IM measurement represents a certain compound, which may be known or unknown. For clustering and classification of measurements, the raw data matrix must be reduced to a set of peaks. Each peak is described by its coordinates (retention time in the MCC and reduced inverse ion mobility) and shape (signal intensity, further shape parameters). This fundamental step is referred to as peak extraction. It is the basis for identifying discriminating peaks, and hence putative biomarkers, between two classes of measurements, such as a healthy control group and a group of patients with a confirmed disease. Current state-of-the-art peak extraction methods require human interaction, such as hand-picking approximate peak locations, assisted by a visualization of the data matrix. In a high-throughput context, however, it is preferable to have robust methods for fully automated peak extraction. We introduce PEAX, a modular framework for automated peak extraction. The framework consists of several steps in a pipeline architecture. Each step performs a specific sub-task and can be instantiated by different methods implemented as modules. We provide open-source software for the framework and several modules for each step. Additionally, an interface that allows easy extension by a new module is provided. Combining the modules in all reasonable ways leads to a large number of peak extraction methods. We evaluate all combinations using intrinsic error measures and by comparing the resulting peak sets with an expert-picked one. Our software PEAX is able to automatically extract peaks from MCC/IM measurements within a few seconds. The automatically obtained results keep up with the results provided by current state-of-the-art peak

  19. Automating the Extraction of Metadata from Archaeological Data Using iRods Rules

    Directory of Open Access Journals (Sweden)

    David Walling

    2011-10-01

    Full Text Available The Texas Advanced Computing Center and the Institute for Classical Archaeology at the University of Texas at Austin developed a method that uses iRods rules and a Jython script to automate the extraction of metadata from digital archaeological data. The first step was to create a record-keeping system to classify the data. The record-keeping system employs file and directory hierarchy naming conventions designed specifically to maintain the relationship between the data objects and map the archaeological documentation process. The metadata implicit in the record-keeping system is automatically extracted upon ingest, combined with additional sources of metadata, and stored alongside the data in the iRods preservation environment. This method enables a more organized workflow for the researchers, helps them archive their data close to the moment of data creation, and avoids error prone manual metadata input. We describe the types of metadata extracted and provide technical details of the extraction process and storage of the data and metadata.

  20. Automated Extraction of the Archaeological Tops of Qanat Shafts from VHR Imagery in Google Earth

    Directory of Open Access Journals (Sweden)

    Lei Luo

    2014-12-01

    Full Text Available Qanats in northern Xinjiang of China provide valuable information for agriculturists and anthropologists who seek fundamental understanding of the distribution of qanat water supply systems with regard to water resource utilization, the development of oasis agriculture, and eventually climate change. Only the tops of qanat shafts (TQSs, indicating the course of the qanats, can be observed from space, and their circular archaeological traces can also be seen in very high resolution imagery in Google Earth. The small size of the TQSs, vast search regions, and degraded features make manually extracting them from remote sensing images difficult and costly. This paper proposes an automated TQS extraction method that adopts mathematical morphological processing methods before an edge detecting module is used in the circular Hough transform approach. The accuracy assessment criteria for the proposed method include: (i extraction percentage (E = 95.9%, branch factor (B = 0 and quality percentage (Q = 95.9% in Site 1; and (ii extraction percentage (E = 83.4%, branch factor (B = 0.058 and quality percentage (Q = 79.5% in Site 2. Compared with the standard circular Hough transform, the quality percentages (Q of our proposed method were improved to 95.9% and 79.5% from 86.3% and 65.8% in test sites 1 and 2, respectively. The results demonstrate that wide-area discovery and mapping can be performed much more effectively based on our proposed method.

  1. Automated extraction of DNA and PCR setup using a Tecan Freedom EVO® liquid handler

    DEFF Research Database (Denmark)

    Frøslev, Tobias Guldberg; Hansen, Anders Johannes; Stangegaard, Michael

    2009-01-01

    We have implemented and validated automated protocols for DNA extraction and PCR setup using a Tecan Freedom EVO® liquid handler mounted with the TeMagS magnetic separation device. The methods were validated for accredited, forensic genetic work according to ISO 17025 using the Qiagen Mag......Attract® DNA Mini M48 kit from fresh, whole blood and blood from deceased. The methods were simplified by returning the DNA extracts to the original tubes reducing the risk of misplacing samples. The original tubes that had contained the samples were washed with 700 µl Milli-Q water prior to the return...... of the DNA extracts. The PCR setup protocols were designed for 96 well microtiter plates. The methods were validated for the kits: AmpFlSTR® Identifiler® and Y-filer® (Applied Biosystems), GenePrint® FFFL and PowerPlex® Y (Promega). Within 3.5 hours, 96 samples were extracted and PCR master mix was added...

  2. Automated Extraction Of Associations Between Methylated Genes and Diseases From Biomedical Literature

    KAUST Repository

    Bin Res, Arwa A.

    2012-12-01

    Associations between methylated genes and diseases have been investigated in several studies, and it is critical to have such information available for better understanding of diseases and clinical decisions. However, such information is scattered in a large number of electronic publications and it is difficult to manually search for it. Therefore, the goal of the project is to develop a machine learning model that can efficiently extract such information. Twelve machine learning algorithms were applied and compared in application to this problem based on three approaches that involve: document-term frequency matrices, position weight matrices, and a hybrid approach that uses the combination of the previous two. The best results we obtained by the hybrid approach with a random forest model that, in a 10-fold cross-validation, achieved F-score and accuracy of nearly 85% and 84%, respectively. On a completely separate testing set, F-score and accuracy of 89% and 88%, respectively, were obtained. Based on this model, we developed a tool that automates extraction of associations between methylated genes and diseases from electronic text. Our study contributed an efficient method for extracting specific types of associations from free text and the methodology developed here can be extended to other similar association extraction problems.

  3. A novel validation algorithm allows for automated cell tracking and the extraction of biologically meaningful parameters.

    Directory of Open Access Journals (Sweden)

    Daniel H Rapoport

    Full Text Available Automated microscopy is currently the only method to non-invasively and label-free observe complex multi-cellular processes, such as cell migration, cell cycle, and cell differentiation. Extracting biological information from a time-series of micrographs requires each cell to be recognized and followed through sequential microscopic snapshots. Although recent attempts to automatize this process resulted in ever improving cell detection rates, manual identification of identical cells is still the most reliable technique. However, its tedious and subjective nature prevented tracking from becoming a standardized tool for the investigation of cell cultures. Here, we present a novel method to accomplish automated cell tracking with a reliability comparable to manual tracking. Previously, automated cell tracking could not rival the reliability of manual tracking because, in contrast to the human way of solving this task, none of the algorithms had an independent quality control mechanism; they missed validation. Thus, instead of trying to improve the cell detection or tracking rates, we proceeded from the idea to automatically inspect the tracking results and accept only those of high trustworthiness, while rejecting all other results. This validation algorithm works independently of the quality of cell detection and tracking through a systematic search for tracking errors. It is based only on very general assumptions about the spatiotemporal contiguity of cell paths. While traditional tracking often aims to yield genealogic information about single cells, the natural outcome of a validated cell tracking algorithm turns out to be a set of complete, but often unconnected cell paths, i.e. records of cells from mitosis to mitosis. This is a consequence of the fact that the validation algorithm takes complete paths as the unit of rejection/acceptance. The resulting set of complete paths can be used to automatically extract important biological parameters

  4. Automated, simple, and efficient influenza RNA extraction from clinical respiratory swabs using TruTip and epMotion.

    Science.gov (United States)

    Griesemer, Sara B; Holmberg, Rebecca; Cooney, Christopher G; Thakore, Nitu; Gindlesperger, Alissa; Knickerbocker, Christopher; Chandler, Darrell P; St George, Kirsten

    2013-09-01

    Rapid, simple and efficient influenza RNA purification from clinical samples is essential for sensitive molecular detection of influenza infection. Automation of the TruTip extraction method can increase sample throughput while maintaining performance. To automate TruTip influenza RNA extraction using an Eppendorf epMotion robotic liquid handler, and to compare its performance to the bioMerieux easyMAG and Qiagen QIAcube instruments. Extraction efficacy and reproducibility of the automated TruTip/epMotion protocol was assessed from influenza-negative respiratory samples spiked with influenza A and B viruses. Clinical extraction performance from 170 influenza A and B-positive respiratory swabs was also evaluated and compared using influenza A and B real-time RT-PCR assays. TruTip/epMotion extraction efficacy was 100% in influenza virus-spiked samples with at least 745 influenza A and 370 influenza B input gene copies per extraction, and exhibited high reproducibility over four log10 concentrations of virus (extraction were also positive following TruTip extraction. Overall Ct value differences obtained between TruTip/epMotion and easyMAG/QIAcube clinical extracts ranged from 1.24 to 1.91. Pairwise comparisons of Ct values showed a high correlation of the TruTip/epMotion protocol to the other methods (R2>0.90). The automated TruTip/epMotion protocol is a simple and rapid extraction method that reproducibly purifies influenza RNA from respiratory swabs, with comparable efficacy and efficiency to both the easyMAG and QIAcube instruments. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Structure and organization of automation subsystem for control of beam extraction from a fast-cycling synchrotron

    International Nuclear Information System (INIS)

    Agababyan, A.G.; Ananyan, S.G.; Grigiryan, V.G.

    1989-01-01

    The status of development of an automation subsystem for control of beam extraction from the Erevan synchrotron is described. The hardware complex of the subsystem contains the RPT-80 microcomputer, seven units of automated control for the beam extraction channel, a timer unit for synchronization of the accelerator output devices, a unit for monitoring status signals, an ADS, an interface with the synchrotron, a commutation line between RPT80 and the host ES1010 computer. As a result pilot operation the beam energy spread instability has been reduced 15 times. 5 refs.; 1 fig

  6. Semi-automated extraction of longitudinal subglacial bedforms from digital terrain models - Two new methods

    Science.gov (United States)

    Jorge, Marco G.; Brennand, Tracy A.

    2017-07-01

    Relict drumlin and mega-scale glacial lineation (positive relief, longitudinal subglacial bedforms - LSBs) morphometry has been used as a proxy for paleo ice-sheet dynamics. LSB morphometric inventories have relied on manual mapping, which is slow and subjective and thus potentially difficult to reproduce. Automated methods are faster and reproducible, but previous methods for LSB semi-automated mapping have not been highly successful. Here, two new object-based methods for the semi-automated extraction of LSBs (footprints) from digital terrain models are compared in a test area in the Puget Lowland, Washington, USA. As segmentation procedures to create LSB-candidate objects, the normalized closed contour method relies on the contouring of a normalized local relief model addressing LSBs on slopes, and the landform elements mask method relies on the classification of landform elements derived from the digital terrain model. For identifying which LSB-candidate objects correspond to LSBs, both methods use the same LSB operational definition: a ruleset encapsulating expert knowledge, published morphometric data, and the morphometric range of LSBs in the study area. The normalized closed contour method was separately applied to four different local relief models, two computed in moving windows and two hydrology-based. Overall, the normalized closed contour method outperformed the landform elements mask method. The normalized closed contour method performed on a hydrological relief model from a multiple direction flow routing algorithm performed best. For an assessment of its transferability, the normalized closed contour method was evaluated on a second area, the Chautauqua drumlin field, Pennsylvania and New York, USA where it performed better than in the Puget Lowland. A broad comparison to previous methods suggests that the normalized relief closed contour method may be the most capable method to date, but more development is required.

  7. Congestive heart failure information extraction framework for automated treatment performance measures assessment.

    Science.gov (United States)

    Meystre, Stéphane M; Kim, Youngjun; Gobbel, Glenn T; Matheny, Michael E; Redd, Andrew; Bray, Bruce E; Garvin, Jennifer H

    2017-04-01

    This paper describes a new congestive heart failure (CHF) treatment performance measure information extraction system - CHIEF - developed as part of the Automated Data Acquisition for Heart Failure project, a Veterans Health Administration project aiming at improving the detection of patients not receiving recommended care for CHF. CHIEF is based on the Apache Unstructured Information Management Architecture framework, and uses a combination of rules, dictionaries, and machine learning methods to extract left ventricular function mentions and values, CHF medications, and documented reasons for a patient not receiving these medications. The training and evaluation of CHIEF were based on subsets of a reference standard of various clinical notes from 1083 Veterans Health Administration patients. Domain experts manually annotated these notes to create our reference standard. Metrics used included recall, precision, and the F 1 -measure. In general, CHIEF extracted CHF medications with high recall (>0.990) and good precision (0.960-0.978). Mentions of Left Ventricular Ejection Fraction were also extracted with high recall (0.978-0.986) and precision (0.986-0.994), and quantitative values of Left Ventricular Ejection Fraction were found with 0.910-0.945 recall and with high precision (0.939-0.976). Reasons for not prescribing CHF medications were more difficult to extract, only reaching fair accuracy with about 0.310-0.400 recall and 0.250-0.320 precision. This study demonstrated that applying natural language processing to unlock the rich and detailed clinical information found in clinical narrative text notes makes fast and scalable quality improvement approaches possible, eventually improving management and outpatient treatment of patients suffering from CHF. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  8. Deep SOMs for automated feature extraction and classification from big data streaming

    Science.gov (United States)

    Sakkari, Mohamed; Ejbali, Ridha; Zaied, Mourad

    2017-03-01

    In this paper, we proposed a deep self-organizing map model (Deep-SOMs) for automated features extracting and learning from big data streaming which we benefit from the framework Spark for real time streams and highly parallel data processing. The SOMs deep architecture is based on the notion of abstraction (patterns automatically extract from the raw data, from the less to more abstract). The proposed model consists of three hidden self-organizing layers, an input and an output layer. Each layer is made up of a multitude of SOMs, each map only focusing at local headmistress sub-region from the input image. Then, each layer trains the local information to generate more overall information in the higher layer. The proposed Deep-SOMs model is unique in terms of the layers architecture, the SOMs sampling method and learning. During the learning stage we use a set of unsupervised SOMs for feature extraction. We validate the effectiveness of our approach on large data sets such as Leukemia dataset and SRBCT. Results of comparison have shown that the Deep-SOMs model performs better than many existing algorithms for images classification.

  9. An Automated Tracking Approach for Extraction of Retinal Vasculature in Fundus Images

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2010-01-01

    Full Text Available Purpose: To present a novel automated method for tracking and detection of retinal blood vessels in fundus images. Methods: For every pixel in retinal images, a feature vector was computed utilizing multiscale analysis based on Gabor filters. To classify the pixels based on their extracted features as vascular or non-vascular, various classifiers including Quadratic Gaussian (QG, K-Nearest Neighbors (KNN, and Neural Networks (NN were investigated. The accuracy of classifiers was evaluated using Receiver Operating Characteristic (ROC curve analysis in addition to sensitivity and specificity measurements. We opted for an NN model due to its superior performance in classification of retinal pixels as vascular and non-vascular. Results: The proposed method achieved an overall accuracy of 96.9%, sensitivity of 96.8%, and specificity of 97.3% for identification of retinal blood vessels using a dataset of 40 images. The area under the ROC curve reached a value of 0.967. Conclusion: Automated tracking and identification of retinal blood vessels based on Gabor filters and neural network classifiers seems highly successful. Through a comprehensive optimization process of operational parameters, our proposed scheme does not require any user intervention and has consistent performance for both normal and abnormal images.

  10. Automated fast extraction of nitrated polycyclic aromatic hydrocarbons from soil by focused microwave-assisted Soxhlet extraction prior to gas chromatography--electron-capture detection.

    Science.gov (United States)

    Priego-Capote, F; Luque-García, J L; Luque de Castro, M D

    2003-04-25

    An approach for the automated fast extraction of nitrated polycyclic aromatic hydrocarbons (nitroPAHs) from soil, using a focused microwave-assisted Soxhlet extractor, is proposed. The main factors affecting the extraction efficiency (namely: irradiation power, irradiation time, number of cycles and extractant volume) were optimised by using experimental design methodology. The reduction of the nitro-PAHs to amino-PAHs and the derivatisation of the reduced analytes with heptafluorobutyric anhydride was mandatory prior to the separation-determination step by gas chromatography--electron-capture detection. The proposed approach has allowed the extraction of these pollutants from spiked and "real" contaminated soils with extraction efficiencies similar to those provided by the US Environmental Protection Agency methods 3540-8091, but with a drastic reduction in both the extraction time and sample handling, and using less organic solvent, as 75-85% of it was recycled.

  11. BLINKER: Automated Extraction of Ocular Indices from EEG Enabling Large-Scale Analysis.

    Science.gov (United States)

    Kleifges, Kelly; Bigdely-Shamlo, Nima; Kerick, Scott E; Robbins, Kay A

    2017-01-01

    Electroencephalography (EEG) offers a platform for studying the relationships between behavioral measures, such as blink rate and duration, with neural correlates of fatigue and attention, such as theta and alpha band power. Further, the existence of EEG studies covering a variety of subjects and tasks provides opportunities for the community to better characterize variability of these measures across tasks and subjects. We have implemented an automated pipeline (BLINKER) for extracting ocular indices such as blink rate, blink duration, and blink velocity-amplitude ratios from EEG channels, EOG channels, and/or independent components (ICs). To illustrate the use of our approach, we have applied the pipeline to a large corpus of EEG data (comprising more than 2000 datasets acquired at eight different laboratories) in order to characterize variability of certain ocular indicators across subjects. We also investigate dependence of ocular indices on task in a shooter study. We have implemented our algorithms in a freely available MATLAB toolbox called BLINKER. The toolbox, which is easy to use and can be applied to collections of data without user intervention, can automatically discover which channels or ICs capture blinks. The tools extract blinks, calculate common ocular indices, generate a report for each dataset, dump labeled images of the individual blinks, and provide summary statistics across collections. Users can run BLINKER as a script or as a plugin for EEGLAB. The toolbox is available at https://github.com/VisLab/EEG-Blinks. User documentation and examples appear at http://vislab.github.io/EEG-Blinks/.

  12. Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports.

    Science.gov (United States)

    Qiu, John X; Yoon, Hong-Jun; Fearn, Paul A; Tourassi, Georgia D

    2018-01-01

    Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this study, we investigated deep learning and a convolutional neural network (CNN), for extracting ICD-O-3 topographic codes from a corpus of breast and lung cancer pathology reports. We performed two experiments, using a CNN and a more conventional term frequency vector approach, to assess the effects of class prevalence and inter-class transfer learning. The experiments were based on a set of 942 pathology reports with human expert annotations as the gold standard. CNN performance was compared against a more conventional term frequency vector space approach. We observed that the deep learning models consistently outperformed the conventional approaches in the class prevalence experiment, resulting in micro- and macro-F score increases of up to 0.132 and 0.226, respectively, when class labels were well populated. Specifically, the best performing CNN achieved a micro-F score of 0.722 over 12 ICD-O-3 topography codes. Transfer learning provided a consistent but modest performance boost for the deep learning methods but trends were contingent on the CNN method and cancer site. These encouraging results demonstrate the potential of deep learning for automated abstraction of pathology reports.

  13. Managing expectations: assessment of chemistry databases generated by automated extraction of chemical structures from patents.

    Science.gov (United States)

    Senger, Stefan; Bartek, Luca; Papadatos, George; Gaulton, Anna

    2015-12-01

    First public disclosure of new chemical entities often takes place in patents, which makes them an important source of information. However, with an ever increasing number of patent applications, manual processing and curation on such a large scale becomes even more challenging. An alternative approach better suited for this large corpus of documents is the automated extraction of chemical structures. A number of patent chemistry databases generated by using the latter approach are now available but little is known that can help to manage expectations when using them. This study aims to address this by comparing two such freely available sources, SureChEMBL and IBM SIIP (IBM Strategic Intellectual Property Insight Platform), with manually curated commercial databases. When looking at the percentage of chemical structures successfully extracted from a set of patents, using SciFinder as our reference, 59 and 51 % were also found in our comparison in SureChEMBL and IBM SIIP, respectively. When performing this comparison with compounds as starting point, i.e. establishing if for a list of compounds the databases provide the links between chemical structures and patents they appear in, we obtained similar results. SureChEMBL and IBM SIIP found 62 and 59 %, respectively, of the compound-patent pairs obtained from Reaxys. In our comparison of automatically generated vs. manually curated patent chemistry databases, the former successfully provided approximately 60 % of links between chemical structure and patents. It needs to be stressed that only a very limited number of patents and compound-patent pairs were used for our comparison. Nevertheless, our results will hopefully help to manage expectations of users of patent chemistry databases of this type and provide a useful framework for more studies like ours as well as guide future developments of the workflows used for the automated extraction of chemical structures from patents. The challenges we have encountered

  14. Development of an automated sequential injection on-line solvent extraction-back extraction procedure as demonstrated for the determination of cadmium with detection by electrothermal atomic absorption spectrometry

    DEFF Research Database (Denmark)

    Wang, Jianhua; Hansen, Elo Harald

    2002-01-01

    An automated sequential injection (SI) on-line solvent extraction-back extraction separation/preconcentration procedure is described. Demonstrated for the assay of cadmium by electrothermal atomic absorption spectrometry (ETAAS), the analyte is initially complexed with ammonium pyrrolidinedithioc......An automated sequential injection (SI) on-line solvent extraction-back extraction separation/preconcentration procedure is described. Demonstrated for the assay of cadmium by electrothermal atomic absorption spectrometry (ETAAS), the analyte is initially complexed with ammonium...

  15. Automated Extraction and Mapping for Desert Wadis from Landsat Imagery in Arid West Asia

    Directory of Open Access Journals (Sweden)

    Yongxue Liu

    2016-03-01

    Full Text Available Wadis, ephemeral dry rivers in arid desert regions that contain water in the rainy season, are often manifested as braided linear channels and are of vital importance for local hydrological environments and regional hydrological management. Conventional methods for effectively delineating wadis from heterogeneous backgrounds are limited for the following reasons: (1 the occurrence of numerous morphological irregularities which disqualify methods based on physical shape; (2 inconspicuous spectral contrast with backgrounds, resulting in frequent false alarms; and (3 the extreme complexity of wadi systems, with numerous tiny tributaries characterized by spectral anisotropy, resulting in a conflict between global and local accuracy. To overcome these difficulties, an automated method for extracting wadis (AMEW from Landsat-8 Operational Land Imagery (OLI was developed in order to take advantage of the complementarity between Water Indices (WIs, which is a technique of mathematically combining different bands to enhance water bodies and suppress backgrounds, and image processing technologies in the morphological field involving multi-scale Gaussian matched filtering and a local adaptive threshold segmentation. Evaluation of the AMEW was carried out in representative areas deliberately selected from Jordan, SW Arabian Peninsula in order to ensure a rigorous assessment. Experimental results indicate that the AMEW achieved considerably higher accuracy than other effective extraction methods in terms of visual inspection and statistical comparison, with an overall accuracy of up to 95.05% for the entire area. In addition, the AMEW (based on the New Water Index (NWI achieved higher accuracy than other methods (the maximum likelihood classifier and the support vector machine classifier used for bulk wadi extraction.

  16. Automated extraction of direct, reactive, and vat dyes from cellulosic fibers for forensic analysis by capillary electrophoresis.

    Science.gov (United States)

    Dockery, C R; Stefan, A R; Nieuwland, A A; Roberson, S N; Baguley, B M; Hendrix, J E; Morgan, S L

    2009-08-01

    Systematic designed experiments were employed to find the optimum conditions for extraction of direct, reactive, and vat dyes from cotton fibers prior to forensic characterization. Automated microextractions were coupled with measurements of extraction efficiencies on a microplate reader UV-visible spectrophotometer to enable rapid screening of extraction efficiency as a function of solvent composition. Solvent extraction conditions were also developed to be compatible with subsequent forensic characterization of extracted dyes by capillary electrophoresis with UV-visible diode array detection. The capillary electrophoresis electrolyte successfully used in this work consists of 5 mM ammonium acetate in 40:60 acetonitrile-water at pH 9.3, with the addition of sodium dithionite reducing agent to facilitate analysis of vat dyes. The ultimate goal of these research efforts is enhanced discrimination of trace fiber evidence by analysis of extracted dyes.

  17. Automated extraction and semantic analysis of mutation impacts from the biomedical literature.

    Science.gov (United States)

    Naderi, Nona; Witte, René

    2012-06-18

    ), the first comprehensive, fully open-source approach to automatically extract impacts and related relevant information from the biomedical literature. We assessed the performance of our work on manually annotated corpora and the results show the reliability of our approach. The representation of the extracted information into a structured format facilitates knowledge management and aids in database curation and correction. Furthermore, access to the analysis results is provided through multiple interfaces, including web services for automated data integration and desktop-based solutions for end user interactions.

  18. A methodology for automated CPA extraction using liver biopsy image analysis and machine learning techniques.

    Science.gov (United States)

    Tsipouras, Markos G; Giannakeas, Nikolaos; Tzallas, Alexandros T; Tsianou, Zoe E; Manousou, Pinelopi; Hall, Andrew; Tsoulos, Ioannis; Tsianos, Epameinondas

    2017-03-01

    Collagen proportional area (CPA) extraction in liver biopsy images provides the degree of fibrosis expansion in liver tissue, which is the most characteristic histological alteration in hepatitis C virus (HCV). Assessment of the fibrotic tissue is currently based on semiquantitative staging scores such as Ishak and Metavir. Since its introduction as a fibrotic tissue assessment technique, CPA calculation based on image analysis techniques has proven to be more accurate than semiquantitative scores. However, CPA has yet to reach everyday clinical practice, since the lack of standardized and robust methods for computerized image analysis for CPA assessment have proven to be a major limitation. The current work introduces a three-stage fully automated methodology for CPA extraction based on machine learning techniques. Specifically, clustering algorithms have been employed for background-tissue separation, as well as for fibrosis detection in liver tissue regions, in the first and the third stage of the methodology, respectively. Due to the existence of several types of tissue regions in the image (such as blood clots, muscle tissue, structural collagen, etc.), classification algorithms have been employed to identify liver tissue regions and exclude all other non-liver tissue regions from CPA computation. For the evaluation of the methodology, 79 liver biopsy images have been employed, obtaining 1.31% mean absolute CPA error, with 0.923 concordance correlation coefficient. The proposed methodology is designed to (i) avoid manual threshold-based and region selection processes, widely used in similar approaches presented in the literature, and (ii) minimize CPA calculation time. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  19. Neuron Image Analyzer: Automated and Accurate Extraction of Neuronal Data from Low Quality Images.

    Science.gov (United States)

    Kim, Kwang-Min; Son, Kilho; Palmore, G Tayhas R

    2015-11-23

    Image analysis software is an essential tool used in neuroscience and neural engineering to evaluate changes in neuronal structure following extracellular stimuli. Both manual and automated methods in current use are severely inadequate at detecting and quantifying changes in neuronal morphology when the images analyzed have a low signal-to-noise ratio (SNR). This inadequacy derives from the fact that these methods often include data from non-neuronal structures or artifacts by simply tracing pixels with high intensity. In this paper, we describe Neuron Image Analyzer (NIA), a novel algorithm that overcomes these inadequacies by employing Laplacian of Gaussian filter and graphical models (i.e., Hidden Markov Model, Fully Connected Chain Model) to specifically extract relational pixel information corresponding to neuronal structures (i.e., soma, neurite). As such, NIA that is based on vector representation is less likely to detect false signals (i.e., non-neuronal structures) or generate artifact signals (i.e., deformation of original structures) than current image analysis algorithms that are based on raster representation. We demonstrate that NIA enables precise quantification of neuronal processes (e.g., length and orientation of neurites) in low quality images with a significant increase in the accuracy of detecting neuronal changes post-stimulation.

  20. Automated Tongue Feature Extraction for ZHENG Classification in Traditional Chinese Medicine

    Directory of Open Access Journals (Sweden)

    Ratchadaporn Kanawong

    2012-01-01

    Full Text Available ZHENG, Traditional Chinese Medicine syndrome, is an integral and essential part of Traditional Chinese Medicine theory. It defines the theoretical abstraction of the symptom profiles of individual patients and thus, used as a guideline in disease classification in Chinese medicine. For example, patients suffering from gastritis may be classified as Cold or Hot ZHENG, whereas patients with different diseases may be classified under the same ZHENG. Tongue appearance is a valuable diagnostic tool for determining ZHENG in patients. In this paper, we explore new modalities for the clinical characterization of ZHENG using various supervised machine learning algorithms. We propose a novel-color-space-based feature set, which can be extracted from tongue images of clinical patients to build an automated ZHENG classification system. Given that Chinese medical practitioners usually observe the tongue color and coating to determine a ZHENG type and to diagnose different stomach disorders including gastritis, we propose using machine-learning techniques to establish the relationship between the tongue image features and ZHENG by learning through examples. The experimental results obtained over a set of 263 gastritis patients, most of whom suffering Cold Zheng or Hot ZHENG, and a control group of 48 healthy volunteers demonstrate an excellent performance of our proposed system.

  1. Automated Diagnosis of Glaucoma Using Empirical Wavelet Transform and Correntropy Features Extracted From Fundus Images.

    Science.gov (United States)

    Maheshwari, Shishir; Pachori, Ram Bilas; Acharya, U Rajendra

    2017-05-01

    Glaucoma is an ocular disorder caused due to increased fluid pressure in the optic nerve. It damages the optic nerve and subsequently causes loss of vision. The available scanning methods are Heidelberg retinal tomography, scanning laser polarimetry, and optical coherence tomography. These methods are expensive and require experienced clinicians to use them. So, there is a need to diagnose glaucoma accurately with low cost. Hence, in this paper, we have presented a new methodology for an automated diagnosis of glaucoma using digital fundus images based on empirical wavelet transform (EWT). The EWT is used to decompose the image, and correntropy features are obtained from decomposed EWT components. These extracted features are ranked based on t value feature selection algorithm. Then, these features are used for the classification of normal and glaucoma images using least-squares support vector machine (LS-SVM) classifier. The LS-SVM is employed for classification with radial basis function, Morlet wavelet, and Mexican-hat wavelet kernels. The classification accuracy of the proposed method is 98.33% and 96.67% using threefold and tenfold cross validation, respectively.

  2. A multi-atlas based method for automated anatomical rat brain MRI segmentation and extraction of PET activity.

    Science.gov (United States)

    Lancelot, Sophie; Roche, Roxane; Slimen, Afifa; Bouillot, Caroline; Levigoureux, Elise; Langlois, Jean-Baptiste; Zimmer, Luc; Costes, Nicolas

    2014-01-01

    Preclinical in vivo imaging requires precise and reproducible delineation of brain structures. Manual segmentation is time consuming and operator dependent. Automated segmentation as usually performed via single atlas registration fails to account for anatomo-physiological variability. We present, evaluate, and make available a multi-atlas approach for automatically segmenting rat brain MRI and extracting PET activies. High-resolution 7T 2DT2 MR images of 12 Sprague-Dawley rat brains were manually segmented into 27-VOI label volumes using detailed protocols. Automated methods were developed with 7/12 atlas datasets, i.e. the MRIs and their associated label volumes. MRIs were registered to a common space, where an MRI template and a maximum probability atlas were created. Three automated methods were tested: 1/registering individual MRIs to the template, and using a single atlas (SA), 2/using the maximum probability atlas (MP), and 3/registering the MRIs from the multi-atlas dataset to an individual MRI, propagating the label volumes and fusing them in individual MRI space (propagation & fusion, PF). Evaluation was performed on the five remaining rats which additionally underwent [18F]FDG PET. Automated and manual segmentations were compared for morphometric performance (assessed by comparing volume bias and Dice overlap index) and functional performance (evaluated by comparing extracted PET measures). Only the SA method showed volume bias. Dice indices were significantly different between methods (PF>MP>SA). PET regional measures were more accurate with multi-atlas methods than with SA method. Multi-atlas methods outperform SA for automated anatomical brain segmentation and PET measure's extraction. They perform comparably to manual segmentation for FDG-PET quantification. Multi-atlas methods are suitable for rapid reproducible VOI analyses.

  3. Evaluation of five automated and one manual method for Toxoplasma and human DNA extraction from artificially spiked amniotic fluid.

    Science.gov (United States)

    Yera, H; Ménégaut, L; Brenier-Pinchart, M-P; Touafek, F; Bastien, P; Dalle, F

    2018-01-31

    Molecular detection of Toxoplasma gondii plays a crucial role in the prenatal and neonatal diagnosis of congenital toxoplasmosis (CT). Sensitivity of this diagnosis is partly related to the efficiency of parasite DNA extraction and amplification. DNA extraction methods with automated platforms have been developed. Therefore, it is essential to evaluate them in combination with adequate PCR amplification assays. In this multisite study, we investigated the suitability of two recent automated procedures for the isolation of Toxoplasma DNA from amniotic fluid (AF) (Magtration system 12GC, PSS and Freedom EVO VacS, Tecan), compared with three other automated procedures (MagNAPure Compact, Roche, BioRobot EZ1, Qiagen and modified NucliSens easyMAG, bioMérieux) and with the manual DNA extraction QIAamp DNA Mini kit (Qiagen). Two Toxoplasma PCR assays targeting the '529-bp' repeat DNA element were used, based upon dual hybridization (FRET) or hydrolysis (TaqMan) probes. A total of 1296 PCRs were performed including 972 Toxoplasma PCRs. We showed variable efficacy (4.2%-100% positive results) among the DNA extraction procedures in isolating up to five T. gondii cells/mL in AF samples. Moreover, for a given DNA extraction method, variable results were obtained among the two Toxoplasma PCR assays for detecting up to five T. gondii cells/mL: when using TaqMan PCR, all the automated systems yielded more than 60% positive results. Nevertheless, when testing the DNA extracts in triplicate, four out of six extraction methods allowed a satisfactory detection of low amounts of T. gondii DNA (≥33% of positive results) independently of the PCR assay used. Despite the influence of the subsequent PCR method used, this study should help microbiologists in the choice of DNA extraction methods for the detection of T. gondii in amniotic fluid. The extraction method should be checked as adequate for the PCR assay used. Copyright © 2018 European Society of Clinical Microbiology and

  4. Extraction of Citrus Hystrix D.C. (Kaffir Lime) Essential Oil Using Automated Steam Distillation Process: Analysis of Volatile Compounds

    International Nuclear Information System (INIS)

    Nurhani Kasuan; Zuraida Muhammad; Zakiah Yusoff; Mohd Hezri Fazalul Rahiman; Mohd Nasir Taib; Zaibunnisa Abdul Haiyee

    2013-01-01

    An automated steam distillation was successfully used to extract volatiles from Citrus hystrix D.C (Kaffir lime) peels. The automated steam distillation integrated with robust temperature control can commercially produce large amount of essential oil with efficient heating system. Objective of this study is to quantify the oil production rate using automated steam distillation and analyze the composition of volatiles in Kaffir lime peels oil at different controlled and uncontrolled temperature conditions. From the experimentation, oil extraction from Kaffir lime peels only took approximately less than 3 hours with amount of oil yield was 13.4 % more than uncontrolled temperature. The identified major compounds from Kaffir lime peels oil were sabinene, β-pinene, limonene, α-pinene, camphene, myrcene, terpinen-4-ol, α-terpineol, linalool, terpinolene and citronellal which are considered to have good organoleptic quality. In contrast with uncontrolled temperature, oil analysis revealed that some important volatile compounds were absent such as terpinolene, linalool, terpinen-4-ol due to thermal degradation effect from fast heating of extracted material. (author)

  5. Auto-OBSD: Automatic parameter selection for reliable Oscillatory Behavior-based Signal Decomposition with an application to bearing fault signature extraction

    Science.gov (United States)

    Huang, Huan; Baddour, Natalie; Liang, Ming

    2017-03-01

    Bearing signals are often contaminated by in-band interferences and random noise. Oscillatory Behavior-based Signal Decomposition (OBSD) is a new technique which decomposes a signal according to its oscillatory behavior, rather than frequency or scale. Due to the low oscillatory transients of bearing fault-induced signals, the OBSD can be used to effectively extract bearing fault signatures from a blurred signal. However, the quality of the result highly relies on the selection of method-related parameters. Such parameters are often subjectively selected and a systematic approach has not been reported in the literature. As such, this paper proposes a systematic approach to automatic selection of OBSD parameters for reliable extraction of bearing fault signatures. The OBSD utilizes the idea of Morphological Component Analysis (MCA) that optimally projects the original signal to low oscillatory wavelets and high oscillatory wavelets established via the Tunable Q-factor Wavelet Transform (TQWT). In this paper, the effects of the selection of each parameter on the performance of the OBSD for bearing fault signature extraction are investigated. It is found that some method-related parameters can be fixed at certain values due to the nature of bearing fault-induced impulses. To adaptively tune the remaining parameters, index-guided parameter selection algorithms are proposed. A Convergence Index (CI) is proposed and a CI-guided self-tuning algorithm is developed to tune the convergence-related parameters, namely, penalty factor and number of iterations. Furthermore, a Smoothness Index (SI) is employed to measure the effectiveness of the extracted low oscillatory component (i.e. bearing fault signature). It is shown that a minimum SI implies an optimal result with respect to the adjustment of relevant parameters. Thus, two SI-guided automatic parameter selection algorithms are also developed to specify two other parameters, i.e., Q-factor of high-oscillatory wavelets and

  6. What is Fault Tolerant Control

    DEFF Research Database (Denmark)

    Blanke, Mogens; Frei, C. W.; Kraus, K.

    2000-01-01

    Faults in automated processes will often cause undesired reactions and shut-down of a controlled plant, and the consequences could be damage to the plant, to personnel or the environment. Fault-tolerant control is the synonym for a set of recent techniques that were developed to increase plant...... availability and reduce the risk of safety hazards. Its aim is to prevent that simple faults develop into serious failure. Fault-tolerant control merges several disciplines to achieve this goal, including on-line fault diagnosis, automatic condition assessment and calculation of remedial actions when a fault...

  7. a New Object Based Method for Automated Extraction of Urban Objects from Airborne Sensors Data

    Science.gov (United States)

    Moussa, A.; El-Sheimy, N.

    2012-07-01

    The classification of urban objects such as buildings, trees and roads from airborne sensors data is an essential step in numerous mapping and modelling applications. The automation of this step is greatly needed as the manual processing is costly and time consuming. The increasing availability of airborne sensors data such as aerial imagery and LIDAR data offers new opportunities to develop more robust approaches for automatic classification. These approaches should integrate these data sources that have different characteristics to exceed the accuracy achieved using any individual data source. The proposed approach presented in this paper fuses the aerial images data with single return LIDAR data to extract buildings and trees for an urban area. Object based analysis is adopted to segment the entire DSM data into objects based on height variation. These objects are preliminarily classified into buildings, trees, and ground. This primary classification is used to compute the height to ground for each object to help improve the accuracy of the second phase of classification. The overlapping perspective aerial images are used to build an ortho-photo to derive a vegetation index value for each object. The second phase of classification is performed based on the height to ground and the vegetation index of each object. The proposed approach has been tested using three areas in the centre of the city of Vaihingen provided by ISPRS test project on urban classification and 3D building reconstruction. These areas have historic buildings having rather complex shapes, few high-rising residential buildings that are surrounded by trees, and a purely residential area with small detached houses. The results of the proposed approach are presented based on a reference solution for evaluation purposes. The classification evaluation exhibits highly successful classification results of buildings class. The proposed approach follows the exact boundary of trees based on LIDAR data

  8. A NEW OBJECT BASED METHOD FOR AUTOMATED EXTRACTION OF URBAN OBJECTS FROM AIRBORNE SENSORS DATA

    Directory of Open Access Journals (Sweden)

    A. Moussa

    2012-07-01

    Full Text Available The classification of urban objects such as buildings, trees and roads from airborne sensors data is an essential step in numerous mapping and modelling applications. The automation of this step is greatly needed as the manual processing is costly and time consuming. The increasing availability of airborne sensors data such as aerial imagery and LIDAR data offers new opportunities to develop more robust approaches for automatic classification. These approaches should integrate these data sources that have different characteristics to exceed the accuracy achieved using any individual data source. The proposed approach presented in this paper fuses the aerial images data with single return LIDAR data to extract buildings and trees for an urban area. Object based analysis is adopted to segment the entire DSM data into objects based on height variation. These objects are preliminarily classified into buildings, trees, and ground. This primary classification is used to compute the height to ground for each object to help improve the accuracy of the second phase of classification. The overlapping perspective aerial images are used to build an ortho-photo to derive a vegetation index value for each object. The second phase of classification is performed based on the height to ground and the vegetation index of each object. The proposed approach has been tested using three areas in the centre of the city of Vaihingen provided by ISPRS test project on urban classification and 3D building reconstruction. These areas have historic buildings having rather complex shapes, few high-rising residential buildings that are surrounded by trees, and a purely residential area with small detached houses. The results of the proposed approach are presented based on a reference solution for evaluation purposes. The classification evaluation exhibits highly successful classification results of buildings class. The proposed approach follows the exact boundary of trees

  9. A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head.

    Science.gov (United States)

    Delora, Adam; Gonzales, Aaron; Medina, Christopher S; Mitchell, Adam; Mohed, Abdul Faheem; Jacobs, Russell E; Bearer, Elaine L

    2016-01-15

    Magnetic resonance imaging (MRI) is a well-developed technique in neuroscience. Limitations in applying MRI to rodent models of neuropsychiatric disorders include the large number of animals required to achieve statistical significance, and the paucity of automation tools for the critical early step in processing, brain extraction, which prepares brain images for alignment and voxel-wise statistics. This novel timesaving automation of template-based brain extraction ("skull-stripping") is capable of quickly and reliably extracting the brain from large numbers of whole head images in a single step. The method is simple to install and requires minimal user interaction. This method is equally applicable to different types of MR images. Results were evaluated with Dice and Jacquard similarity indices and compared in 3D surface projections with other stripping approaches. Statistical comparisons demonstrate that individual variation of brain volumes are preserved. A downloadable software package not otherwise available for extraction of brains from whole head images is included here. This software tool increases speed, can be used with an atlas or a template from within the dataset, and produces masks that need little further refinement. Our new automation can be applied to any MR dataset, since the starting point is a template mask generated specifically for that dataset. The method reliably and rapidly extracts brain images from whole head images, rendering them useable for subsequent analytical processing. This software tool will accelerate the exploitation of mouse models for the investigation of human brain disorders by MRI. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Comparison of QIAsymphony Automated and QIAamp Manual DNA Extraction Systems for Measuring Epstein-Barr Virus DNA Load in Whole Blood Using Real-Time PCR

    OpenAIRE

    Laus, Stella; Kingsley, Lawrence A.; Green, Michael; Wadowsky, Robert M.

    2011-01-01

    Automated and manual extraction systems have been used with real-time PCR for quantification of Epstein-Barr virus [human herpesvirus 4 (HHV-4)] DNA in whole blood, but few studies have evaluated relative performances. In the present study, the automated QIAsymphony and manual QIAamp extraction systems (Qiagen, Valencia, CA) were assessed using paired aliquots derived from clinical whole-blood specimens and an in-house, real-time PCR assay. The detection limits using the QIAsymphony and QIAam...

  11. A Control of Collision and Deadlock Avoidance for Automated Guided Vehicles with a Fault-Tolerance Capability

    Directory of Open Access Journals (Sweden)

    Qin Li

    2016-04-01

    Full Text Available Based on a novel discrete-event zone-control model, in our previous papers [1, 2], we presented a time-efficient traffic control for automated guided vehicle (AGV systems to exclude inter-vehicle collisions and system deadlocks, together with a case study on container terminals. The traffic control allows each vehicle in an AGV system to freely choose its routes for any finite sequence of zone-to-zone transportation tasks and the routes can be constructed in an online fashion. In this paper, we extended our previous results with two practical goals: (1 to increase the utilization of the workspace area by reducing the minimally allowed area of each zone; (2 to avoid vehicle collisions and deadlocks with the occurrence of vehicle breakdowns. To achieve the first goal, we include one extra vehicle event that allows each vehicle to probe further ahead while it is moving on the guide-path. This leads to an extension of our previous discrete-event model and traffic control rules, which are presented in the first part of the paper. The second part of the paper concerns the second goal, for which an emergency traffic control scheme is designed as supplementary to the normal traffic control rules. As in our previous papers, the improved model and traffic control are applied to a simulation of quayside container transshipment at container terminals; our simulation results are compared with those from two interesting works in the literature.

  12. Automated land cover change detection: the quest for meaningful high temporal time series extraction

    CSIR Research Space (South Africa)

    Salmon, BP

    2010-07-01

    Full Text Available An automated land cover change detection method is proposed that uses coarse resolution hyper-temporal satellite time series data. The study compared two different unsupervised clustering approaches that operate on the short term Fourier transform...

  13. Automated extraction of temporal motor activity signals from video recordings of neonatal seizures based on adaptive block matching.

    Science.gov (United States)

    Karayiannis, Nicolaos B; Sami, Abdul; Frost, James D; Wise, Merrill S; Mizrahi, Eli M

    2005-04-01

    This paper presents an automated procedure developed to extract quantitative information from video recordings of neonatal seizures in the form of motor activity signals. This procedure relies on optical flow computation to select anatomical sites located on the infants' body parts. Motor activity signals are extracted by tracking selected anatomical sites during the seizure using adaptive block matching. A block of pixels is tracked throughout a sequence of frames by searching for the most similar block of pixels in subsequent frames; this search is facilitated by employing various update strategies to account for the changing appearance of the block. The proposed procedure is used to extract temporal motor activity signals from video recordings of neonatal seizures and other events not associated with seizures.

  14. Screening for Anabolic Steroids in Urine of Forensic Cases Using Fully Automated Solid Phase Extraction and LC–MS-MS

    DEFF Research Database (Denmark)

    Andersen, David Wederkinck; Linnet, Kristian

    2014-01-01

    A screening method for 18 frequently measured exogenous anabolic steroids and the testosterone/epitestosterone (T/E) ratio in forensic cases has been developed and validated. The method involves a fully automated sample preparation including enzyme treatment, addition of internal standards...... and solid phase extraction followed by analysis by liquid chromatography-tandem mass spectrometry (LC-MS-MS) using electrospray ionization with adduct formation for two compounds. Urine samples from 580 forensic cases were analyzed to determine the T/E ratio and occurrence of exogenous anabolic steroids...... were seen in the majority of cases. The method presented serves as a fast and automated screening procedure, proving the suitability of LC-MS-MS for analyzing anabolic steroids....

  15. Development of a relatively cheap and simple automated separation system for a routine separation procedure based on extraction chromatography

    International Nuclear Information System (INIS)

    Petro Zoriy; Reinhold Flucht; Mechthild Burow; Peter Ostapczuk; Reinhard Lennartz; Myroslav Zoriy

    2010-01-01

    A robust analytical method has been developed in our laboratory for the separation of radionuclides by means of extraction chromatography using an automated separation system. The proposed method is both cheap and simple and provides the advantageous, rapid and accurate separation of the element of interest. The automated separation system enables a shorter separation time by maintaining a constant flow rate of solution and by avoiding clogging or bubbling in the chromatographic column. The present separation method was tested with two types of samples (water and urine) using UTEVA-, TRU- and Sr-specific resins for the separation of U, Th, Am, Pu and Sr. The total separation time for one radionuclide ranged from 60 to 100 min with the separation yield ranging from 68 to 98% depending on the elements separated. We used ICP-QMS, multi-low-level counter and alpha spectroscopy to measure the corresponding elements. (author)

  16. Semi-automated extraction of landslides in Taiwan based on SPOT imagery and DEMs

    Science.gov (United States)

    Eisank, Clemens; Hölbling, Daniel; Friedl, Barbara; Chen, Yi-Chin; Chang, Kang-Tsung

    2014-05-01

    The vast availability and improved quality of optical satellite data and digital elevation models (DEMs), as well as the need for complete and up-to-date landslide inventories at various spatial scales have fostered the development of semi-automated landslide recognition systems. Among the tested approaches for designing such systems, object-based image analysis (OBIA) stepped out to be a highly promising methodology. OBIA offers a flexible, spatially enabled framework for effective landslide mapping. Most object-based landslide mapping systems, however, have been tailored to specific, mainly small-scale study areas or even to single landslides only. Even though reported mapping accuracies tend to be higher than for pixel-based approaches, accuracy values are still relatively low and depend on the particular study. There is still room to improve the applicability and objectivity of object-based landslide mapping systems. The presented study aims at developing a knowledge-based landslide mapping system implemented in an OBIA environment, i.e. Trimble eCognition. In comparison to previous knowledge-based approaches, the classification of segmentation-derived multi-scale image objects relies on digital landslide signatures. These signatures hold the common operational knowledge on digital landslide mapping, as reported by 25 Taiwanese landslide experts during personal semi-structured interviews. Specifically, the signatures include information on commonly used data layers, spectral and spatial features, and feature thresholds. The signatures guide the selection and implementation of mapping rules that were finally encoded in Cognition Network Language (CNL). Multi-scale image segmentation is optimized by using the improved Estimation of Scale Parameter (ESP) tool. The approach described above is developed and tested for mapping landslides in a sub-region of the Baichi catchment in Northern Taiwan based on SPOT imagery and a high-resolution DEM. An object

  17. Analysis of halogenated and priority pesticides at different concentration levels. Automated SPE extraction followed by isotope dilution-GC/MS

    Energy Technology Data Exchange (ETDEWEB)

    Planas, C.; Saulo, J.; Rivera, J.; Caixach, J. [Institut Investigacions Quimiques i Ambientals (IIQAB-CSIC), Barcelona (Spain)

    2004-09-15

    In this work, automatic SPE extraction of 16 pesticides and metabolites with the automated Power-Prep trademark system is evaluated at different concentration levels using polymeric (ENV+) and C{sub 18} sorbent phases. The method was optimised by comparing recoveries obtained using different eluting solvents. The optimised procedure was then applied to spiked water samples at concentration levels of 0.1{mu}g/L (quality standard for individual pesticides in drinking water) and 0.02{mu}g/L (close to the detection limit of most pesticides).

  18. Automated on-line liquid–liquid extraction system for temporal mass spectrometric analysis of dynamic samples

    Energy Technology Data Exchange (ETDEWEB)

    Hsieh, Kai-Ta; Liu, Pei-Han [Department of Applied Chemistry, National Chiao Tung University, 1001 University Rd, Hsinchu, 300, Taiwan (China); Urban, Pawel L. [Department of Applied Chemistry, National Chiao Tung University, 1001 University Rd, Hsinchu, 300, Taiwan (China); Institute of Molecular Science, National Chiao Tung University, 1001 University Rd, Hsinchu, 300, Taiwan (China)

    2015-09-24

    Most real samples cannot directly be infused to mass spectrometers because they could contaminate delicate parts of ion source and guides, or cause ion suppression. Conventional sample preparation procedures limit temporal resolution of analysis. We have developed an automated liquid–liquid extraction system that enables unsupervised repetitive treatment of dynamic samples and instantaneous analysis by mass spectrometry (MS). It incorporates inexpensive open-source microcontroller boards (Arduino and Netduino) to guide the extraction and analysis process. Duration of every extraction cycle is 17 min. The system enables monitoring of dynamic processes over many hours. The extracts are automatically transferred to the ion source incorporating a Venturi pump. Operation of the device has been characterized (repeatability, RSD = 15%, n = 20; concentration range for ibuprofen, 0.053–2.000 mM; LOD for ibuprofen, ∼0.005 mM; including extraction and detection). To exemplify its usefulness in real-world applications, we implemented this device in chemical profiling of pharmaceutical formulation dissolution process. Temporal dissolution profiles of commercial ibuprofen and acetaminophen tablets were recorded during 10 h. The extraction-MS datasets were fitted with exponential functions to characterize the rates of release of the main and auxiliary ingredients (e.g. ibuprofen, k = 0.43 ± 0.01 h{sup −1}). The electronic control unit of this system interacts with the operator via touch screen, internet, voice, and short text messages sent to the mobile phone, which is helpful when launching long-term (e.g. overnight) measurements. Due to these interactive features, the platform brings the concept of the Internet-of-Things (IoT) to the chemistry laboratory environment. - Highlights: • Mass spectrometric analysis normally requires sample preparation. • Liquid–liquid extraction can isolate analytes from complex matrices. • The proposed system automates

  19. Automated on-line liquid–liquid extraction system for temporal mass spectrometric analysis of dynamic samples

    International Nuclear Information System (INIS)

    Hsieh, Kai-Ta; Liu, Pei-Han; Urban, Pawel L.

    2015-01-01

    Most real samples cannot directly be infused to mass spectrometers because they could contaminate delicate parts of ion source and guides, or cause ion suppression. Conventional sample preparation procedures limit temporal resolution of analysis. We have developed an automated liquid–liquid extraction system that enables unsupervised repetitive treatment of dynamic samples and instantaneous analysis by mass spectrometry (MS). It incorporates inexpensive open-source microcontroller boards (Arduino and Netduino) to guide the extraction and analysis process. Duration of every extraction cycle is 17 min. The system enables monitoring of dynamic processes over many hours. The extracts are automatically transferred to the ion source incorporating a Venturi pump. Operation of the device has been characterized (repeatability, RSD = 15%, n = 20; concentration range for ibuprofen, 0.053–2.000 mM; LOD for ibuprofen, ∼0.005 mM; including extraction and detection). To exemplify its usefulness in real-world applications, we implemented this device in chemical profiling of pharmaceutical formulation dissolution process. Temporal dissolution profiles of commercial ibuprofen and acetaminophen tablets were recorded during 10 h. The extraction-MS datasets were fitted with exponential functions to characterize the rates of release of the main and auxiliary ingredients (e.g. ibuprofen, k = 0.43 ± 0.01 h −1 ). The electronic control unit of this system interacts with the operator via touch screen, internet, voice, and short text messages sent to the mobile phone, which is helpful when launching long-term (e.g. overnight) measurements. Due to these interactive features, the platform brings the concept of the Internet-of-Things (IoT) to the chemistry laboratory environment. - Highlights: • Mass spectrometric analysis normally requires sample preparation. • Liquid–liquid extraction can isolate analytes from complex matrices. • The proposed system automates the

  20. An Automated Approach to Extracting River Bank Locations from Aerial Imagery Using Image Texture

    Science.gov (United States)

    2015-11-04

    consuming and labour intensive, and the quality is dependent on the individual doing the task. This paper describes a quick and fully automated method for...generally considered to be supervised classification techniques in that they require the active input of a trained analyst to define the characteristics of

  1. Fault Tolerant Control Systems

    DEFF Research Database (Denmark)

    Bøgh, S. A.

    This thesis considered the development of fault tolerant control systems. The focus was on the category of automated processes that do not necessarily comprise a high number of identical sensors and actuators to maintain safe operation, but still have a potential for improving immunity to component...... failures. It is often feasible to increase availability for these control loops by designing the control system to perform on-line detection and reconfiguration in case of faults before the safety system makes a close-down of the process. A general development methodology is given in the thesis...... that carried the control system designer through the steps necessary to consider fault handling in an early design phase. It was shown how an existing control loop with interface to the plant wide control system could be extended with three additional modules to obtain fault tolerance: Fault detection...

  2. Screening for anabolic steroids in urine of forensic cases using fully automated solid phase extraction and LC-MS-MS.

    Science.gov (United States)

    Andersen, David W; Linnet, Kristian

    2014-01-01

    A screening method for 18 frequently measured exogenous anabolic steroids and the testosterone/epitestosterone (T/E) ratio in forensic cases has been developed and validated. The method involves a fully automated sample preparation including enzyme treatment, addition of internal standards and solid phase extraction followed by analysis by liquid chromatography-tandem mass spectrometry (LC-MS-MS) using electrospray ionization with adduct formation for two compounds. Urine samples from 580 forensic cases were analyzed to determine the T/E ratio and occurrence of exogenous anabolic steroids. Extraction recoveries ranged from 77 to 95%, matrix effects from 48 to 78%, overall process efficiencies from 40 to 54% and the lower limit of identification ranged from 2 to 40 ng/mL. In the 580 urine samples analyzed from routine forensic cases, 17 (2.9%) were found positive for one or more anabolic steroids. Only seven different steroids including testosterone were found in the material, suggesting that only a small number of common steroids are likely to occur in a forensic context. The steroids were often in high concentrations (>100 ng/mL), and a combination of steroids and/or other drugs of abuse were seen in the majority of cases. The method presented serves as a fast and automated screening procedure, proving the suitability of LC-MS-MS for analyzing anabolic steroids. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  3. Analog integrated circuit design automation placement, routing and parasitic extraction techniques

    CERN Document Server

    Martins, Ricardo; Horta, Nuno

    2017-01-01

    This book introduces readers to a variety of tools for analog layout design automation. After discussing the placement and routing problem in electronic design automation (EDA), the authors overview a variety of automatic layout generation tools, as well as the most recent advances in analog layout-aware circuit sizing. The discussion includes different methods for automatic placement (a template-based Placer and an optimization-based Placer), a fully-automatic Router and an empirical-based Parasitic Extractor. The concepts and algorithms of all the modules are thoroughly described, enabling readers to reproduce the methodologies, improve the quality of their designs, or use them as starting point for a new tool. All the methods described are applied to practical examples for a 130nm design process, as well as placement and routing benchmark sets. Introduces readers to hierarchical combination of Pareto fronts of placements; Presents electromigration-aware routing with multilayer multiport terminal structures...

  4. Analysis of polycyclic aromatic hydrocarbons in soil: minimizing sample pretreatment using automated Soxhlet with ethyl acetate as extraction solvent.

    Science.gov (United States)

    Szolar, Oliver H J; Rost, Helmut; Braun, Rudolf; Loibner, Andreas P

    2002-05-15

    A simplified sample pretreatment method for industrially PAH-contaminated soils applying automated Soxhlet (Soxtherm) with ethyl acetate as extraction solvent is presented. Laborious pretreatment steps such as drying of samples, cleanup of crude extracts, and solvent exchange were allowed to be bypassed without notable performance impact. Moisture of the soil samples did not significantly influence recoveries of PAHs at a wide range of water content for the newly developed method. However, the opposite was true for the standard procedure using the more apolar 1:1 (v/v) n-hexane/acetone solvent mixture including postextraction treatments recommended by the U.S. EPA. Moreover, ethyl acetate crude extracts did not appreciably effect the chromatographic performance (HPLC-(3D)FLD), which was confirmed by a comparison of the purity of PAH spectra from both pretreatment methods. Up to 20% (v/v) in acetonitrile, ethyl acetate proved to be fully compatible with the mobile phase of the HPLC whereas the same concentration of n-hexane/acetone in acetonitrile resulted in significant retention time shifts. The newly developed pretreatment method was applied to three historically contaminated soils from different sources with extraction efficiencies not being significantly different compared to the standard procedure. Finally, the certified reference soil CRM 524 was subjected to the simplified procedure resulting in quantitative recoveries (>92%) for all PAHs analyzed.

  5. A Rolling Element Bearing Fault Diagnosis Approach Based on Multifractal Theory and Gray Relation Theory.

    Directory of Open Access Journals (Sweden)

    Jingchao Li

    Full Text Available Bearing failure is one of the dominant causes of failure and breakdowns in rotating machinery, leading to huge economic loss. Aiming at the nonstationary and nonlinear characteristics of bearing vibration signals as well as the complexity of condition-indicating information distribution in the signals, a novel rolling element bearing fault diagnosis method based on multifractal theory and gray relation theory was proposed in the paper. Firstly, a generalized multifractal dimension algorithm was developed to extract the characteristic vectors of fault features from the bearing vibration signals, which can offer more meaningful and distinguishing information reflecting different bearing health status in comparison with conventional single fractal dimension. After feature extraction by multifractal dimensions, an adaptive gray relation algorithm was applied to implement an automated bearing fault pattern recognition. The experimental results show that the proposed method can identify various bearing fault types as well as severities effectively and accurately.

  6. A Rolling Element Bearing Fault Diagnosis Approach Based on Multifractal Theory and Gray Relation Theory.

    Science.gov (United States)

    Li, Jingchao; Cao, Yunpeng; Ying, Yulong; Li, Shuying

    2016-01-01

    Bearing failure is one of the dominant causes of failure and breakdowns in rotating machinery, leading to huge economic loss. Aiming at the nonstationary and nonlinear characteristics of bearing vibration signals as well as the complexity of condition-indicating information distribution in the signals, a novel rolling element bearing fault diagnosis method based on multifractal theory and gray relation theory was proposed in the paper. Firstly, a generalized multifractal dimension algorithm was developed to extract the characteristic vectors of fault features from the bearing vibration signals, which can offer more meaningful and distinguishing information reflecting different bearing health status in comparison with conventional single fractal dimension. After feature extraction by multifractal dimensions, an adaptive gray relation algorithm was applied to implement an automated bearing fault pattern recognition. The experimental results show that the proposed method can identify various bearing fault types as well as severities effectively and accurately.

  7. Automated on-line liquid-liquid extraction system for temporal mass spectrometric analysis of dynamic samples.

    Science.gov (United States)

    Hsieh, Kai-Ta; Liu, Pei-Han; Urban, Pawel L

    2015-09-24

    Most real samples cannot directly be infused to mass spectrometers because they could contaminate delicate parts of ion source and guides, or cause ion suppression. Conventional sample preparation procedures limit temporal resolution of analysis. We have developed an automated liquid-liquid extraction system that enables unsupervised repetitive treatment of dynamic samples and instantaneous analysis by mass spectrometry (MS). It incorporates inexpensive open-source microcontroller boards (Arduino and Netduino) to guide the extraction and analysis process. Duration of every extraction cycle is 17 min. The system enables monitoring of dynamic processes over many hours. The extracts are automatically transferred to the ion source incorporating a Venturi pump. Operation of the device has been characterized (repeatability, RSD = 15%, n = 20; concentration range for ibuprofen, 0.053-2.000 mM; LOD for ibuprofen, ∼0.005 mM; including extraction and detection). To exemplify its usefulness in real-world applications, we implemented this device in chemical profiling of pharmaceutical formulation dissolution process. Temporal dissolution profiles of commercial ibuprofen and acetaminophen tablets were recorded during 10 h. The extraction-MS datasets were fitted with exponential functions to characterize the rates of release of the main and auxiliary ingredients (e.g. ibuprofen, k = 0.43 ± 0.01 h(-1)). The electronic control unit of this system interacts with the operator via touch screen, internet, voice, and short text messages sent to the mobile phone, which is helpful when launching long-term (e.g. overnight) measurements. Due to these interactive features, the platform brings the concept of the Internet-of-Things (IoT) to the chemistry laboratory environment. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Technical Note: Semi-automated effective width extraction from time-lapse RGB imagery of a remote, braided Greenlandic river

    Science.gov (United States)

    Gleason, C. J.; Smith, L. C.; Finnegan, D. C.; LeWinter, A. L.; Pitcher, L. H.; Chu, V. W.

    2015-06-01

    River systems in remote environments are often challenging to monitor and understand where traditional gauging apparatus are difficult to install or where safety concerns prohibit field measurements. In such cases, remote sensing, especially terrestrial time-lapse imaging platforms, offer a means to better understand these fluvial systems. One such environment is found at the proglacial Isortoq River in southwestern Greenland, a river with a constantly shifting floodplain and remote Arctic location that make gauging and in situ measurements all but impossible. In order to derive relevant hydraulic parameters for this river, two true color (RGB) cameras were installed in July 2011, and these cameras collected over 10 000 half hourly time-lapse images of the river by September of 2012. Existing approaches for extracting hydraulic parameters from RGB imagery require manual or supervised classification of images into water and non-water areas, a task that was impractical for the volume of data in this study. As such, automated image filters were developed that removed images with environmental obstacles (e.g., shadows, sun glint, snow) from the processing stream. Further image filtering was accomplished via a novel automated histogram similarity filtering process. This similarity filtering allowed successful (mean accuracy 79.6 %) supervised classification of filtered images from training data collected from just 10 % of those images. Effective width, a hydraulic parameter highly correlated with discharge in braided rivers, was extracted from these classified images, producing a hydrograph proxy for the Isortoq River between 2011 and 2012. This hydrograph proxy shows agreement with historic flooding observed in other parts of Greenland in July 2012 and offers promise that the imaging platform and processing methodology presented here will be useful for future monitoring studies of remote rivers.

  9. Automated extraction of DNA from blood and PCR setup using a Tecan Freedom EVO liquid handler for forensic genetic STR typing of reference samples

    DEFF Research Database (Denmark)

    Stangegaard, Michael; Frøslev, Tobias G; Frank-Hansen, Rune

    2011-01-01

    17025 using the Qiagen MagAttract DNA Mini M48 kit (Qiagen GmbH, Hilden, Germany) from fresh whole blood and blood from deceased individuals. The workflow was simplified by returning the DNA extracts to the original tubes minimizing the risk of misplacing samples. The tubes that originally contained...... the samples were washed with MilliQ water before the return of the DNA extracts. The PCR was setup in 96-well microtiter plates. The methods were validated for the kits: AmpFlSTR Identifiler, SGM Plus and Yfiler (Applied Biosystems, Foster City, CA), GenePrint FFFL and PowerPlex Y (Promega, Madison, WI......). The automated protocols allowed for extraction and addition of PCR master mix of 96 samples within 3.5h. In conclusion, we demonstrated that (1) DNA extraction with magnetic beads and (2) PCR setup for accredited, forensic genetic short tandem repeat typing can be implemented on a simple automated liquid...

  10. Diagnosis and fault-tolerant control

    CERN Document Server

    Blanke, Mogens; Lunze, Jan; Staroswiecki, Marcel

    2016-01-01

    Fault-tolerant control aims at a gradual shutdown response in automated systems when faults occur. It satisfies the industrial demand for enhanced availability and safety, in contrast to traditional reactions to faults, which bring about sudden shutdowns and loss of availability. The book presents effective model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault through the process, to test the fault detectability and to find the redundancies in the process that can be used to ensure fault tolerance. It also introduces design methods suitable for diagnostic systems and fault-tolerant controllers for continuous processes that are described by analytical models of discrete-event systems represented by automata. The book is suitable for engineering students, engineers in industry and researchers who wish to get an overview of the variety of approaches to process diagnosis and fault-tolerant contro...

  11. The ESO-LV project - Automated parameter extraction for 16000 ESO/Uppsala galaxies

    NARCIS (Netherlands)

    Lauberts, Andris; Valentijn, Edwin A.

    1987-01-01

    A program to extract photometric and morphological parameters of the galaxies in the ESO/Uppsala survey (Lauberts and Valentijn, 1982) is discussed. The completeness and accuracy of the survey are evaluated and compared with other surveys. The parameters obtained in the program are listed.

  12. A Simple Method for Automated Solid Phase Extraction of Water Samples for Immunological Analysis of Small Pollutants.

    Science.gov (United States)

    Heub, Sarah; Tscharner, Noe; Kehl, Florian; Dittrich, Petra S; Follonier, Stéphane; Barbe, Laurent

    2016-01-01

    A new method for solid phase extraction (SPE) of environmental water samples is proposed. The developed prototype is cost-efficient and user friendly, and enables to perform rapid, automated and simple SPE. The pre-concentrated solution is compatible with analysis by immunoassay, with a low organic solvent content. A method is described for the extraction and pre-concentration of natural hormone 17β-estradiol in 100 ml water samples. Reverse phase SPE is performed with octadecyl-silica sorbent and elution is done with 200 µl of methanol 50% v/v. Eluent is diluted by adding di-water to lower the amount of methanol. After preparing manually the SPE column, the overall procedure is performed automatically within 1 hr. At the end of the process, estradiol concentration is measured by using a commercial enzyme-linked immune-sorbent assay (ELISA). 100-fold pre-concentration is achieved and the methanol content in only 10% v/v. Full recoveries of the molecule are achieved with 1 ng/L spiked de-ionized and synthetic sea water samples.

  13. Predicted versus actual intraocular lens power in silicon-oil-filled eyes undergoing cataract extraction using automated intraoperative retinoscopy.

    Science.gov (United States)

    Elbendary, Amal M; Elwan, Mohamed M

    2012-08-01

    To compare predicted intraocular lens (IOL) power obtained with adjusted ultrasound biometry versus actual power obtained with automated intraoperative retinoscopy (AIR) in eyes undergoing combined cataract extraction and silicon oil removal in the same session. Fifty eyes with significant cataract; requiring silicon removal were included. Preoperative ultrasonic biometry with adjusted velocity (980 m/s) was recorded. After silicon removal, AIR was done and IOL power was calculated and inserted. Postoperative refraction was recorded up to 3 months. AIR was successfully obtained in all eyes. Significant correlation (p = 0.000, R = 0.91) was detected between mean power of predicted (15.8 ± 8.4) and implanted IOL (11.7 ± 8.5). Mean postoperative refraction was +0.53 ± 0.31 at 1 week, +0.40 ± 0.35 at 1 month and +0.12 ± 0.20 at 3 months. The difference was statistically significant in all time intervals. Myopic shift occurred in 37% of eyes at the third month. AIR in combined cataract extraction and silicon oil removal is easy and provides predictable outcome in all eyes. It represents a bypass to all methods of biometry based on axial length measurement. Future correction formula based on adjusted ultrasound velocity can be a simple alternative and predictable method.

  14. Application-Oriented Optimal Shift Schedule Extraction for a Dual-Motor Electric Bus with Automated Manual Transmission

    Directory of Open Access Journals (Sweden)

    Mingjie Zhao

    2018-02-01

    Full Text Available The conventional battery electric buses (BEBs have limited potential to optimize the energy consumption and reach a better dynamic performance. A practical dual-motor equipped with 4-speed Automated Manual Transmission (AMT propulsion system is proposed, which can eliminate the traction interruption in conventional AMT. A discrete model of the dual-motor-AMT electric bus (DMAEB is built and used to optimize the gear shift schedule. Dynamic programming (DP algorithm is applied to find the optimal results where the efficiency and shift time of each gear are considered to handle the application problem of global optimization. A rational penalty factor and a proper shift time delay based on bench test results are set to reduce the shift frequency by 82.5% in Chinese-World Transient Vehicle Cycle (C-WTVC. Two perspectives of applicable shift rule extraction methods, i.e., the classification method based on optimal operating points and clustering method based on optimal shifting points, are explored and compared. Eventually, the hardware-in-the-loop (HIL simulation results demonstrate that the proposed structure and extracted shift schedule can realize a significant improvement in reducing energy loss by 20.13% compared to traditional empirical strategies.

  15. Automated extraction of clinical traits of multiple sclerosis in electronic medical records

    Science.gov (United States)

    Davis, Mary F; Sriram, Subramaniam; Bush, William S; Denny, Joshua C; Haines, Jonathan L

    2013-01-01

    Objectives The clinical course of multiple sclerosis (MS) is highly variable, and research data collection is costly and time consuming. We evaluated natural language processing techniques applied to electronic medical records (EMR) to identify MS patients and the key clinical traits of their disease course. Materials and methods We used four algorithms based on ICD-9 codes, text keywords, and medications to identify individuals with MS from a de-identified, research version of the EMR at Vanderbilt University. Using a training dataset of the records of 899 individuals, algorithms were constructed to identify and extract detailed information regarding the clinical course of MS from the text of the medical records, including clinical subtype, presence of oligoclonal bands, year of diagnosis, year and origin of first symptom, Expanded Disability Status Scale (EDSS) scores, timed 25-foot walk scores, and MS medications. Algorithms were evaluated on a test set validated by two independent reviewers. Results We identified 5789 individuals with MS. For all clinical traits extracted, precision was at least 87% and specificity was greater than 80%. Recall values for clinical subtype, EDSS scores, and timed 25-foot walk scores were greater than 80%. Discussion and conclusion This collection of clinical data represents one of the largest databases of detailed, clinical traits available for research on MS. This work demonstrates that detailed clinical information is recorded in the EMR and can be extracted for research purposes with high reliability. PMID:24148554

  16. Determination of 21 drugs in oral fluid using fully automated supported liquid extraction and UHPLC-MS/MS.

    Science.gov (United States)

    Valen, Anja; Leere Øiestad, Åse Marit; Strand, Dag Helge; Skari, Ragnhild; Berg, Thomas

    2017-05-01

    Collection of oral fluid (OF) is easy and non-invasive compared to the collection of urine and blood, and interest in OF for drug screening and diagnostic purposes is increasing. A high-throughput ultra-high-performance liquid chromatography-tandem mass spectrometry method for determination of 21 drugs in OF using fully automated 96-well plate supported liquid extraction for sample preparation is presented. The method contains a selection of classic drugs of abuse, including amphetamines, cocaine, cannabis, opioids, and benzodiazepines. The method was fully validated for 200 μL OF/buffer mix using an Intercept OF sampling kit; validation included linearity, sensitivity, precision, accuracy, extraction recovery, matrix effects, stability, and carry-over. Inter-assay precision (RSD) and accuracy (relative error) were Extraction recoveries were between 58 and 76% (RSD < 8%), except for tetrahydrocannabinol and three 7-amino benzodiazepine metabolites with recoveries between 23 and 33% (RSD between 51 and 52 % and 11 and 25%, respectively). Ion enhancement or ion suppression effects were observed for a few compounds; however, to a large degree they were compensated for by the internal standards used. Deuterium-labelled and 13 C-labelled internal standards were used for 8 and 11 of the compounds, respectively. In a comparison between Intercept and Quantisal OF kits, better recoveries and fewer matrix effects were observed for some compounds using Quantisal. The method is sensitive and robust for its purposes and has been used successfully since February 2015 for analysis of Intercept OF samples from 2600 cases in a 12-month period. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  17. Automated solid-phase extraction coupled to gad chromatography with electron-capture detection: a combinatiton of extraction and clean-up of pyrethroids in the analysis of surface water.

    NARCIS (Netherlands)

    van der Hoff, G.R.; Pelusio, F.; Brinkman, U.A.T.; Baumann, R.A.; van Zoonen, P.

    1996-01-01

    The combination of automated solid-phase extraction (SPE) and large-volume introduction gas chromatography electron-capture detection (GC-ECD) is used for the determination of synthetic pyrethroids in surface and drinking water. The selectivity that is needed for the use of GC-ECD of environmental

  18. Automated Extraction of Genomic DNA from Medically Important Yeast Species and Filamentous Fungi by Using the MagNA Pure LC System

    OpenAIRE

    Loeffler, Juergen; Schmidt, Kathrin; Hebart, Holger; Schumacher, Ulrike; Einsele, Hermann

    2002-01-01

    A fully automated assay was established for the extraction of DNA from clinically important fungi by using the MagNA Pure LC instrument. The test was evaluated by DNA isolation from 23 species of yeast and filamentous fungi and by extractions (n = 28) of serially diluted Aspergillus fumigatus conidia (105 to 0 CFU/ml). Additionally, DNA from 67 clinical specimens was extracted and compared to the manual protocol. The detection limit of the MagNA Pure LC assay of 10 CFU corresponded to the sen...

  19. Detecting and extracting clusters in atom probe data: A simple, automated method using Voronoi cells

    International Nuclear Information System (INIS)

    Felfer, P.; Ceguerra, A.V.; Ringer, S.P.; Cairney, J.M.

    2015-01-01

    The analysis of the formation of clusters in solid solutions is one of the most common uses of atom probe tomography. Here, we present a method where we use the Voronoi tessellation of the solute atoms and its geometric dual, the Delaunay triangulation to test for spatial/chemical randomness of the solid solution as well as extracting the clusters themselves. We show how the parameters necessary for cluster extraction can be determined automatically, i.e. without user interaction, making it an ideal tool for the screening of datasets and the pre-filtering of structures for other spatial analysis techniques. Since the Voronoi volumes are closely related to atomic concentrations, the parameters resulting from this analysis can also be used for other concentration based methods such as iso-surfaces. - Highlights: • Cluster analysis of atom probe data can be significantly simplified by using the Voronoi cell volumes of the atomic distribution. • Concentration fields are defined on a single atomic basis using Voronoi cells. • All parameters for the analysis are determined by optimizing the separation probability of bulk atoms vs clustered atoms

  20. Detecting and extracting clusters in atom probe data: A simple, automated method using Voronoi cells

    Energy Technology Data Exchange (ETDEWEB)

    Felfer, P., E-mail: peter.felfer@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia); Ceguerra, A.V., E-mail: anna.ceguerra@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia); Ringer, S.P., E-mail: simon.ringer@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia); Cairney, J.M., E-mail: julie.cairney@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia)

    2015-03-15

    The analysis of the formation of clusters in solid solutions is one of the most common uses of atom probe tomography. Here, we present a method where we use the Voronoi tessellation of the solute atoms and its geometric dual, the Delaunay triangulation to test for spatial/chemical randomness of the solid solution as well as extracting the clusters themselves. We show how the parameters necessary for cluster extraction can be determined automatically, i.e. without user interaction, making it an ideal tool for the screening of datasets and the pre-filtering of structures for other spatial analysis techniques. Since the Voronoi volumes are closely related to atomic concentrations, the parameters resulting from this analysis can also be used for other concentration based methods such as iso-surfaces. - Highlights: • Cluster analysis of atom probe data can be significantly simplified by using the Voronoi cell volumes of the atomic distribution. • Concentration fields are defined on a single atomic basis using Voronoi cells. • All parameters for the analysis are determined by optimizing the separation probability of bulk atoms vs clustered atoms.

  1. Automated feature extraction and spatial organization of seafloor pockmarks, Belfast Bay, Maine, USA

    Science.gov (United States)

    Andrews, Brian D.; Brothers, Laura L.; Barnhardt, Walter A.

    2010-01-01

    Seafloor pockmarks occur worldwide and may represent millions of m3 of continental shelf erosion, but few numerical analyses of their morphology and spatial distribution of pockmarks exist. We introduce a quantitative definition of pockmark morphology and, based on this definition, propose a three-step geomorphometric method to identify and extract pockmarks from high-resolution swath bathymetry. We apply this GIS-implemented approach to 25 km2 of bathymetry collected in the Belfast Bay, Maine USA pockmark field. Our model extracted 1767 pockmarks and found a linear pockmark depth-to-diameter ratio for pockmarks field-wide. Mean pockmark depth is 7.6 m and mean diameter is 84.8 m. Pockmark distribution is non-random, and nearly half of the field's pockmarks occur in chains. The most prominent chains are oriented semi-normal to the steepest gradient in Holocene sediment thickness. A descriptive model yields field-wide spatial statistics indicating that pockmarks are distributed in non-random clusters. Results enable quantitative comparison of pockmarks in fields worldwide as well as similar concave features, such as impact craters, dolines, or salt pools.

  2. Automated DICOM metadata and volumetric anatomical information extraction for radiation dosimetry

    Science.gov (United States)

    Papamichail, D.; Ploussi, A.; Kordolaimi, S.; Karavasilis, E.; Papadimitroulas, P.; Syrgiamiotis, V.; Efstathopoulos, E.

    2015-09-01

    Patient-specific dosimetry calculations based on simulation techniques have as a prerequisite the modeling of the modality system and the creation of voxelized phantoms. This procedure requires the knowledge of scanning parameters and patients’ information included in a DICOM file as well as image segmentation. However, the extraction of this information is complicated and time-consuming. The objective of this study was to develop a simple graphical user interface (GUI) to (i) automatically extract metadata from every slice image of a DICOM file in a single query and (ii) interactively specify the regions of interest (ROI) without explicit access to the radiology information system. The user-friendly application developed in Matlab environment. The user can select a series of DICOM files and manage their text and graphical data. The metadata are automatically formatted and presented to the user as a Microsoft Excel file. The volumetric maps are formed by interactively specifying the ROIs and by assigning a specific value in every ROI. The result is stored in DICOM format, for data and trend analysis. The developed GUI is easy, fast and and constitutes a very useful tool for individualized dosimetry. One of the future goals is to incorporate a remote access to a PACS server functionality.

  3. Towards an Ontology for the Global Geodynamics Project: Automated Extraction of Resource Descriptions from an XML-Based Data Model

    Science.gov (United States)

    Lumb, L. I.; Aldridge, K. D.

    2005-12-01

    Using the Earth Science Markup Language (ESML), an XML-based data model for the Global Geodynamics Project (GGP) was recently introduced [Lumb & Aldridge, Proc. HPCS 2005, Kotsireas & Stacey, eds., IEEE, 2005, 216-222]. This data model possesses several key attributes -i.e., it: makes use of XML schema; supports semi-structured ASCII format files; includes Earth Science affinities; and is on track for compliance with emerging Grid computing standards (e.g., the Global Grid Forum's Data Format Description Language, DFDL). Favorable attributes notwithstanding, metadata (i.e., data about data) was identified [Lumb & Aldridge, 2005] as a key challenge for progress in enabling the GGP for Grid computing. Even in projects of small-to-medium scale like the GGP, the manual introduction of metadata has the potential to be the rate-determining metric for progress. Fortunately, an automated approach for metadata introduction has recently emerged. Based on Gleaning Resource Descriptions from Dialects of Languages (GRDDL, http://www.w3.org/2004/01/rdxh/spec), this bottom-up approach allows for the extraction of Resource Description Format (RDF) representations from the XML-based data model (i.e., the ESML representation of GGP data) subject to rules of transformation articulated via eXtensible Stylesheet Language Transformations (XSLT). In addition to introducing relationships into the GGP data model, and thereby addressing the metadata requirement, the syntax and semantics of RDF comprise a requisite for a GGP ontology - i.e., ``the common words and concepts (the meaning) used to describe and represent an area of knowledge'' [Daconta et al., The Semantic Web, Wiley, 2003]. After briefly reviewing the XML-based model for the GGP, attention focuses on the automated extraction of an RDF representation via GRDDL with XSLT-delineated templates. This bottom-up approach, in tandem with a top-down approach based on the Protege integrated development environment for ontologies (http

  4. A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

    Science.gov (United States)

    Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.

    2017-11-01

    Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.

  5. Exposing exposure: automated anatomy-specific CT radiation exposure extraction for quality assurance and radiation monitoring.

    Science.gov (United States)

    Sodickson, Aaron; Warden, Graham I; Farkas, Cameron E; Ikuta, Ichiro; Prevedello, Luciano M; Andriole, Katherine P; Khorasani, Ramin

    2012-08-01

    To develop and validate an informatics toolkit that extracts anatomy-specific computed tomography (CT) radiation exposure metrics (volume CT dose index and dose-length product) from existing digital image archives through optical character recognition of CT dose report screen captures (dose screens) combined with Digital Imaging and Communications in Medicine attributes. This institutional review board-approved HIPAA-compliant study was performed in a large urban health care delivery network. Data were drawn from a random sample of CT encounters that occurred between 2000 and 2010; images from these encounters were contained within the enterprise image archive, which encompassed images obtained at an adult academic tertiary referral hospital and its affiliated sites, including a cancer center, a community hospital, and outpatient imaging centers, as well as images imported from other facilities. Software was validated by using 150 randomly selected encounters for each major CT scanner manufacturer, with outcome measures of dose screen retrieval rate (proportion of correctly located dose screens) and anatomic assignment precision (proportion of extracted exposure data with correctly assigned anatomic region, such as head, chest, or abdomen and pelvis). The 95% binomial confidence intervals (CIs) were calculated for discrete proportions, and CIs were derived from the standard error of the mean for continuous variables. After validation, the informatics toolkit was used to populate an exposure repository from a cohort of 54 549 CT encounters; of which 29 948 had available dose screens. Validation yielded a dose screen retrieval rate of 99% (597 of 605 CT encounters; 95% CI: 98%, 100%) and an anatomic assignment precision of 94% (summed DLP fraction correct 563 in 600 CT encounters; 95% CI: 92%, 96%). Patient safety applications of the resulting data repository include benchmarking between institutions, CT protocol quality control and optimization, and cumulative

  6. Automated visual inspection of brake shoe wear

    Science.gov (United States)

    Lu, Shengfang; Liu, Zhen; Nan, Guo; Zhang, Guangjun

    2015-10-01

    With the rapid development of high-speed railway, the automated fault inspection is necessary to ensure train's operation safety. Visual technology is paid more attention in trouble detection and maintenance. For a linear CCD camera, Image alignment is the first step in fault detection. To increase the speed of image processing, an improved scale invariant feature transform (SIFT) method is presented. The image is divided into multiple levels of different resolution. Then, we do not stop to extract the feature from the lowest resolution to the highest level until we get sufficient SIFT key points. At that level, the image is registered and aligned quickly. In the stage of inspection, we devote our efforts to finding the trouble of brake shoe, which is one of the key components in brake system on electrical multiple units train (EMU). Its pre-warning on wear limitation is very important in fault detection. In this paper, we propose an automatic inspection approach to detect the fault of brake shoe. Firstly, we use multi-resolution pyramid template matching technology to fast locate the brake shoe. Then, we employ Hough transform to detect the circles of bolts in brake region. Due to the rigid characteristic of structure, we can identify whether the brake shoe has a fault. The experiments demonstrate that the way we propose has a good performance, and can meet the need of practical applications.

  7. Automated high-capacity on-line extraction and bioanalysis of dried blood spot samples using liquid chromatography/high-resolution accurate mass spectrometry.

    Science.gov (United States)

    Oliveira, Regina V; Henion, Jack; Wickremsinhe, Enaksha R

    2014-11-30

    Pharmacokinetic data to support clinical development of pharmaceuticals are routinely obtained from liquid plasma samples. The plasma samples require frozen shipment and storage and are extracted off-line from the liquid chromatography/tandem mass spectrometry (LC/MS/MS) systems. In contrast, the use of dried blood spot (DBS) sampling is an attractive alternative in part due to its benefits in microsampling as well as simpler sample storage and transport. However, from a practical aspect, sample extraction from DBS cards can be challenging as currently performed. The goal of this report was to integrate automated serial extraction of large numbers of DBS cards with on-line liquid chromatography/high-resolution accurate mass spectrometry (LC/HRAMS) bioanalysis. An automated system for direct DBS extraction coupled to a LC/HRAMS was employed for the quantification of midazolam (MDZ) and α-hydroxymidazolam (α-OHMDZ) in human blood. The target analytes were directly extracted from the DBS cards onto an on-line chromatographic guard column followed by HRAMS detection. No additional sample treatment was required. The automated DBS LC/HRAMS method was developed and validated, based on the measurement at the accurate mass-to-charge ratio of the target analytes to ensure specificity for the assay. The automated DBS LC/HRAMS method analyzed a DBS sample within 2 min without the need for punching or additional off-line sample treatment. The fully automated analytical method was shown to be sensitive and selective over the concentration range of 5 to 2000 ng/mL. Intra- and inter-day precision and accuracy was less than 15% (less than 20% at the LLOQ). The validated method was successfully applied to measure MDZ and α-OHMDZ in an incurred human sample after a single 7.5 mg dose of MDZ. The direct DBS LC/HRAMS method demonstrated successful implementation of automated DBS extraction and bioanalysis for MDZ and α-OHMDZ. This approach has the potential to promote workload

  8. Evaluation of Sample Stability and Automated DNA Extraction for Fetal Sex Determination Using Cell-Free Fetal DNA in Maternal Plasma

    Directory of Open Access Journals (Sweden)

    Elena Ordoñez

    2013-01-01

    Full Text Available Objective. The detection of paternally inherited sequences in maternal plasma, such as the SRY gene for fetal sexing or RHD for fetal blood group genotyping, is becoming part of daily routine in diagnostic laboratories. Due to the low percentage of fetal DNA, it is crucial to ensure sample stability and the efficiency of DNA extraction. We evaluated blood stability at 4°C for at least 24 hours and automated DNA extraction, for fetal sex determination in maternal plasma. Methods. A total of 158 blood samples were collected, using EDTA-K tubes, from women in their 1st trimester of pregnancy. Samples were kept at 4°C for at least 24 hours before processing. An automated DNA extraction was evaluated, and its efficiency was compared with a standard manual procedure. The SRY marker was used to quantify cfDNA by real-time PCR. Results. Although lower cfDNA amounts were obtained by automated DNA extraction (mean 107,35 GE/mL versus 259,43 GE/mL, the SRY sequence was successfully detected in all 108 samples from pregnancies with male fetuses. Conclusion. We successfully evaluated the suitability of standard blood tubes for the collection of maternal blood and assessed samples to be suitable for analysis at least 24 hours later. This would allow shipping to a central reference laboratory almost from anywhere in Europe.

  9. Automated characterization of diabetic foot using nonlinear features extracted from thermograms

    Science.gov (United States)

    Adam, Muhammad; Ng, Eddie Y. K.; Oh, Shu Lih; Heng, Marabelle L.; Hagiwara, Yuki; Tan, Jen Hong; Tong, Jasper W. K.; Acharya, U. Rajendra

    2018-03-01

    Diabetic foot is a major complication of diabetes mellitus (DM). The blood circulation to the foot decreases due to DM and hence, the temperature reduces in the plantar foot. Thermography is a non-invasive imaging method employed to view the thermal patterns using infrared (IR) camera. It allows qualitative and visual documentation of temperature fluctuation in vascular tissues. But it is difficult to diagnose these temperature changes manually. Thus, computer assisted diagnosis (CAD) system may help to accurately detect diabetic foot to prevent traumatic outcomes such as ulcerations and lower extremity amputation. In this study, plantar foot thermograms of 33 healthy persons and 33 individuals with type 2 diabetes are taken. These foot images are decomposed using discrete wavelet transform (DWT) and higher order spectra (HOS) techniques. Various texture and entropy features are extracted from the decomposed images. These combined (DWT + HOS) features are ranked using t-values and classified using support vector machine (SVM) classifier. Our proposed methodology achieved maximum accuracy of 89.39%, sensitivity of 81.81% and specificity of 96.97% using only five features. The performance of the proposed thermography-based CAD system can help the clinicians to take second opinion on their diagnosis of diabetic foot.

  10. Automated Control of the Organic and Inorganic Composition of Aloe vera Extracts Using (1)H NMR Spectroscopy.

    Science.gov (United States)

    Monakhova, Yulia B; Randel, Gabriele; Diehl, Bernd W K

    2016-09-01

    Recent classification of Aloe vera whole-leaf extract by the International Agency for Research and Cancer as a possible carcinogen to humans as well as the continuous adulteration of A. vera's authentic material have generated renewed interest in controlling A. vera. The existing NMR spectroscopic method for the analysis of A. vera, which is based on a routine developed at Spectral Service, was extended. Apart from aloverose, glucose, malic acid, lactic acid, citric acid, whole-leaf material (WLM), acetic acid, fumaric acid, sodium benzoate, and potassium sorbate, the quantification of Mg(2+), Ca(2+), and fructose is possible with the addition of a Cs-EDTA solution to sample. The proposed methodology was automated, which includes phasing, baseline-correction, deconvolution (based on the Lorentzian function), integration, quantification, and reporting. The NMR method was applied to 41 A. vera preparations in the form of liquid A. vera juice and solid A. vera powder. The advantages of the new NMR methodology over the previous method were discussed. Correlation between the new and standard NMR methodologies was significant for aloverose, glucose, malic acid, lactic acid, citric acid, and WLM (P vera.

  11. Fault feature extraction method based on local mean decomposition Shannon entropy and improved kernel principal component analysis model

    Directory of Open Access Journals (Sweden)

    Jinlu Sheng

    2016-07-01

    Full Text Available To effectively extract the typical features of the bearing, a new method that related the local mean decomposition Shannon entropy and improved kernel principal component analysis model was proposed. First, the features are extracted by time–frequency domain method, local mean decomposition, and using the Shannon entropy to process the original separated product functions, so as to get the original features. However, the features been extracted still contain superfluous information; the nonlinear multi-features process technique, kernel principal component analysis, is introduced to fuse the characters. The kernel principal component analysis is improved by the weight factor. The extracted characteristic features were inputted in the Morlet wavelet kernel support vector machine to get the bearing running state classification model, bearing running state was thereby identified. Cases of test and actual were analyzed.

  12. A combined approach for weak fault signature extraction of rolling element bearing using Hilbert envelop and zero frequency resonator

    Science.gov (United States)

    Kumar, Keshav; Shukla, Sumitra; Singh, Sachin Kumar

    2018-04-01

    Periodic impulses arise due to localised defects in rolling element bearing. At the early stage of defects, the weak impulses are immersed in strong machinery vibration. This paper proposes a combined approach based upon Hilbert envelop and zero frequency resonator for the detection of the weak periodic impulses. In the first step, the strength of impulses is increased by taking normalised Hilbert envelop of the signal. It also helps in better localization of these impulses on time axis. In the second step, Hilbert envelope of the signal is passed through the zero frequency resonator for the exact localization of the periodic impulses. Spectrum of the resonator output gives peak at the fault frequency. Simulated noisy signal with periodic impulses is used to explain the working of the algorithm. The proposed technique is verified with experimental data also. A comparison of the proposed method with Hilbert-Haung transform (HHT) based method is presented to establish the effectiveness of the proposed method.

  13. Faults Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Through the study of faults and their effects, much can be learned about the size and recurrence intervals of earthquakes. Faults also teach us about crustal...

  14. Automated Solid Phase Extraction (SPE) LC/NMR Applied to the Structural Analysis of Extractable Compounds from a Pharmaceutical Packaging Material of Construction.

    Science.gov (United States)

    Norwood, Daniel L; Mullis, James O; Davis, Mark; Pennino, Scott; Egert, Thomas; Gonnella, Nina C

    2013-01-01

    The structural analysis (i.e., identification) of organic chemical entities leached into drug product formulations has traditionally been accomplished with techniques involving the combination of chromatography with mass spectrometry. These include gas chromatography/mass spectrometry (GC/MS) for volatile and semi-volatile compounds, and various forms of liquid chromatography/mass spectrometry (LC/MS or HPLC/MS) for semi-volatile and relatively non-volatile compounds. GC/MS and LC/MS techniques are complementary for structural analysis of leachables and potentially leachable organic compounds produced via laboratory extraction of pharmaceutical container closure/delivery system components and corresponding materials of construction. Both hyphenated analytical techniques possess the separating capability, compound specific detection attributes, and sensitivity required to effectively analyze complex mixtures of trace level organic compounds. However, hyphenated techniques based on mass spectrometry are limited by the inability to determine complete bond connectivity, the inability to distinguish between many types of structural isomers, and the inability to unambiguously determine aromatic substitution patterns. Nuclear magnetic resonance spectroscopy (NMR) does not have these limitations; hence it can serve as a complement to mass spectrometry. However, NMR technology is inherently insensitive and its ability to interface with chromatography has been historically challenging. This article describes the application of NMR coupled with liquid chromatography and automated solid phase extraction (SPE-LC/NMR) to the structural analysis of extractable organic compounds from a pharmaceutical packaging material of construction. The SPE-LC/NMR technology combined with micro-cryoprobe technology afforded the sensitivity and sample mass required for full structure elucidation. Optimization of the SPE-LC/NMR analytical method was achieved using a series of model compounds

  15. Fault Tree Generation and Augmentation, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Fault Management (FM) is one of the key components of system autonomy. In order to guarantee FM effectiveness and control the cost, tools are required to automate...

  16. Prognostic Utility of Computed Tomography Histogram Analysis in Patients With Post-Cardiac Arrest Syndrome: Evaluation Using an Automated Whole-Brain Extraction Algorithm.

    Science.gov (United States)

    Yamashita, Koji; Hiwatashi, Akio; Kondo, Masatoshi; Togao, Osamu; Kikuchi, Kazufumi; Sugimori, Hiroshi; Yoshiura, Takashi; Honda, Hiroshi

    2016-01-01

    The aim of the study was to evaluate the prognostic utility of computed tomography (CT) histogram analysis with an automated whole-brain extraction algorithm in patients with post-cardiac arrest syndrome (PCAS). Computed tomography data from consecutive patients between January 2009 and February 2012 were obtained and retrospectively analyzed. All CT images were obtained using a 64-detector-row CT scanner with a slice thickness of 4.0 mm. A brain region was extracted from the whole-brain CT images using our original automated algorithm and used for the subsequent histogram analysis. The obtained histogram statistics (mean brain tissue CT value, kurtosis, and skewness), as well as clinical parameters, were compared between the good and poor outcome groups using the Student t test. In addition, receiver operating characteristic curve analysis was performed for the discrimination between the 2 groups for each parameter. One hundred thirty-eight consecutive PCAS patients were enrolled. The patients were classified into good (n = 47) and poor (n = 91) outcome groups. The mean brain tissue CT value was significantly higher in the good outcome group than in the poor outcome group (P brain tissue CT value, skewness, and age were 0.751, 0.639, 0.623, and 0.626, respectively. A combination of the 4 parameters increased the diagnostic performance (area under the curve = 0.814). Histogram analysis of whole-brain CT images with our automated extraction algorithm is useful for assessing the outcome of PCAS patients.

  17. Fault finder

    Science.gov (United States)

    Bunch, Richard H.

    1986-01-01

    A fault finder for locating faults along a high voltage electrical transmission line. Real time monitoring of background noise and improved filtering of input signals is used to identify the occurrence of a fault. A fault is detected at both a master and remote unit spaced along the line. A master clock synchronizes operation of a similar clock at the remote unit. Both units include modulator and demodulator circuits for transmission of clock signals and data. All data is received at the master unit for processing to determine an accurate fault distance calculation.

  18. Automated extraction of genomic DNA from medically important yeast species and filamentous fungi by using the MagNA Pure LC system.

    Science.gov (United States)

    Loeffler, Juergen; Schmidt, Kathrin; Hebart, Holger; Schumacher, Ulrike; Einsele, Hermann

    2002-06-01

    A fully automated assay was established for the extraction of DNA from clinically important fungi by using the MagNA Pure LC instrument. The test was evaluated by DNA isolation from 23 species of yeast and filamentous fungi and by extractions (n = 28) of serially diluted Aspergillus fumigatus conidia (10(5) to 0 CFU/ml). Additionally, DNA from 67 clinical specimens was extracted and compared to the manual protocol. The detection limit of the MagNA Pure LC assay of 10 CFU corresponded to the sensitivity when DNA was extracted manually; in 9 of 28 runs, we could achieve a higher sensitivity of 1 CFU/ml blood, which was found to be significant (p DNA from all fungal species analyzed could be extracted and amplified by real-time PCR. Negative controls from all MagNA Pure isolations remained negative. Sixty-three clinical samples showed identical results by both methods, whereas in 4 of 67 samples, discordant results were obtained. Thus, the MagNA Pure LC technique offers a fast protocol for automated DNA isolation from numerous fungi, revealing high sensitivity and purity.

  19. Automation of DNA and miRNA co-extraction for miRNA-based identification of human body fluids and tissues.

    Science.gov (United States)

    Kulstein, Galina; Marienfeld, Ralf; Miltner, Erich; Wiegand, Peter

    2016-10-01

    In the last years, microRNA (miRNA) analysis came into focus in the field of forensic genetics. Yet, no standardized and recommendable protocols for co-isolation of miRNA and DNA from forensic relevant samples have been developed so far. Hence, this study evaluated the performance of an automated Maxwell® 16 System-based strategy (Promega) for co-extraction of DNA and miRNA from forensically relevant (blood and saliva) samples compared to (semi-)manual extraction methods. Three procedures were compared on the basis of recovered quantity of DNA and miRNA (as determined by real-time PCR and Bioanalyzer), miRNA profiling (shown by Cq values and extraction efficiency), STR profiles, duration, contamination risk and handling. All in all, the results highlight that the automated co-extraction procedure yielded the highest miRNA and DNA amounts from saliva and blood samples compared to both (semi-)manual protocols. Also, for aged and genuine samples of forensically relevant traces the miRNA and DNA yields were sufficient for subsequent downstream analysis. Furthermore, the strategy allows miRNA extraction only in cases where it is relevant to obtain additional information about the sample type. Besides, this system enables flexible sample throughput and labor-saving sample processing with reduced risk of cross-contamination. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. AUTOMATED ANALYSIS OF AQUEOUS SAMPLES CONTAINING PESTICIDES, ACIDIC/BASIC/NEUTRAL SEMIVOLATILES AND VOLATILE ORGANIC COMPOUNDS BY SOLID PHASE EXTRACTION COUPLED IN-LINE TO LARGE VOLUME INJECTION GC/MS

    Science.gov (United States)

    Data is presented on the development of a new automated system combining solid phase extraction (SPE) with GC/MS spectrometry for the single-run analysis of water samples containing a broad range of organic compounds. The system uses commercially available automated in-line 10-m...

  1. Submicrometric Magnetic Nanoporous Carbons Derived from Metal-Organic Frameworks Enabling Automated Electromagnet-Assisted Online Solid-Phase Extraction.

    Science.gov (United States)

    Frizzarin, Rejane M; Palomino Cabello, Carlos; Bauzà, Maria Del Mar; Portugal, Lindomar A; Maya, Fernando; Cerdà, Víctor; Estela, José M; Turnes Palomino, Gemma

    2016-07-19

    We present the first application of submicrometric magnetic nanoporous carbons (μMNPCs) as sorbents for automated solid-phase extraction (SPE). Small zeolitic imidazolate framework-67 crystals are obtained at room temperature and directly carbonized under an inert atmosphere to obtain submicrometric nanoporous carbons containing magnetic cobalt nanoparticles. The μMNPCs have a high contact area, high stability, and their preparation is simple and cost-effective. The prepared μMNPCs are exploited as sorbents in a microcolumn format in a sequential injection analysis (SIA) system with online spectrophotometric detection, which includes a specially designed three-dimensional (3D)-printed holder containing an automatically actuated electromagnet. The combined action of permanent magnets and an automatically actuated electromagnet enabled the movement of the solid bed of particles inside the microcolumn, preventing their aggregation, increasing the versatility of the system, and increasing the preconcentration efficiency. The method was optimized using a full factorial design and Doehlert Matrix. The developed system was applied to the determination of anionic surfactants, exploiting the retention of the ion-pairs formed with Methylene Blue on the μMNPC. Using sodium dodecyl sulfate as a model analyte, quantification was linear from 50 to 1000 μg L(-1), and the detection limit was equal to 17.5 μg L(-1), the coefficient of variation (n = 8; 100 μg L(-1)) was 2.7%, and the analysis throughput was 13 h(-1). The developed approach was applied to the determination of anionic surfactants in water samples (natural water, groundwater, and wastewater), yielding recoveries of 93% to 110% (95% confidence level).

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

    Science.gov (United States)

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

    2018-02-01

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

  3. Satellite mapping and automated feature extraction: Geographic information system-based change detection of the Antarctic coast

    Science.gov (United States)

    Kim, Kee-Tae

    Declassified Intelligence Satellite Photograph (DISP) data are important resources for measuring the geometry of the coastline of Antarctica. By using the state-of-art digital imaging technology, bundle block triangulation based on tie points and control points derived from a RADARSAT-1 Synthetic Aperture Radar (SAR) image mosaic and Ohio State University (OSU) Antarctic digital elevation model (DEM), the individual DISP images were accurately assembled into a map quality mosaic of Antarctica as it appeared in 1963. The new map is one of important benchmarks for gauging the response of the Antarctic coastline to changing climate. Automated coastline extraction algorithm design is the second theme of this dissertation. At the pre-processing stage, an adaptive neighborhood filtering was used to remove the film-grain noise while preserving edge features. At the segmentation stage, an adaptive Bayesian approach to image segmentation was used to split the DISP imagery into its homogenous regions, in which the fuzzy c-means clustering (FCM) technique and Gibbs random field (GRF) model were introduced to estimate the conditional and prior probability density functions. A Gaussian mixture model was used to estimate the reliable initial values for the FCM technique. At the post-processing stage, image object formation and labeling, removal of noisy image objects, and vectorization algorithms were sequentially applied to segmented images for extracting a vector representation of coastlines. Results were presented that demonstrate the effectiveness of the algorithm in segmenting the DISP data. In the cases of cloud cover and little contrast scenes, manual editing was carried out based on intermediate image processing and visual inspection in comparison of old paper maps. Through a geographic information system (GIS), the derived DISP coastline data were integrated with earlier and later data to assess continental scale changes in the Antarctic coast. Computing the area of

  4. Fault detection in reciprocating compressor valves under varying load conditions

    Science.gov (United States)

    Pichler, Kurt; Lughofer, Edwin; Pichler, Markus; Buchegger, Thomas; Klement, Erich Peter; Huschenbett, Matthias

    2016-03-01

    This paper presents a novel approach for detecting cracked or broken reciprocating compressor valves under varying load conditions. The main idea is that the time frequency representation of vibration measurement data will show typical patterns depending on the fault state. The problem is to detect these patterns reliably. For the detection task, we make a detour via the two dimensional autocorrelation. The autocorrelation emphasizes the patterns and reduces noise effects. This makes it easier to define appropriate features. After feature extraction, classification is done using logistic regression and support vector machines. The method's performance is validated by analyzing real world measurement data. The results will show a very high detection accuracy while keeping the false alarm rates at a very low level for different compressor loads, thus achieving a load-independent method. The proposed approach is, to our best knowledge, the first automated method for reciprocating compressor valve fault detection that can handle varying load conditions.

  5. Automated Power-Distribution System

    Science.gov (United States)

    Ashworth, Barry; Riedesel, Joel; Myers, Chris; Miller, William; Jones, Ellen F.; Freeman, Kenneth; Walsh, Richard; Walls, Bryan K.; Weeks, David J.; Bechtel, Robert T.

    1992-01-01

    Autonomous power-distribution system includes power-control equipment and automation equipment. System automatically schedules connection of power to loads and reconfigures itself when it detects fault. Potential terrestrial applications include optimization of consumption of power in homes, power supplies for autonomous land vehicles and vessels, and power supplies for automated industrial processes.

  6. A fast fault classification technique for power systems

    OpenAIRE

    Nouri, H.; Wang, C.; Power Systems, Electronics and Control Research Lab

    2014-01-01

    This paper proposes a fast fault classification technique using three phase current signals for power systems. Digital Fourier Transform, the ‘Least Square’ method or the Kalman Filtering technique are used to extract fundamental frequency components of three phase fault currents. Fast fault classification can be achieved using the fault probability of three phases. Results from simulation work on EMTP have validated the proposed fault classification technique. The response time of the fault ...

  7. Solar Dynamic Power System Fault Diagnosis

    Science.gov (United States)

    Momoh, James A.; Dias, Lakshman G.

    1996-01-01

    The objective of this research is to conduct various fault simulation studies for diagnosing the type and location of faults in the power distribution system. Different types of faults are simulated at different locations within the distribution system and the faulted waveforms are monitored at measurable nodes such as at the output of the DDCU's. These fault signatures are processed using feature extractors such as FFT and wavelet transforms. The extracted features are fed to a clustering based neural network for training and subsequent testing using previously unseen data. Different load models consisting of constant impedance and constant power are used for the loads. Open circuit faults and short circuit faults are studied. It is concluded from present studies that using features extracted from wavelet transforms give better success rates during ANN testing. The trained ANN's are capable of diagnosing fault types and approximate locations in the solar dynamic power distribution system.

  8. Determination of Low Concentrations of Acetochlor in Water by Automated Solid-Phase Extraction and Gas Chromatography with Mass-Selective Detection

    Science.gov (United States)

    Lindley, C.E.; Stewart, J.T.; Sandstrom, M.W.

    1996-01-01

    A sensitive and reliable gas chromatographic/mass spectrometric (GC/MS) method for determining acetochlor in environmental water samples was developed. The method involves automated extraction of the herbicide from a filtered 1 L water sample through a C18 solid-phase extraction column, elution from the column with hexane-isopropyl alcohol (3 + 1), and concentration of the extract with nitrogen gas. The herbicide is quantitated by capillary/column GC/MS with selected-ion monitoring of 3 characteristic ions. The single-operator method detection limit for reagent water samples is 0.0015 ??g/L. Mean recoveries ranged from about 92 to 115% for 3 water matrixes fortified at 0.05 and 0.5 ??g/L. Average single-operator precision, over the course of 1 week, was better than 5%.

  9. Graphical User Interface Aided Online Fault Diagnosis of Electric Motor - DC motor case study

    OpenAIRE

    POSTALCIOGLU OZGEN, S.

    2009-01-01

    This paper contains graphical user interface (GUI) aided online fault diagnosis for DC motor. The aim of the research is to prevent system faults. Online fault diagnosis has been studied. Design of fault diagnosis has two main levels: Level 1 comprises a traditional control loop; Level 2 contains knowledge based fault diagnosis. Fault diagnosis technique contains feature extraction module, feature cluster module and fault decision module. Wavelet analysis has been used for the feature extract...

  10. A new fast and fully automated software based algorithm for extracting respiratory signal from raw PET data and its comparison to other methods.

    Science.gov (United States)

    Kesner, Adam Leon; Kuntner, Claudia

    2010-10-01

    Respiratory gating in PET is an approach used to minimize the negative effects of respiratory motion on spatial resolution. It is based on an initial determination of a patient's respiratory movements during a scan, typically using hardware based systems. In recent years, several fully automated databased algorithms have been presented for extracting a respiratory signal directly from PET data, providing a very practical strategy for implementing gating in the clinic. In this work, a new method is presented for extracting a respiratory signal from raw PET sinogram data and compared to previously presented automated techniques. The acquisition of respiratory signal from PET data in the newly proposed method is based on rebinning the sinogram data into smaller data structures and then analyzing the time activity behavior in the elements of these structures. From this analysis, a 1D respiratory trace is produced, analogous to a hardware derived respiratory trace. To assess the accuracy of this fully automated method, respiratory signal was extracted from a collection of 22 clinical FDG-PET scans using this method, and compared to signal derived from several other software based methods as well as a signal derived from a hardware system. The method presented required approximately 9 min of processing time for each 10 min scan (using a single 2.67 GHz processor), which in theory can be accomplished while the scan is being acquired and therefore allowing a real-time respiratory signal acquisition. Using the mean correlation between the software based and hardware based respiratory traces, the optimal parameters were determined for the presented algorithm. The mean/median/range of correlations for the set of scans when using the optimal parameters was found to be 0.58/0.68/0.07-0.86. The speed of this method was within the range of real-time while the accuracy surpassed the most accurate of the previously presented algorithms. PET data inherently contains information

  11. Arsenic fractionation in agricultural soil using an automated three-step sequential extraction method coupled to hydride generation-atomic fluorescence spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Rosas-Castor, J.M. [Universidad Autónoma de Nuevo León, UANL, Facultad de Ciencias Químicas, Cd. Universitaria, San Nicolás de los Garza, Nuevo León, C.P. 66451 Nuevo León (Mexico); Group of Analytical Chemistry, Automation and Environment, University of Balearic Islands, Cra. Valldemossa km 7.5, 07122 Palma de Mallorca (Spain); Portugal, L.; Ferrer, L. [Group of Analytical Chemistry, Automation and Environment, University of Balearic Islands, Cra. Valldemossa km 7.5, 07122 Palma de Mallorca (Spain); Guzmán-Mar, J.L.; Hernández-Ramírez, A. [Universidad Autónoma de Nuevo León, UANL, Facultad de Ciencias Químicas, Cd. Universitaria, San Nicolás de los Garza, Nuevo León, C.P. 66451 Nuevo León (Mexico); Cerdà, V. [Group of Analytical Chemistry, Automation and Environment, University of Balearic Islands, Cra. Valldemossa km 7.5, 07122 Palma de Mallorca (Spain); Hinojosa-Reyes, L., E-mail: laura.hinojosary@uanl.edu.mx [Universidad Autónoma de Nuevo León, UANL, Facultad de Ciencias Químicas, Cd. Universitaria, San Nicolás de los Garza, Nuevo León, C.P. 66451 Nuevo León (Mexico)

    2015-05-18

    Highlights: • A fully automated flow-based modified-BCR extraction method was developed to evaluate the extractable As of soil. • The MSFIA–HG-AFS system included an UV photo-oxidation step for organic species degradation. • The accuracy and precision of the proposed method were found satisfactory. • The time analysis can be reduced up to eight times by using the proposed flow-based BCR method. • The labile As (F1 + F2) was <50% of total As in soil samples from As-contaminated-mining zones. - Abstract: A fully automated modified three-step BCR flow-through sequential extraction method was developed for the fractionation of the arsenic (As) content from agricultural soil based on a multi-syringe flow injection analysis (MSFIA) system coupled to hydride generation-atomic fluorescence spectrometry (HG-AFS). Critical parameters that affect the performance of the automated system were optimized by exploiting a multivariate approach using a Doehlert design. The validation of the flow-based modified-BCR method was carried out by comparison with the conventional BCR method. Thus, the total As content was determined in the following three fractions: fraction 1 (F1), the acid-soluble or interchangeable fraction; fraction 2 (F2), the reducible fraction; and fraction 3 (F3), the oxidizable fraction. The limits of detection (LOD) were 4.0, 3.4, and 23.6 μg L{sup −1} for F1, F2, and F3, respectively. A wide working concentration range was obtained for the analysis of each fraction, i.e., 0.013–0.800, 0.011–0.900 and 0.079–1.400 mg L{sup −1} for F1, F2, and F3, respectively. The precision of the automated MSFIA–HG-AFS system, expressed as the relative standard deviation (RSD), was evaluated for a 200 μg L{sup −1} As standard solution, and RSD values between 5 and 8% were achieved for the three BCR fractions. The new modified three-step BCR flow-based sequential extraction method was satisfactorily applied for arsenic fractionation in real agricultural

  12. Fault Management Techniques in Human Spaceflight Operations

    Science.gov (United States)

    O'Hagan, Brian; Crocker, Alan

    2006-01-01

    This paper discusses human spaceflight fault management operations. Fault detection and response capabilities available in current US human spaceflight programs Space Shuttle and International Space Station are described while emphasizing system design impacts on operational techniques and constraints. Preflight and inflight processes along with products used to anticipate, mitigate and respond to failures are introduced. Examples of operational products used to support failure responses are presented. Possible improvements in the state of the art, as well as prioritization and success criteria for their implementation are proposed. This paper describes how the architecture of a command and control system impacts operations in areas such as the required fault response times, automated vs. manual fault responses, use of workarounds, etc. The architecture includes the use of redundancy at the system and software function level, software capabilities, use of intelligent or autonomous systems, number and severity of software defects, etc. This in turn drives which Caution and Warning (C&W) events should be annunciated, C&W event classification, operator display designs, crew training, flight control team training, and procedure development. Other factors impacting operations are the complexity of a system, skills needed to understand and operate a system, and the use of commonality vs. optimized solutions for software and responses. Fault detection, annunciation, safing responses, and recovery capabilities are explored using real examples to uncover underlying philosophies and constraints. These factors directly impact operations in that the crew and flight control team need to understand what happened, why it happened, what the system is doing, and what, if any, corrective actions they need to perform. If a fault results in multiple C&W events, or if several faults occur simultaneously, the root cause(s) of the fault(s), as well as their vehicle-wide impacts, must be

  13. Research on intelligent fault diagnosis of gears using EMD, spectral features and data mining techniques

    Science.gov (United States)

    Sagar, M.; Vivekkumar, G.; Reddy, Mallikarjuna; Devendiran, S.; Amarnath, M.

    2017-11-01

    In this present work aims to formulate an automated prediction model using vibration signals of various gear operating conditions by using EMD (empirical mode decomposition) and spectral features and different classification algorithms. In this present work empirical mode decomposition (EMD) is a signal processing technique used to extract more useful fault information from the vibration signals. The proposed method described in following parts gear test rig, data acquisition system, signal processing, feature extraction and classification algorithms and finally identification. Meanwhile, in order to remove the redundant and irrelevant spectral features and classification algorithms, data mining is implemented and it showed promising prediction results.

  14. A filter paper-based microdevice for low-cost, rapid, and automated DNA extraction and amplification from diverse sample types.

    Science.gov (United States)

    Gan, Wupeng; Zhuang, Bin; Zhang, Pengfei; Han, Junping; Li, Cai-Xia; Liu, Peng

    2014-10-07

    A plastic microfluidic device that integrates a filter disc as a DNA capture phase was successfully developed for low-cost, rapid and automated DNA extraction and PCR amplification from various raw samples. The microdevice was constructed by sandwiching a piece of Fusion 5 filter, as well as a PDMS (polydimethylsiloxane) membrane, between two PMMA (poly(methyl methacrylate)) layers. An automated DNA extraction from 1 μL of human whole blood can be finished on the chip in 7 minutes by sequentially aspirating NaOH, HCl, and water through the filter. The filter disc containing extracted DNA was then taken out directly for PCR. On-chip DNA purification from 0.25-1 μL of human whole blood yielded 8.1-21.8 ng of DNA, higher than those obtained using QIAamp® DNA Micro kits. To realize DNA extraction from raw samples, an additional sample loading chamber containing a filter net with an 80 μm mesh size was designed in front of the extraction chamber to accommodate sample materials. Real-world samples, including whole blood, dried blood stains on Whatman® 903 paper, dried blood stains on FTA™ cards, buccal swabs, saliva, and cigarette butts, can all be processed in the system in 8 minutes. In addition, multiplex amplification of 15 STR (short tandem repeat) loci and Sanger-based DNA sequencing of the 520 bp GJB2 gene were accomplished from the filters that contained extracted DNA from blood. To further prove the feasibility of integrating this extraction method with downstream analyses, "in situ" PCR amplifications were successfully performed in the DNA extraction chamber following DNA purification from blood and blood stains without DNA elution. Using a modified protocol to bond the PDMS and PMMA, our plastic PDMS devices withstood the PCR process without any leakage. This study represents a significant step towards the practical application of on-chip DNA extraction methods, as well as the development of fully integrated genetic analytical systems.

  15. Automated solid-phase extraction for trace-metal analysis of seawater: sample preparation for total-reflection X-ray fluorescence measurements

    Science.gov (United States)

    Gerwinski, Wolfgang; Schmidt, Diether

    1998-08-01

    Solid-phase chromatography on silica gel columns can be used as a sample preparation technique for seawater, followed by total-reflection X-ray fluorescence analysis (TXRF). An automated extraction system (Zymark AutoTrace SPE Workstation) was studied for the analysis of blank solutions, seawater samples and certified reference materials. After replacing some stainless steel parts in the system, adequate blanks could be obtained to allow the analysis of seawater samples. Replicate analyses yielded low standard deviations and good recoveries for certified reference materials. Using a six-channel model and user-defined software, the time needed for a complete analytical run was about 100 min.

  16. Automated mini-column solid-phase extraction cleanup for high-throughput analysis of chemical contaminants in foods by low-pressure gas chromatography – tandem mass spectrometry

    Science.gov (United States)

    This study demonstrated the application of an automated high-throughput mini-cartridge solid-phase extraction (mini-SPE) cleanup for the rapid low-pressure gas chromatography – tandem mass spectrometry (LPGC-MS/MS) analysis of pesticides and environmental contaminants in QuEChERS extracts of foods. ...

  17. Fault detection and diagnosis for complex multivariable processes using neural networks

    International Nuclear Information System (INIS)

    Weerasinghe, M.

    1998-06-01

    the complex input-output mapping performed by a network, and are in general difficult to obtain. Statistical techniques and relationships between fuzzy systems and standard radial basis function networks have been exploited to prune a trained network and to extract qualitative rules that explain the network operation for fault diagnosis. Pruning the networks improved the fault classification, while offering simple qualitative rules on process behaviour. Automation of the pruning procedure introduced flexibility and ease of application of the methods. (author)

  18. Fully automated synthesis of ¹¹C-acetate as tumor PET tracer by simple modified solid-phase extraction purification.

    Science.gov (United States)

    Tang, Xiaolan; Tang, Ganghua; Nie, Dahong

    2013-12-01

    Automated synthesis of (11)C-acetate ((11)C-AC) as the most commonly used radioactive fatty acid tracer is performed by a simple, rapid, and modified solid-phase extraction (SPE) purification. Automated synthesis of (11)C-AC was implemented by carboxylation reaction of MeMgBr on a polyethylene Teflon loop ring with (11)C-CO2, followed by acidic hydrolysis with acid and SCX cartridge, and purification on SCX, AG11A8 and C18 SPE cartridges using a commercially available (11)C-tracer synthesizer. Quality control test and animals positron emission tomography (PET) imaging were also carried out. A high and reproducible decay-uncorrected radiochemical yield of (41.0 ± 4.6)% (n=10) was obtained from (11)C-CO2 within the whole synthesis time about 8 min. The radiochemical purity of (11)C-AC was over 95% by high-performance liquid chromatography (HPLC) analysis. Quality control test and PET imaging showed that (11)C-AC injection produced by the simple SPE procedure was safe and efficient, and was in agreement with the current Chinese radiopharmaceutical quality control guidelines. The novel, simple, and rapid method is readily adapted to the fully automated synthesis of (11)C-AC on several existing commercial synthesis module. The method can be used routinely to produce (11)C-AC for preclinical and clinical studies with PET imaging. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Fault diagnosis

    Science.gov (United States)

    Abbott, Kathy

    1990-01-01

    The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to

  20. High-throughput method of dioxin analysis in aqueous samples using consecutive solid phase extraction steps with the new C18 Ultraflow™ pressurized liquid extraction and automated clean-up.

    Science.gov (United States)

    Youn, Yeu-Young; Park, Deok Hie; Lee, Yeon Hwa; Lim, Young Hee; Cho, Hye Sung

    2015-01-01

    A high-throughput analytical method has been developed for the determination of seventeen 2,3,7,8-substituted congeners of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in aqueous samples. A recently introduced octadecyl (C18) disk for semi-automated solid-phase extraction of PCDD/Fs in water samples with a high level of particulate material has been tested for the analysis of dioxins. A new type of C18 disk specially designed for the analysis of hexane extractable material (HEM), but never previously reported for use in PCDD/Fs analysis. This kind of disk allows a higher filtration flow, and therefore the time of analysis is reduced. The solid-phase extraction technique is used to change samples from liquid to solid, and therefore pressurized liquid extraction (PLE) can be used in the pre-treatment. In order to achieve efficient purification, extracts from the PLE are purified using an automated Power-prep system with disposable silica, alumina, and carbon columns. Quantitative analyses of PCDD/Fs were performed by GC-HRMS using multi-ion detection (MID) mode. The method was successfully applied to the analysis of water samples from the wastewater treatment system of a vinyl chloride monomer plant. The entire procedure is in agreement with EPA1613 recommendations regarding the blank control, MDLs (method detection limits), accuracy, and precision. The high-throughput method not only meets the requirements of international standards, but also shortens the required analysis time from 2 weeks to 3d. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Automated Online Solid-Phase Extraction Coupled with Sequential Injection-HPLC-EC System for the Determination of Sulfonamides in Shrimp

    Directory of Open Access Journals (Sweden)

    Pimkwan Chantarateepra

    2012-01-01

    Full Text Available The use of fully automated online solid-phase extraction (SPE coupled with sequential injection analysis, high-performance liquid chromatography (HPLC, and electrochemical detection (EC for the separation and determination of sulfonamides has been developed. A homemade microcolumn SPE system coupled with sequential injection analysis (SIA was used to automate the sample cleanup and extraction of sulfonamides. The optimal flow rate of sample loading and elution was found to be 10 μL/s, and optimal elution time of zone was 20–24 s. Under the optimal conditions, a linear relationship between peak area and sulfonamide concentrations was obtained in the range of 0.01–8.0 μg mL−1. Detection limits for seven sulfonamides were between 1.2 ng mL−1 and 11.2 ng mL−1. The proposed method has been applied for the determination of sulfonamides in shrimp. Recoveries in the range of 84–107% and relative standard deviations (RSDs below 6.5% for intraday and 13% for inter-day were received for three concentration levels of spiking. The results showed that the present method was simple, rapid, accurate and highly sensitive for the determination of sulfonamides.

  2. Analysis of the relationship of automatically and manually extracted lineaments from DEM and geologically mapped tectonic faults around the Main Ethiopian Rift and the Ethiopian highlands, Ethiopia

    Czech Academy of Sciences Publication Activity Database

    Kusák, Michal; Krbcová, K.

    2017-01-01

    Roč. 52, č. 1 (2017), s. 5-17 ISSN 0300-5402 Institutional support: RVO:67985891 Keywords : azimuth * faults * lineaments * Main Ethiopian Rift * morphometry Subject RIV: DE - Earth Magnetism, Geodesy, Geography OBOR OECD: Physical geography

  3. A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds.

    Science.gov (United States)

    Dorninger, Peter; Pfeifer, Norbert

    2008-11-17

    Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects.

  4. A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds

    Directory of Open Access Journals (Sweden)

    Norbert Pfeifer

    2008-11-01

    Full Text Available Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects.

  5. Fault tree analysis: concepts and techniques

    International Nuclear Information System (INIS)

    Fussell, J.B.

    1976-01-01

    Concepts and techniques of fault tree analysis have been developed over the past decade and now predictions from this type analysis are important considerations in the design of many systems such as aircraft, ships and their electronic systems, missiles, and nuclear reactor systems. Routine, hardware-oriented fault tree construction can be automated; however, considerable effort is needed in this area to get the methodology into production status. When this status is achieved, the entire analysis of hardware systems will be automated except for the system definition step. Automated analysis is not undesirable; to the contrary, when verified on adequately complex systems, automated analysis could well become a routine analysis. It could also provide an excellent start for a more in-depth fault tree analysis that includes environmental effects, common mode failure, and human errors. The automated analysis is extremely fast and frees the analyst from the routine hardware-oriented fault tree construction, as well as eliminates logic errors and errors of oversight in this part of the analysis. Automated analysis then affords the analyst a powerful tool to allow his prime efforts to be devoted to unearthing more subtle aspects of the modes of failure of the system

  6. Multiple automated headspace in-tube extraction for the accurate analysis of relevant wine aroma compounds and for the estimation of their relative liquid-gas transfer rates.

    Science.gov (United States)

    Zapata, Julián; Lopez, Ricardo; Herrero, Paula; Ferreira, Vicente

    2012-11-30

    An automated headspace in-tube extraction (ITEX) method combined with multiple headspace extraction (MHE) has been developed to provide simultaneously information about the accurate wine content in 20 relevant aroma compounds and about their relative transfer rates to the headspace and hence about the relative strength of their interactions with the matrix. In the method, 5 μL (for alcohols, acetates and carbonyl alcohols) or 200 μL (for ethyl esters) of wine sample were introduced in a 2 mL vial, heated at 35°C and extracted with 32 (for alcohols, acetates and carbonyl alcohols) or 16 (for ethyl esters) 0.5 mL pumping strokes in four consecutive extraction and analysis cycles. The application of the classical theory of Multiple Extractions makes it possible to obtain a highly reliable estimate of the total amount of volatile compound present in the sample and a second parameter, β, which is simply the proportion of volatile not transferred to the trap in one extraction cycle, but that seems to be a reliable indicator of the actual volatility of the compound in that particular wine. A study with 20 wines of different types and 1 synthetic sample has revealed the existence of significant differences in the relative volatility of 15 out of 20 odorants. Differences are particularly intense for acetaldehyde and other carbonyls, but are also notable for alcohols and long chain fatty acid ethyl esters. It is expected that these differences, linked likely to sulphur dioxide and some unknown specific compositional aspects of the wine matrix, can be responsible for relevant sensory changes, and may even be the cause explaining why the same aroma composition can produce different aroma perceptions in two different wines. Copyright © 2012 Elsevier B.V. All rights reserved.

  7. Computer aided fault tree construction for electrical systems

    International Nuclear Information System (INIS)

    Fussell, J.B.

    1975-01-01

    A technique is presented for automated construction of the Boolean failure logic diagram, called the fault tree, for electrical systems. The method is a technique for synthesizing a fault tree from system-independent component characteristics. Terminology is defined and heuristic examples are given for all phases of the model. The computer constructed fault trees are in conventional format, use conventional symbols, and are deductively constructed from the main failure of interest to the individual component failures. The synthesis technique is generally applicable to automated fault tree construction for other types of systems

  8. Simultaneous analysis of organochlorinated pesticides (OCPs) and polychlorinated biphenyls (PCBs) from marine samples using automated pressurized liquid extraction (PLE) and Power Prep™ clean-up.

    Science.gov (United States)

    Helaleh, Murad I H; Al-Rashdan, Amal; Ibtisam, A

    2012-05-30

    An automated pressurized liquid extraction (PLE) method followed by Power Prep™ clean-up was developed for organochlorinated pesticide (OCP) and polychlorinated biphenyl (PCB) analysis in environmental marine samples of fish, squid, bivalves, shells, octopus and shrimp. OCPs and PCBs were simultaneously determined in a single chromatographic run using gas chromatography-mass spectrometry-negative chemical ionization (GC-MS-NCI). About 5 g of each biological marine sample was mixed with anhydrous sodium sulphate and placed in the extraction cell of the PLE system. PLE is controlled by means of a PC using DMS 6000 software. Purification of the extract was accomplished using automated Power Prep™ clean-up with a pre-packed disposable silica column (6 g) supplied by Fluid Management Systems (FMS). All OCPs and PCBs were eluted from the silica column using two types of solvent: 80 mL of hexane and a 50 mL mixture of hexane and dichloromethane (1:1). A wide variety of fish and shellfish were collected from the fish market and analyzed using this method. The total PCB concentrations were 2.53, 0.25, 0.24, 0.24, 0.17 and 1.38 ng g(-1) (w/w) for fish, squid, bivalves, shells, octopus and shrimp, respectively, and the corresponding total OCP concentrations were 30.47, 2.86, 0.92, 10.72, 5.13 and 18.39 ng g(-1) (w/w). Lipids were removed using an SX-3 Bio-Beads gel permeation chromatography (GPC) column. Analytical criteria such as recovery, reproducibility and repeatability were evaluated through a range of biological matrices. Copyright © 2012 Elsevier B.V. All rights reserved.

  9. Comparison of QIAsymphony automated and QIAamp manual DNA extraction systems for measuring Epstein-Barr virus DNA load in whole blood using real-time PCR.

    Science.gov (United States)

    Laus, Stella; Kingsley, Lawrence A; Green, Michael; Wadowsky, Robert M

    2011-11-01

    Automated and manual extraction systems have been used with real-time PCR for quantification of Epstein-Barr virus [human herpesvirus 4 (HHV-4)] DNA in whole blood, but few studies have evaluated relative performances. In the present study, the automated QIAsymphony and manual QIAamp extraction systems (Qiagen, Valencia, CA) were assessed using paired aliquots derived from clinical whole-blood specimens and an in-house, real-time PCR assay. The detection limits using the QIAsymphony and QIAamp systems were similar (270 and 560 copies/mL, respectively). For samples estimated as having ≥10,000 copies/mL, the intrarun and interrun variations were significantly lower using QIAsymphony (10.0% and 6.8%, respectively), compared with QIAamp (18.6% and 15.2%, respectively); for samples having ≤1000 copies/mL, the two variations ranged from 27.9% to 43.9% and were not significantly different between the two systems. Among 68 paired clinical samples, 48 pairs yielded viral loads ≥1000 copies/mL under both extraction systems. Although the logarithmic linear correlation from these positive samples was high (r(2) = 0.957), the values obtained using QIAsymphony were on average 0.2 log copies/mL higher than those obtained using QIAamp. Thus, the QIAsymphony and QIAamp systems provide similar EBV DNA load values in whole blood. Copyright © 2011 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  10. Automated Information Extraction on Treatment and Prognosis for Non-Small Cell Lung Cancer Radiotherapy Patients: Clinical Study.

    Science.gov (United States)

    Zheng, Shuai; Jabbour, Salma K; O'Reilly, Shannon E; Lu, James J; Dong, Lihua; Ding, Lijuan; Xiao, Ying; Yue, Ning; Wang, Fusheng; Zou, Wei

    2018-02-01

    In outcome studies of oncology patients undergoing radiation, researchers extract valuable information from medical records generated before, during, and after radiotherapy visits, such as survival data, toxicities, and complications. Clinical studies rely heavily on these data to correlate the treatment regimen with the prognosis to develop evidence-based radiation therapy paradigms. These data are available mainly in forms of narrative texts or table formats with heterogeneous vocabularies. Manual extraction of the related information from these data can be time consuming and labor intensive, which is not ideal for large studies. The objective of this study was to adapt the interactive information extraction platform Information and Data Extraction using Adaptive Learning (IDEAL-X) to extract treatment and prognosis data for patients with locally advanced or inoperable non-small cell lung cancer (NSCLC). We transformed patient treatment and prognosis documents into normalized structured forms using the IDEAL-X system for easy data navigation. The adaptive learning and user-customized controlled toxicity vocabularies were applied to extract categorized treatment and prognosis data, so as to generate structured output. In total, we extracted data from 261 treatment and prognosis documents relating to 50 patients, with overall precision and recall more than 93% and 83%, respectively. For toxicity information extractions, which are important to study patient posttreatment side effects and quality of life, the precision and recall achieved 95.7% and 94.5% respectively. The IDEAL-X system is capable of extracting study data regarding NSCLC chemoradiation patients with significant accuracy and effectiveness, and therefore can be used in large-scale radiotherapy clinical data studies. ©Shuai Zheng, Salma K Jabbour, Shannon E O'Reilly, James J Lu, Lihua Dong, Lijuan Ding, Ying Xiao, Ning Yue, Fusheng Wang, Wei Zou. Originally published in JMIR Medical Informatics (http

  11. A simple automated solid-phase extraction procedure for measurement of 25-hydroxyvitamin D3 and D2 by liquid chromatography-tandem mass spectrometry.

    Science.gov (United States)

    Knox, Susan; Harris, John; Calton, Lisa; Wallace, A Michael

    2009-05-01

    Measurement of 25-hydroxyvitamin D(3) (25OHD(3)) and D(2) (25OHD(2)) is challenging. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods have been described but they are often complex and difficult to automate. We have developed a simplified procedure involving an automated solid-phase extraction (SPE). Internal standard (hexadeuterated 25-hydroxyvitamin D(3)) was added to serum or plasma followed by protein precipitation with methanol. Following centrifugation, a robotic instrument (CTC PAL [Presearch] for ITSP SPE [MicroLiter Analytical Supplies, Inc]) performed a six-step SPE procedure and the purified samples were injected into the LC-MS/MS. Quantification of 25OHD(3) and 25OHD(2) was by electrospray ionization MS/MS in the multiple-reaction monitoring mode. The lower limit of quantitation was 4.0 nmol/L for 25OHD(3) and 7.5 nmol/L for 25OHD(2). Within- and between-assay precision was below 10% over the concentration range of 22.5-120 nmol/L for D(3) and 17.5-70 nmol/L for D(2) (n = 10). The calibration was linear up to 2500 nmol/L (r = 0.99). Recoveries ranged between 89% and 104% for both metabolites and no ion suppression was observed. The results obtained compared well (r = 0.96) with the IDS-OCTEIA 25-hydroxyvitamin D enzyme immunoassay for samples containing less than 125 nmol/L, at higher concentrations the immunodiagnostic system (IDS) method showed positive bias. Our simplified sample preparation and automated SPE method is suitable for the measurement of 25OHD(3) and D(2) in a routine laboratory environment. The system can process up to 300 samples per day with no cumbersome solvent evaporation step and minimal operator intervention.

  12. Qualitative detection of Legionella species in bronchoalveolar lavages and induced sputa by automated DNA extraction and real-time polymerase chain reaction.

    Science.gov (United States)

    Raggam, R B; Leitner, E; Mühlbauer, G; Berg, J; Stöcher, M; Grisold, A J; Marth, E; Kessler, H H

    2002-10-01

    Molecular assays for qualitative detection of Legionella spp. in clinical specimens were evaluated. DNA extraction was done either with a fully automated DNA extraction protocol on the MagNA Pure LC System or with manual DNA extraction. Amplification and detection were done by real-time polymerase chain reaction (PCR) on the LightCycler (LC) instrument. Oligonucleotides were derived from the 16S rRNA gene of Legionella spp. The assays included a specially designed DNA fragment as Legionella-specific internal control. For both molecular assays, the detection limit was determined to be 5 CFU per LC PCR run. Sixty-one clinical specimens were tested with the molecular assays. Results were compared to culture. Five samples were found to be positive with the molecular assays. Three of them were positive in culture. No inhibition was found throughout the whole study. In conclusion, the molecular assays described may lead to safe and early diagnosis of Legionnaires' disease. They proved to be suitable for the routine molecular diagnostics laboratory.

  13. Automated on-line renewable solid-phase extraction-liquid chromatography exploiting multisyringe flow injection-bead injection lab-on-valve analysis.

    Science.gov (United States)

    Quintana, José Benito; Miró, Manuel; Estela, José Manuel; Cerdà, Víctor

    2006-04-15

    In this paper, the third generation of flow injection analysis, also named the lab-on-valve (LOV) approach, is proposed for the first time as a front end to high-performance liquid chromatography (HPLC) for on-line solid-phase extraction (SPE) sample processing by exploiting the bead injection (BI) concept. The proposed microanalytical system based on discontinuous programmable flow features automated packing (and withdrawal after single use) of a small amount of sorbent (residues (viz., ketoprofen, naproxen, bezafibrate, diclofenac, and ibuprofen) and one metabolite (viz., salicylic acid) in surface water, urban wastewater, and urine. To this end, the copolymeric divinylbenzene-co-n-vinylpyrrolidone beads (Oasis HLB) were utilized as renewable sorptive entities in the micromachined unit. The automated analytical method features relative recovery percentages of >88%, limits of detection within the range 0.02-0.67 ng mL(-1), and coefficients of variation <11% for the column renewable mode and gives rise to a drastic reduction in operation costs ( approximately 25-fold) as compared to on-line column switching systems.

  14. Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals.

    Science.gov (United States)

    Sudarshan, Vidya K; Acharya, U Rajendra; Oh, Shu Lih; Adam, Muhammad; Tan, Jen Hong; Chua, Chua Kuang; Chua, Kok Poo; Tan, Ru San

    2017-04-01

    Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis process and aid in the proper management of CHF patients. Therefore, in this work, dual tree complex wavelets transform (DTCWT)-based methodology is proposed for an automated identification of ECG signals exhibiting CHF from normal. In the experiment, we have performed a DTCWT on ECG segments of 2s duration up to six levels to obtain the coefficients. From these DTCWT coefficients, statistical features are extracted and ranked using Bhattacharyya, entropy, minimum redundancy maximum relevance (mRMR), receiver-operating characteristics (ROC), Wilcoxon, t-test and reliefF methods. Ranked features are subjected to k-nearest neighbor (KNN) and decision tree (DT) classifiers for automated differentiation of CHF and normal ECG signals. We have achieved 99.86% accuracy, 99.78% sensitivity and 99.94% specificity in the identification of CHF affected ECG signals using 45 features. The proposed method is able to detect CHF patients accurately using only 2s of ECG signal length and hence providing sufficient time for the clinicians to further investigate on the severity of CHF and treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Automatic location of short circuit faults

    Energy Technology Data Exchange (ETDEWEB)

    Lehtonen, M. [VTT Energy, Espoo (Finland); Hakola, T.; Antila, E. [ABB Power Oy (Finland); Seppaenen, M. [North-Carelian Power Company (Finland)

    1998-08-01

    In this chapter, the automatic location of short circuit faults on medium voltage distribution lines, based on the integration of computer systems of medium voltage distribution network automation is discussed. First the distribution data management systems and their interface with the substation telecontrol, or SCADA systems, is studied. Then the integration of substation telecontrol system and computerized relay protection is discussed. Finally, the implementation of the fault location system is presented and the practical experience with the system is discussed

  16. A simple micro-extraction plate assay for automated LC-MS/MS analysis of human serum 25-hydroxyvitamin D levels.

    Science.gov (United States)

    Geib, Timon; Meier, Florian; Schorr, Pascal; Lammert, Frank; Stokes, Caroline S; Volmer, Dietrich A

    2015-01-01

    This short application note describes a simple and automated assay for determination of 25-hydroxyvitamin D (25(OH)D) levels in very small volumes of human serum. It utilizes commercial 96-well micro-extraction plates with commercial 25(OH)D isotope calibration and quality control kits. Separation was achieved using a pentafluorophenyl liquid chromatography column followed by multiple reaction monitoring-based quantification on an electrospray triple quadrupole mass spectrometer. Emphasis was placed on providing a simple assay that can be rapidly established in non-specialized laboratories within days, without the need for laborious and time consuming sample preparation steps, advanced calibration or data acquisition routines. The analytical figures of merit obtained from this assay compared well to established assays. To demonstrate the applicability, the assay was applied to analysis of serum samples from patients with chronic liver diseases and compared to results from a routine clinical immunoassay. Copyright © 2015 John Wiley & Sons, Ltd.

  17. Fault Current Characteristics of the DFIG under Asymmetrical Fault Conditions

    Directory of Open Access Journals (Sweden)

    Fan Xiao

    2015-09-01

    Full Text Available During non-severe fault conditions, crowbar protection is not activated and the rotor windings of a doubly-fed induction generator (DFIG are excited by the AC/DC/AC converter. Meanwhile, under asymmetrical fault conditions, the electrical variables oscillate at twice the grid frequency in synchronous dq frame. In the engineering practice, notch filters are usually used to extract the positive and negative sequence components. In these cases, the dynamic response of a rotor-side converter (RSC and the notch filters have a large influence on the fault current characteristics of the DFIG. In this paper, the influence of the notch filters on the proportional integral (PI parameters is discussed and the simplified calculation models of the rotor current are established. Then, the dynamic performance of the stator flux linkage under asymmetrical fault conditions is also analyzed. Based on this, the fault characteristics of the stator current under asymmetrical fault conditions are studied and the corresponding analytical expressions of the stator fault current are obtained. Finally, digital simulation results validate the analytical results. The research results are helpful to meet the requirements of a practical short-circuit calculation and the construction of a relaying protection system for the power grid with penetration of DFIGs.

  18. Comparison of Boiling and Robotics Automation Method in DNA Extraction for Metagenomic Sequencing of Human Oral Microbes.

    Directory of Open Access Journals (Sweden)

    Junya Yamagishi

    Full Text Available The rapid improvement of next-generation sequencing performance now enables us to analyze huge sample sets with more than ten thousand specimens. However, DNA extraction can still be a limiting step in such metagenomic approaches. In this study, we analyzed human oral microbes to compare the performance of three DNA extraction methods: PowerSoil (a method widely used in this field, QIAsymphony (a robotics method, and a simple boiling method. Dental plaque was initially collected from three volunteers in the pilot study and then expanded to 12 volunteers in the follow-up study. Bacterial flora was estimated by sequencing the V4 region of 16S rRNA following species-level profiling. Our results indicate that the efficiency of PowerSoil and QIAsymphony was comparable to the boiling method. Therefore, the boiling method may be a promising alternative because of its simplicity, cost effectiveness, and short handling time. Moreover, this method was reliable for estimating bacterial species and could be used in the future to examine the correlation between oral flora and health status. Despite this, differences in the efficiency of DNA extraction for various bacterial species were observed among the three methods. Based on these findings, there is no "gold standard" for DNA extraction. In future, we suggest that the DNA extraction method should be selected on a case-by-case basis considering the aims and specimens of the study.

  19. Comparison of Boiling and Robotics Automation Method in DNA Extraction for Metagenomic Sequencing of Human Oral Microbes.

    Science.gov (United States)

    Yamagishi, Junya; Sato, Yukuto; Shinozaki, Natsuko; Ye, Bin; Tsuboi, Akito; Nagasaki, Masao; Yamashita, Riu

    2016-01-01

    The rapid improvement of next-generation sequencing performance now enables us to analyze huge sample sets with more than ten thousand specimens. However, DNA extraction can still be a limiting step in such metagenomic approaches. In this study, we analyzed human oral microbes to compare the performance of three DNA extraction methods: PowerSoil (a method widely used in this field), QIAsymphony (a robotics method), and a simple boiling method. Dental plaque was initially collected from three volunteers in the pilot study and then expanded to 12 volunteers in the follow-up study. Bacterial flora was estimated by sequencing the V4 region of 16S rRNA following species-level profiling. Our results indicate that the efficiency of PowerSoil and QIAsymphony was comparable to the boiling method. Therefore, the boiling method may be a promising alternative because of its simplicity, cost effectiveness, and short handling time. Moreover, this method was reliable for estimating bacterial species and could be used in the future to examine the correlation between oral flora and health status. Despite this, differences in the efficiency of DNA extraction for various bacterial species were observed among the three methods. Based on these findings, there is no "gold standard" for DNA extraction. In future, we suggest that the DNA extraction method should be selected on a case-by-case basis considering the aims and specimens of the study.

  20. Fault tolerance and reliability in integrated ship control

    DEFF Research Database (Denmark)

    Nielsen, Jens Frederik Dalsgaard; Izadi-Zamanabadi, Roozbeh; Schiøler, Henrik

    2002-01-01

    Various strategies for achieving fault tolerance in large scale control systems are discussed. The positive and negative impacts of distribution through network communication are presented. The ATOMOS framework for standardized reliable marine automation is presented along with the corresponding...

  1. Cooperative human-machine fault diagnosis

    Science.gov (United States)

    Remington, Roger; Palmer, Everett

    1987-01-01

    Current expert system technology does not permit complete automatic fault diagnosis; significant levels of human intervention are still required. This requirement dictates a need for a division of labor that recognizes the strengths and weaknesses of both human and machine diagnostic skills. Relevant findings from the literature on human cognition are combined with the results of reviews of aircrew performance with highly automated systems to suggest how the interface of a fault diagnostic expert system can be designed to assist human operators in verifying machine diagnoses and guiding interactive fault diagnosis. It is argued that the needs of the human operator should play an important role in the design of the knowledge base.

  2. Parameter Extraction for PSpice Models by means of an Automated Optimization Tool – An IGBT model Study Case

    DEFF Research Database (Denmark)

    Suárez, Carlos Gómez; Reigosa, Paula Diaz; Iannuzzo, Francesco

    2016-01-01

    An original tool for parameter extraction of PSpice models has been released, enabling a simple parameter identification. A physics-based IGBT model is used to demonstrate that the optimization tool is capable of generating a set of parameters which predicts the steady-state and switching behavior...

  3. Semi-automated extraction of microbial DNA from feces for qPCR and phylogenetic microarray analysis

    NARCIS (Netherlands)

    Nylund, L.; Heilig, G.H.J.; Salminen, S.; Vos, de W.M.; Satokari, R.M.

    2010-01-01

    The human gastrointestinal tract (GI-tract) harbors a complex microbial ecosystem, largely composed of so far uncultured species, which can be detected only by using techniques such as PCR and by different hybridization techniques including phylogenetic microarrays. Manual DNA extraction from feces

  4. A METHOD FOR AUTOMATED ANALYSIS OF 10 ML WATER SAMPLES CONTAINING ACIDIC, BASIC, AND NEUTRAL SEMIVOLATILE COMPOUNDS LISTED IN USEPA METHOD 8270 BY SOLID PHASE EXTRACTION COUPLED IN-LINE TO LARGE VOLUME INJECTION GAS CHROMATOGRAPHY/MASS SPECTROMETRY

    Science.gov (United States)

    Data is presented showing the progress made towards the development of a new automated system combining solid phase extraction (SPE) with gas chromatography/mass spectrometry for the single run analysis of water samples containing a broad range of acid, base and neutral compounds...

  5. Faults Discovery By Using Mined Data

    Science.gov (United States)

    Lee, Charles

    2005-01-01

    Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

  6. Fully automated determination of 74 pharmaceuticals in environmental and waste waters by online solid phase extraction-liquid chromatography-electrospray-tandem mass spectrometry.

    Science.gov (United States)

    López-Serna, Rebeca; Pérez, Sandra; Ginebreda, Antoni; Petrović, Mira; Barceló, Damià

    2010-12-15

    The present work describes the development of a fully automated method, based on on-line solid-phase extraction (SPE)-liquid chromatography-electrospray-tandem mass spectrometry (LC-MS-MS), for the determination of 74 pharmaceuticals in environmental waters (superficial water and groundwater) as well as sewage waters. On-line SPE is performed by passing 2.5 mL of the water sample through a HySphere Resin GP cartridge. For unequivocal identification and confirmation two selected reaction monitoring (SRM) transitions are monitored per compound, thus four identification points are achieved. Quantification is performed by the internal standard approach, indispensable to correct the losses during the solid phase extraction, as well as the matrix effects. The main advantages of the method developed are high sensitivity (limits of detection in the low ng L(-1) range), selectivity due the use of tandem mass spectrometry and reliability due the use of 51 surrogates and minimum sample manipulation. As a part of the validation procedure, the method developed has been applied to the analysis of various environmental and sewage samples from a Spanish river and a sewage treatment plant. Copyright © 2010 Elsevier B.V. All rights reserved.

  7. Text Mining of the Electronic Health Record: An Information Extraction Approach for Automated Identification and Subphenotyping of HFpEF Patients for Clinical Trials.

    Science.gov (United States)

    Jonnalagadda, Siddhartha R; Adupa, Abhishek K; Garg, Ravi P; Corona-Cox, Jessica; Shah, Sanjiv J

    2017-06-01

    Precision medicine requires clinical trials that are able to efficiently enroll subtypes of patients in whom targeted therapies can be tested. To reduce the large amount of time spent screening, identifying, and recruiting patients with specific subtypes of heterogeneous clinical syndromes (such as heart failure with preserved ejection fraction [HFpEF]), we need prescreening systems that are able to automate data extraction and decision-making tasks. However, a major obstacle is the vast amount of unstructured free-form text in medical records. Here we describe an information extraction-based approach that automatically converts unstructured text into structured data, which is cross-referenced against eligibility criteria using a rule-based system to determine which patients qualify for a major HFpEF clinical trial (PARAGON). We show that we can achieve a sensitivity and positive predictive value of 0.95 and 0.86, respectively. Our open-source algorithm could be used to efficiently identify and subphenotype patients with HFpEF and other disorders.

  8. An automated flow injection system for metal determination by flame atomic absorption spectrometry involving on-line fabric disk sorptive extraction technique.

    Science.gov (United States)

    Anthemidis, A; Kazantzi, V; Samanidou, V; Kabir, A; Furton, K G

    2016-08-15

    A novel flow injection-fabric disk sorptive extraction (FI-FDSE) system was developed for automated determination of trace metals. The platform was based on a minicolumn packed with sol-gel coated fabric media in the form of disks, incorporated into an on-line solid-phase extraction system, coupled with flame atomic absorption spectrometry (FAAS). This configuration provides minor backpressure, resulting in high loading flow rates and shorter analytical cycles. The potentials of this technique were demonstrated for trace lead and cadmium determination in environmental water samples. The applicability of different sol-gel coated FPSE media was investigated. The on-line formed complex of metal with ammonium pyrrolidine dithiocarbamate (APDC) was retained onto the fabric surface and methyl isobutyl ketone (MIBK) was used to elute the analytes prior to atomization. For 90s preconcentration time, enrichment factors of 140 and 38 and detection limits (3σ) of 1.8 and 0.4μgL(-1) were achieved for lead and cadmium determination, respectively, with a sampling frequency of 30h(-1). The accuracy of the proposed method was estimated by analyzing standard reference materials and spiked water samples. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Automated extraction of road networks from satellite images for preparing and updating road location data for geographic information systems in transportation (GIS-t)

    Science.gov (United States)

    Gan, Cheng Tin

    Transportation agencies apply GIS (Geographic Information System) technology to better manage spatially distributed transportation facilities and services. However, due to high data conversion and update costs, GIS technology can be expensive. Remotely sensed images are widely recognized as a ready data source that might lower the cost of CIS considerably. One data object critical to transportation applications of GIS that can be extracted from remotely sensed images is the road network. This research presents a three-level (low, intermediate, and high) automated process capable of extracting road network location attributes from SPOT panchromatic images. Low-level operations extract road pixels from gray images. Intermediate-level operations convert road pixels into vectorized links which are usually fragmented. High-level operations defragment links via line-linking functions to construct road networks. This research focuses on improving the various existing techniques employed in each operation level. A comprehensive computer program was developed to implement all algorithms. For low-level operations, extensive testing was conducted to find a suitable line detector; an automated threshold selection strategy for the line detector was developed; a thinning algorithm was adapted to reduce lines to one pixel in width; and a noise removal algorithm was developed to remove pixels that form either short unconnected lines or strokes. Improvements to intermediate-level operations include developments of an adaptive binary image decomposition structure for the Hough transform, a heuristic algorithm to suppress redundant lines in the Hough output, and an adaptive thresholding scheme for the Hough transform based on both cell counts and line-length ratios. For high-level operations, a spatial-vector structure for efficient spatial search in line linking was developed. A best-neighbor finding function and four line-linking functions, each fully supported by the spatial

  10. Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds

    Science.gov (United States)

    Yang, Bisheng; Fang, Lina; Li, Jonathan

    2013-05-01

    Accurate 3D road information is important for applications such as road maintenance and virtual 3D modeling. Mobile laser scanning (MLS) is an efficient technique for capturing dense point clouds that can be used to construct detailed road models for large areas. This paper presents a method for extracting and delineating roads from large-scale MLS point clouds. The proposed method partitions MLS point clouds into a set of consecutive "scanning lines", which each consists of a road cross section. A moving window operator is used to filter out non-ground points line by line, and curb points are detected based on curb patterns. The detected curb points are tracked and refined so that they are both globally consistent and locally similar. To evaluate the validity of the proposed method, experiments were conducted using two types of street-scene point clouds captured by Optech's Lynx Mobile Mapper System. The completeness, correctness, and quality of the extracted roads are over 94.42%, 91.13%, and 91.3%, respectively, which proves the proposed method is a promising solution for extracting 3D roads from MLS point clouds.

  11. Automated chromatographic system with polarimetric detection laser applied in the control of fermentation processes and seaweed extracts characterization

    International Nuclear Information System (INIS)

    Fajer, V.; Naranjo, S.; Mora, W.; Patinno, R.; Coba, E.; Michelena, G.

    2012-01-01

    There are presented applications and innovations of chromatographic and polarimetric systems in which develop methodologies for measuring the input molasses and the resulting product of a fermentation process of alcohol from a rich honey and evaluation of the fermentation process honey servery in obtaining a drink native to the Yucatan region. Composition was assessed optically active substances in seaweed, of interest to the pharmaceutical industry. The findings provide measurements alternative raw materials and products of the sugar industry, beekeeping and pharmaceutical liquid chromatography with automated polarimetric detection reduces measurement times up to 15 min, making it comparable to the times of high chromatography resolution, significantly reducing operating costs. By chromatography system with polarimetric detection (SCDP) is new columns have included standard size designed by the authors, which allow process samples with volumes up to 1 ml and reduce measurement time to 15 min, decreasing to 5 times the volume sample and halving the time of measurement. Was evaluated determining the concentration of substances using the peaks of the chromatograms obtained for the different columns and calculate the uncertainty of measurements. The results relating to the improvement of a data acquisition program (ADQUIPOL v.2.0) and new programs for the preparation of chromatograms (CROMAPOL CROMAPOL V.1.0 and V.1.2) provide important benefits, which allow a considerable saving of time the processing of the results and can be applied in other chromatography systems with the appropriate adjustments. (Author)

  12. Automated extraction and assessment of functional features of areal measured microstructures using a segmentation-based evaluation method

    Science.gov (United States)

    Hartmann, Wito; Loderer, Andreas

    2014-10-01

    In addition to currently available surface parameters, according to ISO 4287:2010 and ISO 25178-2:2012—which are defined particularly for stochastic surfaces—a universal evaluation procedure is provided for geometrical, well-defined, microstructured surfaces. Since several million of features (like diameters, depths, etc) are present on microstructured surfaces, segmentation techniques are used for the automation of the feature-based dimensional evaluation. By applying an additional extended 3D evaluation after the segmentation and classification procedure, the accuracy of the evaluation is improved compared to the direct evaluation of segments, and additional functional parameters can be derived. Advantages of the extended segmentation-based evaluation method include not only the ability to evaluate the manufacturing process statistically (e.g. by capability indices, according to ISO 21747:2007 and ISO 3534-2:2013) and to derive statistical reliable values for the correction of microstructuring processes but also the direct re-use of the evaluated parameter (including its statistical distribution) in simulations for the calculation of probabilities with respect to the functionality of the microstructured surface. The practical suitability of this method is demonstrated using examples of microstructures for the improvement of sliding and ink transfers for printing machines.

  13. Deep learning for automated drivetrain fault detection

    DEFF Research Database (Denmark)

    Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole

    2018-01-01

    A novel data-driven deep-learning system for large-scale wind turbine drivetrain monitoring applications is presented. It uses convolutional neural network processing on complex vibration signal inputs. The system is demonstrated to learn successfully from the actions of human diagnostic experts ...

  14. Bearing fault detection using motor current signal analysis based on wavelet packet decomposition and Hilbert envelope

    Directory of Open Access Journals (Sweden)

    Imaouchen Yacine

    2015-01-01

    Full Text Available To detect rolling element bearing defects, many researches have been focused on Motor Current Signal Analysis (MCSA using spectral analysis and wavelet transform. This paper presents a new approach for rolling element bearings diagnosis without slip estimation, based on the wavelet packet decomposition (WPD and the Hilbert transform. Specifically, the Hilbert transform first extracts the envelope of the motor current signal, which contains bearings fault-related frequency information. Subsequently, the envelope signal is adaptively decomposed into a number of frequency bands by the WPD algorithm. Two criteria based on the energy and correlation analyses have been investigated to automate the frequency band selection. Experimental studies have confirmed that the proposed approach is effective in diagnosing rolling element bearing faults for improved induction motor condition monitoring and damage assessment.

  15. Machine Fault Signature Analysis

    Directory of Open Access Journals (Sweden)

    Pratesh Jayaswal

    2008-01-01

    Full Text Available The objective of this paper is to present recent developments in the field of machine fault signature analysis with particular regard to vibration analysis. The different types of faults that can be identified from the vibration signature analysis are, for example, gear fault, rolling contact bearing fault, journal bearing fault, flexible coupling faults, and electrical machine fault. It is not the intention of the authors to attempt to provide a detailed coverage of all the faults while detailed consideration is given to the subject of the rolling element bearing fault signature analysis.

  16. Toward Expanding Tremor Observations in the Northern San Andreas Fault System in the 1990s

    Science.gov (United States)

    Damiao, L. G.; Dreger, D. S.; Nadeau, R. M.; Taira, T.; Guilhem, A.; Luna, B.; Zhang, H.

    2015-12-01

    The connection between tremor activity and active fault processes continues to expand our understanding of deep fault zone properties and deformation, the tectonic process, and the relationship of tremor to the occurrence of larger earthquakes. Compared to tremors in subduction zones, known tremor signals in California are ~5 to ~10 smaller in amplitude and duration. These characteristics, in addition to scarce geographic coverage, lack of continuous data (e.g., before mid-2001 at Parkfield), and absence of instrumentation sensitive enough to monitor these events have stifled tremor detection. The continuous monitoring of these events over a relatively short time period in limited locations may lead to a parochial view of the tremor phenomena and its relationship to fault, tectonic, and earthquake processes. To help overcome this, we have embarked on a project to expand the geographic and temporal scope of tremor observation along the Northern SAF system using available continuous seismic recordings from a broad array of 100s of surface seismic stations from multiple seismic networks. Available data for most of these stations also extends back into the mid-1990s. Processing and analysis of tremor signal from this large and low signal-to-noise dataset requires a heavily automated, data-science type approach and specialized techniques for identifying and extracting reliable data. We report here on the automated, envelope based methodology we have developed. We finally compare our catalog results with pre-existing tremor catalogs in the Parkfield area.

  17. Optimal fault signal estimation

    NARCIS (Netherlands)

    Stoorvogel, Antonie Arij; Niemann, H.H.; Saberi, A.; Sannuti, P.

    2002-01-01

    We consider here both fault identification and fault signal estimation. Regarding fault identification, we seek either exact or almost fault identification. On the other hand, regarding fault signal estimation, we seek either $H_2$ optimal, $H_2$ suboptimal or Hinfinity suboptimal estimation. By

  18. Simultaneous Sensor and Process Fault Diagnostics for Propellant Feed System

    Science.gov (United States)

    Cao, J.; Kwan, C.; Figueroa, F.; Xu, R.

    2006-01-01

    The main objective of this research is to extract fault features from sensor faults and process faults by using advanced fault detection and isolation (FDI) algorithms. A tank system that has some common characteristics to a NASA testbed at Stennis Space Center was used to verify our proposed algorithms. First, a generic tank system was modeled. Second, a mathematical model suitable for FDI has been derived for the tank system. Third, a new and general FDI procedure has been designed to distinguish process faults and sensor faults. Extensive simulations clearly demonstrated the advantages of the new design.

  19. Automated and quantitative headspace in-tube extraction for the accurate determination of highly volatile compounds from wines and beers.

    Science.gov (United States)

    Zapata, Julián; Mateo-Vivaracho, Laura; Lopez, Ricardo; Ferreira, Vicente

    2012-03-23

    An automatic headspace in-tube extraction (ITEX) method for the accurate determination of acetaldehyde, ethyl acetate, diacetyl and other volatile compounds from wine and beer has been developed and validated. Method accuracy is based on the nearly quantitative transference of volatile compounds from the sample to the ITEX trap. For achieving that goal most methodological aspects and parameters have been carefully examined. The vial and sample sizes and the trapping materials were found to be critical due to the pernicious saturation effects of ethanol. Small 2 mL vials containing very small amounts of sample (20 μL of 1:10 diluted sample) and a trap filled with 22 mg of Bond Elut ENV resins could guarantee a complete trapping of sample vapors. The complete extraction requires 100 × 0.5 mL pumping strokes at 60 °C and takes 24 min. Analytes are further desorbed at 240 °C into the GC injector under a 1:5 split ratio. The proportion of analytes finally transferred to the trap ranged from 85 to 99%. The validation of the method showed satisfactory figures of merit. Determination coefficients were better than 0.995 in all cases and good repeatability was also obtained (better than 7% in all cases). Reproducibility was better than 8.3% except for acetaldehyde (13.1%). Detection limits were below the odor detection thresholds of these target compounds in wine and beer and well below the normal ranges of occurrence. Recoveries were not significantly different to 100%, except in the case of acetaldehyde. In such a case it could be determined that the method is not able to break some of the adducts that this compound forms with sulfites. However, such problem was avoided after incubating the sample with glyoxal. The method can constitute a general and reliable alternative for the analysis of very volatile compounds in other difficult matrixes. Copyright © 2012 Elsevier B.V. All rights reserved.

  20. Debug automation from pre-silicon to post-silicon

    CERN Document Server

    Dehbashi, Mehdi

    2015-01-01

    This book describes automated debugging approaches for the bugs and the faults which appear in different abstraction levels of a hardware system. The authors employ a transaction-based debug approach to systems at the transaction-level, asserting the correct relation of transactions. The automated debug approach for design bugs finds the potential fault candidates at RTL and gate-level of a circuit. Debug techniques for logic bugs and synchronization bugs are demonstrated, enabling readers to localize the most difficult bugs. Debug automation for electrical faults (delay faults)finds the potentially failing speedpaths in a circuit at gate-level. The various debug approaches described achieve high diagnosis accuracy and reduce the debugging time, shortening the IC development cycle and increasing the productivity of designers. Describes a unified framework for debug automation used at both pre-silicon and post-silicon stages; Provides approaches for debug automation of a hardware system at different levels of ...

  1. UML Statechart Fault Tree Generation By Model Checking

    DEFF Research Database (Denmark)

    Herbert, Luke Thomas; Herbert-Hansen, Zaza Nadja Lee

    Creating fault tolerant and efficient process work-flows poses a significant challenge. Individual faults, defined as an abnormal conditions or defects in a component, equipment, or sub-process, must be handled so that the system may continue to operate, and are typically addressed by implementing...... engineers imagine what undesirable events can occur under which conditions. Fault Tree Analysis (FTA) attempts to analyse the failure of systems by composing logic diagrams of separate individual faults to determine the probabil-ity of larger compound faults occurring. FTA is a commonly used method......-pleteness). To avoid these deficiencies, our approach derives the fault tree directly from the formal system model, under the assumption that any state can fail. We present a framework for the automated gener-ation of fault trees from models of real-world pro-cess workflows, expressed in a formalised subset...

  2. Fault Tolerant Position-mooring Control for Offshore Vessels

    DEFF Research Database (Denmark)

    Blanke, Mogens; Nguyen, Trong Dong

    2018-01-01

    by a system to handle faults in mooring lines, sensors or thrusters. Simulations and model basin experiments are carried out to validate the concept for scenarios with single or multiple faults. The results demonstrate that enhanced availability and safety are obtainable with this design approach. While......Fault-tolerance is crucial to maintain safety in offshore operations. The objective of this paper is to show how systematic analysis and design of fault-tolerance is conducted for a complex automation system, exemplified by thruster assisted Position-mooring. Using redundancy as required....... Functional faults that are only detectable, are rendered isolable through an active isolation approach. Once functional faults are isolated, they are handled by fault accommodation techniques to meet overall control objectives specified by class requirements. The paper illustrates the generic methodology...

  3. Fault Tolerant Position-mooring Control for Offshore Vessels

    DEFF Research Database (Denmark)

    Blanke, Mogens; Nguyen, Trong Dong

    2018-01-01

    Fault-tolerance is crucial to maintain safety in offshore operations. The objective of this paper is to show how systematic analysis and design of fault-tolerance is conducted for a complex automation system, exemplified by thruster assisted Position-mooring. Using redundancy as required....... Functional faults that are only detectable, are rendered isolable through an active isolation approach. Once functional faults are isolated, they are handled by fault accommodation techniques to meet overall control objectives specified by class requirements. The paper illustrates the generic methodology...... by a system to handle faults in mooring lines, sensors or thrusters. Simulations and model basin experiments are carried out to validate the concept for scenarios with single or multiple faults. The results demonstrate that enhanced availability and safety are obtainable with this design approach. While...

  4. A new GIS-based model for automated extraction of Sand Dune encroachment case study: Dakhla Oases, western desert of Egypt

    Directory of Open Access Journals (Sweden)

    M. Ghadiry

    2012-06-01

    Full Text Available The movements of the sand dunes are considered as a threat for roads, irrigation networks, water resources, urban areas, agriculture and infrastructures. The main objectives of this study are to develop a new GIS-based model for automated extraction of sand dune encroachment using remote sensing data and to assess the rate of sand dune movement. To monitor and assess the movements of sand dunes in Dakhla oases area, multi-temporal satellite images and a GIS-developed model, using Python script in Arc GIS, were used. The satellite images (SPOT images, 1995 and 2007 were geo-rectified using Erdas Imagine. Image subtraction was performed using spatial analyst in Arc GIS, the result of image subtraction obtains the sand dune movement between the two dates. The raster and vector shape of sand dune migration was automatically extracted using spatial analyst tools. The frontiers of individual dunes were measured at different dates and movement rates were analyzed in GIS. The ModelBuilder in Arc GIS was used in order to create a user friendly tool. The custom built model window is easy to handle by any user who wishes to adapt the model in his work. It was found that the rate of sand dune movement ranged between 3 and 9 m per year. The majority of sand dunes have a rate movement between 0 and 6 m and very few dunes had a movement rate between 6 and 9 m. Integrating remote sensing and GIS provided the necessary information for determining the minimum, maximum, mean, rate and area of sand dune migration.

  5. A novel approach for an automated liquid/liquid extraction system--principle and application for the determination of several trace contaminants in highly alloyed steels and base alloys.

    Science.gov (United States)

    Wiltsche, Helmar; Prattes, Karl; Knapp, Günter

    2011-06-01

    A novel automated liquid/liquid extraction system was developed for the determination of trace contaminants in unalloyed, alloyed and highly alloyed steels and super alloys. In the presented batch extraction system the aqueous phase and the non-water miscible organic phase were brought into close phase contact by high-speed stirring with a magnetic stir bar. Iodide complexes of Ag, Bi, Cd, Pb, Sb, Sn, Tl, and Zn were extracted from aqueous steel digests into 4-methylpentan-2-one (MIBK) containing 20 g L(-1) trioctylphosphine oxide. Ag, Bi, Cd, Pb, and Tl were extracted quantitatively whereas the extraction yields of Sb, Sn, and Zn were 83%, 61% and 75% respectively. Using high resolution continuum source flame AAS (HR-CS-FAAS) for analyte quantification the method was validated using 21 certified steel reference materials (CRMs).

  6. Automated isotope dilution liquid chromatography-tandem mass spectrometry with on-line dilution and solid phase extraction for the measurement of cortisol in human serum sample.

    Science.gov (United States)

    Kawaguchi, Migaku; Eyama, Sakae; Takatsu, Akiko

    2014-08-05

    A candidate reference measurement procedure involving automated isotope dilution coupled with liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS) with on-line dilution and solid phase extraction (SPE) has been developed and critically evaluated. We constructed the LC-MS/MS with on-line dilution and SPE system. An isotopically labelled internal standard, cortisol-d4, was added to serum sample. After equilibration, the methanol was added to the sample, and deproteination was performed. Then, the sample was applied to the LC-MS/MS system. The limit of detection (LOD) and limit of quantification (LOQ) were 0.2 and 1ngg(-1), respectively. Excellent precision was obtained with within-day variation (RSD) of 1.9% for ID-LC-MS/MS analysis (n=6). This method, which demonstrates simple, easy, good accuracy, high precision, and is free from interferences from structural analogues, qualifies as a reference measurement procedure. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. Development and validation of an automated liquid-liquid extraction GC/MS method for the determination of THC, 11-OH-THC, and free THC-carboxylic acid (THC-COOH) from blood serum.

    Science.gov (United States)

    Purschke, Kirsten; Heinl, Sonja; Lerch, Oliver; Erdmann, Freidoon; Veit, Florian

    2016-06-01

    The analysis of Δ(9)-tetrahydrocannabinol (THC) and its metabolites 11-hydroxy-Δ(9)-tetrahydrocannabinol (11-OH-THC), and 11-nor-9-carboxy-Δ(9)-tetrahydrocannabinol (THC-COOH) from blood serum is a routine task in forensic toxicology laboratories. For examination of consumption habits, the concentration of the phase I metabolite THC-COOH is used. Recommendations for interpretation of analysis values in medical-psychological assessments (regranting of driver's licenses, Germany) include threshold values for the free, unconjugated THC-COOH. Using a fully automated two-step liquid-liquid extraction, THC, 11-OH-THC, and free, unconjugated THC-COOH were extracted from blood serum, silylated with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA), and analyzed by GC/MS. The automation was carried out by an x-y-z sample robot equipped with modules for shaking, centrifugation, and solvent evaporation. This method was based on a previously developed manual sample preparation method. Validation guidelines of the Society of Toxicological and Forensic Chemistry (GTFCh) were fulfilled for both methods, at which the focus of this article is the automated one. Limits of detection and quantification for THC were 0.3 and 0.6 μg/L, for 11-OH-THC were 0.1 and 0.8 μg/L, and for THC-COOH were 0.3 and 1.1 μg/L, when extracting only 0.5 mL of blood serum. Therefore, the required limit of quantification for THC of 1 μg/L in driving under the influence of cannabis cases in Germany (and other countries) can be reached and the method can be employed in that context. Real and external control samples were analyzed, and a round robin test was passed successfully. To date, the method is employed in the Institute of Legal Medicine in Giessen, Germany, in daily routine. Automation helps in avoiding errors during sample preparation and reduces the workload of the laboratory personnel. Due to its flexibility, the analysis system can be employed for other liquid-liquid extractions as

  8. Application of Fault Tree Analysis and Fuzzy Neural Networks to Fault Diagnosis in the Internet of Things (IoT) for Aquaculture.

    Science.gov (United States)

    Chen, Yingyi; Zhen, Zhumi; Yu, Huihui; Xu, Jing

    2017-01-14

    In the Internet of Things (IoT) equipment used for aquaculture is often deployed in outdoor ponds located in remote areas. Faults occur frequently in these tough environments and the staff generally lack professional knowledge and pay a low degree of attention in these areas. Once faults happen, expert personnel must carry out maintenance outdoors. Therefore, this study presents an intelligent method for fault diagnosis based on fault tree analysis and a fuzzy neural network. In the proposed method, first, the fault tree presents a logic structure of fault symptoms and faults. Second, rules extracted from the fault trees avoid duplicate and redundancy. Third, the fuzzy neural network is applied to train the relationship mapping between fault symptoms and faults. In the aquaculture IoT, one fault can cause various fault symptoms, and one symptom can be caused by a variety of faults. Four fault relationships are obtained. Results show that one symptom-to-one fault, two symptoms-to-two faults, and two symptoms-to-one fault relationships can be rapidly diagnosed with high precision, while one symptom-to-two faults patterns perform not so well, but are still worth researching. This model implements diagnosis for most kinds of faults in the aquaculture IoT.

  9. Application of Fault Tree Analysis and Fuzzy Neural Networks to Fault Diagnosis in the Internet of Things (IoT for Aquaculture

    Directory of Open Access Journals (Sweden)

    Yingyi Chen

    2017-01-01

    Full Text Available In the Internet of Things (IoT equipment used for aquaculture is often deployed in outdoor ponds located in remote areas. Faults occur frequently in these tough environments and the staff generally lack professional knowledge and pay a low degree of attention in these areas. Once faults happen, expert personnel must carry out maintenance outdoors. Therefore, this study presents an intelligent method for fault diagnosis based on fault tree analysis and a fuzzy neural network. In the proposed method, first, the fault tree presents a logic structure of fault symptoms and faults. Second, rules extracted from the fault trees avoid duplicate and redundancy. Third, the fuzzy neural network is applied to train the relationship mapping between fault symptoms and faults. In the aquaculture IoT, one fault can cause various fault symptoms, and one symptom can be caused by a variety of faults. Four fault relationships are obtained. Results show that one symptom-to-one fault, two symptoms-to-two faults, and two symptoms-to-one fault relationships can be rapidly diagnosed with high precision, while one symptom-to-two faults patterns perform not so well, but are still worth researching. This model implements diagnosis for most kinds of faults in the aquaculture IoT.

  10. An Integrated Framework of Drivetrain Degradation Assessment and Fault Localization for Offshore Wind Turbines

    Directory of Open Access Journals (Sweden)

    Jay Lee

    2013-01-01

    Full Text Available As wind energy proliferates in onshore and offshore applications, it has become significantly important to predict wind turbine downtime and maintain operation uptime to ensure maximal yield. Two types of data systems have been widely adopted for monitoring turbine health condition: supervisory control and data acquisition (SCADA and condition monitoring system (CMS. Provided that research and development have focused on advancing analytical techniques based on these systems independently, an intelligent model that associates information from both systems is necessary and beneficial. In this paper, a systematic framework is designed to integrate CMS and SCADA data and assess drivetrain degradation over its lifecycle. Information reference and advanced feature extraction techniques are employed to procure heterogeneous health indicators. A pattern recognition algorithm is used to model baseline behavior and measure deviation of current behavior, where a Self-organizing Map (SOM and minimum quantization error (MQE method is selected to achieve degradation assessment. Eventually, the computation and ranking of component contribution to the detected degradation offers component-level fault localization. When validated and automated by various applications, the approach is able to incorporate diverse data resources and output actionable information to advise predictive maintenance with precise fault information. The approach is validated on a 3 MW offshore turbine, where an incipient fault is detected well before existing system shuts down the unit. A radar chart is used to illustrate the fault localization result.

  11. Radar Determination of Fault Slip and Location in Partially Decorrelated Images

    Science.gov (United States)

    Parker, Jay; Glasscoe, Margaret; Donnellan, Andrea; Stough, Timothy; Pierce, Marlon; Wang, Jun

    2017-06-01

    Faced with the challenge of thousands of frames of radar interferometric images, automated feature extraction promises to spur data understanding and highlight geophysically active land regions for further study. We have developed techniques for automatically determining surface fault slip and location using deformation images from the NASA Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), which is similar to satellite-based SAR but has more mission flexibility and higher resolution (pixels are approximately 7 m). This radar interferometry provides a highly sensitive method, clearly indicating faults slipping at levels of 10 mm or less. But interferometric images are subject to decorrelation between revisit times, creating spots of bad data in the image. Our method begins with freely available data products from the UAVSAR mission, chiefly unwrapped interferograms, coherence images, and flight metadata. The computer vision techniques we use assume no data gaps or holes; so a preliminary step detects and removes spots of bad data and fills these holes by interpolation and blurring. Detected and partially validated surface fractures from earthquake main shocks, aftershocks, and aseismic-induced slip are shown for faults in California, including El Mayor-Cucapah (M7.2, 2010), the Ocotillo aftershock (M5.7, 2010), and South Napa (M6.0, 2014). Aseismic slip is detected on the San Andreas Fault from the El Mayor-Cucapah earthquake, in regions of highly patterned partial decorrelation. Validation is performed by comparing slip estimates from two interferograms with published ground truth measurements.

  12. Research on fault diagnosis for RCP rotor based on wavelet analysis

    International Nuclear Information System (INIS)

    Chen Zhihui; Xia Hong; Wang Taotao

    2008-01-01

    Wavelet analysis is with the characteristics of noise reduction and multiscale resolution, and can be used to effectively extract the fault features of the typical failures of the main pumps. Simulink is used to simulate the typical faults: Misalignment Fault, Crackle Fault of rotor, and Initial Bending Fault, then the Wavelet method is used to analyze the vibration signal. The result shows that the extracted fault feature from wavelet analysis can effectively identify the fault signals. The Wavelet analysis is a practical method for the diagnosis of main coolant pump failure, and is with certain value for application and significance. (authors)

  13. Fault diagnosis methods for district heating substations

    Energy Technology Data Exchange (ETDEWEB)

    Pakanen, J.; Hyvaerinen, J.; Kuismin, J.; Ahonen, M. [VTT Building Technology, Espoo (Finland). Building Physics, Building Services and Fire Technology

    1996-12-31

    A district heating substation is a demanding process for fault diagnosis. The process is nonlinear, load conditions of the district heating network change unpredictably and standard instrumentation is designed only for control and local monitoring purposes, not for automated diagnosis. Extra instrumentation means additional cost, which is usually not acceptable to consumers. That is why all conventional methods are not applicable in this environment. The paper presents five different approaches to fault diagnosis. While developing the methods, various kinds of pragmatic aspects and robustness had to be considered in order to achieve practical solutions. The presented methods are: classification of faults using performance indexing, static and physical modelling of process equipment, energy balance of the process, interactive fault tree reasoning and statistical tests. The methods are applied to a control valve, a heat excharger, a mud separating device and the whole process. The developed methods are verified in practice using simulation, simulation or field tests. (orig.) (25 refs.)

  14. Fault detection and isolation in systems with parametric faults

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1999-01-01

    The problem of fault detection and isolation of parametric faults is considered in this paper. A fault detection problem based on parametric faults are associated with internal parameter variations in the dynamical system. A fault detection and isolation method for parametric faults is formulated...... in a standard setup and a synthesis method for fault detectors is given. Further, fault detection problems with both parametric faults and faults described by external input signals are also shortly considered....

  15. Fault zone fabric and fault weakness

    NARCIS (Netherlands)

    Collettini, C.; Niemeijer, A.; Viti, C.; Marone, C.

    2009-01-01

    Geological and geophysical evidence suggests that some crustal faults are weak1–6 compared to laboratory measurements of frictional strength7. Explanations for fault weakness include the presence of weak minerals4, high fluid pressures within the fault core8,9 and dynamic processes such as

  16. Determination of phthalates in bottled water by automated on-line solid phase extraction coupled to liquid chromatography with uv detection.

    Science.gov (United States)

    Salazar-Beltrán, Daniel; Hinojosa-Reyes, Laura; Ruiz-Ruiz, Edgar; Hernández-Ramírez, Aracely; Luis Guzmán-Mar, Jorge

    2017-06-01

    An on-line solid phase extraction coupled to liquid chromatography with UV detection (SPE/LC-UV) method was automated by the multisyringe flow-injection analysis (MSFIA) system for the determination of three phthalic acid esters (PAEs). The PAEs determined in drinking water stored in polyethylene terephthalate (PET) bottles of ten commercial brands were dimethyl phthalate (DMP), diethyl phthalate (DEP) and dibutyl phthalate (DBP). C18-bonded silica membrane was used for isolation and enrichment of the PAEs in water samples. The calibration range of the SPE/LC-UV method was 2.5-100μgL -1 for DMP and DEP and 10-100μgL -1 for DBP with correlation coefficients (r) ranging from 0.9970 to 0.9975. Limits of detection (LODs) were between 0.7 and 2.4μgL -1 . Inter-day reproducibility performed at two concentration levels (10 and 100μgL -1 ) expressed as relative standard deviation (%RSD) were found in the range of 0.9-4.0%. The solvent volume was reduced to 18mL with a total analysis time of 48min per sample. The major species detected in bottled water samples was DBP reaching concentrations between 20.5 and 82.8μgL -1 . The recovery percentages for the three analytes in drinking water were 80-115%. The migration test showed a great variation in the sum of migrated PAEs level (10.2-50.6μgL -1 ) among the PET bottle brands analyzed indicating that the presence of these contaminants in the plastic containers may depend on raw materials and the conditions used during their production process. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Determination of 74 new psychoactive substances in serum using automated in-line solid-phase extraction-liquid chromatography-tandem mass spectrometry.

    Science.gov (United States)

    Lehmann, Sabrina; Kieliba, Tobias; Beike, Justus; Thevis, Mario; Mercer-Chalmers-Bender, Katja

    2017-10-01

    A detailed description is given of the development and validation of a fully automated in-line solid-phase extraction-liquid chromatography-tandem mass spectrometry (SPE-LC-MS/MS) method capable of detecting 90 central-stimulating new psychoactive substances (NPS) and 5 conventional amphetamine-type stimulants (amphetamine, 3,4-methylenedioxy-methamphetamine (MDMA), 3,4-methylenedioxy-amphetamine (MDA), 3,4-methylenedioxy-N-ethyl-amphetamine (MDEA), methamphetamine) in serum. The aim was to apply the validated method to forensic samples. The preparation of 150μL of serum was performed by an Instrument Top Sample Preparation (ITSP)-SPE with mixed mode cation exchanger cartridges. The extracts were directly injected into an LC-MS/MS system, using a biphenyl column and gradient elution with 2mM ammonium formate/0.1% formic acid and acetonitrile/0.1% formic acid as mobile phases. The chromatographic run time amounts to 9.3min (including re-equilibration). The total cycle time is 11min, due to the interlacing between sample preparation and analysis. The method was fully validated using 69 NPS and five conventional amphetamine-type stimulants, according to the guidelines of the Society of Toxicological and Forensic Chemistry (GTFCh). The guidelines were fully achieved for 62 analytes (with a limit of detection (LOD) between 0.2 and 4μg/L), whilst full validation was not feasible for the remaining 12 analytes. For the fully validated analytes, the method achieved linearity in the 5μg/L (lower limit of quantification, LLOQ) to 250μg/L range (coefficients of determination>0.99). Recoveries for 69 of these compounds were greater than 50%, with relative standard deviations≤15%. The validated method was then tested for its capability in detecting a further 21 NPS, thus totalling 95 tested substances. An LOD between 0.4 and 1.6μg/L was obtained for these 21 additional qualitatively-measured substances. The method was subsequently successfully applied to 28 specimens from

  18. Research on the Fault Coefficient in Complex Electrical Engineering

    Directory of Open Access Journals (Sweden)

    Yi Sun

    2015-08-01

    Full Text Available Fault detection and isolation in a complex system are research hotspots and frontier problems in the reliability engineering field. Fault identification can be regarded as a procedure of excavating key characteristics from massive failure data, then classifying and identifying fault samples. In this paper, based on the fundamental of feature extraction about the fault coefficient, we will discuss the fault coefficient feature in complex electrical engineering in detail. For general fault types in a complex power system, even if there is a strong white Gaussian stochastic interference, the fault coefficient feature is still accurate and reliable. The results about comparative analysis of noise influence will also demonstrate the strong anti-interference ability and great redundancy of the fault coefficient feature in complex electrical engineering.

  19. AUTOMATION OF CONVEYOR BELT TRANSPORT

    Directory of Open Access Journals (Sweden)

    Nenad Marinović

    1990-12-01

    Full Text Available Belt conveyor transport, although one of the most economical mining transport system, introduce many problems to mantain the continuity of the operation. Every stop causes economical loses. Optimal operation require correct tension of the belt, correct belt position and velocity and faultless rolls, which are together input conditions for automation. Detection and position selection of the faults are essential for safety to eliminate fire hazard and for efficient maintenance. Detection and location of idler roll faults are still open problem and up to now not solved successfully (the paper is published in Croatian.

  20. Systematic review automation technologies

    Science.gov (United States)

    2014-01-01

    Systematic reviews, a cornerstone of evidence-based medicine, are not produced quickly enough to support clinical practice. The cost of production, availability of the requisite expertise and timeliness are often quoted as major contributors for the delay. This detailed survey of the state of the art of information systems designed to support or automate individual tasks in the systematic review, and in particular systematic reviews of randomized controlled clinical trials, reveals trends that see the convergence of several parallel research projects. We surveyed literature describing informatics systems that support or automate the processes of systematic review or each of the tasks of the systematic review. Several projects focus on automating, simplifying and/or streamlining specific tasks of the systematic review. Some tasks are already fully automated while others are still largely manual. In this review, we describe each task and the effect that its automation would have on the entire systematic review process, summarize the existing information system support for each task, and highlight where further research is needed for realizing automation for the task. Integration of the systems that automate systematic review tasks may lead to a revised systematic review workflow. We envisage the optimized workflow will lead to system in which each systematic review is described as a computer program that automatically retrieves relevant trials, appraises them, extracts and synthesizes data, evaluates the risk of bias, performs meta-analysis calculations, and produces a report in real time. PMID:25005128

  1. Automated Contingency Management for Advanced Propulsion Systems Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Automated Contingency Management (ACM), or the ability to confidently and autonomously adapt to fault conditions with the goal of still achieving mission objectives,...

  2. Automated Contingency Management for Advanced Propulsion Systems, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Automated Contingency Management (ACM), or the ability to confidently and autonomously adapt to fault conditions with the goal of still achieving mission objectives,...

  3. Fault size classification of rotating machinery using support vector machine

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Y. S.; Lee, D. H.; Park, S. K. [Korea Hydro and Nuclear Power Co. Ltd., Daejeon (Korea, Republic of)

    2012-03-15

    Studies on fault diagnosis of rotating machinery have been carried out to obtain a machinery condition in two ways. First is a classical approach based on signal processing and analysis using vibration and acoustic signals. Second is to use artificial intelligence techniques to classify machinery conditions into normal or one of the pre-determined fault conditions. Support Vector Machine (SVM) is well known as intelligent classifier with robust generalization ability. In this study, a two-step approach is proposed to predict fault types and fault sizes of rotating machinery in nuclear power plants using multi-class SVM technique. The model firstly classifies normal and 12 fault types and then identifies their sizes in case of predicting any faults. The time and frequency domain features are extracted from the measured vibration signals and used as input to SVM. A test rig is used to simulate normal and the well-know 12 artificial fault conditions with three to six fault sizes of rotating machinery. The application results to the test data show that the present method can estimate fault types as well as fault sizes with high accuracy for bearing an shaft-related faults and misalignment. Further research, however, is required to identify fault size in case of unbalance, rubbing, looseness, and coupling-related faults.

  4. Fault size classification of rotating machinery using support vector machine

    International Nuclear Information System (INIS)

    Kim, Y. S.; Lee, D. H.; Park, S. K.

    2012-01-01

    Studies on fault diagnosis of rotating machinery have been carried out to obtain a machinery condition in two ways. First is a classical approach based on signal processing and analysis using vibration and acoustic signals. Second is to use artificial intelligence techniques to classify machinery conditions into normal or one of the pre-determined fault conditions. Support Vector Machine (SVM) is well known as intelligent classifier with robust generalization ability. In this study, a two-step approach is proposed to predict fault types and fault sizes of rotating machinery in nuclear power plants using multi-class SVM technique. The model firstly classifies normal and 12 fault types and then identifies their sizes in case of predicting any faults. The time and frequency domain features are extracted from the measured vibration signals and used as input to SVM. A test rig is used to simulate normal and the well-know 12 artificial fault conditions with three to six fault sizes of rotating machinery. The application results to the test data show that the present method can estimate fault types as well as fault sizes with high accuracy for bearing an shaft-related faults and misalignment. Further research, however, is required to identify fault size in case of unbalance, rubbing, looseness, and coupling-related faults

  5. Automated hippocampal location and extraction

    OpenAIRE

    Bonnici, Heidi M.

    2010-01-01

    The hippocampus is a complex brain structure that has been studied extensively and is subject to abnormal structural change in various neuropsychiatric disorders. The highest definition in vivo method of visualizing the anatomy of this structure is structural Magnetic Resonance Imaging (MRI). Gross structure can be assessed by the naked eye inspection of MRI scans but measurement is required to compare scans from individuals within normal ranges, and to assess change over time ...

  6. Evaluating Fault Management Operations Concepts for Next-Generation Spacecraft: What Eye Movements Tell Us

    Science.gov (United States)

    Hayashi, Miwa; Ravinder, Ujwala; McCann, Robert S.; Beutter, Brent; Spirkovska, Lily

    2009-01-01

    Performance enhancements associated with selected forms of automation were quantified in a recent human-in-the-loop evaluation of two candidate operational concepts for fault management on next-generation spacecraft. The baseline concept, called Elsie, featured a full-suite of "soft" fault management interfaces. However, operators were forced to diagnose malfunctions with minimal assistance from the standalone caution and warning system. The other concept, called Besi, incorporated a more capable C&W system with an automated fault diagnosis capability. Results from analyses of participants' eye movements indicate that the greatest empirical benefit of the automation stemmed from eliminating the need for text processing on cluttered, text-rich displays.

  7. Fault tree handbook

    International Nuclear Information System (INIS)

    Haasl, D.F.; Roberts, N.H.; Vesely, W.E.; Goldberg, F.F.

    1981-01-01

    This handbook describes a methodology for reliability analysis of complex systems such as those which comprise the engineered safety features of nuclear power generating stations. After an initial overview of the available system analysis approaches, the handbook focuses on a description of the deductive method known as fault tree analysis. The following aspects of fault tree analysis are covered: basic concepts for fault tree analysis; basic elements of a fault tree; fault tree construction; probability, statistics, and Boolean algebra for the fault tree analyst; qualitative and quantitative fault tree evaluation techniques; and computer codes for fault tree evaluation. Also discussed are several example problems illustrating the basic concepts of fault tree construction and evaluation

  8. Validation of a fully automated solid‐phase extraction and ultra‐high‐performance liquid chromatography–tandem mass spectrometry method for quantification of 30 pharmaceuticals and metabolites in post‐mortem blood and brain samples

    DEFF Research Database (Denmark)

    Nielsen, Marie Katrine Klose; Nedahl, Michael; Johansen, Sys Stybe

    2018-01-01

    In this study, we present the validation of an analytical method capable of quantifying 30 commonly encountered pharmaceuticals and metabolites in whole blood and brain tissue from forensic cases. Solid‐phase extraction was performed by a fully automated robotic system, thereby minimising manual...... labour and human error while increasing sample throughput, robustness, and traceability. The method was validated in blood in terms of selectivity, linear range, matrix effect, extraction recovery, process efficiency, carry‐over, stability, precision, and accuracy. Deuterated analogues of each analyte....../kg. Thus, the linear range covered both therapeutic and toxic levels. The method showed acceptable accuracy and precision, with accuracies ranging from 80 to 118% and precision below 19% for the majority of the analytes. Linear range, matrix effect, extraction recovery, process efficiency, precision...

  9. Adaptive Stochastic Resonance in Second-Order System with General Scale Transformation for Weak Feature Extraction and Its Application in Bearing Fault Diagnosis

    Science.gov (United States)

    Ma, Qiang; Huang, Dawen; Yang, Jianhua

    The theory of general scale transformation (GST) is put forward and used in the second-order underdamped bistable system to extract weak signal features submerged into strong noise. An adaptive stochastic resonance (SR) with GST is proposed and realized by the quantum particle swarm optimization (QPSO) algorithm. The harmonic signal and experimental signal are considered to compare GST with normalized scale transformation (NST) in the second-order system. The results show that detection effect of the adaptive SR with GST is better than the NST SR. In addition, the output signal-to-noise ratio (SNR) is significantly improved in the GST method. Meanwhile, the dependence of the signal extraction efficiency on the noise intensity is researched. The output SNR is decreased with the increase of the noise intensity in two methods. However, the proposed method is always superior to the NST. Moreover, the superiority of the Brown particle oscillation in the single well is discussed. The proposed method has certain reference value in the extraction of the weak signal under the strong noise background.

  10. Fault Tolerant Feedback Control

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, H.

    2001-01-01

    An architecture for fault tolerant feedback controllers based on the Youla parameterization is suggested. It is shown that the Youla parameterization will give a residual vector directly in connection with the fault diagnosis part of the fault tolerant feedback controller. It turns out...... that there is a separation be-tween the feedback controller and the fault tolerant part. The closed loop feedback properties are handled by the nominal feedback controller and the fault tolerant part is handled by the design of the Youla parameter. The design of the fault tolerant part will not affect the design...

  11. Two sides of a fault: Grain-scale analysis of pore pressure control on fault slip

    Science.gov (United States)

    Yang, Zhibing; Juanes, Ruben

    2018-02-01

    Pore fluid pressure in a fault zone can be altered by natural processes (e.g., mineral dehydration and thermal pressurization) and industrial operations involving subsurface fluid injection and extraction for the development of energy and water resources. However, the effect of pore pressure change on the stability and slip motion of a preexisting geologic fault remains poorly understood; yet, it is critical for the assessment of seismic hazard. Here, we develop a micromechanical model to investigate the effect of pore pressure on fault slip behavior. The model couples fluid flow on the network of pores with mechanical deformation of the skeleton of solid grains. Pore fluid exerts pressure force onto the grains, the motion of which is solved using the discrete element method. We conceptualize the fault zone as a gouge layer sandwiched between two blocks. We study fault stability in the presence of a pressure discontinuity across the gouge layer and compare it with the case of continuous (homogeneous) pore pressure. We focus on the onset of shear failure in the gouge layer and reproduce conditions where the failure plane is parallel to the fault. We show that when the pressure is discontinuous across the fault, the onset of slip occurs on the side with the higher pore pressure, and that this onset is controlled by the maximum pressure on both sides of the fault. The results shed new light on the use of the effective stress principle and the Coulomb failure criterion in evaluating the stability of a complex fault zone.

  12. Two sides of a fault: Grain-scale analysis of pore pressure control on fault slip.

    Science.gov (United States)

    Yang, Zhibing; Juanes, Ruben

    2018-02-01

    Pore fluid pressure in a fault zone can be altered by natural processes (e.g., mineral dehydration and thermal pressurization) and industrial operations involving subsurface fluid injection and extraction for the development of energy and water resources. However, the effect of pore pressure change on the stability and slip motion of a preexisting geologic fault remains poorly understood; yet, it is critical for the assessment of seismic hazard. Here, we develop a micromechanical model to investigate the effect of pore pressure on fault slip behavior. The model couples fluid flow on the network of pores with mechanical deformation of the skeleton of solid grains. Pore fluid exerts pressure force onto the grains, the motion of which is solved using the discrete element method. We conceptualize the fault zone as a gouge layer sandwiched between two blocks. We study fault stability in the presence of a pressure discontinuity across the gouge layer and compare it with the case of continuous (homogeneous) pore pressure. We focus on the onset of shear failure in the gouge layer and reproduce conditions where the failure plane is parallel to the fault. We show that when the pressure is discontinuous across the fault, the onset of slip occurs on the side with the higher pore pressure, and that this onset is controlled by the maximum pressure on both sides of the fault. The results shed new light on the use of the effective stress principle and the Coulomb failure criterion in evaluating the stability of a complex fault zone.

  13. Graphical User Interface Aided Online Fault Diagnosis of Electric Motor - DC motor case study

    Directory of Open Access Journals (Sweden)

    POSTALCIOGLU OZGEN, S.

    2009-10-01

    Full Text Available This paper contains graphical user interface (GUI aided online fault diagnosis for DC motor. The aim of the research is to prevent system faults. Online fault diagnosis has been studied. Design of fault diagnosis has two main levels: Level 1 comprises a traditional control loop; Level 2 contains knowledge based fault diagnosis. Fault diagnosis technique contains feature extraction module, feature cluster module and fault decision module. Wavelet analysis has been used for the feature extraction module. For the feature cluster module, fuzzy cluster has been applied. Faults effects are examined on the system using statistical analysis. In this study Fault Diagnosis technique obtains fault detection, identification and halting the system. In the meantime graphical user interface (GUI is opened when fault is detected. GUI shows the measurement value, fault time and fault type. This property gives some information about the system to the personnel. As seen from the simulation results, faults can be detected and identified as soon as fault appears. In summary, if the system has a fault diagnosis structure, system dangerous situations can be avoided.

  14. Workflow Fault Tree Generation Through Model Checking

    DEFF Research Database (Denmark)

    Herbert, Luke Thomas; Sharp, Robin

    2014-01-01

    We present a framework for the automated generation of fault trees from models of realworld process workflows, expressed in a formalised subset of the popular Business Process Modelling and Notation (BPMN) language. To capture uncertainty and unreliability in workflows, we extend this formalism...... to calculate the probabilities of reaching each non-error system state. Each generated error state is assigned a variable indicating its individual probability of occurrence. Our method can determine the probability of combined faults occurring, while accounting for the basic probabilistic structure...... of the system being modelled. From these calculations, a comprehensive fault tree is generated. Further, we show that annotating the model with rewards (data) allows the expected mean values of reward structures to be calculated at points of failure....

  15. Fault detection and isolation in systems with parametric faults

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1999-01-01

    The problem of fault detection and isolation of parametric faults is considered in this paper. A fault detection problem based on parametric faults are associated with internal parameter variations in the dynamical system. A fault detection and isolation method for parametric faults is formulated...

  16. Iowa Bedrock Faults

    Data.gov (United States)

    Iowa State University GIS Support and Research Facility — This fault coverage locates and identifies all currently known/interpreted fault zones in Iowa, that demonstrate offset of geologic units in exposure or subsurface...

  17. Design of fault simulator

    International Nuclear Information System (INIS)

    Gabbar, Hossam A.; Sayed, Hanaa E.; Osunleke, Ajiboye S.; Masanobu, Hara

    2009-01-01

    Fault simulator is proposed to understand and evaluate all possible fault propagation scenarios, which is an essential part of safety design and operation design and support of chemical/production processes. Process models are constructed and integrated with fault models, which are formulated in qualitative manner using fault semantic networks (FSN). Trend analysis techniques are used to map real time and simulation quantitative data into qualitative fault models for better decision support and tuning of FSN. The design of the proposed fault simulator is described and applied on experimental plant (G-Plant) to diagnose several fault scenarios. The proposed fault simulator will enable industrial plants to specify and validate safety requirements as part of safety system design as well as to support recovery and shutdown operation and disaster management.

  18. Layered Fault Management Architecture

    National Research Council Canada - National Science Library

    Sztipanovits, Janos

    2004-01-01

    ... UAVs or Organic Air Vehicles. The approach of this effort was to analyze fault management requirements of formation flight for fleets of UAVs, and develop a layered fault management architecture which demonstrates significant...

  19. An automatic fault management model for distribution networks

    Energy Technology Data Exchange (ETDEWEB)

    Lehtonen, M.; Haenninen, S. [VTT Energy, Espoo (Finland); Seppaenen, M. [North-Carelian Power Co (Finland); Antila, E.; Markkila, E. [ABB Transmit Oy (Finland)

    1998-08-01

    An automatic computer model, called the FI/FL-model, for fault location, fault isolation and supply restoration is presented. The model works as an integrated part of the substation SCADA, the AM/FM/GIS system and the medium voltage distribution network automation systems. In the model, three different techniques are used for fault location. First, by comparing the measured fault current to the computed one, an estimate for the fault distance is obtained. This information is then combined, in order to find the actual fault point, with the data obtained from the fault indicators in the line branching points. As a third technique, in the absence of better fault location data, statistical information of line section fault frequencies can also be used. For combining the different fault location information, fuzzy logic is used. As a result, the probability weights for the fault being located in different line sections, are obtained. Once the faulty section is identified, it is automatically isolated by remote control of line switches. Then the supply is restored to the remaining parts of the network. If needed, reserve connections from other adjacent feeders can also be used. During the restoration process, the technical constraints of the network are checked. Among these are the load carrying capacity of line sections, voltage drop and the settings of relay protection. If there are several possible network topologies, the model selects the technically best alternative. The FI/IL-model has been in trial use at two substations of the North-Carelian Power Company since November 1996. This chapter lists the practical experiences during the test use period. Also the benefits of this kind of automation are assessed and future developments are outlined

  20. Fault tolerant computing systems

    International Nuclear Information System (INIS)

    Randell, B.

    1981-01-01

    Fault tolerance involves the provision of strategies for error detection damage assessment, fault treatment and error recovery. A survey is given of the different sorts of strategies used in highly reliable computing systems, together with an outline of recent research on the problems of providing fault tolerance in parallel and distributed computing systems. (orig.)

  1. Performance based fault diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    2002-01-01

    Different aspects of fault detection and fault isolation in closed-loop systems are considered. It is shown that using the standard setup known from feedback control, it is possible to formulate fault diagnosis problems based on a performance index in this general standard setup. It is also shown...

  2. Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump

    Science.gov (United States)

    Zhang, Ming; Jiang, Zhinong; Feng, Kun

    2017-09-01

    Rolling bearing faults are among the primary causes of breakdown in multistage centrifugal pump. A novel method of rolling bearings fault diagnosis based on variational mode decomposition is presented in this contribution. The rolling bearing fault signal calculating model of different location defect is established by failure mechanism analysis, and the simulation vibration signal of the proposed fault model is investigated by FFT and envelope analysis. A comparison has gone to evaluate the performance of bearing defect characteristic extraction for rolling bearings simulation signal by using VMD and EMD. The result of comparison verifies the VMD can accurately extract the principal mode of bearing fault signal, and it better than EMD in bearing defect characteristic extraction. The VMD is then applied to detect different location fault features for rolling bearings fault diagnosis via modeling simulation vibration signal and practical vibration signal. The analysis result of simulation and experiment proves that the proposed method can successfully diagnosis rolling bearings fault.

  3. Fault-Tree Compiler

    Science.gov (United States)

    Butler, Ricky W.; Boerschlein, David P.

    1993-01-01

    Fault-Tree Compiler (FTC) program, is software tool used to calculate probability of top event in fault tree. Gates of five different types allowed in fault tree: AND, OR, EXCLUSIVE OR, INVERT, and M OF N. High-level input language easy to understand and use. In addition, program supports hierarchical fault-tree definition feature, which simplifies tree-description process and reduces execution time. Set of programs created forming basis for reliability-analysis workstation: SURE, ASSIST, PAWS/STEM, and FTC fault-tree tool (LAR-14586). Written in PASCAL, ANSI-compliant C language, and FORTRAN 77. Other versions available upon request.

  4. Information Based Fault Diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2008-01-01

    Fault detection and isolation, (FDI) of parametric faults in dynamic systems will be considered in this paper. An active fault diagnosis (AFD) approach is applied. The fault diagnosis will be investigated with respect to different information levels from the external inputs to the systems....... These inputs are disturbance inputs, reference inputs and auxilary inputs. The diagnosis of the system is derived by an evaluation of the signature from the inputs in the residual outputs. The changes of the signatures form the external inputs are used for detection and isolation of the parametric faults....

  5. Autonomy, Automation, and Systems

    Science.gov (United States)

    Turner, Philip R.

    1987-02-01

    Aerospace industry interest in autonomy and automation, given fresh impetus by the national goal of establishing a Space Station, is becoming a major item of research and technology development. The promise of new technology arising from research in Artificial Intelligence (AI) has focused much attention on its potential in autonomy and automation. These technologies can improve performance in autonomous control functions that involve planning, scheduling, and fault diagnosis of complex systems. There are, however, many aspects of system and subsystem design in an autonomous system that impact AI applications, but do not directly involve AI technology. Development of a system control architecture, establishment of an operating system within the design, providing command and sensory data collection features appropriate to automated operation, and the use of design analysis tools to support system engineering are specific examples of major design issues. Aspects such as these must also receive attention and technology development support if we are to implement complex autonomous systems within the realistic limitations of mass, power, cost, and available flight-qualified technology that are all-important to a flight project.

  6. Fault isolability conditions for linear systems with additive faults

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Stoustrup, Jakob

    2006-01-01

    In this paper, we shall show that an unlimited number of additive single faults can be isolated under mild conditions if a general isolation scheme is applied. Multiple faults are also covered. The approach is algebraic and is based on a set representation of faults, where all faults within a set...... can occur simultaneously, whereas faults belonging to different fault sets appear disjoint in time. The proposed fault detection and isolation (FDI) scheme consists of three steps. A fault detection (FD) step is followed by a fault set isolation (FSI) step. Here the fault set is isolated wherein...... the faults have occurred. The last step is a fault isolation (FI) of the faults occurring in a specific fault set, i.e. equivalent with the standard FI step....

  7. Earthquake fault superhighways

    Science.gov (United States)

    Robinson, D. P.; Das, S.; Searle, M. P.

    2010-10-01

    Motivated by the observation that the rare earthquakes which propagated for significant distances at supershear speeds occurred on very long straight segments of faults, we examine every known major active strike-slip fault system on land worldwide and identify those with long (> 100 km) straight portions capable not only of sustained supershear rupture speeds but having the potential to reach compressional wave speeds over significant distances, and call them "fault superhighways". The criteria used for identifying these are discussed. These superhighways include portions of the 1000 km long Red River fault in China and Vietnam passing through Hanoi, the 1050 km long San Andreas fault in California passing close to Los Angeles, Santa Barbara and San Francisco, the 1100 km long Chaman fault system in Pakistan north of Karachi, the 700 km long Sagaing fault connecting the first and second cities of Burma, Rangoon and Mandalay, the 1600 km Great Sumatra fault, and the 1000 km Dead Sea fault. Of the 11 faults so classified, nine are in Asia and two in North America, with seven located near areas of very dense populations. Based on the current population distribution within 50 km of each fault superhighway, we find that more than 60 million people today have increased seismic hazards due to them.

  8. Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System

    Directory of Open Access Journals (Sweden)

    Jie-jia Li

    2014-01-01

    Full Text Available This paper established the fault diagnosis system of aluminum electrolysis, according to the characteristics of the faults in aluminum electrolysis. This system includes two subsystems; one is process fault subsystem and the other is fault subsystem. Process fault subsystem includes the subneural network layer and decision fusion layer. Decision fusion neural network verifies the diagnosis result of the subneural network by the information transferring over the network and gives the decision of fault synthetically. EMD algorithm is used for data preprocessing of current signal in stator of the fault subsystem. Wavelet decomposition is used to extract feature on current signal in the stator; then, the system inputs the feature to the rough neural network for fault diagnosis and fault classification. The rough neural network gives the results of fault diagnosis. The simulation results verify the feasibility of the method.

  9. Profiling of tryptophan-related plasma indoles in patients with carcinoid tumors by automated, on-line, solid-phase extraction and HPLC with fluorescence detection

    NARCIS (Netherlands)

    Kema, IP; Meijer, WG; Meiborg, G; Ooms, B; Willemse, PHB; de Vries, EGE

    2001-01-01

    Background: Profiling of the plasma indoles tryptophan, 5-hydroxytryptophan (5-HTP), serotonin, and 5-hydroxyindoleacetic acid (5-HIAA) is useful in the diagnosis and follow-up of patients with carcinoid tumors. We describe an automated method for the profiling of these indoles in protein-containing

  10. Enantioselective determination of methylphenidate and ritalinic acid in whole blood from forensic cases using automated solid-phase extraction and liquid chromatography-tandem mass spectrometry

    DEFF Research Database (Denmark)

    Thomsen, Ragnar; B. Rasmussen, Henrik; Linnet, Kristian

    2012-01-01

    A chiral liquid chromatography tandem mass spectrometry (LC–MS-MS) method was developed and validated for quantifying methylphenidate and its major metabolite ritalinic acid in blood from forensic cases. Blood samples were prepared in a fully automated system by protein precipitation followed...

  11. Library Automation

    OpenAIRE

    Dhakne, B. N.; Giri, V. V; Waghmode, S. S.

    2010-01-01

    New technologies library provides several new materials, media and mode of storing and communicating the information. Library Automation reduces the drudgery of repeated manual efforts in library routine. By use of library automation collection, Storage, Administration, Processing, Preservation and communication etc.

  12. Rolling bearing fault diagnostics using artificial neural networks ...

    African Journals Online (AJOL)

    The extracted features are used as inputs to all three ANN classifiers: MLP, RBF, and PNN for four-class: Healthy, outer, inner and roller faults identification. The procedure is illustrated using the experimental vibration data of a rotating machine with different bearing faults. The results show the relative effectiveness of three ...

  13. Medication errors: prescribing faults and prescription errors.

    Science.gov (United States)

    Velo, Giampaolo P; Minuz, Pietro

    2009-06-01

    1. Medication errors are common in general practice and in hospitals. Both errors in the act of writing (prescription errors) and prescribing faults due to erroneous medical decisions can result in harm to patients. 2. Any step in the prescribing process can generate errors. Slips, lapses, or mistakes are sources of errors, as in unintended omissions in the transcription of drugs. Faults in dose selection, omitted transcription, and poor handwriting are common. 3. Inadequate knowledge or competence and incomplete information about clinical characteristics and previous treatment of individual patients can result in prescribing faults, including the use of potentially inappropriate medications. 4. An unsafe working environment, complex or undefined procedures, and inadequate communication among health-care personnel, particularly between doctors and nurses, have been identified as important underlying factors that contribute to prescription errors and prescribing faults. 5. Active interventions aimed at reducing prescription errors and prescribing faults are strongly recommended. These should be focused on the education and training of prescribers and the use of on-line aids. The complexity of the prescribing procedure should be reduced by introducing automated systems or uniform prescribing charts, in order to avoid transcription and omission errors. Feedback control systems and immediate review of prescriptions, which can be performed with the assistance of a hospital pharmacist, are also helpful. Audits should be performed periodically.

  14. Fault Monitoring and Re-Configurable Control for a Ship Propulsion Plant

    DEFF Research Database (Denmark)

    Blanke, M.; Izadi-Zamanabadi, Roozbeh; Lootsma, T.F.

    1998-01-01

    Minor faults in ship propulsion and their associated automation systems can cause dramatic reduction on ships' ability to propel and manoeuvre, and effective means are needed to prevent that simple faults develop into severe failure. The paper analyses the control system for a propulsion plant on...

  15. Analytical Model-based Fault Detection and Isolation in Control Systems

    DEFF Research Database (Denmark)

    Vukic, Z.; Ozbolt, H.; Blanke, M.

    1998-01-01

    The paper gives an introduction and an overview of the field of fault detection and isolation for control systems. The summary of analytical (quantitative model-based) methodds and their implementation are presented. The focus is given to mthe analytical model-based fault-detection and fault diag...... diagnosis methods, often viewed as the classical or deterministic ones. Emphasis is placed on the algorithms suitable for ship automation, unmanned underwater vehicles, and other systems of automatic control....

  16. Process automation

    International Nuclear Information System (INIS)

    Moser, D.R.

    1986-01-01

    Process automation technology has been pursued in the chemical processing industries and to a very limited extent in nuclear fuel reprocessing. Its effective use has been restricted in the past by the lack of diverse and reliable process instrumentation and the unavailability of sophisticated software designed for process control. The Integrated Equipment Test (IET) facility was developed by the Consolidated Fuel Reprocessing Program (CFRP) in part to demonstrate new concepts for control of advanced nuclear fuel reprocessing plants. A demonstration of fuel reprocessing equipment automation using advanced instrumentation and a modern, microprocessor-based control system is nearing completion in the facility. This facility provides for the synergistic testing of all chemical process features of a prototypical fuel reprocessing plant that can be attained with unirradiated uranium-bearing feed materials. The unique equipment and mission of the IET facility make it an ideal test bed for automation studies. This effort will provide for the demonstration of the plant automation concept and for the development of techniques for similar applications in a full-scale plant. A set of preliminary recommendations for implementing process automation has been compiled. Some of these concepts are not generally recognized or accepted. The automation work now under way in the IET facility should be useful to others in helping avoid costly mistakes because of the underutilization or misapplication of process automation. 6 figs

  17. Fault tolerant control for uncertain systems with parametric faults

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2006-01-01

    A fault tolerant control (FTC) architecture based on active fault diagnosis (AFD) and the YJBK (Youla, Jarb, Bongiorno and Kucera)parameterization is applied in this paper. Based on the FTC architecture, fault tolerant control of uncertain systems with slowly varying parametric faults...... is investigated. Conditions are given for closed-loop stability in case of false alarms or missing fault detection/isolation....

  18. Quantification of five compounds with heterogeneous physicochemical properties (morphine, 6-monoacetylmorphine, cyamemazine, meprobamate and caffeine) in 11 fluids and tissues, using automated solid-phase extraction and gas chromatography-tandem mass spectrometry.

    Science.gov (United States)

    Bévalot, Fabien; Bottinelli, Charline; Cartiser, Nathalie; Fanton, Laurent; Guitton, Jérôme

    2014-06-01

    An automated solid-phase extraction (SPE) protocol followed by gas chromatography coupled with tandem mass spectrometry was developed for quantification of caffeine, cyamemazine, meprobamate, morphine and 6-monoacetylmorphine (6-MAM) in 11 biological matrices [blood, urine, bile, vitreous humor, liver, kidney, lung and skeletal muscle, brain, adipose tissue and bone marrow (BM)]. The assay was validated for linearity, within- and between-day precision and accuracy, limits of quantification, selectivity, extraction recovery (ER), sample dilution and autosampler stability on BM. For the other matrices, partial validation was performed (limits of quantification, linearity, within-day precision, accuracy, selectivity and ER). The lower limits of quantification were 12.5 ng/mL(ng/g) for 6-MAM, morphine and cyamemazine, 100 ng/mL(ng/g) for meprobamate and 50 ng/mL(ng/g) for caffeine. Analysis of real-case samples demonstrated the performance of the assay in forensic toxicology to investigate challenging cases in which, for example, blood is not available or in which analysis in alternative matrices could be relevant. The SPE protocol was also assessed as an extraction procedure that could target other relevant analytes of interest. The extraction procedure was applied to 12 molecules of forensic interest with various physicochemical properties (alimemazine, alprazolam, amitriptyline, citalopram, cocaine, diazepam, levomepromazine, nordazepam, tramadol, venlafaxine, pentobarbital and phenobarbital). All drugs were able to be detected at therapeutic concentrations in blood and in the alternate matrices.

  19. Improving the software fault localization process through testability information

    NARCIS (Netherlands)

    Gonzalez-Sanchez, A.; Abreu, R.; Gross, H.; Van Gemund, A.

    2010-01-01

    When failures occur during software testing, automated software fault localization helps to diagnose their root causes and identify the defective components of a program to support debugging. Diagnosis is carried out by selecting test cases in such way that their pass or fail information will narrow

  20. How Faults Shape the Earth.

    Science.gov (United States)

    Bykerk-Kauffman, Ann

    1992-01-01

    Presents fault activity with an emphasis on earthquakes and changes in continent shapes. Identifies three types of fault movement: normal, reverse, and strike faults. Discusses the seismic gap theory, plate tectonics, and the principle of superposition. Vignettes portray fault movement, and the locations of the San Andreas fault and epicenters of…

  1. Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

    Directory of Open Access Journals (Sweden)

    Xiang Wang

    2015-07-01

    Full Text Available Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD, and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches.

  2. Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding.

    Science.gov (United States)

    Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

    2015-07-06

    Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches.

  3. Feature-based handling of surface faults in compact disc players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Andersen, Palle

    2006-01-01

    In this paper a novel method called feature-based control is presented. The method is designed to improve compact disc players’ handling of surface faults on the discs. The method is based on a fault-tolerant control scheme, which uses extracted features of the surface faults to remove those from...... the detector signals used for control during the occurrence of surface faults. The extracted features are coefficients of Karhunen–Loève approximations of the surface faults. The performance of the feature-based control scheme controlling compact disc players playing discs with surface faults has been...... validated experimentally. The proposed scheme reduces the control errors due to the surface faults, and in some cases where the standard fault handling scheme fails, our scheme keeps the CD-player playing....

  4. Fault diagnosis of rotating machine by isometric feature mapping

    International Nuclear Information System (INIS)

    Zhang, Yun; Li, Benwei; Wang, Lin; Wang, Wen; Wang, Zibin

    2013-01-01

    Principal component analysis (PCA) and linear discriminate analysis (LDA) are well-known linear dimensionality reductions for fault classification. However, since they are linear methods, they perform not well for high-dimensional data that has the nonlinear geometric structure. As kernel extension of PCA, Kernel PCA is used for nonlinear fault classification. However, the performance of Kernel PCA largely depends on its kernel function which can only be empirically selected from finite candidates. Thus, a novel rotating machine fault diagnosis approach based on geometrically motivated nonlinear dimensionality reduction named isometric feature mapping (Isomap) is proposed. The approach can effectively extract the intrinsic nonlinear manifold features embedded in high-dimensional fault data sets. Experimental results with rotor and rolling bearing data show that the proposed approach overcomes the flaw of conventional fault pattern recognition approaches and obviously improves the fault classification performance.

  5. Programmable automation systems in PSA

    International Nuclear Information System (INIS)

    Pulkkinen, U.

    1997-06-01

    The Finnish safety authority (STUK) requires plant specific PSAs, and quantitative safety goals are set on different levels. The reliability analysis is more problematic when critical safety functions are realized by applying programmable automation systems. Conventional modeling techniques do not necessarily apply to the analysis of these systems, and the quantification seems to be impossible. However, it is important to analyze contribution of programmable automation systems to the plant safety and PSA is the only method with system analytical view over the safety. This report discusses the applicability of PSA methodology (fault tree analyses, failure modes and effects analyses) in the analysis of programmable automation systems. The problem of how to decompose programmable automation systems for reliability modeling purposes is discussed. In addition to the qualitative analysis and structural reliability modeling issues, the possibility to evaluate failure probabilities of programmable automation systems is considered. One solution to the quantification issue is the use of expert judgements, and the principles to apply expert judgements is discussed in the paper. A framework to apply expert judgements is outlined. Further, the impacts of subjective estimates on the interpretation of PSA results are discussed. (orig.) (13 refs.)

  6. Using Order Tracking Analysis Method to Detect the Angle Faults of Blades on Wind Turbine

    DEFF Research Database (Denmark)

    Li, Pengfei; Hu, Weihao; Liu, Juncheng

    2016-01-01

    The angle faults of blades on wind turbines are usually included in the set angle fault and the pitch angle fault. They are occupied with a high proportion in all wind turbine faults. Compare with the traditional fault detection methods, using order tracking analysis method to detect angle faults...... has many advantages, such as easy implementation and high system reliability. Because of using Power Spectral Density method (PSD) or Fast Fourier Transform (FFT) method cannot get clear fault characteristic frequencies, this kind of faults should be detected by an effective method. This paper...... proposes a novel method of using order tracking analysis to analyze the signal of input aerodynamic torque which is received by hub. After the analyzed process, the fault characteristic frequency could be extracted by the analyzed signals and compared with the signals from normal operating conditions...

  7. Chaos Synchronization Based Novel Real-Time Intelligent Fault Diagnosis for Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Chin-Tsung Hsieh

    2014-01-01

    Full Text Available The traditional solar photovoltaic fault diagnosis system needs two to three sets of sensing elements to capture fault signals as fault features and many fault diagnosis methods cannot be applied with real time. The fault diagnosis method proposed in this study needs only one set of sensing elements to intercept the fault features of the system, which can be real-time-diagnosed by creating the fault data of only one set of sensors. The aforesaid two points reduce the cost and fault diagnosis time. It can improve the construction of the huge database. This study used Matlab to simulate the faults in the solar photovoltaic system. The maximum power point tracker (MPPT is used to keep a stable power supply to the system when the system has faults. The characteristic signal of system fault voltage is captured and recorded, and the dynamic error of the fault voltage signal is extracted by chaos synchronization. Then, the extension engineering is used to implement the fault diagnosis. Finally, the overall fault diagnosis system only needs to capture the voltage signal of the solar photovoltaic system, and the fault type can be diagnosed instantly.

  8. Fault Locating, Prediction and Protection (FLPPS)

    Energy Technology Data Exchange (ETDEWEB)

    Yinger, Robert, J.; Venkata, S., S.; Centeno, Virgilio

    2010-09-30

    One of the main objectives of this DOE-sponsored project was to reduce customer outage time. Fault location, prediction, and protection are the most important aspects of fault management for the reduction of outage time. In the past most of the research and development on power system faults in these areas has focused on transmission systems, and it is not until recently with deregulation and competition that research on power system faults has begun to focus on the unique aspects of distribution systems. This project was planned with three Phases, approximately one year per phase. The first phase of the project involved an assessment of the state-of-the-art in fault location, prediction, and detection as well as the design, lab testing, and field installation of the advanced protection system on the SCE Circuit of the Future located north of San Bernardino, CA. The new feeder automation scheme, with vacuum fault interrupters, will limit the number of customers affected by the fault. Depending on the fault location, the substation breaker might not even trip. Through the use of fast communications (fiber) the fault locations can be determined and the proper fault interrupting switches opened automatically. With knowledge of circuit loadings at the time of the fault, ties to other circuits can be closed automatically to restore all customers except the faulted section. This new automation scheme limits outage time and increases reliability for customers. The second phase of the project involved the selection, modeling, testing and installation of a fault current limiter on the Circuit of the Future. While this project did not pay for the installation and testing of the fault current limiter, it did perform the evaluation of the fault current limiter and its impacts on the protection system of the Circuit of the Future. After investigation of several fault current limiters, the Zenergy superconducting, saturable core fault current limiter was selected for

  9. Automated extraction of DNA from reference samples from various types of biological materials on the Qiagen BioRobot EZ1 Workstation

    DEFF Research Database (Denmark)

    Stangegaard, Michael; Jørgensen, Mads; Hansen, Anders Johannes

    2009-01-01

    We have validated and implemented a protocol for DNA extraction from various types of biological materials using a Qiagen BioRobot EZ1 Workstation. The sample materials included whole blood, blood from deceased, buccal cells on Omni swabs and FTA Cards, blood on FTA Cards and cotton swabs......, and muscle biopsies. The DNA extraction was validated according to EN/ISO 17025 for the STR kits AmpFlSTR« Identifiler« and AmpFlSTR« Yfiler« (Applied Biosystems). Of 298 samples extracted, 11 (4%) did not yield acceptable results. In conclusion, we have demonstrated that extraction of DNA from various types...... of biological material can be performed quickly and without the use of hazardous chemicals, and that the DNA may be successfully STR typed according to the requirements of forensic genetic investigations accredited according to EN/ISO 17025...

  10. Rapid and automated analysis of aflatoxin M1 in milk and dairy products by online solid phase extraction coupled to ultra-high-pressure-liquid-chromatography tandem mass spectrometry.

    Science.gov (United States)

    Campone, Luca; Piccinelli, Anna Lisa; Celano, Rita; Pagano, Imma; Russo, Mariateresa; Rastrelli, Luca

    2016-01-08

    This study reports a fast and automated analytical procedure for the analysis of aflatoxin M1 (AFM1) in milk and dairy products. The method is based on the simultaneous protein precipitation and AFM1 extraction, by salt-induced liquid-liquid extraction (SI-LLE), followed by an online solid-phase extraction (online SPE) coupled to ultra-high-pressure-liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analysis to the automatic pre-concentration, clean up and sensitive and selective determination of AFM1. The main parameters affecting the extraction efficiency and accuracy of the analytical method were studied in detail. In the optimal conditions, acetonitrile and NaCl were used as extraction/denaturant solvent and salting-out agent in SI-LLE, respectively. After centrifugation, the organic phase (acetonitrile) was diluted with water (1:9 v/v) and purified (1mL) by online C18 cartridge coupled with an UHPLC column. Finally, selected reaction monitoring (SRM) acquisition mode was applied to the detection of AFM1. Validation studies were carried out on different dairy products (whole and skimmed cow milk, yogurt, goat milk, and powder infant formula), providing method quantification limits about 25 times lower than AFM1 maximum levels permitted by EU regulation 1881/2006 in milk and dairy products for direct human consumption. Recoveries (86-102%) and repeatability (RSDmilk and dairy products studied. The proposed method improves the performance of AFM1 analysis in milk samples as AFM1 determination is performed with a degree of accuracy higher than the conventional methods. Other advantages are the reduction of sample preparation procedure, time and cost of the analysis, enabling high sample throughput that meet the current concerns of food safety and the public health protection. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. LC-HR-MS/MS standard urine screening approach: Pros and cons of automated on-line extraction by turbulent flow chromatography versus dilute-and-shoot and comparison with established urine precipitation.

    Science.gov (United States)

    Helfer, Andreas G; Michely, Julian A; Weber, Armin A; Meyer, Markus R; Maurer, Hans H

    2017-02-01

    Comprehensive urine screening for drugs and metabolites by LC-HR-MS/MS using Orbitrap technology has been described with precipitation as simple workup. In order to fasten, automate, and/or simplify the workup, on-line extraction by turbulent flow chromatography and a dilute-and-shoot approach were developed and compared. After chromatographic separation within 10min, the Q-Exactive mass spectrometer was run in full scan mode with positive/negative switching and subsequent data dependent acquisition mode. The workup approaches were validated concerning selectivity, recovery, matrix effects, process efficiency, and limits of identification and detection for typical drug representatives and metabolites. The total workup time for on-line extraction was 6min, for the dilution approach 3min. For comparison, the established urine precipitation and evaporation lasted 10min. The validation results were acceptable. The limits for on-line extraction were comparable with those described for precipitation, but lower than for dilution. Thanks to the high sensitivity of the LC-HR-MS/MS system, all three workup approaches were sufficient for comprehensive urine screening and allowed fast, reliable, and reproducible detection of cardiovascular drugs, drugs of abuse, and other CNS acting drugs after common doses. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Uncovering dynamic fault trees

    NARCIS (Netherlands)

    Junges, Sebastian; Guck, Dennis; Katoen, Joost P.; Stoelinga, Mariëlle Ida Antoinette

    Fault tree analysis is a widespread industry standard for assessing system reliability. Standard (static) fault trees model the failure behaviour of systems in dependence of their component failures. To overcome their limited expressive power, common dependability patterns, such as spare management,

  13. Comparison of automated multiplexed bead-based ANA screening assay with ELISA for detecting five common anti-extractable nuclear antigens and anti-dsDNA in systemic rheumatic diseases.

    Science.gov (United States)

    Kim, Yoonjung; Park, Yongjung; Lee, Eun Young; Kim, Hyon-Suk

    2012-01-18

    A newly developed and totally automated Luminex-based assay, the BioPlex™ 2200 system, is able to detect various autoantibodies simultaneously from a single sample. We compared the BioPlex™ 2200 system with ELISA for the detection of six autoantibodies. A total of 127 serum samples from the patients with systemic rheumatic diseases were collected and assayed with the BioPlex™ 2200 system (Bio-Rad, USA) and conventional ELISA (INOVA Diagnostics, USA) for 5 anti-extractable nuclear antigens. Additionally, relative sensitivity of the BioPlex™ 2200 system for detecting anti-dsDNA was evaluated with 79 specimens from SLE patients, which were positive for anti-dsDNA by ELISA. The concordance rates between ELISA and the BioPlex ranged from 88.1% for anti-RNP to 95.2% for anti-Scl-70, and the kappa coefficients between the results by the two assays were from 0.48 to 0.67. Among the 79 anti-dsDNA positive specimens by ELISA, seventy-eight (98.7%) showed positive results for anti-dsDNA by the BioPlex. The BioPlex™ 2200 system showed comparable results with those by conventional ELISA for detecting autoantibodies, and this automated assay could measure multifarious autoantibodies concurrently in a single sample. It could be effectively used in clinical laboratories for screening autoimmune diseases. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Solar system fault detection

    Science.gov (United States)

    Farrington, R.B.; Pruett, J.C. Jr.

    1984-05-14

    A fault detecting apparatus and method are provided for use with an active solar system. The apparatus provides an indication as to whether one or more predetermined faults have occurred in the solar system. The apparatus includes a plurality of sensors, each sensor being used in determining whether a predetermined condition is present. The outputs of the sensors are combined in a pre-established manner in accordance with the kind of predetermined faults to be detected. Indicators communicate with the outputs generated by combining the sensor outputs to give the user of the solar system and the apparatus an indication as to whether a predetermined fault has occurred. Upon detection and indication of any predetermined fault, the user can take appropriate corrective action so that the overall reliability and efficiency of the active solar system are increased.

  15. FAULT DETECTION AND LOCALIZATION IN MOTORCYCLES BASED ON THE CHAIN CODE OF PSEUDOSPECTRA AND ACOUSTIC SIGNALS

    Directory of Open Access Journals (Sweden)

    B. S. Anami

    2013-06-01

    Full Text Available Vehicles produce sound signals with varying temporal and spectral properties under different working conditions. These sounds are indicative of the condition of the engine. Fault diagnosis is a significantly difficult task in geographically remote places where expertise is scarce. Automated fault diagnosis can assist riders to assess the health condition of their vehicles. This paper presents a method for fault detection and location in motorcycles based on the chain code of the pseudospectra and Mel-frequency cepstral coefficient (MFCC features of acoustic signals. The work comprises two stages: fault detection and fault location. The fault detection stage uses the chain code of the pseudospectrum as a feature vector. If the motorcycle is identified as faulty, the MFCCs of the same sample are computed and used as features for fault location. Both stages employ dynamic time warping for the classification of faults. Five types of faults in motorcycles are considered in this work. Observed classification rates are over 90% for the fault detection stage and over 94% for the fault location stage. The work identifies other interesting applications in the development of acoustic fingerprints for fault diagnosis of machinery, tuning of musical instruments, medical diagnosis, etc.

  16. Simultaneous-Fault Diagnosis of Gas Turbine Generator Systems Using a Pairwise-Coupled Probabilistic Classifier

    Directory of Open Access Journals (Sweden)

    Zhixin Yang

    2013-01-01

    Full Text Available A reliable fault diagnostic system for gas turbine generator system (GTGS, which is complicated and inherent with many types of component faults, is essential to avoid the interruption of electricity supply. However, the GTGS diagnosis faces challenges in terms of the existence of simultaneous-fault diagnosis and high cost in acquiring the exponentially increased simultaneous-fault vibration signals for constructing the diagnostic system. This research proposes a new diagnostic framework combining feature extraction, pairwise-coupled probabilistic classifier, and decision threshold optimization. The feature extraction module adopts wavelet packet transform and time-domain statistical features to extract vibration signal features. Kernel principal component analysis is then applied to further reduce the redundant features. The features of single faults in a simultaneous-fault pattern are extracted and then detected using a probabilistic classifier, namely, pairwise-coupled relevance vector machine, which is trained with single-fault patterns only. Therefore, the training dataset of simultaneous-fault patterns is unnecessary. To optimize the decision threshold, this research proposes to use grid search method which can ensure a global solution as compared with traditional computational intelligence techniques. Experimental results show that the proposed framework performs well for both single-fault and simultaneous-fault diagnosis and is superior to the frameworks without feature extraction and pairwise coupling.

  17. PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Jian; Casey, Cameron P.; Zheng, Xueyun; Ibrahim, Yehia M.; Wilkins, Christopher S.; Renslow, Ryan S.; Thomas, Dennis G.; Payne, Samuel H.; Monroe, Matthew E.; Smith, Richard D.; Teeguarden, Justin G.; Baker, Erin S.; Metz, Thomas O.

    2017-05-15

    Motivation: Drift tube ion mobility spectrometry (DTIMS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS coupled with mass spectrometry and compute their associated collisional cross sections (CCS) we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of information necessary to create a reference library containing accu-rate masses, DTIMS arrival times and CCSs for use in high throughput omics analyses. Results: We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were identical to those calculated by hand and within error of those calcu-lated using commercially available instrument vendor software.

  18. AUTOSIM: An automated repetitive software testing tool

    Science.gov (United States)

    Dunham, J. R.; Mcbride, S. E.

    1985-01-01

    AUTOSIM is a software tool which automates the repetitive run testing of software. This tool executes programming tasks previously performed by a programmer with one year of programming experience. Use of the AUTOSIM tool requires a knowledge base containing information about known faults, code fixes, and the fault diagnosis-correction process. AUTOSIM can be considered as an expert system which replaces a low level of programming expertise. Reference information about the design and implementation of the AUTOSIM software test tool provides flowcharts to assist in maintaining the software code and a description of how to use the tool.

  19. Fault-tolerant design

    CERN Document Server

    Dubrova, Elena

    2013-01-01

    This textbook serves as an introduction to fault-tolerance, intended for upper-division undergraduate students, graduate-level students and practicing engineers in need of an overview of the field.  Readers will develop skills in modeling and evaluating fault-tolerant architectures in terms of reliability, availability and safety.  They will gain a thorough understanding of fault tolerant computers, including both the theory of how to design and evaluate them and the practical knowledge of achieving fault-tolerance in electronic, communication and software systems.  Coverage includes fault-tolerance techniques through hardware, software, information and time redundancy.  The content is designed to be highly accessible, including numerous examples and exercises.  Solutions and powerpoint slides are available for instructors.   ·         Provides textbook coverage of the fundamental concepts of fault-tolerance; ·         Describes a variety of basic techniques for achieving fault-toleran...

  20. Fault Management Metrics

    Science.gov (United States)

    Johnson, Stephen B.; Ghoshal, Sudipto; Haste, Deepak; Moore, Craig

    2017-01-01

    This paper describes the theory and considerations in the application of metrics to measure the effectiveness of fault management. Fault management refers here to the operational aspect of system health management, and as such is considered as a meta-control loop that operates to preserve or maximize the system's ability to achieve its goals in the face of current or prospective failure. As a suite of control loops, the metrics to estimate and measure the effectiveness of fault management are similar to those of classical control loops in being divided into two major classes: state estimation, and state control. State estimation metrics can be classified into lower-level subdivisions for detection coverage, detection effectiveness, fault isolation and fault identification (diagnostics), and failure prognosis. State control metrics can be classified into response determination effectiveness and response effectiveness. These metrics are applied to each and every fault management control loop in the system, for each failure to which they apply, and probabilistically summed to determine the effectiveness of these fault management control loops to preserve the relevant system goals that they are intended to protect.

  1. Automated fingerprint identification system

    International Nuclear Information System (INIS)

    Bukhari, U.A.; Sheikh, N.M.; Khan, U.I.; Mahmood, N.; Aslam, M.

    2002-01-01

    In this paper we present selected stages of an automated fingerprint identification system. The software for the system is developed employing algorithm for two-tone conversion, thinning, feature extraction and matching. Keeping FBI standards into account, it has been assured that no details of the image are lost in the comparison process. We have deployed a general parallel thinning algorithm for specialized images like fingerprints and modified the original algorithm after a series of experimentation selecting the one giving the best results. We also proposed an application-based approach for designing automated fingerprint identification systems keeping in view systems requirements. We will show that by using our system, the precision and efficiency of current fingerprint matching techniques are increased. (author)

  2. A probabilistic method to diagnose faults of air handling units

    Science.gov (United States)

    Dey, Debashis

    Air handling unit (AHU) is one of the most extensively used equipment in large commercial buildings. This device is typically customized and lacks quality system integration which can result in hardwire failures and controller errors. Air handling unit Performance Assessment Rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon sensor data and control signals that are commonly available in these systems. Although APAR has many advantages over other methods, for example no training data required and easy to implement commercially, most of the time it is unable to provide the diagnosis of the faults. For instance, a fault on temperature sensor could be fixed bias, drifting bias, inappropriate location, complete failure. Also a fault in mixing box can be return and outdoor damper leak or stuck. In addition, when multiple rules are satisfied the list of faults increases. There is no proper way to have the correct diagnosis for rule based fault detection system. To overcome this limitation we proposed Bayesian Belief Network (BBN) as a diagnostic tool. BBN can be used to simulate diagnostic thinking of FDD experts through a probabilistic way. In this study we developed a new way to detect and diagnose faults in AHU through combining APAR rules and Bayesian Belief network. Bayesian Belief Network is used as a decision support tool for rule based expert system. BBN is highly capable to prioritize faults when multiple rules are satisfied simultaneously. Also it can get information from previous AHU operating conditions and maintenance records to provide proper diagnosis. The proposed model is validated with real time measured data of a campus building at University of Texas at San Antonio (UTSA).The results show that BBN is correctly able to

  3. Automated External Defibrillator

    Science.gov (United States)

    ... To Health Topics / Automated External Defibrillator Automated External Defibrillator Also known as What Is An automated external ... in survival. Training To Use an Automated External Defibrillator Learning how to use an AED and taking ...

  4. Fuzzy classifier for fault diagnosis in analog electronic circuits.

    Science.gov (United States)

    Kumar, Ashwani; Singh, A P

    2013-11-01

    Many studies have presented different approaches for the fault diagnosis with fault models having ± 50% variation in the component values in analog electronic circuits. There is still a need of the approaches which provide the fault diagnosis with the variation in the component value below ± 50%. A new single and multiple fault diagnosis technique for soft faults in analog electronic circuit using fuzzy classifier has been proposed in this paper. This technique uses the simulation before test (SBT) approach by analyzing the frequency response of the analog circuit under faulty and fault free conditions. Three signature parameters peak gain, frequency and phase associated with peak gain, of the frequency response of the analog circuit are observed and extracted such that they give unique values for faulty and fault free configuration of the circuit. The single and double fault models with the component variations from ± 10% to ± 50% are considered. The fuzzy classifier along the classification of faults gives the estimated component value under faulty and faultfree conditions. The proposed method is validated using simulated data and the real time data for a benchmark analog circuit. The comparative analysis is also presented for both the validations. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Analysis of microcontaminants in aqueous samples by fully automated on-line solid-phase extraction-gas chromatography-mass selective detection.

    NARCIS (Netherlands)

    Louter, A.J.H.; van Beekvelt, C.A.; Cid Montanes, P.; Slobodník, J.; Vreuls, J.J.; Brinkman, U.A.T.

    1996-01-01

    The trace-level analysis of unknown organic pollutants in water requires the use of fast and sensitive methods which also provide structural information. In the present study, an on-line technique was used which combines sample preparation by means of solid-phase extraction (SPE) on a small

  6. Fault Analysis in Cryptography

    CERN Document Server

    Joye, Marc

    2012-01-01

    In the 1970s researchers noticed that radioactive particles produced by elements naturally present in packaging material could cause bits to flip in sensitive areas of electronic chips. Research into the effect of cosmic rays on semiconductors, an area of particular interest in the aerospace industry, led to methods of hardening electronic devices designed for harsh environments. Ultimately various mechanisms for fault creation and propagation were discovered, and in particular it was noted that many cryptographic algorithms succumb to so-called fault attacks. Preventing fault attacks without

  7. Fault tolerant control based on active fault diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    2005-01-01

    An active fault diagnosis (AFD) method will be considered in this paper in connection with a Fault Tolerant Control (FTC) architecture based on the YJBK parameterization of all stabilizing controllers. The architecture consists of a fault diagnosis (FD) part and a controller reconfiguration (CR......) part. The FTC architecture can be applied for additive faults, parametric faults, and for system structural changes. Only parametric faults will be considered in this paper. The main focus in this paper is on the use of the new approach of active fault diagnosis in connection with FTC. The active fault...... diagnosis approach is based on including an auxiliary input in the system. A fault signature matrix is introduced in connection with AFD, given as the transfer function from the auxiliary input to the residual output. This can be considered as a generalization of the passive fault diagnosis case, where...

  8. Library Automation.

    Science.gov (United States)

    Husby, Ole

    1990-01-01

    The challenges and potential benefits of automating university libraries are reviewed, with special attention given to cooperative systems. Aspects discussed include database size, the role of the university computer center, storage modes, multi-institutional systems, resource sharing, cooperative system management, networking, and intelligent…

  9. Layered clustering multi-fault diagnosis for hydraulic piston pump

    Science.gov (United States)

    Du, Jun; Wang, Shaoping; Zhang, Haiyan

    2013-04-01

    Efficient diagnosis is very important for improving reliability and performance of aircraft hydraulic piston pump, and it is one of the key technologies in prognostic and health management system. In practice, due to harsh working environment and heavy working loads, multiple faults of an aircraft hydraulic pump may occur simultaneously after long time operations. However, most existing diagnosis methods can only distinguish pump faults that occur individually. Therefore, new method needs to be developed to realize effective diagnosis of simultaneous multiple faults on aircraft hydraulic pump. In this paper, a new method based on the layered clustering algorithm is proposed to diagnose multiple faults of an aircraft hydraulic pump that occur simultaneously. The intensive failure mechanism analyses of the five main types of faults are carried out, and based on these analyses the optimal combination and layout of diagnostic sensors is attained. The three layered diagnosis reasoning engine is designed according to the faults' risk priority number and the characteristics of different fault feature extraction methods. The most serious failures are first distinguished with the individual signal processing. To the desultory faults, i.e., swash plate eccentricity and incremental clearance increases between piston and slipper, the clustering diagnosis algorithm based on the statistical average relative power difference (ARPD) is proposed. By effectively enhancing the fault features of these two faults, the ARPDs calculated from vibration signals are employed to complete the hypothesis testing. The ARPDs of the different faults follow different probability distributions. Compared with the classical fast Fourier transform-based spectrum diagnosis method, the experimental results demonstrate that the proposed algorithm can diagnose the multiple faults, which occur synchronously, with higher precision and reliability.

  10. Ten kilometer vertical Moho offset and shallow velocity contrast along the Denali fault zone from double-difference tomography, receiver functions, and fault zone head waves

    Science.gov (United States)

    Allam, A. A.; Schulte-Pelkum, V.; Ben-Zion, Y.; Tape, C.; Ruppert, N.; Ross, Z. E.

    2017-11-01

    We examine the structure of the Denali fault system in the crust and upper mantle using double-difference tomography, P-wave receiver functions, and analysis (spatial distribution and moveout) of fault zone head waves. The three methods have complementary sensitivity; tomography is sensitive to 3D seismic velocity structure but smooths sharp boundaries, receiver functions are sensitive to (quasi) horizontal interfaces, and fault zone head waves are sensitive to (quasi) vertical interfaces. The results indicate that the Mohorovičić discontinuity is vertically offset by 10 to 15 km along the central 600 km of the Denali fault in the imaged region, with the northern side having shallower Moho depths around 30 km. An automated phase picker algorithm is used to identify 1400 events that generate fault zone head waves only at near-fault stations. At shorter hypocentral distances head waves are observed at stations on the northern side of the fault, while longer propagation distances and deeper events produce head waves on the southern side. These results suggest a reversal of the velocity contrast polarity with depth, which we confirm by computing average 1D velocity models separately north and south of the fault. Using teleseismic events with M ≥ 5.1, we obtain 31,400 P receiver functions and apply common-conversion-point stacking. The results are migrated to depth using the derived 3D tomography model. The imaged interfaces agree with the tomography model, showing a Moho offset along the central Denali fault and also the sub-parallel Hines Creek fault, a suture zone boundary 30 km to the north. To the east, this offset follows the Totschunda fault, which ruptured during the M7.9 2002 earthquake, rather than the Denali fault itself. The combined results suggest that the Denali fault zone separates two distinct crustal blocks, and that the Totschunda and Hines Creeks segments are important components of the fault and Cretaceous-aged suture zone structure.

  11. Automated alkaline-induced salting-out homogeneous liquid-liquid extraction coupled with in-line organic-phase detection by an optical probe for the determination of diclofenac.

    Science.gov (United States)

    Pochivalov, Aleksei; Vakh, Christina; Andruch, Vasil; Moskvin, Leonid; Bulatov, Andrey

    2017-07-01

    A fully automated alkaline-induced salting-out homogeneous liquid-liquid extraction (AI-SHLLE) procedure coupled with in-line organic-phase detection by an optical probe has been suggested. Diclofenac was used as a proof-of-concept analyte. The method is based on the oxidation of diclofenac with potassium ferricyanide in an alkaline medium followed by separation of the acetonitrile phase from the homogeneous sample solution and simultaneous extraction of the derivative. Sodium hydroxide serves as both the alkaline agent for the derivatization of diclofenac and as the salting-out agent for the acetonitrile-rich phase formation. Absorbance of the derivative in the acetonitrile-rich phase was measured in-line using an optical probe. The calibration graph was linear over the range of 2.5-60µmolL -1 with the regression coefficient equal to 0.9997. The LOD calculated from the calibration plot based on 3σ was 0.8µmolL -1 . The sample throughput was 7 samplesh -1 . The method was applied for the determination of diclofenac in spiked saliva samples and pharmaceutical preparations and the results were compared with those obtained by the reference method. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Automated and sensitive determination of four anabolic androgenic steroids in urine by online turbulent flow solid-phase extraction coupled with liquid chromatography-tandem mass spectrometry: a novel approach for clinical monitoring and doping control.

    Science.gov (United States)

    Guo, Feng; Shao, Jing; Liu, Qian; Shi, Jian-Bo; Jiang, Gui-Bin

    2014-07-01

    A novel method for automated and sensitive analysis of testosterone, androstenedione, methyltestosterone and methenolone in urine samples by online turbulent flow solid-phase extraction coupled with high performance liquid chromatography-tandem mass spectrometry was developed. The optimization and validation of the method were discussed in detail. The Turboflow C18-P SPE column showed the best extraction efficiency for all the analytes. Nanogram per liter (ng/L) level of AAS could be determined directly and the limits of quantification (LOQs) were 0.01 ng/mL, which were much lower than normally concerned concentrations for these typical anabolic androgenic steroids (AAS) (0.1 ng/mL). The linearity range was from the LOQ to 100 ng/mL for each compound, with the coefficients of determination (r(2)) ranging from 0.9990 to 0.9999. The intraday and interday relative standard deviations (RSDs) ranged from 1.1% to 14.5% (n=5). The proposed method was successfully applied to the analysis of urine samples collected from 24 male athletes and 15 patients of prostate cancer. The proposed method provides an alternative practical way to rapidly determine AAS in urine samples, especially for clinical monitoring and doping control. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Automated extraction of lysergic acid diethylamide (LSD) and N-demethyl-LSD from blood, serum, plasma, and urine samples using the Zymark RapidTrace with LC/MS/MS confirmation.

    Science.gov (United States)

    de Kanel, J; Vickery, W E; Waldner, B; Monahan, R M; Diamond, F X

    1998-05-01

    A forensic procedure for the quantitative confirmation of lysergic acid diethylamide (LSD) and the qualitative confirmation of its metabolite, N-demethyl-LSD, in blood, serum, plasma, and urine samples is presented. The Zymark RapidTrace was used to perform fully automated solid-phase extractions of all specimen types. After extract evaporation, confirmations were performed using liquid chromatography (LC) followed by positive electrospray ionization (ESI+) mass spectrometry/mass spectrometry (MS/MS) without derivatization. Quantitation of LSD was accomplished using LSD-d3 as an internal standard. The limit of quantitation (LOQ) for LSD was 0.05 ng/mL. The limit of detection (LOD) for both LSD and N-demethyl-LSD was 0.025 ng/mL. The recovery of LSD was greater than 95% at levels of 0.1 ng/mL and 2.0 ng/mL. For LSD at 1.0 ng/mL, the within-run and between-run (different day) relative standard deviation (RSD) was 2.2% and 4.4%, respectively.

  14. Quaternary Fault Lines

    Data.gov (United States)

    Department of Homeland Security — This data set contains locations and information on faults and associated folds in the United States that are believed to be sources of M>6 earthquakes during the...

  15. Development of Asset Fault Signatures for Prognostic and Health Management in the Nuclear Industry

    Energy Technology Data Exchange (ETDEWEB)

    Vivek Agarwal; Nancy J. Lybeck; Randall Bickford; Richard Rusaw

    2014-06-01

    Proactive online monitoring in the nuclear industry is being explored using the Electric Power Research Institute’s Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. The FW-PHM Suite is a set of web-based diagnostic and prognostic tools and databases that serves as an integrated health monitoring architecture. The FW-PHM Suite has four main modules: Diagnostic Advisor, Asset Fault Signature (AFS) Database, Remaining Useful Life Advisor, and Remaining Useful Life Database. This paper focuses on development of asset fault signatures to assess the health status of generator step-up generators and emergency diesel generators in nuclear power plants. Asset fault signatures describe the distinctive features based on technical examinations that can be used to detect a specific fault type. At the most basic level, fault signatures are comprised of an asset type, a fault type, and a set of one or more fault features (symptoms) that are indicative of the specified fault. The AFS Database is populated with asset fault signatures via a content development exercise that is based on the results of intensive technical research and on the knowledge and experience of technical experts. The developed fault signatures capture this knowledge and implement it in a standardized approach, thereby streamlining the diagnostic and prognostic process. This will support the automation of proactive online monitoring techniques in nuclear power plants to diagnose incipient faults, perform proactive maintenance, and estimate the remaining useful life of assets.

  16. An Intelligent Harmonic Synthesis Technique for Air-Gap Eccentricity Fault Diagnosis in Induction Motors

    Science.gov (United States)

    Li, De Z.; Wang, Wilson; Ismail, Fathy

    2017-11-01

    Induction motors (IMs) are commonly used in various industrial applications. To improve energy consumption efficiency, a reliable IM health condition monitoring system is very useful to detect IM fault at its earliest stage to prevent operation degradation, and malfunction of IMs. An intelligent harmonic synthesis technique is proposed in this work to conduct incipient air-gap eccentricity fault detection in IMs. The fault harmonic series are synthesized to enhance fault features. Fault related local spectra are processed to derive fault indicators for IM air-gap eccentricity diagnosis. The effectiveness of the proposed harmonic synthesis technique is examined experimentally by IMs with static air-gap eccentricity and dynamic air-gap eccentricity states under different load conditions. Test results show that the developed harmonic synthesis technique can extract fault features effectively for initial IM air-gap eccentricity fault detection.

  17. An Improved Wavelet‐Based Multivariable Fault Detection Scheme

    KAUST Repository

    Harrou, Fouzi

    2017-07-06

    Data observed from environmental and engineering processes are usually noisy and correlated in time, which makes the fault detection more difficult as the presence of noise degrades fault detection quality. Multiscale representation of data using wavelets is a powerful feature extraction tool that is well suited to denoising and decorrelating time series data. In this chapter, we combine the advantages of multiscale partial least squares (MSPLSs) modeling with those of the univariate EWMA (exponentially weighted moving average) monitoring chart, which results in an improved fault detection system, especially for detecting small faults in highly correlated, multivariate data. Toward this end, we applied EWMA chart to the output residuals obtained from MSPLS model. It is shown through simulated distillation column data the significant improvement in fault detection can be obtained by using the proposed methods as compared to the use of the conventional partial least square (PLS)‐based Q and EWMA methods and MSPLS‐based Q method.

  18. Faults Diagnosis for Vibration Signal Based on HMM

    Directory of Open Access Journals (Sweden)

    Shao Qiang

    2014-02-01

    Full Text Available Faults behaviors of automotive engine in running-up stage are shown a multidimensional pattern that evolves as a function of time (called dynamic patterns. It is necessary to identify the type of fault during early running stages of automotive engine for the selection of appropriate operator actions to prevent a more severe situation. In this situation, the Faults diagnosis method based on continuous HMM is proposed. Feature vectors of main FFT spectrum component are extracted from vibration signals and looked up as observation vectors of HMM. Several HMMs which substitute the types of faults in automotive engine vibration system are modeled. Decision-making for faults classification is performed. The results of experiment are shown the proposed method is executable and effective.

  19. Automatic identification of otologic drilling faults: a preliminary report.

    Science.gov (United States)

    Shen, Peng; Feng, Guodong; Cao, Tianyang; Gao, Zhiqiang; Li, Xisheng

    2009-09-01

    A preliminary study was carried out to identify parameters to characterize drilling faults when using an otologic drill under various operating conditions. An otologic drill was modified by the addition of four sensors. Under consistent conditions, the drill was used to simulate three important types of drilling faults and the captured data were analysed to extract characteristic signals. A multisensor information fusion system was designed to fuse the signals and automatically identify the faults. When identifying drilling faults, there was a high degree of repeatability and regularity, with an average recognition rate of >70%. This study shows that the variables measured change in a fashion that allows the identification of particular drilling faults, and that it is feasible to use these data to provide rapid feedback for a control system. Further experiments are being undertaken to implement such a system.

  20. Rapid and automated on-line solid phase extraction HPLC-MS/MS with peak focusing for the determination of ochratoxin A in wine samples.

    Science.gov (United States)

    Campone, Luca; Piccinelli, Anna Lisa; Celano, Rita; Pagano, Imma; Russo, Mariateresa; Rastrelli, Luca

    2018-04-01

    This study reports a fast and automated analytical procedure based on an on-line SPE-HPLC-MS/MS method for the automatic pre-concentration, clean up and sensitive determination of OTA in wine. The amount of OTA contained in 100μL of sample (pH≅5.5) was retained and concentrated on an Oasis MAX SPE cartridge. After a washing step to remove matrix interferents, the analyte was eluted in back-flush mode and the eluent from the SPE column was diluted through a mixing Tee, using an aqueous solution before the chromatographic separation achieved on a monolithic column. The developed method has been validated according to EU regulation N. 519/2014 and applied for the analysis of 41 red and 17 white wines. The developed method features minimal sample handling, low solvent consumption, high sample throughput, low analysis cost and provides an accurate and highly selective results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Detecting Faults By Use Of Hidden Markov Models

    Science.gov (United States)

    Smyth, Padhraic J.

    1995-01-01

    Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).

  2. A route generator concept for aircraft onboard fault monitoring

    Science.gov (United States)

    Palmer, M. T.; Abbott, K. H.

    1984-01-01

    Because of the increasingly complex environments in which the flight crews of commercial aviation aircraft must operate, a research effort is currently underway at NASA Langley Research Center to investigate the potential benefits of intelligent cockpit aids, and to establish guidelines for the application of artificial intelligence techniques to advanced flight management concepts. The segment of this research area that concentrates on automated fault monitoring and diagnosis requires that a reference frame exist, against which the current state of the aircraft may be compared to determine the existence of a fault. This paper describes a computer program which generates the position of that reference frame that specifies the horizontal flight route.

  3. Fault Length Vs Fault Displacement Evaluation In The Case Of Cerro Prieto Pull-Apart Basin (Baja California, Mexico) Subsidence

    Science.gov (United States)

    Glowacka, E.; Sarychikhina, O.; Nava Pichardo, F. A.; Farfan, F.; Garcia Arthur, M. A.; Orozco, L.; Brassea, J.

    2013-05-01

    The Cerro Prieto pull-apart basin is located in the southern part of San Andreas Fault system, and is characterized by high seismicity, recent volcanism, tectonic deformation and hydrothermal activity (Lomnitz et al, 1970; Elders et al., 1984; Suárez-Vidal et al., 2008). Since the Cerro Prieto geothermal field production started, in 1973, significant subsidence increase was observed (Glowacka and Nava, 1996, Glowacka et al., 1999), and a relation between fluid extraction rate and subsidence rate has been suggested (op. cit.). Analysis of existing deformation data (Glowacka et al., 1999, 2005, Sarychikhina 2011) points to the fact that, although the extraction changes influence the subsidence rate, the tectonic faults control the spatial extent of the observed subsidence. Tectonic faults act as water barriers in the direction perpendicular to the fault, and/or separate regions with different compaction, and as effect the significant part of the subsidence is released as vertical displacement on the ground surface along fault rupture. These faults ruptures cause damages to roads and irrigation canals and water leakage. Since 1996, a network of geotechnical instruments has operated in the Mexicali Valley, for continuous recording of deformation phenomena. To date, the network (REDECVAM: Mexicali Valley Crustal Strain Measurement Array) includes two crackmeters and eight tiltmeters installed on, or very close to, the main faults; all instruments have sampling intervals in the 1 to 20 minutes range. Additionally, there are benchmarks for measuring vertical fault displacements for which readings are recorded every 3 months. Since the crackmeter measures vertical displacement on the fault at one place only, the question appears: can we use the crackmeter data to evaluate how long is the lenth of the fractured fault, and how quickly it grows, so we can know where we can expect fractures in the canals or roads? We used the Wells and Coppersmith (1994) relations between

  4. Fault morphology of the lyo Fault, the Median Tectonic Line Active Fault System

    OpenAIRE

    後藤, 秀昭

    1996-01-01

    In this paper, we investigated the various fault features of the lyo fault and depicted fault lines or detailed topographic map. The results of this paper are summarized as follows; 1) Distinct evidence of the right-lateral movement is continuously discernible along the lyo fault. 2) Active fault traces are remarkably linear suggesting that the angle of fault plane is high. 3) The lyo fault can be divided into four segments by jogs between left-stepping traces. 4) The mean slip rate is 1.3 ~ ...

  5. Automated solid-phase extraction-liquid chromatography-tandem mass spectrometry analysis of 6-acetylmorphine in human urine specimens: application for a high-throughput urine analysis laboratory.

    Science.gov (United States)

    Robandt, P V; Bui, H M; Scancella, J M; Klette, K L

    2010-10-01

    An automated solid-phase extraction-liquid chromatography- tandem mass spectrometry (SPE-LC-MS-MS) method using the Spark Holland Symbiosis Pharma SPE-LC coupled to a Waters Quattro Micro MS-MS was developed for the analysis of 6-acetylmorphine (6-AM) in human urine specimens. The method was linear (R² = 0.9983) to 100 ng/mL, with no carryover at 200 ng/mL. Limits of quantification and detection were found to be 2 ng/mL. Interrun precision calculated as percent coefficient of variation (%CV) and evaluated by analyzing five specimens at 10 ng/mL over nine batches (n = 45) was 3.6%. Intrarun precision evaluated from 0 to 100 ng/mL ranged from 1.0 to 4.4%CV. Other opioids (codeine, morphine, oxycodone, oxymorphone, hydromorphone, hydrocodone, and norcodeine) did not interfere in the detection, quantification, or chromatography of 6-AM or the deuterated internal standard. The quantified values for 41 authentic human urine specimens previously found to contain 6-AM by a validated gas chromatography (GC)-MS method were compared to those obtained by the SPE-LC-MS-MS method. The SPE-LC-MS-MS procedure eliminates the human factors of specimen handling, extraction, and derivatization, thereby reducing labor costs and rework resulting from human error or technique issues. The time required for extraction and analysis was reduced by approximately 50% when compared to a validated 6-AM procedure using manual SPE and GC-MS analysis.

  6. Feature Extraction for Bearing Prognostics and Health Management (PHM) - A Survey (Preprint)

    National Research Council Canada - National Science Library

    Yan, Weizhong; Qiu, Hai; Iyer, Naresh

    2008-01-01

    Feature extraction in bearing PHM involves extracting characteristic signatures from the original sensor measurements, which are sensitive to bearing conditions and thus most useful in determining bearing faults...

  7. A Systematic Methodology for Gearbox Health Assessment and Fault Classification

    Directory of Open Access Journals (Sweden)

    Jay Lee

    2011-01-01

    Full Text Available A systematic methodology for gearbox health assessment and fault classification is developed and evaluated for 560 data sets of gearbox vibration data provided by the Prognostics and Health Management Society for the 2009 data challenge competition. A comprehensive set of signal processing and feature extraction methods are used to extract over 200 features, including features extracted from the raw time signal, time synchronous signal, wavelet decomposition signal, frequency domain spectrum, envelope spectrum, among others. A regime segmentation approach using the tachometer signal, a spectrum similarity metric, and gear mesh frequency peak information are used to segment the data by gear type, input shaft speed, and braking torque load. A health assessment method that finds the minimum feature vector sum in each regime is used to classify and find the 80 baseline healthy data sets. A fault diagnosis method based on a distance calculation from normal along with specific features correlated to different fault signatures is used to diagnosis specific faults. The fault diagnosis method is evaluated for the diagnosis of a gear tooth breakage, input shaft imbalance, bent shaft, bearing inner race defect, and bad key, and the method could be further extended for other faults as long as a set of features can be correlated with a known fault signature. Future work looks to further refine the distance calculation algorithm for fault diagnosis, as well as further evaluate other signal processing method such as the empirical mode decomposition to see if an improved set of features can be used to improve the fault diagnosis accuracy.

  8. A semi-automated magnetic capture probe based DNA extraction and real-time PCR method applied in the Swedish surveillance of Echinococcus multilocularis in red fox (Vulpes vulpes) faecal samples.

    Science.gov (United States)

    Isaksson, Mats; Hagström, Åsa; Armua-Fernandez, Maria Teresa; Wahlström, Helene; Ågren, Erik Olof; Miller, Andrea; Holmberg, Anders; Lukacs, Morten; Casulli, Adriano; Deplazes, Peter; Juremalm, Mikael

    2014-12-19

    Following the first finding of Echinococcus multilocularis in Sweden in 2011, 2985 red foxes (Vulpes vulpes) were analysed by the segmental sedimentation and counting technique. This is a labour intensive method and requires handling of the whole carcass of the fox, resulting in a costly analysis. In an effort to reduce the cost of labour and sample handling, an alternative method has been developed. The method is sensitive and partially automated for detection of E. multilocularis in faecal samples. The method has been used in the Swedish E. multilocularis monitoring program for 2012-2013 on more than 2000 faecal samples. We describe a new semi-automated magnetic capture probe DNA extraction method and real time hydrolysis probe polymerase chain reaction assay (MC-PCR) for the detection of E. multilocularis DNA in faecal samples from red fox. The diagnostic sensitivity was determined by validating the new method against the sedimentation and counting technique in fox samples collected in Switzerland where E. multilocularis is highly endemic. Of 177 foxes analysed by the sedimentation and counting technique, E. multilocularis was detected in 93 animals. Eighty-two (88%, 95% C.I 79.8-93.9) of these were positive in the MC-PCR. In foxes with more than 100 worms, the MC-PCR was positive in 44 out of 46 (95.7%) cases. The two MC-PCR negative samples originated from foxes with only immature E. multilocularis worms. In foxes with 100 worms or less, (n = 47), 38 (80.9%) were positive in the MC-PCR. The diagnostic specificity of the MC-PCR was evaluated using fox scats collected within the Swedish screening. Of 2158 samples analysed, two were positive. This implies that the specificity is at least 99.9% (C.I. = 99.7-100). The MC-PCR proved to have a high sensitivity and a very high specificity. The test is partially automated but also possible to perform manually if desired. The test is well suited for nationwide E. multilocularis surveillance programs where sampling

  9. A seismic fault recognition method based on ant colony optimization

    Science.gov (United States)

    Chen, Lei; Xiao, Chuangbai; Li, Xueliang; Wang, Zhenli; Huo, Shoudong

    2018-05-01

    Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results.

  10. The Development of an Automated Clean-up for Fat Extracts in the Routine Analysis of Organochlorine Compounds in Fish Meat

    Directory of Open Access Journals (Sweden)

    Ana Andreea CIOCA

    2017-05-01

    Full Text Available The present work describes the development of a new, automatic High Performance Liquid Chromatography (HPLC Clean-up step, in the methodology of sample preparation and multi-residue determination of organochlorine compounds (OCs in fish meat. 24 OCs were taken into study. In addition 7 Polychlorinated Biphenyls (PCBs, 7 chlorobenzene compounds and one 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD were investigated. The HPLC conditions were established in accordance with the validated traditional Clean-up step of the laboratory. The technique was applied on a dilution of analytes of interest in order to establish the period of time in which the compounds are eluted. Another set of experiments involved fish oil, in order to identify and separate the fat fraction from the analytes. To confirm the findings of the experiments mentioned above, extracts of fish samples obtained after Accelerated Solvent Extraction (ASE were examined. The samples were spiked with the analytes of interest before HPLC clean-up step and quantified through Gas Chromatography coupled with tandem Mass Spectrometry (GC-MS/MS. A HPLC clean-up technique lasting 38 minutes/sample was developed. The method is not suitable for OCs such as Endosulfansulfat and Endrine Ketone due to the very low recovery results.Â

  11. Collection and analysis of existing information on applicability of investigation methods for estimation of beginning age of faulting in present faulting pattern

    International Nuclear Information System (INIS)

    Doke, Ryosuke; Yasue, Ken-ichi; Tanikawa, Shin-ichi; Nakayasu, Akio; Niizato, Tadafumi; Tanaka, Takenobu; Aoki, Michinori; Sekiya, Ayako

    2011-12-01

    In the field of R and D programs of a geological disposal of high level radioactive waste, it is great importance to develop a set of investigation and analysis techniques for the assessment of long-term geosphere stability over a geological time, which means that any changes of geological environment will not significantly impact on the long-term safety of a geological disposal system. In Japanese archipelago, crustal movements are so active that uplift and subsidence are remarkable in recent several hundreds of thousands of years. Therefore, it is necessary to assess the long-term geosphere stability taking into account a topographic change caused by crustal movements. One of the factors for the topographic change is the movement of an active fault, which is a geological process to release a strain accumulated by plate motion. A beginning age of the faulting in the present faulting pattern suggests the beginning age of neotectonic activities around the active fault, and also provides basic information to identifying the stage of a geomorphic development of mountains. Therefore, the age of faulting in the present faulting pattern is important information to estimate a topographic change in the future on the mountain regions of Japan. In this study, existing information related to methods for the estimation of the beginning age of the faulting in the present faulting pattern on the active fault were collected and reviewed. A principle of method, noticing points and technical know-hows in the application of the methods, data uncertainty, and so on were extracted from the existing information. Based on these extracted information, task-flows indicating working process on the estimation of the beginning age for the faulting of the active fault were illustrated on each method. Additionally, the distribution map of the beginning age with accuracy of faulting in the present faulting pattern on the active fault was illustrated. (author)

  12. Active Fault Isolation in MIMO Systems

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2014-01-01

    Active fault isolation of parametric faults in closed-loop MIMO system s are considered in this paper. The fault isolation consists of two steps. T he first step is group- wise fault isolation. Here, a group of faults is isolated from other pos sible faults in the system. The group-wise fault...... isolation is based directly on the input/output s ignals applied for the fault detection. It is guaranteed that the fault group includes the fault that had occurred in the system. The second step is individual fault isolation in the fault group . Both types of isolation are obtained by applying dedicated...

  13. Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis.

    Science.gov (United States)

    Deng, Xiaogang; Tian, Xuemin; Chen, Sheng; Harris, Chris J

    2018-03-01

    Many industrial processes contain both linear and nonlinear parts, and kernel principal component analysis (KPCA), widely used in nonlinear process monitoring, may not offer the most effective means for dealing with these nonlinear processes. This paper proposes a new hybrid linear-nonlinear statistical modeling approach for nonlinear process monitoring by closely integrating linear principal component analysis (PCA) and nonlinear KPCA using a serial model structure, which we refer to as serial PCA (SPCA). Specifically, PCA is first applied to extract PCs as linear features, and to decompose the data into the PC subspace and residual subspace (RS). Then, KPCA is performed in the RS to extract the nonlinear PCs as nonlinear features. Two monitoring statistics are constructed for fault detection, based on both the linear and nonlinear features extracted by the proposed SPCA. To effectively perform fault identification after a fault is detected, an SPCA similarity factor method is built for fault recognition, which fuses both the linear and nonlinear features. Unlike PCA and KPCA, the proposed method takes into account both linear and nonlinear PCs simultaneously, and therefore, it can better exploit the underlying process's structure to enhance fault diagnosis performance. Two case studies involving a simulated nonlinear process and the benchmark Tennessee Eastman process demonstrate that the proposed SPCA approach is more effective than the existing state-of-the-art approach based on KPCA alone, in terms of nonlinear process fault detection and identification.

  14. Faults in Linux

    DEFF Research Database (Denmark)

    Palix, Nicolas Jean-Michel; Thomas, Gaël; Saha, Suman

    2011-01-01

    In 2001, Chou et al. published a study of faults found by applying a static analyzer to Linux versions 1.0 through 2.4.1. A major result of their work was that the drivers directory contained up to 7 times more of certain kinds of faults than other directories. This result inspired a number...... a major problem? To answer these questions, we have transported the experiments of Chou et al. to Linux versions 2.6.0 to 2.6.33, released between late 2003 and early 2010. We find that Linux has more than doubled in size during this period, but that the number of faults per line of code has been...... decreasing. And, even though drivers still accounts for a large part of the kernel code and contains the most faults, its fault rate is now below that of other directories, such as arch (HAL) and fs (file systems). These results can guide further development and research efforts. To enable others...

  15. Fault location on power networks

    CERN Document Server

    Saha, Murari Mohan

    2009-01-01

    Fault Location on Power Lines enables readers to pinpoint the location of a fault on power lines following a disturbance. The nine chapters are organised according to the design of different locators. The authors do not simply refer the reader to manufacturers' documentation, but instead have compiled detailed information to allow for in-depth comparison. Fault Location on Power Lines describes basic algorithms used in fault locators, focusing on fault location on overhead transmission lines, but also covering fault location in distribution networks. An application of artificial intelligence i

  16. A System for Fault Management and Fault Consequences Analysis for NASA's Deep Space Habitat

    Science.gov (United States)

    Colombano, Silvano; Spirkovska, Liljana; Baskaran, Vijaykumar; Aaseng, Gordon; McCann, Robert S.; Ossenfort, John; Smith, Irene; Iverson, David L.; Schwabacher, Mark

    2013-01-01

    NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy

  17. Tolerance towards sensor faults: An application to a flexible arm manipulator

    Directory of Open Access Journals (Sweden)

    Chee Pin Tan

    2008-11-01

    Full Text Available As more engineering operations become automatic, the need for robustness towards faults increases. Hence, a fault tolerant control (FTC scheme is a valuable asset. This paper presents a robust sensor fault FTC scheme implemented on a flexible arm manipulator, which has many applications in automation. Sensor faults affect the system's performance in the closed loop when the faulty sensor readings are used to generate the control input. In this paper, the non-faulty sensors are used to reconstruct the faults on the potentially faulty sensors. The reconstruction is subtracted from the faulty sensors to form a compensated `virtual sensor' and this signal (instead of the normally used faulty sensor output is then used to generate the control input. A design method is also presented in which the FTC scheme is made insensitive to any system uncertainties. Two fault conditions are tested; total failure and incipient faults. Then the scheme robustness is tested by implementing the flexible joint's FTC scheme on a flexible link, which has different parameters. Excellent results have been obtained for both cases (joint and link; the FTC scheme caused the system performance is almost identical to the fault-free scenario, whilst providing an indication that a fault is present, even for simultaneous faults.

  18. Tolerance Towards Sensor Faults: An Application to a Flexible Arm Manipulator

    Directory of Open Access Journals (Sweden)

    Chee Pin Tan

    2006-12-01

    Full Text Available As more engineering operations become automatic, the need for robustness towards faults increases. Hence, a fault tolerant control (FTC scheme is a valuable asset. This paper presents a robust sensor fault FTC scheme implemented on a flexible arm manipulator, which has many applications in automation. Sensor faults affect the system's performance in the closed loop when the faulty sensor readings are used to generate the control input. In this paper, the non-faulty sensors are used to reconstruct the faults on the potentially faulty sensors. The reconstruction is subtracted from the faulty sensors to form a compensated ‘virtual sensor’ and this signal (instead of the normally used faulty sensor output is then used to generate the control input. A design method is also presented in which the FTC scheme is made insensitive to any system uncertainties. Two fault conditions are tested; total failure and incipient faults. Then the scheme robustness is tested by implementing the flexible joint's FTC scheme on a flexible link, which has different parameters. Excellent results have been obtained for both cases (joint and link; the FTC scheme caused the system performance is almost identical to the fault-free scenario, whilst providing an indication that a fault is present, even for simultaneous faults.

  19. Wind turbine fault detection and fault tolerant control

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Johnson, Kathryn

    2013-01-01

    In this updated edition of a previous wind turbine fault detection and fault tolerant control challenge, we present a more sophisticated wind turbine model and updated fault scenarios to enhance the realism of the challenge and therefore the value of the solutions. This paper describes...... the challenge model and the requirements for challenge participants. In addition, it motivates many of the faults by citing publications that give field data from wind turbine control tests....

  20. Sub-module Short Circuit Fault Diagnosis in Modular Multilevel Converter Based on Wavelet Transform and Adaptive Neuro Fuzzy Inference System

    DEFF Research Database (Denmark)

    Liu, Hui; Loh, Poh Chiang; Blaabjerg, Frede

    2015-01-01

    by employing wavelet transform under different fault conditions. Then the fuzzy logic rules are automatically trained based on the fuzzified fault features to diagnose the different faults. Neither additional sensor nor the capacitor voltages are needed in the proposed method. The high accuracy, good...... for continuous operation and post-fault maintenance. In this article, a fault diagnosis technique is proposed for the short circuit fault in a modular multi-level converter sub-module using the wavelet transform and adaptive neuro fuzzy inference system. The fault features are extracted from output phase voltage...

  1. Fault Tolerant Computer Architecture

    CERN Document Server

    Sorin, Daniel

    2009-01-01

    For many years, most computer architects have pursued one primary goal: performance. Architects have translated the ever-increasing abundance of ever-faster transistors provided by Moore's law into remarkable increases in performance. Recently, however, the bounty provided by Moore's law has been accompanied by several challenges that have arisen as devices have become smaller, including a decrease in dependability due to physical faults. In this book, we focus on the dependability challenge and the fault tolerance solutions that architects are developing to overcome it. The two main purposes

  2. Computer hardware fault administration

    Science.gov (United States)

    Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

    2010-09-14

    Computer hardware fault administration carried out in a parallel computer, where the parallel computer includes a plurality of compute nodes. The compute nodes are coupled for data communications by at least two independent data communications networks, where each data communications network includes data communications links connected to the compute nodes. Typical embodiments carry out hardware fault administration by identifying a location of a defective link in the first data communications network of the parallel computer and routing communications data around the defective link through the second data communications network of the parallel computer.

  3. High-resolution twin-ion metabolite extraction (HiTIME) mass spectrometry: nontargeted detection of unknown drug metabolites by isotope labeling, liquid chromatography mass spectrometry, and automated high-performance computing.

    Science.gov (United States)

    Leeming, Michael G; Isaac, Andrew P; Pope, Bernard J; Cranswick, Noel; Wright, Christine E; Ziogas, James; O'Hair, Richard A J; Donald, William A

    2015-04-21

    The metabolic fate of a compound can often determine the success of a new drug lead. Thus, significant effort is directed toward identifying the metabolites formed from a given molecule. Here, an automated and nontargeted procedure is introduced for detecting drug metabolites without authentic metabolite standards via the use of stable isotope labeling, liquid chromatography mass spectrometry (LC/MS), and high-performance computing. LC/MS of blood plasma extracts from rats that were administered a 1:1 mixture of acetaminophen (APAP) and (13)C6-APAP resulted in mass spectra that contained "twin" ions for drug metabolites that were not detected in control spectra (i.e., no APAP administered). Because of the development of a program (high-resolution twin-ion metabolite extraction; HiTIME) that can identify twin-ions in high-resolution mass spectra without centroiding (i.e., reduction of mass spectral peaks to single data points), 9 doublets corresponding to APAP metabolites were identified. This is nearly twice that obtained by use of existing programs that make use of centroiding to reduce computational cost under these conditions with a quadrupole time-of-flight mass spectrometer. By a manual search for all reported APAP metabolite ions, no additional twin-ion signals were assigned. These data indicate that all the major metabolites of APAP and multiple low-abundance metabolites (e.g., acetaminophen hydroxy- and methoxysulfate) that are rarely reported were detected. This methodology can be used to detect drug metabolites without prior knowledge of their identity. HiTIME is freely available from https://github.com/bjpop/HiTIME .

  4. A high-throughput, fully automated liquid/liquid extraction liquid chromatography/mass spectrometry method for the quantitation of a new investigational drug ABT-869 and its metabolite A-849529 in human plasma samples.

    Science.gov (United States)

    Rodila, Ramona C; Kim, Joseph C; Ji, Qin C; El-Shourbagy, Tawakol A

    2006-01-01

    ABT-869 is a novel ATP-competitive inhibitor for all the vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF) receptor tyrosine kinases (RTKs). It is one of the oncology drugs in development at Abbott Laboratories and has great potential for enhanced anti-tumor efficacy as well as activity in a broad range of human cancers. We report here an accurate, precise and rugged liquid chromatography/mass spectrometry (LC/MS/MS) assay for the quantitative measurement of ABT-869 and its acid metabolite A-849529. A fully automated 96-well liquid/liquid extraction method was achieved utilizing a Hamilton liquid handler. The only manual intervention required prior to LC/MS/MS injection is to transfer the 96-well plate to a drying rack to dry the extracts then transfer the plate back to the Hamilton for robotic reconstitution. The linear dynamic ranges were from 1.1 to 598.8 ng/mL for ABT-869 and from 1.1 to 605.8 ng/mL for A-849529. The coefficient of determination (r2) for all analytes was greater than 0.9995. For the drug ABT-869, the intra-assay coefficient of variance (CV) was between 0.4% and 3.7% and the inter-assay CV was between 0.9% and 2.8%. The inter-assay mean accuracy, expressed as percent of theoretical, was between 96.8% and 102.2%. For the metabolite A-849529, the intra-assay CV was between 0.5% and 5.1% and the inter-assay CV was between 0.8% and 4.9%. The inter-assay mean accuracy, expressed as percent of theoretical, was between 96.9% and 100.6%. Copyright 2006 John Wiley & Sons, Ltd.

  5. Quantification of the anti-leukemia drug STI571 (Gleevec) and its metabolite (CGP 74588) in monkey plasma using a semi-automated solid phase extraction procedure and liquid chromatography-tandem mass spectrometry.

    Science.gov (United States)

    Bakhtiar, R; Khemani, L; Hayes, M; Bedman, T; Tse, F

    2002-06-15

    Signal Transduction Inhibitor 571 (STI571, formerly known as CGP 57148B) or Gleevec received fast track approval by the US Food and Drug Administration (FDA) for treatment of chronic myeloid leukemia (CML). STI571 (Gleevec) is a revolutionary and promising new oral therapy for CML, which functions at the molecular level with high specificity. The dramatic improvement in efficacy compared with existing treatments prompted an equally profound increase in the pace of development of Gleevec. The duration from first dose in man to completion of the New Drug Application (NDA) filing was less than 3 years. In addition, recently, FDA approved Gleevec for the treatment of gastrointestinal stromal tumor (GIST). In order to support all toxicokinetic (TK) studies with sufficient speed to meet various target dates, a semi-automated procedure using solid phase extraction (SPE) was developed and validated. A Packard Multi-Probe I and a SPE step in a 96-well plate format were utilized. A 3M Empore octyl (C(8))-standard density 96-well plate was used for plasma sample extraction. A Sciex API 3000 triple quadrupole mass spectrometer with an atmospheric pressure chemical ionization (APCI) interface operated in positive ion mode was used for detection. Lower limits of quantification of 1.00 and 2.00 ng/ml were attained for STI571 and its metabolite, CGP 74588, respectively. The method proved to be rugged and allowed the simultaneous quantification of STI571 and CGP 74588 in monkey plasma. Herein, assay development, validation, and representative concentration-time profiles obtained from TK studies are presented.

  6. Automated magnetic sorbent extraction based on octadecylsilane functionalized maghemite magnetic particles in a sequential injection system coupled with electrothermal atomic absorption spectrometry for metal determination.

    Science.gov (United States)

    Giakisikli, Georgia; Anthemidis, Aristidis N

    2013-06-15

    A new automatic sequential injection (SI) system for on-line magnetic sorbent extraction coupled with electrothermal atomic absorption spectrometry (ETAAS) has been successfully developed for metal determination. In this work, we reported effective on-line immobilization of magnetic silica particles into a microcolumn by the external force of two strong neodymium iron boron (NdFeB) magnets across it, avoiding the use of frits. Octadecylsilane functionalized maghemite magnetic particles were used as sorbent material. The potentials of the system were demonstrated for trace cadmium determination in water samples. The method was based on the on-line complex formation with diethyldithiocarbamate (DDTC), retention of Cd-DDTC on the surface of the MPs and elution with isobutyl methyl ketone (IBMK). The formation mechanism of the magnetic solid phase packed column and all critical parameters (chemical, flow, graphite furnace) influencing the performance of the system were optimized and offered good analytical characteristics. For 5 mL sample volume, a detection limit of 3 ng L(-1), a relative standard deviation of 3.9% at 50 ng L(-1) level (n=11) and a linear range of 9-350 ng L(-1) were obtained. The column remained stable for more than 600 cycles keeping the cost down in routine analysis. The proposed method was evaluated by analyzing certified reference materials and natural waters. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. Improving Multiple Fault Diagnosability using Possible Conflicts

    Data.gov (United States)

    National Aeronautics and Space Administration — Multiple fault diagnosis is a difficult problem for dynamic systems. Due to fault masking, compensation, and relative time of fault occurrence, multiple faults can...

  8. ESR dating of fault rocks

    International Nuclear Information System (INIS)

    Lee, Hee Kwon

    2002-03-01

    Past movement on faults can be dated by measurement of the intensity of ESR signals in quartz. These signals are reset by local lattice deformation and local frictional heating on grain contacts at the time of fault movement. The ESR signals then trow back as a result of bombardment by ionizing radiation from surrounding rocks. The age is obtained from the ratio of the equivalent dose, needed to produce the observed signal, to the dose rate. Fine grains are more completely reset during faulting, and a plot of age vs grain size shows a plateau for grains below critical size : these grains are presumed to have been completely zeroed by the last fault activity. We carried out ESR dating of fault rocks collected from the Yangsan fault system. ESR dates from the this fault system range from 870 to 240 ka. Results of this research suggest that long-term cyclic fault activity continued into the pleistocene

  9. Fault diagnosis of induction motors

    CERN Document Server

    Faiz, Jawad; Joksimović, Gojko

    2017-01-01

    This book is a comprehensive, structural approach to fault diagnosis strategy. The different fault types, signal processing techniques, and loss characterisation are addressed in the book. This is essential reading for work with induction motors for transportation and energy.

  10. Fault management and systems knowledge

    Science.gov (United States)

    2016-12-01

    Pilots are asked to manage faults during flight operations. This leads to the training question of the type and depth of system knowledge required to respond to these faults. Based on discussions with multiple airline operators, there is agreement th...

  11. Autonomous Systems: Habitat Automation

    Data.gov (United States)

    National Aeronautics and Space Administration — The Habitat Automation Project Element within the Autonomous Systems Project is developing software to automate the automation of habitats and other spacecraft. This...

  12. An Automation Planning Primer.

    Science.gov (United States)

    Paynter, Marion

    1988-01-01

    This brief planning guide for library automation incorporates needs assessment and evaluation of options to meet those needs. A bibliography of materials on automation planning and software reviews, library software directories, and library automation journals is included. (CLB)

  13. A semi-automated solid-phase extraction liquid chromatography/tandem mass spectrometry method for the analysis of tetrahydrocannabinol and metabolites in whole blood.

    Science.gov (United States)

    Jagerdeo, Eshwar; Schaff, Jason E; Montgomery, Madeline A; LeBeau, Marc A

    2009-09-01

    Marijuana is one of the most commonly abused illicit substances in the USA, making cannabinoids important to detect in clinical and forensic toxicology laboratories. Historically, cannabinoids in biological fluids have been derivatized and analyzed by gas chromatography/mass spectrometry (GC/MS). There has been a gradual shift in many laboratories towards liquid chromatography/mass spectrometry (LC/MS) for this analysis due to its improved sensitivity and reduced sample preparation compared with GC/MS procedures. This paper reports a validated method for the analysis of Delta(9)-tetrahydrocannabinol (THC) and its two main metabolites, 11-nor-9-carboxy-Delta(9)-tetrahydrocannabinol (THC-COOH) and 11-hydroxy-Delta(9)-tetrahydrocannabinol (THC-OH), in whole blood samples. The method has also been validated for cannabinol (CBD) and cannabidiol (CDN), two cannabinoids that were shown not to interfere with the method. This method has been successfully applied to samples both from living people and from deceased individuals obtained during autopsy. This method utilizes online solid-phase extraction (SPE) with LC/MS. Pretreatment of samples involves protein precipitation, sample concentration, ultracentrifugation, and reconstitution. The online SPE procedure was developed using Hysphere C8-EC sorbent. A chromatographic gradient with an Xterra MS C(18) column was used for the separation. Four multiple-reaction monitoring (MRM) transitions were monitored for each analyte and internal standard. Linearity generally fell between 2 and 200 ng/mL. The limits of detection (LODs) ranged from 0.5 to 3 ng/mL and the limits of quantitation (LOQs) ranged from 2 to 8 ng/mL. The bias and imprecision were determined using a simple analysis of variance (ANOVA: single factor). The results demonstrate bias as <7%, and imprecision as <9%, for all components at each quantity control level. Published in 2009 by John Wiley & Sons, Ltd.

  14. Prototype Software for Automated Structural Analysis of Systems

    DEFF Research Database (Denmark)

    Jørgensen, A.; Izadi-Zamanabadi, Roozbeh; Kristensen, M.

    2004-01-01

    In this paper we present a prototype software tool that is developed to analyse the structural model of automated systems in order to identify redundant information that is hence utilized for Fault detection and Isolation (FDI) purposes. The dedicated algorithms in this software tool use a tri...

  15. Fault-Mechanism Simulator

    Science.gov (United States)

    Guyton, J. W.

    1972-01-01

    An inexpensive, simple mechanical model of a fault can be produced to simulate the effects leading to an earthquake. This model has been used successfully with students from elementary to college levels and can be demonstrated to classes as large as thirty students. (DF)

  16. Row fault detection system

    Science.gov (United States)

    Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

    2008-10-14

    An apparatus, program product and method checks for nodal faults in a row of nodes by causing each node in the row to concurrently communicate with its adjacent neighbor nodes in the row. The communications are analyzed to determine a presence of a faulty node or connection.

  17. Guilt without fault

    DEFF Research Database (Denmark)

    Schrøder, Katja; la Cour, Karen; Jørgensen, Jan Stener

    2017-01-01

    -free approach is promoted in the aftermath of adverse events. The purpose is to illustrate how healthcare professionals may experience guilt without being at fault after adverse events, and Gamlund's theory on forgiveness without blame is used as the theoretical framework for this analysis. Philosophical...

  18. Fault Monitoring and Fault Recovery Control for Position Moored Tanker

    DEFF Research Database (Denmark)

    Fang, Shaoji; Blanke, Mogens

    2011-01-01

    This paper addresses fault tolerant control for position mooring of a shuttle tanker operating in the North Sea. A complete framework for fault diagnosis is presented but the loss of a sub-sea mooring line buoyancy element is given particular attention, since this fault could lead to mooring line...... breakage and a high-risk abortion of an oil-loading operation. With significant drift forces from waves, non-Gaussian elements dominate forces and the residuals designed for fault diagnosis. Hypothesis testing need be designed using dedicated change detection for the type of distribution encountered....... Properties of detection and fault-tolerant control are demonstrated by high fidelity simulations....

  19. Automated Budget System -

    Data.gov (United States)

    Department of Transportation — The Automated Budget System (ABS) automates management and planning of the Mike Monroney Aeronautical Center (MMAC) budget by providing enhanced capability to plan,...

  20. Fault-Related Sanctuaries

    Science.gov (United States)

    Piccardi, L.

    2001-12-01

    Beyond the study of historical surface faulting events, this work investigates the possibility, in specific cases, of identifying pre-historical events whose memory survives in myths and legends. The myths of many famous sacred places of the ancient world contain relevant telluric references: "sacred" earthquakes, openings to the Underworld and/or chthonic dragons. Given the strong correspondence with local geological evidence, these myths may be considered as describing natural phenomena. It has been possible in this way to shed light on the geologic origin of famous myths (Piccardi, 1999, 2000 and 2001). Interdisciplinary researches reveal that the origin of several ancient sanctuaries may be linked in particular to peculiar geological phenomena observed on local active faults (like ground shaking and coseismic surface ruptures, gas and flames emissions, strong underground rumours). In many of these sanctuaries the sacred area is laid directly above the active fault. In a few cases, faulting has affected also the archaeological relics, right through the main temple (e.g. Delphi, Cnidus, Hierapolis of Phrygia). As such, the arrangement of the cult site and content of relative myths suggest that specific points along the trace of active faults have been noticed in the past and worshiped as special `sacred' places, most likely interpreted as Hades' Doors. The mythological stratification of most of these sanctuaries dates back to prehistory, and points to a common derivation from the cult of the Mother Goddess (the Lady of the Doors), which was largely widespread since at least 25000 BC. The cult itself was later reconverted into various different divinities, while the `sacred doors' of the Great Goddess and/or the dragons (offspring of Mother Earth and generally regarded as Keepers of the Doors) persisted in more recent mythologies. Piccardi L., 1999: The "Footprints" of the Archangel: Evidence of Early-Medieval Surface Faulting at Monte Sant'Angelo (Gargano, Italy

  1. A Fast Classification Method of Faults in Power Electronic Circuits Based on Support Vector Machines

    OpenAIRE

    Cui Jiang; Shi Ge; Gong Chunying

    2017-01-01

    Fault detection and location are important and front-end tasks in assuring the reliability of power electronic circuits. In essence, both tasks can be considered as the classification problem. This paper presents a fast fault classification method for power electronic circuits by using the support vector machine (SVM) as a classifier and the wavelet transform as a feature extraction technique. Using one-against-rest SVM and one-against-one SVM are two general approaches to fault classificatio...

  2. Electromagnetic Transient Response Analysis of DFIG under Cascading Grid Faults Considering Phase Angel Jumps

    DEFF Research Database (Denmark)

    Wang, Yun; Wu, Qiuwei

    2014-01-01

    This paper analysis the electromagnetic transient response characteristics of DFIG under symmetrical and asymmetrical cascading grid fault conditions considering phaseangel jump of grid. On deriving the dynamic equations of the DFIG with considering multiple constraints on balanced and unbalanced...... conditions, phase angel jumps, interval of cascading fault, electromagnetic transient characteristics, the principle of the DFIG response under cascading voltage fault can be extract. The influence of grid angel jump on the transient characteristic of DFIG is analyzed and electromagnetic response...

  3. Transformer fault diagnosis using continuous sparse autoencoder.

    Science.gov (United States)

    Wang, Lukun; Zhao, Xiaoying; Pei, Jiangnan; Tang, Gongyou

    2016-01-01

    This paper proposes a novel continuous sparse autoencoder (CSAE) which can be used in unsupervised feature learning. The CSAE adds Gaussian stochastic unit into activation function to extract features of nonlinear data. In this paper, CSAE is applied to solve the problem of transformer fault recognition. Firstly, based on dissolved gas analysis method, IEC three ratios are calculated by the concentrations of dissolved gases. Then IEC three ratios data is normalized to reduce data singularity and improve training speed. Secondly, deep belief network is established by two layers of CSAE and one layer of back propagation (BP) network. Thirdly, CSAE is adopted to unsupervised training and getting features. Then BP network is used for supervised training and getting transformer fault. Finally, the experimental data from IEC TC 10 dataset aims to illustrate the effectiveness of the presented approach. Comparative experiments clearly show that CSAE can extract features from the original data, and achieve a superior correct differentiation rate on transformer fault diagnosis.

  4. Automation 2017

    CERN Document Server

    Zieliński, Cezary; Kaliczyńska, Małgorzata

    2017-01-01

    This book consists of papers presented at Automation 2017, an international conference held in Warsaw from March 15 to 17, 2017. It discusses research findings associated with the concepts behind INDUSTRY 4.0, with a focus on offering a better understanding of and promoting participation in the Fourth Industrial Revolution. Each chapter presents a detailed analysis of a specific technical problem, in most cases followed by a numerical analysis, simulation and description of the results of implementing the solution in a real-world context. The theoretical results, practical solutions and guidelines presented are valuable for both researchers working in the area of engineering sciences and practitioners looking for solutions to industrial problems. .

  5. Marketing automation

    Directory of Open Access Journals (Sweden)

    TODOR Raluca Dania

    2017-01-01

    Full Text Available The automation of the marketing process seems to be nowadays, the only solution to face the major changes brought by the fast evolution of technology and the continuous increase in supply and demand. In order to achieve the desired marketing results, businessis have to employ digital marketing and communication services. These services are efficient and measurable thanks to the marketing technology used to track, score and implement each campaign. Due to the technical progress, the marketing fragmentation, demand for customized products and services on one side and the need to achieve constructive dialogue with the customers, immediate and flexible response and the necessity to measure the investments and the results on the other side, the classical marketing approached had changed continue to improve substantially.

  6. Fault Diagnosis and Fault Handling for Autonomous Aircraft

    DEFF Research Database (Denmark)

    Hansen, Søren

    that the fault is discovered in time such that appropriate actions can be taken. That could either be the aircraft controlling computer taking the fault into account or a human operator that intervenes. Detection of faults that occur during flight is exactly the subject of this thesis. Safety towards faults...... for manned aircraft is often achieved by making most of the systems onboard redundant. This is an easy way to obtain safety since no single system fault is catastrophic. The failed subsystem can be disconnected and the redundant systems can take over the tasks of the failed system. For smaller UAVs both...... a specific UAV, used by the Danish military, it is investigated how a number of critical faults can be detected and handled. One of the challenges using telemetry data for the fault diagnosis is the limited bandwidth in the radio link between the aircraft and the base-station on ground. This combined...

  7. A semi-automated system for quantifying the oxidative potential of ambient particles in aqueous extracts using the dithiothreitol (DTT) assay: results from the Southeastern Center for Air Pollution and Epidemiology (SCAPE)

    Science.gov (United States)

    Fang, T.; Verma, V.; Guo, H.; King, L. E.; Edgerton, E. S.; Weber, R. J.

    2015-01-01

    A variety of methods are used to measure the capability of particulate matter (PM) to catalytically generate reactive oxygen species (ROS) in vivo, also defined as the aerosol oxidative potential. A widely used measure of aerosol oxidative potential is the dithiothreitol (DTT) assay, which monitors the depletion of DTT (a surrogate for cellular antioxidants) as catalyzed by the redox-active species in PM. However, a major constraint in the routine use of the DTT assay for integrating it with large-scale health studies is its labor-intensive and time-consuming protocol. To specifically address this concern, we have developed a semi-automated system for quantifying the oxidative potential of aerosol liquid extracts using the DTT assay. The system, capable of unattended analysis at one sample per hour, has a high analytical precision (coefficient of variation of 15% for positive control, 4% for ambient samples) and reasonably low limit of detection (0.31 nmol min-1). Comparison of the automated approach with the manual method conducted on ambient samples yielded good agreement (slope = 1.08 ± 0.12, r2 = 0.92, N = 9). The system was utilized for the Southeastern Center for Air Pollution & Epidemiology (SCAPE) to generate an extensive data set on DTT activity of ambient particles collected from contrasting environments (urban, roadside, and rural) in the southeastern US. We find that water-soluble PM2.5 DTT activity on a per-air-volume basis was spatially uniform and often well correlated with PM2.5 mass (r = 0.49 to 0.88), suggesting regional sources contributing to the PM oxidative potential in the southeastern US. The correlation may also suggest a mechanistic explanation (oxidative stress) for observed PM2.5 mass-health associations. The heterogeneity in the intrinsic DTT activity (per-PM-mass basis) across seasons indicates variability in the DTT activity associated with aerosols from sources that vary with season. Although developed for the DTT assay, the

  8. Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine.

    Science.gov (United States)

    Zhong, Jian-Hua; Wong, Pak Kin; Yang, Zhi-Xin

    2016-02-02

    This study combines signal de-noising, feature extraction, two pairwise-coupled relevance vector machines (PCRVMs) and particle swarm optimization (PSO) for parameter optimization to form an intelligent diagnostic framework for gearbox fault detection. Firstly, the noises of sensor signals are de-noised by using the wavelet threshold method to lower the noise level. Then, the Hilbert-Huang transform (HHT) and energy pattern calculation are applied to extract the fault features from de-noised signals. After that, an eleven-dimension vector, which consists of the energies of nine intrinsic mode functions (IMFs), maximum value of HHT marginal spectrum and its corresponding frequency component, is obtained to represent the features of each gearbox fault. The two PCRVMs serve as two different fault detection committee members, and they are trained by using vibration and sound signals, respectively. The individual diagnostic result from each committee member is then combined by applying a new probabilistic ensemble method, which can improve the overall diagnostic accuracy and increase the number of detectable faults as compared to individual classifiers acting alone. The effectiveness of the proposed framework is experimentally verified by using test cases. The experimental results show the proposed framework is superior to existing single classifiers in terms of diagnostic accuracies for both single- and simultaneous-faults in the gearbox.

  9. Development of a morphological convolution operator for bearing fault detection

    Science.gov (United States)

    Li, Yifan; Liang, Xihui; Liu, Weiwei; Wang, Yan

    2018-05-01

    This paper presents a novel signal processing scheme, namely morphological convolution operator (MCO) lifted morphological undecimated wavelet (MUDW), for rolling element bearing fault detection. In this scheme, a MCO is first designed to fully utilize the advantage of the closing & opening gradient operator and the closing-opening & opening-closing gradient operator for feature extraction as well as the merit of excellent denoising characteristics of the convolution operator. The MCO is then introduced into MUDW for the purpose of improving the fault detection ability of the reported MUDWs. Experimental vibration signals collected from a train wheelset test rig and the bearing data center of Case Western Reserve University are employed to evaluate the effectiveness of the proposed MCO lifted MUDW on fault detection of rolling element bearings. The results show that the proposed approach has a superior performance in extracting fault features of defective rolling element bearings. In addition, comparisons are performed between two reported MUDWs and the proposed MCO lifted MUDW. The MCO lifted MUDW outperforms both of them in detection of outer race faults and inner race faults of rolling element bearings.

  10. Fault Diagnosis of Batch Reactor Using Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Sujatha Subramanian

    2014-01-01

    Full Text Available Fault diagnosis of a batch reactor gives the early detection of fault and minimizes the risk of thermal runaway. It provides superior performance and helps to improve safety and consistency. It has become more vital in this technical era. In this paper, support vector machine (SVM is used to estimate the heat release (Qr of the batch reactor both normal and faulty conditions. The signature of the residual, which is obtained from the difference between nominal and estimated faulty Qr values, characterizes the different natures of faults occurring in the batch reactor. Appropriate statistical and geometric features are extracted from the residual signature and the total numbers of features are reduced using SVM attribute selection filter and principle component analysis (PCA techniques. artificial neural network (ANN classifiers like multilayer perceptron (MLP, radial basis function (RBF, and Bayes net are used to classify the different types of faults from the reduced features. It is observed from the result of the comparative study that the proposed method for fault diagnosis with limited number of features extracted from only one estimated parameter (Qr shows that it is more efficient and fast for diagnosing the typical faults.

  11. Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine

    Science.gov (United States)

    Zhong, Jian-Hua; Wong, Pak Kin; Yang, Zhi-Xin

    2016-01-01

    This study combines signal de-noising, feature extraction, two pairwise-coupled relevance vector machines (PCRVMs) and particle swarm optimization (PSO) for parameter optimization to form an intelligent diagnostic framework for gearbox fault detection. Firstly, the noises of sensor signals are de-noised by using the wavelet threshold method to lower the noise level. Then, the Hilbert-Huang transform (HHT) and energy pattern calculation are applied to extract the fault features from de-noised signals. After that, an eleven-dimension vector, which consists of the energies of nine intrinsic mode functions (IMFs), maximum value of HHT marginal spectrum and its corresponding frequency component, is obtained to represent the features of each gearbox fault. The two PCRVMs serve as two different fault detection committee members, and they are trained by using vibration and sound signals, respectively. The individual diagnostic result from each committee member is then combined by applying a new probabilistic ensemble method, which can improve the overall diagnostic accuracy and increase the number of detectable faults as compared to individual classifiers acting alone. The effectiveness of the proposed framework is experimentally verified by using test cases. The experimental results show the proposed framework is superior to existing single classifiers in terms of diagnostic accuracies for both single- and simultaneous-faults in the gearbox. PMID:26848665

  12. Gear fault detection using customized multiwavelet lifting schemes

    Science.gov (United States)

    Yuan, Jing; He, Zhengjia; Zi, Yanyang

    2010-07-01

    Fault symptoms of running gearboxes must be detected as early as possible to avoid serious accidents. Diverse advanced methods are developed for this challenging task. However, for multiwavelet transforms, the fixed basis functions independent of the input dynamic response signals will possibly reduce the accuracy of fault diagnosis. Meanwhile, for multiwavelet denoising technique, the universal threshold denoising tends to overkill important but weak features in gear fault diagnosis. To overcome the shortcoming, a novel method incorporating customized (i.e., signal-based) multiwavelet lifting schemes with sliding window denoising is proposed in this paper. On the basis of Hermite spline interpolation, various vector prediction and update operators with the desirable properties of biorthogonality, symmetry, short support and vanishing moments are constructed. The customized lifting-based multiwavelets for feature matching are chosen by the minimum entropy principle. Due to the periodic characteristics of gearbox vibration signals, sliding window denoising favorable to retain valuable information as much as possible is employed to extract and identify the fault features in gearbox signals. The proposed method is applied to simulation experiments, gear fault diagnosis and normal gear detection to testify the efficiency and reliability. The results show that the method involving the selection of appropriate basis functions and the proper feature extraction technique could act as an effective and promising tool for gear fault detection.

  13. Fault diagnosis of rolling bearing based on second generation wavelet denoising and morphological filter

    International Nuclear Information System (INIS)

    Meng, Lingjie; Xiang, Jiawei; Zhong, Yongteng; Song, Wenlei

    2015-01-01

    Defective rolling bearing response is often characterized by the presence of periodic impulses. However, the in-situ sampled vibration signal is ordinarily mixed with ambient noises and easy to be interfered even submerged. The hybrid approach combining the second generation wavelet denoising with morphological filter is presented. The raw signal is purified using the second generation wavelet. The difference between the closing and opening operator is employed as the morphology filter to extract the periodicity impulsive features from the purified signal and the defect information is easily to be extracted from the corresponding frequency spectrum. The proposed approach is evaluated by simulations and vibration signals from defective bearings with inner race fault, outer race fault, rolling element fault and compound faults, espectively. Results show that the ambient noises can be fully restrained and the defect information of the above defective bearings is well extracted, which demonstrates that the approach is feasible and effective for the fault detection of rolling bearing.

  14. Model-Based Fault Diagnosis: Performing Root Cause and Impact Analyses in Real Time

    Science.gov (United States)

    Figueroa, Jorge F.; Walker, Mark G.; Kapadia, Ravi; Morris, Jonathan

    2012-01-01

    Generic, object-oriented fault models, built according to causal-directed graph theory, have been integrated into an overall software architecture dedicated to monitoring and predicting the health of mission- critical systems. Processing over the generic fault models is triggered by event detection logic that is defined according to the specific functional requirements of the system and its components. Once triggered, the fault models provide an automated way for performing both upstream root cause analysis (RCA), and for predicting downstream effects or impact analysis. The methodology has been applied to integrated system health management (ISHM) implementations at NASA SSC's Rocket Engine Test Stands (RETS).

  15. Automating the fault tolerance process in Grid Environment

    OpenAIRE

    Maninder Singh; Inderpreet Chopra

    2010-01-01

    As Grid encourages the dynamic addition of resources that are not likely to be benefited from the manual management techniques as these are time-consuming, unsecure and more prone to errors. A new paradigm for self-management is pervading over the old manual system to begin the next generation of computing. In this paper we have discussed the different approaches for self-healing the current grid middleware use, and after analyzing these we have proposed the new approach, Selfhealing Manageme...

  16. Study on a Novel Bearing Fault Diagnosis Method from Frequency and Energy Perspective

    Science.gov (United States)

    Li, Xiumei; Liu, Yong; Zhao, Huiming; Deng, Wu Aa(Artificial Intelligence Key Laboratory Of Sichuan Province, Sichuan University Of Science; Engineering, Zigong 643000, China), Ac(Hm Zhao1977@126. Com),

    2017-11-01

    Early identification of faults in rolling element bearings is a challenging task; especially extracting transient characteristics from a noisy signal and identifying bearings fault become critical steps. In this paper, a novel method for real time fault detection in rolling element bearings is proposed to deal with non-stationary fault signals from frequency and energy perspective. Second-order blind identification (SOBI) and wavelet packet decomposition are organically integrated to diagnose the early bearing faults, the fault vibration signals are processed by SOBI algorithm, and feature information is extracted; meanwhile, fault vibration signals are decomposed by the wavelet packet, the energy of terminal nodes(at the bottom layer of wavelet packet decomposition) are analyzed because the energy of terminal nodes has different sensitive to different component faults. Therefore, the bearing faults can be diagnosed by organic combination of fault characteristic frequency analysis and energy of the terminal nodes, and the effectiveness, feasibility and robustness of the proposed method have been verified by experimental data.

  17. Fault rocks and uranium mineralization

    International Nuclear Information System (INIS)

    Tong Hangshou.

    1991-01-01

    The types of fault rocks, microstructural characteristics of fault tectonite and their relationship with uranium mineralization in the uranium-productive granite area are discussed. According to the synthetic analysis on nature of stress, extent of crack and microstructural characteristics of fault rocks, they can be classified into five groups and sixteen subgroups. The author especially emphasizes the control of cataclasite group and fault breccia group over uranium mineralization in the uranium-productive granite area. It is considered that more effective study should be made on the macrostructure and microstructure of fault rocks. It is of an important practical significance in uranium exploration

  18. FTREX Testing Report (Fault Tree Reliability Evaluation eXpert) Version 1.5

    International Nuclear Information System (INIS)

    Jung, Woo Sik

    2009-07-01

    In order to verify FTREX functions and to confirm the correctness of FTREX 1.5, various tests were performed 1.fault trees with negates 2.fault trees with house events 3.fault trees with multiple tops 4.fault trees with logical loops 5.fault trees with initiators, house events, negates, logical loops, and flag events By using the automated cutest propagation test, the FTREX 1.5 functions are verified. FTREX version 1.3 and later versions have capability to perform bottom-up cutset-propagation test in order check cutest status. FTREX 1.5 always generates the proper minimal cut sets. All the output cutsets of the tested problems are MCSs (Minimal Cut Sets) and have no non-minimal cutsets and improper cutsets. The improper cutsets are those that have no effect to top, have multiple initiators, or have disjoint events A * -A

  19. A New Fault Diagnosis Method of Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Chih-Hao Chen

    2008-01-01

    Full Text Available This paper presents a new fault diagnosis procedure for rotating machinery using the wavelet packets-fractal technology and a radial basis function neural network. The faults of rotating machinery considered in this study include imbalance, misalignment, looseness and imbalance combined with misalignment conditions. When such faults occur, they usually induce non-stationary vibrations to the machine. After measuring the vibration signals, the wavelet packets transform is applied to these signals. The fractal dimension of each frequency bands is extracted and the box counting dimension is used to depict the failure characteristics of the vibration signals. The failure modes are then classified by a radial basis function neural network. An experimental study was performed to evaluate the proposed method and the results show that the method can effectively detect and recognize different kinds of faults of rotating machinery.

  20. Multiscale singular value manifold for rotating machinery fault diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Feng, Yi; Lu, BaoChun; Zhang, Deng Feng [School of Mechanical Engineering, Nanjing University of Science and Technology,Nanjing (United States)

    2017-01-15

    Time-frequency distribution of vibration signal can be considered as an image that contains more information than signal in time domain. Manifold learning is a novel theory for image recognition that can be also applied to rotating machinery fault pattern recognition based on time-frequency distributions. However, the vibration signal of rotating machinery in fault condition contains cyclical transient impulses with different phrases which are detrimental to image recognition for time-frequency distribution. To eliminate the effects of phase differences and extract the inherent features of time-frequency distributions, a multiscale singular value manifold method is proposed. The obtained low-dimensional multiscale singular value manifold features can reveal the differences of different fault patterns and they are applicable to classification and diagnosis. Experimental verification proves that the performance of the proposed method is superior in rotating machinery fault diagnosis.

  1. Scattering transform and LSPTSVM based fault diagnosis of rotating machinery

    Science.gov (United States)

    Ma, Shangjun; Cheng, Bo; Shang, Zhaowei; Liu, Geng

    2018-05-01

    This paper proposes an algorithm for fault diagnosis of rotating machinery to overcome the shortcomings of classical techniques which are noise sensitive in feature extraction and time consuming for training. Based on the scattering transform and the least squares recursive projection twin support vector machine (LSPTSVM), the method has the advantages of high efficiency and insensitivity for noise signal. Using the energy of the scattering coefficients in each sub-band, the features of the vibration signals are obtained. Then, an LSPTSVM classifier is used for fault diagnosis. The new method is compared with other common methods including the proximal support vector machine, the standard support vector machine and multi-scale theory by using fault data for two systems, a motor bearing and a gear box. The results show that the new method proposed in this study is more effective for fault diagnosis of rotating machinery.

  2. Remote online machine fault diagnostic system

    Science.gov (United States)

    Pan, Min-Chun; Li, Po-Ching

    2004-07-01

    The study aims at implementing a remote online machine fault diagnostic system built up in the architecture of both the BCB software-developing environment and Internet transmission communication. Variant signal-processing computation schemes for signal analysis and pattern recognition purposes are implemented in the BCB graphical user interface. Hence, machine fault diagnostic capability can be extended by using the socket application program interface as the TCP/IP protocol. In the study, the effectiveness of the developed remote diagnostic system is validated by monitoring a transmission-element test rig. A complete monitoring cycle includes data acquisition, signal processing, feature extraction, pattern recognition through the ANNs, and online video monitoring, is demonstrated.

  3. Fault tolerant architecture for artificial olfactory system

    International Nuclear Information System (INIS)

    Lotfivand, Nasser; Hamidon, Mohd Nizar; Abdolzadeh, Vida

    2015-01-01

    In this paper, to cover and mask the faults that occur in the sensing unit of an artificial olfactory system, a novel architecture is offered. The proposed architecture is able to tolerate failures in the sensors of the array and the faults that occur are masked. The proposed architecture for extracting the correct results from the output of the sensors can provide the quality of service for generated data from the sensor array. The results of various evaluations and analysis proved that the proposed architecture has acceptable performance in comparison with the classic form of the sensor array in gas identification. According to the results, achieving a high odor discrimination based on the suggested architecture is possible. (paper)

  4. Release fault: A variety of cross fault in linked extensional fault systems, in the Sergipe-Alagoas Basin, NE Brazil

    Science.gov (United States)

    Destro, Nivaldo

    1995-05-01

    Two types of cross faults are herein recognized: transfer faults and the newly termed release faults. Transfer faults form where cross faults connect distinct normal faults and horizontal displacements predominate over vertical ones. In contrast, release faults form where cross faults associated with individual normal faults die out within the hangingwall before connecting to other normal faults, and have predominantly vertical displacements. Release faults are geometrically required to accommodate variable displacements along the strike of a normal fault. Thus, they form to release the bending stresses in the hangingwall, and do not cut normal fault planes nor detachment surfaces at depth. Release faults have maximum throws adjacent to normal faults, and may be nearly perpendicular or obliquely oriented to the strike of the latter. Such geometry appears not to depend upon pre-existing weaknesses, but such variable orientation to normal faults is an inherent property of release faults. Release faults commonly appear as simple normal faults in seismic sections, without implying extension along the strike of rift and basins. Three-dimensional strain deformation occurs in the hangingwall only between the terminations of an individual normal fault, but regionally, release faulting is associated with plane strain deformation in linked extensional fault systems.

  5. Fault Ride Through Capability Enhancement of a Large-Scale PMSG Wind System with Bridge Type Fault Current Limiters

    Directory of Open Access Journals (Sweden)

    ALAM, M. S.

    2018-02-01

    Full Text Available In this paper, bridge type fault current limiter (BFCL is proposed as a potential solution to the fault problems of permanent magnet synchronous generator (PMSG based large-scale wind energy system. As PMSG wind system is more vulnerable to disturbances, it is essential to guarantee the stability during severe disturbances by enhancing the fault ride through capability. BFCL controller has been designed to insert resistance and inductance during the inception of system disturbances in order to limit fault current. Constant capacitor voltage has been maintained by the grid voltage source converter (GVSC controller while current extraction or injection has been achieved by machine VSC (MVSC controller. Symmetrical and unsymmetrical faults have been applied in the system to show the effectiveness of the proposed BFCL solution. PMSG wind system, BFCL and their controllers have been implemented by real time hardware in loop (RTHIL setup with real time digital simulator (RTDS and dSPACE. Another significant feature of this work is that the performance of the proposed BFCL is compared with that of series dynamic braking resistor (SDBR. Comparative RTHIL implementation results show that the proposed BFCL is very efficient in improving system fault ride through capability by limiting the fault current and outperforms SDBR.

  6. Fault linkage and continental breakup

    Science.gov (United States)

    Cresswell, Derren; Lymer, Gaël; Reston, Tim; Stevenson, Carl; Bull, Jonathan; Sawyer, Dale; Morgan, Julia

    2017-04-01

    The magma-poor rifted margin off the west coast of Galicia (NW Spain) has provided some of the key observations in the development of models describing the final stages of rifting and continental breakup. In 2013, we collected a 68 x 20 km 3D seismic survey across the Galicia margin, NE Atlantic. Processing through to 3D Pre-stack Time Migration (12.5 m bin-size) and 3D depth conversion reveals the key structures, including an underlying detachment fault (the S detachment), and the intra-block and inter-block faults. These data reveal multiple phases of faulting, which overlap spatially and temporally, have thinned the crust to between zero and a few km thickness, producing 'basement windows' where crustal basement has been completely pulled apart and sediments lie directly on the mantle. Two approximately N-S trending fault systems are observed: 1) a margin proximal system of two linked faults that are the upward extension (breakaway faults) of the S; in the south they form one surface that splays northward to form two faults with an intervening fault block. These faults were thus demonstrably active at one time rather than sequentially. 2) An oceanward relay structure that shows clear along strike linkage. Faults within the relay trend NE-SW and heavily dissect the basement. The main block bounding faults can be traced from the S detachment through the basement into, and heavily deforming, the syn-rift sediments where they die out, suggesting that the faults propagated up from the S detachment surface. Analysis of the fault heaves and associated maps at different structural levels show complementary fault systems. The pattern of faulting suggests a variation in main tectonic transport direction moving oceanward. This might be interpreted as a temporal change during sequential faulting, however the transfer of extension between faults and the lateral variability of fault blocks suggests that many of the faults across the 3D volume were active at least in part

  7. Maneuver Automation Software

    Science.gov (United States)

    Uffelman, Hal; Goodson, Troy; Pellegrin, Michael; Stavert, Lynn; Burk, Thomas; Beach, David; Signorelli, Joel; Jones, Jeremy; Hahn, Yungsun; Attiyah, Ahlam; hide

    2009-01-01

    The Maneuver Automation Software (MAS) automates the process of generating commands for maneuvers to keep the spacecraft of the Cassini-Huygens mission on a predetermined prime mission trajectory. Before MAS became available, a team of approximately 10 members had to work about two weeks to design, test, and implement each maneuver in a process that involved running many maneuver-related application programs and then serially handing off data products to other parts of the team. MAS enables a three-member team to design, test, and implement a maneuver in about one-half hour after Navigation has process-tracking data. MAS accepts more than 60 parameters and 22 files as input directly from users. MAS consists of Practical Extraction and Reporting Language (PERL) scripts that link, sequence, and execute the maneuver- related application programs: "Pushing a single button" on a graphical user interface causes MAS to run navigation programs that design a maneuver; programs that create sequences of commands to execute the maneuver on the spacecraft; and a program that generates predictions about maneuver performance and generates reports and other files that enable users to quickly review and verify the maneuver design. MAS can also generate presentation materials, initiate electronic command request forms, and archive all data products for future reference.

  8. Study of Intelligent Photovoltaic System Fault Diagnostic Scheme Based on Chaotic Signal Synchronization

    Directory of Open Access Journals (Sweden)

    Chin-Tsung Hsieh

    2013-01-01

    Full Text Available As the photovoltaic system consists of many equipment components, manual inspection will be very costly. This study proposes the photovoltaic system fault diagnosis based on chaotic signal synchronization. First, MATLAB was used to simulate the fault conditions of solar system, and the maximum power point tracking (MPPT was used to ensure the system's stable power and capture and record the system fault feature signals. The dynamic errors of various fault signals were extracted by chaotic signal synchronization, and the dynamic error data of various fault signals were recorded completely. In the photovoltaic system, the captured output voltage signal was used as the characteristic values for fault recognition, and the extension theory was used to create the joint domain and classical domain of various fault conditions according to the collected feature data. The matter-element model of extension engineering was constructed. Finally, the whole fault diagnosis system is only needed to capture the voltage signal of the solar photovoltaic system, so as to know the exact fault condition effectively and rapidly. The proposed fault diagnostor can be implemented by embedded system and be combined with ZigBee wireless network module in the future, thus reducing labor cost and building a complete portable renewable energy system fault diagnostor.

  9. Both Automation and Paper.

    Science.gov (United States)

    Purcell, Royal

    1988-01-01

    Discusses the concept of a paperless society and the current situation in library automation. Various applications of automation and telecommunications are addressed, and future library automation is considered. Automation at the Monroe County Public Library in Bloomington, Indiana, is described as an example. (MES)

  10. Automated Motivic Analysis

    DEFF Research Database (Denmark)

    Lartillot, Olivier

    2016-01-01

    Motivic analysis provides very detailed understanding of musical composi- tions, but is also particularly difficult to formalize and systematize. A computational automation of the discovery of motivic patterns cannot be reduced to a mere extraction of all possible sequences of descriptions....... The systematic approach inexorably leads to a proliferation of redundant structures that needs to be addressed properly. Global filtering techniques cause a drastic elimination of interesting structures that damages the quality of the analysis. On the other hand, a selection of closed patterns allows...... for lossless compression. The structural complexity resulting from successive repetitions of patterns can be controlled through a simple modelling of cycles. Generally, motivic patterns cannot always be defined solely as sequences of descriptions in a fixed set of dimensions: throughout the descriptions...

  11. Screening of over 100 drugs in horse urine using automated on-line solid-phase extraction coupled to liquid chromatography-high resolution mass spectrometry for doping control.

    Science.gov (United States)

    Kwok, W H; Choi, Timmy L S; Tsoi, Yeuki Y K; Leung, Gary N W; Wan, Terence S M

    2017-03-24

    A fast method for the direct analysis of enzyme-hydrolysed horse urine using an automated on-line solid-phase extraction (SPE) coupled to a liquid-chromatography/high resolution mass spectrometer was developed. Over 100 drugs of diverse drug classes could be simultaneously detected in horse urine at sub to low parts per billion levels. Urine sample was first hydrolysed by β-glucuronidase to release conjugated drugs, followed by centrifugal filtration. The filtrate (1mL) was directly injected into an on-line SPE system consisting of a pre-column filter and a SPE cartridge column for the separation of analytes from matrix components. Through valves-switching, the interfering matrix components were flushed to waste, and the analytes were eluted to a C 18 analytical column for refocusing and chromatographic separation. Detections were achieved by full-scan HRMS in alternating positive and negative electrospray ionisation modes within a turn-around time of 16min, inclusive of on-line sample clean-up and post-run mobile phase equilibration. No significant matrix interference was observed at the expected retention times of the targeted masses. Over 90% of the drugs studied gave estimated limits of detection (LoDs) at or below 5ng/mL, with some LoDs reaching down to 0.05ng/mL. Data-dependent acquisition (DDA) was included to provide additional product-ion scan data to substantiate the presence of detected analytes. The resulting product-ion spectra can be searched against an in-house MS/MS library for identity verification. The applicability of the method has been demonstrated by the detection of drugs in doping control samples. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Development of a fully automated sequential injection solid-phase extraction procedure coupled to liquid chromatography to determine free 2-hydroxy-4-methoxybenzophenone and 2-hydroxy-4-methoxybenzophenone-5-sulphonic acid in human urine

    International Nuclear Information System (INIS)

    Leon, Zacarias; Chisvert, Alberto; Balaguer, Angel; Salvador, Amparo

    2010-01-01

    2-Hydroxy-4-methoxybenzophenone and 2-hydroxy-4-methoxybenzophenone-5-sulphonic acid, commonly known as benzophenone-3 (BZ3) and benzophenone-4 (BZ4), respectively, are substances widely used as UV filters in cosmetic products in order to absorb UV radiation and protect human skin from direct exposure to the deleterious wavelengths of sunlight. As with other UV filters, there is evidence of their percutaneous absorption. This work describes an analytical method developed to determine trace levels of free BZ3 and BZ4 in human urine. The methodology is based on a solid-phase extraction (SPE) procedure for clean-up and pre-concentration, followed by the monitoring of the UV filters by liquid chromatography-ultraviolet spectrophotometry detection (LC-UV). In order to improve not only the sensitivity and selectivity, but also the precision of the method, the principle of sequential injection analysis was used to automate the SPE process and to transfer the eluates from the SPE to the LC system. The application of a six-channel valve as an interface for the switching arrangements successfully allowed the on-line connection of SPE sample processing with LC analysis. The SPE process for BZ3 and BZ4 was performed using octadecyl (C18) and diethylaminopropyl (DEA) modified silica microcolumns, respectively, in which the analytes were retained and eluted selectively. Due to the matrix effects, the determination was based on standard addition quantification and was fully validated. The relative standard deviations of the results were 13% and 6% for BZ3 and BZ4, respectively, whereas the limits of detection were 60 and 30 ng mL -1 , respectively. The method was satisfactorily applied to determine BZ3 and BZ4 in urine from volunteers that had applied a sunscreen cosmetic containing both UV filters.

  13. Development of a fully automated sequential injection solid-phase extraction procedure coupled to liquid chromatography to determine free 2-hydroxy-4-methoxybenzophenone and 2-hydroxy-4-methoxybenzophenone-5-sulphonic acid in human urine

    Energy Technology Data Exchange (ETDEWEB)

    Leon, Zacarias; Chisvert, Alberto; Balaguer, Angel [Departamento de Quimica Analitica, Facultad de Quimica, Universitat de Valencia, Doctor Moliner 50, 46100 Burjassot, Valencia (Spain); Salvador, Amparo, E-mail: amparo.salvador@uv.es [Departamento de Quimica Analitica, Facultad de Quimica, Universitat de Valencia, Doctor Moliner 50, 46100 Burjassot, Valencia (Spain)

    2010-04-07

    2-Hydroxy-4-methoxybenzophenone and 2-hydroxy-4-methoxybenzophenone-5-sulphonic acid, commonly known as benzophenone-3 (BZ3) and benzophenone-4 (BZ4), respectively, are substances widely used as UV filters in cosmetic products in order to absorb UV radiation and protect human skin from direct exposure to the deleterious wavelengths of sunlight. As with other UV filters, there is evidence of their percutaneous absorption. This work describes an analytical method developed to determine trace levels of free BZ3 and BZ4 in human urine. The methodology is based on a solid-phase extraction (SPE) procedure for clean-up and pre-concentration, followed by the monitoring of the UV filters by liquid chromatography-ultraviolet spectrophotometry detection (LC-UV). In order to improve not only the sensitivity and selectivity, but also the precision of the method, the principle of sequential injection analysis was used to automate the SPE process and to transfer the eluates from the SPE to the LC system. The application of a six-channel valve as an interface for the switching arrangements successfully allowed the on-line connection of SPE sample processing with LC analysis. The SPE process for BZ3 and BZ4 was performed using octadecyl (C18) and diethylaminopropyl (DEA) modified silica microcolumns, respectively, in which the analytes were retained and eluted selectively. Due to the matrix effects, the determination was based on standard addition quantification and was fully validated. The relative standard deviations of the results were 13% and 6% for BZ3 and BZ4, respectively, whereas the limits of detection were 60 and 30 ng mL{sup -1}, respectively. The method was satisfactorily applied to determine BZ3 and BZ4 in urine from volunteers that had applied a sunscreen cosmetic containing both UV filters.

  14. Fault isolatability conditions for linear systems

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Henrik

    2006-01-01

    In this paper, we shall show that an unlimited number of additive single faults can be isolated under mild conditions if a general isolation scheme is applied. Multiple faults are also covered. The approach is algebraic and is based on a set representation of faults, where all faults within a set...... can occur simultaneously, whereas faults belonging to different fault sets appear disjoint in time. The proposed fault detection and isolation (FDI) scheme consists of three steps. A fault detection (FD) step is followed by a fault set isolation (FSI) step. Here the fault set is isolated wherein...... the faults have occurred. The last step is a fault isolation (FI) of the faults occurring in a specific fault set, i.e. equivalent with the standard FI step. A simple example demonstrates how to turn the algebraic necessary and sufficient conditions into explicit algorithms for designing filter banks, which...

  15. A fault diagnosis scheme for planetary gearboxes using adaptive multi-scale morphology filter and modified hierarchical permutation entropy

    Science.gov (United States)

    Li, Yongbo; Li, Guoyan; Yang, Yuantao; Liang, Xihui; Xu, Minqiang

    2018-05-01

    The fault diagnosis of planetary gearboxes is crucial to reduce the maintenance costs and economic losses. This paper proposes a novel fault diagnosis method based on adaptive multi-scale morphological filter (AMMF) and modified hierarchical permutation entropy (MHPE) to identify the different health conditions of planetary gearboxes. In this method, AMMF is firstly adopted to remove the fault-unrelated components and enhance the fault characteristics. Second, MHPE is utilized to extract the fault features from the denoised vibration signals. Third, Laplacian score (LS) approach is employed to refine the fault features. In the end, the obtained features are fed into the binary tree support vector machine (BT-SVM) to accomplish the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault categories of planetary gearboxes.

  16. Generic, scalable and decentralized fault detection for robot swarms.

    Science.gov (United States)

    Tarapore, Danesh; Christensen, Anders Lyhne; Timmis, Jon

    2017-01-01

    Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system's capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation.

  17. The Sorong Fault Zone, Indonesia: Mapping a Fault Zone Offshore

    Science.gov (United States)

    Melia, S.; Hall, R.

    2017-12-01

    The Sorong Fault Zone is a left-lateral strike-slip fault zone in eastern Indonesia, extending westwards from the Bird's Head peninsula of West Papua towards Sulawesi. It is the result of interactions between the Pacific, Caroline, Philippine Sea, and Australian Plates and much of it is offshore. Previous research on the fault zone has been limited by the low resolution of available data offshore, leading to debates over the extent, location, and timing of movements, and the tectonic evolution of eastern Indonesia. Different studies have shown it north of the Sula Islands, truncated south of Halmahera, continuing to Sulawesi, or splaying into a horsetail fan of smaller faults. Recently acquired high resolution multibeam bathymetry of the seafloor (with a resolution of 15-25 meters), and 2D seismic lines, provide the opportunity to trace the fault offshore. The position of different strands can be identified. On land, SRTM topography shows that in the northern Bird's Head the fault zone is characterised by closely spaced E-W trending faults. NW of the Bird's Head offshore there is a fold and thrust belt which terminates some strands. To the west of the Bird's Head offshore the fault zone diverges into multiple strands trending ENE-WSW. Regions of Riedel shearing are evident west of the Bird's Head, indicating sinistral strike-slip motion. Further west, the ENE-WSW trending faults turn to an E-W trend and there are at least three fault zones situated immediately south of Halmahera, north of the Sula Islands, and between the islands of Sanana and Mangole where the fault system terminates in horsetail strands. South of the Sula islands some former normal faults at the continent-ocean boundary with the North Banda Sea are being reactivated as strike-slip faults. The fault zone does not currently reach Sulawesi. The new fault map differs from previous interpretations concerning the location, age and significance of different parts of the Sorong Fault Zone. Kinematic

  18. Faults in Linux

    DEFF Research Database (Denmark)

    Palix, Nicolas Jean-Michel; Thomas, Gaël; Saha, Suman

    2011-01-01

    In 2001, Chou et al. published a study of faults found by applying a static analyzer to Linux versions 1.0 through 2.4.1. A major result of their work was that the drivers directory contained up to 7 times more of certain kinds of faults than other directories. This result inspired a number...... of development and research efforts on improving the reliability of driver code. Today Linux is used in a much wider range of environments, provides a much wider range of services, and has adopted a new development and release model. What has been the impact of these changes on code quality? Are drivers still...... a major problem? To answer these questions, we have transported the experiments of Chou et al. to Linux versions 2.6.0 to 2.6.33, released between late 2003 and early 2010. We find that Linux has more than doubled in size during this period, but that the number of faults per line of code has been...

  19. ESR dating of fault rocks

    International Nuclear Information System (INIS)

    Lee, Hee Kwon

    2003-02-01

    Past movement on faults can be dated by measurement of the intensity of ESR signals in quartz. These signals are reset by local lattice deformation and local frictional heating on grain contacts at the time of fault movement. The ESR signals then grow back as a result of bombardment by ionizing radiation from surrounding rocks. The age is obtained from the ratio of the equivalent dose, needed to produce the observed signal, to the dose rate. Fine grains are more completely reset during faulting, and a plot of age vs. grain size shows a plateau for grains below critical size; these grains are presumed to have been completely zeroed by the last fault activity. We carried out ESR dating of fault rocks collected near the Gori nuclear reactor. Most of the ESR signals of fault rocks collected from the basement are saturated. This indicates that the last movement of the faults had occurred before the Quaternary period. However, ESR dates from the Oyong fault zone range from 370 to 310 ka. Results of this research suggest that long-term cyclic fault activity of the Oyong fault zone continued into the Pleistocene

  20. Real-time fault diagnosis and fault-tolerant control

    OpenAIRE

    Gao, Zhiwei; Ding, Steven X.; Cecati, Carlo

    2015-01-01

    This "Special Section on Real-Time Fault Diagnosis and Fault-Tolerant Control" of the IEEE Transactions on Industrial Electronics is motivated to provide a forum for academic and industrial communities to report recent theoretic/application results in real-time monitoring, diagnosis, and fault-tolerant design, and exchange the ideas about the emerging research direction in this field. Twenty-three papers were eventually selected through a strict peer-reviewed procedure, which represent the mo...

  1. Power transmission line fault location based on current traveling waves

    Energy Technology Data Exchange (ETDEWEB)

    Elhaffar, A.M.

    2008-07-01

    Transmission lines are designed to transfer electric power from source locations to distribution networks. However, their lengths are exposed to various faults. Protective relay and fault recorder systems, based on fundamental power frequency signals, are installed to isolate and the faulty line and provide the fault position. However, the error is high especially in transmission lines. This thesis investigates the problem of fault localization using traveling wave current signals obtained at a single-end of a transmission line and/or at multi-ends of a transmission network. A review of various signal processing techniques is presented. The wavelet transform is found to be more accurate than conventional signal processing techniques for extracting the traveling wave signals from field measurements. In this thesis, an optimization method has been developed to select the best wavelet candidate from several mother wavelets. The optimum mother wavelet was selected and used to analyze the fault signal at different details' levels. The best details' level, which carries the fault features, was selected according to its energy content. From the line and network data, the traveling wave speed is calculated for each line using the optimum mother wavelet at different detail levels. Accurate determination fault location depends on the proper details wavelet level as well as the propagation speed. A high frequency current transformer model has been verified experimentally using impulse current signals at the high voltage laboratory, Helsinki University of Technology. Single-end method has been studied for several transmission line configurations, including lines equipped with/without overhead ground wires, counterpoises, or overhead ground wires and counterpoises. The time difference between the aerial and ground mode has also been investigated for these line configurations. Multi-ended method, using recordings sparsely located in the transmission network, has been

  2. Imaging of Subsurface Faults using Refraction Migration with Fault Flooding

    KAUST Repository

    Metwally, Ahmed Mohsen Hassan

    2017-05-31

    We propose a novel method for imaging shallow faults by migration of transmitted refraction arrivals. The assumption is that there is a significant velocity contrast across the fault boundary that is underlain by a refracting interface. This procedure, denoted as refraction migration with fault flooding, largely overcomes the difficulty in imaging shallow faults with seismic surveys. Numerical results successfully validate this method on three synthetic examples and two field-data sets. The first field-data set is next to the Gulf of Aqaba and the second example is from a seismic profile recorded in Arizona. The faults detected by refraction migration in the Gulf of Aqaba data were in agreement with those indicated in a P-velocity tomogram. However, a new fault is detected at the end of the migration image that is not clearly seen in the traveltime tomogram. This result is similar to that for the Arizona data where the refraction image showed faults consistent with those seen in the P-velocity tomogram, except it also detected an antithetic fault at the end of the line. This fault cannot be clearly seen in the traveltime tomogram due to the limited ray coverage.

  3. Fluid involvement in normal faulting

    Science.gov (United States)

    Sibson, Richard H.

    2000-04-01

    Evidence of fluid interaction with normal faults comes from their varied role as flow barriers or conduits in hydrocarbon basins and as hosting structures for hydrothermal mineralisation, and from fault-rock assemblages in exhumed footwalls of steep active normal faults and metamorphic core complexes. These last suggest involvement of predominantly aqueous fluids over a broad depth range, with implications for fault shear resistance and the mechanics of normal fault reactivation. A general downwards progression in fault rock assemblages (high-level breccia-gouge (often clay-rich) → cataclasites → phyllonites → mylonite → mylonitic gneiss with the onset of greenschist phyllonites occurring near the base of the seismogenic crust) is inferred for normal fault zones developed in quartzo-feldspathic continental crust. Fluid inclusion studies in hydrothermal veining from some footwall assemblages suggest a transition from hydrostatic to suprahydrostatic fluid pressures over the depth range 3-5 km, with some evidence for near-lithostatic to hydrostatic pressure cycling towards the base of the seismogenic zone in the phyllonitic assemblages. Development of fault-fracture meshes through mixed-mode brittle failure in rock-masses with strong competence layering is promoted by low effective stress in the absence of thoroughgoing cohesionless faults that are favourably oriented for reactivation. Meshes may develop around normal faults in the near-surface under hydrostatic fluid pressures to depths determined by rock tensile strength, and at greater depths in overpressured portions of normal fault zones and at stress heterogeneities, especially dilational jogs. Overpressures localised within developing normal fault zones also determine the extent to which they may reutilise existing discontinuities (for example, low-angle thrust faults). Brittle failure mode plots demonstrate that reactivation of existing low-angle faults under vertical σ1 trajectories is only likely if

  4. Wilshire fault: Earthquakes in Hollywood?

    Science.gov (United States)

    Hummon, Cheryl; Schneider, Craig L.; Yeats, Robert S.; Dolan, James F.; Sieh, Kerry E.; Huftile, Gary J.

    1994-04-01

    The Wilshire fault is a potentially seismogenic, blind thrust fault inferred to underlie and cause the Wilshire arch, a Quaternary fold in the Hollywood area, just west of downtown Los Angeles, California. Two inverse models, based on the Wilshire arch, allow us to estimate the location and slip rate of the Wilshire fault, which may be illuminated by a zone of microearthquakes. A fault-bend fold model indicates a reverse-slip rate of 1.5-1.9 mm/yr, whereas a three-dimensional elastic-dislocation model indicates a right-reverse slip rate of 2.6-3.2 mm/yr. The Wilshire fault is a previously unrecognized seismic hazard directly beneath Hollywood and Beverly Hills, distinct from the faults under the nearby Santa Monica Mountains.

  5. Fault Tolerant Wind Farm Control

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2013-01-01

    In the recent years the wind turbine industry has focused on optimizing the cost of energy. One of the important factors in this is to increase reliability of the wind turbines. Advanced fault detection, isolation and accommodation are important tools in this process. Clearly most faults are dealt...... with best at a wind turbine control level. However, some faults are better dealt with at the wind farm control level, if the wind turbine is located in a wind farm. In this paper a benchmark model for fault detection and isolation, and fault tolerant control of wind turbines implemented at the wind farm...... control level is presented. The benchmark model includes a small wind farm of nine wind turbines, based on simple models of the wind turbines as well as the wind and interactions between wind turbines in the wind farm. The model includes wind and power references scenarios as well as three relevant fault...

  6. A review on data-driven fault severity assessment in rolling bearings

    Science.gov (United States)

    Cerrada, Mariela; Sánchez, René-Vinicio; Li, Chuan; Pacheco, Fannia; Cabrera, Diego; Valente de Oliveira, José; Vásquez, Rafael E.

    2018-01-01

    Health condition monitoring of rotating machinery is a crucial task to guarantee reliability in industrial processes. In particular, bearings are mechanical components used in most rotating devices and they represent the main source of faults in such equipments; reason for which research activities on detecting and diagnosing their faults have increased. Fault detection aims at identifying whether the device is or not in a fault condition, and diagnosis is commonly oriented towards identifying the fault mode of the device, after detection. An important step after fault detection and diagnosis is the analysis of the magnitude or the degradation level of the fault, because this represents a support to the decision-making process in condition based-maintenance. However, no extensive works are devoted to analyse this problem, or some works tackle it from the fault diagnosis point of view. In a rough manner, fault severity is associated with the magnitude of the fault. In bearings, fault severity can be related to the physical size of fault or a general degradation of the component. Due to literature regarding the severity assessment of bearing damages is limited, this paper aims at discussing the recent methods and techniques used to achieve the fault severity evaluation in the main components of the rolling bearings, such as inner race, outer race, and ball. The review is mainly focused on data-driven approaches such as signal processing for extracting the proper fault signatures associated with the damage degradation, and learning approaches that are used to identify degradation patterns with regards to health conditions. Finally, new challenges are highlighted in order to develop new contributions in this field.

  7. A Method for Aileron Actuator Fault Diagnosis Based on PCA and PGC-SVM

    Directory of Open Access Journals (Sweden)

    Wei-Li Qin

    2016-01-01

    Full Text Available Aileron actuators are pivotal components for aircraft flight control system. Thus, the fault diagnosis of aileron actuators is vital in the enhancement of the reliability and fault tolerant capability. This paper presents an aileron actuator fault diagnosis approach combining principal component analysis (PCA, grid search (GS, 10-fold cross validation (CV, and one-versus-one support vector machine (SVM. This method is referred to as PGC-SVM and utilizes the direct drive valve input, force motor current, and displacement feedback signal to realize fault detection and location. First, several common faults of aileron actuators, which include force motor coil break, sensor coil break, cylinder leakage, and amplifier gain reduction, are extracted from the fault quadrantal diagram; the corresponding fault mechanisms are analyzed. Second, the data feature extraction is performed with dimension reduction using PCA. Finally, the GS and CV algorithms are employed to train a one-versus-one SVM for fault classification, thus obtaining the optimal model parameters and assuring the generalization of the trained SVM, respectively. To verify the effectiveness of the proposed approach, four types of faults are introduced into the simulation model established by AMESim and Simulink. The results demonstrate its desirable diagnostic performance which outperforms that of the traditional SVM by comparison.

  8. All Roads Lead to Fault Diagnosis : Model-Based Reasoning with LYDIA

    NARCIS (Netherlands)

    Feldman, A.B.; Pietersma, J.; Van Gemund, A.J.C.

    2006-01-01

    Model-Based Reasoning (MBR) over qualitative models of complex, real-world systems has proven succesful for automated fault diagnosis, control, and repair. Expressing a system under diagnosis in a formal model and infering a diagnosis given observations are both challenging problems. In this paper

  9. Automated diagnostics scoping study. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Quadrel, R.W.; Lash, T.A.

    1994-06-01

    The objective of the Automated Diagnostics Scoping Study was to investigate the needs for diagnostics in building operation and to examine some of the current technologies in automated diagnostics that can address these needs. The study was conducted in two parts. In the needs analysis, the authors interviewed facility managers and engineers at five building sites. In the technology survey, they collected published information on automated diagnostic technologies in commercial and military applications as well as on technologies currently under research. The following describe key areas that the authors identify for the research, development, and deployment of automated diagnostic technologies: tools and techniques to aid diagnosis during building commissioning, especially those that address issues arising from integrating building systems and diagnosing multiple simultaneous faults; technologies to aid diagnosis for systems and components that are unmonitored or unalarmed; automated capabilities to assist cause-and-effect exploration during diagnosis; inexpensive, reliable sensors, especially those that expand the current range of sensory input; technologies that aid predictive diagnosis through trend analysis; integration of simulation and optimization tools with building automation systems to optimize control strategies and energy performance; integration of diagnostic, control, and preventive maintenance technologies. By relating existing technologies to perceived and actual needs, the authors reached some conclusions about the opportunities for automated diagnostics in building operation. Some of a building operator`s needs can be satisfied by off-the-shelf hardware and software. Other needs are not so easily satisfied, suggesting directions for future research. Their conclusions and suggestions are offered in the final section of this study.

  10. 20 CFR 404.507 - Fault.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Fault. 404.507 Section 404.507 Employees... Officer § 404.507 Fault. Fault as used in without fault (see § 404.506 and 42 CFR 405.355) applies only to the individual. Although the Administration may have been at fault in making the overpayment, that...

  11. Final Technical Report: PV Fault Detection Tool.

    Energy Technology Data Exchange (ETDEWEB)

    King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    The PV Fault Detection Tool project plans to demonstrate that the FDT can (a) detect catastrophic and degradation faults and (b) identify the type of fault. This will be accomplished by collecting fault signatures using different instruments and integrating this information to establish a logical controller for detecting, diagnosing and classifying each fault.

  12. Human-centered automation and AI - Ideas, insights, and issues from the Intelligent Cockpit Aids research effort

    Science.gov (United States)

    Abbott, Kathy H.; Schutte, Paul C.

    1989-01-01

    A development status evaluation is presented for the NASA-Langley Intelligent Cockpit Aids research program, which encompasses AI, human/machine interfaces, and conventional automation. Attention is being given to decision-aiding concepts for human-centered automation, with emphasis on inflight subsystem fault management, inflight mission replanning, and communications management. The cockpit envisioned is for advanced commercial transport aircraft.

  13. An Overview of Transmission Line Protection by Artificial Neural Network: Fault Detection, Fault Classification, Fault Location, and Fault Direction Discrimination

    Directory of Open Access Journals (Sweden)

    Anamika Yadav

    2014-01-01

    Full Text Available Contemporary power systems are associated with serious issues of faults on high voltage transmission lines. Instant isolation of fault is necessary to maintain the system stability. Protective relay utilizes current and voltage signals to detect, classify, and locate the fault in transmission line. A trip signal will be sent by the relay to a circuit breaker with the purpose of disconnecting the faulted line from the rest of the system in case of a disturbance for maintaining the stability of the remaining healthy system. This paper focuses on the studies of fault detection, fault classification, fault location, fault phase selection, and fault direction discrimination by using artificial neural networks approach. Artificial neural networks are valuable for power system applications as they can be trained with offline data. Efforts have been made in this study to incorporate and review approximately all important techniques and philosophies of transmission line protection reported in the literature till June 2014. This comprehensive and exhaustive survey will reduce the difficulty of new researchers to evaluate different ANN based techniques with a set of references of all concerned contributions.

  14. Advanced cloud fault tolerance system

    Science.gov (United States)

    Sumangali, K.; Benny, Niketa

    2017-11-01

    Cloud computing has become a prevalent on-demand service on the internet to store, manage and process data. A pitfall that accompanies cloud computing is the failures that can be encountered in the cloud. To overcome these failures, we require a fault tolerance mechanism to abstract faults from users. We have proposed a fault tolerant architecture, which is a combination of proactive and reactive fault tolerance. This architecture essentially increases the reliability and the availability of the cloud. In the future, we would like to compare evaluations of our proposed architecture with existing architectures and further improve it.

  15. Seismological Studies for Tensile Faults

    Directory of Open Access Journals (Sweden)

    Gwo-Bin Ou

    2008-01-01

    Full Text Available A shear slip fault, an equivalence of a double couple source, has often been assumed to be a kinematic source model in ground motion simulation. Estimation of seismic moment based on the shear slip model indicates the size of an earthquake. However, if the dislocation of the hanging wall relative to the footwall includes not only a shear slip tangent to the fault plane but also expansion and compression normal to the fault plane, the radiating seismic waves will feature differences from those out of the shear slip fault. Taking account of the effects resulting from expansion and compression to a fault plane, we can resolve the tension and pressure axes as well as the fault plane solution more exactly from ground motions than previously, and can evaluate how far a fault zone opens or contracts during a developing rupture. In addition to a tensile angle and Poisson¡¦s ratio for the medium, a tensile fault with five degrees of freedom has been extended from the shear slip fault with only three degrees of freedom, strike, dip, and slip.

  16. SEISMOLOGY: Watching the Hayward Fault.

    Science.gov (United States)

    Simpson, R W

    2000-08-18

    The Hayward fault, located on the east side of the San Francisco Bay, represents a natural laboratory for seismologists, because it does not sleep silently between major earthquakes. In his Perspective, Simpson discusses the study by Bürgmann et al., who have used powerful new techniques to study the fault. The results indicate that major earthquakes cannot originate in the northern part of the fault. However, surface-rupturing earthquakes have occurred in the area, suggesting that they originated to the north or south of the segment studied by Bürgmann et al. Fundamental questions remain regarding the mechanism by which plate tectonic stresses are transferred to the Hayward fault.

  17. Fault-Tree Compiler Program

    Science.gov (United States)

    Butler, Ricky W.; Martensen, Anna L.

    1992-01-01

    FTC, Fault-Tree Compiler program, is reliability-analysis software tool used to calculate probability of top event of fault tree. Five different types of gates allowed in fault tree: AND, OR, EXCLUSIVE OR, INVERT, and M OF N. High-level input language of FTC easy to understand and use. Program supports hierarchical fault-tree-definition feature simplifying process of description of tree and reduces execution time. Solution technique implemented in FORTRAN, and user interface in Pascal. Written to run on DEC VAX computer operating under VMS operating system.

  18. In-flight Fault Detection and Isolation in Aircraft Flight Control Systems

    Science.gov (United States)

    Azam, Mohammad; Pattipati, Krishna; Allanach, Jeffrey; Poll, Scott; Patterson-Hine, Ann

    2005-01-01

    In this paper we consider the problem of test design for real-time fault detection and isolation (FDI) in the flight control system of fixed-wing aircraft. We focus on the faults that are manifested in the control surface elements (e.g., aileron, elevator, rudder and stabilizer) of an aircraft. For demonstration purposes, we restrict our focus on the faults belonging to nine basic fault classes. The diagnostic tests are performed on the features extracted from fifty monitored system parameters. The proposed tests are able to uniquely isolate each of the faults at almost all severity levels. A neural network-based flight control simulator, FLTZ(Registered TradeMark), is used for the simulation of various faults in fixed-wing aircraft flight control systems for the purpose of FDI.

  19. A Spectrum Detection Approach for Bearing Fault Signal Based on Spectral Kurtosis

    Directory of Open Access Journals (Sweden)

    Yunfeng Li

    2017-01-01

    Full Text Available According to the similarity between Morlet wavelet and fault signal and the sensitive characteristics of spectral kurtosis for the impact signal, a new wavelet spectrum detection approach based on spectral kurtosis for bearing fault signal is proposed. This method decreased the band-pass filter range and reduced the wavelet window width significantly. As a consequence, the bearing fault signal was detected adaptively, and time-frequency characteristics of the fault signal can be extracted accurately. The validity of this method was verified by the identifications of simulated shock signal and test bearing fault signal. The method provides a new understanding of wavelet spectrum detection based on spectral kurtosis for rolling element bearing fault signal.

  20. Fault Severity Estimation of Rotating Machinery Based on Residual Signals

    Directory of Open Access Journals (Sweden)

    Fan Jiang

    2012-01-01

    Full Text Available Fault severity estimation is an important part of a condition-based maintenance system, which can monitor the performance of an operation machine and enhance its level of safety. In this paper, a novel method based on statistical property and residual signals is developed for estimating the fault severity of rotating machinery. The fast Fourier transformation (FFT is applied to extract the so-called multifrequency-band energy (MFBE from the vibration signals of rotating machinery with different fault severity levels in the first stage. Usually these features of the working conditions with different fault sensitivities are different. Therefore a sensitive features-selecting algorithm is defined to construct the feature matrix and calculate the statistic parameter (mean in the second stage. In the last stage, the residual signals computed by the zero space vector are used to estimate the fault severity. Simulation and experimental results reveal that the proposed method based on statistics and residual signals is effective and feasible for estimating the severity of a rotating machine fault.

  1. A Fault Recognition System for Gearboxes of Wind Turbines

    Science.gov (United States)

    Yang, Zhiling; Huang, Haiyue; Yin, Zidong

    2017-12-01

    Costs of maintenance and loss of power generation caused by the faults of wind turbines gearboxes are the main components of operation costs for a wind farm. Therefore, the technology of condition monitoring and fault recognition for wind turbines gearboxes is becoming a hot topic. A condition monitoring and fault recognition system (CMFRS) is presented for CBM of wind turbines gearboxes in this paper. The vibration signals from acceleration sensors at different locations of gearbox and the data from supervisory control and data acquisition (SCADA) system are collected to CMFRS. Then the feature extraction and optimization algorithm is applied to these operational data. Furthermore, to recognize the fault of gearboxes, the GSO-LSSVR algorithm is proposed, combining the least squares support vector regression machine (LSSVR) with the Glowworm Swarm Optimization (GSO) algorithm. Finally, the results show that the fault recognition system used in this paper has a high rate for identifying three states of wind turbines’ gears; besides, the combination of date features can affect the identifying rate and the selection optimization algorithm presented in this paper can get a pretty good date feature subset for the fault recognition.

  2. Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Jinde Zheng

    2014-01-01

    Full Text Available A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE, Laplacian score (LS, and support vector machines (SVMs is proposed in this paper. Permutation entropy (PE was recently proposed and defined to measure the randomicity and detect dynamical changes of time series. However, for the complexity of mechanical systems, the randomicity and dynamic changes of the vibration signal will exist in different scales. Thus, the definition of MPE is introduced and employed to extract the nonlinear fault characteristics from the bearing vibration signal in different scales. Besides, the SVM is utilized to accomplish the fault feature classification to fulfill diagnostic procedure automatically. Meanwhile, in order to avoid a high dimension of features, the Laplacian score (LS is used to refine the feature vector by ranking the features according to their importance and correlations with the main fault information. Finally, the rolling bearing fault diagnosis method based on MPE, LS, and SVM is proposed and applied to the experimental data. The experimental data analysis results indicate that the proposed method could identify the fault categories effectively.

  3. Rolling Bearing Fault Diagnosis Based on an Improved HTT Transform.

    Science.gov (United States)

    Pang, Bin; Tang, Guiji; Tian, Tian; Zhou, Chong

    2018-04-14

    When rolling bearing failure occurs, vibration signals generally contain different signal components, such as impulsive fault feature signals, background noise and harmonic interference signals. One of the most challenging aspects of rolling bearing fault diagnosis is how to inhibit noise and harmonic interference signals, while enhancing impulsive fault feature signals. This paper presents a novel bearing fault diagnosis method, namely an improved Hilbert time-time (IHTT) transform, by combining a Hilbert time-time (HTT) transform with principal component analysis (PCA). Firstly, the HTT transform was performed on vibration signals to derive a HTT transform matrix. Then, PCA was employed to de-noise the HTT transform matrix in order to improve the robustness of the HTT transform. Finally, the diagonal time series of the de-noised HTT transform matrix was extracted as the enhanced impulsive fault feature signal and the contained fault characteristic information was identified through further analyses of amplitude and envelope spectrums. Both simulated and experimental analyses validated the superiority of the presented method for detecting bearing failures.

  4. Planetary gearbox fault diagnosis using an adaptive stochastic resonance method

    Science.gov (United States)

    Lei, Yaguo; Han, Dong; Lin, Jing; He, Zhengjia

    2013-07-01

    Planetary gearboxes are widely used in aerospace, automotive and heavy industry applications due to their large transmission ratio, strong load-bearing capacity and high transmission efficiency. The tough operation conditions of heavy duty and intensive impact load may cause gear tooth damage such as fatigue crack and teeth missed etc. The challenging issues in fault diagnosis of planetary gearboxes include selection of sensitive measurement locations, investigation of vibration transmission paths and weak feature extraction. One of them is how to effectively discover the weak characteristics from noisy signals of faulty components in planetary gearboxes. To address the issue in fault diagnosis of planetary gearboxes, an adaptive stochastic resonance (ASR) method is proposed in this paper. The ASR method utilizes the optimization ability of ant colony algorithms and adaptively realizes the optimal stochastic resonance system matching input signals. Using the ASR method, the noise may be weakened and weak characteristics highlighted, and therefore the faults can be diagnosed accurately. A planetary gearbox test rig is established and experiments with sun gear faults including a chipped tooth and a missing tooth are conducted. And the vibration signals are collected under the loaded condition and various motor speeds. The proposed method is used to process the collected signals and the results of feature extraction and fault diagnosis demonstrate its effectiveness.

  5. Fault current limiter

    Science.gov (United States)

    Darmann, Francis Anthony

    2013-10-08

    A fault current limiter (FCL) includes a series of high permeability posts for collectively define a core for the FCL. A DC coil, for the purposes of saturating a portion of the high permeability posts, surrounds the complete structure outside of an enclosure in the form of a vessel. The vessel contains a dielectric insulation medium. AC coils, for transporting AC current, are wound on insulating formers and electrically interconnected to each other in a manner such that the senses of the magnetic field produced by each AC coil in the corresponding high permeability core are opposing. There are insulation barriers between phases to improve dielectric withstand properties of the dielectric medium.

  6. Thruster fault identification method for autonomous underwater vehicle using peak region energy and least square grey relational grade

    Directory of Open Access Journals (Sweden)

    Mingjun Zhang

    2015-12-01

    Full Text Available A novel thruster fault identification method for autonomous underwater vehicle is presented in this article. It uses the proposed peak region energy method to extract fault feature and uses the proposed least square grey relational grade method to estimate fault degree. The peak region energy method is developed from fusion feature modulus maximum method. It applies the fusion feature modulus maximum method to get fusion feature and then regards the maximum of peak region energy in the convolution operation results of fusion feature as fault feature. The least square grey relational grade method is developed from grey relational analysis algorithm. It determines the fault degree interval by the grey relational analysis algorithm and then estimates fault degree in the interval by least square algorithm. Pool experiments of the experimental prototype are conducted to verify the effectiveness of the proposed methods. The experimental results show that the fault feature extracted by the peak region energy method is monotonic to fault degree while the one extracted by the fusion feature modulus maximum method is not. The least square grey relational grade method can further get an estimation result between adjacent standard fault degrees while the estimation result of the grey relational analysis algorithm is just one of the standard fault degrees.

  7. Blind Source Separation and Dynamic Fuzzy Neural Network for Fault Diagnosis in Machines

    International Nuclear Information System (INIS)

    Huang, Haifeng; Ouyang, Huajiang; Gao, Hongli

    2015-01-01

    Many assessment and detection methods are used to diagnose faults in machines. High accuracy in fault detection and diagnosis can be achieved by using numerical methods with noise-resistant properties. However, to some extent, noise always exists in measured data on real machines, which affects the identification results, especially in the diagnosis of early- stage faults. In view of this situation, a damage assessment method based on blind source separation and dynamic fuzzy neural network (DFNN) is presented to diagnose the early-stage machinery faults in this paper. In the processing of measurement signals, blind source separation is adopted to reduce noise. Then sensitive features of these faults are obtained by extracting low dimensional manifold characteristics from the signals. The model for fault diagnosis is established based on DFNN. Furthermore, on-line computation is accelerated by means of compressed sensing. Numerical vibration signals of ball screw fault modes are processed on the model for mechanical fault diagnosis and the results are in good agreement with the actual condition even at the early stage of fault development. This detection method is very useful in practice and feasible for early-stage fault diagnosis. (paper)

  8. Simultaneous-Fault Diagnosis of Automotive Engine Ignition Systems Using Prior Domain Knowledge and Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Chi-Man Vong

    2013-01-01

    Full Text Available Engine ignition patterns can be analyzed to identify the engine fault according to both the specific prior domain knowledge and the shape features of the patterns. One of the challenges in ignition system diagnosis is that more than one fault may appear at a time. This kind of problem refers to simultaneous-fault diagnosis. Another challenge is the acquisition of a large amount of costly simultaneous-fault ignition patterns for constructing the diagnostic system because the number of the training patterns depends on the combination of different single faults. The above problems could be resolved by the proposed framework combining feature extraction, probabilistic classification, and decision threshold optimization. With the proposed framework, the features of the single faults in a simultaneous-fault pattern are extracted and then detected using a new probabilistic classifier, namely, pairwise coupling relevance vector machine, which is trained with single-fault patterns only. Therefore, the training dataset of simultaneous-fault patterns is not necessary. Experimental results show that the proposed framework performs well for both single-fault and simultaneous-fault diagnoses and is superior to the existing approach.

  9. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor

    2016-08-26

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

  10. An artificial intelligence approach to onboard fault monitoring and diagnosis for aircraft applications

    Science.gov (United States)

    Schutte, P. C.; Abbott, K. H.

    1986-01-01

    Real-time onboard fault monitoring and diagnosis for aircraft applications, whether performed by the human pilot or by automation, presents many difficult problems. Quick response to failures may be critical, the pilot often must compensate for the failure while diagnosing it, his information about the state of the aircraft is often incomplete, and the behavior of the aircraft changes as the effect of the failure propagates through the system. A research effort was initiated to identify guidelines for automation of onboard fault monitoring and diagnosis and associated crew interfaces. The effort began by determining the flight crew's information requirements for fault monitoring and diagnosis and the various reasoning strategies they use. Based on this information, a conceptual architecture was developed for the fault monitoring and diagnosis process. This architecture represents an approach and a framework which, once incorporated with the necessary detail and knowledge, can be a fully operational fault monitoring and diagnosis system, as well as providing the basis for comparison of this approach to other fault monitoring and diagnosis concepts. The architecture encompasses all aspects of the aircraft's operation, including navigation, guidance and controls, and subsystem status. The portion of the architecture that encompasses subsystem monitoring and diagnosis was implemented for an aircraft turbofan engine to explore and demonstrate the AI concepts involved. This paper describes the architecture and the implementation for the engine subsystem.

  11. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor

    2016-08-01

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

  12. Feature fusion using kernel joint approximate diagonalization of eigen-matrices for rolling bearing fault identification

    Science.gov (United States)

    Liu, Yongbin; He, Bing; Liu, Fang; Lu, Siliang; Zhao, Yilei

    2016-12-01

    Fault pattern identification is a crucial step for the intelligent fault diagnosis of real-time health conditions in monitoring a mechanical system. However, many challenges exist in extracting the effective feature from vibration signals for fault recognition. A new feature fusion method is proposed in this study to extract new features using kernel joint approximate diagonalization of eigen-matrices (KJADE). In the method, the input space that is composed of original features is mapped into a high-dimensional feature space by nonlinear mapping. Then, the new features can be estimated through the eigen-decomposition of the fourth-order cumulative kernel matrix obtained from the feature space. Therefore, the proposed method could be used to reduce data redundancy because it extracts the inherent pattern structure of different fault classes as it is nonlinear by nature. The integration evaluation factor of between-class and within-class scatters (SS) is employed to depict the clustering performance quantitatively, and the new feature subset extracted by the proposed method is fed into a multi-class support vector machine for fault pattern identification. Finally, the effectiveness of the proposed method is verified by experimental vibration signals with different bearing fault types and severities. Results of several cases show that the KJADE algorithm is efficient in feature fusion for bearing fault identification.

  13. Central Asia Active Fault Database

    Science.gov (United States)

    Mohadjer, Solmaz; Ehlers, Todd A.; Kakar, Najibullah

    2014-05-01

    The ongoing collision of the Indian subcontinent with Asia controls active tectonics and seismicity in Central Asia. This motion is accommodated by faults that have historically caused devastating earthquakes and continue to pose serious threats to the population at risk. Despite international and regional efforts to assess seismic hazards in Central Asia, little attention has been given to development of a comprehensive database for active faults in the region. To address this issue and to better understand the distribution and level of seismic hazard in Central Asia, we are developing a publically available database for active faults of Central Asia (including but not limited to Afghanistan, Tajikistan, Kyrgyzstan, northern Pakistan and western China) using ArcGIS. The database is designed to allow users to store, map and query important fault parameters such as fault location, displacement history, rate of movement, and other data relevant to seismic hazard studies including fault trench locations, geochronology constraints, and seismic studies. Data sources integrated into the database include previously published maps and scientific investigations as well as strain rate measurements and historic and recent seismicity. In addition, high resolution Quickbird, Spot, and Aster imagery are used for selected features to locate and measure offset of landforms associated with Quaternary faulting. These features are individually digitized and linked to attribute tables that provide a description for each feature. Preliminary observations include inconsistent and sometimes inaccurate information for faults documented in different studies. For example, the Darvaz-Karakul fault which roughly defines the western margin of the Pamir, has been mapped with differences in location of up to 12 kilometers. The sense of motion for this fault ranges from unknown to thrust and strike-slip in three different studies despite documented left-lateral displacements of Holocene and late

  14. Fault Monitooring and Fault Recovery Control for Position Moored Tanker

    DEFF Research Database (Denmark)

    Fang, Shaoji; Blanke, Mogens

    2009-01-01

    This paper addresses fault tolerant control for position mooring of a shuttle tanker operating in the North Sea. A complete framework for fault diagnosis is presented but the loss of a sub-sea mooring line buoyancy element is given particular attention, since this fault could lead to line breakage...... and risky abortion of an oil-loading operation. With signicant drift forces from waves, non-Gaussian elements dominate in residuals and fault diagnosis need be designed using dedicated change detection for the type of distribution encountered. In addition to dedicated diagnosis, an optimal position...... algorithm is proposed to accommodate buoyancy element failure and keep the mooring system in a safe state. Detection properties and fault-tolerant control are demonstrated by high delity simulations...

  15. Fault shear stiffness as the key parameter determining fault behavior

    Science.gov (United States)

    Ostapchuk, A. A.; Kocharyan, G. G.; Pavlov, D. V.; Kabychenko, N. V.

    2017-12-01

    Presented are the results of laboratory experiments on studying the variation of fault shear stiffness during a seismic cycle. It is shown that the slip mode correlates well with the specific value of fault stiffness ks1 at the loading stage. As the fault goes over to a metastable state, its stiffness changes abruptly from ks1 to 0. This change can be detected in active monitoring, which consists in analyzing the frequency response of an oscillatory "block-fault" system. A periodic pulsed action on the "block-fault" system allowed us to reliably detect a relative decrease by 30% of the resonance frequency of its response when the system goes over to the metastable state.

  16. Automated uranium determination in solutions

    International Nuclear Information System (INIS)

    Radil, V.; Bankova, Z.; Homolka, V.

    1983-01-01

    An extraction spectrophotometric method was developed for the automated determination of uranium in solutions used in chemical extraction and hydrometallurgical processing of uranium ore. The method is based on the separation of uranium from accompanying elements by extraction from the 6 N HCl medium using tributyl phosphate and on its reaction with the arsenazo 3 reagent in the single phase medium tributyl phosphate - benzene - ethanol - water. An analyzer has been designed and constructed operating on the same principle. The analyzer is discontinuous, peristaltic pumps are used for mixing and dosing the solutions. The evaluation cycle is electronically controlled, the results are recorded with a recorder or digital voltmeter with a printer. (M.D.)

  17. Fault Management Design Strategies

    Science.gov (United States)

    Day, John C.; Johnson, Stephen B.

    2014-01-01

    Development of dependable systems relies on the ability of the system to determine and respond to off-nominal system behavior. Specification and development of these fault management capabilities must be done in a structured and principled manner to improve our understanding of these systems, and to make significant gains in dependability (safety, reliability and availability). Prior work has described a fundamental taxonomy and theory of System Health Management (SHM), and of its operational subset, Fault Management (FM). This conceptual foundation provides a basis to develop framework to design and implement FM design strategies that protect mission objectives and account for system design limitations. Selection of an SHM strategy has implications for the functions required to perform the strategy, and it places constraints on the set of possible design solutions. The framework developed in this paper provides a rigorous and principled approach to classifying SHM strategies, as well as methods for determination and implementation of SHM strategies. An illustrative example is used to describe the application of the framework and the resulting benefits to system and FM design and dependability.

  18. Fault location using synchronized sequence measurements

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Chun; Jia, Qing-Quan; Li, Xin-Bin; Dou, Chun-Xia [Department of Power Electrical Engineering, Yanshan University, Qinhuangdao 066004 (China)

    2008-02-15

    This paper proposes fault location formulas using synchronized sequence measurements. For earth faults, zero-sequence voltages and currents at two terminals of faulted line are applied to fault location. Negative-sequence measurements are utilized for asymmetrical faults and positive-sequence measurements are used for three-phase faults. The fault location formulas are derived from a fault location technique [Wang C, Dou C, Li X, Jia Q. A WAMS/PMU-based fault location technique. Elect Power Syst Res 2007;77(8):936-945] based on WAMS/PMU. The technique uses synchronized fault voltages measured by PMUs in power network. The formulas are simple and are easy for application. Case studies on a testing network with 500 kV transmission lines including ATP/EMTP simulations are presented. Various fault types and fault resistances are also considered. (author)

  19. Autonomy and Automation

    Science.gov (United States)

    Shively, Jay

    2017-01-01

    A significant level of debate and confusion has surrounded the meaning of the terms autonomy and automation. Automation is a multi-dimensional concept, and we propose that Remotely Piloted Aircraft Systems (RPAS) automation should be described with reference to the specific system and task that has been automated, the context in which the automation functions, and other relevant dimensions. In this paper, we present definitions of automation, pilot in the loop, pilot on the loop and pilot out of the loop. We further propose that in future, the International Civil Aviation Organization (ICAO) RPAS Panel avoids the use of the terms autonomy and autonomous when referring to automated systems on board RPA. Work Group 7 proposes to develop, in consultation with other workgroups, a taxonomy of Levels of Automation for RPAS.

  20. An automated swimming respirometer

    DEFF Research Database (Denmark)

    STEFFENSEN, JF; JOHANSEN, K; BUSHNELL, PG

    1984-01-01

    An automated respirometer is described that can be used for computerized respirometry of trout and sharks.......An automated respirometer is described that can be used for computerized respirometry of trout and sharks....

  1. Configuration Management Automation (CMA) -

    Data.gov (United States)

    Department of Transportation — Configuration Management Automation (CMA) will provide an automated, integrated enterprise solution to support CM of FAA NAS and Non-NAS assets and investments. CMA...

  2. Semi-automatic mapping of fault rocks on a Digital Outcrop Model, Gole Larghe Fault Zone (Southern Alps, Italy)

    Science.gov (United States)

    Mittempergher, Silvia; Vho, Alice; Bistacchi, Andrea

    2016-04-01

    them with respect to biotite. In higher resolution images this could be performed using circularity and size thresholds, however this could not be easily implemented in an automated procedure since the thresholds must be varied by the interpreter almost for each image. In 1 x 1 m images the resolution is generally too low to distinguish cataclasite and pseudotachylyte, so most of the time fault rocks were treated together. For this analysis we developed a fully automated workflow that, after applying noise correction, classification and skeletonization algorithms, returns labeled edge images of fault segments together with vector polylines associated to edge properties. Vector and edge properties represent a useful format to perform further quantitative analysis, for instance for classifying fault segments based on structural criteria, detect continuous fault traces, and detect the kind of termination of faults/fractures. This approach allows to collect statistically relevant datasets useful for further quantitative structural analysis.

  3. Sensors and Automated Analyzers for Radionuclides

    International Nuclear Information System (INIS)

    Grate, Jay W.; Egorov, Oleg B.

    2003-01-01

    The production of nuclear weapons materials has generated large quantities of nuclear waste and significant environmental contamination. We have developed new, rapid, automated methods for determination of radionuclides using sequential injection methodologies to automate extraction chromatographic separations, with on-line flow-through scintillation counting for real time detection. This work has progressed in two main areas: radionuclide sensors for water monitoring and automated radiochemical analyzers for monitoring nuclear waste processing operations. Radionuclide sensors have been developed that collect and concentrate radionuclides in preconcentrating minicolumns with dual functionality: chemical selectivity for radionuclide capture and scintillation for signal output. These sensors can detect pertechnetate to below regulatory levels and have been engineered into a prototype for field testing. A fully automated process monitor has been developed for total technetium in nuclear waste streams. This instrument performs sample acidification, speciation adjustment, separation and detection in fifteen minutes or less

  4. Automated Sleep Stage Scoring by Decision Tree Learning

    National Research Council Canada - National Science Library

    Hanaoka, Masaaki

    2001-01-01

    In this paper we describe a waveform recognition method that extracts characteristic parameters from wave- forms and a method of automated sleep stage scoring using decision tree learning that is in...

  5. Techniques for Diagnosing Software Faults

    NARCIS (Netherlands)

    Abreu, R.F.; Zoeteweij, P.; Van Gemund, A.J.C.

    2008-01-01

    This technical report is meant to report our findings and ideas with respect to spectrum-based fault localization and modelbased diagnosis. In the following we want to introduce and compare model-based diagnosis (MBD), spectrum-based fault localization (SFL) and our contributions using 3-inverters

  6. Data-driven simultaneous fault diagnosis for solid oxide fuel cell system using multi-label pattern identification

    Science.gov (United States)

    Li, Shuanghong; Cao, Hongliang; Yang, Yupu

    2018-02-01

    Fault diagnosis is a key process for the reliability and safety of solid oxide fuel cell (SOFC) systems. However, it is difficult to rapidly and accurately identify faults for complicated SOFC systems, especially when simultaneous faults appear. In this research, a data-driven Multi-Label (ML) pattern identification approach is proposed to address the simultaneous fault diagnosis of SOFC systems. The framework of the simultaneous-fault diagnosis primarily includes two components: feature extraction and ML-SVM classifier. The simultaneous-fault diagnosis approach can be trained to diagnose simultaneous SOFC faults, such as fuel leakage, air leakage in different positions in the SOFC system, by just using simple training data sets consisting only single fault and not demanding simultaneous faults data. The experimental result shows the proposed framework can diagnose the simultaneous SOFC system faults with high accuracy requiring small number training data and low computational burden. In addition, Fault Inference Tree Analysis (FITA) is employed to identify the correlations among possible faults and their corresponding symptoms at the system component level.

  7. Clay mineral formation and fabric development in the DFDP-1B borehole, central Alpine Fault, New Zealand

    International Nuclear Information System (INIS)

    Schleicher, A.M.; Sutherland, R.; Townend, J.; Toy, V.G.; Van der Pluijm, B.A.

    2015-01-01

    Clay minerals are increasingly recognised as important controls on the state and mechanical behaviour of fault systems in the upper crust. Samples retrieved by shallow drilling from two principal slip zones within the central Alpine Fault, South Island, New Zealand, offer an excellent opportunity to investigate clay formation and fluid-rock interaction in an active fault zone. Two shallow boreholes, DFDP-1A (100.6 m deep) and DFDP-1B (151.4 m) were drilled in Phase 1 of the Deep Fault Drilling Project (DFDP-1) in 2011. We provide a mineralogical and textural analysis of clays in fault gouge extracted from the Alpine Fault. Newly formed smectitic clays are observed solely in the narrow zones of fault gouge in drill core, indicating that localised mineral reactions are restricted to the fault zone. The weak preferred orientation of the clay minerals in the fault gouge indicates minimal strain-driven modification of rock fabrics. While limited in extent, our results support observations from surface outcrops and faults systems elsewhere regarding the key role of clays in fault zones and emphasise the need for future, deeper drilling into the Alpine Fault in order to understand correlative mineralogies and fabrics as a function of higher temperature and pressure conditions. (author).

  8. Automation in College Libraries.

    Science.gov (United States)

    Werking, Richard Hume

    1991-01-01

    Reports the results of a survey of the "Bowdoin List" group of liberal arts colleges. The survey obtained information about (1) automation modules in place and when they had been installed; (2) financing of automation and its impacts on the library budgets; and (3) library director's views on library automation and the nature of the…

  9. Application of SVM and SVD Technique Based on EMD to the Fault Diagnosis of the Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Junsheng Cheng

    2009-01-01

    Full Text Available Targeting the characteristics that periodic impulses usually occur whilst the rotating machinery exhibits local faults and the limitations of singular value decomposition (SVD techniques, the SVD technique based on empirical mode decomposition (EMD is applied to the fault feature extraction of the rotating machinery vibration signals. The EMD method is used to decompose the vibration signal into a number of intrinsic mode functions (IMFs by which the initial feature vector matrices could be formed automatically. By applying the SVD technique to the initial feature vector matrices, the singular values of matrices could be obtained, which could be used as the fault feature vectors of support vector machines (SVMs classifier. The analysis results from the gear and roller bearing vibration signals show that the fault diagnosis method based on EMD, SVD and SVM can extract fault features effectively and classify working conditions and fault patterns of gears and roller bearings accurately even when the number of samples is small.

  10. Fault tolerant control for switched linear systems

    CERN Document Server

    Du, Dongsheng; Shi, Peng

    2015-01-01

    This book presents up-to-date research and novel methodologies on fault diagnosis and fault tolerant control for switched linear systems. It provides a unified yet neat framework of filtering, fault detection, fault diagnosis and fault tolerant control of switched systems. It can therefore serve as a useful textbook for senior and/or graduate students who are interested in knowing the state-of-the-art of filtering, fault detection, fault diagnosis and fault tolerant control areas, as well as recent advances in switched linear systems.  

  11. ESR dating of the fault rocks

    International Nuclear Information System (INIS)

    Lee, Hee Kwon

    2005-01-01

    We carried out ESR dating of fault rocks collected near the nuclear reactor. The Upcheon fault zone is exposed close to the Ulzin nuclear reactor. The space-time pattern of fault activity on the Upcheon fault deduced from ESR dating of fault gouge can be summarised as follows : this fault zone was reactivated between fault breccia derived from Cretaceous sandstone and tertiary volcanic sedimentary rocks about 2 Ma, 1.5 Ma and 1 Ma ago. After those movements, the Upcheon fault was reactivated between Cretaceous sandstone and fault breccia zone about 800 ka ago. This fault zone was reactivated again between fault breccia derived form Cretaceous sandstone and Tertiary volcanic sedimentary rocks about 650 ka and after 125 ka ago. These data suggest that the long-term(200-500 k.y.) cyclic fault activity of the Upcheon fault zone continued into the Pleistocene. In the Ulzin area, ESR dates from the NW and EW trend faults range from 800 ka to 600 ka NE and EW trend faults were reactivated about between 200 ka and 300 ka ago. On the other hand, ESR date of the NS trend fault is about 400 ka and 50 ka. Results of this research suggest the fault activity near the Ulzin nuclear reactor fault activity continued into the Pleistocene. One ESR date near the Youngkwang nuclear reactor is 200 ka

  12. Nuclear Power Plant Thermocouple Sensor-Fault Detection and Classification Using Deep Learning and Generalized Likelihood Ratio Test

    Science.gov (United States)

    Mandal, Shyamapada; Santhi, B.; Sridhar, S.; Vinolia, K.; Swaminathan, P.

    2017-06-01

    In this paper, an online fault detection and classification method is proposed for thermocouples used in nuclear power plants. In the proposed method, the fault data are detected by the classification method, which classifies the fault data from the normal data. Deep belief network (DBN), a technique for deep learning, is applied to classify the fault data. The DBN has a multilayer feature extraction scheme, which is highly sensitive to a small variation of data. Since the classification method is unable to detect the faulty sensor; therefore, a technique is proposed to identify the faulty sensor from the fault data. Finally, the composite statistical hypothesis test, namely generalized likelihood ratio test, is applied to compute the fault pattern of the faulty sensor signal based on the magnitude of the fault. The performance of the proposed method is validated by field data obtained from thermocouple sensors of the fast breeder test reactor.

  13. Fault Tolerance in ZigBee Wireless Sensor Networks

    Science.gov (United States)

    Alena, Richard; Gilstrap, Ray; Baldwin, Jarren; Stone, Thom; Wilson, Pete

    2011-01-01

    Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 PRO Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. This technology is supported by System-on-a-Chip solutions, resulting in extremely small and low-power nodes. The Wireless Connections in Space Project addresses the aerospace flight domain for both flight-critical and non-critical avionics. WSNs provide the inherent fault tolerance required for aerospace applications utilizing such technology. The team from Ames Research Center has developed techniques for assessing the fault tolerance of ZigBee WSNs challenged by radio frequency (RF) interference or WSN node failure.

  14. Mode automata and their compilation into fault trees

    International Nuclear Information System (INIS)

    Rauzy, Antoine

    2002-01-01

    In this article, we advocate the use of mode automata as a high level representation language for reliability studies. Mode automata are states/transitions based representations with the additional notion of flow. They can be seen as a generalization of both finite capacity Petri nets and block diagrams. They can be assembled into hierarchies by means of composition operations. The contribution of this article is twofold. First, we introduce mode automata and we discuss their relationship with other formalisms. Second, we propose an algorithm to compile mode automata into Boolean equations (fault trees). Such a compilation is of interest for two reasons. First, assessment tools for Boolean models are much more efficient than those for states/transitions models. Second, the automated generation of fault trees from higher level representations makes easier their maintenance through the life cycle of systems under study

  15. Arc fault detection system

    Science.gov (United States)

    Jha, K.N.

    1999-05-18

    An arc fault detection system for use on ungrounded or high-resistance-grounded power distribution systems is provided which can be retrofitted outside electrical switchboard circuits having limited space constraints. The system includes a differential current relay that senses a current differential between current flowing from secondary windings located in a current transformer coupled to a power supply side of a switchboard, and a total current induced in secondary windings coupled to a load side of the switchboard. When such a current differential is experienced, a current travels through a operating coil of the differential current relay, which in turn opens an upstream circuit breaker located between the switchboard and a power supply to remove the supply of power to the switchboard. 1 fig.

  16. Thruster fault identification method for autonomous underwater vehicle using peak region energy and least square grey relational grade

    OpenAIRE

    Mingjun Zhang; Baoji Yin; Xing Liu; Jia Guo

    2015-01-01

    A novel thruster fault identification method for autonomous underwater vehicle is presented in this article. It uses the proposed peak region energy method to extract fault feature and uses the proposed least square grey relational grade method to estimate fault degree. The peak region energy method is developed from fusion feature modulus maximum method. It applies the fusion feature modulus maximum method to get fusion feature and then regards the maximum of peak region energy in the convol...

  17. A System for Fault Management for NASA's Deep Space Habitat

    Science.gov (United States)

    Colombano, Silvano P.; Spirkovska, Liljana; Aaseng, Gordon B.; Mccann, Robert S.; Baskaran, Vijayakumar; Ossenfort, John P.; Smith, Irene Skupniewicz; Iverson, David L.; Schwabacher, Mark A.

    2013-01-01

    NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy.

  18. Automation in Clinical Microbiology

    Science.gov (United States)

    Ledeboer, Nathan A.

    2013-01-01

    Historically, the trend toward automation in clinical pathology laboratories has largely bypassed the clinical microbiology laboratory. In this article, we review the historical impediments to automation in the microbiology laboratory and offer insight into the reasons why we believe that we are on the cusp of a dramatic change that will sweep a wave of automation into clinical microbiology laboratories. We review the currently available specimen-processing instruments as well as the total laboratory automation solutions. Lastly, we outline the types of studies that will need to be performed to fully assess the benefits of automation in microbiology laboratories. PMID:23515547

  19. Automation of industrial bioprocesses.

    Science.gov (United States)

    Beyeler, W; DaPra, E; Schneider, K

    2000-01-01

    The dramatic development of new electronic devices within the last 25 years has had a substantial influence on the control and automation of industrial bioprocesses. Within this short period of time the method of controlling industrial bioprocesses has changed completely. In this paper, the authors will use a practical approach focusing on the industrial applications of automation systems. From the early attempts to use computers for the automation of biotechnological processes up to the modern process automation systems some milestones are highlighted. Special attention is given to the influence of Standards and Guidelines on the development of automation systems.

  20. Fast EEMD Based AM-Correntropy Matrix and Its Application on Roller Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Yunxiao Fu

    2016-06-01

    Full Text Available Roller bearing plays a significant role in industrial sectors. To improve the ability of roller bearing fault diagnosis under multi-rotating situation, this paper proposes a novel roller bearing fault characteristic: the Amplitude Modulation (AM based correntropy extracted from the Intrinsic Mode Functions (IMFs, which are decomposed by Fast Ensemble Empirical mode decomposition (FEEMD and employ Least Square Support Vector Machine (LSSVM to implement intelligent fault identification. Firstly, the roller bearing vibration acceleration signal is decomposed by FEEMD to extract IMFs. Secondly, IMF correntropy matrix (IMFCM as the fault feature matrix is calculated from the AM-correntropy model of the primary vibration signal and IMFs. Furthermore, depending on LSSVM, the fault identification results of the roller bearing are obtained. Through the bearing identification experiments in stationary rotating conditions, it was verified that IMFCM generates more stable and higher diagnosis accuracy than conventional fault features such as energy moment, fuzzy entropy, and spectral kurtosis. Additionally, it proves that IMFCM has more diagnosis robustness than conventional fault features under cross-mixed roller bearing operating conditions. The diagnosis accuracy was more than 84% for the cross-mixed operating condition, which is much higher than the traditional features. In conclusion, it was proven that FEEMD-IMFCM-LSSVM is a reliable technology for roller bearing fault diagnosis under the constant or multi-positioned operating conditions, and as such, it possesses potential prospects for a broad application of uses.