Sample records for fault detection method

  1. Fault detection methods: A literature survey

    Microsoft Academic Search

    Dubravko Miljkovic

    2011-01-01

    Fault detection plays an important role in high- cost and safety-critical processes. Early detection of process faults can help avoid abnormal event progression. Fault detection can be accomplished through various means. This paper presents the literature survey of major methods and current state of research in the field with a selection of important practical applications. I. INTRODUCTION Increasing demands on

  2. Arc Fault Detection and Discrimination Methods

    Microsoft Academic Search

    Carlos E. Restrepo

    2007-01-01

    Arc waveform characteristics can be evaluated with various methods to recognize the presence of hazardous arc fault conditions. Discussion covers the arc phenomena and how it is generated in a low voltage electrical distribution circuit, as well as the isolation of the presence of hazardous conditions versus conditions that could falsely mimic the presence of an arc fault. Many waveform

  3. Fault Detection and Diagnosis Method for VAV Terminal Units 

    E-print Network

    Miyata, M.; Yoshida, H.; Asada, M.; Wang, F.; Hashiguchi, S.

    2004-01-01

    This paper proposes two fault detection and diagnosis methods for VAV units without a sensor of supply air volume, and the results of applying these methods to a real building are presented. One method detects faults by applying a statistical method...

  4. Supervision, fault-detection and fault-diagnosis methods — An introduction

    Microsoft Academic Search

    R. Isermann

    1997-01-01

    The operation of technical processes requires increasingly advanced supervision and fault diagnosis to improve reliability, safety and economy. This paper gives an introduction to the field of fault detection and diagnosis. It begins with a consideration of a knowledge-based procedure that is based on analytical and heuristic information. Then different methods of fault detection are considered, which extract features from

  5. A Survey of Fault Detection, Isolation, and Reconfiguration Methods

    Microsoft Academic Search

    Inseok Hwang; Sungwan Kim; Youdan Kim; Chze Eng Seah

    2010-01-01

    Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI)

  6. Method of Fault Detection and Rerouting

    NASA Technical Reports Server (NTRS)

    Medelius, Pedro J. (Inventor); Gibson, Tracy L. (Inventor); Lewis, Mark E. (Inventor)

    2013-01-01

    A system and method for detecting damage in an electrical wire, including delivering at least one test electrical signal to an outer electrically conductive material in a continuous or non-continuous layer covering an electrically insulative material layer that covers an electrically conductive wire core. Detecting the test electrical signals in the outer conductive material layer to obtain data that is processed to identify damage in the outer electrically conductive material layer.

  7. Incipient mechanical fault detection based on multifractal and MTS methods

    Microsoft Academic Search

    Jinqiu Hu; Laibin Zhang; Wei Liang; Zhaohui Wang

    2009-01-01

    An incipient mechanical fault detection method, combining multifractal theory and Mahalanobis-Taguchi system (MTS), which\\u000a is based on statistical technology, is proposed in this paper. Multifractal features of vibration signals obtained from machine\\u000a state monitoring are extracted by multifractal spectrum analysis and generalized fractal dimensions. Considering the situation\\u000a of mass samples of normal mechanical running state and few fault states, the

  8. Improved Hidden-Markov-Model Method Of Detecting Faults

    NASA Technical Reports Server (NTRS)

    Smyth, Padhraic J.

    1994-01-01

    Method of automated, continuous monitoring to detect faults in complicated dynamic system based on hidden-Markov-model (HMM) approach. Simpler than another, recently proposed HMM method, but retains advantages of that method, including low susceptibility to false alarms, no need for mathematical model of dynamics of system under normal or faulty conditions, and ability to detect subtle changes in characteristics of monitored signals. Examples of systems monitored by use of this method include motors, turbines, and pumps critical in their applications; chemical-processing plants; powerplants; and biomedical systems.

  9. ACTUATOR FAULT DETECTION, ISOLATION METHOD AND STATE ESTIMATOR DESIGN FOR HOT ROLLING MILL MONITORING

    E-print Network

    Paris-Sud XI, Université de

    ACTUATOR FAULT DETECTION, ISOLATION METHOD AND STATE ESTIMATOR DESIGN FOR HOT ROLLING MILL difficult, however model-based approach among fault diagnosis methods or Fault Detection and Isolation (FDI of this paper is to develop an actuator fault diagnosis technique for a Single Input Multiple Output (SIMO

  10. An On-line Method for Stator Fault Detection in Multi-phase PMSM Drives

    E-print Network

    Paris-Sud XI, Université de

    An On-line Method for Stator Fault Detection in Multi-phase PMSM Drives Fabien Meinguet*, Eric deals with an on-line fault detection method for multi-phase PMSM drives. The method is based an original method for detecting an abnormal asymmetrical behavior in five-phase PMSM drives and we apply

  11. A method of fault line detection in distribution systems based on wavelets

    Microsoft Academic Search

    Jun Liang; Zhihao Yun; Feifan Liu; Yutian Liu

    2002-01-01

    On the basis of further research about characteristics of single-phase-to-ground fault transient information in neutral indirectly grounded systems and feature information which is abstracted from transient fault signals by wavelets, a novel fault line identifying method using signal singularity detection with the wavelet transform modulus maxima is presented in this paper. A new criterion is constituted by the distinct information

  12. System and method for bearing fault detection using stator current noise cancellation

    Microsoft Academic Search

    Wei Zhou; Bin Lu; Thomas G. Habetler; Ronald G. Harley; Peter J. Theisen

    2010-01-01

    A system and method for detecting incipient mechanical motor faults by way of current noise cancellation is disclosed. The system includes a controller configured to detect indicia of incipient mechanical motor faults. The controller further includes a processor programmed to receive a baseline set of current data from an operating motor and define a noise component in the baseline set

  13. System and method for motor fault detection using stator current noise cancellation

    Microsoft Academic Search

    Wei Zhou; Bin Lu; Michael P. Nowak; Steven A. Dimino

    2010-01-01

    A system and method for detecting incipient mechanical motor faults by way of current noise cancellation is disclosed. The system includes a controller configured to detect indicia of incipient mechanical motor faults. The controller further includes a processor programmed to receive a baseline set of current data from an operating motor and define a noise component in the baseline set

  14. Mathematical Comparison Methods to Assess Transfer Functions of Transformers to Detect Different Types of Mechanical Faults

    Microsoft Academic Search

    Ebrahim Rahimpour; Mehdi Jabbari; Stefan Tenbohlen

    2010-01-01

    The transfer function (TF) these days is a well-known method to detect different types of mechanical damage in power transformers. The most important mechanical faults mentioned by the authors and researchers, which are most likely to be detected using the TF and occur frequently in transformers, are disc-space variation, radial deformation, and axial displacement. These faults are investigated in this

  15. Zoom-MUSIC frequency estimation method for three-phase induction machine fault detection

    Microsoft Academic Search

    Shahin Hedayati Kia; Humbero Henao; Gérard-André Capolino

    2005-01-01

    Fault diagnosis of electrical machines based on frequency analysis of stator current has been the interest of many researchers for the past twenty years. Several frequency estimation techniques have been developed and are used to help the induction machine fault detection and diagnosis and it is still necessary to test new methods. This paper presents a technique to improve the

  16. Method of detecting the direction of arcing faults on power distribution feeders

    E-print Network

    Fernando, W. Anand Krisantha

    1992-01-01

    METHOD OF DETECTING THE DIRECTION OF ARCING FAULTS ON POWER DISTRIBUTION FEEDERS A Thesis by W. ANAND KRISANTHA FERNANDO Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE May 1992 Major Subject: Electrical Engineering METHOD OF DETECTING THE DIRECTION OF ARCING FAULTS ON POWER DISTRIBUTION FEEDERS A Thesis by W. ANAND KRISANTHA FERNANDO Approved as to style and content by: B. Don...

  17. Method of detecting the direction of arcing faults on power distribution feeders 

    E-print Network

    Fernando, W. Anand Krisantha

    1992-01-01

    METHOD OF DETECTING THE DIRECTION OF ARCING FAULTS ON POWER DISTRIBUTION FEEDERS A Thesis by W. ANAND KRISANTHA FERNANDO Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE May 1992 Major Subject: Electrical Engineering METHOD OF DETECTING THE DIRECTION OF ARCING FAULTS ON POWER DISTRIBUTION FEEDERS A Thesis by W. ANAND KRISANTHA FERNANDO Approved as to style and content by: B. Don...

  18. Method and apparatus for in-situ detection and isolation of aircraft engine faults

    NASA Technical Reports Server (NTRS)

    Bonanni, Pierino Gianni (Inventor); Brunell, Brent Jerome (Inventor)

    2007-01-01

    A method for performing a fault estimation based on residuals of detected signals includes determining an operating regime based on a plurality of parameters, extracting predetermined noise standard deviations of the residuals corresponding to the operating regime and scaling the residuals, calculating a magnitude of a measurement vector of the scaled residuals and comparing the magnitude to a decision threshold value, extracting an average, or mean direction and a fault level mapping for each of a plurality of fault types, based on the operating regime, calculating a projection of the measurement vector onto the average direction of each of the plurality of fault types, determining a fault type based on which projection is maximum, and mapping the projection to a continuous-valued fault level using a lookup table.

  19. Evaluation of a new proposal for arcing fault detection method based on wavelet packet analysis

    Microsoft Academic Search

    A. Lazkano; J. Ruiz; E. Aramendi; L. A. Leturiondo

    2001-01-01

    This paper presents a new proposal for the detection of arcing faults (AF) and evaluates the detection rate and the security level of the proposed method. This method is based on an analysis of three-phase unbalanced current, feeder 3I0, using decomposition of the signal by means of wavelet transform techniques. Combining both temporal and frequency localizing properties, criteria are set

  20. System and method for bearing fault detection using stator current noise cancellation

    DOEpatents

    Zhou, Wei (Los Angeles, CA); Lu, Bin (Kenosha, WI); Habetler, Thomas G. (Snellville, GA); Harley, Ronald G. (Lawrenceville, GA); Theisen, Peter J. (West Bend, WI)

    2010-08-17

    A system and method for detecting incipient mechanical motor faults by way of current noise cancellation is disclosed. The system includes a controller configured to detect indicia of incipient mechanical motor faults. The controller further includes a processor programmed to receive a baseline set of current data from an operating motor and define a noise component in the baseline set of current data. The processor is also programmed to repeatedly receive real-time operating current data from the operating motor and remove the noise component from the operating current data in real-time to isolate any fault components present in the operating current data. The processor is then programmed to generate a fault index for the operating current data based on any isolated fault components.

  1. System and method for motor fault detection using stator current noise cancellation

    DOEpatents

    Zhou, Wei (Los Angeles, CA); Lu, Bin (Kenosha, WI); Nowak, Michael P. (Menomonee Falls, WI); Dimino, Steven A. (Wauwatosa, WI)

    2010-12-07

    A system and method for detecting incipient mechanical motor faults by way of current noise cancellation is disclosed. The system includes a controller configured to detect indicia of incipient mechanical motor faults. The controller further includes a processor programmed to receive a baseline set of current data from an operating motor and define a noise component in the baseline set of current data. The processor is also programmed to acquire at least on additional set of real-time operating current data from the motor during operation, redefine the noise component present in each additional set of real-time operating current data, and remove the noise component from the operating current data in real-time to isolate any fault components present in the operating current data. The processor is then programmed to generate a fault index for the operating current data based on any isolated fault components.

  2. Real-time fault detection of braiding ropes using recognition methods

    NASA Astrophysics Data System (ADS)

    Matela, Lukas

    2004-10-01

    Formation of this paper is evoked by solving of device that is able to detect faults of braiding ropes in real-time. Many various inspection devices for textile industry were developed. However, rope-producing textile company has come with demand of intelligent inspection device that is able to detect faults in finishing process. The winding speeds are 50 - 200 m/min. Nowadays commercial devices are focused on textile fabrics (weaving or knitting) and they are only able to detect basic faults (holes, dirty and oil spots). Considering textile structure faults are possible to find in several research papers, however, for specific types of textiles or for slow processes only. The inspection device, which has been developed in our laboratory, is able to work with high winding speeds of rope. The device is based on fast line-scan camera with Camera-Link interface. The goal of the project was to search three basic structure faults: missing strand, strands pulled tight and stitch irregularity. The principle of fault detection is based on gathering the most suitable symptoms that are used for recognition methods. These methods are very successful for speech recognition and using them even bring us better results than using neural networks. This paper shows the way of finding the most suitable symptoms, their statistical evaluation and decision making algorithms. The most important step is reducing the problem from time-consuming image processing to one-dimensional signal processing.

  3. A Comparison of Fault Detection Methods For a Transcritical Refrigeration System 

    E-print Network

    Janecke, Alex Karl

    2012-10-19

    pairings of four faults: over/undercharge, evaporator fouling, gas cooler fouling, and compressor valve leakage. This technique allows for low cost measurement and independent detection of individual faults even when multiple faults are present. Results...

  4. Amplitude and phase modulation analysis methods for early detection of gear faults

    NASA Astrophysics Data System (ADS)

    Nicks, J. E.; Krishnappa, G.

    This paper presents methods of analysis of vibration data for detecting gear tooth damage using amplitude and phase modulation techniques. Based on examined vibration data from a gear test rig, these methods appear to be effective and reliable diagnostics tools. All stages of gear tooth damage - light, intermediate, and advanced - were detected. A number of processing enhancements to improve the fault detection rate are discussed. These techniques were found to be useful for both discrete and distributed tooth damage.

  5. An alternative fault-detection method using predictive sensitivity

    Microsoft Academic Search

    Larry V. Kirkland; Lloyd G. Allred; Jere D. Wiederholt

    1993-01-01

    Traditional algorithms for determining defective components using circuit card data can provide inconsistent results. Model-based tools and expert systems derive conclusions using circuit performance data, circuit theory and statistics. The authors have developed a predictive sensitivity approach which views failure paths and actual failure data to identify alternate fault-isolation strategies

  6. Fault detection of helicopter gearboxes using the multi-valued influence matrix method

    NASA Technical Reports Server (NTRS)

    Chin, Hsinyung; Danai, Kourosh; Lewicki, David G.

    1993-01-01

    In this paper we investigate the effectiveness of a pattern classifying fault detection system that is designed to cope with the variability of fault signatures inherent in helicopter gearboxes. For detection, the measurements are monitored on-line and flagged upon the detection of abnormalities, so that they can be attributed to a faulty or normal case. As such, the detection system is composed of two components, a quantization matrix to flag the measurements, and a multi-valued influence matrix (MVIM) that represents the behavior of measurements during normal operation and at fault instances. Both the quantization matrix and influence matrix are tuned during a training session so as to minimize the error in detection. To demonstrate the effectiveness of this detection system, it was applied to vibration measurements collected from a helicopter gearbox during normal operation and at various fault instances. The results indicate that the MVIM method provides excellent results when the full range of faults effects on the measurements are included in the training set.

  7. A Method Based on Multi-Sensor Data Fusion for Fault Detection of Planetary Gearboxes

    PubMed Central

    Lei, Yaguo; Lin, Jing; He, Zhengjia; Kong, Detong

    2012-01-01

    Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes exhibit unique behaviors, which invalidate fault diagnosis methods that work well for fixed-axis gearboxes. It is a fact that for systems as complex as planetary gearboxes, multiple sensors mounted on different locations provide complementary information on the health condition of the systems. On this basis, a fault detection method based on multi-sensor data fusion is introduced in this paper. In this method, two features developed for planetary gearboxes are used to characterize the gear health conditions, and an adaptive neuro-fuzzy inference system (ANFIS) is utilized to fuse all features from different sensors. In order to demonstrate the effectiveness of the proposed method, experiments are carried out on a planetary gearbox test rig, on which multiple accelerometers are mounted for data collection. The comparisons between the proposed method and the methods based on individual sensors show that the former achieves much higher accuracies in detecting planetary gearbox faults. PMID:22438750

  8. Arc fault detection based on wavelet packet

    Microsoft Academic Search

    Wen-Jun Li; Yuan-Chun Li

    2005-01-01

    Methods of arc fault detection are beginning to develop to protect against conditions that may cause fire on aircraft. This paper provides a new method for the detection of arc fault based on wavelet packet transform. Wavelet packets with automatically adjusted time windows are used to distinguished arc fault from non-arcing fault transient phenomena and conditions similar to an arc

  9. A High-Resolution Frequency Estimation Method for Three-Phase Induction Machine Fault Detection

    Microsoft Academic Search

    Shahin Hedayati Kia; Humberto Henao; Gérard-André Capolino

    2007-01-01

    Fault detection in alternating-current electrical machines that is based on frequency analysis of stator current has been the interest of many researchers. Several frequency estimation techniques have been developed and are used to help the induction machine fault detection and diagnosis. This paper presents a technique to improve the fault detection technique by using the classical multiple signal classification (MUSIC)

  10. A Wavelet-Based Method for Detection and Classification of Single and Crosscountry Faults in Transmission Lines

    Microsoft Academic Search

    B. A. Souza; N. S. D. Brito

    2009-01-01

    This paper presents a discrete wavelet transform approach to detect and classify faults in transmission lines by the analysis of oscillographic records. Most of the existing methods treat the fault as a single type. Thus, the performance of these methods might be limited for real applications in power systems. In this framework, the proposed approach overcomes this problem by the

  11. Randomness fault detection system

    NASA Technical Reports Server (NTRS)

    Russell, B. Don (Inventor); Aucoin, B. Michael (Inventor); Benner, Carl L. (Inventor)

    1996-01-01

    A method and apparatus are provided for detecting a fault on a power line carrying a line parameter such as a load current. The apparatus monitors and analyzes the load current to obtain an energy value. The energy value is compared to a threshold value stored in a buffer. If the energy value is greater than the threshold value a counter is incremented. If the energy value is greater than a high value threshold or less than a low value threshold then a second counter is incremented. If the difference between two subsequent energy values is greater than a constant then a third counter is incremented. A fault signal is issued if the counter is greater than a counter limit value and either the second counter is greater than a second limit value or the third counter is greater than a third limit value.

  12. Fault detection and fault tolerance in robotics

    NASA Technical Reports Server (NTRS)

    Visinsky, Monica; Walker, Ian D.; Cavallaro, Joseph R.

    1992-01-01

    Robots are used in inaccessible or hazardous environments in order to alleviate some of the time, cost and risk involved in preparing men to endure these conditions. In order to perform their expected tasks, the robots are often quite complex, thus increasing their potential for failures. If men must be sent into these environments to repair each component failure in the robot, the advantages of using the robot are quickly lost. Fault tolerant robots are needed which can effectively cope with failures and continue their tasks until repairs can be realistically scheduled. Before fault tolerant capabilities can be created, methods of detecting and pinpointing failures must be perfected. This paper develops a basic fault tree analysis of a robot in order to obtain a better understanding of where failures can occur and how they contribute to other failures in the robot. The resulting failure flow chart can also be used to analyze the resiliency of the robot in the presence of specific faults. By simulating robot failures and fault detection schemes, the problems involved in detecting failures for robots are explored in more depth.

  13. A COMPARISON OF TWO METHODS FOR STOCHASTIC FAULT DETECTION: THE PARITY SPACE APPROACH AND

    E-print Network

    Gustafsson, Fredrik

    setting, assuming additive faults on input and output signals and stochastic unmeasurable disturbances aircraft, where six different faults are considered. The result is that PCA has similar fault detection, but it can be highly sensitive to measurement noise and process noise, since these are not taken

  14. PEM fuel cell fault detection and identification using differential method: simulation and experimental validation

    NASA Astrophysics Data System (ADS)

    Frappé, E.; de Bernardinis, A.; Bethoux, O.; Candusso, D.; Harel, F.; Marchand, C.; Coquery, G.

    2011-05-01

    PEM fuel cell performance and lifetime strongly depend on the polymer membrane and MEA hydration. As the internal moisture is very sensitive to the operating conditions (temperature, stoichiometry, load current, water management…), keeping the optimal working point is complex and requires real-time monitoring. This article focuses on PEM fuel cell stack health diagnosis and more precisely on stack fault detection monitoring. This paper intends to define new, simple and effective methods to get relevant information on usual faults or malfunctions occurring in the fuel cell stack. For this purpose, the authors present a fault detection method using simple and non-intrusive on-line technique based on the space signature of the cell voltages. The authors have the objective to minimize the number of embedded sensors and instrumentation in order to get a precise, reliable and economic solution in a mass market application. A very low number of sensors are indeed needed for this monitoring and the associated algorithm can be implemented on-line. This technique is validated on a 20-cell PEMFC stack. It demonstrates that the developed method is particularly efficient in flooding case. As a matter of fact, it uses directly the stack as a sensor which enables to get a quick feedback on its state of health.

  15. Application of the Wenner resistivity method to the detection of buried shallow faults in the Gulf Coast province 

    E-print Network

    Andrews, Charles Hubert

    1961-01-01

    APPLICATION OF THE WENNER RESISTIVITY METHOD TO THE DETECTION OF BURIED SHALLOW FAULTS IN THE GULF COAST PROVINCE A Thesis By CHARLES HUBER T ANDREWS Submitted to the Graduate School of the Agricultural and Mechanical College of Texas... in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE January 1961 Major Subject: Geophysics APPLICATION OF THE WENNER RESISTIVITY METHOD TO THE DETECTION OF BURIED SHALLOW FAULTS IN THE GULF COAST PROVINCE A Thesis...

  16. Fault detection for modern Diesel engines using signal- and process model-based methods

    Microsoft Academic Search

    Frank Kimmich; Anselm Schwarte; Rolf Isermann

    2005-01-01

    Modern Diesel engines with direct fuel injection and turbo charging have shown a significant progress in fuel consumption, emissions and driveability. Together with exhaust gas recirculation and variable geometry turbochargers they became complicated and complex processes. Therefore, fault detection and diagnosis is not easily done and need to be improved. This contribution shows a systematic development of fault detection and

  17. A New Bearing Fault Detection Method in Induction Machines Based on Instantaneous Power Factor

    Microsoft Academic Search

    Ali Ibrahim; Mohamed El Badaoui; FranÇois Guillet; FrÉdÉric Bonnardot

    2008-01-01

    Fault detection and diagnosis of asynchronous machine has become a central problem in industry over the past decade. A solution to tackle this problem is to use stator current for a condition monitoring, referred to as motor current signature analysis. This paper argues that bearing faults would have a negligible effect on motor currents and instead argues that the more

  18. Presented at Institute of Navigation GPS2002 (September 24-27, 2002, Portland, OR) 1 Fault Detection Methods And Testing

    E-print Network

    Calgary, University of

    Detection Methods And Testing For Marine GPS Receivers G. MacGougan and J. Liu Department of Geomatics. Investigative testing involved a selection of typical marine-grade GPS receivers. The receivers' susceptibility This research involves development of fault detection methods and testing of marine-grade GPS receivers

  19. Discrete Data Qualification System and Method Comprising Noise Series Fault Detection

    NASA Technical Reports Server (NTRS)

    Fulton, Christopher; Wong, Edmond; Melcher, Kevin; Bickford, Randall

    2013-01-01

    A Sensor Data Qualification (SDQ) function has been developed that allows the onboard flight computers on NASA s launch vehicles to determine the validity of sensor data to ensure that critical safety and operational decisions are not based on faulty sensor data. This SDQ function includes a novel noise series fault detection algorithm for qualification of the output data from LO2 and LH2 low-level liquid sensors. These sensors are positioned in a launch vehicle s propellant tanks in order to detect propellant depletion during a rocket engine s boost operating phase. This detection capability can prevent the catastrophic situation where the engine operates without propellant. The output from each LO2 and LH2 low-level liquid sensor is a discrete valued signal that is expected to be in either of two states, depending on whether the sensor is immersed (wet) or exposed (dry). Conventional methods for sensor data qualification, such as threshold limit checking, are not effective for this type of signal due to its discrete binary-state nature. To address this data qualification challenge, a noise computation and evaluation method, also known as a noise fault detector, was developed to detect unreasonable statistical characteristics in the discrete data stream. The method operates on a time series of discrete data observations over a moving window of data points and performs a continuous examination of the resulting observation stream to identify the presence of anomalous characteristics. If the method determines the existence of anomalous results, the data from the sensor is disqualified for use by other monitoring or control functions.

  20. Applications of Fault Detection in Vibrating Structures

    NASA Technical Reports Server (NTRS)

    Eure, Kenneth W.; Hogge, Edward; Quach, Cuong C.; Vazquez, Sixto L.; Russell, Andrew; Hill, Boyd L.

    2012-01-01

    Structural fault detection and identification remains an area of active research. Solutions to fault detection and identification may be based on subtle changes in the time series history of vibration signals originating from various sensor locations throughout the structure. The purpose of this paper is to document the application of vibration based fault detection methods applied to several structures. Overall, this paper demonstrates the utility of vibration based methods for fault detection in a controlled laboratory setting and limitations of applying the same methods to a similar structure during flight on an experimental subscale aircraft.

  1. Fault Tolerant Quantum Filtering and Fault Detection for Quantum Systems

    E-print Network

    Qing Gao; Daoyi Dong; Ian R. Petersen

    2015-04-26

    This paper aims to determine the fault tolerant quantum filter and fault detection equation for a class of open quantum systems coupled to laser fields and subject to stochastic faults. In order to analyze open quantum systems where the system dynamics involve both classical and quantum random variables, a quantum-classical probability space model is developed. Using a reference probability approach, a fault tolerant quantum filter and a fault detection equation are simultaneously derived for this class of open quantum systems. An example of two-level open quantum systems subject to Poisson-type faults is presented to illustrate the proposed method. These results have the potential to lead to a new fault tolerant control theory for quantum systems.

  2. Fault detection methods for vapor-compression air conditioners using electrical measurements

    E-print Network

    Laughman, Christopher Reed.

    2008-01-01

    (cont.) This method was experimentally tested and validated on a commercially available air handler and duct system. In the second class of faults studied, liquid refrigerant, rather than vapor, enters the cylinder of a ...

  3. Row fault detection system

    SciTech Connect

    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.

  4. Row fault detection system

    DOEpatents

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2012-02-07

    An apparatus, program product and method check 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.

  5. A comparison of Fourier transform and wavelet transform methods for detection and classification of faults on transmission lines

    Microsoft Academic Search

    Debrup Das; N. K. Singh; A. K. Sinha

    2006-01-01

    This paper presents a comparative study of the performance of Fourier transform and wavelet transform based methods for detection, classification and location of faults on high voltage transmission lines. The algorithms devised are based on Fourier transform analysis of transient current signals recorded in the event of a short circuit on a transmission line. Similar analysis is performed using multi-resolution

  6. Simultaneous Fault Detection and Classification for Semiconductor Manufacturing Tools

    E-print Network

    Boning, Duane S.

    Simultaneous Fault Detection and Classification for Semiconductor Manufacturing Tools Brian E detection of equipment and process faults to maintain high process yields and rapid fault classification treat fault detection and classification as a two-step process. We present a novel method

  7. An investigation into a method of detecting the fault induced high frequency voltage signals of EHV transmission lines for protection applications

    Microsoft Academic Search

    P. L. Agrawal

    1991-01-01

    This paper investigates a method of detecting the fault induced high frequency voltage signals of the EHV transmission lines for the protection applications. The method is based on the principle of power line carrier communication system using a stack tuner for detecting the high frequency voltage signals in a particular frequency bandwidth. The digitally simulated fault responses of different frequency

  8. Polynomially Complete Fault Detection Problems

    Microsoft Academic Search

    Oscar H. Ibarra; Sartaj Sahni

    1975-01-01

    We look at several variations of the single fault detection problem for combinational logic circuits and show that deciding whether single faults are detectable by input-output (I\\/O) experiments is polynomially complete, i.e., there is a polynomial time algorithm to decide if these single faults are detectable if and only if there is a polynomial time algorithm for problems such as

  9. New Combined Method for Fault Detection, Classification, and Location in Series-compensated Transmission Line

    Microsoft Academic Search

    Z. Moravej; M. Khederzadeh; M. Pazoki

    2012-01-01

    In this article, a new full-scheme distance protection for a series-compensated transmission line is proposed. The new combination of hyperbolic S-transform and learning machines is applied for fault detection, classification, and location, which are the three main aspects of distance relays. The hyperbolic S-transform is used for extracting useful features from the current and voltage signals sample of the power

  10. Abstract--A method for fault detection and isolation is proposed and applied to inverter faults in multi-phase drives. An

    E-print Network

    Boyer, Edmond

    . The method is applied to a five-phase permanent-magnet synchronous machine drive. Simulations and experiments-magnet synchronous machine (PMSM) drive. The faults under consideration are: open-phase faults and open-switch faults in multi-phase drives. An analysis of simulations in faulty conditions leads to the derivation of suitable

  11. Tunable architecture for aircraft fault detection

    NASA Technical Reports Server (NTRS)

    Ganguli, Subhabrata (Inventor); Papageorgiou, George (Inventor); Glavaski-Radovanovic, Sonja (Inventor)

    2012-01-01

    A method for detecting faults in an aircraft is disclosed. The method involves predicting at least one state of the aircraft and tuning at least one threshold value to tightly upper bound the size of a mismatch between the at least one predicted state and a corresponding actual state of the non-faulted aircraft. If the mismatch between the at least one predicted state and the corresponding actual state is greater than or equal to the at least one threshold value, the method indicates that at least one fault has been detected.

  12. A New Method for Earth Fault Line Detection Based on Two-Dimensional Wavelet Transform in Distribution Automation

    Microsoft Academic Search

    Jun Liang; Zengxun Liu; Zhihao Yun; Mei Li; Li Zhang

    2005-01-01

    A novel method based on two-dimensional wavelet transform to detect single-phase faults in distribution systems is proposed in this paper. After structuring analytic signals of zero sequence current, the two-dimensional wavelet transform is applied. Thus the analysis of combined signal of amplitude and phase is realized. Compared with the use of single amplitude or single phase, combined signal carries more

  13. Fault Detection and Isolation of Actuator Faults in Overactuated Systems

    Microsoft Academic Search

    Nader Meskin; K. Khorasani

    2007-01-01

    This paper investigates development of fault detection and isolation (FDI) filters for overactuated systems. Due to input channels coupling effects and dependencies in overactuated systems, the necessary condition for applying geometric FDI approaches is not satisfied. In this work a geometric FDI approach for linear systems is extended to overactuated systems. The proposed method is applied to an F-18 HARV

  14. Application of a Subspace-Based Fault Detection Method to Industrial Structures

    NASA Astrophysics Data System (ADS)

    Mevel, L.; Hermans, L.; van der Auweraer, H.

    1999-11-01

    Early detection and localization of damage allow increased expectations of reliability, safety and reduction of the maintenance cost. This paper deals with the industrial validation of a technique to monitor the health of a structure in operating conditions (e.g. rotating machinery, civil constructions subject to ambient excitations, etc.) and to detect slight deviations in a modal model derived from in-operation measured data. In this paper, a statistical local approach based on covariance-driven stochastic subspace identification is proposed. The capabilities and limitations of the method with respect to health monitoring and damage detection are discussed and it is explained how the method can be practically used in industrial environments. After the successful validation of the proposed method on a few laboratory structures, its application to a sports car is discussed. The example illustrates that the method allows the early detection of a vibration-induced fatigue problem of a sports car.

  15. Generalized Method of Fault Analysis

    Microsoft Academic Search

    V. Brandwajn; W. F. Tinney

    1985-01-01

    A generalized method is given for solving shortcircuit faults of any conceivable complexity. The method efficiently combines the application of sparsity-oriented compensation techniques to sequence networks with the simulation of fault conditions in phase coordinates. All recent advances in features and modeling aspects of fault studies are incorporated in the method. Sparse vector techniques are extensively used to enhance speed

  16. Including Faults Detected By Near-Surface Seismic Methods in the USGS National Seismic Hazard Maps - Some Restrictions Apply

    NASA Astrophysics Data System (ADS)

    Williams, R. A.; Haller, K. M.

    2014-12-01

    Every 6 years, the USGS updates the National Seismic Hazard Maps (new version released July 2014) that are intended to help society reduce risk from earthquakes. These maps affect hundreds of billions of dollars in construction costs each year as they are used to develop seismic-design criteria of buildings, bridges, highways, railroads, and provide data for risk assessment that help determine insurance rates. Seismic source characterization, an essential component of hazard model development, ranges from detailed trench excavations across faults at the ground surface to less detailed analysis of broad regions defined mainly on the basis of historical seismicity. Though it is a priority for the USGS to discover new Quaternary fault sources, the discovered faults only become a part of the hazard model if there are corresponding constraints on their geometry (length and depth extent) and slip-rate (or recurrence interval). When combined with fault geometry and slip-rate constraints, near-surface seismic studies that detect young (Quaternary) faults have become important parts of the hazard source model. Examples of seismic imaging studies with significant hazard impact include the Southern Whidbey Island fault, Washington; Santa Monica fault, San Andreas fault, and Palos Verdes fault zone, California; and Commerce fault, Missouri. There are many more faults in the hazard model in the western U.S. than in the expansive region east of the Rocky Mountains due to the higher rate of tectonic deformation, frequent surface-rupturing earthquakes and, in some cases, lower erosion rates. However, the recent increase in earthquakes in the central U.S. has revealed previously unknown faults for which we need additional constraints before we can include them in the seismic hazard maps. Some of these new faults may be opportunities for seismic imaging studies to provide basic data on location, dip, style of faulting, and recurrence.

  17. Row fault detection system

    DOEpatents

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2010-02-23

    An apparatus and program product check 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.

  18. Cell boundary fault detection system

    DOEpatents

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2009-05-05

    A method determines a nodal fault along the boundary, or face, of a computing cell. Nodes on adjacent cell boundaries communicate with each other, and the communications are analyzed to determine if a node or connection is faulty.

  19. Exogenous Fault Detection in a Collective Robotic Task

    E-print Network

    Birattari, Mauro

    - nous fault detection in autonomous robots. We present a concrete method for obtaining components function which ham- pers or disturbs normal operation, causing unacceptable deterioration in perfor- mance

  20. A new method for comparing the transfer function of transformers in order to detect the location and amount of winding faults

    Microsoft Academic Search

    Ebrahim Rahimpour; Danial Gorzin

    2006-01-01

    Since the transfer function (TF) is an acknowledged method for detecting power transformer faults, introduction of a proper manner to compare these TFs is necessary. Although a lot of effort has been made, proposed methods are not reliable. This paper presents a new approach based on weight functions, compared with all other methods. This comparison shows that the weight function

  1. FAULT DETECTION AND IDENTIFICATION OF ACTUATOR FAULTS USING LINEAR PARAMETER VARYING MODELS

    Microsoft Academic Search

    R. Hallouzi; V. Verdult; R. Babuska; M. Verhaegen

    A method is proposed to detect and identify two common classes of actuator faults in nonlinear systems. The two fault classes are total and partial actuator faults. This is accomplished by representing the nonlinear system by a Linear Parameter Varying (LPV) model, which is derived from experimental input-output data. The LPV model is used in a Kalman filter to estimate

  2. In-situ fault detection apparatus and method for an encased energy storing device

    DOEpatents

    Hagen, Ronald A. (Stillwater, MN); Comte, Christophe (Montreal, CA); Knudson, Orlin B. (Vadnais Heights, MN); Rosenthal, Brian (Stillwater, MN); Rouillard, Jean (Saint-Luc, CA)

    2000-01-01

    An apparatus and method for detecting a breach in an electrically insulating surface of an electrically conductive power system enclosure within which a number of series connected energy storing devices are disposed. The energy storing devices disposed in the enclosure are connected to a series power connection. A detector is coupled to the series connection and detects a change of state in a test signal derived from the series connected energy storing devices. The detector detects a breach in the insulating layer of the enclosure by detecting a state change in the test signal from a nominal state to a non-nominal state. A voltage detector detects a state change of the test signals from a nominal state, represented by a voltage of a selected end energy storing device, to a non-nominal state, represented by a voltage that substantially exceeds the voltage of the selected opposing end energy storing device. Alternatively, the detector may comprise a signal generator that produces the test signal as a time-varying or modulated test signal and injects the test signal into the series connection. The detector detects the state change of the time-varying or modulated test signal from a nominal state, represented by a signal substantially equivalent to the test signal, to a non-nominal state, representative by an absence of the test signal.

  3. All row, planar fault detection system

    DOEpatents

    Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D; Smith, Brian Edward

    2013-07-23

    An apparatus, program product and method for detecting nodal faults may simultaneously cause designated nodes of a cell to communicate with all nodes adjacent to each of the designated nodes. Furthermore, all nodes along the axes of the designated nodes are made to communicate with their adjacent nodes, and the communications are analyzed to determine if a node or connection is faulty.

  4. The detection of high impedance faults using random fault behavior 

    E-print Network

    Carswell, Patrick Wayne

    1988-01-01

    prevent it from detecting arcing faults under certain fault scenarios. Past research into the behavior of arcing high impedance faults has demon- strated them to be very random in nature. That is, the actual bursts occur in random intervals of time... and with random intensity. The new algorithm presented attempts to utilize this random behavior as well as time to discriminate the pres- ence of high impedance arcing faults from normal system operations which may also generate a, high frequency current signal...

  5. A new protective method for grid connected dispersed PV systems to detect short circuit fault in distribution line

    Microsoft Academic Search

    Hiromu Kobayashi; Kiyoshi Takigawa

    1997-01-01

    A new protective meausre installed in the grid connected dispersed PV system for detecting short circuit fault with high-resistance in a high-voltage distribution line was designed. Relationship between voltage absolute value change and voltage phase change of the distribution line is monitored in the measure for achieving not only enhancement of detective performance but also prevention of misdetection in normal

  6. A Fault Detection and Isolation Method Applied to Liquid Oxygen Loading for the Space Shuttle

    Microsoft Academic Search

    Ethan A. Scarl; John R. Jamieson; Carl I. Delaune

    1985-01-01

    Process-monitoring and fault location techniques have been developed at the Kennedy Space Center in a domain of mixed media control in NASA's Space Shuttle Launch Processing System. An intuitively appealing diagnostic technique and representation of the system's structure and function were formulated in cooperation with system engineers. Functional relationships that determine the consistency of sensor measurements are represented by symbolic

  7. Survey of robust residual generation and evaluation methods in observer-based fault detection systems

    Microsoft Academic Search

    P. M. Frank; X. Ding

    1997-01-01

    The paper outlines recent advances of the theory of observer-based fault diagnosis in dynamic systems towards the design of robust techniques of residual generation and residual evaluation. Emphasis will be placed upon the latest contributions using frequency domain techniques including H? theory, nonlinear unknown input observer theory, adaptive observer theory, artificial intelligence including fuzzy logic, knowledge-based techniques and the natural

  8. Expert System Detects Power-Distribution Faults

    NASA Technical Reports Server (NTRS)

    Walters, Jerry L.; Quinn, Todd M.

    1994-01-01

    Autonomous Power Expert (APEX) computer program is prototype expert-system program detecting faults in electrical-power-distribution system. Assists human operators in diagnosing faults and deciding what adjustments or repairs needed for immediate recovery from faults or for maintenance to correct initially nonthreatening conditions that could develop into faults. Written in Lisp.

  9. High Resolution Seismic Reflection Survey for Coal Mine: fault detection

    NASA Astrophysics Data System (ADS)

    Khukhuudei, M.; Khukhuudei, U.

    2014-12-01

    High Resolution Seismic Reflection (HRSR) methods will become a more important tool to help unravel structures hosting mineral deposits at great depth for mine planning and exploration. Modern coal mining requires certainly about geological faults and structural features. This paper focuses on 2D Seismic section mapping results from an "Zeegt" lignite coal mine in the "Mongol Altai" coal basin, which required the establishment of major structure for faults and basement. HRSR method was able to detect subsurface faults associated with the major fault system. We have used numerical modeling in an ideal, noise free environment with homogenous layering to detect of faults. In a coal mining setting where the seismic velocity of the high ranges from 3000m/s to 3600m/s and the dominant seismic frequency is 100Hz, available to locate faults with a throw of 4-5m. Faults with displacements as seam thickness detected down to several hundred meter beneath the surface.

  10. Detection of arcing faults on distribution feeders

    NASA Astrophysics Data System (ADS)

    Russell, B. D.

    1982-12-01

    The problem of detecting high impedance faults is examined from the perspective of current utility protection practices and it is shown why conventional overcurrent protection systems may not detect such faults. A microcomputer based prototype of an arcing, high impedance fault detector was tested. The fault detection technique is based on an increase in the high frequency component of distribution feeder current caused by the arcing associated with many high impedance faults. This theory is supported by field data measurements and analysis of a large number of staged distribution primary faults and normal system conditions. The design and demonstration of the prototype is explained. The device successfully detected many faults of greater than 5 to 10 A on a typical distribution feeder without false trips. General application of this fault detection techniques is considered.

  11. The Fault Detection Problem Andreas Haeberlen1

    E-print Network

    Pennsylvania, University of

    The Fault Detection Problem Andreas Haeberlen1 and Petr Kuznetsov2 1 Max Planck Institute challenges in distributed com- puting is ensuring that services are correct and available despite faults. Recently it has been argued that fault detection can be factored out from computation, and that a generic

  12. The Fault Detection Problem Andreas Haeberlen

    E-print Network

    Pennsylvania, University of

    The Fault Detection Problem Andreas Haeberlen Petr Kuznetsov Abstract One of the most important challenges in distributed computing is ensuring that services are correct and available despite faults. Recently it has been argued that fault detection can be factored out from computation, and that a generic

  13. Evaluation of a Decoupling-Based Fault Detection and Diagnostic Technique - Part I: Field Emulation Evaluation 

    E-print Network

    Li, H.; Braun, J.

    2006-01-01

    Existing methods addressing automated fault detection and diagnosis (FDD) for vapor compression air conditioning system have good performance for faults that occur individually, but they have difficulty in handling multiple-simultaneous faults...

  14. Bisectional fault detection system

    SciTech Connect

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2008-11-11

    An apparatus, program product and method logically divides a group of nodes and causes node pairs comprising a node from each section to communicate. Results from the communications may be analyzed to determine performance characteristics, such as bandwidth and proper connectivity.

  15. Bisectional fault detection system

    DOEpatents

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2012-02-14

    An apparatus, program product and method logically divide a group of nodes and causes node pairs comprising a node from each section to communicate. Results from the communications may be analyzed to determine performance characteristics, such as bandwidth and proper connectivity.

  16. A Case Study on the Comparison of Non-parametric Spectrum Methods for Broken Rotor Bar Fault Detection

    E-print Network

    Chow, Mo-Yuen

    for broken rotor bar fault detection, the Fast Fourier Transform (FFT) is the most widely used technique. There are other spectrum techniques, which are based on the power spectral density estimates. In this paper we standards. The failure of induction motors can result in a total loss of the machine itself, in addition

  17. Sensor Fault Detection and Isolation System

    E-print Network

    Yang, Cheng-Ken

    2014-08-01

    The purpose of this research is to develop a Fault Detection and Isolation (FDI) system which is capable to diagnosis multiple sensor faults in nonlinear cases. In order to lead this study closer to real world applications in oil industries...

  18. A PARAMETER ESTIMATION METHOD FOR THE DIAGNOSIS OF SENSOR OR ACTUATOR ABRUPT FAULTS

    E-print Network

    Paris-Sud XI, Université de

    A PARAMETER ESTIMATION METHOD FOR THE DIAGNOSIS OF SENSOR OR ACTUATOR ABRUPT FAULTS P. Weber and S.Gentil@inpg.fr Keywords: Fault detection; fault isolation; sensor and actuator abrupt faults; parameter estimation. Abstract This paper describes a method for additive abrupt fault detection and isolation. Parameter

  19. Engine Fault Analysis: Part I-Statistical Methods

    Microsoft Academic Search

    Arun K. Sood; Carl B. Friedlander; Ali Amin Fahs

    1985-01-01

    Several studies have been performed to detect faults in engines. Fourier series and autocorrelation-based methods have been shown to be useful for this purpose. However, these and other methods discussed in the literature cannot locate the fault. In this paper, the focus is on techniques that will enable the location of the fault. In general, our approach involves the analysis

  20. Fault detection and diagnosis capabilities of test sequence selection

    E-print Network

    Thulsiraman, Krishnaiyan

    Review Fault detection and diagnosis capabilities of test sequence selection methods based on the FSM model T Ramalingam*, Anindya Dast and K ThuIasiraman* Different test sequence selection methods resolution in diagnosing the fault. The test sequence selection methods are then compared based on the length

  1. Observer-based fault detection for nuclear reactors

    E-print Network

    Li, Qing, 1972-

    2001-01-01

    This is a study of fault detection for nuclear reactor systems. Basic concepts are derived from fundamental theories on system observers. Different types of fault- actuator fault, sensor fault, and system dynamics fault ...

  2. Fault detection in dielectric grid scatterers.

    PubMed

    Brancaccio, Adriana; Solimene, Raffaele

    2015-04-01

    The problem of diagnosing a grid of small (in terms of the probing wavelength) dielectric scatterers is considered. The aim is to detect and locate possible defects occurring within a known grid when one (or more) scatterer is removed/missing (fault). The study is developed for the canonical case of a TM scalar two-dimensional geometry with the scatterers consisting of dielectric cylinders of small circular cross section. The scattering by a fault is modeled by relaying only to a priori information about the complete grid which leads to a numerically effective inversion procedures as the bulk of the numerical effort is to be done only once. Inversion is achieved by a truncated singular value decomposition scheme and results are provided in terms of closed form expressions for the probability of detection and of false alarm. This allows us to foreseen the achievable performance and to highlight the role of scattering configuration parameters. Numerical examples are also enclosed to corroborate theoretical outcomes. The case of two or more faults is considered as well. For such a case it is numerically shown that detection method still works well even though multiple scattering (occurring between faults) is neglected. PMID:25968659

  3. Signal injection as a fault detection technique.

    PubMed

    Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

    2011-01-01

    Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies. PMID:22163801

  4. Outlier Detection Rules for Fault Detection in Solar Photovoltaic Arrays

    E-print Network

    Lehman, Brad

    and fire hazards [2]. While the topic of fault tolerance and detection has received considerable attention analysis specifically for PV installation. Several fault detection models and monitoring systems have been studied for PV systems [8]­[14]. PV monitoring and fault detection models based on energy yield and power

  5. Method and apparatus for generating motor current spectra to enhance motor system fault detection

    Microsoft Academic Search

    D. J. Linehan; S. L. Bunch; C. T. Lyster

    1995-01-01

    A method and circuitry are disclosed for sampling periodic amplitude modulations in a nonstationary periodic carrier wave to determine frequencies in the amplitude modulations. The method and circuit are described in terms of an improved motor current signature analysis. The method insures that the sampled data set contains an exact whole number of carrier wave cycles by defining the rate

  6. Method and apparatus for generating motor current spectra to enhance motor system fault detection

    Microsoft Academic Search

    Daniel J. Linehan; Stanley L. Bunch; Carl T. Lyster

    1995-01-01

    A method and circuitry for sampling periodic amplitude modulations in a nonstationary periodic carrier wave to determine frequencies in the amplitude modulations. The method and circuit are described in terms of an improved motor current signature analysis. The method insures that the sampled data set contains an exact whole number of carrier wave cycles by defining the rate at which

  7. Model reconstruction using POD method for gray-box fault detection

    NASA Technical Reports Server (NTRS)

    Park, H. G.; Zak, M.

    2003-01-01

    This paper describes using Proper Orthogonal Decomposition (POD) method to create low-order dynamical models for the Model Filter component of Beacon-based Exception Analysis for Multi-missions (BEAM).

  8. Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test

    NASA Technical Reports Server (NTRS)

    Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)

    2008-01-01

    System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

  9. Fault detection in finite frequency domain for Takagi-Sugeno fuzzy systems with sensor faults.

    PubMed

    Li, Xiao-Jian; Yang, Guang-Hong

    2014-08-01

    This paper is concerned with the fault detection (FD) problem in finite frequency domain for continuous-time Takagi-Sugeno fuzzy systems with sensor faults. Some finite-frequency performance indices are initially introduced to measure the fault/reference input sensitivity and disturbance robustness. Based on these performance indices, an effective FD scheme is then presented such that the generated residual is designed to be sensitive to both fault and reference input for faulty cases, while robust against the reference input for fault-free case. As the additional reference input sensitivity for faulty cases is considered, it is shown that the proposed method improves the existing FD techniques and achieves a better FD performance. The theory is supported by simulation results related to the detection of sensor faults in a tunnel-diode circuit. PMID:24184791

  10. All-to-all sequenced fault detection system

    DOEpatents

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2010-11-02

    An apparatus, program product and method enable nodal fault detection by sequencing communications between all system nodes. A master node may coordinate communications between two slave nodes before sequencing to and initiating communications between a new pair of slave nodes. The communications may be analyzed to determine the nodal fault.

  11. Fault detection of univariate non-Gaussian data with Bayesian network

    E-print Network

    Paris-Sud XI, Université de

    Fault detection of univariate non-Gaussian data with Bayesian network Sylvain Verron, Teodor.verron@univ-angers.fr Abstract--The purpose of this article is to present a new method for fault detection with Bayesian network. The interest of this method is to propose a new structure of Bayesian network allowing to detect a fault

  12. An arc fault detection system

    SciTech Connect

    Jha, Kamal N.

    1997-12-01

    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.

  13. Transient fault detection via simultaneous multithreading

    Microsoft Academic Search

    Steven K. Reinhardt; Shubhendu S. Mukherjee

    2000-01-01

    Smaller feature sizes, reduced voltage levels, higher transistor counts, and reduced noise margins make future generations of microprocessors increasingly prone to transient hardware faults. Most commercial fault-tolerant computers use fully replicated hardware components to detect microprocessor faults. The components are lockstepped (cycle-by-cycle synchronized) to ensure that, in each cycle, they perform the same operation on the same inputs, producing the

  14. A fault detection approach for aero-engines based on PCA

    Microsoft Academic Search

    Lin Zhang; Min Huang; Dongpao Hong

    2009-01-01

    Traditional fault detection approaches for aeroengines based on PCA cannot effectively detect faults when the data does not follow the normal distribution. Meanwhile, there are few effective methods for the elimination of outliers during the modeling thus the model precision cannot be guaranteed. Aiming at a solution of the problems above, a new fault detection approach for aero-engines based on

  15. Predicting Fault Detection Effectiveness J. A. Morgan & G. J. Knafl W. E. Wong

    E-print Network

    Morgan, Joseph

    Predicting Fault Detection Effectiveness J. A. Morgan & G. J. Knafl W. E. Wong School of Computer Regression methods are used to model fault detection effectiveness in terms of several product and testing process measures. The relative importance of these product/process measures for predicting fault detection

  16. Trends in the application of model-based fault detection and diagnosis of technical processes

    Microsoft Academic Search

    R. Isermann; P. Ballé

    1997-01-01

    After a short overview of the historical development of model-based fault detection, some proposals for the terminology in the field of supervision, fault detection and diagnosis are stated, based on the work within the IFAC SAFEPROCESS Technical Committee. Some basic fault-detection and diagnosis methods are briefly considered. Then, an evaluation of publications during the last 5 years shows some trends

  17. A DWT-based approach for detection of interturn faults in power transformers

    Microsoft Academic Search

    Vahid Behjat; Abolfazl Vahedi

    2011-01-01

    Purpose – Interturn winding faults, one of the most important causes of power transformers failures, cannot be detected by existing detection methods until they develop into high-level faults with more severe damage to the transformer. The purpose of this paper is to describe development of a new discrete wavelet transform (DWT) based approach for detection of winding interturn faults. Design\\/methodology\\/approach

  18. Autonomous Fault Detection in Self-Healing Systems: Comparing Hidden Markov Models and Artificial Neural

    E-print Network

    Dobson, Simon

    Autonomous Fault Detection in Self-Healing Systems: Comparing Hidden Markov Models and Artificial of the art by allowing self-healing systems to detect faults with greater autonomy than existing]: Heuristic methods--Plan execution, formation, and generation Keywords self-healing systems; fault detection

  19. Negative Selection Algorithm for Aircraft Fault Detection

    NASA Technical Reports Server (NTRS)

    Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

    2004-01-01

    We investigated a real-valued Negative Selection Algorithm (NSA) for fault detection in man-in-the-loop aircraft operation. The detection algorithm uses body-axes angular rate sensory data exhibiting the normal flight behavior patterns, to generate probabilistically a set of fault detectors that can detect any abnormalities (including faults and damages) in the behavior pattern of the aircraft flight. We performed experiments with datasets (collected under normal and various simulated failure conditions) using the NASA Ames man-in-the-loop high-fidelity C-17 flight simulator. The paper provides results of experiments with different datasets representing various failure conditions.

  20. Arcing fault detection using artificial neural networks

    Microsoft Academic Search

    Tarlochan S. Sidhu; Gurdeep Singh; Mohindar S. Sachdev

    1998-01-01

    A technique that detects the presence of arcing faults is presented in this paper. The proposed technique analyzes the radiation produced due to arcing faults. Acoustic, infra-red and radio waves are recorded using appropriate sensors and a DSP-based data acquisition system. The recorded signals are then classified using artificial neural networks. The sensors, data acquisition system and design of the

  1. Fault Detection in DC Electro Motors Using the Continuous Wavelet Transform

    Microsoft Academic Search

    Miha Boltežar; Igor Simonovski; Martin Furlan

    2003-01-01

    Two time–frequency methods were used to detect typical faults in DC electro motors: the windowed Fourier transform and the continuous wavelet transform. Four groups containing three electro motors each were manufactured with typical faults and examined. These faults included a bearing fault, an increased unbalance, a fragmented brush and a fragmented collector. The velocity of the vibrations at selected points

  2. Evaluation of a Decoupling-Based Fault Detection and Diagnostic Technique - Part II: Field Evaluation and Application 

    E-print Network

    Li, H.; Braun, J.

    2006-01-01

    Existing methods addressing automated fault detection and diagnosis (FDD) for vapor compression air conditioning system have good performance for faults that occur individually, but they have difficulty in handling multiple-simultaneous faults...

  3. Detection, diagnosis, and evaluation of faults in vapor compression equipment

    Microsoft Academic Search

    Todd Michael Rossi

    1995-01-01

    This thesis develops techniques for automated detection, diagnostics, and evaluation of faults in vapor compression equipment. Fault evaluation was added to the more common steps of fault detection and diagnostics to consider the special aspects of performance degradation faults over abrupt faults. A model for testing these techniques in a simulation environment was developed. The model is described and experimental

  4. Design of arc fault detection system based on CAN bus

    Microsoft Academic Search

    Zong Ming; Yang Tian; Fengge Zhang

    2009-01-01

    Arc fault detection system (AFDS) is a device intended to protect the power system against the arc fault that may cause fire. When there is an arc fault, the scale of fault current is lower than the initialization of most of the protection devices installed in the lowers, hence AFDS is an effective device to detect the arc fault successfully

  5. Detecting Faults By Use Of Hidden Markov Models

    NASA Technical Reports Server (NTRS)

    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).

  6. Data Fault Detection in Medical Sensor Networks

    PubMed Central

    Yang, Yang; Liu, Qian; Gao, Zhipeng; Qiu, Xuesong; Meng, Luoming

    2015-01-01

    Medical body sensors can be implanted or attached to the human body to monitor the physiological parameters of patients all the time. Inaccurate data due to sensor faults or incorrect placement on the body will seriously influence clinicians’ diagnosis, therefore detecting sensor data faults has been widely researched in recent years. Most of the typical approaches to sensor fault detection in the medical area ignore the fact that the physiological indexes of patients aren’t changing synchronously at the same time, and fault values mixed with abnormal physiological data due to illness make it difficult to determine true faults. Based on these facts, we propose a Data Fault Detection mechanism in Medical sensor networks (DFD-M). Its mechanism includes: (1) use of a dynamic-local outlier factor (D-LOF) algorithm to identify outlying sensed data vectors; (2) use of a linear regression model based on trapezoidal fuzzy numbers to predict which readings in the outlying data vector are suspected to be faulty; (3) the proposal of a novel judgment criterion of fault state according to the prediction values. The simulation results demonstrate the efficiency and superiority of DFD-M. PMID:25774708

  7. Immunity-Based Aircraft Fault Detection System

    NASA Technical Reports Server (NTRS)

    Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

    2004-01-01

    In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

  8. Model based fault detection of vehicle suspension and hydraulic brake systems

    Microsoft Academic Search

    Marcus Börner; Harald Straky; Thomas Weispfenning; Rolf Isermann

    2002-01-01

    In modern vehicles, mechatronic systems are increasingly used. To improve reliability, safety and economy, an early recognition of small or drifting faults is becoming increasingly important. After a short introduction to methods of model based fault detection and diagnosis, application examples for fault detection of automotive vehicle suspension and hydraulic brake systems are given.

  9. Fault Detection and Isolation in Manufacturing Systems with an Identified Discrete Event Model

    E-print Network

    Paris-Sud XI, Université de

    Fault Detection and Isolation in Manufacturing Systems with an Identified Discrete Event Model) In this paper a generic method for fault detection and isolation (FDI) in manufacturing systems considered and controller built on the basis of observed fault free system behavior. An identification algorithm known from

  10. MULTIPLE FAULT DETECTION AND ISOLATION Weber P. , Gentil S. , Ripoll P.

    E-print Network

    Paris-Sud XI, Université de

    MULTIPLE FAULT DETECTION AND ISOLATION Weber P. , Gentil S. , Ripoll P. TTTT , Foulloy L. TTTT CNRS 40 (ripoll@esia.univ-savoie.fr, foulloy@esia.univ-savoie.fr) Abstract: Model-based fault detection methods allow the generation of residuals as fault indicators. Isolation is generally based

  11. Detect and classify faults using neural nets

    SciTech Connect

    Kezunovic, M.; Rikalo, I.

    1996-10-01

    The analysis of transmission line faults is essential to the proper performance of the power system. It is required if protective relays are to take the appropriate action and in monitoring the performance of relays, circuit breakers, and other protective and control elements. The detection and classification of transmission line faults is a fundamental component of such fault analysis. Another application of fault analysis is in software packages for automated analysis of digital fault recorder (DFR) files. Recently, such a package, called DFR Assistant, was developed for substation applications. This program can be installed locally in a substation, in which case it is connected directly to the DFR via a high speed parallel link, or it can be installed at a central station, in which case it can be configured to automatically analyze events coming from all DFRs.

  12. A Unified Nonlinear Adaptive Approach for Detection and Isolation of Engine Faults

    NASA Technical Reports Server (NTRS)

    Tang, Liang; DeCastro, Jonathan A.; Zhang, Xiaodong; Farfan-Ramos, Luis; Simon, Donald L.

    2010-01-01

    A challenging problem in aircraft engine health management (EHM) system development is to detect and isolate faults in system components (i.e., compressor, turbine), actuators, and sensors. Existing nonlinear EHM methods often deal with component faults, actuator faults, and sensor faults separately, which may potentially lead to incorrect diagnostic decisions and unnecessary maintenance. Therefore, it would be ideal to address sensor faults, actuator faults, and component faults under one unified framework. This paper presents a systematic and unified nonlinear adaptive framework for detecting and isolating sensor faults, actuator faults, and component faults for aircraft engines. The fault detection and isolation (FDI) architecture consists of a parallel bank of nonlinear adaptive estimators. Adaptive thresholds are appropriately designed such that, in the presence of a particular fault, all components of the residual generated by the adaptive estimator corresponding to the actual fault type remain below their thresholds. If the faults are sufficiently different, then at least one component of the residual generated by each remaining adaptive estimator should exceed its threshold. Therefore, based on the specific response of the residuals, sensor faults, actuator faults, and component faults can be isolated. The effectiveness of the approach was evaluated using the NASA C-MAPSS turbofan engine model, and simulation results are presented.

  13. Gear fault detection using customized multiwavelet lifting schemes

    NASA Astrophysics Data System (ADS)

    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.

  14. Unbalanced Underground Distribution Systems Fault Detection and Section Estimation

    NASA Astrophysics Data System (ADS)

    de Oliveira, Karen Rezende Caino; Salim, Rodrigo Hartstein; Filomena, André Darós; Resener, Mariana; Bretas, Arturo Suman

    This paper presents a novel fault detection and section estimation method for unbalanced underground distribution systems (UDS). The method proposed is based on artificial neural networks (ANNs) and wavelet transforms (WTs). The majority of UDS are characterized by having several single/double phase laterals and non-symmetrical lines. Also, Digital Fourier Transforms (DFT), used in the majority of traditional protection relays, supplies a low level of robustness to the fault diagnosis process due to its inversely proportional time-frequency characteristic. These characteristics compromise the traditional fault diagnosis methods performance. ANNs are capable of learning and generalizing, whereas WTs are robust tools capable of evaluating a signal's frequency range that can characterize the fault phenomenon. This paper describes the proposed diagnosis method and discusses the results obtained from simulated implementation. The obtained results demonstrate the capability and robustness of the technique indicating its potential for on-line applications.

  15. Vibration-based fault detection of sharp bearing faults in helicopters

    E-print Network

    Paris-Sud XI, Université de

    Vibration-based fault detection of sharp bearing faults in helicopters Victor Girondin , Herve the characteristic symptoms of sharp bearing faults (like localized spalling) from vibratory analysis. However mainly in identifying fault frequencies. Local bearing faults induce temporal periodic and impulsive

  16. Fault detection and management system for fault tolerant switched reluctance motor drives

    Microsoft Academic Search

    C. M. Stephens

    1989-01-01

    Fault-tolerance characteristics of the switched reluctance motor are discussed, and winding fault detectors are presented which recognize shorted motor windings. Logic circuitry in the inverter blocks the power switch gating signals of the affected phase at the receipt of a fault-detection signal from one of the fault detectors. The fault detectors were implemented on a laboratory drive system to demonstrate

  17. Reset Tree-Based Optical Fault Detection

    PubMed Central

    Lee, Dong-Geon; Choi, Dooho; Seo, Jungtaek; Kim, Howon

    2013-01-01

    In this paper, we present a new reset tree-based scheme to protect cryptographic hardware against optical fault injection attacks. As one of the most powerful invasive attacks on cryptographic hardware, optical fault attacks cause semiconductors to misbehave by injecting high-energy light into a decapped integrated circuit. The contaminated result from the affected chip is then used to reveal secret information, such as a key, from the cryptographic hardware. Since the advent of such attacks, various countermeasures have been proposed. Although most of these countermeasures are strong, there is still the possibility of attack. In this paper, we present a novel optical fault detection scheme that utilizes the buffers on a circuit's reset signal tree as a fault detection sensor. To evaluate our proposal, we model radiation-induced currents into circuit components and perform a SPICE simulation. The proposed scheme is expected to be used as a supplemental security tool. PMID:23698267

  18. Cell boundary fault detection system

    DOEpatents

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2011-04-19

    An apparatus and program product determine a nodal fault along the boundary, or face, of a computing cell. Nodes on adjacent cell boundaries communicate with each other, and the communications are analyzed to determine if a node or connection is faulty.

  19. Detecting Incipient Faults via Numerical Modeling and Statistical Change Detection

    Microsoft Academic Search

    Mirrasoul J. Mousavi; Karen L. Butler-Purry

    2010-01-01

    This paper deals with the detection of incipient faults in underground distribution systems using online voltage and current measurements. The approach presented in this paper is based on the numerical modeling of incipient fault patterns established from the oscillographic data. Specific energy features in the wavelet domain were extracted and used in the modeling task using the self-organizing map technology.

  20. Study on Fault Line Detection Based on Genetic Artificial Neural Network in Compensated Distribution System

    Microsoft Academic Search

    Tao Ji; Qingle Pang; Xinyun Liu

    2006-01-01

    The faulty line detection of single phase to earth fault in power system with neutral grounding via arc suppression coil has not been well solved. The commonly used single faulty line detection methods, such as wavelet transform method, the fifth harmonic current method and zero sequence current active components method, etc., can only process partial fault information, so their reliability

  1. Fault Detection in Dynamic Systems Using the Largest Lyapunov Exponent

    E-print Network

    Sun, Yifu

    2012-10-19

    .................................................................................... 76 5.2 Proposed Method for Incipient Fault Detection ............................. 76 5.3 A Real World Example .................................................................. 77 5.4 Experimental Results... machines, and automatic control systems are always accompanied by nonlinear dynamics which may exhibit chaotic behavior, especially as motion changes from regular to chaotic. Many traditional methods can’t effectively extract these useful nonlinear...

  2. Multiple-Fault Detection and Isolation Based on Disturbance Attenuation Theory

    NASA Astrophysics Data System (ADS)

    Murray, Emmanuell

    In this dissertation, a linear estimator for fault detection and isolation called the Game Theoretic Multiple-Fault Detection Filter is derived for both continuous and discrete systems. The detection filter uses a disturbance attenuation formulation to bound the transmission of disturbances to the output, approximately blocking all but one fault from each of a set of projected residuals. However, different from previous approximate methods for single-fault detection filters, the multiple-fault detection filter utilizes a secondary optimization problem to generate a solution for the estimator gain that achieves more advanced detection filter goals. Specifically, the current work examines an optimization that increases sensitivity of each projected residual to its target fault. For the continuous case, it is proven that the new detection filter approximates previous detection filters obtained from geometric and spectral theories and extends them to finite time-varying systems. Further, the detection filter is demonstrated via numerical examples.

  3. The Perils of Detecting Measurement Faults in Environmental Monitoring Networks

    E-print Network

    Amir, Yair

    The Perils of Detecting Measurement Faults in Environmental Monitoring Networks (Invited Paper by such networks are perturbed by sensor faults. In response, multiple fault detection techniques have been (e.g. rain events for soil moisture measurements) as faults, poten- tially discarding the most

  4. Double fault detection of cone-shaped redundant IMUs using wavelet transformation and EPSA.

    PubMed

    Lee, Wonhee; Park, Chan Gook

    2014-01-01

    A model-free hybrid fault diagnosis technique is proposed to improve the performance of single and double fault detection and isolation. This is a model-free hybrid method which combines the extended parity space approach (EPSA) with a multi-resolution signal decomposition by using a discrete wavelet transform (DWT). Conventional EPSA can detect and isolate single and double faults. The performance of fault detection and isolation is influenced by the relative size of noise and fault. In this paper; the DWT helps to cancel the high frequency sensor noise. The proposed technique can improve low fault detection and isolation probability by utilizing the EPSA with DWT. To verify the effectiveness of the proposed fault detection method Monte Carlo numerical simulations are performed for a redundant inertial measurement unit (RIMU). PMID:24556675

  5. Learning approach to nonlinear fault diagnosis: detectability analysis

    Microsoft Academic Search

    Marios M. Polycarpou; Alexander B. Trunov

    2000-01-01

    The learning approach to fault diagnosis provides a methodology for designing monitoring architectures which can be used for detection, identification and accommodation of failures in dynamical systems. This paper considers the issues of detectability conditions and detection time in a nonlinear fault diagnosis scheme based on the learning approach. First, conditions are derived to characterize the range of detectable faults.

  6. A distributed fault-detection and diagnosis system using on-line parameter estimation

    NASA Technical Reports Server (NTRS)

    Guo, T.-H.; Merrill, W.; Duyar, A.

    1991-01-01

    The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

  7. Catastrophic fault diagnosis in dynamic systems using bond graph methods

    SciTech Connect

    Yarom, Tamar.

    1990-01-01

    Detection and diagnosis of faults has become a critical issue in high performance engineering systems as well as in mass-produced equipment. It is particularly helpful when the diagnosis can be made at the initial design level with respect to a prospective fault list. A number of powerful methods have been developed for aiding in the general fault analysis of designs. Catastrophic faults represent the limit case of complete local failure of connections or components. They result in the interruption of energy transfer between corresponding points in the system. In this work the conventional approach to fault detection and diagnosis is extended by means of bond-graph methods to a wide variety of engineering systems. Attention is focused on catastrophic fault diagnosis. A catastrophic fault dictionary is generated from the system model based on topological properties of the bond graph. The dictionary is processed by existing methods to extract a catastrophic fault report to aid the engineer in performing a design analysis.

  8. Nonlinear system fault detection and isolation based on bootstrap particle filters

    E-print Network

    LeGland, François

    Nonlinear system fault detection and isolation based on bootstrap particle filters Qinghua ZHANG, France. Email: zhang@irisa.fr Abstract-- A particle filter based method for nonlinear system fault from the basic bootstrap particle filter, and capable of rejecting a subset of the faults possibly

  9. The Detection of Fault-Prone Programs

    Microsoft Academic Search

    John C. Munson; Taghi M. Khoshgoftaar

    1992-01-01

    The use of the statistical technique of discriminant analysis as a tool for the detection of fault-prone programs is explored. A principal-components procedure was employed to reduce simple multicollinear complexity metrics to uncorrelated measures on orthogonal complexity domains. These uncorrelated measures were then used to classify programs into alternate groups, depending on the metric values of the program. The criterion

  10. Arc Fault Detection Through Model Reference Estimation

    Microsoft Academic Search

    Jan B. Beck; David C. Nemir

    2006-01-01

    In most arc fault circuit breakers, arc detection is accomplished through the signature analysis of remotely sensed branch currents, with high frequency spectral components being indicative of arcing. This paper presents an alternative approach based upon system identification. A model is assumed for the load on the distribution bus. This model is updated continuously by comparing measured voltages and\\/or currents

  11. Fault detection and management system for fault-tolerant switched reluctance motor drives

    Microsoft Academic Search

    C. M. Stephens

    1991-01-01

    The superior fault tolerance characteristics of the switched reluctance motor (SRM) have been proved in a working laboratory drive system. The program started by defining the performance effects of various types of motor winding faults. Motor winding fault detection devices were developed, along with control circuitry, to isolate a faulted winding by blocking the gating signals to the semiconductor power

  12. Fault detection for mobile robots using redundant positioning systems

    E-print Network

    Jensfelt, Patric

    Fault detection for mobile robots using redundant positioning systems Paul Sundvall and Patric is a very important part of an autonomous mobile robot system. This means for instance that the robot should can be important for the rest of the robot system, for instance the top level planner. The method uses

  13. The process chemometrics approach to process monitoring and fault detection

    Microsoft Academic Search

    Barry M. Wise; Neal B. Gallagher

    1996-01-01

    Chemometrics, the application of mathematical and statistical methods to the analysis of chemical data, is finding ever widening applications in the chemical process environment. This article reviews the chemometrics approach to chemical process monitoring and fault detection. These approaches rely on the formation of a mathematical\\/statistical model that is based on historical process data. New process data can then be

  14. Performance Analysis of Fault Detection and Identification for Multiple Faults in GNSS and GNSS/INS Integration

    NASA Astrophysics Data System (ADS)

    Alqurashi, Muwaffaq; Wang, Jinling

    2015-03-01

    For positioning, navigation and timing (PNT) purposes, GNSS or GNSS/INS integration is utilised to provide real-time solutions. However, any potential sensor failures or faulty measurements due to malfunctions of sensor components or harsh operating environments may cause unsatisfactory estimation for PNT parameters. The inability for immediate detecting faulty measurements or sensor component failures will reduce the overall performance of the system. So, real time detection and identification of faulty measurements is required to make the system more accurate and reliable for different applications that need real time solutions such as real time mapping for safety or emergency purposes. Consequently, it is necessary to implement an online fault detection and isolation (FDI) algorithm which is a statistic-based approach to detect and identify multiple faults.However, further investigations on the performance of the FDI for multiple fault scenarios is still required. In this paper, the performance of the FDI method under multiple fault scenarios is evaluated, e.g., for two, three and four faults in the GNSS and GNSS/INS measurements under different conditions of visible satellites and satellites geometry. Besides, the reliability (e.g., MDB) and separability (correlation coefficients between faults detection statistics) measures are also investigated to measure the capability of the FDI method. A performance analysis of the FDI method is conducted under the geometric constraints, to show the importance of the FDI method in terms of fault detectability and separability for robust positioning and navigation for real time applications.

  15. An adaptive statistical time-frequency method for detection of broken bars and bearing faults in motors using stator current

    Microsoft Academic Search

    B. Yazici; G. B. Kliman

    1999-01-01

    It is well known that motor current is a nonstationary signal, the properties of which vary with respect to the time-varying normal operating conditions of the motor. As a result, Fourier analysis makes it difficult to recognize fault conditions from the normal operating conditions of the motor. Time-frequency analysis, on the other hand, unambiguously represents the motor current which makes

  16. Robust Fault Detection and Isolation for Stochastic Systems

    NASA Technical Reports Server (NTRS)

    George, Jemin; Gregory, Irene M.

    2010-01-01

    This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

  17. Fault detection and isolation with robust principal component analysis

    E-print Network

    Paris-Sud XI, Université de

    fault detection and isolation Let us consider a data matrix X N×n , with vector lines xT i , whichFault detection and isolation with robust principal component analysis Yvon THARRAULT, Gilles.tharrault@ensem.inpl-nancy.fr Abstract. Principal component analysis (PCA) is a powerful fault detection technique which has been widely

  18. Distributed Fault Detection Using Consensus of Markov Chains

    E-print Network

    Pollett, Phil

    Distributed Fault Detection Using Consensus of Markov Chains Dejan P. Jovanovi and Philip K. Pollett Abstract We propose a fault detection procedure appropriate for use in a variety of industrial Models. Index Terms Fault detection, consensus algorithm, mixtures of Markov chains, the EM algorithm

  19. Fault Detection and Load Distribution for the Wind Farm Challenge

    SciTech Connect

    Borchehrsen, Anders B.; Larsen, Jesper A.; Stoustrup, Jakob

    2014-08-24

    In this paper a fault detection system and a fault tolerant controller for a wind farm model. The wind farm model used is the one proposed as a public challenge. In the model three types of faults are introduced to a wind farm consisting of nine turbines. A fault detection system designed, by taking advantage of the fact that within a wind farm several wind turbines will be operating under all most identical conditions. The turbines are then grouped, and then turbines within each group are used to generate residuals for turbines in the group. The generated residuals are then evaluated using dynamical cumulative sum. The designed fault detection system is cable of detecting all three fault types occurring in the model. But there is room for improving the fault detection in some areas. To take advantage of the fault detection system a fault tolerant controller for the wind farm has been designed. The fault tolerant controller is a dispatch controller which is estimating the possible power at each individual turbine and then setting the reference accordingly. The fault tolerant controller has been compared to a reference controller. And the comparison shows that the fault tolerant controller performance better in all measures. The fault detection and a fault tolerant controller has been designed, and based on the simulated results the overall performance of the wind farm is improved on all measures. Thereby this is a step towards improving the overall performance of current and future wind farms.

  20. Bearing fault detection using wavelet packet transform of induction motor stator current

    Microsoft Academic Search

    Jafar Zarei; Javad Poshtan

    2007-01-01

    Induction motor vibrations, caused by bearing defects, result in the modulation of the stator current. In this research, bearing defect is detected using the stator current analysis via Meyer wavelet in the wavelet packet structure, with energy comparison as the fault index. The advantage of this method is in the detection of incipient faults. The presented method is evaluated using

  1. A bilinear fault detection observer and its application to a hydraulic drive system

    Microsoft Academic Search

    Dingli Yu; D. N. SHIELDS; S. DALEY

    1996-01-01

    A bilinear fault detection observer is proposed for bilinear systems with unknown input. A sufficient condition for the existence of the observer is given. The residual generated by this observer is decoupled from the unknown input. The method is applied to a hydraulic test rig to detect and isolate a large group of simulated faults. The effectiveness of the method

  2. Wavelet analysis based scheme for fault detection and classification in underground power cable systems

    Microsoft Academic Search

    W. Zhao; Y. H. Song; Y. Min

    2000-01-01

    This paper presents a new method for detecting and classifying fault transients in underground cable systems based on the use of discrete wavelet transform. A 400 kV underground cable system is simulated by ATP\\/EMTP (electro-magnetic transients program) under various system and fault conditions. Daubechies eight wavelet transform is employed to analyze fault transients for the development of a novel fault

  3. Detection and extraction of fault surfaces in 3D seismic data

    Microsoft Academic Search

    Israel Cohen; Nicholas Coult; Anthony A. Vassiliou

    2006-01-01

    We propose an efficient method for detecting and extract- ing fault surfaces in 3D-seismic volumes. The seismic data aretransformedintoavolumeoflocal-fault-extractionLFE estimatesthatrepresentsthelikelihoodthatagivenpointlies onafaultsurface.Wepartitionthefaultsurfacesintorelative- lysmalllinearportions,whichareidentifiedbyanalyzingtilt- ed and rotated subvolumes throughout the region of interest. Directional filtering and thresholding further enhance the seismic discontinuities that are attributable to fault surfaces. Subsequently, the volume of LFE estimates is skeletonized, and individual fault surfaces are extracted

  4. Weak fault signal detection of rolling bearing

    Microsoft Academic Search

    Meng Li

    2011-01-01

    The characteristics of local singularity of vibration signal under the wavelet transform are studied, and quantitative analysis of the noise reduction features of wavelet transform methods is carried out. Based on that the modulus maxima of the local singularity of fault vibration signal and noise of rolling bearing under wavelet transform has different propagation characteristics in different scales, the wavelet

  5. Multi-directional fault detection system

    DOEpatents

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2009-03-17

    An apparatus, program product and method checks for nodal faults in a group of nodes comprising a center node and all adjacent nodes. The center node concurrently communicates with the immediately adjacent nodes in three dimensions. The communications are analyzed to determine a presence of a faulty node or connection.

  6. Multi-directional fault detection system

    DOEpatents

    Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

    2010-11-23

    An apparatus, program product and method checks for nodal faults in a group of nodes comprising a center node and all adjacent nodes. The center node concurrently communicates with the immediately adjacent nodes in three dimensions. The communications are analyzed to determine a presence of a faulty node or connection.

  7. Multi-directional fault detection system

    DOEpatents

    Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D.; Smith, Brian Edward

    2010-06-29

    An apparatus, program product and method checks for nodal faults in a group of nodes comprising a center node and all adjacent nodes. The center node concurrently communicates with the immediately adjacent nodes in three dimensions. The communications are analyzed to determine a presence of a faulty node or connection.

  8. Envelope order tracking for fault detection in rolling element bearings

    NASA Astrophysics Data System (ADS)

    Guo, Yu; Liu, Ting-Wei; Na, Jing; Fung, Rong-Fong

    2012-12-01

    An envelope order tracking analysis scheme is proposed in the paper for the fault detection of rolling element bearing (REB) under varying-speed running condition. The developed method takes the advantages of order tracking, envelope analysis and spectral kurtosis. The fast kurtogram algorithm is utilized to obtain both optimal center frequency and bandwidth of the band-pass filter based on the maximum spectral kurtosis. The envelope containing vibration features of the incipient REB fault can be extracted adaptively. The envelope is re-sampled by the even-angle sampling scheme, and thus the non-stationary signal in the time domain is represented as a quasi-stationary signal in the angular domain. As a result, the frequency-smear problem can be eliminated in order spectrum and the fault diagnosis of REB in the varying-speed running condition of the rotating machinery is achieved. Experiments are conducted to verify the validity of the proposed method.

  9. Fault-detection technique in a WDM-PON.

    PubMed

    Park, Juhee; Baik, Jinserk; Lee, Changhee

    2007-02-19

    We propose and demonstrate a new in-service fault-localization method for a wavelength division multiplexing passive optical network (WDM-PON). This scheme uses a tunable OTDR realized by a wavelength-locked Fabry-Perot laser diode. We successfully detect the faults both at the feeder fiber and the drop fibers. The resolution and the dynamic range are 100 m and 12 dB, respectively. In addition, the crosstalk induced by the OTDR signal to the transmission data is negligible. PMID:19532377

  10. Transmission Line Fault Detection Using Time-Frequency Analysis

    Microsoft Academic Search

    S. R. Samantaray; P. K. Dash; G. Panda

    2005-01-01

    A new approach for fault detection in power system network using time-frequency analysis is presented in this paper. The S-transform with complex window is used for generating frequency contours(S-contours), which distinguishes the faulted condition from no-fault. Here the fault current data for one cycle back and one cycle from the fault inception is processed through S-transform to generate time-frequency patterns

  11. Design of unknown input observers and robust fault detection filters

    Microsoft Academic Search

    JIE CHEN; RON J. PATTON; HONG-YUE ZHANG

    1996-01-01

    Fault detection filters are a special class of observers that can generate directional residuals for the purpose of fault isolation. This paper proposes a new approach to design robust (in the disturbance de-coupling sense) fault detection filters which ensure that the residual vector, generated by this filter, has both robust and directional properties. This is done by combining the unknown

  12. Online Fault Detection and Tolerance for Photovoltaic Energy Harvesting Systems

    E-print Network

    Pedram, Massoud

    Online Fault Detection and Tolerance for Photovoltaic Energy Harvesting Systems Xue Lin 1 , Yanzhi (PV systems) are subject to PV cell faults, which decrease the efficiency of PV systems and even shorten the PV system lifespan. Manual PV cell fault detection and elimination are expensive and nearly

  13. PSEUDO POWER SIGNATURES FOR AIRCRAFT FAULT DETECTION AND IDENTIFICATION

    E-print Network

    Koppelman, David M.

    orthogonal components and permits the definition of narrow frequency bands where the effect of a fault1 PSEUDO POWER SIGNATURES FOR AIRCRAFT FAULT DETECTION AND IDENTIFICATION Min Luo, Louisiana State processing tools for fast fault detection in a model free framework. In this paper, we elaborate

  14. Bearing Fault Detection in DFIG-Based Wind Turbines Using the First Intrinsic Mode Function

    E-print Network

    Boyer, Edmond

    Bearing Fault Detection in DFIG-Based Wind Turbines Using the First Intrinsic Mode Function Y turbines so competitive as the classical electric power stations it is important to reduce the operational for bearing fault detection in DFIG-based wind turbines. The proposed method uses the first Intrinsic Mode

  15. Model-based Fault Detection and Isolation Using Neural Networks: An Industrial Gas Turbine Case Study

    Microsoft Academic Search

    Hasan Abbasi Nozari; Hamed Dehghan Banadaki; Mehdi Aliyari Shoorehdeli; Silvio Simani

    2011-01-01

    This study proposed a model based fault detection and isolation (FDI) method using multi-layer perceptron (MLP) neural network. Detection and isolation of realistic faults of an industrial gas turbine engine in steady-state conditions is mainly centered. A bank of MLP models which are obtained by nonlinear dynamic system identification is used to generate the residuals, and also simple thresholding is

  16. Automated Monitoring with a BSP Fault-Detection Test

    NASA Technical Reports Server (NTRS)

    Bickford, Randall L.; Herzog, James P.

    2003-01-01

    The figure schematically illustrates a method and procedure for automated monitoring of an asset, as well as a hardware- and-software system that implements the method and procedure. As used here, asset could signify an industrial process, power plant, medical instrument, aircraft, or any of a variety of other systems that generate electronic signals (e.g., sensor outputs). In automated monitoring, the signals are digitized and then processed in order to detect faults and otherwise monitor operational status and integrity of the monitored asset. The major distinguishing feature of the present method is that the fault-detection function is implemented by use of a Bayesian sequential probability (BSP) technique. This technique is superior to other techniques for automated monitoring because it affords sensitivity, not only to disturbances in the mean values, but also to very subtle changes in the statistical characteristics (variance, skewness, and bias) of the monitored signals.

  17. Fault detection and diagnosis using neural network approaches

    NASA Technical Reports Server (NTRS)

    Kramer, Mark A.

    1992-01-01

    Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

  18. Experimental Study of Fault Arc Protection Based on UV Pulse Method in High Voltage Switchgear

    NASA Astrophysics Data System (ADS)

    Wang, Jingang; Xu, Cheng; Sun, Jiaxiang

    2014-06-01

    Based on the relationship between electrical equipment discharge and ultraviolet radiation, this paper proposed the use of UV pulse method to detect switchgear arcing faults. Switchgear protection system based on this new technique detects arcing faults by analyzing the ultraviolet produced by electric arc. This technique was implemented and tested in laboratory, and the performance of the protection module was verified: it is capable of calculating the number of UV pulses quickly and precisely, which indicates the intensity of fault arc, and therefore it can be applied to arcing faults protection system for detecting faults.

  19. Abstract--The detection of single line-to-ground (SLG) fault in compensated distribution networks can be hampered by

    E-print Network

    Paris-Sud XI, Université de

    1 Abstract--The detection of single line-to-ground (SLG) fault in compensated distribution networks determine pre-fault values of the faulty line voltage. The discharging currents are absent at =0 propagation area. The fault detection can also be out of reach of steady state methods which are based

  20. Detecting Undetectable Controller Faults Using Power Analysis J. Carletta \\Lambda C. A. Papachristou y M. Nourani z

    E-print Network

    Nourani, Mehrdad

    Detecting Undetectable Controller Faults Using Power Analysis J. Carletta \\Lambda C. A. The effect of these faults on power consumption is explored, and a method based on power analysis is given for detecting these faults. Analysis is given for three example systems. 1 Introduction This work addresses

  1. Fault Detection and Isolation of Actuator Faults in Spacecraft Formation Flight

    Microsoft Academic Search

    Nader Meskin; K. Khorasani

    2006-01-01

    This paper investigates the development of fault detection and isolation (FDI) filters for spacecraft formation flight. A MIMO architecture for formation flying control is considered. By utilizing a geometric FDI methodology, a local\\/decentralized detection filter is developed for detecting faults in other spacecraft by determining the required unobservability subspace of the local system. In the case when such an unobservability

  2. A Probability Extension of PCA to Detect and Diagnose Sensor Faults in Air Handling Units 

    E-print Network

    Li, Z.

    2011-01-01

    Due to sensor faults, it is a challenge to successfully detect and diagnose component faults in HVAC systems. The Principal Component Analysis (PCA) method has become a popular method to tackle this problem in recent years, but PCA is not capable...

  3. A Probability Extension of PCA to Detect and Diagnose Sensor Faults in Air Handling Units

    E-print Network

    Li, Z.

    2011-01-01

    Due to sensor faults, it is a challenge to successfully detect and diagnose component faults in HVAC systems. The Principal Component Analysis (PCA) method has become a popular method to tackle this problem in recent years, but PCA is not capable...

  4. On Finding a Nearly Minimal Set of Fault Detection Tests for Combinational Logic Nets

    Microsoft Academic Search

    D. B. Armstrong

    1966-01-01

    A procedure is described for finding, by shortcut methods, a near-minimal set of tests for detecting all single faults in a combinational logic net. The procedure should prove useful for nets which are too large to be treated by more exact methods [2]. The set of tests so found also appears useful for diagnosing (i.e., locating) faults. The class of

  5. Robust parametric fault detection and isolation for nonlinear systems

    Microsoft Academic Search

    Xiaodong Zhang; Thomas Parisini; Marios Polycarpou

    1999-01-01

    Although most practical failure situations require nonlinear modeling, quite often the nonlinearity associated with the fault function is partially known based on past experience of plant technicians, with the uncertainty arising due to unknown parameters. Motivated by such practical considerations, this paper presents a robust fault diagnosis scheme for parametric faults in nonlinear dynamical systems. A detection and approximation observer

  6. Rapid detection of faults for safety critical aircraft operation

    Microsoft Academic Search

    Kai Goebel; Neil Eklund; Brent Brunell

    2004-01-01

    Fault diagnosis typically assumes a sufficiently large fault signature and enough time for a reliable decision to be reached. However, for a class of safety critical faults on commercial aircraft engines, prompt detection is paramount within a millisecond range to allow accommodation to avert undesired engine behavior. At the same time, false positives must be avoided to prevent inappropriate control

  7. Early fault detection in automotive ball bearings using the minimum variance cepstrum

    NASA Astrophysics Data System (ADS)

    Park, Choon-Su; Choi, Young-Chul; Kim, Yang-Hann

    2013-07-01

    Ball bearings in automotive wheels play an important role in a vehicle. They enable an automobile to run and simultaneously support the vehicle. Once faults are generated, even if they are small, they often grow fast even under normal driving condition and cause vibration and noise. Therefore, it is critical to detect faults as early as possible to prevent bearings from generating harsh noise and vibration. How early faults can be detected is associated with how well a detecting method finds the information of early faults from measured signal. Incipient faults are so small that the fault signal is inherently buried by noise. Minimum variance cepstrum (MVC) has been introduced for the observation of periodic impulse signal under noisy environments. We are particularly focusing on the definition of MVC that goes back to the original definition by Bogert et al. in comparison with the recently prevalent definition of cepstral analysis. In this work, the MVC is, therefore, obtained by liftering a logarithmic power spectrum, and the lifter bank is designed by the minimum variance algorithm. Furthermore, it is also shown how efficient the method is for detecting periodic fault signal made by early faults by using automotive ball bearings, with which an automobile is equipped under running conditions. We were able to detect incipient faults in 4 out of 12 normal bearings which passed acceptance test as well as in bearings that were recalled due to noise and vibration. In addition, we compared the results of the proposed method with results obtained using other older well-established early fault detection methods that were chosen from 4 groups of methods which were classified by the domain of observation. The results demonstrated that MVC determined bearing fault periods more clearly than other methods under the given condition.

  8. Fault measurement detection in an urban water supply network

    Microsoft Academic Search

    José Ragot; Didier Maquin

    2006-01-01

    For the improvement of the performance of technical processes, faults and abnormal system operation must be detected and identified. For that purpose different approaches for fault detection have been developed and, here, a model-based approach is used. A diagnosis strategy based on fuzzy residual analysis is presented in this paper. The proposed approach uses the analytical redundancy to detect and

  9. Dynamic fault detection and accommodation for dissipative distributed processes

    Microsoft Academic Search

    Antonios Armaou; Michael A. Demetriou

    2009-01-01

    This paper proposes a nonlinear detection observer for the component fault detection and accommodation of nonlinear distributed processes. Specifically, the proposed results constitute an extension to previous work which utilized a linear observer for both detection and diagnosis of component faults for the same class of nonlinear distributed processes. An advantage of the proposed nonlinear observer is not simply the

  10. Detection of arc fault based on frequency constrained independent component analysis

    NASA Astrophysics Data System (ADS)

    Yang, Kai; Zhang, Rencheng; Xu, Renhao; Chen, Yongzhi; Yang, Jianhong; Chen, Shouhong

    2015-02-01

    Arc fault is one of the main reasons of electrical fires. As a result of weakness, randomness and cross talk of arc faults, very few of methods have been successfully used to protect loads from all arc faults in low-voltage circuits. Therefore, a novel detection method is developed for detection of arc faults. The method is based on frequency constrained independent component analysis. In the process of the method derivation, a band-pass filter was introduced as a constraint condition to separate independent components of mixed signals. In the process of the independent component separations, although the fault mixed signals were under the conditions of the strong background noise and the frequency aliasing, the effective high frequency components of arc faults could be separated by frequency constrained independent component analysis. Based on the separated components, the power spectrums of them were calculated to classify the normal and the arc fault conditions. The validity of the developed method was verified by using an arc fault experimental platform set up. The results show that arc faults of nine typical electrical loads are successfully detected based on frequency constrained independent component analysis.

  11. VCSEL fault location apparatus and method

    DOEpatents

    Keeler, Gordon A. (Albuquerque, NM); Serkland, Darwin K. (Albuquerque, NM)

    2007-05-15

    An apparatus for locating a fault within an optical fiber is disclosed. The apparatus, which can be formed as a part of a fiber-optic transmitter or as a stand-alone instrument, utilizes a vertical-cavity surface-emitting laser (VCSEL) to generate a test pulse of light which is coupled into an optical fiber under test. The VCSEL is subsequently reconfigured by changing a bias voltage thereto and is used as a resonant-cavity photodetector (RCPD) to detect a portion of the test light pulse which is reflected or scattered from any fault within the optical fiber. A time interval .DELTA.t between an instant in time when the test light pulse is generated and the time the reflected or scattered portion is detected can then be used to determine the location of the fault within the optical fiber.

  12. Detection of faults and software reliability analysis

    NASA Technical Reports Server (NTRS)

    Knight, John C.

    1987-01-01

    Multi-version or N-version programming is proposed as a method of providing fault tolerance in software. The approach requires the separate, independent preparation of multiple versions of a piece of software for some application. These versions are executed in parallel in the application environment; each receives identical inputs and each produces its version of the required outputs. The outputs are collected by a voter and, in principle, they should all be the same. In practice there may be some disagreement. If this occurs, the results of the majority are taken to be the correct output, and that is the output used by the system. A total of 27 programs were produced. Each of these programs was then subjected to one million randomly-generated test cases. The experiment yielded a number of programs containing faults that are useful for general studies of software reliability as well as studies of N-version programming. Fault tolerance through data diversity and analytic models of comparison testing are discussed.

  13. Data-driven and adaptive statistical residual evaluation for fault detection with an automotive application

    NASA Astrophysics Data System (ADS)

    Svärd, Carl; Nyberg, Mattias; Frisk, Erik; Krysander, Mattias

    2014-03-01

    An important step in model-based fault detection is residual evaluation, where residuals are evaluated with the aim to detect changes in their behavior caused by faults. To handle residuals subject to time-varying uncertainties and disturbances, which indeed are present in practice, a novel statistical residual evaluation approach is presented. The main contribution is to base the residual evaluation on an explicit comparison of the probability distribution of the residual, estimated online using current data, with a no-fault residual distribution. The no-fault distribution is based on a set of a priori known no-fault residual distributions, and is continuously adapted to the current situation. As a second contribution, a method is proposed for estimating the required set of no-fault residual distributions off-line from no-fault training data. The proposed residual evaluation approach is evaluated with measurement data on a residual for fault detection in the gas-flow system of a Scania truck diesel engine. Results show that small faults can be reliably detected with the proposed approach in cases where regular methods fail.

  14. Toward Reducing Fault Fix Time: Understanding Developer Behavior for the Design of Automated Fault Detection Tools, the Full Report

    E-print Network

    Young, R. Michael

    Toward Reducing Fault Fix Time: Understanding Developer Behavior for the Design of Automated Fault}@csc.ncsu.edu Abstract The longer a fault remains in the code from the time it was injected, the more time it will take to fix the fault. Increasingly, automated fault detection (AFD) tools are providing developers

  15. A fault detection service for wide area distributed computations

    Microsoft Academic Search

    Paul Stelling; Cheryl DeMatteis; Ian Foster; Carl Kesselman; Craig Lee; Gregor von Laszewski

    1999-01-01

    The potential for faults in distributed computing systems is a significant complicating factor for application developers.\\u000a While a variety of techniques exist for detecting and correcting faults, the implementation of these techniques in a particular\\u000a context can be difficult. Hence, we propose a fault detection service designed to be incorporated, in a modular fashion, into\\u000a distributed computing systems, tools, or

  16. Application of fault detection and identification (FDI) techniques in power regulating systems of nuclear reactors

    Microsoft Academic Search

    Kallol Roy; R. N. Banavar; S. Thangasamy

    1998-01-01

    Application of failure detection and identification (FDI) algorithms have essentially been limited to identification of a global fault in the system, and no further attempts have been made to locate subcomponent faults for root cause analysis. This paper presents Kalman filter-based methods for FDI in power regulating systems of nuclear reactors. The attempt here is to explain how the behavior

  17. Evaluation of a Decoupling-Based Fault Detection and Diagnostic Technique - Part I: Field Emulation Evaluation

    E-print Network

    Li, H.; Braun, J.

    2006-01-01

    and Diagnosis Approach for Packaged Air Conditioners, Ph.D. Thesis, School of Mechanical Engineering, Purdue University, 2004. [4] Dexter, Arthur; Pakanen, Jouko et al., Demonstrating Automated Fault Detection and Diagnosis Methods in Real Buildings. Espoo...

  18. Systematic and Design Diversity - Software Techniques for Hardware Fault Detection

    Microsoft Academic Search

    Tomislav Lovric; Brown Boveri

    1994-01-01

    For the detection of hardware operational faults in most safe systems static redundancy is used. Thus, in the most simple case we have the well known Duplex System. If design fault detection is required, design diversity in the software has to be used, too. We suggest the combined utilization of so called systematic diversity and design diversity in a time-redundant

  19. Fault Detection, Identification and Accommodation for an Electro-hydraulic

    E-print Network

    Yao, Bin

    Fault Detection, Identification and Accommodation for an Electro-hydraulic System: An Adaptive in electro-hydraulic systems. It is well known fact that any realistic model of a hydraulic system suffers, such a scheme becomes a natural choice for designing robust fault detection algorithms for electro-hydraulic

  20. Fault detection\\/monitoring using time Petri nets

    Microsoft Academic Search

    V. S. Srinivasan; M. A. Jafari

    1993-01-01

    While controlling manufacturing systems, real time data is collected through sensory devices or some other means and fed back to the controller for the purpose of monitoring that system. Monitoring refers to the analysis of data collected from the system. It involves fault detection and diagnostics. Here, we shall emphasize the fault detection aspects of monitoring. Modeling the control system

  1. A net-oriented method for realistic fault analysis

    Microsoft Academic Search

    Hua Xue; Chennian Di; Jochen A. G. Jess

    1993-01-01

    In this paper, a net-oriented method to analyze realistic faults ispresented. The keypointof the method is to analyze the faults caused by a spot defect net by net. First the possible faults related to a net are extracted. Hence all faults in a layout are extracted by enumerating all nets on the layout. An approach to calculate the critical area

  2. Detection of faults and software reliability analysis

    NASA Technical Reports Server (NTRS)

    Knight, J. C.

    1987-01-01

    Specific topics briefly addressed include: the consistent comparison problem in N-version system; analytic models of comparison testing; fault tolerance through data diversity; and the relationship between failures caused by automatically seeded faults.

  3. Fiber Bragg Grating sensor for fault detection in radial and network transmission lines.

    PubMed

    Moghadas, Amin A; Shadaram, Mehdi

    2010-01-01

    In this paper, a fiber optic based sensor capable of fault detection in both radial and network overhead transmission power line systems is investigated. Bragg wavelength shift is used to measure the fault current and detect fault in power systems. Magnetic fields generated by currents in the overhead transmission lines cause a strain in magnetostrictive material which is then detected by Fiber Bragg Grating (FBG). The Fiber Bragg interrogator senses the reflected FBG signals, and the Bragg wavelength shift is calculated and the signals are processed. A broadband light source in the control room scans the shift in the reflected signal. Any surge in the magnetic field relates to an increased fault current at a certain location. Also, fault location can be precisely defined with an artificial neural network (ANN) algorithm. This algorithm can be easily coordinated with other protective devices. It is shown that the faults in the overhead transmission line cause a detectable wavelength shift on the reflected signal of FBG and can be used to detect and classify different kind of faults. The proposed method has been extensively tested by simulation and results confirm that the proposed scheme is able to detect different kinds of fault in both radial and network system. PMID:22163416

  4. Fault detection in a ball bearing system using minimum variance cepstrum

    NASA Astrophysics Data System (ADS)

    Choi, Young-Chul; Kim, Yang-Hann

    2007-05-01

    The signals that can be obtained from rotating machines convey information on a machine operating condition. For example, if the machine has faults, it generates a signal that is usually composed of pulse signals. This paper addresses the way in which we can find the faults for periodic pulse signals. Specifically, we have an interest in the case that it is embedded in noise. How well we can detect the fault signal in noise directly determines the quality of fault diagnosis of rotating machines. We propose a signal processing method to detect fault signals in noisy environments. The proposed method is 'minimum variance cepstrum' because it minimizes the variance of the signal power in its cepstrum representation. To test the performance of this technique, various experiments have been performed for ball bearing elements that have man-made faults. Results show that the proposed technique is quite powerful in the detection of faults in noisy environments. In other words, it is possible to detect faults earlier than with conventional methods (McFadden and Smith 1984 J. Sound Vib. 96 69-82, Ho and Randall 1999 6th Int. Congress on Sound and Vibration pp 2943-50, Lee and White 1998 J. Sound Vib. 217 485-505, Kim et al 1991 Mech. Syst. Signal Process. 5 461-73, Staszewski and Tomlinson 1997 Mech. Syst. Signal Process. 11 331-50).

  5. Advanced Fault Diagnosis Methods in Molecular Networks

    PubMed Central

    Habibi, Iman; Emamian, Effat S.; Abdi, Ali

    2014-01-01

    Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally. PMID:25290670

  6. INDUCTION MOTOR FAULT DIAGNOSTIC AND MONITORING METHODS

    E-print Network

    Povinelli, Richard J.

    INDUCTION MOTOR FAULT DIAGNOSTIC AND MONITORING METHODS by Aderiano M. da Silva, B.S. A Thesis Acknowledgement Special thanks for my advisor Dr. Richard J. Povinelli for his teaching, support and encouragement, support and discussions during this research. Finally, I would like to thanks my wife Marcia Silva for her

  7. Digital signal processing algorithm for arcing faults detection and fault distance calculation on transmission lines

    Microsoft Academic Search

    Milenko B. Djuri?; Zoran M. Radojevi?; Vladimir V. Terzija

    1997-01-01

    In this paper a new digital signal processing algorithm for arcing fault detection and fault distance calculation is presented. It was derived by processing the line terminal voltages and currents. A simple square wave arc voltage model was assumed to represent the long arc in free air. The unknown model parameters (the line resistance and inductance, and arc voltage amplitude)

  8. Optimal robust fault detection for linear discrete time systems

    Microsoft Academic Search

    Nike Liu; Kemin Zhou

    2007-01-01

    This paper considers robust fault detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault detection problems, such as H-\\/Hinfin, H2\\/Hinfin, and Hinfin\\/Hinfin problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Moreover, the optimal filters for those problems do not depend on

  9. Fault detection and classification in electrical power transmission system using artificial neural network.

    PubMed

    Jamil, Majid; Sharma, Sanjeev Kumar; Singh, Rajveer

    2015-01-01

    This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment. PMID:26180754

  10. Expert system structures for fault detection in spaceborne power systems

    NASA Technical Reports Server (NTRS)

    Watson, Karan; Russell, B. Don; Hackler, Irene

    1988-01-01

    This paper presents an architecture for an expert system structure suitable for use with power system fault detection algorithms. The system described is not for the purpose of reacting to faults which have occurred, but rather for the purpose of performing on-line diagnostics and parameter evaluation to determine potential or incipient fault conditions. The system is also designed to detect high impedance or arcing faults which cannot be detected by conventional protection devices. This system is part of an overall monitoring computer hierarchy which would provide a full evaluation of the status of the power system and react to both incipient and catastrophic faults. An approximate hardware structure is suggested and software requirements are discussed. Modifications to CLIPS software, to capitalize on features offered by expert systems, are presented. It is suggested that such a system would have significant advantages over existing protection philosophy.

  11. ASCS online fault detection and isolation based on an improved MPCA

    NASA Astrophysics Data System (ADS)

    Peng, Jianxin; Liu, Haiou; Hu, Yuhui; Xi, Junqiang; Chen, Huiyan

    2014-09-01

    Multi-way principal component analysis (MPCA) has received considerable attention and been widely used in process monitoring. A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces. However, low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model. This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information. The MPCA model and the knowledge base are built based on the new subspace. Then, fault detection and isolation with the squared prediction error (SPE) statistic and the Hotelling ( T 2) statistic are also realized in process monitoring. When a fault occurs, fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables. For fault isolation of subspace based on the T 2 statistic, the relationship between the statistic indicator and state variables is constructed, and the constraint conditions are presented to check the validity of fault isolation. Then, to improve the robustness of fault isolation to unexpected disturbances, the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation. Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system (ASCS) to prove the correctness and effectiveness of the algorithm. The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model, and sets the relationship between the state variables and fault detection indicators for fault isolation.

  12. Motor Fault Detection Using a Rogowski Sensor Without an Integrator

    Microsoft Academic Search

    Oscar Poncelas; Javier A. Rosero; Jordi Cusido; Juan Antonio Ortega; Luis Romeral

    2009-01-01

    This paper presents a new approach for the current acquisition system in motor fault detection applications. This paper includes the study, design, and implementation of a Rogowski-coil current sensor without the integrator circuit that is typically used. The circuit includes an autotuning block able to adjust to different motor speeds. Equalizing the amplitudes of the fundamental and fault harmonics leads

  13. Fault detection and multiclassifier fusion for unmanned aerial vehicles (UAVs)

    Microsoft Academic Search

    Weizhong Yan

    2001-01-01

    UAVs demand more accurate fault accommodation for their mission manager and vehicle control system in order to achieve a reliability level that is comparable to that of a pilot aircraft. This paper attempts to apply multi-classifier fusion techniques to achieve the necessary performance of the fault detection function for the Lockheed Martin Skunk Works (LMSW) UAV Mission Manager. Three different

  14. Distributed Fault Detection for Wireless Sensor Based on Weighted Average

    Microsoft Academic Search

    Sai Ji; Shen-fang Yuan; Ting-huai Ma; Chang Tan

    2010-01-01

    This paper presents a distributed fault detection algorithm for wireless sensor networks (WSNs) by exploring the weighted average value scheme. Considering the spatial correlations in WSNs, a faulty sensor can diagnose itself through comparing its own sensed data with the average of neighbors' data. Simulation results show that sensor nodes with permanent faults are identified with high accuracy for a

  15. ARCING HIGH IMPEDANCE FAULT DETECTION USING REAL CODED GENETIC ALGORITHM

    Microsoft Academic Search

    Naser Zamanan; Jan Sykulski; A. K. Al-Othman

    Safety and reliability are two of the most important aspects of electric power supply systems. Sensitivity and robustness to detect and isolate faults can influence the safety and reliability of such systems. Overcurrent relays are generally used to protect the high voltage feeders in distribution systems. Downed conductors, tree branches touching conductors, and failing insulators often cause high-impedance faults in

  16. AUTOMATED ROLLING CONTACT BEARING FAULT DETECTION USING CEPSTRUM ANALYSIS

    Microsoft Academic Search

    David J. Van Dyke; William A. Watts

    Integral to a versatile automated expert diagnostic system is the ability to detect rolling contact bearing wear without specific knowledge of the type or geometry of the bearings in the machine component. The fact that rolling contact bearing faults generate harmonics and sidebands lends itself to the application of Cepstrum analysis. An algorithm is described in which bearing fault related

  17. Observer and data-driven-model-based fault detection in power plant coal mills

    SciTech Connect

    Odgaard, P.F.; Lin, B.; Jorgensen, S.B. [University of Aalborg, Aalborg (Denmark). Dept. of Electrical Systems

    2008-06-15

    This paper presents and compares model-based and data-driven fault detection approaches for coal mill systems. The first approach detects faults with an optimal unknown input observer developed from a simplified energy balance model. Due to the time-consuming effort in developing a first principles model with motor power as the controlled variable, data-driven methods for fault detection are also investigated. Regression models that represent normal operating conditions (NOCs) are developed with both static and dynamic principal component analysis and partial least squares methods. The residual between process measurement and the NOC model prediction is used for fault detection. A hybrid approach, where a data-driven model is employed to derive an optimal unknown input observer, is also implemented. The three methods are evaluated with case studies on coal mill data, which includes a fault caused by a blocked inlet pipe. All three approaches detect the fault as it emerges. The optimal unknown input observer approach is most robust, in that, it has no false positives. On the other hand, the data-driven approaches are more straightforward to implement, since they just require the selection of appropriate confidence limit to avoid false detection. The proposed hybrid approach is promising for systems where a first principles model is cumbersome to obtain.

  18. Bearings fault detection in helicopters using frequency readjustment and cyclostationary analysis

    E-print Network

    Boyer, Edmond

    Bearings fault detection in helicopters using frequency readjustment and cyclostationary analysis-based automated framework dealing with local faults occurring on bearings in the transmission of a helicopter for operational helicopter monitoring. Keywords: fault detection, helicopter, health monitoring, rolling element

  19. Fault diagnosis of ball bearings using machine learning methods

    Microsoft Academic Search

    P. K. Kankar; Satish C. Sharma; S. P. Harsha

    2011-01-01

    Ball bearings faults are one of the main causes of breakdown of rotating machines. Thus, detection and diagnosis of mechanical faults in ball bearings is very crucial for the reliable operation. This study is focused on fault diagnosis of ball bearings using artificial neural network (ANN) and support vector machine (SVM). A test rig of high speed rotor supported on

  20. Vibration-based fault detection of accelerometers in helicopters

    E-print Network

    Paris-Sud XI, Université de

    than standard indicators. Keywords: accelerometers; vibration; helicopter; monitoring; skewness; HUMSVibration-based fault detection of accelerometers in helicopters Victor Girondin , Mehena Loudahi LAGIS - UMR CNRS 8219 Universit´e Lille 1 Boulevard Langevin 59655 Villeneuve d'Ascq Abstract: Vibration

  1. Non-intrusive fault detection in reciprocating compressors

    E-print Network

    Schantz, Christopher James

    2011-01-01

    This thesis presents a set of techniques for non-intrusive sensing and fault detection in reciprocating compressors driven by induction motors. The procedures developed here are "non-intrusive" because they rely only on ...

  2. Low cost fault detection system for railcars and tracks 

    E-print Network

    Vengalathur, Sriram T.

    2004-09-30

    A "low cost fault detection system" that identifies wheel flats and defective tracks is explored here. This is achieved with the conjunction of sensors, microcontrollers and Radio Frequency (RF) transceivers. The objective of the proposed research...

  3. Occupancy Based Fault Detection on Building Level - a Feasibility Study

    E-print Network

    Tuip, B.; Houten, M.; Trcka, M.; Hensen, M.

    2010-01-01

    based on real time weather conditions and occupancy. Fault detection is performed by comparing this predicted consumption with measured values. The prototype procedure is currently tested in an office building in the Netherlands, the first results...

  4. Fault detection of multivariable system using its directional properties 

    E-print Network

    Pandey, Amit Nath

    2006-04-12

    A novel algorithm for making the combination of outputs in the output zero direction of the plant always equal to zero was formulated. Using this algorithm and the result of MacFarlane and Karcanias, a fault detection ...

  5. Optimal solutions to multi-objective robust fault detection problems

    Microsoft Academic Search

    Nike Liu; Kemin Zhou

    2007-01-01

    This paper will give complete, analytic, and optimal solutions to several robust fault detection problems that have been considered in the research community in the last twenty years. It is shown that several well-recognized robust fault detection problems, such as H-\\/Hinfin, H2\\/Hinfin, and Hinfin\\/Hinfin problems, have a very simple optimal solution in an observer form by solving a standard algebraic

  6. Soft Computing Application in Fault Detection of Induction Motor

    SciTech Connect

    Konar, P.; Puhan, P. S.; Chattopadhyay, P. Dr. [Electrical Engineering Department, BESUS, Shibpur (India)

    2010-10-26

    The paper investigates the effectiveness of different patter classifier like Feed Forward Back Propagation (FFBPN), Radial Basis Function (RBF) and Support Vector Machine (SVM) for detection of bearing faults in Induction Motor. The steady state motor current with Park's Transformation has been used for discrimination of inner race and outer race bearing defects. The RBF neural network shows very encouraging results for multi-class classification problems and is hoped to set up a base for incipient fault detection of induction motor. SVM is also found to be a very good fault classifier which is highly competitive with RBF.

  7. A Hierarchical Fault Diagnosis Method Using a Decision Support System Applied to a Chemical Plant

    E-print Network

    Paris-Sud XI, Université de

    A Hierarchical Fault Diagnosis Method Using a Decision Support System Applied to a Chemical Plant D. A hierarchical scheme of fault detection and isolation based on Decision Support System (DSS) is presentedHeuristic Symptoms DECISION Figure 1: Architecture of a Decision Support System This paper is organised as follows

  8. Detecting Hidden Faults and Other Lineations with UAVSAR

    NASA Astrophysics Data System (ADS)

    Parker, J. W.; Glasscoe, M. T.; Donnellan, A.

    2013-12-01

    Jay Parker, Margaret Glasscoe, Andrea Donnellan Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA The M7.2 El Mayor Cucapah Earthquake of April 4, 2010 is the main earthquake to date observed by the NASA UAVSAR. By observing with repeat passes (October 2009, April 2010 captures the coseismic strain pattern, and subsequent flights capture the postseismic process) over the adjoining portion of California, the interferometric phase maps of geodetic displacements are exceptionally high definition (pixel size is roughly 7 m) records of the extended deformation field from the earthquake process, including revelation of a rich network of plate parallel and conjugate faulting, apparently slipping sympathetically to the earthquake-induced quasistatic changes in stress. While the most significant of these faults have been documented by cooperative use of UAVSAR maps and field research, a subsequent opportunity arises: to use this data to develop and validate an automated approach to detecting faults and other lineations directly from the UAVSAR unwrapped phase product that corresponds to a single-component deformation map. The Canny edge detection algorithm is employed, after a preparation stage to clean the data. This preprocessing step is tailored to the nature of the radar phase data: data dropouts in single pixels and extended areas (blown sand dunes, farms) are a much larger problem than background white noise. Blocks of typically 3x3 pixels are currently reduced to a single value, the average after bad pixels are discarded. The smoothing methods typically used with the Canny method are minimized (smoothing makes data drop-out problems worse). The aperture size that determines a gradient estimation is chosen large (7 vs. the typical 3), as this is found to produce continuous (rather than dashed) lineations. The main Canny threshold is chosen to correspond to a user selected slip threshold in mm. Reasonable maps of lineations in the Salton Trough occur with a threshold of 3mm: higher values result in a loss of interesting lineations; lower ones produce excess clutter. Lineation detection from InSAR phase will miss faults parallel to the aircraft flight line. But because it relies on phase changes over small (~20 m) distances the lineations are unaffected by most atmospheric water vapor effects, uncompensated aircraft motion, and distributed tectonic deformation

  9. Subspace-based fault detection algorithms for vibration monitoring

    Microsoft Academic Search

    Michèle Basseville; Maher Abdelghani; Albert Benveniste

    2000-01-01

    We address the problem of detecting faults modeled as changes in the eigenstructureof a linear dynamical system. This problem is of primary interest for structuralvibration monitoring. The purpose of the paper is to describe and analyze newfault detection algorithms, based on recent stochastic subspace-based identificationmethods and the statistical local approach to the design of detection algorithms.

  10. Methods to identify intermittent electrical and mechanical faults in permanent magnet AC drives based on wavelet analysis

    Microsoft Academic Search

    Wesley G. Zanardelli; Elias G. Strangas

    2005-01-01

    Prognosis of failures of electric drives can be achieved through the detection of non-catastrophic faults. As the frequency and severity of these faults increase, the expected working life of the drive decreases, leading to eventual failure. In this work, a method is presented to identify developing electrical and mechanical faults based on analysis of the undecimated discrete wavelet transform of

  11. Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.

    PubMed

    Li, Ke; Chen, Peng

    2011-01-01

    Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks. PMID:22163833

  12. Robust Fault Detection System for Insulin Pump Therapy Using Continuous Glucose Monitoring

    PubMed Central

    Herrero, Pau; Calm, Remei; Vehí, Josep; Armengol, Joaquim; Georgiou, Pantelis; Oliver, Nick; Tomazou, Christofer

    2012-01-01

    Background The popularity of continuous subcutaneous insulin infusion (CSII), or insulin pump therapy, as a way to deliver insulin more physiologically and achieve better glycemic control in diabetes patients has increased. Despite the substantiated therapeutic advantages of using CSII, its use has also been associated with an increased risk of technical malfunctioning of the device, which leads to an increased risk of acute metabolic complications, such as diabetic ketoacidosis. Current insulin pumps already incorporate systems to detect some types of faults, such as obstructions in the infusion set, but are not able to detect other types of fault such as the disconnection or leakage of the infusion set. Methods In this article, we propose utilizing a validated robust model-based fault detection technique, based on interval analysis, for detecting disconnections of the insulin infusion set. For this purpose, a previously validated metabolic model of glucose regulation in type 1 diabetes mellitus (T1DM) and a continuous glucose monitoring device were used. As a first step to assess the performance of the presented fault detection system, a Food and Drug Administration-accepted T1DM simulator was employed. Results Of the 100 in silico tests (10 scenarios on 10 subjects), only two false negatives and one false positive occurred. All faults were detected before plasma glucose concentration reached 300 mg/dl, with a mean plasma glucose detection value of 163 mg/dl and a mean detection time of 200 min. Conclusions Interval model-based fault detection has been proven (in silico) to be an effective tool for detecting disconnection faults in sensor-augmented CSII systems. Proper quantification of the uncertainty associated with the employed model has been observed to be crucial for the good performance of the proposed approach. PMID:23063040

  13. Low-cost inverter based detection of rotor faults in induction machines for quality management systems

    Microsoft Academic Search

    Thomas M. Wolbank; J. L. Machl; R. Woehrnschimmel; R. Schneiderbauer

    2004-01-01

    Most fault detection systems for rotor bar defects require specific load conditions or at least sufficient moments of inertia to establish a minimum load by repetitive acceleration or deceleration. The application of a method able to detect a rotor defect at no load condition is thus advantageous especially for quality management systems in the manufacturing process where a high number

  14. Investigation of advanced fault insertion and simulator methods

    NASA Technical Reports Server (NTRS)

    Dunn, W. R.; Cottrell, D.

    1986-01-01

    The cooperative agreement partly supported research leading to the open-literature publication cited. Additional efforts under the agreement included research into fault modeling of semiconductor devices. Results of this research are presented in this report which is summarized in the following paragraphs. As a result of the cited research, it appears that semiconductor failure mechanism data is abundant but of little use in developing pin-level device models. Failure mode data on the other hand does exist but is too sparse to be of any statistical use in developing fault models. What is significant in the failure mode data is that, unlike classical logic, MSI and LSI devices do exhibit more than 'stuck-at' and open/short failure modes. Specifically they are dominated by parametric failures and functional anomalies that can include intermittent faults and multiple-pin failures. The report discusses methods of developing composite pin-level models based on extrapolation of semiconductor device failure mechanisms, failure modes, results of temperature stress testing and functional modeling. Limitations of this model particularly with regard to determination of fault detection coverage and latency time measurement are discussed. Indicated research directions are presented.

  15. Aircraft Fault Detection and Classification Using Multi-Level Immune Learning Detection

    NASA Technical Reports Server (NTRS)

    Wong, Derek; Poll, Scott; KrishnaKumar, Kalmanje

    2005-01-01

    This work is an extension of a recently developed software tool called MILD (Multi-level Immune Learning Detection), which implements a negative selection algorithm for anomaly and fault detection that is inspired by the human immune system. The immunity-based approach can detect a broad spectrum of known and unforeseen faults. We extend MILD by applying a neural network classifier to identify the pattern of fault detectors that are activated during fault detection. Consequently, MILD now performs fault detection and identification of the system under investigation. This paper describes the application of MILD to detect and classify faults of a generic transport aircraft augmented with an intelligent flight controller. The intelligent control architecture is designed to accommodate faults without the need to explicitly identify them. Adding knowledge about the existence and type of a fault will improve the handling qualities of a degraded aircraft and impact tactical and strategic maneuvering decisions. In addition, providing fault information to the pilot is important for maintaining situational awareness so that he can avoid performing an action that might lead to unexpected behavior - e.g., an action that exceeds the remaining control authority of the damaged aircraft. We discuss the detection and classification results of simulated failures of the aircraft's control system and show that MILD is effective at determining the problem with low false alarm and misclassification rates.

  16. Fault Tree Analysis, Methods, and Applications ? A Review

    Microsoft Academic Search

    W. S. Lee; D. L. Grosh; F. A. Tillman; C. H. Lie

    1985-01-01

    This paper reviews and classifies fault-tree analysis methods developed since 1960 for system safety and reliability. Fault-tree analysis is a useful analytic tool for the reliability and safety of complex systems. The literature on fault-tree analysis is, for the most part, scattered through conference proceedings and company reports. We have classified the literature according to system definition, fault-tree construction, qualitative

  17. Automated Fault Detection for DIII-D Tokamak Experiments

    SciTech Connect

    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.

  18. Detecting BGP configuration faults with static analysis

    Microsoft Academic Search

    Nick Feamster; Hari Balakrishnan

    2005-01-01

    The Internet is composed of many independent autonomous systems (ASes) that exchange reachability information to destinations using the Border Gateway Protocol (BGP). Network operators in each AS configure BGP routers to control the routes that are learned, selected, and announced to other routers. Faults in BGP configuration can cause forwarding loops, packet loss, and unintended paths between hosts, each of

  19. MIL-M-38510/470 test vectors: Fault detection efficiency measurement via hardware fault simulation. [rca 1802 microprocessor

    NASA Technical Reports Server (NTRS)

    Timoc, C. C.

    1980-01-01

    The stuck fault detection efficiency of the test vectors developed for the MIL-M-38510/470 NASA was measured using a hardware stuck fault simulator for the 1802 microprocessor. Thirty-nine stuck faults were not detected out of a total of 874 injected into the combinatorial and sequential parts of the microprocessor. Since undetected faults can create catastrophic errors in equipment designed for high reliability applications, it is recommended that the MIL-M-38510/470 NASA be enhanced with additional test vectors so as to achieve 100% stuck fault detection efficiency.

  20. Game theoretic and decentralized estimation for fault detection

    NASA Astrophysics Data System (ADS)

    Chung, Walter H.

    In this dissertation, we introduce a new tool for fault detection and identification (FDI): the game theoretic fault detection filter. This filter is obtained by posing and solving a disturbance attenuation problem patterned after the fault detection process. The result is an Hsbinfty filter which bounds the transmission of all exogenous signals, save the fault to be detected. The disturbance attenuating property of the game theoretic fault detection filter approximates the disturbance blocking property of a type of detection filter known as the unknown input observer. We show that there is, in fact, a limiting case relationship between the two filters. That is, as the disturbance attenuation bound is brought to zero, the game theoretic filter asymptotically obtains the invariant subspace structure of an unknown input observer. In this structure, the reachable subspace of all the disturbance inputs is restricted to an unobservable subspace. As a result, these disturbances are unseen at the output. One can take further advantage of this structure to reduce the order of the limiting filter by simply factoring out this unobservable subspace. A game theoretic approach to fault detection filtering allows for new flexibility in detection filter design. We use this flexibility to derive a parameter robust detection filter and a decentralized detection filter. The parameter robust filter falls out when we recast the disturbance attenuation problem to account for modeling uncertainty as an additional disturbance. The solution to this new problem leads to a filter capable of detecting and identifying faults in the presence of plant parameter variations. A tradeoff, however, comes in reduced performance and in the loss of the asymptotic structure described earlier. The decentralized fault detection filter falls out when we merge the game theoretic filter with decentralized estimation theory. The resulting filter is better suited than standard detection filters for the monitoring of large-scale or spatially distributed systems. The game theoretic fault detection filter turns out to be the key to this construction, as it is shown to be the only type of detection filter that can be implemented in this way. Finally, we demonstrate that the game theoretic fault detection filter extends detection filter theory, for the first time, to time-varying systems. Existing techniques are limited to time-invariant systems because of their reliance upon geometric control theory or eigenstructure assignment for designs. Disturbance attenuation, on the other hand, is equally applicable to time-varying systems, which opens up a new class of problems for the field. Examples spread throughout the dissertation demonstrate the use of the game theoretic fault detection filter in all of its variations. These examples bring to light aspects of the filter which are not immediately evident from the theory. Conclusions given at the end of the dissertation speculate on possible extensions of the main results for future work.

  1. Integrated technology enhanced automatic test equipment with adaptive fault detection

    Microsoft Academic Search

    Larry V. Kirkland; Jesse Ayala; Steve Bolton; Lloyd G. Allred; Jeffrey S. Dean

    1993-01-01

    The authors have developed a machine-based intelligence system for automatic test equipment, which integrates various technologies in an adaptive fault-detection environment. Various technologies, other than normal ATE stimulus - reaction, including infrared, RF detection, etc. perceive non-visible information of current flow and circuit activity which can significantly enhance the technician's perception of defective components

  2. A joint wavelet lifting and independent component analysis approach to fault detection of rolling element bearings

    NASA Astrophysics Data System (ADS)

    Fan, Xianfeng; Liang, Ming; Yeap, Tet H.; Kind, Bob

    2007-10-01

    Though wavelet transforms have been used to extract bearing fault signatures from vibration signals in the literature, detection results often rely on a proper wavelet function and deep wavelet decomposition. The selection of a proper wavelet function is time consuming and deep decomposition demands more computing effort. This is unsuitable for on-line fault detection. As such, we propose a joint wavelet lifting scheme and independent component analysis (ICA) approach to detecting weak signatures of bearing faults. The optimal envelope spectrum of independent components for signature extraction is selected based on the maximum energy and total energy of each independent component. The performance of the proposed method is evaluated by comparing with several other methods using both simulated and real vibration signals. The results reveal that the proposed method is more effective and robust in extracting bearing fault signatures. The following advantages of the proposed method have also been observed: (a) it is insensitive to wavelet selection and hence is less susceptible to ill selected wavelet function; (b) it is insensitive to the depth of wavelet decomposition, leading to an efficient algorithm; and (c) it takes advantage of ICA in fault detection without using multiple sensors as required in the original ICA.

  3. Fault detection and accommodation testing on an F100 engine in an F-15 airplane

    NASA Technical Reports Server (NTRS)

    Myers, L. P.; Baer-Riedhart, J. L.; Maxwell, M. D.

    1985-01-01

    The fault detection and accommodation (FDA) methodology for digital engine-control systems may range from simple comparisons of redundant parameters to the more complex and sophisticated observer models of the entire engine system. Evaluations of the various FDA schemes are done using analytical methods, simulation, and limited-altitude-facility testing. Flight testing of the FDA logic has been minimal because of the difficulty of inducing realistic faults in flight. A flight program was conducted to evaluate the fault detection and accommodation capability of a digital electronic engine control in an F-15 aircraft. The objective of the flight program was to induce selected faults and evaluate the resulting actions of the digital engine controller. Comparisons were made between the flight results and predictions. Several anomalies were found in flight and during the ground test. Simulation results showed that the inducement of dual pressure failures was not feasible since the FDA logic was not designed to accommodate these types of failures.

  4. A Dynamic Integrated Fault Diagnosis Method for Power Transformers

    PubMed Central

    Gao, Wensheng; Liu, Tong

    2015-01-01

    In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified. PMID:25685841

  5. Detecting Small Earthquakes on Remote Oceanic Transform Faults

    NASA Astrophysics Data System (ADS)

    Vieceli, R.; Ammon, C. J.; Cleveland, M.

    2014-12-01

    Although oceanic transform faults (OTF) constitute a small fraction of the total plate boundary area, better constraints on OTF tectonic parameters (e.g. fault length, slip rate, thermal structure) compared to other tectonic boundaries make OTFs a useful focus of the investigation of earthquake processes. The large fraction of aseismic deformation that accompanies OTF earthquakes also makes them an interesting target for exploring the interaction of creep with slow and quick earthquakes. Because most typical OTFs are quite remote, even indirectly observing these deformation processes is a serious challenge. Standard teleseismic analysis methods have yielded valuable constraints on the first-order characteristics of moderate-to-large magnitude OTF earthquakes, but fundamental questions rgarding rupture length and area as well as rupture-front propagation speed remain unknown in these systems. Even identifying the smaller-magnitude activity that often provides clues to some of these quantities is difficult. Short-period seismic arrays at least occasionally provide information suitable for locations of small (mb < 4.0) earthquakes along Mid-Atlantic transforms such as the Romanche and Chain. In this work, we explore the possibility of detecting smaller earthquakes along remote OTFs using waveform-based comparisons (e.g. cross correlations) of template signals with the continuous seismic wavefield for seismic stations surrounding several OTFs. We examine our ability to detect these small events using a range of frequency bands from short-to-intermediate periods and investigating effective approaches for identifying small-magnitude events along remote OTFs. Preliminary results suggest that at least some small events can be identified using simple waveform templates. Our goal is to construct a metric that will produce acceptable false-alarm rates and that will allow us to visually confirm detections and extend the seismicity catalogs along OTFs to lower magnitude threshold and allow us to continue to investigate OTF deformation processes using remote seismic observations.

  6. Robust Fault Detection of Wind Energy Conversion Systems Based on Dynamic Neural Networks

    PubMed Central

    Talebi, Nasser; Sadrnia, Mohammad Ali; Darabi, Ahmad

    2014-01-01

    Occurrence of faults in wind energy conversion systems (WECSs) is inevitable. In order to detect the occurred faults at the appropriate time, avoid heavy economic losses, ensure safe system operation, prevent damage to adjacent relevant systems, and facilitate timely repair of failed components; a fault detection system (FDS) is required. Recurrent neural networks (RNNs) have gained a noticeable position in FDSs and they have been widely used for modeling of complex dynamical systems. One method for designing an FDS is to prepare a dynamic neural model emulating the normal system behavior. By comparing the outputs of the real system and neural model, incidence of the faults can be identified. In this paper, by utilizing a comprehensive dynamic model which contains both mechanical and electrical components of the WECS, an FDS is suggested using dynamic RNNs. The presented FDS detects faults of the generator's angular velocity sensor, pitch angle sensors, and pitch actuators. Robustness of the FDS is achieved by employing an adaptive threshold. Simulation results show that the proposed scheme is capable to detect the faults shortly and it has very low false and missed alarms rate. PMID:24744774

  7. Bearing Fault Detection via Wavelet Packet Decomposition with Spectral Post Processing

    Microsoft Academic Search

    Levent Eren; Kaptan Teotrakool; M. J. Devaney

    2007-01-01

    We present a method for detecting motor bearing fault conditions via wavelet packet decomposition (WPD) of induction motor current. This method involves the decomposition of motor current into equally spaced frequency bands by using all-pass implementation of Elliptic IIR half-band filters in the filter bank structure to obtain wavelet packet coefficients (WPC). Then, the bias in WPCs for each frequency

  8. Visualization of Induction Machine Fault Detection Using Self-Organizing Map and Support Vector Machine

    Microsoft Academic Search

    Sitao Wu; Tommy W. S. Chow; Di Huang

    2006-01-01

    Induction machines play an important role in today's industries. How to monitoring, detection, classification, and diagnosis of induction machine faults have been the essential problems. Although there have been many methods proposed to deal with these problems, there is lack of visualization tool for understanding the problems more easily. In this paper, a visualization method is proposed to help users

  9. Experimental analysis of change detection algorithms for multitooth machine tool fault detection

    NASA Astrophysics Data System (ADS)

    Reñones, Aníbal; de Miguel, Luis J.; Perán, José R.

    2009-10-01

    This paper describes an industrial application of fault diagnosis method for a multitooth machine tool. Different statistical approaches have been used to detect and diagnose insert breakage in multitooth tools based on the analysis of electrical power consumption of the tool drives. Great effort has been made to obtain a robust method, able to avoid any needed re-calibration process, after, for example, a maintenance operation. From the point of view of maintenance costs, these multitooth tools are the most critical part of the machine tools used for mass production in the car industry. These tools integrate different kinds of machining operations and cutting conditions.

  10. Incipient fault detection and identification in process systems using accelerating neural network learning

    Microsoft Academic Search

    A. G. Parlos; J. Muthusami; A. F. Atiya

    1994-01-01

    The objective of this paper is to present the development and numerical testing of a robust fault detection and identification (FDI) system using artificial neural networks (ANNs), for incipient (slowly developing) faults occurring in process systems. The challenge in using ANNs in FDI systems arises because of one's desire to detect faults of varying severity, faults from noisy sensors, and

  11. Detection, Isolation and Management of Actuator Faults in Parabolic PDEs under Uncertainty and Constraints

    E-print Network

    Sontag, Eduardo

    Detection, Isolation and Management of Actuator Faults in Parabolic PDEs under Uncertainty of integrated robust fault detection and isolation (FDI) and fault-tolerant control (FTC) architecture-varying uncertain variables, actuator constraints and faults. The design is based on an approximate, finite

  12. On the Probability of Detecting Data Errors Generated by Permanent Faults Using Time Redundancy

    E-print Network

    Karlsson, Johan

    On the Probability of Detecting Data Errors Generated by Permanent Faults Using Time Redundancy faults in computer systems. However, time redundancy is also capable of detecting permanent faults that occur during or between the executions of two task replicas, provided the faults affect the results

  13. A novel fault-detection technique of high-impedance arcing faults in transmission lines using the wavelet transform

    Microsoft Academic Search

    Chul-Hwan Kim; Hyun Kim; Young-Hun Ko; Sung-Hyun Byun; Raj K. Aggarwal; Allan T. Johns

    2002-01-01

    This paper describes a novel fault-detection technique of high-impedance faults (HIFs) in high-voltage transmission lines using the wavelet transform. The wavelet transform (WT) has been successfully applied in many fields. The technique is based on using the absolute sum value of coefficients in multiresolution signal decomposition (MSD) based on the discrete wavelet transform (DWT). A fault indicator and fault criteria

  14. Sliding mode based fault detection, reconstruction and fault tolerant control scheme for motor systems.

    PubMed

    Mekki, Hemza; Benzineb, Omar; Boukhetala, Djamel; Tadjine, Mohamed; Benbouzid, Mohamed

    2015-07-01

    The fault-tolerant control problem belongs to the domain of complex control systems in which inter-control-disciplinary information and expertise are required. This paper proposes an improved faults detection, reconstruction and fault-tolerant control (FTC) scheme for motor systems (MS) with typical faults. For this purpose, a sliding mode controller (SMC) with an integral sliding surface is adopted. This controller can make the output of system to track the desired position reference signal in finite-time and obtain a better dynamic response and anti-disturbance performance. But this controller cannot deal directly with total system failures. However an appropriate combination of the adopted SMC and sliding mode observer (SMO), later it is designed to on-line detect and reconstruct the faults and also to give a sensorless control strategy which can achieve tolerance to a wide class of total additive failures. The closed-loop stability is proved, using the Lyapunov stability theory. Simulation results in healthy and faulty conditions confirm the reliability of the suggested framework. PMID:25747198

  15. A Mode-Shape-Based Fault Detection Methodology for Cantilever Beams

    NASA Technical Reports Server (NTRS)

    Tejada, Arturo

    2009-01-01

    An important goal of NASA's Internal Vehicle Health Management program (IVHM) is to develop and verify methods and technologies for fault detection in critical airframe structures. A particularly promising new technology under development at NASA Langley Research Center is distributed Bragg fiber optic strain sensors. These sensors can be embedded in, for instance, aircraft wings to continuously monitor surface strain during flight. Strain information can then be used in conjunction with well-known vibrational techniques to detect faults due to changes in the wing's physical parameters or to the presence of incipient cracks. To verify the benefits of this technology, the Formal Methods Group at NASA LaRC has proposed the use of formal verification tools such as PVS. The verification process, however, requires knowledge of the physics and mathematics of the vibrational techniques and a clear understanding of the particular fault detection methodology. This report presents a succinct review of the physical principles behind the modeling of vibrating structures such as cantilever beams (the natural model of a wing). It also reviews two different classes of fault detection techniques and proposes a particular detection method for cracks in wings, which is amenable to formal verification. A prototype implementation of these methods using Matlab scripts is also described and is related to the fundamental theoretical concepts.

  16. Rolling bearing fault detection using an adaptive lifting multiwavelet packet with a {1\\frac{1}{2}} dimension spectrum

    NASA Astrophysics Data System (ADS)

    Jiang, Hongkai; Xia, Yong; Wang, Xiaodong

    2013-12-01

    Defect faults on the surface of rolling bearing elements are the most frequent cause of malfunctions and breakages of electrical machines. Due to increasing demands for quality and reliability, extracting fault features in vibration signals is an important topic for fault detection in rolling bearings. In this paper, a novel adaptive lifting multiwavelet packet with {1\\frac{1}{2}} dimension spectrum to detect defects in rolling bearing elements is developed. The adaptive lifting multiwavelet packet is constructed to match vibration signal properties based on the minimum singular value decomposition (SVD) entropy using a genetic algorithm. A {1\\frac{1}{2}} dimension spectrum is further employed to extract rolling bearing fault characteristic frequencies from background noise. The proposed method is applied to analyze the vibration signal collected from electric locomotive rolling bearings with outer raceway and inner raceway defects. The experimental investigation shows that the method is accurate and robust in rolling bearing fault detection.

  17. POD Model Reconstruction for Gray-Box Fault Detection

    NASA Technical Reports Server (NTRS)

    Park, Han; Zak, Michail

    2007-01-01

    Proper orthogonal decomposition (POD) is the mathematical basis of a method of constructing low-order mathematical models for the "gray-box" fault-detection algorithm that is a component of a diagnostic system known as beacon-based exception analysis for multi-missions (BEAM). POD has been successfully applied in reducing computational complexity by generating simple models that can be used for control and simulation for complex systems such as fluid flows. In the present application to BEAM, POD brings the same benefits to automated diagnosis. BEAM is a method of real-time or offline, automated diagnosis of a complex dynamic system.The gray-box approach makes it possible to utilize incomplete or approximate knowledge of the dynamics of the system that one seeks to diagnose. In the gray-box approach, a deterministic model of the system is used to filter a time series of system sensor data to remove the deterministic components of the time series from further examination. What is left after the filtering operation is a time series of residual quantities that represent the unknown (or at least unmodeled) aspects of the behavior of the system. Stochastic modeling techniques are then applied to the residual time series. The procedure for detecting abnormal behavior of the system then becomes one of looking for statistical differences between the residual time series and the predictions of the stochastic model.

  18. A method of fault analysis for test generation and fault diagnosis

    Microsoft Academic Search

    Henry Cox; Janusz Rajski

    1988-01-01

    The authors present a fault coverage analysis method for test generation and fault diagnosis of large combinational circuits. Input vectors are analyzed in pairs in two steps using a 16-valued logic system, GEMINI. Forward propagation is performed to determine, for each line in the network, the set of all possible values it can take if the network contains any single

  19. SENSOR CLASSIFICATION FOR THE FAULT DETECTION AND ISOLATION PROBLEM

    E-print Network

    Paris-Sud XI, Université de

    SENSOR CLASSIFICATION FOR THE FAULT DETECTION AND ISOLATION PROBLEM Christian Commault Jean is solvable with the existing sensors, we will classify these sensors according to their importance for the solvability of the considered FDI problem. The sensors will be classified into essential sensors, useless

  20. Backlash Fault Detection in Mechatronic R. Merzoukia,1

    E-print Network

    Boyer, Edmond

    Backlash Fault Detection in Mechatronic System R. Merzoukia,1 , K. Medjaherb , M. A. Djeziric and B, motivated by the multi-energy domain of such mechatronic system. The innovation interest of the use carrying a mechanical load, through a reducer part containing a backlash phenomenon. Key words: Mechatronic

  1. Fault Detection Effectiveness of Spathic Test Data Jane Huffman Hayes

    E-print Network

    Hayes, Jane E.

    Fault Detection Effectiveness of Spathic Test Data Jane Huffman Hayes Computer Science Department This paper presents an approach for generating test data for unit-level, and possibly integration-level, testing based on sampling over intervals of the input probability distribution, i.e., one that has been

  2. FAULT DETECTION OBSERVERS FOR SYSTEMS WITH UNKNOWN INPUTS

    E-print Network

    Paris-Sud XI, Université de

    FAULT DETECTION OBSERVERS FOR SYSTEMS WITH UNKNOWN INPUTS Besma GADDOUNA, Didier MAQUIN and José}@ensem.u-nancy.fr Abstract. Many approaches for the design of unknown input observers were developed to estimate the state of a linear time-invariant dynamical system driven by both known and unknown inputs. These observers are often

  3. Arcing faults detection on overhead lines from the voltage signals

    Microsoft Academic Search

    M. B. Djuric; V. V. Terzija

    1997-01-01

    This paper presents a simple algorithm for arcing faults detection on overhead lines. The algorithm is based on the harmonic analysis of the bus voltage signals. It uses only the sine components of the odd higher harmonics of the bus voltage. Such an approach provides the algorithm with insensitivity to the cosine components of the bus voltage odd higher harmonics

  4. Arcing fault detection in underground distribution networks-feasibility study

    Microsoft Academic Search

    Wiktor Charytoniuk; Wei-Jen Lee; Mo-Shing Chen; Joe Cultrera; Theodore Maffetone

    2000-01-01

    In some circumstances, arcing faults on insulated low-voltage conductors can sustain or reignite intermittently for several or even several dozen minutes, generating large amounts of heat and gases. In underground secondary distribution cables in ducts, the decomposition gases escape to the ends of the duct, typically manholes, where they can ignite fire or explode, throwing out the manhole cover. Detection

  5. Robust fault detection based on adaptive set observers

    Microsoft Academic Search

    Denis Efimov; Tarek Raïssi; Ali Zolghadri

    2010-01-01

    The paper deals with robust fault detection for nonlinear continuous-time systems based on a LPV transformation. The adaptive set observers technique is applied for joint state and parameter estimation in order to avoid the exponential complexity obstruction usually met in the set-membership nonlinear estimation. The obtained estimates on the sets of admissible values for the parameters and the state are

  6. Discriminative Pattern Mining in Software Fault Detection Giuseppe Di Fatta

    E-print Network

    Reiterer, Harald

    Discriminative Pattern Mining in Software Fault Detection Giuseppe Di Fatta Department of Computer and Subject Descriptors D.2.5 [Software Engineering]: Testing and Debugging-- Debugging aids, Diagnostics. This money is largely spent during the software testing and debugging phases [12]. The applicable software

  7. A geometric approach to nonlinear fault detection and isolation

    Microsoft Academic Search

    Claudio De Persis; Alberto Isidori

    2001-01-01

    We present a differential geometric approach to the problem of fault detection and isolation for nonlinear systems. A necessary condition for the problem to be solvable is derived in terms of an unobservability distribution, which is computable by means of suitable algorithms. The existence and regularity of such a distribution implies the existence of changes of coordinates in the state

  8. MODEL BASED FAULT DETECTION OF FREEWAY TRAFFIC SENSORS Gunes Dervisoglu

    E-print Network

    Horowitz, Roberto

    . The second step fits the empiri- cal fundamental diagram to traffic data provided by loop detec- tors steps: 1) Network Spec- ification, 2) Fundamental Diagram Calibration, 3) Ramp Flow Imputation (if rampMODEL BASED FAULT DETECTION OF FREEWAY TRAFFIC SENSORS Gunes Dervisoglu Department of Mechanical

  9. Artificial neural networks and genetic algorithm for bearing fault detection

    Microsoft Academic Search

    B. Samanta; K. R. Al-balushi; S. A. Al-araimi

    2006-01-01

    A study is presented to compare the performance of three types of artificial neural network (ANN), namely, multi layer perceptron (MLP), radial basis function (RBF) network and probabilistic neural network (PNN), for bearing fault detection. Features are extracted from time domain vibration signals, without and with preprocessing, of a rotating machine with normal and defective bearings. The extracted features are

  10. Development of an Automated Fault Detection and Diagnosis tool for AHU's 

    E-print Network

    Bruton, K.; Raftery, P.; Aughney, N.; Keane, M.; O'Sullivan, D.

    2012-01-01

    -commissioning HVAC systems to rectify faulty operation with savings of over 20 percent of total energy cost possible by continuously commissioning. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with automating the detection of faults...

  11. Functional Fault Modeling of a Cryogenic System for Real-Time Fault Detection and Isolation

    NASA Technical Reports Server (NTRS)

    Ferrell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Brown, Barbara

    2010-01-01

    The purpose of this paper is to present the model development process used to create a Functional Fault Model (FFM) of a liquid hydrogen (L H2) system that will be used for realtime fault isolation in a Fault Detection, Isolation and Recover (FDIR) system. The paper explains th e steps in the model development process and the data products required at each step, including examples of how the steps were performed fo r the LH2 system. It also shows the relationship between the FDIR req uirements and steps in the model development process. The paper concl udes with a description of a demonstration of the LH2 model developed using the process and future steps for integrating the model in a live operational environment.

  12. FAULT DETECTION USING SUPPORT VECTOR MACHINES AND ARTIFICIAL NEURAL NETWORKS, AUGMENTED BY GENETIC ALGORITHMS

    Microsoft Academic Search

    L. B. JACK; A. K. NANDI

    2002-01-01

    Artificial neural networks (ANNs) have been used to detect faults in rotating machinery for a number of years, using statistical methods to preprocess the vibration signals as input features. ANNs have been shown to be highly successful in this type of application; in comparison, support vector machines (SVMs) are a more recent development, and little use has been made of

  13. Concurrent Fault Detection in Random Combinational Logic Petros Drineas and Yiorgos Makris

    E-print Network

    Drineas, Petros

    added in parallel to the original circuit, which is assumed to be optimized and may not be modified to duplication, wherein a replica of the circuit acts as a predictor that immediately detects poten- tial faults by comparison to the original circuit. However, instead of duplicating the circuit, the proposed method se

  14. Application of model-based fault detection to a brushless DC motor

    Microsoft Academic Search

    Olaf Moseler; Rolf Isermann

    2000-01-01

    In comparison to classical DC motors, brushless DC motors are very reliable, Nevertheless, they can also fail, caused by, e.g., overheating or mechanical wear. This paper proposes a parameter estimation technique for fault detection on this type of motor. Simply by measuring the motor's input and output signals, its parameters can be estimated. This method is based on a mathematical

  15. Feature extraction using adaptive multiwavelets and synthetic detection index for rotor fault diagnosis of rotating machinery

    NASA Astrophysics Data System (ADS)

    Lu, Na; Xiao, Zhihuai; Malik, O. P.

    2015-02-01

    State identification to diagnose the condition of rotating machinery is often converted to a classification problem of values of non-dimensional symptom parameters (NSPs). To improve the sensitivity of the NSPs to the changes in machine condition, a novel feature extraction method based on adaptive multiwavelets and the synthetic detection index (SDI) is proposed in this paper. Based on the SDI maximization principle, optimal multiwavelets are searched by genetic algorithms (GAs) from an adaptive multiwavelets library and used for extracting fault features from vibration signals. By the optimal multiwavelets, more sensitive NSPs can be extracted. To examine the effectiveness of the optimal multiwavelets, conventional methods are used for comparison study. The obtained NSPs are fed into K-means classifier to diagnose rotor faults. The results show that the proposed method can effectively improve the sensitivity of the NSPs and achieve a higher discrimination rate for rotor fault diagnosis than the conventional methods.

  16. Probability based vehicle fault diagnosis: Bayesian network method

    Microsoft Academic Search

    Yingping Huang; Ross McMurran; Gunwant Dhadyalla; R. Peter Jones

    2008-01-01

    Fault diagnostics are increasingly important for ensuring vehicle safety and reliability. One of the issues in vehicle fault\\u000a diagnosis is the difficulty of successful interpretation of failure symptoms to correctly diagnose the real root cause. This\\u000a paper presents an innovative Bayesian Network based method for guiding off-line vehicle fault diagnosis. By using a vehicle\\u000a infotainment system as a case study,

  17. Decomposition Methods for Fault Tree Analysis

    Microsoft Academic Search

    Arnon Rosenthal

    1980-01-01

    Some kinds of fault tree analysis are described for which cut set enumeration is inadequate. Modularization leads to more efficient computer programs, and also identifies subsystems which are intuitively meaningful. The problem of finding all modules of a fault tree is formulated as as extension of the problem of finding all ``cut-points'' of an undirected graph. The major result is

  18. Autonomous Fault Detection in Self-Healing Systems using Restricted Boltzmann Machines

    E-print Network

    Dobson, Simon

    detect and resolve faults without human supervision [5], [7], [8]. This is important when consideringAutonomous Fault Detection in Self-Healing Systems using Restricted Boltzmann Machines Chris.dobson@st-andrews.ac.uk Abstract--Autonomously detecting and recovering from faults is one approach for reducing the operational

  19. Fault Detection Filter Design For Networked Control System With Communication Delays

    Microsoft Academic Search

    Yuqiang Chen; Bo Xiao; Zhiyan Xu

    2006-01-01

    In this paper, we studied fault detection filter design problem for a class of linear networked control systems with communication delays. The communication delays can be modeled as a random Markov jump process with a finite number of states. We demonstrated that a fault detection observer can be developed to detect the fault occurrence for the system, and a LMI-based

  20. Monitoring Cycles for Fault Detection in Meshed All-Optical Networks

    Microsoft Academic Search

    Hongqing Zeng; Changcheng Huang; Alex Vukovic

    2004-01-01

    Fault detection is critical for all-optical networks (AONs). This paper introduces the concept of monitoring cycle and proposes a fault detection mechanism based on decomposing AONs into a set of cycles (a cycle cover), in which each one is defined as a monitoring cycle. Two cycle-finding algorithms are developed and compared for the proposed fault detection mechanism: heuristic depth first

  1. Robust Model-Based Fault Detection Using Adaptive Robust Observers Phanindra Garimella and Bin Yao

    E-print Network

    Yao, Bin

    Robust Model-Based Fault Detection Using Adaptive Robust Observers Phanindra Garimella and Bin Yao with experimental data to detect faults in a system at an early enough stage as to conduct preventive maintenance in the design of model-based fault detection schemes is the effect of the model uncertainties such as severe

  2. Development of Fault Detection System using Wavelength Division Multiplexing Transmission of Optical Fiber Current Sensor

    Microsoft Academic Search

    Masahiro Kayaki; Toshinari Hirata; Kiyoshi Kurosawa; Reishi Kondo; Toshiharu Yamada; Eiji Itakura

    2010-01-01

    A fault detection system is applied to power lines consisting of both overhead power line and underground power cable in order to detect a fault on the underground power cable section and prevent the automatic reclosing. The fault detection system using optical fiber current sensor has two subjects. The fist subject is that we have to use wound-type current transformer

  3. Main propulsion functional path analysis for performance monitoring fault detection and annunciation

    NASA Technical Reports Server (NTRS)

    Keesler, E. L.

    1974-01-01

    A total of 48 operational flight instrumentation measurements were identified for use in performance monitoring and fault detection. The Operational Flight Instrumentation List contains all measurements identified for fault detection and annunciation. Some 16 controller data words were identified for use in fault detection and annunciation.

  4. Incipient fault detection study for advanced spacecraft systems

    NASA Technical Reports Server (NTRS)

    Milner, G. Martin; Black, Michael C.; Hovenga, J. Mike; Mcclure, Paul F.

    1986-01-01

    A feasibility study to investigate the application of vibration monitoring to the rotating machinery of planned NASA advanced spacecraft components is described. Factors investigated include: (1) special problems associated with small, high RPM machines; (2) application across multiple component types; (3) microgravity; (4) multiple fault types; (5) eight different analysis techniques including signature analysis, high frequency demodulation, cepstrum, clustering, amplitude analysis, and pattern recognition are compared; and (6) small sample statistical analysis is used to compare performance by computation of probability of detection and false alarm for an ensemble of repeated baseline and faulted tests. Both detection and classification performance are quantified. Vibration monitoring is shown to be an effective means of detecting the most important problem types for small, high RPM fans and pumps typical of those planned for the advanced spacecraft. A preliminary monitoring system design and implementation plan is presented.

  5. Statistical Fault Analysis

    Microsoft Academic Search

    Sunil K. JainandVishwani; Vishwani Agrawal

    1985-01-01

    Statistical Fault Analysis, or Stafan, is proposed as an alternative to fault simulation of digital circuits. This method defines Controllabilities and observabilities of circuit nodes as probabilities estimated from signal statistics of fault-free simulation. Special Procedures deal with these quantities at fanout and feedback nodes. The computed probabilities are used to derive unbiased estimates of fault detection probabilities and overall

  6. Crustal deformation detected by GPS observation network across the Sumatran fault system in northwestern Sumatra, Indonesia

    NASA Astrophysics Data System (ADS)

    Tabei, T.; Ito, T.; Kimata, F.; Ohta, Y.; Gunawan, E.; Ismail, N.; Sugiyanto, D.; Nurdin, I.

    2013-12-01

    We have deployed Aceh GPS network for the Sumatran fault system (AGNeSS) in the northwestern part of Sumatra Island, Indonesia to evaluate regional earthquake generation potential in parallel to the decaying process of postseismic deformation after the 2004 Sumatra-Andaman earthquake (Mw 9.2). The AGNeSS consists of seven continuous and 17 campaign sites deployed mostly along two main roads spanning approximately 200 km x 200 km area across the fault. Using horizontal displacement data up to 2010, we detected postseismic deformation exceeding 80 cm in about five years after the 2004 event and also inferred shallow creep/locking distribution along the Sumatran fault (Ito et al., 2012). On January 22 and July 2, 2013 two M6.1 earthquakes occurred in the AGNeSS. Hypocenter location and mechanism of the first earthquake strongly suggest a right-lateral strike-slip event on the NW-SE trending Sumatran fault. The second earthquake occurred when GPS campaign observation was being conducted in the vicinity of the source region. While the epicenter is about 25 km departed from the main trace of the Sumatran fault, source mechanism is very similar to that of the first one. However, coseismic displacement field from the nearby GPS sites clearly show a left-lateral strike-slip motion on a NE-SW trending fault plane. So far no evidence has been obtained that supports the existence of conjugate faults that are perpendicular to the Sumatran fault system. We are planning to conduct supplementary geomorphologic survey and microearthquake observation. Preliminary results of fault parameter estimation using a Markov Chain Monte Carlo method are very consistent with the observations.

  7. Sensor configuration and test for fault diagnoses of subway braking system based on signed digraph method

    NASA Astrophysics Data System (ADS)

    Zuo, Jianyong; Chen, Zhongkai

    2014-05-01

    Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers. However, obtaining an optimized sensor set of these systems, which is a prerequisite for fault diagnosis, remains a major challenge. Available literature suggests that the configuration of sensors in these systems is presently dependent on the knowledge and engineering experiences of designers, which may lead to insufficient or redundant development of various sensors. In this paper, the optimization of sensor sets is addressed by using the signed digraph (SDG) method. The method is modified for use in braking systems by the introduction of an effect-function method to replace the traditional quantitative methods. Two criteria are adopted to evaluate the capability of the sensor sets, namely, observability and resolution. The sensors configuration method of braking system is proposed. It consists of generating bipartite graphs from SDG models and then solving the set cover problem using a greedy algorithm. To demonstrate the improvement, the sensor configuration of the HP2008 braking system is investigated and fault diagnosis on a test bench is performed. The test results show that SDG algorithm can improve single-fault resolution from 6 faults to 10 faults, and with additional four brake cylinder pressure (BCP) sensors it can cover up to 67 double faults which were not considered by traditional fault diagnosis system. SDG methods are suitable for reducing redundant sensors and that the sensor sets thereby obtained are capable of detecting typical faults, such as the failure of a release valve. This study investigates the formal extension of the SDG method to the sensor configuration of braking system, as well as the adaptation supported by the effect-function method.

  8. Cyclostationarity analysis and diagnosis method of bearing faults

    Microsoft Academic Search

    Bin Wu; Minjie Wang; Yuegang Luo; Changjian Feng

    2009-01-01

    The vibration signal of rotating machine is typical amplitude-modulated signal. In that case, the method of cyclostationary analysis is very effective for extracting and demodulating the modulating signal that usually contains some fault message. However, duo to a good many factors, such as the special construction, the amalgamation of multiple faults and the fluctuation of rotating speed etc., the cyclostationary

  9. Real-time fault detection in manufacturing environments using face recognition techniques

    Microsoft Academic Search

    Fadel M. Megahed; Jaime A. Camelio

    New image processing techniques as well digital image capture equipment provide an opportunity for fast detection and diagnosis\\u000a of quality problems in manufacturing environments compared with traditional dimensional measurement techniques. This paper\\u000a proposes a new use of image processing to detect in real-time quality faults using images traditionally obtained to guide\\u000a manufacturing processes. The proposed method utilizes face recognition tools

  10. ROTOR FAULTS DETECTION IN SQUIRREL-CAGE INDUCTION MOTORS BY CURRENT SIGNATURE ANALYSIS

    Microsoft Academic Search

    SZABÓ Loránd

    The condition monitoring of the electrical machines can significantly reduce the costs of maintenance by allowing the early detection of faults, which could be expensive to repair. In this paper some results on non-invasive detection of broken rotor bars in squirrel-cage induction motors are presented. The applied method is the so-called motor current signature analysis (MCSA) which utilises the results

  11. Battery Fault Detection with Saturating Transformers

    NASA Technical Reports Server (NTRS)

    Davies, Francis J. (Inventor); Graika, Jason R. (Inventor)

    2013-01-01

    A battery monitoring system utilizes a plurality of transformers interconnected with a battery having a plurality of battery cells. Windings of the transformers are driven with an excitation waveform whereupon signals are responsively detected, which indicate a health of the battery. In one embodiment, excitation windings and sense windings are separately provided for the plurality of transformers such that the excitation waveform is applied to the excitation windings and the signals are detected on the sense windings. In one embodiment, the number of sense windings and/or excitation windings is varied to permit location of underperforming battery cells utilizing a peak voltage detector.

  12. Attributes of the interface affect fault detection and fault diagnosis in supervisory control

    Microsoft Academic Search

    Torsten Heinbokel; Rainer H. Kluwe

    In this paper, a cognitive psychological framework of human-machine interaction, the methodological approach and the results\\u000a of two empirical studies, are reported. The research was directed at the goal of identifying interface attributes which are\\u000a assumed to be crucial for fault detection and diagnosis during supervisory control. In the first study, it was assumed that\\u000a due to attributes of standard

  13. A simplified fault currents analysis method considering transient of synchronous machine

    Microsoft Academic Search

    T. Kai; N. Takeuchi; T. Funabashi; H. Sasaki

    1997-01-01

    The transient fault currents of a synchronous machine fault were mathematically analyzed by using the two-reaction theory, Clarke's components, etc. However, the methods were extremely complicated and the transient fault analysis of synchronous machine with a load was not carried out except for three-phase faults. This paper proposes a simplified fault currents analysis method considering synchronous machine transients. The method

  14. Application of fault detection techniques to spiral bevel gear fatigue data

    NASA Technical Reports Server (NTRS)

    Zakrajsek, James J.; Handschuh, Robert F.; Decker, Harry J.

    1994-01-01

    Results of applying a variety of gear fault detection techniques to experimental data is presented. A spiral bevel gear fatigue rig was used to initiate a naturally occurring fault and propagate the fault to a near catastrophic condition of the test gear pair. The spiral bevel gear fatigue test lasted a total of eighteen hours. At approximately five and a half hours into the test, the rig was stopped to inspect the gears for damage, at which time a small pit was identified on a tooth of the pinion. The test was then stopped an additional seven times throughout the rest of the test in order to observe and document the growth and propagation of the fault. The test was ended when a major portion of a pinion tooth broke off. A personal computer based diagnostic system was developed to obtain vibration data from the test rig, and to perform the on-line gear condition monitoring. A number of gear fault detection techniques, which use the signal average in both the time and frequency domain, were applied to the experimental data. Among the techniques investigated, two of the recently developed methods appeared to be the first to react to the start of tooth damage. These methods continued to react to the damage as the pitted area grew in size to cover approximately 75% of the face width of the pinion tooth. In addition, information gathered from one of the newer methods was found to be a good accumulative damage indicator. An unexpected result of the test showed that although the speed of the rig was held to within a band of six percent of the nominal speed, and the load within eighteen percent of nominal, the resulting speed and load variations substantially affected the performance of all of the gear fault detection techniques investigated.

  15. Fault Detection and Isolation for Hydraulic Control

    NASA Technical Reports Server (NTRS)

    1987-01-01

    Pressure sensors and isolation valves act to shut down defective servochannel. Redundant hydraulic system indirectly senses failure in any of its electrical control channels and mechanically isolates hydraulic channel controlled by faulty electrical channel so flat it cannot participate in operating system. With failure-detection and isolation technique, system can sustains two failed channels and still functions at full performance levels. Scheme useful on aircraft or other systems with hydraulic servovalves where failure cannot be tolerated.

  16. Detection of sensor faults with observer structures in control loops

    Microsoft Academic Search

    C.-S. Berendsen; G. Rostaing; G. Champenois; G. Obrecht; J. Saadi

    1993-01-01

    Electrical machines of high power scale have a redundant control electronic which might be confused by external disturbances. In this paper we propose a method to distinguish sensor failures (speed and current loops) from power supply fluctuations and load torque impacts or to be at least robust to it. The proposed technique is based on analytical redundancy: faults are represented

  17. Condition detection and fault diagnosis system for recoil system based on simulation

    Microsoft Academic Search

    Lijun Cao; Huibin Hu; Junqi Qin

    2009-01-01

    Dynamic analysis is carried out for recoil parts in recoil and counter-recoil process to find out the fault effects of liquid and gas leakage of recoil brake and recuperator. In order to detect and simulate the fault occurrence and development process, virtual prototyping is firstly adopted into fault simulation and detection fields in this paper. The basic steps of virtual

  18. Adaptive Particle Filter for Unknown Fault Detection of Wheeled Mobile Robots

    Microsoft Academic Search

    Zhuohua Duan; Zixing Cai; Jinxia Yu

    2006-01-01

    Fault detection and diagnosis (FDD) is very important for wheeled mobile robots (WMRs). In this paper, an adaptive particle filter is developed to deal with unknown fault detection as well as known fault diagnosis for wheeled mobile robots. Two parameters are extracted from sample-based expression for a posteriori probability density: sum of unnormalized weight of samples, and Kullback-Leiber divergence of

  19. March Tests Improvement for Address Decoder Open and Resistive Open Fault Detection

    E-print Network

    Paris-Sud XI, Université de

    of these defects two bit lines or word lines may be erroneously selected at the same time. This fault, also called1 March Tests Improvement for Address Decoder Open and Resistive Open Fault Detection * Luigi presents a complete analysis of the ability of March tests to detect ADOFs (Address Decoder Open Faults

  20. Distributed Real-time Fault Detection and Isolation For Cooperative Multi-agent Systems

    E-print Network

    Johansson, Karl Henrik

    Distributed Real-time Fault Detection and Isolation For Cooperative Multi-agent Systems Meng Guo-time fault detection, isolation and mitigation framework for multi- agent systems performing cooperative. Then a scheme based on limited relative state measurements is developed. Furthermore, we propose fault isolation

  1. A novel measurement technique for extra high voltage bus bar fault detection

    Microsoft Academic Search

    S. H. Haggag; Ali M. El-Rifaie; R. M. Sharkawy

    2012-01-01

    This paper introduces a new fault detection tool for Extra High Voltage (EHV) busbars. The new tool is to be used by extra high speed digital relays to detect busbar faults besides differentiating between close up line faults and busbar ones. The suggested tool uses a new technique that squares both of the instantaneous voltage signal and its complement to

  2. Fundamental Fault Detection Limitations in Linear Non-Gaussian Systems Gustaf Hendeby

    E-print Network

    Gustafsson, Fredrik

    Fundamental Fault Detection Limitations in Linear Non-Gaussian Systems Gustaf Hendeby Division Linköpings universitet, SE-581 83 Linköping, SWEDEN fredrik@isy.liu.se Abstract-- Sophisticated fault detection (FD) algorithms often include nonlinear mappings of observed data to fault decisions

  3. STATE OF CALIFORNIA FAULT DETECTION AND DIAGNOSTICS (FDD) FOR PACKAGED DIRECT EXPANSION UNITS

    E-print Network

    STATE OF CALIFORNIA FAULT DETECTION AND DIAGNOSTICS (FDD) FOR PACKAGED DIRECT EXPANSION UNITS CEC-MECH-12A (Revised 08/09) CALIFORNIA ENERGY COMMISSION CERTIFICATE OF ACCEPTANCE MECH-12A NA7.5.11 Fault Signed: Position With Company (Title): #12;STATE OF CALIFORNIA FAULT DETECTION AND DIAGNOSTICS (FDD

  4. FAULT DETECTION IN HVAC SYSTEMS USING MODEL-BASED FEEDFORWARD CONTROL

    E-print Network

    Diamond, Richard

    1 FAULT DETECTION IN HVAC SYSTEMS USING MODEL- BASED FEEDFORWARD CONTROL T. I. Salsbury, Ph.D. R. C and detect faults in the controlled process. The scheme uses static simulation models of the system under control action, the models act as a reference of correct operation. Faults that occur in the system under

  5. Detection and Diagnosis of Incipient Faults in Heavy-Duty Diesel Engines

    Microsoft Academic Search

    Ian Morgan; Honghai Liu; Bernardo Tormos; Antonio Sala

    2010-01-01

    This paper proposes a new methodology for detecting and diagnosing faults found in heavy-duty diesel engines based upon spectrometric analysis of lubrication samples and is compared against a conventional method, the redline limits, which is utilized in a number of major laboratories in the U.K. and across Europe. The proposed method applies computational power to a well-known maintenance technique and

  6. Simulation of secondary fault shear displacements - method and application

    NASA Astrophysics Data System (ADS)

    Fälth, Billy; Hökmark, Harald; Lund, Björn; Mai, P. Martin; Munier, Raymond

    2014-05-01

    We present an earthquake simulation method to calculate dynamically and statically induced shear displacements on faults near a large earthquake. Our results are aimed at improved safety assessment of underground waste storage facilities, e.g. a nuclear waste repository. For our simulations, we use the distinct element code 3DEC. We benchmark 3DEC by running an earthquake simulation and then compare the displacement waveforms at a number of surface receivers with the corresponding results obtained from the COMPSYN code package. The benchmark test shows a good agreement in terms of both phase and amplitude. In our application to a potential earthquake near a storage facility, we use a model with a pre-defined earthquake fault plane (primary fault) surrounded by numerous smaller discontinuities (target fractures) representing faults in which shear movements may be induced by the earthquake. The primary fault and the target fractures are embedded in an elastic medium. Initial stresses are applied and the fault rupture mechanism is simulated through a programmed reduction of the primary fault shear strength, which is initiated at a pre-defined hypocenter. The rupture is propagated at a typical rupture propagation speed and arrested when it reaches the fault plane boundaries. The primary fault residual strength properties are uniform over the fault plane. The method allows for calculation of target fracture shear movements induced by static stress redistribution as well as by dynamic effects. We apply the earthquake simulation method in a model of the Forsmark nuclear waste repository site in Sweden with rock mass properties, in situ stresses and fault geometries according to the description of the site established by the Swedish Nuclear Fuel and Waste Management Co (SKB). The target fracture orientations are based on the Discrete Fracture Network model developed for the site. With parameter values set to provide reasonable upper bound estimates of target fracture displacements, the model generates primary fault slip and slip velocities that are both high compared to those found in real earthquakes. The calculated target fracture movements reach some tens of millimetres on 300 m diameter fractures. We also present results indicating the sensitivity of primary fault slip and target fracture movements to e.g. variation of primary fault residual strength, change of hypocenter location and variations in the initial stress field.

  7. Sensor Fault Detection and Isolation System 

    E-print Network

    Yang, Cheng-Ken

    2014-08-01

    , the system parameters of the applied system are assumed to be unknown. In the first step of the proposed method, phase space reconstruction techniques are used to reconstruct the phase space of the applied system. This step is aimed to infer the system...

  8. Classification techniques for fault detection and diagnosis of an air-handling unit

    SciTech Connect

    House, J.M.; Lee, W.Y.; Shin, D.R.

    1999-07-01

    The objective of this study is to demonstrate the application of several classification techniques to the problem of detecting and diagnosing faults in data generated by a variable-air-volume air-handling unit simulation model and to describe the strengths and weaknesses of the techniques considered. Artificial neural network classifiers, nearest neighbor classifiers, nearest prototype classifiers, a rule-based classifier, and a Bayes classifier are considered for both fault detection and diagnostics. Based on the performance of the classification techniques, the Bayes classifier appears to be a good choice for fault detection. It is a straightforward method that requires limited memory and computational effort, and it consistently yielded the lowest percentage of incorrect diagnosis. For fault diagnosis, the rule-based method is favored for classification problems such as the one considered here, where the various classes of faulty operation are well separated and can be distinguished by a single dominant symptom or feature. Results also indicate that the success or failure of classification techniques hinges to a large degree on an ability to separate different classes of operation in some feature (temperature, pressure, etc.) space. Hence, preprocessing of data to extract dominant features is as important as the selection of the classifier.

  9. Documentation of the current fault detection, isolation and reconfiguration software of the AIPS fault-tolerant processor

    NASA Technical Reports Server (NTRS)

    Lanning, David T.; Shepard, Allen W.; Johnson, Sally C.

    1987-01-01

    Documentation is presented of the December 1986 version of the ADA code for the fault detection, isolation, and reconfiguration (FDIR) functions of the Advanced Information processing System (AIPS) Fault-Tolerant Processor (FTP). Because the FTP is still under development and the software is constantly undergoing changes, this should not be considered final documentation of the FDIR software of the FTP.

  10. A new three-dimensional method of fault reactivation analysis

    NASA Astrophysics Data System (ADS)

    Leclère, Henri; Fabbri, Olivier

    2013-03-01

    A 3-D method to evaluate the reactivation potential of fault planes is proposed. The method can be applied to cohesive or noncohesive faults whatever their orientation and without any conditions on the regional stress field. It allows computation of the effective stress ratio ?3'/?1' required to reactivate any fault plane and to determine whether the plane is favorably oriented, unfavorably oriented or severely misoriented with respect to the ambient stress field. The method also includes a graphical sorting tool that involves plotting poles of fault planes on stereoplots for which the boundaries separating the three domains corresponding to favorable orientations, unfavorable orientations and severe misorientations cases are shown. The delineation of these domains is based on the value of the ?3'/?1' ratio that depends on the orientation of the fault plane with respect to the principal stress axis orientations, the stress shape ratio (? = (?2 - ?3)/(?1 - ?3)), the coefficient of static friction ?s of the fault, and the fault cohesion C0. The method is applied on 145 focal mechanisms of the 2011 March 11th Tohoku-Oki (Japan) earthquake sequence. This application delineates, along or in the vicinity of the Pacific-Okhotsk plate interface, three types of domains characterized by favorable orientations, unfavorable orientations or severe misorientations of mainshock/aftershock fault planes. Aftershock focal mechanisms that plot in the 'severe misorientation' domains are interpreted to have occurred because of pore fluid pressures exceeding the regional minimum principal stress at those locations. The distribution of these 'severe misorientation' domains partly overlaps the asperities or the low-velocity anomalies mapped on the plate interface off NE Japan. The proposed 3-D fault reactivation analysis appears complementary to geophysical investigations.

  11. A Model-Based Probabilistic Inversion Framework for Wire Fault Detection Using TDR

    NASA Technical Reports Server (NTRS)

    Schuet, Stefan R.; Timucin, Dogan A.; Wheeler, Kevin R.

    2010-01-01

    Time-domain reflectometry (TDR) is one of the standard methods for diagnosing faults in electrical wiring and interconnect systems, with a long-standing history focused mainly on hardware development of both high-fidelity systems for laboratory use and portable hand-held devices for field deployment. While these devices can easily assess distance to hard faults such as sustained opens or shorts, their ability to assess subtle but important degradation such as chafing remains an open question. This paper presents a unified framework for TDR-based chafing fault detection in lossy coaxial cables by combining an S-parameter based forward modeling approach with a probabilistic (Bayesian) inference algorithm. Results are presented for the estimation of nominal and faulty cable parameters from laboratory data.

  12. Fault diagnosis using hybrid artificial intelligent methods

    Microsoft Academic Search

    Yann-Chang Huang; Chao-Ming Huang; Huo-Ching Sun; Yi-Shi Liao

    2010-01-01

    This paper presents genetic-based neural networks (GNNs) for fault diagnosis of power transformers. The GNNs automatically tune the network parameters, connection weights and bias terms of the neural networks, to yield the best model according to the proposed genetic algorithm. Due to the global search capabilities of the genetic algorithm and the highly nonlinear mapping nature of the neural networks,

  13. A neural network approach to fault detection in spacecraft attitude determination and control systems

    NASA Astrophysics Data System (ADS)

    Schreiner, John N.

    This thesis proposes a method of performing fault detection and isolation in spacecraft attitude determination and control systems. The proposed method works by deploying a trained neural network to analyze a set of residuals that are defined such that they encompass the attitude control, guidance, and attitude determination subsystems. Eight neural networks were trained using either the resilient backpropagation, Levenberg-Marquardt, or Levenberg-Marquardt with Bayesian regularization training algorithms. The results of each of the neural networks were analyzed to determine the accuracy of the networks with respect to isolating the faulty component or faulty subsystem within the ADCS. The performance of the proposed neural network-based fault detection and isolation method was compared and contrasted with other ADCS FDI methods. The results obtained via simulation showed that the best neural networks employing this method successfully detected the presence of a fault 79% of the time. The faulty subsystem was successfully isolated 75% of the time and the faulty components within the faulty subsystem were isolated 37% of the time.

  14. Exact Computation of Maximally Dominating Faults and Its Application to -Detection Tests

    E-print Network

    Polian, Ilia

    Exact Computation of Maximally Dominating Faults and Its Application to -Detection Tests Ilia, IN 47907, USA Abstract £ -detection test sets for stuck-at faults have been shown to be useful in detecting an important role in controlling the increase in the size of an £ -detection test set as £ is increased

  15. Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

    PubMed

    Tafinine, Farid; Mokrani, Karim

    2012-11-01

    A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor. PMID:23145702

  16. Coupled magnetic circuit method and permeance network method modeling of stator faults in induction machines

    Microsoft Academic Search

    Amin Mahyob; Mohamed Y. Ould Elmoctar; Pascal Reghem; Georges Barakat

    2008-01-01

    The aim of this paper is to present and compare two modeling methods of the inter-turn short circuit fault in the stator winding of a cage induction machine. The first method is a Coupled Magnetic Circuit Method (CMCM) and the second method is a Permeance Network Method (PNM) which allows taking into account the saturation effect on the fault signature.

  17. Fault detection and isolation in aircraft gas turbine engines. Part 2: validation on a simulation test bed

    Microsoft Academic Search

    S Sarkar; S Gupta; K Mukherjee; A Ray

    2008-01-01

    The first part of this two-part paper, which is a companion paper, has developed a novel concept of fault detection and isolation (FDI) in aircraft gas turbine engines. The FDI algorithms are built upon the statistical pattern recognition method of symbolic dynamic filtering (SDF) that is especially suited for real-time detection and isolation of slowly evolving anomalies in engine components,

  18. A Method for Constructing Fault Trees from AADL Models

    Microsoft Academic Search

    Yue Li; Yi-an Zhu; Chun-yan Ma; Meng Xu

    \\u000a System safety analysis based on fault tree has been widely used for providing assurance to the stringent safety requirement\\u000a of safety-critical systems. Generating fault trees from models described in AADL, a promising standard language for modeling\\u000a complicated embedded system, would realize the automation of system safety analysis which is traditionally performed manually.\\u000a This paper proposes a whole method for constructing

  19. Intermittent-Chaos-and-Cepstrum-Analysis-Based Early Fault Detection on Shuttle Valve of Hydraulic Tube Tester

    Microsoft Academic Search

    Zhen Zhao; Fu-Li Wang; Ming-Xing Jia; Shu Wang

    2009-01-01

    To ensure the safety and continuity of production, make a reasonable maintenance plan, and save the cost of maintenance for a hydraulic tube tester, it is needed to quickly identify an assignable cause of a fault. This paper is concerned with early fault detection of shuttle valves, which are the key components in hydraulic tube tester. An intermittent-chaos-and-cepstrum-analysis-based method is

  20. Multigrid contact detection method

    NASA Astrophysics Data System (ADS)

    He, Kejing; Dong, Shoubin; Zhou, Zhaoyao

    2007-03-01

    Contact detection is a general problem of many physical simulations. This work presents a O(N) multigrid method for general contact detection problems (MGCD). The multigrid idea is integrated with contact detection problems. Both the time complexity and memory consumption of the MGCD are O(N) . Unlike other methods, whose efficiencies are influenced strongly by the object size distribution, the performance of MGCD is insensitive to the object size distribution. We compare the MGCD with the no binary search (NBS) method and the multilevel boxing method in three dimensions for both time complexity and memory consumption. For objects with similar size, the MGCD is as good as the NBS method, both of which outperform the multilevel boxing method regarding memory consumption. For objects with diverse size, the MGCD outperform both the NBS method and the multilevel boxing method. We use the MGCD to solve the contact detection problem for a granular simulation system based on the discrete element method. From this granular simulation, we get the density property of monosize packing and binary packing with size ratio equal to 10. The packing density for monosize particles is 0.636. For binary packing with size ratio equal to 10, when the number of small particles is 300 times as the number of big particles, the maximal packing density 0.824 is achieved.

  1. Migrating Fault Trees To Decision Trees For Real Time Fault Detection On International Space Station

    Microsoft Academic Search

    Charles Lee; Richard L. Alena; Peter Robinson

    2005-01-01

    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. 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

  2. H fault detection filter design for linear discrete-time systems with multiple time delays

    Microsoft Academic Search

    B. Jiang; M. Staroswiecki; V. Cocquempot

    2003-01-01

    This paper deals with the design of H fault detection filters for discrete-time systems with multiple time delays, in which total decoupling of the fault effects from unknown inputs, including model uncertainties and external plant disturbances, is impossible. Through the appropriate choice of the filter gain, the filter is convergent if there is no fault in the system, and the

  3. Real-time fault detection and isolation in biological wastewater treatment plants

    E-print Network

    Real-time fault detection and isolation in biological wastewater treatment plants F. Baggiani and S of an unchecked fault propagating through the plant. This paper describes the development of a real-time Fault and then ported into the LabView 8.20 (National Instruments, Austin, TX, USA) platform for real-time operation

  4. Fault detection and isolation of a two non-interacting tanks system using partial PCA

    Microsoft Academic Search

    N. Bhattacharjee; B. K. Roy

    2010-01-01

    In this paper, the concept of principal component analysis (PCA) has been used to generate a residual space to detect an actuator and a sensor fault in a two non-interacting tank system. Since there is only one residual vector in the present case, isolation of faults using PCA is not feasible. For isolation of the fault, partial PCA based structured

  5. Electromagnetic detection of plate hydration due to bending faults at the Middle America Trench

    E-print Network

    Constable, Steve

    Electromagnetic detection of plate hydration due to bending faults at the Middle America Trench bending faults on the incoming oceanic plate of the Middle America Trench offshore Nicaragua have been of the Middle America Trench containing fewer bending faults have less fluid flux from the subducting slab

  6. Arcing fault detection for distribution feeders: Security assessment in long term field trials

    Microsoft Academic Search

    B. D. Russell; C. L. Benner

    1995-01-01

    A downed conductor, arcing fault detection system has been designed using multiple protection algorithms. An intelligent analysis system processes the outputs from several algorithms to determine the ``confidence`` that a fault exists. The design includes careful attention to discriminating arcing faults from normal system activity to ensure system security. Key to the acceptance of this system is testing under actual

  7. Fault detection and diagnosis for three-tank system using robust residual generator

    Microsoft Academic Search

    A. Asokan; D. Sivakumar

    2009-01-01

    Fault detection and diagnosis (FDD) is a task to deduce from observed variable of the system if any component is faulty, to locate the faults and also to estimate the fault magnitude present in the system. The main goal when synthesizing robust residual generators, for diagnosis and supervision, is to attenuate influence from model uncertainty on the residuals while keeping

  8. Application of fault detection techniques to spiral bevel gear fatigue data

    Microsoft Academic Search

    James J. Zakrajsek; Robert F. Handschuh; Harry J. Decker

    1994-01-01

    Results of applying a variety of gear fault detection techniques to experimental data is presented. A spiral bevel gear fatigue rig was used to initiate a naturally occurring fault and propagate the fault to a near catastrophic condition of the test gear pair. The spiral bevel gear fatigue test lasted a total of eighteen hours. At approximately five and a

  9. Wavelet Decomposition for the Detection and Diagnosis of Faults in Rolling Element Bearings

    Microsoft Academic Search

    J. Chebil; G. Noel; M. Mesbah; M. Deriche

    2009-01-01

    Condition monitoring and fault diagnosis of equipment and processes are of great concern in industries. Early fault detection in machineries can save millions of dollars in emergency maintenance costs. This paper presents a wavelet-based analysis technique for the diagnosis of faults in rotating machinery from its mechanical vibrations. The choice between the discrete wavelet transform and the discrete wavelet packet

  10. Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis

    Microsoft Academic Search

    Sinan Altug; Mo-Yuen Chen; H. Joel Trussell

    1999-01-01

    Motor fault detection and diagnosis involves processing a large amount of information of the motor system. With the combined synergy of fuzzy logic and neural networks, a better understanding of the heuristics underlying the motor fault detection\\/diagnosis process and successful fault detection\\/diagnosis schemes can be achieved. This paper presents two neural fuzzy (NN\\/FZ) inference systems, namely, fuzzy adaptive learning control\\/decision

  11. Hidden Markov models for fault detection in dynamic systems

    NASA Technical Reports Server (NTRS)

    Smyth, Padhraic J. (inventor)

    1995-01-01

    The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

  12. RCS propulsion functional path analysis for performance monitoring fault detection and annunciation

    NASA Technical Reports Server (NTRS)

    Keesler, E. L.

    1974-01-01

    The operational flight instrumentation required for performance monitoring and fault detection are presented. Measurements by the burn through monitors are presented along with manifold and helium source pressures.

  13. Evaluation of MEMS-Based Wireless Accelerometer Sensors in Detecting Gear Tooth Faults in Helicopter Transmissions

    NASA Technical Reports Server (NTRS)

    Lewicki, David George; Lambert, Nicholas A.; Wagoner, Robert S.

    2015-01-01

    The diagnostics capability of micro-electro-mechanical systems (MEMS) based rotating accelerometer sensors in detecting gear tooth crack failures in helicopter main-rotor transmissions was evaluated. MEMS sensors were installed on a pre-notched OH-58C spiral-bevel pinion gear. Endurance tests were performed and the gear was run to tooth fracture failure. Results from the MEMS sensor were compared to conventional accelerometers mounted on the transmission housing. Most of the four stationary accelerometers mounted on the gear box housing and most of the CI's used gave indications of failure at the end of the test. The MEMS system performed well and lasted the entire test. All MEMS accelerometers gave an indication of failure at the end of the test. The MEMS systems performed as well, if not better, than the stationary accelerometers mounted on the gear box housing with regards to gear tooth fault detection. For both the MEMS sensors and stationary sensors, the fault detection time was not much sooner than the actual tooth fracture time. The MEMS sensor spectrum data showed large first order shaft frequency sidebands due to the measurement rotating frame of reference. The method of constructing a pseudo tach signal from periodic characteristics of the vibration data was successful in deriving a TSA signal without an actual tach and proved as an effective way to improve fault detection for the MEMS.

  14. A fault tolerant control system for hexagram inverter motor drive

    Microsoft Academic Search

    Liang Zhou; Keyue Smedley

    2010-01-01

    In this paper, a fault tolerant control method for hexagram inverter motor drive is proposed. Due to its unique topology, the hexagram inverter is able to tolerate certain degree of switch failure with a proper control method. The proposed method consists of fault detection, fault isolation and post fault control. A simple fault isolation method is to use fuses in

  15. Fault Detection and Diagnosis System for the Air-conditioning

    NASA Astrophysics Data System (ADS)

    Nakahara, Nobuo

    The fault detection and diagnosis system, the FDD system, for the HVAC was initiated around the middle of 1970s in Japan but it still remains at the elementary stage. The HVAC is really one of the most complicated and large scaled system for the FDD system. Besides, the maintenance engineering was never focussed as the target of the academic study since after the war, but the FDD system for some kinds of the components and subsystems has been developed for the sake of the practical industrial needs. Recently, international cooperative study in the IEA Annex 25 on the energy conservation for the building and community targetted on the BOFD, the building optimization, fault detection and diagnosis. Not a few academic peaple from various engineering field got interested and, moreover, some national projects seem to start in the European countries. The author has reviewed the state of the art of the FDD and BO as well based on the references and the experience at the IEA study.

  16. Detection of Crosstalk Faults in Field Programmable Gate Arrays (FPGA)

    NASA Astrophysics Data System (ADS)

    Das, N.; Roy, P.; Rahaman, H.

    2014-07-01

    In this work, a Built-in-Self-Test (BIST) technique has been proposed to detect crosstalk faults in FPGA and run time congestion and to provide the crosstalk aware router for FPGA. The proposed BIST circuits require less overhead as compared to earlier techniques. The proposed detector can detect any logic hazard or delay due to crosstalk. A technique has also been proposed to avoid the crosstalk by routing the path in such a way that no interference occurs between the interconnects. The proposed router has achieved better utilization of routing resource to determine the net as compared to the earlier works. The proposed scheme is simulated in MATLAB and verified using Xilinx ISE tools and Modelsim 6.0. The router is implemented by using class provided by JBits for Xilinx, Vertex-II FPGA. It has been found that the results are quite encouraging.

  17. FINDS: A fault inferring nonlinear detection system. User's guide

    NASA Technical Reports Server (NTRS)

    Lancraft, R. E.; Caglayan, A. K.

    1983-01-01

    The computer program FINDS is written in FORTRAN-77, and is intended for operation on a VAX 11-780 or 11-750 super minicomputer, using the VMS operating system. The program detects, isolates, and compensates for failures in navigation aid instruments and onboard flight control and navigation sensors of a Terminal Configured Vehicle aircraft in a Microwave Landing System environment. In addition, FINDS provides sensor fault tolerant estimates for the aircraft states which are then used by an automatic guidance and control system to land the aircraft along a prescribed path. FINDS monitors for failures by evaluating all sensor outputs simultaneously using the nonlinear analytic relationships between the various sensor outputs arising from the aircraft point mass equations of motion. Hence, FINDS is an integrated sensor failure detection and isolation system.

  18. Natural Language Names Recognition Method -Fault Tolerant to the

    E-print Network

    Mustakerov, Ivan

    #12;Natural Language Names Recognition Method - Fault Tolerant to the Most Common Mistypings Introduction The paper considers recognition of character strings and, in particular, recognition of natural a character string of substantial length, the method is tolerant to most common typist errors. To this end

  19. A Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery

    PubMed Central

    Wang, Huaqing; Chen, Peng

    2009-01-01

    This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to. PMID:22574021

  20. A Compound Fault Diagnosis for Rolling Bearings Method Based on Blind Source Separation and Ensemble Empirical Mode Decomposition

    PubMed Central

    Wang, Huaqing; Li, Ruitong; Tang, Gang; Yuan, Hongfang; Zhao, Qingliang; Cao, Xi

    2014-01-01

    A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals’ separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion, the corresponding IMF is selected as the input matrix of ICA. Finally, the compound faults can be separated effectively by executing ICA method, which makes the fault features more easily extracted and more clearly identified. Experimental results validate the effectiveness of the proposed method in compound fault separating, which works not only for the outer race defect, but also for the rollers defect and the unbalance fault of the experimental system. PMID:25289644

  1. Analysis of faults using gravity methods in Mason County, Texas 

    E-print Network

    Milligan, Michael Glen

    1992-01-01

    ANALYSIS OF FAULTS USING GRAVITY METHODS IN MASON COUNTY& TEXAS A Thesis by MICHAEL GLEN MILLIGAN Submitted to the Office of Graduate Studies of Texas ARM University in partial fulfillment of the requirements for the degree of MASTER... OF SCIENCE May 1992 Major Subject: Geophysics ANALYSIS OF FAULTS USING GRAVITY METHODS IN MASON COUNTY) TEXAS A Thesis by MICHAEL GLEN MILLIGAN Approved as to style and content by: k-d, Pm&k D. A. Fahlquist Co-Chair of Committee . Johnson Co...

  2. A new PMU-based fault detection\\/location technique for transmission lines with consideration of arcing fault discrimination-part I: theory and algorithms

    Microsoft Academic Search

    Ying-Hong Lin; Chih-Wen Liu; Ching-Shan Chen

    2004-01-01

    A new fault detection\\/location technique with consideration of arcing fault discrimination based on phasor measurement units for extremely high voltage\\/ultra-high voltage transmission lines is presented in this two-paper set. Part I of this two-paper set is mainly aimed at theory and algorithm derivation. The proposed fault detection technique for both arcing and permanent faults is achieved by a combination of

  3. A new three-dimensional method of fault reactivation analysis

    NASA Astrophysics Data System (ADS)

    Leclere, H.; Fabbri, O.

    2012-12-01

    A 3-D method to evaluate the reactivation potential of fault planes is proposed. The method can be applied to cohesive or non cohesive faults whatever their orientation and without any condition on the regional stress field. It allows to compute the effective stress ratio ?3'/?1' required to reactivate any fault plane and to determine whether the plane is favorably oriented, unfavorably oriented or severely misoriented with respect to the ambient stress field. The method also includes a graphical sorting tool which consists in plotting poles of fault planes on stereoplots on which the boundaries separating the three domains corresponding to favorable orientations, unfavorable orientations and severe misorientations cases are drawn. The delineation of these domains is based on the value of the ?3'/?1' ratio which itself depends on the orientation of the fault plane with respect to the principal stress axis orientations, the stress shape ratio (? = (?2 - ?3)/(?1- ?3)), the coefficient of static friction ?s of the fault, and the fault cohesion C0. The method is applied on 145 focal mechanisms of the 2011 March 11th Tohoku-Oki (Japan) earthquake sequence. This application allows to delineate, along or in the vicinity of the plate interface, three types of domains characterized by favorable orientations, unfavorable orientations or severe misorientations of mainshock/aftershock fault planes. The 'severe misorientation' domains likely correspond to parts of the plate interface characterized by pore fluid pressures exceeding the magnitude of the regional least principal stress component. Stereoplots for application of the 3-D fault reactivation analysis. The stereoplots at the summits of the central triangle correspond to the three possible Andersonian stress tensors (one vertical principal stress axis, successively ?1 ,?2 and ?3). The three other triangles shearing two tops with the central triangle are characterized by non-Andersonian stress tensors with one horizontal principal stress axis and two titled principal stress axes. These non-Andersonian stress tensors correspond to rotations of 45° around one horizontal stress axis of the Andersonian tensors. For the six stress tensors plotting on each summits, seven stereoplots are computed by varying the values of C0/?1, ?s and ?. Each of the 42 stereoplots displays the location of the favorable orientation, unfavorable orientation and severely misorientation domains.

  4. Online Sensor Fault Detection Based on an Improved Strong Tracking Filter

    PubMed Central

    Wang, Lijuan; Wu, Lifeng; Guan, Yong; Wang, Guohui

    2015-01-01

    We propose a method for online sensor fault detection that is based on the evolving Strong Tracking Filter (STCKF). The cubature rule is used to estimate states to improve the accuracy of making estimates in a nonlinear case. A residual is the difference in value between an estimated value and the true value. A residual will be regarded as a signal that includes fault information. The threshold is set at a reasonable level, and will be compared with residuals to determine whether or not the sensor is faulty. The proposed method requires only a nominal plant model and uses STCKF to estimate the original state vector. The effectiveness of the algorithm is verified by simulation on a drum-boiler model. PMID:25690553

  5. Fault Detection, Diagnosis and Prediction in Electrical Valves Using Self-Organizing Maps

    Microsoft Academic Search

    Luiz Fernando Gonçalves; Jefferson Luiz Bosa; Tiago Roberto Balen; Marcelo Soares Lubaszewski; Eduardo Luis Schneider; Renato Ventura Henriques

    This paper presents a proactive maintenance scheme for fault detection, diagnosis and prediction in electrical valves. The\\u000a proposed scheme is validated with a case study, considering a specific valve used for controlling the oil flow in a distribution\\u000a network. The scheme is based in self-organizing maps, which perform fault detection and diagnosis, and temporal self-organizing\\u000a maps for fault prediction. The

  6. Robust nonlinear observer-based fault detection for a U-tube steam generator

    Microsoft Academic Search

    R. Seliger; B. Koppen-Seliger

    1995-01-01

    Based on previously proposed nonlinear unknown input observer-based fault detection schemes for uncertain systems the authors suggest a robust fault detection technique for a U-tube steam generator. One major problem in modelling steam generators is the proper identification of the heat transfer coefficients which in reality are distributed parameters depending on the temperature and pressure conditions inside the steam generator.

  7. Fourier and wavelet transformations for the fault detection of induction motor with stator current

    Microsoft Academic Search

    Sang-Hyuk Lee; Sungshin Kim; Jang Mok Kim; Man Hyung Lee

    2004-01-01

    In this literature, fault detection of an induction motor is carried out using the information of stator current. After preprocessing actual data, Fourier and wavelet transforms are applied to detect characteristics under the healthy and various faulted conditions. The most reliable phase current among 3-phase currents is selected by the fuzzy entropy. Data are trained with a neural network system,

  8. System for detecting and limiting electrical ground faults within electrical devices

    Microsoft Academic Search

    Gaubatz; Donald C

    1990-01-01

    An electrical ground fault detection and limitation system for employment with a nuclear reactor utilizing a liquid metal coolant. Elongate electromagnetic pumps submerged within the liquid metal coolant and electrical support equipment experiencing an insulation breakdown occasion the development of electrical ground fault current. Without some form of detection and control, these currents may build to damaging power levels to

  9. A Comparative Study of Time-Frequency Representations for Fault Detection in Wind Turbine

    E-print Network

    Paris-Sud XI, Université de

    A Comparative Study of Time-Frequency Representations for Fault Detection in Wind Turbine El of wind energy, minimization and prediction of maintenance operations in wind turbine is of key importance and the easiness of interpretation. Index Terms--Wind turbine, fault detection, broken-rotor bars, signal

  10. STATE OF CALIFORNIA AUTOMATIC FAULT DETECTION AND DIAGNOSTICS (FDD) FOR AIR HANDLING UNITS

    E-print Network

    STATE OF CALIFORNIA AUTOMATIC FAULT DETECTION AND DIAGNOSTICS (FDD) FOR AIR HANDLING UNITS AND ZONE TERMINAL UNITS ACCEPTANCE CEC-MECH-13A (Revised 08/09) CALIFORNIA ENERGY COMMISSION CERTIFICATE OF ACCEPTANCE MECH-13A NA7.5.12 Automatic Fault Detection and Diagnostics (FDD) for Air Handling Units and Zone

  11. A representation for coordination fault detection in large-scale multi-agent systems

    Microsoft Academic Search

    Michael Lindner; Meir Kalech; Gal A. Kaminka

    2009-01-01

    Teamwork requires that team members coordinate their actions. The representation of the coordination is a key requirement since it influences the complexity and flexibility of reasoning team-members. One aspect of this requirement is detecting coordination faults as a result of intermittent failures of sensors, communication failures, etc. Detection of such faults, based on observations of the behavior of agents, is

  12. Fault detection for salinity sensors in the Columbia estuary Cynthia Archer

    E-print Network

    Leen, Todd K.

    Fault detection for salinity sensors in the Columbia estuary Cynthia Archer Department of Computer, salinity measurement Citation: Archer, C., A. Baptista, and T. K. Leen, Fault detection for salinity [U.S. Army Corps of Engineers, 2001]. [3] CORIE salinity sensors deployed in the harsh estuary

  13. Fault detection system in gas lift well based on artificial immune system

    Microsoft Academic Search

    Manana Araujo; Jose Aguilar; Hugo Aponte

    2003-01-01

    In this paper we propose an Artificial Immune System for fault detection in gas lift oil well. Our novel approach inspired by the Immune System allows the application of a pattern recognition model to perform fault detection. A significant feature of our approach is its ability to dynamically learning the fluid patterns of the 'self' and predicting new patterns of

  14. Arcing faults detection on power lines from the voltage and current signals

    Microsoft Academic Search

    M. B. ?uri?; Z. M. Radojevi?; V. V. Terzija

    1996-01-01

    Contents To avoid automatic reclosing on permanent faults, a new digital algorithm for arcing faults detection has been developed. Some important features of a long arc in the air are investigated and used as a base in the algorithm design. The fact that the nonlinear arc behavior influences other voltages and currents distorting them, offered an opportunity to detect the

  15. A new approach to the arcing faults detection for fast autoreclosure in transmission systems

    Microsoft Academic Search

    M. B. Djuric; V. V. Terzija

    1995-01-01

    To avoid automatic reclosing on permanent faults, a new numerical algorithm for arcing faults detection has been developed. Some important features of long arc in air are investigated and used as a base in the algorithm design. The fact that the nonlinear arc behavior influences other voltages and currents distorting them, offered an opportunity to detect the arc by measuring

  16. A laboratory investigation of electro-optic Kerr effect for detection of electric transmission line faults

    Microsoft Academic Search

    Thad J. Englert; B. H. Chowdhury; E. Grigsby

    1991-01-01

    A prototype Kerr cell has been constructed and tested for detecting and identifying faults by monitoring high voltages such as are found in electric power delivery systems. Simulated faults have been generated under laboratory conditions, monitored by the Ken cell, and preliminary analysis done using analog-to-digital conversion of the detected waveforms with a single board microprocessor serially interfaced with a

  17. A neural-network approach to fault detection and diagnosis in industrial processes

    Microsoft Academic Search

    Yunosuke Maki; Kenneth A. Loparo

    1997-01-01

    Using a multilayered feedforward neural-network approach, the detection and diagnosis of faults in industrial processes that requires observing multiple data simultaneously are studied in this paper. The main feature of our approach is that the detection of the faults occurs during transient periods of operation of the process. A two-stage neural network is proposed as the basic structure of the

  18. A joint wavelet lifting and independent component analysis approach to fault detection of rolling element bearings

    Microsoft Academic Search

    Xianfeng Fan; Ming Liang; Tet H. Yeap; Bob Kind

    2007-01-01

    Though wavelet transforms have been used to extract bearing fault signatures from vibration signals in the literature, detection results often rely on a proper wavelet function and deep wavelet decomposition. The selection of a proper wavelet function is time consuming and deep decomposition demands more computing effort. This is unsuitable for on-line fault detection. As such, we propose a joint

  19. Detection of transmission line faults in the presence of STATCOM using wavelets

    Microsoft Academic Search

    P. Venugopal Rao; Shaik Abdul Gafoor; C. Venkatesh

    2011-01-01

    In this paper, wavelet transform technique is applied to detect fault in the transmission line with flexible alternating current transmission (FACTS) device. Presence of FACTS device changes the system impedance and hence makes it difficult to detect faults on the line which may result into maloperation of relay. Three phase currents are monitored at both ends of the transmission line

  20. Synchronous Machine Faults Detection and Diagnosis for Electro-mechanical Actuators

    E-print Network

    Boyer, Edmond

    Detection and Isolation system for permanent magnet synchronous machine (PMSM). Two main faults occurring-circuit, Permanent Magnet Synchronous Machine, Diagnosis. 1. INTRODUCTION Facing the growth of the air transportSynchronous Machine Faults Detection and Diagnosis for Electro-mechanical Actuators in Aeronautics

  1. Virtual prototype and experimental research on gear multi-fault diagnosis using wavelet-autoregressive model and principal component analysis method

    NASA Astrophysics Data System (ADS)

    Li, Zhixiong; Yan, Xinping; Yuan, Chengqing; Peng, Zhongxiao; Li, Li

    2011-10-01

    Gear systems are an essential element widely used in a variety of industrial applications. Since approximately 80% of the breakdowns in transmission machinery are caused by gear failure, the efficiency of early fault detection and accurate fault diagnosis are therefore critical to normal machinery operations. Reviewed literature indicates that only limited research has considered the gear multi-fault diagnosis, especially for single, coupled distributed and localized faults. Through virtual prototype simulation analysis and experimental study, a novel method for gear multi-fault diagnosis has been presented in this paper. This new method was developed based on the integration of Wavelet transform (WT) technique, Autoregressive (AR) model and Principal Component Analysis (PCA) for fault detection. The WT method was used in the study as the de-noising technique for processing raw vibration signals. Compared with the noise removing method based on the time synchronous average (TSA), the WT technique can be performed directly on the raw vibration signals without the need to calculate any ensemble average of the tested gear vibration signals. More importantly, the WT can deal with coupled faults of a gear pair in one operation while the TSA must be carried out several times for multiple fault detection. The analysis results of the virtual prototype simulation prove that the proposed method is a more time efficient and effective way to detect coupled fault than TSA, and the fault classification rate is superior to the TSA based approaches. In the experimental tests, the proposed method was compared with the Mahalanobis distance approach. However, the latter turns out to be inefficient for the gear multi-fault diagnosis. Its defect detection rate is below 60%, which is much less than that of the proposed method. Furthermore, the ability of the AR model to cope with localized as well as distributed gear faults is verified by both the virtual prototype simulation and experimental studies.

  2. Error detection method

    DOEpatents

    Olson, Eric J.

    2013-06-11

    An apparatus, program product, and method that run an algorithm on a hardware based processor, generate a hardware error as a result of running the algorithm, generate an algorithm output for the algorithm, compare the algorithm output to another output for the algorithm, and detect the hardware error from the comparison. The algorithm is designed to cause the hardware based processor to heat to a degree that increases the likelihood of hardware errors to manifest, and the hardware error is observable in the algorithm output. As such, electronic components may be sufficiently heated and/or sufficiently stressed to create better conditions for generating hardware errors, and the output of the algorithm may be compared at the end of the run to detect a hardware error that occurred anywhere during the run that may otherwise not be detected by traditional methodologies (e.g., due to cooling, insufficient heat and/or stress, etc.).

  3. Fault Attack Resistant Cryptographic Hardware with Uniform Error Detection

    E-print Network

    Karpovsky, Mark

    consumption, electro-magnetic radia- tion, execution time, and behavior in the presence of faults of a device the circuit (permanent or tran- sient) which may be due to natural effects or be maliciously induced. Faults

  4. A new hybrid method for fault tree analysis

    Microsoft Academic Search

    S. Contini

    1995-01-01

    This paper describes a new method for determining the significant minimal cut sets of complex fault trees. It can be classified as hybrid, being based on the application of both Top Down and Bottom Up reduction approaches. This solution has been adopted particularly to accurately estimate the truncation error when the probabilistic cut-off technique is applied. Experimental results on real

  5. Assessing Method of Voltage Sag Frequency Caused by Transmission Line faults

    Microsoft Academic Search

    Xian-Yong Xiao; Chao Ma; Zheng-Guang Li; Yin Wang

    2009-01-01

    Fault location on transmission line influences the characteristics of voltage sag at given bus. It is difficult to determine the fault pattern and voltage sag frequency. A new method based on maximum entropy principle was proposed to assess sag frequency synthetically considered different fault types and objective probability distribution of fault location in the power system. The faulty line intervals

  6. Method for detecting biomolecules

    DOEpatents

    Huo, Qisheng (Albuquerque, NM); Liu, Jun (Albuquerque, NM)

    2008-08-12

    A method for detecting and measuring the concentration of biomolecules in solution, utilizing a conducting electrode in contact with a solution containing target biomolecules, with a film with controllable pore size distribution characteristics applied to at least one surface of the conducting electrode. The film is functionalized with probe molecules that chemically interact with the target biomolecules at the film surface, blocking indicator molecules present in solution from diffusing from the solution to the electrode, thereby changing the electrochemical response of the electrode

  7. Detecting and approximating fault lines from randomly scattered data

    Microsoft Academic Search

    Andrew Crampton; John C. Mason

    2005-01-01

    Discretely defined surfaces that exhibit vertical displacements across unknown fault lines can be difficult to approximate accurately unless a representation of the faults is known. Accurate representations of these faults enable the construction of constrained approximation models that can successfully overcome common problems such as over-smoothing.

  8. A Multi-Fault Diagnosis Method for Sensor Systems Based on Principle Component Analysis

    PubMed Central

    Zhu, Daqi; Bai, Jie; Yang, Simon X.

    2010-01-01

    A model based on PCA (principal component analysis) and a neural network is proposed for the multi-fault diagnosis of sensor systems. Firstly, predicted values of sensors are computed by using historical data measured under fault-free conditions and a PCA model. Secondly, the squared prediction error (SPE) of the sensor system is calculated. A fault can then be detected when the SPE suddenly increases. If more than one sensor in the system is out of order, after combining different sensors and reconstructing the signals of combined sensors, the SPE is calculated to locate the faulty sensors. Finally, the feasibility and effectiveness of the proposed method is demonstrated by simulation and comparison studies, in which two sensors in the system are out of order at the same time. PMID:22315537

  9. IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 24, NO. 2, JUNE 2009 431 Fault Detection and Diagnosis in a Set

    E-print Network

    Boyer, Edmond

    W inverter-fed asynchronous motor, in order to detect supply and motor faults. In this application the efficiency of our diagnosis method. Index Terms--Data standardization, diagnosis, induction ma- chine effective when the motor is supplied by the three-phase main network. However, in more and more industrials

  10. A Low Cost Approach for Detecting, Locating, and Avoiding Interconnect Faults in FPGA-Based Reconfigurable Systems

    Microsoft Academic Search

    Debaleena Das; Nur A. Touba

    1999-01-01

    An FPGA-based reconfigurable system may contain boards of FPGAs which are reconfigured for different applications and must work correctly. This paper presents a novel approach for rapidly testing the interconnect in the FPGAs each time the system is reconfigured. A low- cost configuration-dependent test method is used to both detect and locate faults in the interconnect. The \\

  11. A hybrid fault diagnosis method using morphological filter-translation invariant wavelet and improved ensemble empirical mode decomposition

    NASA Astrophysics Data System (ADS)

    Meng, Lingjie; Xiang, Jiawei; Wang, Yanxue; Jiang, Yongying; Gao, Haifeng

    2015-01-01

    Defective rolling bearing response is often characterized by the presence of periodic impulses, which are usually immersed in heavy noise. Therefore, a hybrid fault diagnosis approach is proposed. The morphological filter combining with translation invariant wavelet is taken as the pre-filter process unit to reduce the narrowband impulses and random noises in the original signal, then the purified signal will be decomposed by improved ensemble empirical mode decomposition (EEMD), in which a new selection method integrating autocorrelation analysis with the first two intrinsic mode functions (IMFs) having the maximum energies is put forward to eliminate the pseudo low-frequency components of IMFs. Applying the envelope analysis on those selected IMFs, the defect information is easily extracted. The proposed hybrid approach is evaluated by simulations and vibration signals of defective bearings with outer race fault, inner race fault, rolling element fault. Results show that the approach is feasible and effective for the fault detection of rolling bearing.

  12. Distributed Fault Detection and Isolation with Imprecise Network Iman Shames, Andre M. H. Teixeira, Henrik Sandberg, Karl H. Johansson

    E-print Network

    Johansson, Karl Henrik

    Distributed Fault Detection and Isolation with Imprecise Network Models Iman Shames, Andr´e M. H- tributed Fault Detection and Isolation (D-FDI) in large net- worked systems with imprecise models. Taking that for this kind of perturbations there exist suitable thresholds for which fault detection and isolation

  13. Performance Study of Enhanced Auto-Associative Neural Networks For Sensor Fault Detection 

    E-print Network

    Najafi, M.; Culp, C.; Langari, R.

    2004-01-01

    Performance Study of Enhanced Auto-Associative Neural Networks For Sensor Fault Detection Massieh Najafi, Charles Culp and Reza Langari Department of Mechanical Engineering Texas A&M University College Station, TX 77843-3123 1... into evaporator), and evap (mass flow rate of water into evaporator). The outputs to the model are: cout _ (temperature of water existing condenser), eout _ ( temperature of Sensor Fault Condition AANN Analyzer + + + - - -Ext E-AANN Sensor Fault Condition...

  14. Model-based fault detection and isolation for a powered wheelchair

    Microsoft Academic Search

    Masafumi Hashimoto; Fumihiro Itaba; Kazuhiko Takahashi

    2010-01-01

    This paper presents a model-based fault detection and isolation (FDI) for a powered wheelchair handling faults of both the internal sensors (two wheel-resolvers and a gyro) and the external sensor (a forward-looking laser range sensor), as well as actuators (two wheel motors). Hard faults of the internal sensors and actuators are diagnosed based on mode probability estimated with interacting multi-model

  15. Detection of high impedance arcing faults using a multi-layer perceptron

    Microsoft Academic Search

    F. F. Sultan; G. W. Swift; D. J. Fedirchuk

    1992-01-01

    A feed-forward three-layer perceptron was trained by high impedance fault, fault-like load, and normal load current patterns, using the back-propagation training algorithm. This paper reports that the neural network parameters were embodied in a high impedance arcing faults detection algorithm, which uses a simple preprocessing technique to prepare the information input to the network. The algorithm was tested by traces

  16. A Hardware-Based Approach for Fault Detection in RTOS-Based Embedded Systems

    Microsoft Academic Search

    D. Silva; K. Stangherlin; L. Bolzani; F. Vargas

    2011-01-01

    This paper presents a new hardware-based approach able to monitor the execution flow of the Real-Time Operating System (RTOS) in order to detect faults changing the tasks' execution flow in embedded systems. Results obtained during experiments performed according to the IEC 61000-4-29 standard demonstrate that the proposed approach is able to provide higher fault coverage with respect to the fault

  17. Fault-Detection Tool Has Companies 'Mining' Own Business

    NASA Technical Reports Server (NTRS)

    2005-01-01

    A successful launching of NASA's Space Shuttle hinges heavily on the three Space Shuttle Main Engines (SSME) that power the orbiter. These critical components must be monitored in real time, with sensors, and compared against expected behaviors that could scrub a launch or, even worse, cause in- flight hazards. Since 1981, SSME faults have caused 23 scrubbed launches and 29 percent of total Space Shuttle downtime, according to a compilation of analysis reports. The most serious cases typically occur in the last few seconds before ignition; a launch scrub that late in the countdown usually means a period of investigation of a month or more. For example, during the launch attempt of STS-41D in 1984, an anomaly was detected in the number three engine, causing the mission to be scrubbed at T-4 seconds. This not only affected STS-41D, but forced the cancellation of another mission and caused a 2-month flight delay. In 2002, NASA s Kennedy Space Center, the Florida Institute of Technology, and Interface & Control Systems, Inc., worked together to attack this problem by creating a system that could automate the detection of mechanical failures in the SSMEs fuel control valves.

  18. New method for the location of ground faults on transmission system

    Microsoft Academic Search

    Haifa Al Motairy; Redy Mardiana; Charles Q. Su

    2011-01-01

    This paper presents a new fault location method using high-frequency transient voltages generated by ground faults on transmission system. The method is based on the measurement from one end of the transmission line. The fault location is determined solely from the arrival time of initial waves of modal voltages at the measuring bus. The method does not need to exploit

  19. Fault Detection, Isolation and Reconfiguration in Presence of Incipient Sensor Faults in an Electromechanical Flight Control Actuation System

    Microsoft Academic Search

    M. Jayakumar; B. B. Das

    2006-01-01

    This paper presents a scheme for the detection and isolation of incipient sensor faults in a flight control actuation system. The system considered here is a practical system, which is an electromechanical flight actuator, based on a DC torque motor. The scheme utilizes the analytical redundancy that exists in the system between the linear actuator position, motor shaft velocity and

  20. Hidden Markov Models for Fault Detection in Dynamic Systems

    NASA Technical Reports Server (NTRS)

    Smyth, Padhraic

    1994-01-01

    Continuous monitoring of complex dynamic systems is an increasingly important issue in diverse areas such as nuclear plant safety, production line reliability, and medical health monitoring systems. Recent advances in both sensor technology and computational capabilities have made on-line permanent monitoring much more feasible than it was in the past. In this paper it is shown that a pattern recognition system combined with a finite-state hidden Markov model provides a particularly useful method for modelling temporal context in continuous monitoring. The parameters of the Markov model are derived from gross failure statistics such as the mean time between failures. The model is validated on a real-world fault diagnosis problem and it is shown that Markov modelling in this context offers significant practical benefits.

  1. Low-cost motor drive embedded fault diagnosis systems 

    E-print Network

    Akin, Bilal

    2009-05-15

    cost incipient fault detection of inverter-fed driven motors. Basically, low order inverter harmonics contributions to fault diagnosis, a motor drive embedded condition monitoring method, analysis of motor fault signatures in noisy line current, and a...

  2. Intermittent/transient fault phenomena in digital systems

    NASA Technical Reports Server (NTRS)

    Masson, G. M.

    1977-01-01

    An overview of the intermittent/transient (IT) fault study is presented. An interval survivability evaluation of digital systems for IT faults is discussed along with a method for detecting and diagnosing IT faults in digital systems.

  3. Functional Fault Modeling of a Cryogenic System for Real-Time Fault Detection and Isolation

    NASA Technical Reports Server (NTRS)

    Ferrell, Bob; Lewis, Mark; Oostdyk, Rebecca; Perotti, Jose

    2009-01-01

    When setting out to model and/or simulate a complex mechanical or electrical system, a modeler is faced with a vast array of tools, software, equations, algorithms and techniques that may individually or in concert aid in the development of the model. Mature requirements and a well understood purpose for the model may considerably shrink the field of possible tools and algorithms that will suit the modeling solution. Is the model intended to be used in an offline fashion or in real-time? On what platform does it need to execute? How long will the model be allowed to run before it outputs the desired parameters? What resolution is desired? Do the parameters need to be qualitative or quantitative? Is it more important to capture the physics or the function of the system in the model? Does the model need to produce simulated data? All these questions and more will drive the selection of the appropriate tools and algorithms, but the modeler must be diligent to bear in mind the final application throughout the modeling process to ensure the model meets its requirements without needless iterations of the design. The purpose of this paper is to describe the considerations and techniques used in the process of creating a functional fault model of a liquid hydrogen (LH2) system that will be used in a real-time environment to automatically detect and isolate failures.

  4. Development, Implementation, and Testing of Fault Detection Strategies on the National Wind Technology Center's Controls Advanced Research Turbines

    SciTech Connect

    Johnson, K. E.; Fleming, P. A.

    2011-06-01

    The National Renewable Energy Laboratory's National Wind Technology Center dedicates two 600 kW turbines for advanced control systems research. A fault detection system for both turbines has been developed, analyzed, and improved across years of experiments to protect the turbines as each new controller is tested. Analysis of field data and ongoing fault detection strategy improvements have resulted in a system of sensors, fault definitions, and detection strategies that have thus far been effective at protecting the turbines. In this paper, we document this fault detection system and provide field data illustrating its operation while detecting a range of failures. In some cases, we discuss the refinement process over time as fault detection strategies were improved. The purpose of this article is to share field experience obtained during the development and field testing of the existing fault detection system, and to offer a possible baseline for comparison with more advanced turbine fault detection controllers.

  5. Usage of Fault Detection Isolation & Recovery (FDIR) in Constellation (CxP) Launch Operations

    NASA Technical Reports Server (NTRS)

    Ferrell, Rob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Spirkovska, Lilly; Hall, David; Brown, Barbara

    2010-01-01

    This paper will explore the usage of Fault Detection Isolation & Recovery (FDIR) in the Constellation Exploration Program (CxP), in particular Launch Operations at Kennedy Space Center (KSC). NASA's Exploration Technology Development Program (ETDP) is currently funding a project that is developing a prototype FDIR to demonstrate the feasibility of incorporating FDIR into the CxP Ground Operations Launch Control System (LCS). An architecture that supports multiple FDIR tools has been formulated that will support integration into the CxP Ground Operation's Launch Control System (LCS). In addition, tools have been selected that provide fault detection, fault isolation, and anomaly detection along with integration between Flight and Ground elements.

  6. Advanced Signal Processing Techniques for Fault Detection and Diagnosis in a Wind Turbine

    E-print Network

    Paris-Sud XI, Université de

    Advanced Signal Processing Techniques for Fault Detection and Diagnosis in a Wind Turbine Induction rotor bars and bearing damages. Index Terms--Wind turbines, motor current signature analy- sis, time of maintenance in offshore environment, teledetection of wind turbine faults is becoming a crucial issue

  7. Adaptive threshold-based fault detection and isolation for automotive electrical systems

    Microsoft Academic Search

    Ali Hashemi; Pierluigi Pisu

    2011-01-01

    In this paper, a fault diagnosis scheme to detect and isolate faults commonly occurring in a vehicle alternator system based on an adaptive thresholds approach is developed. The mathematical model of the alternator subsystem is quite involved and highly nonlinear; to simplify the diagnostic scheme, an equivalent linear time varying model based on the input- output behavior of the system

  8. Limitations for detecting small-scale faults using the coherency analysis of seismic data 

    E-print Network

    Barnett, David Benjamin

    2006-08-16

    . The sensitivity of the coherency algorithms to variations in wave frequency, signal-to-noise ratio and fault throw was investigated. Correlation between the coherency values of a faulted reflector and the known offset shows that coherency has the ability to detect...

  9. Detection and extraction of fault surfaces in 3D seismic data Israel Cohen1

    E-print Network

    Cohen, Israel

    that are unrelated to faults. Furthermore, creating a consistent geological interpretation from large 3D-seismicDetection and extraction of fault surfaces in 3D seismic data Israel Cohen1 , Nicholas Coult2 surfaces in 3D-seismic volumes. The seismic data are transformed into a volume of local

  10. Process monitoring using causal map and multivariate statistics: fault detection and identification

    E-print Network

    Braatz, Richard D.

    .V. All rights reserved. Keywords: Fault detection; Fault identification; Process monitoring; Chemometrics). www.elsevier.com/locate/chemometrics Chemometrics and Intelligent Laboratory Systems 65 (2003) 159 / Chemometrics and Intelligent Laboratory Systems 65 (2003) 159­178160 #12;Fig. 3. Example 3: (a) The normalized

  11. Analysis and detection of arcing faults in low-voltage electrical power systems

    Microsoft Academic Search

    D. G. Ece; F. M. Wells

    1994-01-01

    This work focuses on developing a more complete understanding of the properties of arcing fault waveforms in a 230 volt, three-phase electrical system and to detect them in a cost efficient way. Analysis of waveform properties of experimental arcing fault current waveforms revealed significant variations from an unfaulted system current. Using the results of the analysis of the data gathered

  12. Edge-Based Fault Detection in a DiffServ Network A. Striegel, G. Manimaran

    E-print Network

    Manimaran, Govindarasu

    Edge-Based Fault Detection in a DiffServ Network A. Striegel, G. Manimaran Dependable Computing accelerated the development of key tech- nologies such as Differentiated Services (DiffServ). Al- though Qo in the DiffServ architecture. For traditional IP networks, the underlying link state protocol provides fault

  13. Recurrent neuro-fuzzy system for fault detection and isolation in nuclear reactors

    Microsoft Academic Search

    Alexandre Evsukoff; Sylviane Gentil

    2005-01-01

    This paper presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors. A general framework is adopted, in which a fuzzification module is linked to an inference module that is actually a neural network adapted to the recognition of the dynamic evolution of process variables and related faults. Process data is fuzzified in order to

  14. Induction motors' faults detection and localization using stator current advanced signal processing techniques

    Microsoft Academic Search

    Mohamed El Hachemi Benbouzid; Michelle Vieira; C. Theys

    1999-01-01

    The knowledge about fault mode behavior of an induction motor drive system is extremely important from the standpoint of improved system design, protection, and fault-tolerant control. This paper addresses the application of motor current spectral analysis for the detection and localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of induction motors. Intensive research

  15. APPLICATION OF WAVELETS TO GEARBOX VIBRATION SIGNALS FOR FAULT DETECTION

    Microsoft Academic Search

    W. J. Wang; P. D. McFadden

    1996-01-01

    The wavelet transform is used to represent all possible types of transients in vibration signals generated by faults in a gearbox. It is shown that the transform provides a powerful tool for condition monitoring and fault diagnosis. The vibration signal from a helicopter gearbox is used to demonstrate the application of the suggested wavelet by a simple computer algorithm. The

  16. Waveguide disturbance detection method

    DOEpatents

    Korneev, Valeri A. (Albany, CA); Nihei, Kurt T. (Oakland, CA); Myer, Larry R. (Benicia, CA)

    2000-01-01

    A method for detection of a disturbance in a waveguide comprising transmitting a wavefield having symmetric and antisymmetric components from a horizontally and/or vertically polarized source and/or pressure source disposed symmetrically with respect to the longitudinal central axis of the waveguide at one end of the waveguide, recording the horizontal and/or vertical component or a pressure of the wavefield with a vertical array of receivers disposed at the opposite end of the waveguide, separating the wavenumber transform of the wavefield into the symmetric and antisymmetric components, integrating the symmetric and antisymmetric components over a broad frequency range, and comparing the magnitude of the symmetric components and the antisymmetric components to an expected magnitude for the symmetric components and the antisymmetric components for a waveguide of uniform thickness and properties thereby determining whether or not a disturbance is present inside the waveguide.

  17. In-flight Fault Detection and Isolation in Aircraft Flight Control Systems

    NASA Technical Reports Server (NTRS)

    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.

  18. Study of Gray Analysis Method of Fault Probability for Quality of Product Design

    Microsoft Academic Search

    Yiyong Yao; Liing Zha; Fei Li

    2007-01-01

    Quality of product design is formed in the process of product design. Quality problem of product design is found and solved through analysis fault reason. In the paper, Based on structure tree of product and fault tree, with combination of Node Knowledge Representation method (NKR) and Gray Analysis method (GRA), fault probability analysis model is established for product design, then

  19. A new fault location method for transmission lines taking the places of transposing into account

    Microsoft Academic Search

    Roberto Schulze; Peter Schegner

    2011-01-01

    The increasing load on the transmission system requires a fast fault location for high reliability of the grid. New communication and synchronization techniques allow the development of advanced fault location methods especially two- terminal methods. The installation of powerful hardware e. g. DSP makes the implementation of complex algorithms using directly the samples of a fault record possible. The objective

  20. Final Technical Report Recovery Act: Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines

    SciTech Connect

    Wei Qiao

    2012-05-29

    The penetration of wind power has increased greatly over the last decade in the United States and across the world. The U.S. wind power industry installed 1,118 MW of new capacity in the first quarter of 2011 alone and entered the second quarter with another 5,600 MW under construction. By 2030, wind energy is expected to provide 20% of the U.S. electricity needs. As the number of wind turbines continues to grow, the need for effective condition monitoring and fault detection (CMFD) systems becomes increasingly important [3]. Online CMFD is an effective means of not only improving the reliability, capacity factor, and lifetime, but it also reduces the downtime, energy loss, and operation and maintenance (O&M) of wind turbines. The goal of this project is to develop novel online nonintrusive CMFD technologies for wind turbines. The proposed technologies use only the current measurements that have been used by the control and protection system of a wind turbine generator (WTG); no additional sensors or data acquisition devices are needed. Current signals are reliable and easily accessible from the ground without intruding on the wind turbine generators (WTGs) that are situated on high towers and installed in remote areas. Therefore, current-based CMFD techniques have great economic benefits and the potential to be adopted by the wind energy industry. Specifically, the following objectives and results have been achieved in this project: (1) Analyzed the effects of faults in a WTG on the generator currents of the WTG operating at variable rotating speed conditions from the perspective of amplitude and frequency modulations of the current measurements; (2) Developed effective amplitude and frequency demodulation methods for appropriate signal conditioning of the current measurements to improve the accuracy and reliability of wind turbine CMFD; (3) Developed a 1P-invariant power spectrum density (PSD) method for effective signature extraction of wind turbine faults with characteristic frequencies in the current or current demodulated signals, where 1P stands for the shaft rotating frequency of a WTG; (4) Developed a wavelet filter for effective signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (5) Developed an effective adaptive noise cancellation method as an alternative to the wavelet filter method for signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (6) Developed a statistical analysis-based impulse detection method for effective fault signature extraction and evaluation of WTGs based on the 1P-invariant PSD of the current or current demodulated signals; (7) Validated the proposed current-based wind turbine CMFD technologies through extensive computer simulations and experiments for small direct-drive WTGs without gearboxes; and (8) Showed, through extensive experiments for small direct-drive WTGs, that the performance of the proposed current-based wind turbine CMFD technologies is comparable to traditional vibration-based methods. The proposed technologies have been successfully applied for detection of major failures in blades, shafts, bearings, and generators of small direct-drive WTGs. The proposed technologies can be easily integrated into existing wind turbine control, protection, and monitoring systems and can be implemented remotely from the wind turbines being monitored. The proposed technologies provide an alternative to vibration-sensor-based CMFD. This will reduce the cost and hardware complexity of wind turbine CMFD systems. The proposed technologies can also be combined with vibration-sensor-based methods to improve the accuracy and reliability of wind turbine CMFD systems. When there are problems with sensors, the proposed technologies will ensure proper CMFD for the wind turbines, including their sensing systems. In conclusion, the proposed technologies offer an effective means to achieve condition-based smart maintenance for wind turbines and have a gre

  1. System for detecting and limiting electrical ground faults within electrical devices

    DOEpatents

    Gaubatz, Donald C. (Cupertino, CA)

    1990-01-01

    An electrical ground fault detection and limitation system for employment with a nuclear reactor utilizing a liquid metal coolant. Elongate electromagnetic pumps submerged within the liquid metal coolant and electrical support equipment experiencing an insulation breakdown occasion the development of electrical ground fault current. Without some form of detection and control, these currents may build to damaging power levels to expose the pump drive components to liquid metal coolant such as sodium with resultant undesirable secondary effects. Such electrical ground fault currents are detected and controlled through the employment of an isolated power input to the pumps and with the use of a ground fault control conductor providing a direct return path from the affected components to the power source. By incorporating a resistance arrangement with the ground fault control conductor, the amount of fault current permitted to flow may be regulated to the extent that the reactor may remain in operation until maintenance may be performed, notwithstanding the existence of the fault. Monitors such as synchronous demodulators may be employed to identify and evaluate fault currents for each phase of a polyphase power, and control input to the submerged pump and associated support equipment.

  2. Fault Detection and Isolation Techniques for Quasi DelayInsensitive Circuits Christopher LaFrieda and Rajit Manohar

    E-print Network

    Manohar, Rajit

    logic would be analogous to faults in data as well as clock lines in a clocked sys­ tem. FaultyFault Detection and Isolation Techniques for Quasi Delay­Insensitive Circuits Christopher La presents a novel circuit fault detection and isolation technique for quasi delay­insensitive asyn­ chronous

  3. Fault Detection and Isolation Techniques for Quasi Delay-Insensitive Circuits Christopher LaFrieda and Rajit Manohar

    E-print Network

    Manohar, Rajit

    logic would be analogous to faults in data as well as clock lines in a clocked sys- tem. FaultyFault Detection and Isolation Techniques for Quasi Delay-Insensitive Circuits Christopher La presents a novel circuit fault detection and isolation technique for quasi delay-insensitive asyn- chronous

  4. Probability of detecting single faults in Hadamard and SWAP gates of a quantum computer after several operations

    E-print Network

    Probability of detecting single faults in Hadamard and SWAP gates of a quantum computer after 1A7 Decoherence of quantum states is the main factor which causes fault in a quantum computer. In this article, the probability of detecting fault in a quantum computer is examined mainly for the Hadamard

  5. A comprehensive evaluation of multicategory classification methods for fault classification in series compensated transmission line

    Microsoft Academic Search

    V. Malathi; N. S. Marimuthu; S. Baskar

    2010-01-01

    This paper presents a new method for fault classification in series-compensated transmission line using multiclass support\\u000a vector machine (MCSVM) and multi class extreme learning machine (MCELM). These methods use the information obtained from the\\u000a wavelet decomposition of fault current signals for fault classification. Using MATLAB simulink, data set has been generated\\u000a with different types of fault and system variables, which

  6. Lessons Learned on Implementing Fault Detection, Isolation, and Recovery (FDIR) in a Ground Launch Environment

    NASA Technical Reports Server (NTRS)

    Ferell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Goerz, Jesse; Brown, Barbara

    2010-01-01

    This paper's main purpose is to detail issues and lessons learned regarding designing, integrating, and implementing Fault Detection Isolation and Recovery (FDIR) for Constellation Exploration Program (CxP) Ground Operations at Kennedy Space Center (KSC).

  7. On-line early fault detection and diagnosis of municipal solid waste incinerators

    SciTech Connect

    Zhao Jinsong [College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029 (China)], E-mail: jinsongzhao@mail.tsinghua.edu.cn; Huang Jianchao [College of Information Science and Technology, Beijing Institute of Technology, Beijing 10086 (China); Sun Wei [College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China)

    2008-11-15

    A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows that automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI.

  8. Monitoring and fault detection in processes with multiple operating modes, transitory phases and start-ups using principal component analysis

    Microsoft Academic Search

    D. Garcia-Alvarez; M. J. Fuente; G. Sainz

    2010-01-01

    This paper presents a global monitoring and fault detection approach considering the different operation points, start-ups and transitory states that can appear during plant operation. Stationary states have been monitored using the classical PCA approach and start-ups, while grade transition due to, for example changes in the set-point, are monitored using batch and semi-batch PCA-based methods. These methods have been

  9. Statistic-based spectral indicator for bearing fault detection in permanent-magnet synchronous machines using the stator current

    NASA Astrophysics Data System (ADS)

    Picot, A.; Obeid, Z.; Régnier, J.; Poignant, S.; Darnis, O.; Maussion, P.

    2014-06-01

    In this paper, an original method for bearing fault detection in high speed synchronous machines is presented. This method is based on the statistical process of Welch's periodogram of the stator currents in order to obtain stable and normalized fault indicators. The principle of the method is to statistically compare the current spectrum to a healthy reference so as to quantify the changes over the time. A statistic-based indicator is then constructed by monitoring specific harmonic family. The proposed method was tested on two experimental test campaigns for four different speeds and compared to a vibration indicator. The method was evaluated using a rigorous performance evaluation metric. A threshold evaluation was performed and shows that the proposed method is very tolerant to the machine speed. Thus, the use of a unique fault threshold whatever the speed can be considered. Results showed excellent agreement as compared with the vibration indicator, with an overall correlation of r=0.74 and only 4% of false alarms. Performance demonstrated by this novel method was superior to those of a classical energy-based indicator in terms of correlation with the vibration indicator and detection stability. Moreover, results also showed a better robustness of the proposed method since good performance can be obtained with the same detection threshold whatever the speed or the measure campaign whereas it needs to be redefined for each case with the classical indicator. This work shows the advantages of a statistic-based approach in order to increase the robustness of bearing fault detection in permanent-magnet synchronous machines.

  10. Fourier and Wavelet Transformations for the Fault Detection of Induction Motor with Stator Current

    Microsoft Academic Search

    Sang-hyuk Lee; Seong-pyo Cheon; Youn Tae Kim; Sungshin Kim

    2006-01-01

    \\u000a In this literature, fault detection of an induction motor is carried out using the information of stator current. After preprocessing\\u000a actual data, Fourier and Wavelet transforms are applied to detect characteristics under the healthy and various faulted conditions.\\u000a The most reliable phase current among 3-phase currents is selected by the fuzzy entropy. Data are trained with a neural network\\u000a system,

  11. Fourier and Wavelet Transformations for the Fault Detection of Induction Motor with Stator Current

    Microsoft Academic Search

    Sang-Hyuk Lee; Seong-Pyo Cheon; Yountae Kim; Sungshin Kim

    \\u000a In this literature, fault detection of an induction motor is carried out using the information of stator current. After preprocessing\\u000a actual data, Fourier and Wavelet transforms are applied to detect characteristics under the healthy and various faulted conditions.\\u000a The most reliable phase current among 3-phase currents is selected by the fuzzy entropy. Data are trained with a neural network\\u000a system,

  12. Study on fault detection for networked control systems with stochastic time-delay

    Microsoft Academic Search

    Zhou Gu; Engang Tian; Chen Peng; Wei Wu

    2010-01-01

    The problem of fault detection scheme for networked control systems with non-ideal QoS (such as network-induced delay, data dropout, error sequence) is addressed in this paper. By assuming integrated index ?k obeys a homogeneous Markovian chain, we develop an augmented Markov Jump Systems (MJSs) model. The observer-based fault detection filter problem is formulated as an H? optimization problem. Using linear

  13. Research on Fault Detection and Diagnosis of Scrolling Chiller with ANN 

    E-print Network

    Zhou, Y.; Zheng, J.; Liu, Z.; Yang, C.; Peng, P.

    2006-01-01

    ICEBO2006, Shenzhen, China Co ntrol Systems for Energy Efficiency and Comfort, Vol. V-5-3 Research on Fault Detection and Diagnosis of Scrolling Chiller with ANN1 Yuli ZHOU Jie ZHENG Zhiju LIU Chaojie YANG Peng PENG... researches on the fault diagnosis of screw chiller. 2 DETECTION MECHANISM The refrigerating cycle of screw chiller is consisted of four thermodynamic cycles which are compression, heat discharging, throttling and heat absorbing. the change of one...

  14. A Qualitive Modeling Approach for Fault Detection and Diagnosis on HVAC Systems 

    E-print Network

    Muller, T.; Rehault, N.; Rist, T.

    2013-01-01

    A QUALITATIVE MODELING APPROACH FOR FAULT DETECTION AND DIAGNOSIS ON HVAC SYSTEMS Thorsten M?ller Nicolas R?hault Fraunhofer Institute for Solar Energy Systems - ISE 79110 Freiburg, Germany Tim Rist ABSTRACT This paper describes... be saved by the practical implementation of automated Fault Detection and Diagnosis (FDD) to support a condition-based maintenance (Katipamula and Brambley 2005). Although big research efforts have been carried out in the last two decades...

  15. Self-Checking Detection and Diagnosis of Transient, Delay, and Crosstalk Faults Affecting Bus Lines

    Microsoft Academic Search

    Cecilia Metra; Michele Favalli

    2000-01-01

    We present a self-checking detection and diagnosis scheme for transient, delay, and crosstalk faults affecting bus lines of synchronous systems. Faults that are likely to result in the connected logic sampling incorrect bus data are on-line detected. The position of the affected line(s) within the considered bus is identified and properly encoded. The proposed scheme is self-checking with respect to

  16. A processor architecture for power automation systems that detect high impedance faults

    E-print Network

    Lada, Henry Francis

    1990-01-01

    A PROCESSOR ARCHITECTURE FOR POWER AUTOMATION SYSTEMS THAT DETECT HIGH IMPEDANCE FAULTS A Thesis by HENRY FRANCIS LADA, JR. Submitted to the Office of Graduate Studies of Texas ASM University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE August 1990 Major Subject: Electrical Engineering A PROCESSOR ARCHITECTURE FOR POWER AUTOMATION SYSTEMS THAT DETECT HIGH IMPEDANCE FAULTS A Thesis by HENRY FRANCIS LADA, JR. Approved as to style and content by: Karan...

  17. Research on Fault Detection and Diagnosis of Scrolling Chiller with ANN

    E-print Network

    Zhou, Y.; Zheng, J.; Liu, Z.; Yang, C.; Peng, P.

    2006-01-01

    ICEBO2006, Shenzhen, China Co ntrol Systems for Energy Efficiency and Comfort, Vol. V-5-3 Research on Fault Detection and Diagnosis of Scrolling Chiller with ANN1 Yuli ZHOU Jie ZHENG Zhiju LIU Chaojie YANG Peng PENG... Co ntrol Systems for Energy Efficiency and Comfort, Vol. V-5-3 [2] Meli Stylianou.Darius Nikanpour. Performance monitoring. Fault detection. and diagnosis of Reciprocating Chillers. ASHARE Transactions.102.1996( ). 615-627 [3] Tuo LIU, Jie...

  18. An adaptive PMU based fault detection\\/location technique for transmission lines. I. Theory and algorithms

    Microsoft Academic Search

    Joe-Air Jiang; Jun-Zhe Yang; Ying-Hong Lin; Chih-Wen Liu; Jih-Chen Ma

    2000-01-01

    An adaptive fault detection\\/location technique based on a phasor measurement unit (PMU) for an EHV\\/UHV transmission line is presented. A fault detection\\/location index in terms of Clarke components of the synchronized voltage and current phasors is derived. The line parameter estimation algorithm is also developed to solve the uncertainty of parameters caused by aging of transmission lines. This paper also

  19. Fault detection system for distribution lines using a DSP for filtering and data manipulation 

    E-print Network

    Schultz, Kevin L

    1991-01-01

    FAULT DETECTION SYSTEM FOR DISTRIBUTION LINES USING A DSP FOR FILTERING AND DATA MANIPULATION A Thesis by Kevin L. Schultz Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE May 1991 Major Subject: Electrical Engineering FAULT DETECTION SYSTEM FOR DISTRIBUTION LINES USING A DSP FOR FILTERING AND DATA MANIPULATION A Thesis by Kevin L. Schultz Approved as to style and content by: Karan...

  20. A hybrid system for fault detection and sensor fusion based on fuzzy clustering and artificial immune systems 

    E-print Network

    Jaradat, Mohammad Abdel Kareem Rasheed

    2007-04-25

    In this study, an efficient new hybrid approach for multiple sensors data fusion and fault detection is presented, addressing the problem with possible multiple faults, which is based on conventional fuzzy soft clustering and artificial immune...

  1. Rotor fault detection system for inverter driven induction motor using currents signal

    Microsoft Academic Search

    N. H. Kim; M. H. Kim; H. A. Toliyat; S. H. Lee; C. H. Choi; W. S. Baik

    2007-01-01

    In this paper, the induction motor rotor fault diagnosis system using current signals which are measured using axis-transformation method is presented. In inverter-fed motor drives unlike line-driven motor drives the stator currents are rich in harmonics and therefore fault diagnosis using stator current is not trivial. The current signals for rotor fault diagnosis need precise and high resolution information, which

  2. Detection of stator winding faults in induction machines using flux and vibration analysis

    NASA Astrophysics Data System (ADS)

    Lamim Filho, P. C. M.; Pederiva, R.; Brito, J. N.

    2014-01-01

    This work aims at presenting the detection and diagnosis of electrical faults in the stator winding of three-phase induction motors using magnetic flux and vibration analysis techniques. A relationship was established between the main electrical faults (inter-turn short circuits and unbalanced voltage supplies) and the signals of magnetic flux and vibration, in order to identify the characteristic frequencies of those faults. The experimental results showed the efficiency of the conjugation of these techniques for detection, diagnosis and monitoring tasks. The results were undoubtedly impressive and can be adapted and used in real predictive maintenance programs in industries.

  3. Sensor Fault Diagnosis Using Principal Component Analysis

    E-print Network

    Sharifi, Mahmoudreza

    2010-07-14

    of sensor faults 3. A stochastic method for the decision process 4. A nonlinear approach to sensor fault diagnosis. In this study, first a geometrical approach to sensor fault detection is proposed. The sensor fault is isolated based on the direction...

  4. Airborne LiDAR detection of postglacial faults and Pulju moraine in Palojärvi, Finnish Lapland

    NASA Astrophysics Data System (ADS)

    Sutinen, Raimo; Hyvönen, Eija; Middleton, Maarit; Ruskeeniemi, Timo

    2014-04-01

    Postglacial faults (PGFs) are indicative of young tectonic activity providing crucial information for nuclear repository studies. Airborne LiDAR (Light Detection And Ranging) data revealed three previously unrecognized late- or postglacial faults in northernmost Finnish Lapland. Under the canopies of mountain birch (Betula pubescens ssp. czerepanovii) we also found clusters of the Pulju moraine, typically found on the ice-divide zone of the former Fennoscandian ice sheet (FIS), to be spatially associated with the fault-scarps. Tilt derivative (TDR) filtered LiDAR data revealed the previously unknown Palojärvi fault that, by the NE-SW orientation parallels with the well documented Lainio-Suijavaara PGF in northern Sweden. This suggests that PGFs are more extensive features than previously recognized. Two inclined diamond drill holes verified the fractured system of the Palojärvi fault and revealed clear signs of postglacial reactivation. Two other previously unrecognized PGFs, the W-E trending Paatsikkajoki fault and the SE-NW trending Kultima fault, differ from the Palojärvi faulting in orientation and possibly also with regard to age. The Pulju moraine, a morphological feature showing transitions from shallow (< 2-m-high) circular/arcuate ridges to sinusoidal/anastomosing esker networks was found to be concentrated within 6 km from the Kultima fault-scarp. We advocate that some of the past seismic events took place under the retreating wet-base ice sheet and the increased pore-water pressure triggered the sediment mass flows and formation of the Pulju moraine-esker landscape.

  5. An expert system for fault detection and diagnosis 

    E-print Network

    Spasojevic, Predrag

    1992-01-01

    . Characteristic PS Parameter Relations During Faults G. Knowledge Acquisition: Interviews H. Experts' Approach I. Event Analysis J. Case Study K. Protection System Operation Analysis L. Conclusion 7 8 10 13 13 16 16 18 24 27 31 32 34 36 41 45.... 42 13 14 DEDIAS Block Diagram . MATLAB to CLIPS Interface 47 58 15 Decision System 60 16 17 18 Event Analysis Rules . Protection System Operation Analysis Rules . One Line Diagram of the Reduced TVA System 61 62 70 19 AG Fault...

  6. Hideen Markov Models and Neural Networks for Fault Detection in Dynamic Systems

    NASA Technical Reports Server (NTRS)

    Smyth, Padhraic

    1994-01-01

    None given. (From conclusion): Neural networks plus Hidden Markov Models(HMM)can provide excellene detection and false alarm rate performance in fault detection applications. Modified models allow for novelty detection. Also covers some key contributions of neural network model, and application status.

  7. On-line diagnosis of incipient faults and cellulose degradation based on artificial intelligence methods

    Microsoft Academic Search

    M. A. Izzularab; G. E. M. Aly; D. A. Mansour

    2004-01-01

    In this paper, a new artificial intelligence technique is proposed to detect incipient faults and cellulose degradation in power transformers using dissolved gas analysis. The proposed technique is based on a combination between neural networks and fuzzy logic theory. Incipient faults diagnosis is based on hydrocarbon gases as an input while cellulose degradation detection is based on carbon monoxide and

  8. Robust fault tolerant control based on sliding mode method for uncertain linear systems with quantization.

    PubMed

    Hao, Li-Ying; Yang, Guang-Hong

    2013-09-01

    This paper is concerned with the problem of robust fault-tolerant compensation control problem for uncertain linear systems subject to both state and input signal quantization. By incorporating novel matrix full-rank factorization technique with sliding surface design successfully, the total failure of certain actuators can be coped with, under a special actuator redundancy assumption. In order to compensate for quantization errors, an adjustment range of quantization sensitivity for a dynamic uniform quantizer is given through the flexible choices of design parameters. Comparing with the existing results, the derived inequality condition leads to the fault tolerance ability stronger and much wider scope of applicability. With a static adjustment policy of quantization sensitivity, an adaptive sliding mode controller is then designed to maintain the sliding mode, where the gain of the nonlinear unit vector term is updated automatically to compensate for the effects of actuator faults, quantization errors, exogenous disturbances and parameter uncertainties without the need for a fault detection and isolation (FDI) mechanism. Finally, the effectiveness of the proposed design method is illustrated via a model of a rocket fairing structural-acoustic. PMID:23701895

  9. A separable method for incorporating imperfect fault-coverage into combinatorial models

    Microsoft Academic Search

    S. V. Amari; J. B. Dugan; R. B. Misra

    1999-01-01

    This paper presents a new method for incorporating imperfect FC (fault coverage) into a combinatorial model. Imperfect FC, the probability that a single malicious fault can thwart automatic recovery mechanisms, is important to accurate reliability assessment of fault-tolerant computer systems. Until recently, it was thought that the consideration of this probability necessitated a Markov model rather than the simpler (and

  10. A Method for Impact Assessment of Faults on the Performance of Field-Oriented Control Drives

    E-print Network

    Liberzon, Daniel

    A Method for Impact Assessment of Faults on the Performance of Field-Oriented Control Drives, the effects of certain component faults on the performance of three-phase inverter-fed induction motors are analyzed under indirect field- oriented control. Simulations of faults in the current sensors, speed

  11. Automatic calibration of a building energy performance model and remote fault detection for continuous commissioning using a global optimization program

    E-print Network

    Lee, Seung Uk

    2002-01-01

    detection result 3-2. . . . . 185 . . . . . 186 . . . . . 187 . . . . . 188 . . . . . 189 X IV Page Table 84. Remote fault detection result 4-1 Table 85. Remote fault detection result 4-2 Table 86. Remote fault detection result 5-1 Table 87... . Figure 2. Simulation model diagram (SDCV system) . . . . . 5 1 Figure 3. Flow diagram for simulation model (SDCV system) computations. . . . . . ?. 52 Figure 4. Typical bin weather bin data for Houston, Texas. . . . 53 Figure 5. Mean coincident...

  12. APPLICATION OF A CAUSAL DIGRAPH BASED FAULT DIAGNOSIS METHOD WITH DISCRETE STATE SPACE MODEL ON A PAPER MACHINE SIMULATOR

    Microsoft Academic Search

    Hui Cheng; Mats Nikus; Sirkka-Liisa Jämsä-Jounela

    The aim of the work presented in this paper is to evaluate the ability of the causal digraph method to detect and isolate faults on a si mulated paper machine process. In order to represent the causal relations between the variable s using discrete state space models, a linearity test was performed for the short circulat ion sub process in

  13. Remote sensing analysis for fault-zones detection in the Central Andean Plateau (Catamarca, Argentina)

    NASA Astrophysics Data System (ADS)

    Traforti, Anna; Massironi, Matteo; Zampieri, Dario; Carli, Cristian

    2015-04-01

    Remote sensing techniques have been extensively used to detect the structural framework of investigated areas, which includes lineaments, fault zones and fracture patterns. The identification of these features is fundamental in exploration geology, as it allows the definition of suitable sites for the exploitation of different resources (e.g. ore mineral, hydrocarbon, geothermal energy and groundwater). Remote sensing techniques, typically adopted in fault identification, have been applied to assess the geological and structural framework of the Laguna Blanca area (26°35'S-66°49'W). This area represents a sector of the south-central Andes localized in the Argentina region of Catamarca, along the south-eastern margin of the Puna plateau. The study area is characterized by a Precambrian low-grade metamorphic basement intruded by Ordovician granitoids. These rocks are unconformably covered by a volcano-sedimentary sequence of Miocene age, followed by volcanic and volcaniclastic rocks of Upper Miocene to Plio-Pleistocene age. All these units are cut by two systems of major faults, locally characterized by 15-20 m wide damage zones. The detection of main tectonic lineaments in the study area was firstly carried out by classical procedures: image sharpening of Landsat 7 ETM+ images, directional filters applied to ASTER images, medium resolution Digital Elevation Models analysis (SRTM and ASTER GDEM) and hill shades interpretation. In addition, a new approach in fault zone identification, based on multispectral satellite images classification, has been tested in the Laguna Blanca area and in other sectors of south-central Andes. In this perspective, several prominent fault zones affecting basement and granitoid rocks have been sampled. The collected fault gouge samples have been analyzed with a Field-Pro spectrophotometer mounted on a goniometer. We acquired bidirectional reflectance spectra, from 0.35?m to 2.5?m with 1nm spectral sampling, of the sampled fault rocks. Subsequently, two different Spectral Angle Mapper (SAM) classifications were applied to ASTER images: the first one based on fault rock spectral signatures resampled at the ASTER sensor resolution; the second one based on spectral signatures retrieved from specific Region of Interest (ROI), which were directly derived from the ASTER image on the analyzed fault zones. The SAM classification based on the spectral signatures of fault rocks gave outstanding results since it was able to classify the analyzed fault zone, both in terms of length and width. Moreover, in some specific cases, this SAM classification identified not only the sampled fault zone, but also other prominent neighboring faults cutting the same host rock. These results define the SAM supervised classification on ASTER images as a tool to identify prominent fault zones directly on the base of fault-rocks spectra.

  14. Rotor fault detection in inverter drive systems using inverter input current analysis

    Microsoft Academic Search

    I. P. Georgakopoulos; E. D. Mitronikas; A. N. Safacas; I. P. Tsoumas

    2010-01-01

    Broken rotor bar\\/ end-ring is a common fault in squirrel cage induction motors and has been thoroughly investigated in the case of AC grid supply. In this paper, this type of fault is studied in case of inverter driven motor. Induction motor is driven using scalar Volts\\/ Hz control method. Motor stator current and inverter input current spectra are studied

  15. Detecting dominant resonant modes of rolling bearing faults using the niching genetic algorithm

    Microsoft Academic Search

    Adam Docekal; Radislav Smid; Marcel Kreidl; Pavel Krpata

    2011-01-01

    In this paper we propose an improvement of methods for adaptive selection of frequency bands containing transients which indicate the presence of the dominant resonant modes of rolling bearing faults using niching genetic algorithm optimization. The main aim of this approach is to diagnose the condition of the bearings and to be able to recognize faults on various parts of

  16. WETLAND DETECTION METHODS INVESTIGATION

    EPA Science Inventory

    The purpose of this investigation was to research and document the application of remote sensing technology for wetlands detection. arious sensors and platforms are evaluated for: suitability to monitor specific wetland systems; effectiveness of detailing wetland extent and capab...

  17. Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors

    PubMed Central

    Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

    2009-01-01

    This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented. PMID:22400008

  18. Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

    PubMed

    Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

    2009-01-01

    This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented. PMID:22400008

  19. Simulation of growth normal fault sandbox tests using the 2D discrete element method

    NASA Astrophysics Data System (ADS)

    Chu, Sheng-Shin; Lin, Ming-Lang; Huang, Wen-Chao; Nien, Wei-Tung; Liu, Huan-Chi; Chan, Pei-Chen

    2015-01-01

    A fault slip can cause the deformation of shallow soil layers and destroy infrastructures. The Shanchiao Fault on the west side of the Taipei Basin is one such fault. The activities of the Shanchiao Fault have caused the quaternary sediment beneath the Taipei Basin to become deformed, damaging structures, traffic construction, and utility lines in the area. Data on geological drilling and dating have been used to determine that a growth fault exists in the Shanchiao Fault. In an experiment, a sandbox model was built using noncohesive sandy soil to simulate the existence of a growth fault in the Shanchiao Fault and forecast the effect of the growth fault on shear-band development and ground differential deformation. The experimental results indicated that when a normal fault contains a growth fault at the offset of the base rock, the shear band develops upward beside the weak side of the shear band of the original-topped soil layer, and surfaces considerably faster than that of the single-topped layer. The offset ratio required is approximately one-third that of the single-cover soil layer. In this study, a numerical simulation of the sandbox experiment was conducted using a discrete element method program, PFC2D, to simulate the upper-covering sand layer shear-band development pace and the scope of a growth normal fault slip. The simulation results indicated an outcome similar to that of the sandbox experiment, which can be applied to the design of construction projects near fault zones.

  20. Electrical properties and detection methods for CMOS IC defects

    Microsoft Academic Search

    Jerry M. Soden; Charles F. Hawkins

    1989-01-01

    CMOS failure modes and mechanisms and the test vector and parametric test requirements for the detection are reviewed. The CMOS stuck-open fault is discussed from a physical viewpoint, with results given from failure analysis of ICs having this failure mode. The results show that among functional, stuck-at, stuck-open, and IDDQ test strategies, no single method guarantees detection of all types

  1. New Time Domain Method for the Detection of Roller Bearing Defects

    Microsoft Academic Search

    Tahsin Doguer; Jens Strackeljan

    2008-01-01

    The main focus of this paper is given to the detection of different fault types in the inner or outer race of roller bearing. The first group covers faults with an extension beyond the spacing between two rolling elements. In these cases some of the classical methods like envelop techniques could fail. We show that the vibration structure generated by

  2. New method of fiber Bragg grating demodulation technique and applied in detection of equipment

    Microsoft Academic Search

    Bing Zhao; Zhi-Li Zhang; Qi-Yuan Zhong; Hongliang Tu; Lilong Tan

    2009-01-01

    Numbers of temperature signal and both dynamic and static strain signal in different places should be detected in fault diagnosis of some equipment system. Fiber Bragg Grating sensor was provided usefully as detection instrument for fault diagnosis of equipment system, but the demodulation technique in existence couldn't satisfy multi-dots and multi-parameters detection of the system. F-P scan method amalgamated non-balance

  3. Performance of diagnosis methods for IGBT open circuit faults in three phase voltage source inverters for AC variable speed drives

    Microsoft Academic Search

    K. Rothenhagen; F. W. Fuchs

    2005-01-01

    Variable speed drives have become industrial standard in many applications. Therefore fault diagnosis of voltage source inverters is becoming more and more important. One possible fault within the inverter is an open circuit transistor fault. An overview of the different strategies to detect this fault is given, including the algorithms used to localize the open transistor. Previous work showed significant

  4. Advanced power system protection and incipient fault detection and protection of spaceborne power systems

    NASA Technical Reports Server (NTRS)

    Russell, B. Don

    1989-01-01

    This research concentrated on the application of advanced signal processing, expert system, and digital technologies for the detection and control of low grade, incipient faults on spaceborne power systems. The researchers have considerable experience in the application of advanced digital technologies and the protection of terrestrial power systems. This experience was used in the current contracts to develop new approaches for protecting the electrical distribution system in spaceborne applications. The project was divided into three distinct areas: (1) investigate the applicability of fault detection algorithms developed for terrestrial power systems to the detection of faults in spaceborne systems; (2) investigate the digital hardware and architectures required to monitor and control spaceborne power systems with full capability to implement new detection and diagnostic algorithms; and (3) develop a real-time expert operating system for implementing diagnostic and protection algorithms. Significant progress has been made in each of the above areas. Several terrestrial fault detection algorithms were modified to better adapt to spaceborne power system environments. Several digital architectures were developed and evaluated in light of the fault detection algorithms.

  5. A New Method for the Computation of Faults on Transmission Lines

    Microsoft Academic Search

    B. R. Oswald; A. Panosyan

    2006-01-01

    A systematic matrix method for modeling short-circuits and interruptions on transmission lines is presented. The method fits perfectly into the calculation method for short-circuits on network buses with the nodal admittance equations, which are also presented here. All types of balanced or unbalanced faults, both in single and multiple constellations are treated systematically with the same method. Each fault is

  6. [Application of optimized parameters SVM based on photoacoustic spectroscopy method in fault diagnosis of power transformer].

    PubMed

    Zhang, Yu-xin; Cheng, Zhi-feng; Xu, Zheng-ping; Bai, Jing

    2015-01-01

    In order to solve the problems such as complex operation, consumption for the carrier gas and long test period in traditional power transformer fault diagnosis approach based on dissolved gas analysis (DGA), this paper proposes a new method which is detecting 5 types of characteristic gas content in transformer oil such as CH4, C2H2, C2H4, C2H6 and H2 based on photoacoustic Spectroscopy and C2H2/C2H4, CH4/H2, C2H4/C2H6 three-ratios data are calculated. The support vector machine model was constructed using cross validation method under five support vector machine functions and four kernel functions, heuristic algorithms were used in parameter optimization for penalty factor c and g, which to establish the best SVM model for the highest fault diagnosis accuracy and the fast computing speed. Particles swarm optimization and genetic algorithm two types of heuristic algorithms were comparative studied in this paper for accuracy and speed in optimization. The simulation result shows that SVM model composed of C-SVC, RBF kernel functions and genetic algorithm obtain 97. 5% accuracy in test sample set and 98. 333 3% accuracy in train sample set, and genetic algorithm was about two times faster than particles swarm optimization in computing speed. The methods described in this paper has many advantages such as simple operation, non-contact measurement, no consumption for the carrier gas, long test period, high stability and sensitivity, the result shows that the methods described in this paper can instead of the traditional transformer fault diagnosis by gas chromatography and meets the actual project needs in transformer fault diagnosis. PMID:25993810

  7. Diagnostic and Detection Fault Collapsing for Multiple Output Circuits Raja K. K. R. Sandireddy and Vishwani D. Agrawal

    E-print Network

    Paris-Sud XI, Université de

    - able. The definitions for fault dominance follow on similar lines. A novel algorithm basedDiagnostic and Detection Fault Collapsing for Multiple Output Circuits Raja K. K. R. Sandireddy, USA sandira@auburn.edu, vagrawal@eng.auburn.edu Abstract We discuss fault equivalence and dominance

  8. A novel selectivity technique for high impedance arcing fault detection in compensated MV networks

    Microsoft Academic Search

    Nagy I. Elkalashy; Matti Lehtonen; Hatem A. Darwish; Abdel-Maksoud I. Taalab; Mohamed A. Izzularab

    2007-01-01

    SUMMARY In this paper, the initial transients due to arc reignitions associated with high impedance faults caused by leaning trees are extracted using discrete wavelet transform (DWT). In this way, the fault occurrence is localized. The feature extraction is carried out for the phase quantities corresponding to a band frequency 12.5-6.25 kHz. The detection security is enhanced because the DWT

  9. An integrated decision, control and fault detection scheme for cooperating unmanned vehicle formations

    Microsoft Academic Search

    N. Lechevin; C. A. Rabbath; M. Shanmugavel; A. Tsourdos; B. A. White

    2008-01-01

    We propose a hierarchical and decentralized scheme for integrated decision, control and fault detection in cooperating unmanned aerial systems flying in formations and operating in adversarial environments. To handle, in a cooperative fashion, events that may adversely affect the outcome of a multi-vehicle mission, events such as actuator faults, body damage, network interruption\\/delays, and vehicle loss, we present a decision-control

  10. Hybrid Fault Detection Technique: A Case Study on Virtex-II Pro's PowerPC 405

    Microsoft Academic Search

    P. Bernardi; L. Sterpone; M. Violante; M. Portela-Garcia

    2006-01-01

    Hardening processor-based systems against transient faults requires new techniques able to combine high fault detection capabilities with the usual design requirements, e.g., reduced design-time, low area overhead, reduced (or null) accessibility to processor internal hardware. This paper proposes the adoption of a hybrid approach, which combines ideas from previous techniques based on software transformations with the introduction of an Infrastructure

  11. A Hardware-Scheduler for Fault Detection in RTOS-Based Embedded Systems

    Microsoft Academic Search

    Jimmy Tarrillo; Leticia Maria Bolzani Pohls; Fabian Vargas

    2009-01-01

    Nowadays, Real-Time Operating Systems (RTOSs) are often adopted in order to simplify the design of safety-critical applications. However, real-time embedded systems are sensitive to transient faults that can affect the system causing scheduling dysfunctions and consequently changing the correct system behavior. In this context, we propose a new hardware-based approach able to detect faults that change the tasks' execution time

  12. An adaptive fault-tolerant event detection scheme for wireless sensor networks.

    PubMed

    Yim, Sung-Jib; Choi, Yoon-Hwa

    2010-01-01

    In this paper, we present an adaptive fault-tolerant event detection scheme for wireless sensor networks. Each sensor node detects an event locally in a distributed manner by using the sensor readings of its neighboring nodes. Confidence levels of sensor nodes are used to dynamically adjust the threshold for decision making, resulting in consistent performance even with increasing number of faulty nodes. In addition, the scheme employs a moving average filter to tolerate most transient faults in sensor readings, reducing the effective fault probability. Only three bits of data are exchanged to reduce the communication overhead in detecting events. Simulation results show that event detection accuracy and false alarm rate are kept very high and low, respectively, even in the case where 50% of the sensor nodes are faulty. PMID:22294929

  13. Integrating Actuator Fault and Wheel Slippage Detections within FDI Framework

    Microsoft Academic Search

    NAIM SIDEK; NILANJAN SARKAR

    We have witnessed a significant advancement in the field of mobile robot applications in the past two decades. From performing mission critical tasks such as in planetary exploration to simply doing household chores, this type of robots requires availability, reliability and safety of its operations. Consequently, there is a growing demand for fault tolerant control system (FTCS) for mobile robots

  14. Permanent Magnets Synchronous Machines Faults Detection and Identification

    E-print Network

    Paris-Sud XI, Université de

    for permanent magnet synchronous machines (PMSM). Two main faults occurring on these machines are identified of the PMSM is devel- oped and simulated using Matlab Simulink. The model enables simulating nominal and faulty PMSM behavior, with several stages of degradation, and is supported by tests results. Specific

  15. Optimal sensor allocation for fault detection and isolation

    Microsoft Academic Search

    Mohammad Azam; Krishna R. Pattipati; Ann Patterson-hine

    2004-01-01

    Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc.) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a

  16. Localized Fault-Tolerant Event Boundary Detection in Sensor Networks

    E-print Network

    Cheng, Xiuzhen "Susan"

    - tion, fault tolerance, faulty sensor identification. I. INTRODUCTION The marriage of Sensor and network to identify the regions containing sensors that behave differently from those in the outside of the regions. In habitat monitoring, sensors in close proximity may have a similar level of residual energy since

  17. Robust Fault Detection and Isolation Using Robust 1 Estimation

    E-print Network

    Collins, Emmanuel

    to that expected on the basis of the model; deviations are indications of a fault (or disturbances, noise disturbances as well as mod- eling uncertainty. Mixed structured singular value and 1 theories are used]T diag(Z), Z Dn [z11, z22, . . . , znn]T Introduction In modern systems such as aircraft and spacecraft

  18. Detection of stator winding faults in induction motors using three-phase current monitoring.

    PubMed

    Sharifi, Rasool; Ebrahimi, Mohammad

    2011-01-01

    The objective of this paper is to propose a new method for the detection of inter-turn short circuits in the stator windings of induction motors. In the previous reported methods, the supply voltage unbalance was the major difficulty, and this was solved mostly based on the sequence component impedance or current which are difficult to implement. Some other methods essentially are included in the offline methods. The proposed method is based on the motor current signature analysis and utilizes three phase current spectra to overcome the mentioned problem. Simulation results indicate that under healthy conditions, the rotor slot harmonics have the same magnitude in three phase currents, while under even 1 turn (0.3%) short circuit condition they differ from each other. Although the magnitude of these harmonics depends on the level of unbalanced voltage, they have the same magnitude in three phases in these conditions. Experiments performed under various load, fault, and supply voltage conditions validate the simulation results and demonstrate the effectiveness of the proposed technique. It is shown that the detection of resistive slight short circuits, without sensitivity to supply voltage unbalance is possible. PMID:21074767

  19. A review of induction motors signature analysis as a medium for faults detection

    Microsoft Academic Search

    Mohamed El Hachemi Benbouzid

    2000-01-01

    This paper is intended as a tutorial overview of induction motors signature analysis as a medium for fault detection. The purpose is to introduce in a concise manner the fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure

  20. Timed Residuals for Fault Detection and Isolation in Discrete Event Systems

    E-print Network

    Paris-Sud XI, Université de

    Timed Residuals for Fault Detection and Isolation in Discrete Event Systems Stefan Schneider detection and isolation in discrete event systems is proposed. An identified model constitutes a timed of a virtual production plant with an external controller. Keywords-Discrete Event System; Timed Automata

  1. The variant cycle-cover problem in fault detection and localization for mesh all-optical networks

    Microsoft Academic Search

    Hongqing Zeng; Alex Vukovic

    2007-01-01

    With the soaring channel speed and density in all-optical networks (AONs), the risk of high data loss upon network faults\\u000a increases quickly. To manage network faults efficiently, an m-cycle based fault detection and localization (MFDL) scheme has been introduced recently. This paper verifies the necessary\\u000a and sufficient condition for achieving the complete fault localization (CFL) in MFDL, which is defined

  2. An intelligent fault identification method of rolling bearings based on LSSVM optimized by improved PSO

    NASA Astrophysics Data System (ADS)

    Xu, Hongbo; Chen, Guohua

    2013-02-01

    This paper presents an intelligent fault identification method of rolling bearings based on least squares support vector machine optimized by improved particle swarm optimization (IPSO-LSSVM). The method adopts a modified PSO algorithm to optimize the parameters of LSSVM, and then the optimized model could be established to identify the different fault patterns of rolling bearings. Firstly, original fault vibration signals are decomposed into some stationary intrinsic mode functions (IMFs) by empirical mode decomposition (EMD) method and the energy feature indexes extraction based on IMF energy entropy is analyzed in detail. Secondly, the extracted energy indexes serve as the fault feature vectors to be input to the IPSO-LSSVM classifier for identifying different fault patterns. Finally, a case study on rolling bearing fault identification demonstrates that the method can effectively enhance identification accuracy and convergence rate.

  3. Test Generation Algorithm for Fault Detection of Analog Circuits Based on Extreme Learning Machine

    PubMed Central

    Zhou, Jingyu; Tian, Shulin; Yang, Chenglin; Ren, Xuelong

    2014-01-01

    This paper proposes a novel test generation algorithm based on extreme learning machine (ELM), and such algorithm is cost-effective and low-risk for analog device under test (DUT). This method uses test patterns derived from the test generation algorithm to stimulate DUT, and then samples output responses of the DUT for fault classification and detection. The novel ELM-based test generation algorithm proposed in this paper contains mainly three aspects of innovation. Firstly, this algorithm saves time efficiently by classifying response space with ELM. Secondly, this algorithm can avoid reduced test precision efficiently in case of reduction of the number of impulse-response samples. Thirdly, a new process of test signal generator and a test structure in test generation algorithm are presented, and both of them are very simple. Finally, the abovementioned improvement and functioning are confirmed in experiments. PMID:25610458

  4. Applications of pattern recognition techniques to online fault detection

    SciTech Connect

    Singer, R.M.; Gross, K.C. [Argonne National Lab., IL (United States); King, R.W. [Argonne National Lab., Idaho Falls, ID (United States)

    1993-11-01

    A common problem to operators of complex industrial systems is the early detection of incipient degradation of sensors and components in order to avoid unplanned outages, to orderly plan for anticipated maintenance activities and to assure continued safe operation. In such systems, there usually are a large number of sensors (upwards of several thousand is not uncommon) serving many functions, ranging from input to control systems, monitoring of safety parameters and component performance limits, system environmental conditions, etc. Although sensors deemed to measure important process conditions are generally alarmed, the alarm set points usually are just high-low limits and the operator`s response to such alarms is based on written procedures and his or her experience and training. In many systems this approach has been successful, but in situations where the cost of a forced outage is high an improved method is needed. In such cases it is desirable, if not necessary, to detect disturbances in either sensors or the process prior to any actual failure that could either shut down the process or challenge any safety system that is present. Recent advances in various artificial intelligence techniques have provided the opportunity to perform such functions of early detection and diagnosis. In this paper, the experience gained through the application of several pattern-recognition techniques to the on-line monitoring and incipient disturbance detection of several coolant pumps and numerous sensors at the Experimental Breeder Reactor-II (EBR-II) which is located at the Idaho National Engineering Laboratory is presented.

  5. Techniques and equipment for detecting and locating incipient faults in underground power transmission cable systems. First technical progress report, 21 August 1978-31 March 1979

    Microsoft Academic Search

    A. C. Phillips; J. E. Nanevicz; R. C. Adamo; C. A. Cole; S. K. Honey; J. P. Petro

    1979-01-01

    This work is to provide practical methods for detecting and locating incipient faults in energized and deenergized underground power transmission cable systems. Radio-frequency probing techniques are emphasized. Supporting tasks include measurements of cable characteristics at manufacturing plants and utility installations, field evaluation, development of signal couplers to access transmission lines, and a study of methods leading to technically effective and

  6. Geophysical imaging of near subsurface layers to detect fault and fractured zones in the Tournemire Experimental Platform, France.

    NASA Astrophysics Data System (ADS)

    Nhu Ba, Elise, Vi; Noble, Mark; Gélis, Céline; Gesret, Alexandrine; Cabrera, Justo

    2013-04-01

    IRSN (the French Institute for Radiological Protection and Nuclear Safety) is in charge of the expertise of the safety report of the French deep geological disposal site project in the East of France. With the goal of understanding the various transport and mechanical properties of clay-rocks, IRSN has conducted several research programs at the Tournemire Experimental Platform (TEP, in the Department of Aveyron in the South of France). Three major sub-horizontal layers characterize the sedimentary Jurassic formations of the TEP. At the base of the stratigraphic column, we find a sequence of limestones and dolomites, that is overlain by an argillaceous formation composed of a 250 m thick clay-rock layer. Above this layer, there is another sequence of limestones and dolomites. The TEP is characterized by a 2 km long tunnel, which allows in situ access to the Toarcian clay- rock layer. In addition to the main Cernon fault, secondary fault zones affect the clay-rock formation and have been observed in the galleries and also identified in several underground boreholes. These sub-vertical fault zones or fracture network display mainly subhorizontal offset (decametric scale) and a small vertical one (meter scale). In the upper limestone, these fault zones widen and fracturing becomes more scattered. In an attempt to detect fault zones in clay-rock layers such as the one described above, IRSN carried out in 2001 a 3D high-resolution seismic survey from the surface in collaboration with CGG. A sub-vertical fault was successfully picked out by the seismic data at the interface between the clay-rock formation and the underlying limestones. This fault is interpreted as the downward continuation of one of the fault zones identified in the tunnel. However, because of the weak seismic impedance contrast in the clay-rock layer and the small vertical offset of sub-vertical fault zones, these fault zones could not be identified in the clay-rock formation. No fault or fracture zone could either be detected in the upper limestone formation because of the acquisition geometry. In order to better image the clay-rock and upper limestone layers, IRSN, Mines ParisTech and UPPA conducted large-scale 2D and 3D very high-resolution seismic surveys in 2010 and 2011 from the surface in the framework of the GNR TRASSE. We analyze this new dataset with the first arrival traveltime tomography method in order to assess its potential to detect fault and fracture zones in near subsurface layers. For this purpose, we develop a new fast inversion algorithm that allows introducing a priori information and choosing a specific model parameterization. We validate our approach based on the Simultaneous Iterative Reconstruction Technique with synthetic data and present the first results of the new real dataset processing. We finally compare these results to a 2D high-resolution electrical resistivity profile acquired at the same location. These electrical resistivity data could also be considered as some a priori information in our inversion scheme.

  7. Statistical Fault Detection for Parallel Applications with AutomaDeD

    SciTech Connect

    Bronevetsky, G; Laguna, I; Bagchi, S; de Supinski, B R; Ahn, D; Schulz, M

    2010-03-23

    Today's largest systems have over 100,000 cores, with million-core systems expected over the next few years. The large component count means that these systems fail frequently and often in very complex ways, making them difficult to use and maintain. While prior work on fault detection and diagnosis has focused on faults that significantly reduce system functionality, the wide variety of failure modes in modern systems makes them likely to fail in complex ways that impair system performance but are difficult to detect and diagnose. This paper presents AutomaDeD, a statistical tool that models the timing behavior of each application task and tracks its behavior to identify any abnormalities. If any are observed, AutomaDeD can immediately detect them and report to the system administrator the task where the problem began. This identification of the fault's initial manifestation can provide administrators with valuable insight into the fault's root causes, making it significantly easier and cheaper for them to understand and repair it. Our experimental evaluation shows that AutomaDeD detects a wide range of faults immediately after they occur 80% of the time, with a low false-positive rate. Further, it identifies weaknesses of the current approach that motivate future research.

  8. SOM Neural Network Fault Diagnosis Method of Polymerization Kettle Equipment Optimized by Improved PSO Algorithm

    PubMed Central

    Wang, Jie-sheng; Li, Shu-xia; Gao, Jie

    2014-01-01

    For meeting the real-time fault diagnosis and the optimization monitoring requirements of the polymerization kettle in the polyvinyl chloride resin (PVC) production process, a fault diagnosis strategy based on the self-organizing map (SOM) neural network is proposed. Firstly, a mapping between the polymerization process data and the fault pattern is established by analyzing the production technology of polymerization kettle equipment. The particle swarm optimization (PSO) algorithm with a new dynamical adjustment method of inertial weights is adopted to optimize the structural parameters of SOM neural network. The fault pattern classification of the polymerization kettle equipment is to realize the nonlinear mapping from symptom set to fault set according to the given symptom set. Finally, the simulation experiments of fault diagnosis are conducted by combining with the industrial on-site historical data of the polymerization kettle and the simulation results show that the proposed PSO-SOM fault diagnosis strategy is effective. PMID:25152929

  9. A method for generating volumetric fault zone grids for pillar gridded reservoir models

    NASA Astrophysics Data System (ADS)

    Qu, Dongfang; Røe, Per; Tveranger, Jan

    2015-08-01

    The internal structure and petrophysical property distribution of fault zones are commonly exceedingly complex compared to the surrounding host rock from which they are derived. This in turn produces highly complex fluid flow patterns which affect petroleum migration and trapping as well as reservoir behavior during production and injection. Detailed rendering and forecasting of fluid flow inside fault zones require high-resolution, explicit models of fault zone structure and properties. A fundamental requirement for achieving this is the ability to create volumetric grids in which modeling of fault zone structures and properties can be performed. Answering this need, a method for generating volumetric fault zone grids which can be seamlessly integrated into existing standard reservoir modeling tools is presented. The algorithm has been tested on a wide range of fault configurations of varying complexity, providing flexible modeling grids which in turn can be populated with fault zone structures and properties.

  10. SOM neural network fault diagnosis method of polymerization kettle equipment optimized by improved PSO algorithm.

    PubMed

    Wang, Jie-sheng; Li, Shu-xia; Gao, Jie

    2014-01-01

    For meeting the real-time fault diagnosis and the optimization monitoring requirements of the polymerization kettle in the polyvinyl chloride resin (PVC) production process, a fault diagnosis strategy based on the self-organizing map (SOM) neural network is proposed. Firstly, a mapping between the polymerization process data and the fault pattern is established by analyzing the production technology of polymerization kettle equipment. The particle swarm optimization (PSO) algorithm with a new dynamical adjustment method of inertial weights is adopted to optimize the structural parameters of SOM neural network. The fault pattern classification of the polymerization kettle equipment is to realize the nonlinear mapping from symptom set to fault set according to the given symptom set. Finally, the simulation experiments of fault diagnosis are conducted by combining with the industrial on-site historical data of the polymerization kettle and the simulation results show that the proposed PSO-SOM fault diagnosis strategy is effective. PMID:25152929

  11. A universal, fault-tolerant, non-linear analytic network for modeling and fault detection

    SciTech Connect

    Mott, J.E. (Advanced Modeling Techniques Corp., Idaho Falls, ID (United States)); King, R.W.; Monson, L.R.; Olson, D.L.; Staffon, J.D. (Argonne National Lab., Idaho Falls, ID (United States))

    1992-03-06

    The similarities and differences of a universal network to normal neural networks are outlined. The description and application of a universal network is discussed by showing how a simple linear system is modeled by normal techniques and by universal network techniques. A full implementation of the universal network as universal process modeling software on a dedicated computer system at EBR-II is described and example results are presented. It is concluded that the universal network provides different feature recognition capabilities than a neural network and that the universal network can provide extremely fast, accurate, and fault-tolerant estimation, validation, and replacement of signals in a real system.

  12. Nucleic Acid Detection Methods

    Microsoft Academic Search

    Cassandra L. Smith; Ron Yaar; Przemyslaw Szafranski; Charles R. Cantor

    1998-01-01

    The invention relates to methods for rapidly determining the sequence and\\/or length a target sequence. The target sequence may be a series of known or unknown repeat sequences which are hybridized to an array of probes. The hybridized array is digested with a single-strand nuclease and free 3'-hydroxyl groups extended with a nucleic acid polymerase. Nuclease cleaved heteroduplexes can be

  13. Nucleic acid detection methods

    Microsoft Academic Search

    C. L. Smith; R. Yaar; P. Szafranski; C. R. Cantor

    1998-01-01

    The invention relates to methods for rapidly determining the sequence and\\/or length a target sequence. The target sequence may be a series of known or unknown repeat sequences which are hybridized to an array of probes. The hybridized array is digested with a single-strand nuclease and free 3â²-hydroxyl groups extended with a nucleic acid polymerase. Nuclease cleaved heteroduplexes can be

  14. Abstract-A fault detection and reconfiguration technique for a cascaded H-bridge 11-level inverter drives during faulty condition

    E-print Network

    Tolbert, Leon M.

    Abstract-A fault detection and reconfiguration technique for a cascaded H-bridge 11-level inverter can be used as a diagnostic signal to detect faults and their locations. AI-based techniques are used to perform the fault classification. A neural network (NN) classification is applied to the fault diagnosis

  15. Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks

    PubMed Central

    Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

    2011-01-01

    Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate. PMID:22163789

  16. Fault diagnosis for a hydraulic drive system using a parameter-estimation method

    Microsoft Academic Search

    D. Yu

    1997-01-01

    Fault diagnosis using a parameter-estimation method is investigated in this paper. A digital state variable filter is employed to obtain derivatives of the variables, and an interpolation technique is used to approximate the values of the variables between samples. The method is applied to a hydraulic test rig based on real data, and the simulated faults — changes in the

  17. A New Assessment Method for System Reliability Based on Dynamic Fault Tree

    Microsoft Academic Search

    Duan Rongxing; Wan Guochun; Dong Decun

    2010-01-01

    According to the deficiency of traditional Markov chain approach in dynamic fault tree analysis, a new modular method for system reliability analysis is proposed. This paper focuses on dividing the fault tree of system into independent subtrees using a linear-time algorithm, and the processing method for different subtrees: Binary decision diagram solution for static subtrees and Bayesian Network solution for

  18. Method for detecting an element

    DOEpatents

    Blackwood, Larry G.; Reber, Edward L.; Rohde, Kenneth W.

    2007-02-06

    A method for detecting an element is disclosed and which includes the steps of providing a gamma-ray spectrum which depicts, at least in part, a test region having boundaries, and which has a small amount of the element to be detected; providing a calculation which detects the small amount of the element to be detected; and providing a moving window and performing the calculation within the moving window, and over a range of possible window boundaries within the test region to determine the location of the optimal test region within the gamma-ray spectrum.

  19. Combined expert system/neural networks method for process fault diagnosis

    DOEpatents

    Reifman, J.; Wei, T.Y.C.

    1995-08-15

    A two-level hierarchical approach for process fault diagnosis of an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach. 9 figs.

  20. To err is robotic, to tolerate immunological: fault detection in multirobot systems.

    PubMed

    Tarapore, Danesh; Lima, Pedro U; Carneiro, Jorge; Christensen, Anders Lyhne

    2015-01-01

    Fault detection and fault tolerance represent two of the most important and largely unsolved issues in the field of multirobot systems (MRS). Efficient, long-term operation requires an accurate, timely detection, and accommodation of abnormally behaving robots. Most existing approaches to fault-tolerance prescribe a characterization of normal robot behaviours, and train a model to recognize these behaviours. Behaviours unrecognized by the model are consequently labelled abnormal or faulty. MRS employing these models do not transition well to scenarios involving temporal variations in behaviour (e.g., online learning of new behaviours, or in response to environment perturbations). The vertebrate immune system is a complex distributed system capable of learning to tolerate the organism's tissues even when they change during puberty or metamorphosis, and to mount specific responses to invading pathogens, all without the need of a genetically hardwired characterization of normality. We present a generic abnormality detection approach based on a model of the adaptive immune system, and evaluate the approach in a swarm of robots. Our results reveal the robust detection of abnormal robots simulating common electro-mechanical and software faults, irrespective of temporal changes in swarm behaviour. Abnormality detection is shown to be scalable in terms of the number of robots in the swarm, and in terms of the size of the behaviour classification space. PMID:25642825

  1. Gear Fault Detection Effectiveness as Applied to Tooth Surface Pitting Fatigue Damage

    NASA Technical Reports Server (NTRS)

    Lewicki, David G.; Dempsey, Paula J.; Heath, Gregory F.; Shanthakumaran, Perumal

    2009-01-01

    A study was performed to evaluate fault detection effectiveness as applied to gear tooth pitting fatigue damage. Vibration and oil-debris monitoring (ODM) data were gathered from 24 sets of spur pinion and face gears run during a previous endurance evaluation study. Three common condition indicators (RMS, FM4, and NA4) were deduced from the time-averaged vibration data and used with the ODM to evaluate their performance for gear fault detection. The NA4 parameter showed to be a very good condition indicator for the detection of gear tooth surface pitting failures. The FM4 and RMS parameters performed average to below average in detection of gear tooth surface pitting failures. The ODM sensor was successful in detecting a significant amount of debris from all the gear tooth pitting fatigue failures. Excluding outliers, the average cumulative mass at the end of a test was 40 mg.

  2. A fault detection, isolation and reconstruction strategy for a satellite's attitude control subsystem with redundant reaction wheels

    Microsoft Academic Search

    Tao Jiang; Khashayar Khorasani

    2007-01-01

    In time-critical systems such as spacecraft systems, fault detection and isolation requirements are of paramount importance and necessity. This paper uses a second order nonlinear sliding mode observer to detect actuator faults in the attitude control subsystem of a satellite with four reaction wheels in a tetrahedron configuration. Through a postprocessing of residual signals it is shown how to isolate

  3. Integrated model-based and data-driven fault detection and diagnosis approach for an automotive electric power steering system

    Microsoft Academic Search

    Rajeev Ghimire; Chaitanya Sankavaram; Alireza Ghahari; Krishna Pattipati; Youssef Ghoneim; Mark Howell; Mutasim Salman

    2011-01-01

    Integrity of electric power steering system is vital to vehicle handling and driving performance. Advances in electric power steering (EPS) system have increased complexity in detecting and isolating faults. In this paper, we propose a hybrid model-based and data-driven approach to fault detection and diagnosis (FDD) in an EPS system. We develop a physics- based model of an EPS system,

  4. Fault detection and isolation in aircraft gas turbine engines. Part 2: validation on a simulation test bed

    E-print Network

    Ray, Asok

    319 Fault detection and isolation in aircraft gas turbine engines. Part 2: validation of fault detection and isolation (FDI) in aircraft gas turbine engines. The FDI algorithms are built upon,onasimulationtestbed.Thetestbedisbuiltuponanintegratedmodelofageneric two-spool turbofan aircraft gas turbine engine including the engine control system. Keywords: aircraft

  5. A robust model-based information system for monitoring and fault detection of large scale belt conveyor systems

    Microsoft Academic Search

    T. Jeinsch; M. Sader; R. Noack; K. Barber; S. X. Ding; P. Zang; M. Zhong

    2002-01-01

    In this paper an information system is presented, which is developed to meet the requirements on fault detection and online monitoring of large scale belt conveyor systems. The core of this information system consists of a mathematical model, observer and fault detection system.

  6. Multi-fault detection of rolling element bearings under harsh working condition using IMF-based adaptive envelope order analysis.

    PubMed

    Zhao, Ming; Lin, Jing; Xu, Xiaoqiang; Li, Xuejun

    2014-01-01

    When operating under harsh condition (e.g., time-varying speed and load, large shocks), the vibration signals of rolling element bearings are always manifested as low signal noise ratio, non-stationary statistical parameters, which cause difficulties for current diagnostic methods. As such, an IMF-based adaptive envelope order analysis (IMF-AEOA) is proposed for bearing fault detection under such conditions. This approach is established through combining the ensemble empirical mode decomposition (EEMD), envelope order tracking and fault sensitive analysis. In this scheme, EEMD provides an effective way to adaptively decompose the raw vibration signal into IMFs with different frequency bands. The envelope order tracking is further employed to transform the envelope of each IMF to angular domain to eliminate the spectral smearing induced by speed variation, which makes the bearing characteristic frequencies more clear and discernible in the envelope order spectrum. Finally, a fault sensitive matrix is established to select the optimal IMF containing the richest diagnostic information for final decision making. The effectiveness of IMF-AEOA is validated by simulated signal and experimental data from locomotive bearings. The result shows that IMF-AEOA could accurately identify both single and multiple faults of bearing even under time-varying rotating speed and large extraneous shocks. PMID:25353982

  7. Induction Motors Bearing Failures Detection and Diagnosis Using a RBF ANN Park Pattern Based Method

    E-print Network

    Paris-Sud XI, Université de

    Induction Motors Bearing Failures Detection and Diagnosis Using a RBF ANN Park Pattern Based Method of bearing failure detection and diagnosis in induction motors. The proposed approach is a sensor to automate the fault detection and diagnosis process. Experimental tests with artificial bearing damages

  8. Recursion method for electron and phonon spectra of Si with stacking faults

    Microsoft Academic Search

    Zheng Zhao-bo; Lee Jin-ling

    1986-01-01

    The authors have calculated the local densities of states of the electron and phonon spectra of Si with stacking faults by the recursion method. The stacking fault energy and the width in which the local densities of states are changed by the stacking fault are calculated to be 48 mJ m-2 and 17.94 AA respectively, in good agreement with the

  9. Detecting dominant resonant modes of rolling bearing faults using the niching genetic algorithm

    NASA Astrophysics Data System (ADS)

    Docekal, Adam; Smid, Radislav; Kreidl, Marcel; Krpata, Pavel

    2011-10-01

    In this paper we propose an improvement of methods for adaptive selection of frequency bands containing transients which indicate the presence of the dominant resonant modes of rolling bearing faults using niching genetic algorithm optimization. The main aim of this approach is to diagnose the condition of the bearings and to be able to recognize faults on various parts of bearings and possible combinations of faults. Because the vibration signals corresponding to faults on bearings are typically transients with a wide frequency range occurring around the excited mechanical resonant modes and drowned in the acquired vibration signals, it is necessary to emphasize these excited transients using a matched bank of filters. The dominant resonant modes of a bearing and the system modes produced from fault source are usually unknown, and so there is a need for robust global search methods able to deal with non-linear problems with multiple optima. Instead of applying an optimization method repeatedly for every optimum, non-dominated extensions of the genetic algorithm can be applied only one time to find and maintain multiple optimal solutions. The efficiency of the proposed approach - niching genetic algorithm with fitness sharing - was evaluated using vibration signals acquired on four tapered roller bearings with defined combinations of seeded faults.

  10. Power transformer multi-parameter fault fusion diagnosis method

    Microsoft Academic Search

    Lin Du; Lei Yuan; Youyuan Wang

    2010-01-01

    The fault diagnosis for large oil-immersed power transformer is generally carried out through preventive test data. However, the preventive test data must be obtained until power-off time, and the amounts and accuracy of the field data is limited. When a fault occurs in the running time, it always accompanies by the variations of the appearance such as color, sound, temperature

  11. Travelling wave fault location in power transmission lines using statistic data analysis methods

    NASA Astrophysics Data System (ADS)

    Lachugin, V. F.; Panfilov, D. I.; Smirnov, A. N.

    2014-12-01

    A method used for determination of the distance to the location of a fault in a power transmission line is considered. The method is based on separation of traveling waves upon a short circuit and use of statistic analysis methods for determination of the wave front. The efficiency of the proposed method is verified using a mathematical model of a power transmission line. The results of testing the devices for implementation of the proposed method for fault location are cited.

  12. Ability of High-Resolution Resistivity Tomography to Detect Fault and Fracture Zones: Application to the Tournemire Experimental Platform, France

    NASA Astrophysics Data System (ADS)

    Gélis, C.; Noble, M.; Cabrera, J.; Penz, S.; Chauris, H.; Cushing, E. M.

    2015-05-01

    The Experimental Platform of Tournemire (Aveyron, France) developed by IRSN (French Institute for Radiological Protection and Nuclear Safety) is composed of a tunnel excavated in an argillite formation belonging to a limestone-argillite-limestone subhorizontal sedimentary sequence. Subvertical secondary fault zones were intercepted in argillite using drifts and boreholes in the tunnel excavated at a depth of about 250 m located under the Larzac Plateau. A 2D 2.5 km baseline large-scale electrical resistivity survey conducted in 2007 allowed detecting in the upper limestones several significantly low electrical resistivity subvertical zones (Guc(élis) et al. Appl Geophys 167(11): 1405-1418, 2010). One of these discontinuities is consistent with the extension towards the surface of the secondary fault zones identified in the argillite formation from the tunnel. In an attempt to better characterize this zone, IRSN and MINES ParisTech conducted a high-resolution electrical resistivity survey located transversally to the fault and fracture zones. A 760-m-long profile was acquired using two array geometries and take-outs of 2, 4 and 8 m, requiring several roll-alongs. These data were first inverted independently for each take-out and then using all take-outs together for a given array geometry. Different inverted 2D electrical resistivity models display the same global features with high (higher than 5000 ?m) to low (lower than 100 ?m) electrical resistivity zones. These electrical resistivity models are finally compared with a geological cross-section based on independent data. The subvertical conductive zones are in agreement with the fault and fracture locations inferred from the geological cross-section. Moreover, the top of a more conductive zone, below a high electrical conductive zone and between two subvertical fault zones, is located in a more sandy and argillaceous layer. This conductive zone is interpreted as the presence of a more scattered fracture zone located at depth between two fault zones. This zone could be correlated with the fractured zones identified at 250-m depth in underground works. This study highlights the interest of multi-scale approaches to image complex heterogeneous near subsurface layers. Finally, this study shows that the electrical resistivity tomography is a useful and powerful tool to detect fault and fracture zones in upper limestones. Such a method is complementary to other geophysical and geological data.

  13. Mechanical fault detection in a medium-sized induction motor using stator current monitoring

    Microsoft Academic Search

    Andrew M. Knight; Sergio P. Bertani

    2005-01-01

    This paper presents the results of an experimental study of the detection of mechanical faults in an induction motor. As is reasonably well known, by means of analysis of combinations of permeance and magneto-motive force (MMF) harmonics, it is possible to predict the frequency of air gap flux density harmonics which occur as a result of certain irregularities in an

  14. Broadband RF process-state sensor for fault detection and classification

    Microsoft Academic Search

    Francisco Martinez; Paul Scullin; John Scanlan

    2005-01-01

    In this paper, we present a novel broadband radio frequency (RF) sensor technology, which can be used for plasma process control, including Fault Detection and Classification (FDC). Plasma is a non-linear complex electrical load, therefore generates harmonics of the driving frequency in the electrical circuit. Plasma etch processes have dependencies on chamber pressure, delivered power, wall and substrate temperatures, gas

  15. Artificial neural networks and support vector machines with genetic algorithm for bearing fault detection

    Microsoft Academic Search

    B. Samanta; K. R. Al-Balushi; S. A. Al-Araimi

    2003-01-01

    A study is presented to compare the performance of bearing fault detection using two different classifiers, namely, artificial neural networks (ANNs) and support vector machines (SMVs). The time-domain vibration signals of a rotating machine with normal and defective bearings are processed for feature extraction. The extracted features from original and preprocessed signals are used as inputs to the classifiers for

  16. Gear fault detection using artificial neural networks and support vector machines with genetic algorithms

    Microsoft Academic Search

    B. Samanta

    2004-01-01

    A study is presented to compare the performance of gear fault detection using artificial neural networks (ANNs) and support vector machines (SMVs). The time-domain vibration signals of a rotating machine with normal and defective gears are processed for feature extraction. The extracted features from original and preprocessed signals are used as inputs to both classifiers based on ANNs and SVMs

  17. Fault Detection, Isolation and Control Reconfiguration of Three-Phase PMSM Drives

    E-print Network

    Paris-Sud XI, Université de

    Fault Detection, Isolation and Control Reconfiguration of Three-Phase PMSM Drives Fabien Meinguet purposes and for transport appli- cations [1], [2]. Although permanent magnet synchronous ma- chines (PMSM. Considering PMSM drives, the neutral accessibility may be an issue since most of the commercial PMSMs have

  18. Fault detection and isolation filter design for linear parameter varying systems

    Microsoft Academic Search

    M. O. Abdalla; E. G. Nobrega; K. M. Grigoriadis

    2001-01-01

    An ℋ? approach to design a fault detection and isolation gain scheduled filter for linear parameter varying (LPV) systems is presented in this paper. The system matrices are assumed to depend affinely on real-time measured varying parameters. Solvability conditions are derived using the quadratic ℋ? performance; these conditions result in convex linear matrix inequalities (LMIs) that can be solved efficiently

  19. Novel surface wave exciters for power line fault detection and communications

    Microsoft Academic Search

    M. N. Alam; R. H. Bhuiyan; R. Dougal; M. Ali

    2011-01-01

    A novel conformal surface wave (CSW) exciter is introduced which can excite electromagnetic (EM) surface waves along unshielded power line cables non-intrusively. The CSW exciter is small, cost effective and can be easily placed on a power cable compared to conventional monopole type launchers or horn type launchers. Besides cable fault detection, the potential applications of the proposed exciter include

  20. Fault detection monitor circuit provides ''self-heal capability'' in electronic modules - A concept

    NASA Technical Reports Server (NTRS)

    Kennedy, J. J.

    1970-01-01

    Self-checking technique detects defective solid state modules used in electronic test and checkout instrumentation. A ten bit register provides failure monitor and indication for 1023 comparator circuits, and the automatic fault-isolation capability permits the electronic subsystems to be repaired by replacing the defective module.

  1. A distributed approach for fault detection and diagnosis based on Time Petri Nets

    Microsoft Academic Search

    George Jiroveanu; René K. Boel

    2006-01-01

    This paper proposes an algorithm for the model based design of a distributed protocol for fault detection and diagnosis for very large systems. The overall process is modeled as different Time Petri Net (TPN) models (each one modeling a local process) that interact with each other via guarded transitions that becomes enabled only when certain conditions (expressed as predicates over

  2. Particle Filters for Real-Time Fault Detection in Planetary Rovers

    Microsoft Academic Search

    Richard Dearden; Dan Clancy

    2002-01-01

    Planetary rovers provide a considerable challenge for robotic systems in that they must operate for long periods autonomously, or with relatively little intervention. To achieve this, they need to have on-board fault detection and diagnosis capabilities in order to determine the actual state of the vehicle, and decide what actions are safe to perform. Traditional model-based diagnosis techniques are not

  3. Non-Stationary Spectral Estimation for Wind Turbine Induction Generator Faults Detection

    E-print Network

    Paris-Sud XI, Université de

    to detect and diagnose the generator faults from vibration, acoustic, or generator current signals technologies for wind turbine condition mon- itoring require additional sensors and data acquisition devices to be implemented [5]. The use of these sensors and devices increases cost, size, and hardware wiring complexity

  4. High impedance fault detection in EHV series compensated lines using the wavelet transform

    Microsoft Academic Search

    E. S. T. Eldin; D. k. Ibrahim; E. M. Aboul-Zahab; S. M. Saleh

    2009-01-01

    Coupling capacitive voltage transformers behave as low pass filters which reject the high frequencies associated with voltage signals, so the effect of HIF on voltage signals is neglected. In addition, using series capacitors (SCs) equipped with metal oxide varistors (MOVs) increases the protection relaying problems and complicates the trip decision. This paper presents a high impedance fault detection algorithm for

  5. Unknown Inputs Observers Design for Fault Detection in a Two-Tank Hydraulic System

    Microsoft Academic Search

    J. Anzurez-Marin; N. Pitalua-Diaz; O. Cuevas-Silva; J. Villar-Garcia

    2008-01-01

    A technique for design of unknown inputs observers is presented, applied to the solution of fault detection problem. The proposed technique is mainly based on observation of error signals known as residuals, which are obtained by taking away actual input from estimated input. An unknown inputs observer has the estimation error vector in asymptomatic cero tendency as its special feature,

  6. Power efficiency estimation based health monitoring and fault detection of modular and reconfigurable robot

    Microsoft Academic Search

    Jing Yuan; Guangjun Liu; Bin Wu

    2008-01-01

    Power efficiency degradation of machines often provides intrinsic indication of problems associated with their operation conditions. Inspired by this observation, in this paper, a simple yet effective power efficiency estimation based health monitoring and fault detection technique is proposed for modular and reconfigurable robot with joint torque sensor. Power efficiency coefficients of each joint module are obtained using sensor measurements

  7. Power Efficiency Estimation-Based Health Monitoring and Fault Detection of Modular and Reconfigurable Robot

    Microsoft Academic Search

    Jing Yuan; Guangjun Liu; Bin Wu

    2011-01-01

    The power efficiency degradation of machines often provides intrinsic indication of problems associated with their operation health conditions. Inspired by this observation, as presented in this paper, a simple yet effective power efficiency estimation-based health monitoring and fault detection technique is developed for a modular and reconfigurable robot (MRR) with a joint torque sensor. Power efficiency coefficients of each joint

  8. Detection and Classification of Rolling-Element Bearing Faults using Support Vector Machines

    Microsoft Academic Search

    Alfonso Rojas; Asoke K Nandi

    2005-01-01

    This paper proposes development of support vector machines (SVMs) for detection and classification of rolling-element bearing faults. The training of the SVMs is carried out using the sequential minimal optimization (SMO) algorithm. In this paper, a mechanism for selecting adequate training parameters is proposed. This proposal makes the classification procedure fast and effective. Various scenarios are examined using two sets

  9. A weighted multi-scale morphological gradient filter for rolling element bearing fault detection

    Microsoft Academic Search

    Bing Li; Pei-lin Zhang; Zheng-jun Wang; Shuang-shan Mi; Dong-sheng Liu

    2011-01-01

    This paper presents a novel signal processing scheme, named the weighted multi-scale morphological gradient filter (WMMG), for rolling element bearing fault detection. The WMMG can depress the noise at large scale and preserve the impulsive shape details at small scale. Both a simulated signal and vibration signals from a bearing test rig are employed to evaluate the performance of the

  10. Faults Detection Using Gaussian Mixture Models, Mel-Frequency Cepstral Coefficients and Kurtosis

    Microsoft Academic Search

    Fulufhelo V. Nelwamondo; T. Marwala

    2006-01-01

    Most machines failures can be associated with mechanical failures on bearing failures. This paper proposes a novel approach to detect and classify three types of common faults in rolling element bearings. The approach proposed here makes use Gaussian mixture model to classify, Mel-frequency cepstral coefficients (MFCC) and kurtosis are extracted from the bearing vibration signal and are used as features.

  11. Sensor Analysis for Fault Detection in Tightly-Coupled Multi-Robot Team Tasks

    E-print Network

    Parker, Lynne E.

    transitions from a history of sensor data during the normal operational mode of the robot. Faults are then identified online via a deviation of the sensor data from the model of normal operation. Our approach detection approach (which we call SAFDetection) that is used to monitor tightly-coupled multi-robot team

  12. Induction Machine Broken Bars Fault Detection Using Stray Flux after Supply Disconnection

    Microsoft Academic Search

    Shahin Hedayati Kia; Humberto Henao; Gérard-André Capolino; C. Martis

    2006-01-01

    The aim of this paper is to present a new approach to detect broken bars fault in squirrel-cage induction machine. This approach is based on the study of stray flux signal after the supply disconnection. This type of test is useful especially for the maintenance purpose when it is possible to remove the load and supply effects. In this case,

  13. On-line scheduling and fault detection in NCS with communication constraints in Drone application

    Microsoft Academic Search

    H. H. Nejad; Dominique Sauter; Samir Aberkane

    2010-01-01

    This paper considers the fault detection problem of mini-helicopter (Drone) where sensing and actuation signals are exchanged among various parts of the system via communication networks. For reducing the network load and thus minimizing the uncertainty caused by transmission delay or packet dropout, instead of transmitting all measurements of velocity sensors at each sampling time, only one velocity sensor can

  14. Combined wavelet transfoms and neural network (WNN) based fault detection and classification in transmission lines

    Microsoft Academic Search

    M. Geethanjali; K. S. Priya

    2009-01-01

    Transmission line protection is an important issue in power system engineering because 85-87% of power system faults are occurring in transmission lines. This project work presents a technique to detect and classify the different operating conditions in transmission lines to contribute quick and reliable operation of protection schemes. Discrimination among different transient conditions of transmission lines is achieved by combining

  15. Fast detection of data retention faults and other SRAM cell open defects

    Microsoft Academic Search

    Josh Yang; Baosheng Wang; Yuejian Wu; André Ivanov

    2006-01-01

    Detection of open defects in static random access memory (SRAM) cells, including those causing data retention faults (DRFs), is known to be difficult and time consuming. This paper proposes a novel design-for-test (DFT) technique that allows SRAMs to be tested at full speed for these defects. As a result, it achieves not only significant test time reduction but also full

  16. Measurement of neutral currents in a power transformer and fault detection using wavelet techniques

    Microsoft Academic Search

    A. Bhoomaiah; P. Krishna Reddyl; K. S. Linga Murthyl; P. Appla Naidu; B. P. Singh

    2004-01-01

    Fault analysis and diagnosis of a transformer are essential, as power quality is one of the primary concerns of the electric power utilities. Insulation failure within transformer windings is considered to be one of the most important causes of the failure of power transformers. A comparison of neutral currents at reduced and full voltages is carried out for detection of

  17. Automatic Fault Detection and Recovery in Real Time Switched Ethernet Networks

    E-print Network

    Chiueh, Tzi-cker

    on the prototype show that the fault detection and recovery time on a network whose diameter is 10 hops are 220ms for an end­to­end resource guarantees. A connection­oriented mechanism is needed to deliver hard resource to deliver the guarantee. Our EtheReal[11] architecture provides a transparent connection­oriented mechanism

  18. Kalman Filter Innovation Sequence Based Fault Detection in LEO Satellite Attitude Determination and Control System

    Microsoft Academic Search

    A. Okatan; Ch. Hajiyev; U. Hajiyeva

    2007-01-01

    In this paper, fault detection algorithm for LEO satellite attitude determination and control system using an approach for checking the statistical characteristics of Extended Kalman filter (EKF) innovation sequence is proposed. It is based on given statistics for the mathematical expectation of the spectral norm of the normalized innovation matrix of the EKF. The attitude dynamics of the LEO satellite

  19. Fault detection and isolation for an experimental internal combustion engine via fuzzy identification

    Microsoft Academic Search

    E. G. Laukonen; K. M. Passino; V. Krishnaswami; G.-C. Luh; G. Rizzoni

    1995-01-01

    Certain engine faults can be detected and isolated by examining the pattern of deviations of engine signals from their nominal unfailed values. In this brief paper, we show how to construct a fuzzy identifier to estimate the engine signals necessary to calculate the deviation from nominal engine behavior, so that we may determine if the engine has certain actuator and

  20. Comparison of Centralized MultiSensor Measurement and State Fusion Methods with an Adaptive Unscented Kalman Filter for Process Fault diagnosis

    Microsoft Academic Search

    Mohsen Mosallaei; Karim Salahshoor

    2008-01-01

    This paper investigates the application of centralized multi-sensor data fusion (CMSDF) technique to enhance the process fault detection. Adaptive Unscented Kalman Filter (AUKF) is used to estimate the process faults of the simulated continuous stirred tank reactor (CSTR) benchmark. Currently there exist two commonly used centralized multi-sensor data fusion methods for Kalman filter including centralized measurement fusion and centralized state-vector