Sample records for fault detection method

  1. Fault detection method with antennas [communication wires

    Microsoft Academic Search

    M. Kando

    1997-01-01

    A fault detection method with antennas has been developed and compared with conventional methods such as the Murry loop bridge and the pulse method. The method was applied to communication wire (surge impedance 50 ohms) with an artificial fault using metal electrode systems, and an artificial void as breakdown and\\/or degradation. The results showed that the detecting distance precision was

  2. An adaptive high and low impedance fault detection method

    Microsoft Academic Search

    D. C. Yu; S. H. Khan

    1994-01-01

    An integrated high impedance fault (HIF) and low impedance fault (LIF) detection method is proposed in this paper. For a HIF detection, the proposed technique is based on a number of characteristics of the HIF current. These characteristics are: fault current magnitude, magnitude of the 3rd harmonic current, magnitude of the 5th harmonic current, the angle of the third harmonic

  3. 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

  4. 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.

  5. A novel selective earth fault detection method using residual current

    Microsoft Academic Search

    Xinzhou Dong; Tao Cui; Zhiqian Bo; Andrzej Juszczyk

    2009-01-01

    In neutral point non-directly grounded medium voltage distribution system, to selectively detect single phase to ground fault remains as a challenge for protection relays. Conventional selective \\/ directional detection method can be used in such cases, but they cannot be implemented without voltage measurements. If the radial connected feeders are grounded via resistor at neutral point on busbar, a novel

  6. 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.

  7. Fault detection in electromagnetic suspension systems with state estimation methods

    SciTech Connect

    Sinha, P.K.; Zhou, F.B.; Kutiyal, R.S. (Univ. of Reading (United Kingdom). Dept. of Engineering)

    1993-11-01

    High-speed maglev vehicles need a high level of safety that depends on the whole vehicle system's reliability. There are many ways of attaining high reliability for the system. Conventional method uses redundant hardware with majority vote logic circuits. Hardware redundancy costs more, weigh more and occupy more space than that of analytically redundant methods. Analytically redundant systems use parameter identification and state estimation methods based on the system models to detect and isolate the fault of instruments (sensors), actuator and components. In this paper the authors use the Luenberger observer to estimate three state variables of the electromagnetic suspension system: position (airgap), vehicle velocity, and vertical acceleration. These estimates are compared with the corresponding sensor outputs for fault detection. In this paper, they consider FDI of the accelerometer, the sensor which provides the ride quality.

  8. 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

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

    E-print Network

    Janecke, Alex Karl

    2012-10-19

    useful information. The same tests are performed on a subcritical air-conditioner showing little value in dynamic fault detection. A static component based method of fault detection which has been applied to subcritical systems is also tested for all...

  10. High resolution seismics methods in application to fault zone detection

    NASA Astrophysics Data System (ADS)

    Matula, Rafal; Czaja, Klaudia; Mahmod, Adam Ahmed

    2014-05-01

    Surveys were carried out along border line between Outer Carpathians, Inner Carpathians and Pieniny Klippen Belt. Main point of interest was imaging transition zone structured by para-conglomerates, sandstone and clays lenses, crossing in near neighbourhood of Stare Bystre, village in the southern part of Poland. Actually geological works states existence of two hypothetical faults, first at the direction NE-SW and second NNW-SSE. Main aim of geological and geophysical investigation was to prove that mentioned fault has a system of smaller discontinuities connected with previous main fault activity. Para-conglomerate exposures, which is localized close to discussed fault is cut by visible system of cracks. That fact provide geological evidences that this system could be the effect of previous fault activity so in other words, it has a continuation up to main discontinuities. What is more part of the same formation para-conglomerates is covered by Neogen river sediments, so non-direct detection methods of cracks azimuth must be applied. Geophysical investigation was located near mentioned exposure and conducted in 3-D variant. Measurements were extremely focused on determining any changes of elevation buried para-conglomerates and velocity variation inside studied sediments. Seismic methods such as refraction and refraction tomography were used to imaging bedrock. Surveys were carried out in non typical acquisition, azimuthal schema. During field works 24- channels seismograph and 4 Hz, 10 Hz and 100 Hz geophones were used. Hypothetical discontinuities were estimated after analysing seismic records and expressed by velocity variation in bedding rocks and additionally evaluated changes in its elevation. Furthermore, in this study attempt of use refraction wave attributes related to loosing rock - para-conglomerates continuity were exposed. The presentation of geophysical data had a volumetric character what was easier to interpret and better related to assumptions about geological structure of mentioned zone. Correlation between geophysical and geological results seems to be very effective in reconstruction the forming processes of fault zones. Better understanding phenomena, which rules of young fault activities, reduce incorporated hazards and simultaneously bring information about presence geodynamics processes.

  11. A Statistical, Rule-Based Fault Detection and Diagnostic Method for Vapor Compression Air Conditioners

    Microsoft Academic Search

    Todd M. Rossi; James E. Braun

    1997-01-01

    This paper presents a method for automated detection and diagnosis of faults in vapor compression air conditioners that only requires temperature measurements, and one humidity measurement. The differences between measured thermodynamic states and predicted states obtained from models for normal performance (residuals) are used as performance indices for both fault detection and diagnosis. For fault detection, statistical properties of the

  12. High impedance fault detection based on wavelet transform and Prony's method

    Microsoft Academic Search

    H. B. Elrefaie

    2006-01-01

    A novel method for high impedance fault (HIP) detection based on wavelet transform and Prony's method is presented. Using this method, HIFs can be discriminated from capacitor switching, transformer inrush current, and arc furnace. Wavelet transform is used for the decomposition of current signals and detecting disturbance resulting from either faults or normal switching currents. Prony's method is used for

  13. Solar system fault detection

    DOEpatents

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

    1984-05-14

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

  14. Solar system fault detection

    DOEpatents

    Farrington, Robert B. (Wheatridge, CO); Pruett, Jr., James C. (Lakewood, CO)

    1986-01-01

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

  15. New high impedance fault detection

    Microsoft Academic Search

    A. Siadatan; H. Kazemi Karegar; V. Najmi

    2010-01-01

    The high impedance fault detection in power system is one of the hard works and if the fault does not clear then the power system may get into damage. In this paper a new method for high impedance fault detection is proposed. The proposed method is based on the chaotic and doffing function. The paper will propose the appropriate formula

  16. A statistical-based sequential method for fast online detection of fault-induced voltage dips

    Microsoft Academic Search

    Irene Y. H. Gu; Nichlas Ernberg; Emmanouil Styvaktakis; M. H. J. Bollen

    2004-01-01

    This paper addresses the problem of detecting voltage dips regarding measurements consisting of fault events, transformer saturation events, and capacitor-switching events. A novel statistical-based sequential detection method is proposed for online classification of these events. The detector is based on the Neyman-Pearson criterion that maximizes the detection rate of fault-induced dips with constrained false alarm rate of the other two

  17. 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.

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

    SciTech Connect

    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.

  19. 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.

  20. 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

  1. Methods and apparatus using commutative error detection values for fault isolation in multiple node computers

    DOEpatents

    Almasi, Gheorghe (Ardsley, NY) [Ardsley, NY; Blumrich, Matthias Augustin (Ridgefield, CT) [Ridgefield, CT; Chen, Dong (Croton-On-Hudson, NY) [Croton-On-Hudson, NY; Coteus, Paul (Yorktown, NY) [Yorktown, NY; Gara, Alan (Mount Kisco, NY) [Mount Kisco, NY; Giampapa, Mark E. (Irvington, NY) [Irvington, NY; Heidelberger, Philip (Cortlandt Manor, NY) [Cortlandt Manor, NY; Hoenicke, Dirk I. (Ossining, NY) [Ossining, NY; Singh, Sarabjeet (Mississauga, CA) [Mississauga, CA; Steinmacher-Burow, Burkhard D. (Wernau, DE) [Wernau, DE; Takken, Todd (Brewster, NY) [Brewster, NY; Vranas, Pavlos (Bedford Hills, NY) [Bedford Hills, NY

    2008-06-03

    Methods and apparatus perform fault isolation in multiple node computing systems using commutative error detection values for--example, checksums--to identify and to isolate faulty nodes. When information associated with a reproducible portion of a computer program is injected into a network by a node, a commutative error detection value is calculated. At intervals, node fault detection apparatus associated with the multiple node computer system retrieve commutative error detection values associated with the node and stores them in memory. When the computer program is executed again by the multiple node computer system, new commutative error detection values are created and stored in memory. The node fault detection apparatus identifies faulty nodes by comparing commutative error detection values associated with reproducible portions of the application program generated by a particular node from different runs of the application program. Differences in values indicate a possible faulty node.

  2. Model-Based Methods for Textile Fault Detection J. G. Campbell,1

    E-print Network

    Raftery, Adrian

    Model-Based Methods for Textile Fault Detection J. G. Campbell,1 C. Fraley,2,3 D. Stanford,2 F for woven textiles in discriminating subtle flaw patterns from the pronounced background of repetitive. Int J Imaging Syst Technol, 10, 339­346, 1999 I. FLAW DETECTION IN TEXTILE FABRIC Obstacles to machine

  3. A Survey of Methods for Detection of Stator-Related Faults in Induction Machines

    Microsoft Academic Search

    Rangarajan M. Tallam; Sang Bin Lee; Greg C. Stone; Gerald B. Kliman; Jiyoon Yoo; Thomas G. Habetler; Ronald G. Harley

    2007-01-01

    As evidenced by industrial surveys, stator-related failures account for a large percentage of faults in induction machines. The objective of this paper is to provide a survey of existing techniques for detection of stator-related faults, which include stator winding turn faults, stator core faults, temperature monitoring and thermal protection, and stator winding insulation testing. The root causes of fault inception,

  4. Optimal stochastic fault detection filter

    Microsoft Academic Search

    Robert H. Chen; Jason L. Speyer

    1999-01-01

    Properties of the optimal stochastic fault detection filter for fault detection and identification are determined. The objective of the filter is to monitor certain faults called target faults and block other faults which are called nuisance faults. This filter is derived by keeping the ratio of the transmission from nuisance fault to the transmission from target fault small. It is

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    1993-04-01

    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. Optimal stochastic fault detection filter

    Microsoft Academic Search

    Robert H. Chen; D. Lewis Mingori; Jason L. Speyer

    2003-01-01

    A fault detection and identification algorithm, called optimal stochastic fault detection filter, is determined. The objective of the filter is to detect a single fault, called the target fault, and block other faults, called the nuisance faults, in the presence of the process and sensor noises. The filter is derived by maximizing the transmission from the target fault to the

  8. Method and system for early detection of incipient faults in electric motors

    DOEpatents

    Parlos, Alexander G; Kim, Kyusung

    2003-07-08

    A method and system for early detection of incipient faults in an electric motor are disclosed. First, current and voltage values for one or more phases of the electric motor are measured during motor operations. A set of current predictions is then determined via a neural network-based current predictor based on the measured voltage values and an estimate of motor speed values of the electric motor. Next, a set of residuals is generated by combining the set of current predictions with the measured current values. A set of fault indicators is subsequently computed from the set of residuals and the measured current values. Finally, a determination is made as to whether or not there is an incipient electrical, mechanical, and/or electromechanical fault occurring based on the comparison result of the set of fault indicators and a set of predetermined baseline values.

  9. 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

  10. 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.

  11. Slow active fault detection and imaging using multiple geophysical methods : the Trevaresse thrust (Provence, France)

    NASA Astrophysics Data System (ADS)

    Nguyen, F.; Garambois, S.; Chardon, D.; Jongmans, D.; Bellier, O.; Hermitte, D.

    2003-04-01

    As many regions of Western Europe, the Provence area is characterized by slow deformation rates, substantial erosion rates, dense vegetation coverage and human activity. These combined factors affect the detection of geomorphological evidence of slow active faults and consequently the selection of trench sites for paleoseismological studies. However, in term of seismic hazard, these regions have to be studied carefully. For example, the most important instrumental seismic event in France history, the Lambesc earthquake (M=6), occurred in Provence in 1909. A review of recent combined studies (Chardon et al., this volume) allows constraining the tectonic and geomorphic evolution of the Trevaresse ridge anticline and associated thrust ramp that obviously ruptured during the 1909 event. In this context, the use of combined geophysical methods can be interesting to determine i) their ability to detect directly, from physico-mechanical contrasts, the location of an active fault (and its characterization) in such a compressional regime where deformation rates are slow, ii) their efficiency in imaging at depth the area around the fault (and consequently, in further constraining geological interpretations), iii) to observe possible recent displacements in Quaternary deposits. Electrical tomography, seismic experiments (refraction tomography and surface wave inversion), EM34 (electromagnetics) and GPR (Ground Penetrating Radar) profiles and CMP were conducted. Four sites were investigated along the Trevaresse thrust. As a lower scale, the Ganay site, where Quaternary deposits crop out, has been studied in more details. Although the fault can not be directly detected from the data at this stage of interpretation, electrical tomographies and the use of direct modeling provided further constrains on the fault system geometry. Seismic anomalies are also clearly visible and could be partially explained by known geological features. Parallel GPR profiles also show anomalies, which could be generated by the fault trace, and thus should at least help in locating trenches for paleoseimological studies. This study is developed within the ACI PCN and the E.U. S.A.F.E. programs.

  12. 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.

  13. Fault detection for T-S fuzzy time-delay systems: delta operator and input-output methods.

    PubMed

    Li, Hongyi; Gao, Yabin; Wu, Ligang; Lam, H K

    2015-02-01

    This paper focuses on the problem of fault detection for Takagi-Sugeno fuzzy systems with time-varying delays via delta operator approach. By designing a filter to generate a residual signal, the fault detection problem addressed in this paper can be converted into a filtering problem. The time-varying delay is approximated by the two-term approximation method. Fuzzy augmented fault detection system is constructed in ? -domain, and a threshold function is given. By applying the scaled small gain theorem and choosing a Lyapunov-Krasovskii functional in ? -domain, a sufficient condition of asymptotic stability with a prescribed H? disturbance attenuation level is derived for the proposed fault detection system. Then, a solvability condition for the designed fault detection filter is established, with which the desired filter can be obtained by solving a convex optimization problem. Finally, an example is given to demonstrate the feasibility and effectiveness of the proposed method. PMID:24919207

  14. SVM-based method for high-impedance faults detection in distribution networks

    Microsoft Academic Search

    M. Sarlak; S. M. Shahrtash

    2011-01-01

    Purpose – The purpose of this paper is to present a new pattern recognition-based algorithm to detect high-impedance faults (HIFs), including only with broken conductor and arcs, in distribution networks. Design\\/methodology\\/approach – In the proposed method, using discrete wavelet transform, the time-frequency-based features of the current waveform are calculated. Then, to extract the best feature set of the generated time-frequency

  15. A Novel Method for the Rotor Fault Detection in Small Inverter-Fed Induction Motors

    Microsoft Academic Search

    Loredana Cristaldi; Marco Faifer; Massimo Lazzaroni; Sergio Toscani

    Ab st ra c t - It is known that when a rotor fault occurs, an induction machine draws an alternative power at twice the rotor frequency. In previous work the authors have shown how to employ this phenomenon in order to detect rotor faults in small inverter fed induction machines. In particular, a rotor fault index has been presented

  16. Fault detection and isolation

    NASA Technical Reports Server (NTRS)

    Bernath, Greg

    1994-01-01

    In order for a current satellite-based navigation system (such as the Global Positioning System, GPS) to meet integrity requirements, there must be a way of detecting erroneous measurements, without help from outside the system. This process is called Fault Detection and Isolation (FDI). Fault detection requires at least one redundant measurement, and can be done with a parity space algorithm. The best way around the fault isolation problem is not necessarily isolating the bad measurement, but finding a new combination of measurements which excludes it.

  17. High impedance fault detection on distribution systems

    Microsoft Academic Search

    C. G. Wester

    1998-01-01

    The detection of high impedance faults on electrical distribution systems has been one of the most persistent and difficult problems facing the electric utility industry. Recent advances in digital technology have enabled practical solutions for the detection of a high percentage of these previously undetectable faults. This paper reviews several mechanical and electrical methods of detecting high impedance faults. The

  18. 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.

  19. 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

  20. Flight elements: Fault detection and fault management

    NASA Technical Reports Server (NTRS)

    Lum, H.; Patterson-Hine, A.; Edge, J. T.; Lawler, D.

    1990-01-01

    Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system.

  1. Method for line-ground fault detection in variable frequency drives

    Microsoft Academic Search

    Carlos D. Rodriguez-Valdez; Rangarajan M. Tallam; Russ J. Kerkman

    2011-01-01

    An Industrial-Power-Converter-System (IPCS) is a system made up of several power converters, such as Adjustable Speed Drives (ASDs), filters, and reactive power-compensation components. An IPCS requires the ability to accurately detect and isolate electric faults to avoid further compromising the integrity of the system. A rather common type of electric fault is the line-to-ground fault. It can occur either from

  2. Monitoring, fault detection and operation prediction of MSW incinerators using multivariate statistical methods.

    PubMed

    Tavares, Gilberto; Zsigraiová, Zdena; Semiao, Viriato; Carvalho, Maria da Graca

    2011-07-01

    This work proposes the application of two multivariate statistical methods, principal component analysis (PCA) and partial least square (PLS), to a continuous process of a municipal solid waste (MSW) moving grate-type incinerator for process control--monitoring, fault detection and diagnosis--through the extraction of information from historical data. PCA model is built for process monitoring capable of detecting abnormal situations and the original 16-variable process dimension is reduced to eight, the first 4 being able to capture together 86% of the total process variation. PLS model is constructed to predict the generated superheated steam flow rate allowing for control of its set points. The model retained six of the original 13 variables, explaining together 90% of the input variation and almost 98% of the output variation. The proposed methodology is demonstrated by applying those multivariate statistical methods to process data continuously measured in an actual incinerator. Both models exhibited very good performance in fault detection and isolation. In predicting the generated superheated steam flow rate for its set point control the PLS model performed very well with low prediction errors (RMSE of 3.1 and 4.1). PMID:21376557

  3. A subspace-based rejection method for detecting bearing fault in asynchronous motor

    Microsoft Academic Search

    Guillaume Bouleux; Ali Ibrahim; François Guillet; Rémy Boyer

    2008-01-01

    Fault detection and diagnosis of asynchronous machine is became a central problem for industrial domain since the past decade. A solution to tackle this problem is to use stator current for a great condition monitoring, as referred to the ldquoMCSArdquo (Motor Current Signal Analysis). Indeed, it is known that due to the motor structure, mechanical spectral signature fault, as for

  4. 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.

  5. 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.

  6. Method to detect line-to-ground faults in high-resistance-ground networks

    Microsoft Academic Search

    Carlos D. Rodríguez-Valdez; Russ J. Kerkman

    2010-01-01

    An Industrial-Power-Converter-System (IPCS) is a system made up of several power converters, such as Adjustable Speed Drive (ASDs), filters, and any kind of reactive power-compensation components. Today, an IPCS requires the ability to accurately detect and isolate electric faults to avoid further compromise of the integrity of the whole system. One particular type of electric fault is the cable line-to-ground

  7. 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 ...

  8. 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.

  9. 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)

    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.

  10. A decentralized fault detection filter

    Microsoft Academic Search

    W. H. Chung; Jason L. Speyer

    1998-01-01

    We introduce the decentralized fault detection filter which is the structure that results from merging decentralized estimation theory with a game theoretic fault detection filter. A decentralized approach may be the ideal way to health monitor large-scale systems for faults, since it decomposes the problem down into (potentially smaller) “local” problems and then blends the “local” results into a “global”

  11. CMOS Bridging Fault Detection

    Microsoft Academic Search

    Thomas M. Storey; Wojciech Maly

    1990-01-01

    The authors compare the performance of two test generation techniques, stuck fault testing and current testing, when applied to CMOS bridging faults. Accurate simulation of such faults mandated the development of several new design automation tools, including an analog-digital fault simulator. The results of this simulation are analyzed. It is shown that stuck fault test generation, while inherently incapable of

  12. A new method for High Impedance Faults detection in power system connected to the wind farm equipped with DFIGs

    Microsoft Academic Search

    Mehrdad Fazli; Ali Reza Shafighi Malekshah; Ali Fazli; Abbas Seif

    2011-01-01

    This paper, investigates the effect of High Impedance Fault (HIF) on wind turbine equipped with Doubly Fed Induction Generator (DFIG) operation. Consequently, a new proposed method is used to HIF detecting in power system connected to wind farm equipped with DFIGs means of harmonic component analyzing of DFIG rotor current. The simulation has been done with PSCAD\\/EMTDC software.

  13. Arc burst pattern analysis fault detection system

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

    A method and apparatus are provided for detecting an arcing fault on a power line carrying a load current. Parameters indicative of power flow and possible fault events on the line, such as voltage and load current, are monitored and analyzed for an arc burst pattern exhibited by arcing faults in a power system. These arcing faults are detected by identifying bursts of each half-cycle of the fundamental current. Bursts occurring at or near a voltage peak indicate arcing on that phase. Once a faulted phase line is identified, a comparison of the current and voltage reveals whether the fault is located in a downstream direction of power flow toward customers, or upstream toward a generation station. If the fault is located downstream, the line is de-energized, and if located upstream, the line may remain energized to prevent unnecessary power outages.

  14. Fault Detection and Identification Methods Used for the LHC Cryomagnets and Related Cabling

    E-print Network

    Bozzini, D; Chareyre, V; Duse, Y; Kroyer, T; López, R; Poncet, A; Russenschuck, Stephan

    2006-01-01

    Several methods for electrical fault location have been developed and tested. As part of the electrical quality assurance program for the LHC, certain wires have to be subjected to a (high) DC voltage for the testing of the insulation. With the time difference of spark-induced electromagnetic signals measured with an oscilloscope, fault localization within ± 10 cm has been achieved. Another method used, and adapted for particular needs, is the synthetic pulse time-domain reflectometry (TDR) with a vector network analyzer (VNA). This instrument has also been applied as a low frequency sweep impedance analyzer in order to measure fractional capacitances of cable assemblies where TDR was not applicable.

  15. 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

  16. Classification of Aircraft Maneuvers for Fault Detection

    NASA Technical Reports Server (NTRS)

    Oza, Nikunj; Tumer, Irem Y.; Tumer, Kagan; Huff, Edward M.; Koga, Dennis (Technical Monitor)

    2002-01-01

    Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, the first assumption is unreasonable and the second is difficult to determine. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

  17. Maneuver Classification for Aircraft Fault Detection

    NASA Technical Reports Server (NTRS)

    Oza, Nikunj C.; Tumer, Irem Y.; Tumer, Kagan; Huff, Edward M.

    2003-01-01

    Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, identifying all possible faulty and proper operating modes is clearly impossible. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

  18. Optimal stochastic multiple-fault detection filter

    Microsoft Academic Search

    Robert H. Chen; Jason L. Speyer

    1999-01-01

    A class of robust fault detection filters is generalized from detecting single fault to multiple faults. This generalization is called the optimal stochastic multiple-fault detection filter since in the formulation, the unknown fault amplitudes are modeled as white noise. The residual space of the filter is divided into several subspaces and each subspace is sensitive to only one fault (target

  19. Exogenous Fault Detection in a Collective Robotic Task

    E-print Network

    Birattari, Mauro

    is capable of detecting faults in the follower robot. All results are based on experiments with real robots or communicate that it has experienced a fault. The method relies on recording sensory data, firstly over simulated hardware faults have been injected. After the data collection phase, fault detection components

  20. Arc fault detection system

    DOEpatents

    Jha, Kamal N. (Bethel Park, PA)

    1999-01-01

    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.

  1. Arc fault detection system

    DOEpatents

    Jha, K.N.

    1999-05-18

    An arc fault detection system for use on ungrounded or high-resistance-grounded power distribution systems is provided which can be retrofitted outside electrical switchboard circuits having limited space constraints. The system includes a differential current relay that senses a current differential between current flowing from secondary windings located in a current transformer coupled to a power supply side of a switchboard, and a total current induced in secondary windings coupled to a load side of the switchboard. When such a current differential is experienced, a current travels through a operating coil of the differential current relay, which in turn opens an upstream circuit breaker located between the switchboard and a power supply to remove the supply of power to the switchboard. 1 fig.

  2. 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.

  3. 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 NÃ?n , with vector lines xT i , whichFault detection and isolation with robust principal component analysis Yvon THARRAULT, Gilles. This paper is concerned with the fault detection and isolation problem. The proposed method does not require

  4. On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification

    NASA Technical Reports Server (NTRS)

    Joshi, Suresh M.

    2012-01-01

    This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are presented for identifiability of actuator faults, sensor faults, and simultaneous actuator and sensor faults. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have biases.

  5. 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.

  6. 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.

  7. Fault Classification and Ground detection using Support Vector Machine

    Microsoft Academic Search

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

    2006-01-01

    This paper presents a new approach for the fault classification and ground detection in transmission line in large power system networks using support vector machine (SVM). The proposed method uses post fault current and voltage samples for 1\\/4th cycle (5 samples) from the inception of the fault as inputs to the SVM. SVM-1 is trained with current and voltage samples

  8. 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.

  9. Fault detection via parameter robust estimation

    Microsoft Academic Search

    Walter H. Chung; Jason L. Speyer

    1997-01-01

    We derive and analyze a fault detection filter which is robust to model uncertainty. To do this, we recast the fault detection problem as a disturbance attenuation problem and then incorporate parameter variations as an additional disturbance. The corresponding solution is a parameter robust game theoretic fault detection filter. A second look at our results, however, shows that the parameter

  10. 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

  11. Model-based fault detection and isolation for intermittently active faults with application to motion-based thruster fault detection and isolation for spacecraft

    NASA Technical Reports Server (NTRS)

    Wilson, Edward (Inventor)

    2008-01-01

    The present invention is a method for detecting and isolating fault modes in a system having a model describing its behavior and regularly sampled measurements. The models are used to calculate past and present deviations from measurements that would result with no faults present, as well as with one or more potential fault modes present. Algorithms that calculate and store these deviations, along with memory of when said faults, if present, would have an effect on the said actual measurements, are used to detect when a fault is present. Related algorithms are used to exonerate false fault modes and finally to isolate the true fault mode. This invention is presented with application to detection and isolation of thruster faults for a thruster-controlled spacecraft. As a supporting aspect of the invention, a novel, effective, and efficient filtering method for estimating the derivative of a noisy signal is presented.

  12. 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)

    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.

  13. 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.

  14. 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

  15. 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

  16. 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...

  17. Planetary Gearbox Fault Detection Using Vibration Separation Techniques

    NASA Technical Reports Server (NTRS)

    Lewicki, David G.; LaBerge, Kelsen E.; Ehinger, Ryan T.; Fetty, Jason

    2011-01-01

    Studies were performed to demonstrate the capability to detect planetary gear and bearing faults in helicopter main-rotor transmissions. The work supported the Operations Support and Sustainment (OSST) program with the U.S. Army Aviation Applied Technology Directorate (AATD) and Bell Helicopter Textron. Vibration data from the OH-58C planetary system were collected on a healthy transmission as well as with various seeded-fault components. Planetary fault detection algorithms were used with the collected data to evaluate fault detection effectiveness. Planet gear tooth cracks and spalls were detectable using the vibration separation techniques. Sun gear tooth cracks were not discernibly detectable from the vibration separation process. Sun gear tooth spall defects were detectable. Ring gear tooth cracks were only clearly detectable by accelerometers located near the crack location or directly across from the crack. Enveloping provided an effective method for planet bearing inner- and outer-race spalling fault detection.

  18. 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...

  19. 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 ...

  20. An ANN-impedance-based fault detection technique in T-Connection transmission overhead lines

    Microsoft Academic Search

    Hassan Abniki; Saeed Nateghi; Mohammad Nabavi Razavi

    2012-01-01

    The aim of this paper is to present an impedance-based technique in order to fault detection in transmission overhead lines. When a fault happens in a power system, fast and reliable fault detection methods are not only desirable but also necessary. In this paper, an impedance-based fault detection technique is presented which applied in ANN. In this regard, using the

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

    E-print Network

    Paris-Sud XI, Université de

    the fault isolation capability [Weber 98]. The isolation is only possible when the incidence matrix.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

  2. 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).

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

    DOEpatents

    Linehan, Daniel J. (Knoxville, TN); Bunch, Stanley L. (Oak Ridge, TN); Lyster, Carl T. (Knoxville, TN)

    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 samples of motor current data are collected. The circuitry insures that a sampled data set containing stationary carrier waves is recreated from the analog motor current signal containing nonstationary carrier waves by conditioning the actual sampling rate to adjust with the frequency variations in the carrier wave. After the sampled data is transformed to the frequency domain via the Discrete Fourier Transform, the frequency distribution in the discrete spectra of those components due to the carrier wave and its harmonics will be minimized so that signals of interest are more easily analyzed.

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

    DOEpatents

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

    1995-10-24

    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 at which samples of motor current data are collected. The circuitry insures that a sampled data set containing stationary carrier waves is recreated from the analog motor current signal containing nonstationary carrier waves by conditioning the actual sampling rate to adjust with the frequency variations in the carrier wave. After the sampled data is transformed to the frequency domain via the Discrete Fourier Transform, the frequency distribution in the discrete spectra of those components due to the carrier wave and its harmonics will be minimized so that signals of interest are more easily analyzed. 29 figs.

  5. 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.

  6. Surveillance system and method having an adaptive sequential probability fault detection test

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

    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.

  7. 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)

    2006-01-01

    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.

  8. A game theoretic fault detection filter

    Microsoft Academic Search

    Walter H. Chung; Jason L. Speyer

    1998-01-01

    The fault detection process is approximated with a disturbance attenuation problem. The solution to this problem, for both linear time-varying and time-invariant systems, leads to a game theoretic filter which bounds the transmission of all exogenous signals except the fault to be detected. In the limit, when the disturbance attenuation bound is brought to zero, a complete transmission block is

  9. A Game Theoretic Fault Detection Filter

    NASA Technical Reports Server (NTRS)

    Chung, Walter H.; Speyer, Jason L.

    1995-01-01

    The fault detection process is modelled as a disturbance attenuation problem. The solution to this problem is found via differential game theory, leading to an H(sub infinity) filter which bounds the transmission of all exogenous signals save the fault to be detected. For a general class of linear systems which includes some time-varying systems, it is shown that this transmission bound can be taken to zero by simultaneously bringing the sensor noise weighting to zero. Thus, in the limit, a complete transmission block can he achieved, making the game filter into a fault detection filter. When we specialize this result to time-invariant system, it is found that the detection filter attained in the limit is identical to the well known Beard-Jones Fault Detection Filter. That is, all fault inputs other than the one to be detected (the "nuisance faults") are restricted to an invariant subspace which is unobservable to a projection on the output. For time-invariant systems, it is also shown that in the limit, the order of the state-space and the game filter can be reduced by factoring out the invariant subspace. The result is a lower dimensional filter which can observe only the fault to be detected. A reduced-order filter can also he generated for time-varying systems, though the computational overhead may be intensive. An example given at the end of the paper demonstrates the effectiveness of the filter as a tool for fault detection and identification.

  10. All-to-all sequenced 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)

    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. High impedance fault detection using feature-pattern based relaying

    Microsoft Academic Search

    A. M. Sharaf; Guosheng Wang

    2003-01-01

    The paper presents a novel time domain high impedance fault (HIF) detection scheme based on low frequency (third, fifth harmonic excursion patterns and phase-portraits). The proposed relaying scheme utilizes a pattern\\/shape recognition method.

  12. Approximate active fault detection and control

    NASA Astrophysics Data System (ADS)

    Škach, Jan; Pun?ochá?, Ivo; Šimandl, Miroslav

    2014-12-01

    This paper deals with approximate active fault detection and control for nonlinear discrete-time stochastic systems over an infinite time horizon. Multiple model framework is used to represent fault-free and finitely many faulty models. An imperfect state information problem is reformulated using a hyper-state and dynamic programming is applied to solve the problem numerically. The proposed active fault detector and controller is illustrated in a numerical example of an air handling unit.

  13. Detecting Latent Faults In Digital Flight Controls

    NASA Technical Reports Server (NTRS)

    Mcgough, John; Mulcare, Dennis; Larsen, William E.

    1992-01-01

    Report discusses theory, conduct, and results of tests involving deliberate injection of low-level faults into digital flight-control system. Part of study of effectiveness of techniques for detection of and recovery from faults, based on statistical assessment of inputs and outputs of parts of control systems. Offers exceptional new capability to establish reliabilities of critical digital electronic systems in aircraft.

  14. 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.

  15. Creating an automated chiller fault detection and diagnostics tool using a data fault library.

    PubMed

    Bailey, Margaret B; Kreider, Jan F

    2003-07-01

    Reliable, automated detection and diagnosis of abnormal behavior within vapor compression refrigeration cycle (VCRC) equipment is extremely desirable for equipment owners and operators. The specific type of VCRC equipment studied in this paper is a 70-ton helical rotary, air-cooled chiller. The fault detection and diagnostic (FDD) tool developed as part of this research analyzes chiller operating data and detects faults through recognizing trends or patterns existing within the data. The FDD method incorporates a neural network (NN) classifier to infer the current state given a vector of observables. Therefore the FDD method relies upon the availability of normal and fault empirical data for training purposes and therefore a fault library of empirical data is assembled. This paper presents procedures for conducting sophisticated fault experiments on chillers that simulate air-cooled condenser, refrigerant, and oil related faults. The experimental processes described here are not well documented in literature and therefore will provide the interested reader with a useful guide. In addition, the authors provide evidence, based on both thermodynamics and empirical data analysis, that chiller performance is significantly degraded during fault operation. The chiller's performance degradation is successfully detected and classified by the NN FDD classifier as discussed in the paper's final section. PMID:12858981

  16. Impulse response analysis of a real feeder for high impedance fault detection

    Microsoft Academic Search

    P. R. Silva; W. C. Boaventura; G. C. Miranda; J. A. Scott

    1994-01-01

    A high impedance fault is an abnormal event that occurs in distribution feeders. Owing to its nature it cannot be detected by conventional protection. A technique for high impedance fault detection is presented in this work. The method consists in injecting an impulsive signal in the feeder followed by the monitoring of its response. High impedance faults are detected by

  17. Determination of Timed Transitions in Identified Discrete-Event Models for Fault Detection

    E-print Network

    Boyer, Edmond

    Determination of Timed Transitions in Identified Discrete-Event Models for Fault Detection Stefan Schneider1, Lothar Litz1 and Jean-Jacques Lesage2 Abstract-- Model-based fault detection compares modeled. The method identifies a set of time guards leading to an advantageous trade-off between the fault detection

  18. 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

  19. 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

  20. A Simultaneous Imaging Method of Multiple Scattering Modes for Detecting a Fault-Zone Heterogeneous Structure of the San Andreas Fault, Parkfield, California

    NASA Astrophysics Data System (ADS)

    Taira, T.; Silver, P. G.; Niu, F.; Nadeau, R. M.

    2005-12-01

    One approach to understanding the generation process of earthquakes is to image fault-zone heterogeneity through the use of single-point scatterers. We present an imaging methodology for imaging multiple scattering modes (P-P, P-S, S-P, and S-S) to assess the relative amplitude of heterogeneity in the bulk and shear modulus in the fault zone. This method is designed for a network of three-component seismic stations and a source array produced from an aftershock sequence. Scattering modes and scatterer locations are determined by the following procedure. For each station, the wave-type and slowness (i.e., propagation) vector for the source-to-scatterer part of the path are estimated by performing a semblance analysis. For the scatterer-to-station segment of the path, the wave-type is constrained by comparing the observed polarization vector, inferred from particle motion, with the predicted propagation vectors from candidate scatterer locations, assuming a half-space velocity model (Vp and V_s are 6.40 km/s and 3.45 km/s, respectively in this study). Candidate scatterer locations and allowable scattering modes are then evaluated by comparison of the observed slowness and polarization vectors with a probability density function based on the 95 per cent confidence levels for these two parameters, in addition to the travel time residual between the observed and predicted travel times. We apply the method to borehole seismograms from 10 relocated aftershocks of the October 20, 1992, M=4.7 Parkfield earthquake recorded by eight stations of the High Resolution Seismic Network. To examine the spatial resolution of the image sections and the ability of our data set to distinguishing among scattering modes, we perform a simple numerical experiment with synthetic seismograms in the frequency range of 8-16 Hz where the signal level was highest, adding 20 per cent of Gaussian random noise to the average signal level at each station. We place three scatterers of each scattering mode at various locations along the San Andreas Fault. We find that the scatterers are generally well recovered so that we expect to resolve each of the scattering modes. From the Parkfield data, we obtain image sections for P-P, P-S, S-P, and S-S scattering modes in the frequency band used in the synthetic test. We find a well constrained region for S-S scattering mode that is located about 10 km south-southeast of the epicenter of the 1966 M=6 Parkfield earthquake at 5 km depth. The size is estimated to be 300 m. We observe no other scattering modes with this data set in this region. The strength of the S-S scattering, combined with the absence of P-P, P-S, and S-P scattering modes implies that structural heterogeneity in the region is dominated by variations in the shear modulus. As such, we hypothesize that the S-S scatterer is associated with fluid-filled cracks or fractures (O'Connell and Budiansky, 1974).

  1. Bearing fault detection for direct-drive wind turbines via stator current spectrum analysis

    Microsoft Academic Search

    Xiang Gong; Wei Qiao

    2011-01-01

    Bearing faults constitute a significant portion of all faults in wind turbine generators (WTGs). Current-based bearing fault detection has significant advantages over traditional vibration-based methods in terms of cost, implementation, and system reliability. This paper proposes a method based on stator current power spectral density (PSD) analysis for bearing fault detection of direct-drive WTGs. In the proposed method, appropriate interpolation\\/up-sampling

  2. Incipient bearing fault detection via wind generator stator current and wavelet filter

    Microsoft Academic Search

    Xiang Gong; Wei Qiao; Wei Zhou

    2010-01-01

    Bearing faults constitute a significant portion of all faults in rotating machines, including wind turbine generators (WTGs). Current-based bearing fault detection has significant advantages over traditional vibration-based methods in terms of cost, implementation, and system reliability. This paper proposes a new wavelet filter-based method for incipient bearing fault detection using electric machine stator currents. The proposed method can dramatically increase

  3. Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

    In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

  4. Tracy-Widom distribution based fault detection approach: application to aircraft sensor/actuator fault detection.

    PubMed

    Hajiyev, Ch

    2012-01-01

    The fault detection approach based on the Tracy-Widom distribution is presented and applied to the aircraft flight control system. An operative method of testing the innovation covariance of the Kalman filter is proposed. The maximal eigenvalue of the random Wishart matrix is used as the monitoring statistic, and the testing problem is reduced to determine the asymptotics for the largest eigenvalue of the Wishart matrix. As a result, an algorithm for testing the innovation covariance based on the Tracy-Widom distribution is proposed. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor and control surface faults in the flight control system which affect the innovation covariance, are examined. PMID:21855060

  5. 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...

  6. Space shuttle main engine fault detection using neural networks

    NASA Technical Reports Server (NTRS)

    Bishop, Thomas; Greenwood, Dan; Shew, Kenneth; Stevenson, Fareed

    1991-01-01

    A method for on-line Space Shuttle Main Engine (SSME) anomaly detection and fault typing using a feedback neural network is described. The method involves the computation of features representing time-variance of SSME sensor parameters, using historical test case data. The network is trained, using backpropagation, to recognize a set of fault cases. The network is then able to diagnose new fault cases correctly. An essential element of the training technique is the inclusion of randomly generated data along with the real data, in order to span the entire input space of potential non-nominal data.

  7. Data fault detection in medical sensor networks.

    PubMed

    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

  8. 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.

  9. 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).

  10. Fault detection in HVAC systems using fuzzy models

    NASA Astrophysics Data System (ADS)

    Dexter, A. L.; Mok, B. K. K.

    1993-12-01

    A fault detection scheme which uses qualitative models, consisting of sets of fuzzy rules, to describe the generic behavior of both fault free and faulty operation of plant is described. It is applied to Heating, Ventilating and Air Conditioning (HVAC) systems. These fuzzy reference models are generated off line from training data produced by computer simulation of a typical plant, with and without the faults, using a fuzzy identification scheme. A computationally efficient, fuzzy identification algorithm, that is suitable for implementation in packaged controls, is used to estimate the credibility of each of the rules. Faults are detected by comparing the behavior of the plant with the behavior predicted by the fuzzy reference models. Two methods of comparing the actual and predicted behavior are examined: a prediction based method in which faults are detected by comparing measurements, available from the building energy management system connected to the plant, with the predictions of the fuzzy reference models; and a rule similarity method in which data collected on line from the real plant are used to identify a partial fuzzy model. The degree to which faulty or correct operation is present, is determined by comparing the rules of the partial fuzzy model with the rules of the fuzzy reference models, using a fuzzy measure of similarity. Results which demonstrate the ability of both schemes to detect faults in the mixing box of the air handling unit of an air conditioning system are presented.

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. A New Nonstationary Test Procedure For Improved Loudspeaker Fault Detection

    Microsoft Academic Search

    M. Davy; C. Doncarli

    2001-01-01

    Loudspeaker fault detection is a dicult industrial problem, for both manufacturing fault detectionand maintenance. In this paper, we present a new, brief (< 100ms), nonstationary test signal aimedat detecting acoustic loudspeaker faults. Recorded loudspeaker responses are compared to a referenceresponse using improved time-frequency signal classication and fault detection algorithms. The eciencyof the proposed test procedure is shown with real data.

  17. The Effects of Fault Counting Methods on Fault Model Quality

    NASA Technical Reports Server (NTRS)

    Nikora, Allen P.; Munson, John C.

    2004-01-01

    In this paper, we describe three other fault-counting techniques and compare the models resulting from the application of two of those methods to the models obtained from the application of our proposed definition.

  18. 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 Abstract--This paper deals with on-line software fault de- tection and isolation method for a drive faults are single-phase open-circuit and current sensor outage. The method is based on the monitoring

  19. Decision tree-based methodology for high impedance fault detection

    Microsoft Academic Search

    Yong Sheng; Steven M. Rovnyak

    2004-01-01

    This paper presents a high impedance fault (HIF) detection method based on decision trees (DTs). The features of HIF, which are the inputs of DTs, are those well-known ones, including current [in root mean square (rms)], magnitudes of the second, third, and fifth harmonics, and the phase of the third harmonics. The only measurements needed in the proposed method are

  20. Imbalance Fault Detection of Direct-Drive Wind Turbines Using Generator Current Signals

    Microsoft Academic Search

    Xiang Gong; Wei Qiao

    2012-01-01

    Imbalance faults constitute a significant portion of all faults in wind turbine generators (WTGs). WTG imbalance fault detection using generator current measurements has advantages over traditional vibration-based methods in terms of cost, implementation, and system reliability. However, there are challenges in using current signals for imbalance fault detection due to low signal-to-noise ratio of the useful information in current signals

  1. Wind tunnel test of UAV fault detection using principal component based aerodynamic model

    Microsoft Academic Search

    Annop Ruangwiset; Banterng Suwantragul

    2008-01-01

    In our previous work the fault detection using aerodynamic model was proposed as more directly method to detect the fault such as configuration damage of the UAV. In this paper the wind tunnel test is performed with the object of verifying the capability of this method to detect the damage during flight. The result shows that by observing the residual

  2. Double Fault Detection of Cone-Shaped Redundant IMUs Using Wavelet Transformation and EPSA

    PubMed Central

    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

  3. Fault detection and diagnosis of photovoltaic systems

    NASA Astrophysics Data System (ADS)

    Wu, Xing

    The rapid growth of the solar industry over the past several years has expanded the significance of photovoltaic (PV) systems. One of the primary aims of research in building-integrated PV systems is to improve the performance of the system's efficiency, availability, and reliability. Although much work has been done on technological design to increase a photovoltaic module's efficiency, there is little research so far on fault diagnosis for PV systems. Faults in a PV system, if not detected, may not only reduce power generation, but also threaten the availability and reliability, effectively the "security" of the whole system. In this paper, first a circuit-based simulation baseline model of a PV system with maximum power point tracking (MPPT) is developed using MATLAB software. MATLAB is one of the most popular tools for integrating computation, visualization and programming in an easy-to-use modeling environment. Second, data collection of a PV system at variable surface temperatures and insolation levels under normal operation is acquired. The developed simulation model of PV system is then calibrated and improved by comparing modeled I-V and P-V characteristics with measured I--V and P--V characteristics to make sure the simulated curves are close to those measured values from the experiments. Finally, based on the circuit-based simulation model, a PV model of various types of faults will be developed by changing conditions or inputs in the MATLAB model, and the I--V and P--V characteristic curves, and the time-dependent voltage and current characteristics of the fault modalities will be characterized for each type of fault. These will be developed as benchmark I-V or P-V, or prototype transient curves. If a fault occurs in a PV system, polling and comparing actual measured I--V and P--V characteristic curves with both normal operational curves and these baseline fault curves will aid in fault diagnosis.

  4. 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

  5. NEURAL NETWORKS FOR PNEUMATIC ACTUATOR FAULT DETECTION

    E-print Network

    Drummond, Tom

    offsets. Key Words. Fault detection; neural networks; system identification; control valves; pneumatic 1 in pneumatic control valve actuators is investigated. Specifically, the ability of a neural network to act architectures are unsuitable for temporal prediction of non­linear system behaviour. An original recurrent

  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. High impedance fault detection utilizing incremental variance of normalized even order harmonic power

    Microsoft Academic Search

    Wook Hyun Kwon; Gi Wen Lee; Young Moon Park; Man Chul Yoon; Myeong Ho Yoo

    1991-01-01

    In this paper, the authors propose a new method for the detection of high impedance faults, which uses the incremental variance of normalized even order ratio measure. Staged fault tests are extensively carried in Korean electric power systems. From the analysis of the staged fault test data, it was found that there exists an intermittent arcing phenomenon in most high

  8. Distributed Fault Detection for Interconnected Second-Order Systems

    E-print Network

    Johansson, Karl Henrik

    and uses fault detection and isolation (FDI) to design a distributed FDI scheme for a network, distributed FDI for systems comprised of a network of autonomous nodes still lacks a thorough theory of the proposed method to FDI in power networks is presented. The outline of the paper is as follows. In the next

  9. Passive Robust Fault Detection for Interval LPV Systems using Zonotopes

    Microsoft Academic Search

    Fatiha Nejjari; Atefeh Sadeghzadeh

    In this paper the problem of robust fault detection using an interval observer for dynamic systems characterized by LPV (Linear Parameter Varying) models is presented. The observer face the robustness problem using two complementary strategies. Parametric modeling uncertainties are consid- ered unknown but bounded by intervals. Their effect is addressed using an interval state observation method based on zonotope representation

  10. 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.

  11. On Distributed Fault-Tolerant Detection in Wireless Sensor Networks

    E-print Network

    Huang, Yinlun

    On Distributed Fault-Tolerant Detection in Wireless Sensor Networks Xuanwen Luo, Student Member problems for distributed fault-tolerant detection in wireless sensor networks: 1) how to address both it possible to perform energy- efficient fault-tolerant detection in a wireless sensor network. Index Terms

  12. 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

  13. Multi-UAV Cooperative Fault Detection Employing Vision-Based RelativePosition Estimation

    Microsoft Academic Search

    G. Heredia; F. Caballero; I. Maza; L. Merino; A. Viguria; A. Ollero

    2008-01-01

    This paper presents a method to increase the reliability of UAV sensor fault detection in a multi- UAV context. The method uses additional position estimations that augment individual UAV fault detection 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

  14. 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

  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 context of helicopter imposes a limited sampling frequency regarding the observed phenomena, many noisy their efficiency. Keywords: vibration, helicopter, health monitoring, frequency estimation, bearing, HUMS

  16. 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.

  17. 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.

  18. 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

  19. Fault detection and isolation in the NT-OMS\\/RCS

    Microsoft Academic Search

    Mohammad Azam; David Pham; Fang Tu; Krishna Pattipati; N. Patterson-Hine; Lui Wang

    2004-01-01

    In this paper, we consider the problem of test design for real-time fault detection and diagnosis in the Space Shuttle's non-toxic orbital maneuvering system and reaction control system (NT-OMS\\/RCS). For demonstration purposes, we restrict our attention to the shaft section of the NT-OMS\\/RCS, which consists of 160 faults (each fault being either a leakage, blockage, igniter fault, or regulator fault)

  20. Application of a fault detection filter to structural health monitoring

    Microsoft Academic Search

    Sauro Liberatore; Jason L. Speyer; Andy Chunliang Hsu

    2006-01-01

    A model-based fault detection filter is developed for structural health monitoring of a simply supported beam. The structural damage represented in the plant model is shown to decompose into a known fault direction vector maintaining a fixed direction, dependent on the damage location, and an arbitrary fault magnitude representing the extent of the damage. According to detection filter theory, if

  1. 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.

  2. LEVERAGING BIM FOR AUTOMATED FAULT DETECTION IN OPERATIONAL *A. Golabchi1

    E-print Network

    Kamat, Vineet R.

    LEVERAGING BIM FOR AUTOMATED FAULT DETECTION IN OPERATIONAL BUILDINGS *A. Golabchi1 , M. Akula1@umich.edu) #12;LEVERAGING BIM FOR AUTOMATED FAULT DETECTION IN OPERATIONAL BUILDINGS ABSTRACT Building Information Modeling (BIM) is an increasingly popular method for generating and managing facility information

  3. 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 become a focal point in the research of renewable energy sources. In order to make the DFIG-based wind for bearing fault detection in DFIG-based wind turbines. The proposed method uses the first Intrinsic Mode

  4. Fault Detection of Broken Rotor Bars in Induction Motor using a Global Fault Index

    E-print Network

    Boyer, Edmond

    Modulation Index, Global Fault Index. 1 Introduction Induction motors, especially the asynchronous motorsFault Detection of Broken Rotor Bars in Induction Motor using a Global Fault Index G. Didier , E. Ternisien , O. Caspary , and H. Razik Abstract Induction motors play a very important part in the safe

  5. Modeling, estimation, fault detection and fault diagnosis of spacecraft air contaminants

    NASA Astrophysics Data System (ADS)

    Narayan, Anand P.

    1998-07-01

    The objective of this dissertation is to develop a framework for the modeling, estimation, fault detection and diagnosis of air contaminants aboard spacecraft. Safe air is a vital resource aboard spacecraft for crewed missions, and especially so in long range missions, where the luxury of returning to earth for a clean-up does not exist. This research uses modern control theory in conjunction with advanced fluid mechanics to achieve the objective of developing an implementable comprehensive monitoring systems, suitable for use on space missions. First, a three-dimensional transport model is developed in order to model the dispersion of air contaminants. The flow field, which is an important input to the transport model, is obtained by solving the Navier Stokes equations for the cabin geometry and the appropriate boundary conditions, using a finite element method. Steady flow fields are computed for various conditions for both laminar and turbulent cases. Contamination dispersion studies are undertaken both for routine substances introduced through the inlet ducts and for emissions of toxics inside the cabin volume. The dispersion studies indicate that lumped models and even a two-dimensional model are sometimes inadequate to assure that the Spacecraft Maximum Allowable Concentrations (SMACs) are not exceeded locally. Since the research was targeted at real-time application aboard Spacecraft, a state estimation routine is implemented using Implicit Kalman Filtering. The routine makes use of the model predictions and measurements from the sensor system in order to arrive at an optimal estimate of the state of the system for each time step. Fault detection is accomplished through the use of analytical redundancy, where error residuals from the Kalman filter are monitored in order to detect any faults in the system, and to distinguish between sensor and process faults. Finally, a fault diagnosis system is developed, which is a combination of sensitivity analysis and an Extended Kalman Filter, which is used to estimate the location and capacity of an unknown source emission in the system. The sensitivity analysis involves pre-calculating sensitivity coefficients, which measure the response of each sensor to a source emission at each location in the cabin, and in the event of a fault, current measurements are used and inverted to arrive at an initial guess for the unknown source that is causing the fault. An Extended Implicit Kalman filter, developed especially for this application then makes use of the initial guess to arrive at an optimal estimate for the unknown source, by minimizing the squared estimation error. The fault diagnosis procedure is successfully tested for various test cases.

  6. Neural network based fault detection in robotic manipulators

    Microsoft Academic Search

    Arun T. Vemuri; Marios M. Polycarpou; Sotiris A. Diakourtis

    1998-01-01

    Fault detection, diagnosis, and accommodation play a key role in the operation of autonomous and intelligent robotic systems. System faults, which typically result in changes in critical system parameters or even system dynamics, may lead to degradation in performance and unsafe operating: conditions. This paper investigates the problem of fault diagnosis in rigid-link robotic manipulators. A learning architecture, with neural

  7. Soft computing applications in high impedance fault detection in distribution systems

    Microsoft Academic Search

    A.-R. Sedighi; M.-R. Haghifam; O. P. Malik

    2005-01-01

    Two methods, one based on genetic algorithm (GA) and one based on neural networks (NN), are proposed for high impedance fault (HIF) detection in distribution systems. These methods are used to discriminate HIFs from isolator leakage current (ILC) and transients such as capacitor switching, load switching (high\\/low voltage), ground fault, inrush current and no load line switching. Wavelet transform is

  8. High impedance fault detection based on wavelet transform and statistical pattern recognition

    Microsoft Academic Search

    Ali-Reza Sedighi; Mahmood-Reza Haghifam; O. P. Malik; Mohammad-Hassan Ghassemian

    2005-01-01

    A novel method for high impedance fault (HIF) detection based on pattern recognition systems is presented in this paper. Using this method, HIFs can be discriminated from insulator leakage current (ILC) and transients such as capacitor switching, load switching (high\\/low voltage), ground fault, inrush current and no load line switching. Wavelet transform is used for the decomposition of signals and

  9. 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...

  10. 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

  11. Research on transient behaviors and detection methods of stator winding inter-turn short circuit fault in induction motors based on multi-loop mathematical model

    Microsoft Academic Search

    Li Heming; Sun Liling; Xu Boqiang

    2005-01-01

    This paper aims to the detection of stator winding inter-turn short circuit fault (SWITSCF) in induction motors. Firstly, the multi-loop mathematical models of squirrel cage induction motor, YN, Y or D connected, under the conditions that the motor is healthy\\/faulty with stator winding inter-turn shorts, are developed. Secondly, the transient simulation of SWITSCF as well as the related experiment is

  12. 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.

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

    SciTech Connect

    Parlos, A.G.; Muthusami, J.; Atiya, A.F. (Texas A and M Univ., College Station, TX (United States). Dept. of Nuclear Engineering)

    1994-02-01

    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 multiple simultaneous faults. To address these issues, it becomes essential to have a learning algorithm that ensures quick convergence to a high level of accuracy. A recently developed accelerated learning algorithm, namely a form of an adaptive back propagation (ABP) algorithm, is used for this purpose. The ABP algorithm is used for the development of an FDI system for a process composed of a direct current motor, a centrifugal pump, and the associated piping system. Simulation studies indicate that the FDI system has significantly high sensitivity to incipient fault severity, while exhibiting insensitivity to sensor noise. For multiple simultaneous faults, the FDI system detects the fault with the predominant signature. The major limitation of the developed FDI system is encountered when it is subjected to simultaneous faults with similar signatures. During such faults, the inherent limitation of pattern-recognition-based FDI methods becomes apparent. Thus, alternate, more sophisticated FDI methods become necessary to address such problems. Even though the effectiveness of pattern-recognition-based FDI methods using ANNs has been demonstrated, further testing using real-world data is necessary.

  14. 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.

  15. Induction machine faults detection using stator current parametric spectral estimation

    NASA Astrophysics Data System (ADS)

    El Bouchikhi, El Houssin; Choqueuse, Vincent; Benbouzid, Mohamed

    2015-02-01

    Current spectrum analysis is a proven technique for fault diagnosis in electrical machines. Current spectral estimation is usually performed using classical techniques such as periodogram (FFT) or its extensions. However, these techniques have several drawbacks since their frequency resolution is limited and additional post-processing algorithms are required to extract a relevant fault detection criterion. Therefore, this paper proposes a new parametric spectral estimator that fully exploits the faults sensitive frequencies. The proposed technique is based on the maximum likelihood estimator (MLE) and offers high-resolution capabilities. Based on this approach, a fault criterion is derived for detecting several fault types. The proposed technique is assessed using simulation signals, issued from a coupled electromagnetic circuits approach-based simulation tool for mechanical unbalance and electrical asymmetry faults detection. It is afterward validated using experiments on a 0.75-kW induction machine test bed for the particular case of bearing faults.

  16. A fault detection and diagnosis system based on input and output residual generation scheme for a CSTR benchmark process

    Microsoft Academic Search

    Mehdi Rezagholizadeh; Karim Salahshoor; Ebrahim Moradi Shahrivar

    2010-01-01

    Aim of this study is to propose fault detection and diagnosis (FDD) algorithm based on input and output residuals that consider both sensor and actuator faults separately. The existing methods which have capability of fault diagnosis and its magnitude estimation suffer from great computational complexity, so they would not be suitable for the real-time applications. The proposed method in this

  17. 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

  18. 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.

  19. Robust Fault Detection and Isolation Using Robust 1 Estimation

    E-print Network

    Collins, Emmanuel

    Robust Fault Detection and Isolation Using Robust 1 Estimation Tramone D. Curry and Emmanuel G considers the application of robust 1 estimation to robust fault detection and isolation , Pn n Ã? n real diagonal, nonnegative definite, positive definite matrices 0, I zero matrix, identity

  20. 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

  1. 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

  2. High-impedance fault detection using discrete wavelet transform and frequency range and RMS conversion

    Microsoft Academic Search

    T. M. Lai; L. A. Snider; E. Lo; D. Sutanto

    2005-01-01

    High-impedance faults (HIFs) are faults which are difficult to detect by overcurrent protection relays. Various pattern recognition techniques have been suggested, including the use of wavelet transform . However this method cannot indicate the physical properties of output coefficients using the wavelet transform. We propose to use the Discrete Wavelet Transform (DWT) as well as frequency range and rms conversion

  3. Model-based fault detection and isolation for electric power steering system

    Microsoft Academic Search

    Jeongjun Lee; Hyeongcheol Lee; Jihwan Kim; Jiyoel Jeong

    2007-01-01

    Electric power steering (EPS) system is an advanced steering system that assists steering torque using the electric motor. To guarantee reliability and safety of EPS System, fault management is especially important. This paper provides a fault detection and isolation (FDI) technique for the sensors of EPS system through the model-based FDI method. In the presented work, FDI algorithm is composed

  4. Dynamic process monitoring and fault detection in a batch fermentation process

    Microsoft Academic Search

    Isaac Monroy; Kris Villez; Moisès Graells; Venkat Venkatasubramanian

    2011-01-01

    A comparative study between two multivariate statistical techniques for batch process monitoring and fault diagnosis is presented. Such methods are Multiway Principal Component Analysis (MPCA) and Batch Dynamic Principal Component Analysis (BDPCA) and both are applied for monitoring the penicillin production process. Three faults are used to evaluate the detection performance and the effects of the unfolding arrangement and the

  5. Distributed fault detection and isolation resilient to network model uncertainties.

    PubMed

    Teixeira, Andre; Shames, Iman; Sandberg, Henrik; Johansson, Karl H

    2014-11-01

    The ability to maintain state awareness in the face of unexpected and unmodeled errors and threats is a defining feature of a resilient control system. Therefore, in this paper, we study the problem of distributed fault detection and isolation (FDI) in large networked systems with uncertain system models. The linear networked system is composed of interconnected subsystems and may be represented as a graph. The subsystems are represented by nodes, while the edges correspond to the interconnections between subsystems. Considering faults that may occur on the interconnections and subsystems, as our first contribution, we propose a distributed scheme to jointly detect and isolate faults occurring in nodes and edges of the system. As our second contribution, we analyze the behavior of the proposed scheme under model uncertainties caused by the addition or removal of edges. Additionally, we propose a novel distributed FDI scheme based on local models and measurements that is resilient to changes outside of the local subsystem and achieves FDI. Our third contribution addresses the complexity reduction of the distributed FDI method, by characterizing the minimum amount of model information and measurements needed to achieve FDI and by reducing the number of monitoring nodes. The proposed methods can be fused to design a scalable and resilient distributed FDI architecture that achieves local FDI despite unknown changes outside the local subsystem. The proposed approach is illustrated by numerical experiments on the IEEE 118-bus power network benchmark. PMID:25222962

  6. 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

  7. Remote Fault Detection of Building HVAC System Using a Global Optimization Program

    E-print Network

    Lee, S. U.; Claridge, D. E.

    2004-01-01

    fault detection method using the global optimization program Solver® (Frontline Systems, 2000) coupled to a simplified simulation program, which is a coding of the ASHRAE 'Simplified Energy Analysis Procedure' (Knebel, 1983). This approach uses...

  8. Fiber Bragg Grating Sensor for Fault Detection in Radial and Network Transmission Lines

    PubMed Central

    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

  9. Fuzzy Set Theory and Fault Tree Analysis based Method Suitable for Fault Diagnosis of Power Transformer

    Microsoft Academic Search

    Tong Wu; Guangyu Tu; Z. Q. Bo; A. Klimek

    2007-01-01

    The fault detection and analysis for power transformer are the key measures to improve the security of power systems and the reliability of power supply. Due to the complicity of the power transformer structure and the variations in operating conditions, the occurrence of a fault inside power transformer is uncertain and random. Until now, the fault statistics of power transformer

  10. Composite Bending Box Section Modal Vibration Fault Detection

    NASA Technical Reports Server (NTRS)

    Werlink, Rudy

    2002-01-01

    One of the primary concerns with Composite construction in critical structures such as wings and stabilizers is that hidden faults and cracks can develop operationally. In the real world, catastrophic sudden failure can result from these undetected faults in composite structures. Vibration data incorporating a broad frequency modal approach, could detect significant changes prior to failure. The purpose of this report is to investigate the usefulness of frequency mode testing before and after bending and torsion loading on a composite bending Box Test section. This test article is representative of construction techniques being developed for the recent NASA Blended Wing Body Low Speed Vehicle Project. The Box section represents the construction technique on the proposed blended wing aircraft. Modal testing using an impact hammer provides an frequency fingerprint before and after bending and torsional loading. If a significant structural discontinuity develops, the vibration response is expected to change. The limitations of the data will be evaluated for future use as a non-destructive in-situ method of assessing hidden damage in similarly constructed composite wing assemblies. Modal vibration fault detection sensitivity to band-width, location and axis will be investigated. Do the sensor accelerometers need to be near the fault and or in the same axis? The response data used in this report was recorded at 17 locations using tri-axial accelerometers. The modal tests were conducted following 5 independent loading conditions before load to failure and 2 following load to failure over a period of 6 weeks. Redundant data was used to minimize effects from uncontrolled variables which could lead to incorrect interpretations. It will be shown that vibrational modes detected failure at many locations when skin de-bonding failures occurred near the center section. Important considerations are the axis selected and frequency range.

  11. A Fault Analytic Method against HB+

    E-print Network

    Carrijo, Jose; Nascimento, Anderson C A

    2010-01-01

    The search for lightweight authentication protocols suitable for low-cost RFID tags constitutes an active and challenging research area. In this context, a family of protocols based on the LPN problem has been proposed: the so-called HB-family. Despite the rich literature regarding the cryptanalysis of these protocols, there are no published results about the impact of fault analysis over them. The purpose of this paper is to fill this gap by presenting a fault analytic method against a prominent member of the HB-family: HB+ protocol. We demonstrate that the fault analysis model can lead to a flexible and effective attack against HB-like protocols, posing a serious threat over them.

  12. Detection of feed-through faults in CMOS storage elements

    NASA Technical Reports Server (NTRS)

    Al-Assadi, Waleed K.; Malaiya, Yashwant K.; Jayasumana, Anura P.

    1992-01-01

    In testing sequential circuits, internal faults in the storage elements (SE's) are sometimes modeled as stuck-at faults in the combinational circuits surrounding the SE. The detection of some transistor-level faults that cannot be modeled as stuck-at are considered. These feed-through faults cause the cell to become either data-feed-through, which makes the cell combinational, or clock-feed-through, which causes the clock signal or its complement to appear at the output. Under such faults, the cell does not function as a memory element. Here it is shown that such faults may or may not be detected depending on delays involved. Conditions under which race-ahead occurs are identified.

  13. Detection filters for aircraft sensor and actuator faults

    Microsoft Academic Search

    Daniel M. Wilbers; Jason L. Speyer

    1989-01-01

    f.rd t detectiou and isolation problem is developed foi both actuator faults and sensor faults of an aircraft. l'ei tiueiit theorems and definitioiis are presented. The fault dettctioii lilter design is tEeated as an eigensystem assign- nirilt probleni. A computer algorithm which calculate8 the dde, lion filters i9 discussed. Detection filter gains are de- veloped for a hear aircraft niodel

  14. Fault Detection and Diagnosis Techniques for Liquid-Propellant Rocket Propellant Engines

    NASA Astrophysics Data System (ADS)

    Wua, Jianjun; Tanb, Songlin

    2002-01-01

    Fault detection and diagnosis plays a pivotal role in the health-monitoring techniques for liquid- propellant rocket engines. This paper firstly gives a brief summary on the techniques of fault detection and diagnosis utilized in liquid-propellant rocket engines. Then, the applications of fault detection and diagnosis algorithms studied and developed to the Long March Main Engine System(LMME) are introduced. For fault detection, an analytical model-based detection algorithm, a time-series-analysis algorithm and a startup- transient detection algorithm based on nonlinear identification developed and evaluated through ground-test data of the LMME are given. For fault diagnosis, neural-network approaches, nonlinear-static-models based methods, and knowledge-based intelligent approaches are presented. Keywords: Fault detection; Fault diagnosis; Health monitoring; Neural networks; Fuzzy logic; Expert system; Long March main engines Contact author and full address: Dr. Jianjun Wu Department of Astronautical Engineering School of Aerospace and Material Engineering National University of Defense Technology Changsha, Hunan 410073 P.R.China Tel:86-731-4556611(O), 4573175(O), 2219923(H) Fax:86-731-4512301 E-mail:jjwu@nudt.edu.cn

  15. Guaranteed robust fault detection and isolation techniques for small satellites

    NASA Astrophysics Data System (ADS)

    Valavani, L.; Tantouris, N.

    2013-12-01

    The paper presents two generic fault detection and isolation (FDI) techniques which have shown remarkable robustness when applied to the SIMULINK model of a small satellite for thruster failures. While fundamentally different in their design approach, they both generate ?structured residuals' which accurately capture the failure mode. The diagnosis criterion in both methods relies on residuals direction rather than magnitude, which avoids the delays and expense of setting accurate thresholds for residuals magnitudes. Most importantly, this fact can account for the enhanced robustness to disturbances and sensor noise, as well as to significant parametric variations. Extensive Monte Carlo simulations are presented validating the robust performance of the two algorithms.

  16. Practical high-impedance fault detection on distribution feeders

    Microsoft Academic Search

    Carl L. Benner; B. Don Russell

    1997-01-01

    Distribution protection systems must balance dependability with security considerations to be practical. This is quite difficult for high-impedance faults. Only highly sensitive algorithms can achieve absolute dependability in detecting very low current faults. This high sensitivity results in a propensity for false tripping, creating a less secure, system and resulting in the potential for decreased service continuity and lower reliability.

  17. 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

  18. Built-In Dynamic Current Sensor for Hard-to-Detect Faults in Mixed-Signal Ics

    Microsoft Academic Search

    Y. Lechuga; R. Mozuelos; Mar Martínez; Salvador Bracho

    2002-01-01

    There are some types of faults in analogue and mixedsignal circuits which are very difficult to detect usingeither voltage or current based test methods. However, itis possible to detect these faults if we add to theconventional dynamic power supply current test methodsIDDT, the analysis of the changes in the slope of thisdynamic power supply current. In this work, we present

  19. 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.

  20. Process fault detection and nonlinear time series analysis for anomaly detection in safeguards

    SciTech Connect

    Burr, T.L.; Mullen, M.F.; Wangen, L.E.

    1994-02-01

    In this paper we discuss two advanced techniques, process fault detection and nonlinear time series analysis, and apply them to the analysis of vector-valued and single-valued time-series data. We investigate model-based process fault detection methods for analyzing simulated, multivariate, time-series data from a three-tank system. The model-predictions are compared with simulated measurements of the same variables to form residual vectors that are tested for the presence of faults (possible diversions in safeguards terminology). We evaluate two methods, testing all individual residuals with a univariate z-score and testing all variables simultaneously with the Mahalanobis distance, for their ability to detect loss of material from two different leak scenarios from the three-tank system: a leak without and with replacement of the lost volume. Nonlinear time-series analysis tools were compared with the linear methods popularized by Box and Jenkins. We compare prediction results using three nonlinear and two linear modeling methods on each of six simulated time series: two nonlinear and four linear. The nonlinear methods performed better at predicting the nonlinear time series and did as well as the linear methods at predicting the linear values.

  1. 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

  2. Incipient Fault Detection and Isolation of Field Devices in Nuclear Power Systems Using Principal Component Analysis

    SciTech Connect

    Kaistha, Nitin; Upadhyaya, Belle R. [University of Tennessee, Knoxville (United States)

    2001-11-15

    An integrated method for the detection and isolation of incipient faults in common field devices, such as sensors and actuators, using plant operational data is presented. The approach is based on the premise that data for normal operation lie on a surface and abnormal situations lead to deviations from the surface in a particular way. Statistically significant deviations from the surface result in the detection of faults, and the characteristic directions of deviations are used for isolation of one or more faults from the set of typical faults. Principal component analysis (PCA), a multivariate data-driven technique, is used to capture the relationships in the data and fit a hyperplane to the data. The fault direction for each of the scenarios is obtained using the singular value decomposition on the state and control function prediction errors, and fault isolation is then accomplished from projections on the fault directions. This approach is demonstrated for a simulated pressurized water reactor steam generator system and for a laboratory process control system under single device fault conditions. Enhanced fault isolation capability is also illustrated by incorporating realistic nonlinear terms in the PCA data matrix.

  3. 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 ...

  4. Vibration-based fault detection of accelerometers in helicopters

    E-print Network

    Boyer, Edmond

    Vibration-based fault detection of accelerometers in helicopters Victor Girondin , Mehena Loudahi-based monitoring is an approach for health analysis of helicopters. However, accelerometers and other sub than standard indicators. Keywords: accelerometers; vibration; helicopter; monitoring; skewness; HUMS

  5. Fault detection in rotary blood pumps using motor speed response.

    PubMed

    Soucy, Kevin G; Koenig, Steven C; Sobieski, Michael A; Slaughter, Mark S; Giridharan, Guruprasad A

    2013-01-01

    Clinical acceptance of ventricular assist devices (VADs) as long-term heart failure therapy requires safe and effective circulatory support for a minimum of 5 years. Yet, VAD failure beyond 2 years of support is still a concern. Currently, device controllers cannot consistently predict VAD failure modes, and undetected VAD faults may lead to catastrophic device failure. To minimize this risk, a model-based algorithm for reliable VAD fault detection that only requires VAD revolutions per minute (rpm) was developed. The algorithm was tested using computer models of the human cardiovascular system simulating heart failure and axial flow (AF) or centrifugal flow (CF) VADs. Ventricular assist device rpm was monitored after a step down of motor current for normal and simulated fault conditions (>750 faults). The ability to detect fault conditions with 1%, 5%, and 10% rpm measurement noise was evaluated. All failure modes affected the VAD rpm responses to the motor current step down. Fault detection rates were >95% for AF and >89% for CF VADs, even with 10% rpm measurement noise. The VAD rpm responses were significantly altered by blood viscosity (3.5-6.2 cP), which should be accounted for in clinical application. The proposed VAD fault detection algorithm may deliver a convenient and nonintrusive way to minimize catastrophic device failures. PMID:23820281

  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. DUKF-based GTM UAV fault detection and diagnosis with nonlinear and LPV models

    Microsoft Academic Search

    Ling Ma; Youmin Zhang

    2010-01-01

    Fault tolerant control system (FTCS) is to maintain system stability in the presence of fault occurred in the actuators, sensors or other system components. When a fault\\/failure occurs either in an actuator, sensor or plant, the fault detection and diagnosis (FDD) as the central part of a FTCS will detect and diagnose the source and the magnitude of the fault.

  8. A robust detection and isolation scheme for abrupt and incipient faults in nonlinear systems

    Microsoft Academic Search

    Xiaodong Zhang; Marios M. Polycarpou; Thomas Parisini

    2002-01-01

    This paper presents a robust fault diagnosis scheme for abrupt and incipient faults in nonlinear uncertain dynamic systems. A detection and approximation estimator is used for online health monitoring. Once a fault is detected, a bank of isolation estimators is activated for the purpose of fault isolation. A key design issue of the proposed fault isolation scheme is the adaptive

  9. Similarity Ratio Analysis for Early Stage Fault Detection with Optical Emission Spectrometer in Plasma Etching Process

    PubMed Central

    Yang, Jie; McArdle, Conor; Daniels, Stephen

    2014-01-01

    A Similarity Ratio Analysis (SRA) method is proposed for early-stage Fault Detection (FD) in plasma etching processes using real-time Optical Emission Spectrometer (OES) data as input. The SRA method can help to realise a highly precise control system by detecting abnormal etch-rate faults in real-time during an etching process. The method processes spectrum scans at successive time points and uses a windowing mechanism over the time series to alleviate problems with timing uncertainties due to process shift from one process run to another. A SRA library is first built to capture features of a healthy etching process. By comparing with the SRA library, a Similarity Ratio (SR) statistic is then calculated for each spectrum scan as the monitored process progresses. A fault detection mechanism, named 3-Warning-1-Alarm (3W1A), takes the SR values as inputs and triggers a system alarm when certain conditions are satisfied. This design reduces the chance of false alarm, and provides a reliable fault reporting service. The SRA method is demonstrated on a real semiconductor manufacturing dataset. The effectiveness of SRA-based fault detection is evaluated using a time-series SR test and also using a post-process SR test. The time-series SR provides an early-stage fault detection service, so less energy and materials will be wasted by faulty processing. The post-process SR provides a fault detection service with higher reliability than the time-series SR, but with fault testing conducted only after each process run completes. PMID:24755865

  10. 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

  11. Surveillance system and method having an operating mode partitioned fault classification model

    NASA Technical Reports Server (NTRS)

    Bickford, Randall L. (Inventor)

    2005-01-01

    A system and method which partitions a parameter estimation model, a fault detection model, and a fault classification model for a process surveillance scheme into two or more coordinated submodels together providing improved diagnostic decision making for at least one determined operating mode of an asset.

  12. 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

  13. Detection of signal transients based on wavelet and statistics for machine fault diagnosis

    NASA Astrophysics Data System (ADS)

    Zhu, Z. K.; Yan, Ruqiang; Luo, Liheng; Feng, Z. H.; Kong, F. R.

    2009-05-01

    This paper presents a transient detection method that combines continuous wavelet transform (CWT) and Kolmogorov-Smirnov (K-S) test for machine fault diagnosis. According to this method, the CWT represents the signal in the time-scale plane, and the proposed "step-by-step detection" based on K-S test identifies the transient coefficients. Simulation study shows that the transient feature can be effectively identified in the time-scale plane with the K-S test. Moreover, the transients can be further transformed back into the time domain through the inverse CWT. The proposed method is then utilized in the gearbox vibration transient detection for fault diagnosis, and the results show that the transient features both expressed in the time-scale plane and re-constructed in the time domain characterize the gearbox condition and fault severity development more clearly than the original time domain signal. The proposed method is also applied to the vibration signals of cone bearings with the localized fault in the inner race, outer race and the rolling elements, respectively. The detected transients indicate not only the existence of the bearing faults, but also the information about the fault severity to a certain degree.

  14. Optimal Sensor Allocation for Fault Detection and Isolation

    NASA Technical Reports Server (NTRS)

    Azam, Mohammad; Pattipati, Krishna; Patterson-Hine, Ann

    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 large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

  15. Soft-Fault Detection Technologies Developed for Electrical Power Systems

    NASA Technical Reports Server (NTRS)

    Button, Robert M.

    2004-01-01

    The NASA Glenn Research Center, partner universities, and defense contractors are working to develop intelligent power management and distribution (PMAD) technologies for future spacecraft and launch vehicles. The goals are to provide higher performance (efficiency, transient response, and stability), higher fault tolerance, and higher reliability through the application of digital control and communication technologies. It is also expected that these technologies will eventually reduce the design, development, manufacturing, and integration costs for large, electrical power systems for space vehicles. The main focus of this research has been to incorporate digital control, communications, and intelligent algorithms into power electronic devices such as direct-current to direct-current (dc-dc) converters and protective switchgear. These technologies, in turn, will enable revolutionary changes in the way electrical power systems are designed, developed, configured, and integrated in aerospace vehicles and satellites. Initial successes in integrating modern, digital controllers have proven that transient response performance can be improved using advanced nonlinear control algorithms. One technology being developed includes the detection of "soft faults," those not typically covered by current systems in use today. Soft faults include arcing faults, corona discharge faults, and undetected leakage currents. Using digital control and advanced signal analysis algorithms, we have shown that it is possible to reliably detect arcing faults in high-voltage dc power distribution systems (see the preceding photograph). Another research effort has shown that low-level leakage faults and cable degradation can be detected by analyzing power system parameters over time. This additional fault detection capability will result in higher reliability for long-lived power systems such as reusable launch vehicles and space exploration missions.

  16. Fuzzy-model-based robust fault detection with stochastic mixed time delays and successive packet dropouts.

    PubMed

    Dong, Hongli; Wang, Zidong; Lam, James; Gao, Huijun

    2012-04-01

    This paper is concerned with the network-based robust fault detection problem for a class of uncertain discrete-time Takagi-Sugeno fuzzy systems with stochastic mixed time delays and successive packet dropouts. The mixed time delays comprise both the multiple discrete time delays and the infinite distributed delays. A sequence of stochastic variables is introduced to govern the random occurrences of the discrete time delays, distributed time delays, and successive packet dropouts, where all the stochastic variables are mutually independent but obey the Bernoulli distribution. The main purpose of this paper is to design a fuzzy fault detection filter such that the overall fault detection dynamics is exponentially stable in the mean square and, at the same time, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions are first established via intensive stochastic analysis for the existence of the desired fuzzy fault detection filters, and then, the corresponding solvability conditions for the desired filter gains are established. In addition, the optimal performance index for the addressed robust fuzzy fault detection problem is obtained by solving an auxiliary convex optimization problem. An illustrative example is provided to show the usefulness and effectiveness of the proposed design method. PMID:21926025

  17. Sensor fault detection using the Mahalanobis distance

    SciTech Connect

    White, A.M.; Gross, K.C. (Argonne National Lab., IL (United States)); Kubic, W.L (Los Alamos National Lab., NM (United States))

    1993-01-01

    A method is described by which a localized sensor abnormality can be detected using the Mahalanobis distance. The Mahalanobis distance is approximately the weighted distance from the hyperplane formed by the principal components to the particular observation. Qualitatively, the principal components correspond to the physical laws that govern the behavior of the systems and constraints placed on the system. If there are more sensors than principal components, there are redundant measurements. This redundancy can be used to detect abnormalities that are due either to sensor failure or a localized change in the system being measured. The method compares the distribution of the Mahalanobis distance during normal operation with the distribution during the current operation. A likelihood ratio test is then used to determine if a sensor has gone bad or if operations in the reactor are different from normal. The sensor whose value is not normal is identified by comparing Mahalanobis distances computed with one sensor masked. When the abnormal sensor is masked, the Mahalanobis distance for this subset of sensors will be within prespecified bounds. The method is demonstrated on 20 subassembly output thermocouples in the core of Experimental Breeder Reactor II.

  18. 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.

  19. 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.

  20. 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

  1. A dynamic integrated fault diagnosis method for power transformers.

    PubMed

    Gao, Wensheng; Bai, Cuifen; 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

  2. Leakage fault detection of pneumatic pipe system using neural networks

    Microsoft Academic Search

    Sheng Zhang; T. Asakura; S. Hayashi

    2003-01-01

    This paper is concerned with leakage fault detection of pneumatic pipe system using neural networks filter. In this research, neural networks are used as nonlinear filter to eliminate noise and raise sound noise ratio of sound signal. Application to pneumatic system verifies the effectiveness of nonlinear filter by neural networks in leakage detection.

  3. Detecting Faults In High-Voltage Transformers

    NASA Technical Reports Server (NTRS)

    Blow, Raymond K.

    1988-01-01

    Simple fixture quickly shows whether high-voltage transformer has excessive voids in dielectric materials and whether high-voltage lead wires too close to transformer case. Fixture is "go/no-go" indicator; corona appears if transformer contains such faults. Nests in wire mesh supported by cap of clear epoxy. If transformer has defects, blue glow of corona appears in mesh and is seen through cap.

  4. 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.

  5. High Resolution Seismic Imaging of Fault Zones: Methods and Examples From The San Andreas Fault

    NASA Astrophysics Data System (ADS)

    Catchings, R. D.; Rymer, M. J.; Goldman, M.; Prentice, C. S.; Sickler, R. R.; Criley, C.

    2011-12-01

    Seismic imaging of fault zones at shallow depths is challenging. Conventional seismic reflection methods do not work well in fault zones that consist of non-planar strata or that have large variations in velocity structure, two properties that occur in most fault zones. Understanding the structure and geometry of fault zones is important to elucidate the earthquake hazard associated with fault zones and the barrier effect that faults impose on subsurface fluid flow. In collaboration with the San Francisco Public Utilities Commission (SFPUC) at San Andreas Lake on the San Francisco peninsula, we acquired combined seismic P-wave and S-wave reflection, refraction, and guided-wave data to image the principal strand of the San Andreas Fault (SAF) that ruptured the surface during the 1906 San Francisco earthquake and additional fault strands east of the rupture. The locations and geometries of these fault strands are important because the SFPUC is seismically retrofitting the Hetch Hetchy water delivery system, which provides much of the water for the San Francisco Bay area, and the delivery system is close to the SAF at San Andreas Lake. Seismic reflection images did not image the SAF zone well due to the brecciated bedrock, a lack of layered stratigraphy, and widely varying velocities. Tomographic P-wave velocity images clearly delineate the fault zone as a low-velocity zone at about 10 m depth in more competent rock, but due to soil saturation above the rock, the P-waves do not clearly image the fault strands at shallower depths. S-wave velocity images, however, clearly show a diagnostic low-velocity zone at the mapped 1906 surface break. To image the fault zone at greater depths, we utilized guided waves, which exhibit high amplitude seismic energy within fault zones. The guided waves appear to image the fault zone at varying depths depending on the frequency of the seismic waves. At higher frequencies (~30 to 40 Hz), the guided waves show strong amplification at the 1906 surface break and at about 20 m to the east, but at lower frequencies (2-5 Hz), the guided waves show strong amplification approximately 10 m east of the 1906 surface break. We attribute the difference in amplification of guided waves to an east-dipping fault strand that merges with other strands below about 10 m depth. Vp/Vs and Poisson's ratios clearly delineate multiple fault strands about 2 km north of the mapped 1906 surface break at the SFPUC intake structure. Combining these fault-imaging methods provide a powerful set of tools for mapping fault zones in the shallow subsurface in areas of complex geology.

  6. A Study of Static Analysis for Fault Detection in Software Jiang Zheng1

    E-print Network

    Young, R. Michael

    -detection technique is capable of addressing all fault-detection concerns. Similar to software reviews and testing-detection technique is capable of addressing all fault-detection concerns [28]. One such technique is static analysis1 A Study of Static Analysis for Fault Detection in Software Jiang Zheng1 , Laurie Williams1

  7. 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

  8. Method and apparatus for fault tolerance

    NASA Technical Reports Server (NTRS)

    Masson, Gerald M. (Inventor); Sullivan, Gregory F. (Inventor)

    1993-01-01

    A method and apparatus for achieving fault tolerance in a computer system having at least a first central processing unit and a second central processing unit. The method comprises the steps of first executing a first algorithm in the first central processing unit on input which produces a first output as well as a certification trail. Next, executing a second algorithm in the second central processing unit on the input and on at least a portion of the certification trail which produces a second output. The second algorithm has a faster execution time than the first algorithm for a given input. Then, comparing the first and second outputs such that an error result is produced if the first and second outputs are not the same. The step of executing a first algorithm and the step of executing a second algorithm preferably takes place over essentially the same time period.

  9. Terrain Change Detection Using ASTER Optical Satellite Imagery Along the Kunlun fault, Tibet

    NASA Astrophysics Data System (ADS)

    Schiek, C. G.; Hurtado, J. M.; Velasco, A. A.; Keller, G. R.; Kreinovich, V.

    2004-12-01

    Terrain changes are manifested in satellite images as pixel offsets, which represent the apparent difference in the position of corresponding pixels in two time-separated images of the same portion of the Earth's surface. We present terrain change detection results using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. The change detection methods employed are Fourier analysis, image window cross-correlation ("imageodesy"), and a wavelet analysis. These methods were applied to the detection of seismic displacement due to the November 14, 2001 Kokoxilli earthquake. During this Ms = 8.1 event, the Kunlun fault experienced a maximum of 16.3 m of displacement. Three ASTER image pairs along the Kunlun fault were used, each with different time separation windows. Each time separation window represents a different time interval, from two years to two months. Our results show that terrain change detection was most successful using the Fourier and wavelet techniques. The Fourier analysis detected left-lateral slip of 4.5 m along a fault oriented 270° in the proximal area of the Kunlun fault. These results are in good agreement with field observations. Wavelet analysis was very effective at delineating fault scarps caused by the 2001 Kokoxili earthquake.

  10. Fault detection and isolation in aircraft gas turbine engines. Part 1: underlying concept

    E-print Network

    Ray, Asok

    two-spool turbofan aircraft engine model for detection and isolation of incipient faults. Keywords both model-based and sensor-based analyses. A linear model-based method, called gas path analysis (GPA), was introduced in 1967 by Urban [5] and subsequently different modifications of this method were proposed

  11. 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.

  12. Fault detection and isolation for multisensor navigation systems

    NASA Technical Reports Server (NTRS)

    Kline, Paul A.; Vangraas, Frank

    1991-01-01

    Increasing attention is being given to the problem of erroneous measurement data for multisensor navigation systems. A recursive estimator can be used in conjunction with a 'snapshot' batch estimator to provide fault detection and isolation (FDI) for these systems. A recursive estimator uses past system states to form a new state estimate and compares it to the calculated state based on a new set of measurements. A 'snapshot' batch estimator uses a set of measurements collected simultaneously and compares solutions based on subsets of measurements. The 'snapshot' approach requires redundant measurements in order to detect and isolate faults. FDI is also referred to as Receiver Autonomous Integrity Monitoring (RAIM).

  13. Modeling, estimation, fault detection and fault diagnosis of spacecraft air contaminants

    Microsoft Academic Search

    Anand P. Narayan

    1998-01-01

    The objective of this dissertation is to develop a framework for the modeling, estimation, fault detection and diagnosis of air contaminants aboard spacecraft. Safe air is a vital resource aboard spacecraft for crewed missions, and especially so in long range missions, where the luxury of returning to earth for a clean-up does not exist. This research uses modern control theory

  14. Method and system for environmentally adaptive fault tolerant computing

    NASA Technical Reports Server (NTRS)

    Copenhaver, Jason L. (Inventor); Jeremy, Ramos (Inventor); Wolfe, Jeffrey M. (Inventor); Brenner, Dean (Inventor)

    2010-01-01

    A method and system for adapting fault tolerant computing. The method includes the steps of measuring an environmental condition representative of an environment. An on-board processing system's sensitivity to the measured environmental condition is measured. It is determined whether to reconfigure a fault tolerance of the on-board processing system based in part on the measured environmental condition. The fault tolerance of the on-board processing system may be reconfigured based in part on the measured environmental condition.

  15. Fault Detection of Rotating Machinery using the Spectral Distribution Function

    NASA Technical Reports Server (NTRS)

    Davis, Sanford S.

    1997-01-01

    The spectral distribution function is introduced to characterize the process leading to faults in rotating machinery. It is shown to be a more robust indicator than conventional power spectral density estimates, but requires only slightly more computational effort. The method is illustrated with examples from seeded gearbox transmission faults and an analytical model of a defective bearing. Procedures are suggested for implementation in realistic environments.

  16. A new engine fault diagnosis method based on spectrometric oil analysis

    NASA Astrophysics Data System (ADS)

    Gao, Jingwei; Zhang, Peilin; Wang, Zhengjun; Zeng, Degui

    2006-11-01

    According to statistics, wear fault is about sixty percent to eighty percent of all the machinery faults. Spectrometric oil analysis is an important condition monitoring and fault diagnosis technique for machinery maintenance. In practice, there are two existing fault diagnosis model of the engine based on spectrometric oil analysis, namely concentration model and gradient model. However, the two above models have their respective disadvantages in condition monitoring and fault diagnosis of the engine. In this paper, a new condition monitoring and fault diagnosis method, proportional model is described. Proportional model use the correlation among the elements in the lubricating oil to detect wear condition and occurring faults in the engine. Then the limit value of proportional model is established by analyzing a lot of spectrum data. In order to validate the availability and effect of proportional model, this paper apply proportional model to an engine and sampling the lubricating oil every 5 hours. Through analyzing the lubricating oil by spectrometer, we find that proportional model could find the abnormal wear information in spectrum data, give more accurate result of wear condition and give the fault form in the engine. The results from this paper prove that this method based on proportional model is applicable and available in condition monitoring and fault diagnosis of the engine.

  17. Early Oscillation Detection for DC/DC Converter Fault Diagnosis

    NASA Technical Reports Server (NTRS)

    Wang, Bright L.

    2011-01-01

    The electrical power system of a spacecraft plays a very critical role for space mission success. Such a modern power system may contain numerous hybrid DC/DC converters both inside the power system electronics (PSE) units and onboard most of the flight electronics modules. One of the faulty conditions for DC/DC converter that poses serious threats to mission safety is the random occurrence of oscillation related to inherent instability characteristics of the DC/DC converters and design deficiency of the power systems. To ensure the highest reliability of the power system, oscillations in any form shall be promptly detected during part level testing, system integration tests, flight health monitoring, and on-board fault diagnosis. The popular gain/phase margin analysis method is capable of predicting stability levels of DC/DC converters, but it is limited only to verification of designs and to part-level testing on some of the models. This method has to inject noise signals into the control loop circuitry as required, thus, interrupts the DC/DC converter's normal operation and increases risks of degrading and damaging the flight unit. A novel technique to detect oscillations at early stage for flight hybrid DC/DC converters was developed.

  18. 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.

  19. 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.

  20. 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.

  1. Sensor Fault Detection in Power Plants Andrew Kusiak1

    E-print Network

    Kusiak, Andrew

    Sensor Fault Detection in Power Plants Andrew Kusiak1 and Zhe Song2 Abstract: This paper presents sensors monitor assembly quality Li and Chen 2006 . In a safety- critical process e.g., a nuclear power et al. 1999; Perla et al. 2004; Cho et al. 2004; Lee et al. 2004; Li and Chen 2006; Mehranbod

  2. Effect of test set minimization on fault detection effectiveness

    Microsoft Academic Search

    W. Eric Wong; Joseph Robert Horgan; Saul London; Aditya P. Mathur

    1995-01-01

    Size and code coverage are important attributes of a set of tests. When a program P is executed on el- ements of the test set T, we can observe the fault detecting capability of T for P. We can also observe the degree to which T induces code coverage on P according to some coverage criterion. We would like to

  3. 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 scheme was proposed which...

  4. FAULT DETECTION IN COAL MILLS USED IN POWER PLANTS

    Microsoft Academic Search

    Peter Fogh Odgaard; Babak Mataji

    In order to achieve high performance and efficiency of coal-fired power plants, it is highly important to control the coal flow into the boiler in the power plant. This means suppression of disturbances and force the coal mill to deliver the required coal flow, as well as monitor the coal mill in order to detect faults in the coal mill

  5. 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

  6. Fault Detection and Elimination for Galileo-GPS Vertical Guidance

    E-print Network

    Stanford University

    Fault Detection and Elimination for Galileo-GPS Vertical Guidance Alexandru Ene, Juan Blanch, J focus is software simulation in the area of combined GPS/Galileo signals, positioning error threat space, such as Galileo and GPS block III, a series of new developments has taken place in the field of Receiver

  7. Multiple Sensor Fault Detection in Heat Exchanger Systems

    E-print Network

    Paris-Sud XI, Université de

    Multiple Sensor Fault Detection in Heat Exchanger Systems Abdelwahab Aïtouche* , Didier Maquin strategy is presented for a heat exchanger system for which the process model consists of a set of linear equations, and can be found in heat exchangers. The increasing importance of heat exchangers in the industry

  8. Automatic fault detection and execution monitoring for AUV missions

    Microsoft Academic Search

    Juhan Emits; Richard Dearden; Miles Pebody

    2010-01-01

    Advanced AUV's, particularly those capable of long duration missions, need increasing amounts of autonomy in order to carry out sophisticated missions without requiring constant support from a ship. One important aspect of this autonomy is fault detection and execution monitoring. In this paper we describe the application of the Livingstone 2 diagnosis system on Autosub 6000 and examine in particular

  9. Parameter-free bearing fault detection based on maximum likelihood estimation and differentiation

    NASA Astrophysics Data System (ADS)

    Bozchalooi, I. Soltani; Liang, Ming

    2009-06-01

    Bearing faults can lead to malfunction and ultimately complete stall of many machines. The conventional high-frequency resonance (HFR) method has been commonly used for bearing fault detection. However, it is often very difficult to obtain and calibrate bandpass filter parameters, i.e. the center frequency and bandwidth, the key to the success of the HFR method. This inevitably undermines the usefulness of the conventional HFR technique. To avoid such difficulties, we propose parameter-free, versatile yet straightforward techniques to detect bearing faults. We focus on two types of measured signals frequently encountered in practice: (1) a mixture of impulsive faulty bearing vibrations and intrinsic background noise and (2) impulsive faulty bearing vibrations blended with intrinsic background noise and vibration interferences. To design a proper signal processing technique for each case, we analyze the effects of intrinsic background noise and vibration interferences on amplitude demodulation. For the first case, a maximum likelihood-based fault detection method is proposed to accommodate the Rician distribution of the amplitude-demodulated signal mixture. For the second case, we first illustrate that the high-amplitude low-frequency vibration interferences can make the amplitude demodulation ineffective. Then we propose a differentiation method to enhance the fault detectability. It is shown that the iterative application of a differentiation step can boost the relative strength of the impulsive faulty bearing signal component with respect to the vibration interferences. This preserves the effectiveness of amplitude demodulation and hence leads to more accurate fault detection. The proposed approaches are evaluated on simulated signals and experimental data acquired from faulty bearings.

  10. State variable method of fault tree analysis

    Microsoft Academic Search

    R. J. Bartholomew; H. K. Knudsen; G. A. Whan

    1984-01-01

    The current technique of Fault Tree Analysis (FTA) generally employs computer codes that calculate the minimal cut sets of the Boolean function, where each cut set comprises basic initiator events (roots) whose intersection implies the occurrence of a TOP (system failure) event. Because the number of calculations can be very large for typical fault trees, the importance of any given

  11. Machine Learning Methods for Industrial Systems Fault Diagnosis

    Microsoft Academic Search

    Gerasimos G. Rigatos

    \\u000a Machine learning methods can be of particular interest for fault diagnosis of systems that exhibit event-driven dynamics.\\u000a For this type of systems fault diagnosis based on automata and finite state machine models has to be performed. In this chapter\\u000a the application of fuzzy automata for fault diagnosis is analyzed. The output of the monitored system is partitioned into\\u000a linear segments

  12. An online outlier identification and removal scheme for improving fault detection performance.

    PubMed

    Ferdowsi, Hasan; Jagannathan, Sarangapani; Zawodniok, Maciej

    2014-05-01

    Measured data or states for a nonlinear dynamic system is usually contaminated by outliers. Identifying and removing outliers will make the data (or system states) more trustworthy and reliable since outliers in the measured data (or states) can cause missed or false alarms during fault diagnosis. In addition, faults can make the system states nonstationary needing a novel analytical model-based fault detection (FD) framework. In this paper, an online outlier identification and removal (OIR) scheme is proposed for a nonlinear dynamic system. Since the dynamics of the system can experience unknown changes due to faults, traditional observer-based techniques cannot be used to remove the outliers. The OIR scheme uses a neural network (NN) to estimate the actual system states from measured system states involving outliers. With this method, the outlier detection is performed online at each time instant by finding the difference between the estimated and the measured states and comparing its median with its standard deviation over a moving time window. The NN weight update law in OIR is designed such that the detected outliers will have no effect on the state estimation, which is subsequently used for model-based fault diagnosis. In addition, since the OIR estimator cannot distinguish between the faulty or healthy operating conditions, a separate model-based observer is designed for fault diagnosis, which uses the OIR scheme as a preprocessing unit to improve the FD performance. The stability analysis of both OIR and fault diagnosis schemes are introduced. Finally, a three-tank benchmarking system and a simple linear system are used to verify the proposed scheme in simulations, and then the scheme is applied on an axial piston pump testbed. The scheme can be applied to nonlinear systems whose dynamics and underlying distribution of states are subjected to change due to both unknown faults and operating conditions. PMID:24808037

  13. Fault detection and exclusion in multisensor navigation systems

    NASA Technical Reports Server (NTRS)

    Bernath, Gregory N.

    1995-01-01

    In order for a multisensor navigation system to meet integrity requirements, there must be a way of detecting erroneous measurements, using only data from those measurements. This can be accomplished using a parity space estimation algorithm. Erroneous measurements must then be removed from the position solution; the entire process is called fault detection and exclusion (FDE). A baseline FDE algorithm has been determined, and is capable of working in real time on present affordable hardware.

  14. A hybrid approach for detecting and isolating faults in nuclear power plant interacting systems

    SciTech Connect

    Hines, J.W.; Miller, D.W.; Hajek, B.K. [Ohio State Univ., Columbus, OH (United States). Dept. of Mechanical Engineering

    1996-09-01

    A fault detection and isolation (FDI) system is presented that can detect and isolate nuclear power plant (NPP) faults occurring in interacting systems. The proposed methodology combines two tools, observer-based residual generation and neural network pattern matching, into a powerful, hybrid diagnostic system. A computer-based model of a commercial boiling water reactor (BWR) is used as the reference plant. Two FDI methods are implemented on each of two BWR systems, and their performance characteristics are compared. One method uses conventional neural network techniques that use parameter values for input, and a second, hybrid methodology uses system models to create residuals for input to a neural network. Both FDI systems show good generalization abilities, but only the hybrid system decouples system interactions. Although implementation is impractical for all NPP systems, this hybrid technique is most useful in specific applications where operators have difficulty diagnosing faults in strongly interacting systems.

  15. Wavelet transform approach to high impedance fault detection in MV networks

    Microsoft Academic Search

    Marek Michalik; Waldemar Rebizant; Miroslaw Lukowicz; Seung-Jae Lee; Sang-Hee Kang

    2005-01-01

    Application of wavelet transform technique to high impedance arcing fault detection in distribution networks is presented. Phase displacement between discrete wavelet coefficients calculated for zero sequence voltage and current signals at natural network frequency is tracked. The developed wavelet based HIF detector has been tested with EMTP-ATP generated signals, proving better performance than traditionally used algorithms and methods. The protection

  16. Decentralised fault detection and diagnosis in navigation systems for unmanned aerial vehicles

    Microsoft Academic Search

    S. M. Magrabi; P. W. Gibbens

    2000-01-01

    Autonomous unmanned aerial vehicles (UAVs) are a technological phenomenon sweeping the world stage. Full autonomy implies that the guidance and navigation system employed must exhibit the highest level of integrity. This paper looks at the parity space fault detection and diagnosis (FDD) methods, and its applicability in fully autonomous guidance and navigation systems in a decentralised system architecture. Using the

  17. Detection of Rotor Faults in Brushless DC Motors Operating Under Nonstationary Conditions

    Microsoft Academic Search

    Satish Rajagopalan; José M. Aller; José A. Restrepo; Thomas G. Habetler; Ronald G. Harley

    2006-01-01

    There are several applications where the motor is operating in continuous nonstationary operating conditions. Actuators and servo motors in the aerospace and transportation industries are examples of this kind of operation. Detection of faults in such applications is, however, challenging because of the need for complex signal processing techniques. Two novel methods using windowed Fourier ridges and Wigner-Ville-based distributions are

  18. 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

  19. Fault detection of batch processes using multiway kernel principal component analysis

    Microsoft Academic Search

    Jong-min Lee; Changkyoo Yoo; In-beum Lee

    2004-01-01

    Batch processes are very important in most industries and are used to produce high-quality materials, which causes their monitoring and control to emerge as essential techniques. Several multivariate statistical analyses, including multiway principal component analysis (MPCA), have been developed for the monitoring and fault detection of batch process. In this paper, a new batch monitoring method using multiway kernel principal

  20. Robust fault detection for LPV systems using interval observers and zonotopes

    Microsoft Academic Search

    Fatiha Nejjari; Vicenç Puig; Saúl Montes de Oca; Atefeh Sadeghzadeh

    2009-01-01

    In this paper, the problem of robust fault detection using an interval observer for dynamic systems characterized by LPV (linear parameter varying) models is presented. The observer faces the robustness problem using two complementary strategies. Modeling uncertainties are considered unknown but bounded by intervals. Their effect is addressed using an interval state observation method based on zonotope representation of the

  1. Artificial Neural Network Based Detection and Diagnosis of Plasma-Etch Faults

    Microsoft Academic Search

    Shumeet Baluja; Roy A. Maxion

    Abstract The plasma-etch process is one of many steps in the fabrication of semiconductorwafers. Currently, faultdetection\\/diagnosis for this process is done primarily by visual inspection of graphically displayed process data. By observing these data, experienced technicians can detect and classify many types of faults. The tediousness and intrinsic human unreliability of this method, as well as the high cost of

  2. 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

  3. 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.

  4. Fault detection and bypass in a sequence information signal processor

    NASA Technical Reports Server (NTRS)

    Peterson, John C. (Inventor); Chow, Edward T. (Inventor)

    1992-01-01

    The invention comprises a plurality of scan registers, each such register respectively associated with a processor element; an on-chip comparator, encoder and fault bypass register. Each scan register generates a unitary signal the logic state of which depends on the correctness of the input from the previous processor in the systolic array. These unitary signals are input to a common comparator which generates an output indicating whether or not an error has occurred. These unitary signals are also input to an encoder which identifies the location of any fault detected so that an appropriate multiplexer can be switched to bypass the faulty processor element. Input scan data can be readily programmed to fully exercise all of the processor elements so that no fault can remain undetected.

  5. Gas Leakage Fault Detection of Pneumatic Pipe System Using Neural Networks

    Microsoft Academic Search

    Sheng Zhang; Toshiyuki Asakura; Shoji Hayashi

    2004-01-01

    This paper is concerned with gas leakage fault detection of a pneumatic pipe system using a neural network filter. In modern plants, the ability to detect and identify gas leakage faults is becoming increasingly important. The main difficulty to detect gas leakage faults by sound signals lies in that the practical plants are usually very noisy. In this research, neural

  6. The Effect of Code Coverage on Fault Detection under Different Testing Profiles

    E-print Network

    Lyu, Michael R.

    experimental data, code coverage is simply a moderate indicator for the capability of fault detection the relationship between code coverage and fault detection capability under different testing profiles. From our]. Such experimental data indicate that both code coverage and fault detected in programs grow over time, as testing

  7. 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.

  8. 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.

  9. ESR detection of seismic frictional heating events in the Nojima fault drill core samples, Japan

    Microsoft Academic Search

    Tatsuro Fukuchi; Jun-ichiro Yurugi; Noboru Imai

    2007-01-01

    We have analyzed the Nojima fault NIED 1800 m drill core samples by ESR (Electron Spin Resonance) to detect seismic frictional heating events, especially during the 1995 Kobe Earthquake. Dark gray fault gouge with foliation >10 cm away from the fault plane at about 1140 m in depth, which was produced by ancient fault movements, has a FMR (ferrimagnetic resonance) signal. Heating experiments

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

    E-print Network

    Paris-Sud XI, Université de

    of the incidence matrix represents the signature of fault Fj. The fault isolation capability depends the linearity hypothesis, isolation of multiple faults may be processed using an extended incidence matrixMULTIPLE FAULT DETECTION AND ISOLATION Weber P. , Gentil S. , Ripoll P. TTTT , Foulloy L. TTTT CNRS

  11. Study of high impedance fault detection in Levante area in Spain

    Microsoft Academic Search

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

    2000-01-01

    This paper presents a study of high impedance fault detection in a particular case of the Spanish power distribution network. It aims to carry out an analysis of high impedance fault riskiness in three-wire distribution systems. A study of the presumed fault is performed considering 64N protection device alarm. Data from staged faults are presented in which downed conductors in

  12. Seismic slip propagation along a fault in the Shimanto accretionary prism detected by vitrinite reflectance studies

    NASA Astrophysics Data System (ADS)

    Kitamura, M.; Mukoyoshi, H.; Hirose, T.

    2011-12-01

    Quantitative assessment of heat generation along faults during fault movement is of primary importance in understanding the dynamics of earthquakes. Last several years localized heat anomaly in a fault zone due to rapid seismic sliding has been detected by various analyses of fault zone materials, such as ferromagnetic resonance signal (Fukuchi et al., 2005), trace elements and isotopes (e.g., Ishikawa et al., 2008) and mineralogical change of clay (e.g., Hirono et al., 2008) and vitrinite reflectance (O'Hara, 2004). Here we report a heat anomaly found in a fault zone in the Shimanto accretionary complex by vitrinite reflectance measurements. Mature faults in nature mostly experience multiple seismic events, resulting in integrated heat anomaly. Thus, in addition to vitrinite reflectance measurements across natural faults, we performed high-velocity friction experiments on a mixture of quartz and vitrinite grains to evaluate how multiple rapid-slip events affect vitrinite reflectance in a fault zone. A localized heat anomaly is found in one of fault zones which are developed within a mélange unit in the Cretaceous Shimanto belt, SW Japan. A principle slip zone with thickness of ~5 mm forms within cataclastic damage zone with thickness of ~3 m. The slip zone is mainly composed of well-foliated clay minerals. Host rocks are characterized by a block-in-matrix texture: aligned sandstone and chert blocks embedded in mudstone matrix. We measured vitrinite reflectance across the fault zone by the same method as reported in Sakaguchi et al., (2011). The measurement reveals that the principle slip zone underwent localized temperature of more than 220°C, while background temperature of both damage zone and host rocks is ~170°C. Since fault motion along most active faults occurs seismological, that inevitably generates frictional heat, the localized heat anomaly is possibly caused by the rapid seismic slip. In order to evaluate the change in vitrinite reflectance by coseismic sliding, we conducted friction experiments on a mixture of 90 wt% quartz and 10 wt% vitrinite at slip rates of 1.3 mm/s and 1.3 m/s, normal stress of 1.0 MPa and displacement of 15 m under anoxic, nitrogen atmosphere. A series of slide-hold-slide tests are also performed to reproduce multiple seismic-slip events. Our preliminary observation of recovered specimens indicated that significant heat anomaly, especially at shear localized zone in the simulated gouge zone, can be detected by vitrinite reflectance measurement. Detailed results will be reported in our presentation.

  13. Fault detection and predictive maintenance program using SEMY Statistical Machine Control (SMC)

    NASA Astrophysics Data System (ADS)

    Ogasawara, Tammie; Izzio, Brian

    2000-08-01

    This presentation describes the introduction of a fault detection and predictive maintenance strategy into the Diffusion area of a semiconductor manufacturing facility. The goal of the fault detection and predictive maintenance strategy is to maximize tool availability for production while minimizing the risk to product. The predictive maintenance methods allow the user to increase the elapsed time between maintenance activities while minimizing the risk of unexpected equipment failure. The predictive maintenance methods are based on the use of a statistically based fault detection system. The selected equipment parameters are monitored throughout the run for drift beyond established threshold limits. Fault detection is reported directly to a maintenance planning and scheduling application which in turn sends a message to the operating personnel. An option is available which will inhibit the use of the tool until the maintenance activity has been completed. A major part of this project was the identification of equipment parameters for monitoring, the statistical methods used in the analysis and the determination of the threshold values at which t originate a maintenance activity. The decision process leading to the definition of these factors is discussed.

  14. 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.

  15. Detection of High-impedance Arcing Faults in Radial Distribution DC Systems

    NASA Technical Reports Server (NTRS)

    Gonzalez, Marcelo C.; Button, Robert M.

    2003-01-01

    High voltage, low current arcing faults in DC power systems have been researched at the NASA Glenn Research Center in order to develop a method for detecting these 'hidden faults', in-situ, before damage to cables and components from localized heating can occur. A simple arc generator was built and high-speed and low-speed monitoring of the voltage and current waveforms, respectively, has shown that these high impedance faults produce a significant increase in high frequency content in the DC bus voltage and low frequency content in the DC system current. Based on these observations, an algorithm was developed using a high-speed data acquisition system that was able to accurately detect high impedance arcing events induced in a single-line system based on the frequency content of the DC bus voltage or the system current. Next, a multi-line, radial distribution system was researched to see if the arc location could be determined through the voltage information when multiple 'detectors' are present in the system. It was shown that a small, passive LC filter was sufficient to reliably isolate the fault to a single line in a multi-line distribution system. Of course, no modification is necessary if only the current information is used to locate the arc. However, data shows that it might be necessary to monitor both the system current and bus voltage to improve the chances of detecting and locating high impedance arcing faults

  16. 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.

  17. Two Trees: Migrating Fault Trees to Decision Trees for Real Time Fault Detection on International Space Station

    NASA Technical Reports Server (NTRS)

    Lee, Charles; Alena, Richard L.; Robinson, Peter

    2004-01-01

    We started from ISS fault trees example to migrate to decision trees, presented a method to convert fault trees to decision trees. The method shows that the visualizations of root cause of fault are easier and the tree manipulating becomes more programmatic via available decision tree programs. The visualization of decision trees for the diagnostic shows a format of straight forward and easy understands. For ISS real time fault diagnostic, the status of the systems could be shown by mining the signals through the trees and see where it stops at. The other advantage to use decision trees is that the trees can learn the fault patterns and predict the future fault from the historic data. The learning is not only on the static data sets but also can be online, through accumulating the real time data sets, the decision trees can gain and store faults patterns in the trees and recognize them when they come.

  18. Signal based fault detection for stator insulation in electric motors

    Microsoft Academic Search

    Emine Ayaz; Murat Ucar; Serhat Seker; Belle R. Upadhyaya

    2008-01-01

    Stator winding insulation damage in induction motors is considered in this research and fault features developed during the artificial aging process of the stator insulation are extracted from the collected data by the spectral analysis methods. Even harmonic effects are determined as a common feature between the phase currents and vibration signals using the coherence analysis and hence this feature

  19. Application of an improved kurtogram method for fault diagnosis of rolling element bearings

    NASA Astrophysics Data System (ADS)

    Lei, Yaguo; Lin, Jing; He, Zhengjia; Zi, Yanyang

    2011-07-01

    Kurtogram, due to the superiority of detecting and characterizing transients in a signal, has been proved to be a very powerful and practical tool in machinery fault diagnosis. Kurtogram, based on the short time Fourier transform (STFT) or FIR filters, however, limits the accuracy improvement of kurtogram in extracting transient characteristics from a noisy signal and identifying machinery fault. Therefore, more precise filters need to be developed and incorporated into the kurtogram method to overcome its shortcomings and to further enhance its accuracy in discovering characteristics and detecting faults. The filter based on wavelet packet transform (WPT) can filter out noise and precisely match the fault characteristics of noisy signals. By introducing WPT into kurtogram, this paper proposes an improved kurtogram method adopting WPT as the filter of kurtogram to overcome the shortcomings of the original kurtogram. The vibration signals collected from rolling element bearings are used to demonstrate the improved performance of the proposed method compared with the original kurtogram. The results verify the effectiveness of the method in extracting fault characteristics and diagnosing faults of rolling element bearings.

  20. 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.

  1. Dynamic Structural Fault Detection and Identification

    NASA Technical Reports Server (NTRS)

    Smith, Timothy; Reichenbach, Eric; Urnes, James M.

    2009-01-01

    Aircraft structures are designed to guarantee safety of flight in some required operational envelope. When the aircraft becomes structurally impaired, safety of flight may not be guaranteed within that previously safe operational envelope. In this case the safe operational envelope must be redefined in-flight and a means to prevent excursion from this new envelope must be implemented. A specific structural failure mode that may result in a reduced safe operating envelope, the exceedance of which could lead to catastrophic structural failure of the aircraft, will be addressed. The goal of the DFEAP program is the detection of this failure mode coupled with flight controls adaptation to limit critical loads in the damaged aircraft structure. The DFEAP program is working with an F/A-18 aircraft model. The composite wing skins are bonded to metallic spars in the wing substructure. Over time, it is possible that this bonding can deteriorate due to fatigue. In this case, the ability of the wing spar to transfer loading between the wing skins is reduced. This failure mode can translate to a reduced allowable compressive strain on the wing skin and could lead to catastrophic wing buckling if load limiting of the wing structure is not applied. The DFEAP program will make use of a simplified wing strain model for the healthy aircraft. The outputs of this model will be compared in real-time to onboard strain measurements at several locations on the aircraft wing. A damage condition is declared at a given location when the strain measurements differ sufficiently from the strain model. Parameter identification of the damaged structure wing strain parameters will be employed to provide load limiting control adaptation for the aircraft. This paper will discuss the simplified strain models used in the implementation and their interaction with the strain sensor measurements. Also discussed will be the damage detection and identification schemes employed and the means by which the damaged aircraft parameters will be used to provide load limiting that keeps the aircraft within the safe operational envelope.

  2. Detection of shallow faults using different seismic sources - a comparison

    NASA Astrophysics Data System (ADS)

    Roy-Chowdhury, K.

    2003-04-01

    Studies regarding the paleo-seismic activity along the Felbis Fault in Belgium (western boundary of the of the Roer-valley graben) have given rise to an investigation regarding the detectibility of very shallow faulting. Different geophysical and geological techniques have been employed to try to constrain, continue and correlate the faults identified at depth by deeper geophysical imaging techniques. To support this investigation, a seismic line was recorded in an area, where the fault is known to outcrop, using two different seismic sources. A weight-drop along with vertical geophones were used in the first experiment to produce a conventional P-wave seismic section (CMP stack). The same line was later recorded using a portable S-wave vibrator and horizontal geophones for obtaining an SH-wave section. The processing strategies were quite simliar but for the extra deconvolution for the vibrator signal. Anisotropic effects were not considered. The two sections differ in resolution and some other features and these will be discussed in the context of the field layout/geometry and the band-width of the source-signals. Aspects of field-work like the speed and ease of data-acquistion wil also be compared.

  3. High Impedance Faults Detection in EHV Transmission Lines Using the Wavelet Transforms

    Microsoft Academic Search

    El Sayed Tag Eldin; D. k. Ibrahim; E. M. Aboul-Zahab; S. M. Saleh

    2007-01-01

    High impedance faults (HIFs) are difficult to detect by overcurrent protection relays. This paper presents an ATP\\/EMTP fault simulations studies based algorithm for high impedance fault detection in extra high voltage transmission line. The scheme recognizes the distortion of the voltage waveforms caused by the arcs usually associated with HIF. The discrete wavelet transform (DWT) based analysis, yields three phase

  4. Conditions for Detecting and Isolating Sets of Faults in Nonlinear Systems

    E-print Network

    De Luca, Alessandro

    and disturbances (i.e., to solve the standard Fault Detection and Isolation (FDI) problem), some necessary are structurally violated, we introduce a more general class of FDI problems, referred to as Fault Set Detection faults and from disturbances (the standard FDI problem) [1]. The FDI problem for systems modeled

  5. Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks

    Microsoft Academic Search

    Bhaskar Krishnamachari; S. Sitharama Iyengar

    2004-01-01

    We propose a distributed solution for a canonical task in wireless sensor networks—the binary detection of interesting environmental events. We explicitly take into account the possibility of sensor measurement faults and develop a distributed Bayesian algorithm for detecting and correcting such faults. Theoretical analysis and simulation results show that 85-95 percent of faults can be corrected using this algorithm, even

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

    E-print Network

    Dobson, Simon

    Autonomous 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 for autonomously generating investigation leads that help identify systems faults, and extends our previous work

  7. The Effectiveness of Automated Static Analysis Tools for Fault Detection and Refactoring Prediction

    E-print Network

    Bieman, James M.

    The Effectiveness of Automated Static Analysis Tools for Fault Detection and Refactoring Prediction of faults that caused failures, and refac- toring modifications. The results show that fewer than 3% of the detected faults correspond to the coding concerns re- ported by the ASA tools. ASA tools were more

  8. Distributed Fault Detection of Wireless Sensor Networks Jinran Chen, Shubha Kher, and Arun Somani

    E-print Network

    Distributed Fault Detection of Wireless Sensor Networks Jinran Chen, Shubha Kher, and Arun Somani for a variety of applications. Faults occurring to sensor nodes are common due to the sensor device itself it is necessary for the WSN to be able to detect the faults and take actions to avoid further degradation

  9. 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

  10. 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.

  11. 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.

  12. Design Method of Fault Detector for Injection Unit

    NASA Astrophysics Data System (ADS)

    Ochi, Kiyoshi; Saeki, Masami

    An injection unit is considered as a speed control system utilizing a reaction-force sensor. Our purpose is to design a fault detector that detects and isolates actuator and sensor faults under the condition that the system is disturbed by a reaction force. First described is the fault detector's general structure. In this system, a disturbance observer that estimates the reaction force is designed for the speed control system in order to obtain the residual signals, and then post-filters that separate the specific frequency elements from the residual signals are applied in order to generate the decision signals. Next, we describe a fault detector designed specifically for a model of the injection unit. It is shown that the disturbance imposed on the decision variables can be made significantly small by appropriate adjustments to the observer bandwidth, and that most of the sensor faults and actuator faults can be detected and some of them can be isolated in the frequency domain by setting the frequency characteristics of the post-filters appropriately. Our result is verified by experiments for an actual injection unit.

  13. A Study on Transfer Switching in Consideration of Fault Detection in FRIENDS

    NASA Astrophysics Data System (ADS)

    Suzuki, Toshihiro; Hara, Ryoichi; Kita, Hiroyuki; Tanaka, Eiichi; Hasegawa, Jun; Iyoda, Isao

    The authors have proposed a new concept of a distribution system ‘Flexible, Reliable and Intelligent ENergy Delivery System (FRIENDS)’ with a view of solving problems in near future and providing several services for electric companies and customers. The main idea of FRIENDS is to install new facilities named Quality Control Center (QCC) in the neighborhood of customers to realize various functions, e.g. Customized Power Quality Service. In addition, these QCCs make a network of electricity and information below distribution substations. The configuration of the network can be changed frequently depending on the system and load conditions. This frequent reconfiguration of the network requires fast and reliable Transfer Switching in QCC to ease an effect on customers. The reconfiguration with the aim of removing a fault wire also requires fast Fault Detection. This paper presents a new method for controlling Transfer Switching and a method of Fault Detection in order to realize a fast and reliable reconfiguration of QCC network in an ordinary state, and even in a fault. Besides, this paper analyzes the methods in terms of instantaneous values calculated by PSCAD/EMTDC.

  14. 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.

  15. Detecting Faults in Southern California using Computer-Vision Techniques and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) Interferometry

    NASA Astrophysics Data System (ADS)

    Barba, M.; Rains, C.; von Dassow, W.; Parker, J. W.; Glasscoe, M. T.

    2013-12-01

    Knowing the location and behavior of active faults is essential for earthquake hazard assessment and disaster response. In Interferometric Synthetic Aperture Radar (InSAR) images, faults are revealed as linear discontinuities. Currently, interferograms are manually inspected to locate faults. During the summer of 2013, the NASA-JPL DEVELOP California Disasters team contributed to the development of a method to expedite fault detection in California using remote-sensing technology. The team utilized InSAR images created from polarimetric L-band data from NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) project. A computer-vision technique known as 'edge-detection' was used to automate the fault-identification process. We tested and refined an edge-detection algorithm under development through NASA's Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) project. To optimize the algorithm we used both UAVSAR interferograms and synthetic interferograms generated through Disloc, a web-based modeling program available through NASA's QuakeSim project. The edge-detection algorithm detected seismic, aseismic, and co-seismic slip along faults that were identified and compared with databases of known fault systems. Our optimization process was the first step toward integration of the edge-detection code into E-DECIDER to provide decision support for earthquake preparation and disaster management. E-DECIDER partners that will use the edge-detection code include the California Earthquake Clearinghouse and the US Department of Homeland Security through delivery of products using the Unified Incident Command and Decision Support (UICDS) service. Through these partnerships, researchers, earthquake disaster response teams, and policy-makers will be able to use this new methodology to examine the details of ground and fault motions for moderate to large earthquakes. Following an earthquake, the newly discovered faults can be paired with infrastructure overlays, allowing emergency response teams to identify sites that may have been exposed to damage. The faults will also be incorporated into a database for future integration into fault models and earthquake simulations, improving future earthquake hazard assessment. As new faults are mapped, they will further understanding of the complex fault systems and earthquake hazards within the seismically dynamic state of California.

  16. 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

  17. Customized Multiwavelets for Planetary Gearbox Fault Detection Based on Vibration Sensor Signals

    PubMed Central

    Sun, Hailiang; Zi, Yanyang; He, Zhengjia; Yuan, Jing; Wang, Xiaodong; Chen, Lue

    2013-01-01

    Planetary gearboxes exhibit complicated dynamic responses which are more difficult to detect in vibration signals than fixed-axis gear trains because of the special gear transmission structures. Diverse advanced methods have been developed for this challenging task to reduce or avoid unscheduled breakdown and catastrophic accidents. It is feasible to make fault features distinct by using multiwavelet denoising which depends on the feature separation and the threshold denoising. However, standard and fixed multiwavelets are not suitable for accurate fault feature detections because they are usually independent of the measured signals. To overcome this drawback, a method to construct customized multiwavelets based on the redundant symmetric lifting scheme is proposed in this paper. A novel indicator which combines kurtosis and entropy is applied to select the optimal multiwavelets, because kurtosis is sensitive to sharp impulses and entropy is effective for periodic impulses. The improved neighboring coefficients method is introduced into multiwavelet denoising. The vibration signals of a planetary gearbox from a satellite communication antenna on a measurement ship are captured under various motor speeds. The results show the proposed method could accurately detect the incipient pitting faults on two neighboring teeth in the planetary gearbox. PMID:23334609

  18. Customized multiwavelets for planetary gearbox fault detection based on vibration sensor signals.

    PubMed

    Sun, Hailiang; Zi, Yanyang; He, Zhengjia; Yuan, Jing; Wang, Xiaodong; Chen, Lue

    2013-01-01

    Planetary gearboxes exhibit complicated dynamic responses which are more difficult to detect in vibration signals than fixed-axis gear trains because of the special gear transmission structures. Diverse advanced methods have been developed for this challenging task to reduce or avoid unscheduled breakdown and catastrophic accidents. It is feasible to make fault features distinct by using multiwavelet denoising which depends on the feature separation and the threshold denoising. However, standard and fixed multiwavelets are not suitable for accurate fault feature detections because they are usually independent of the measured signals. To overcome this drawback, a method to construct customized multiwavelets based on the redundant symmetric lifting scheme is proposed in this paper. A novel indicator which combines kurtosis and entropy is applied to select the optimal multiwavelets, because kurtosis is sensitive to sharp impulses and entropy is effective for periodic impulses. The improved neighboring coefficients method is introduced into multiwavelet denoising. The vibration signals of a planetary gearbox from a satellite communication antenna on a measurement ship are captured under various motor speeds. The results show the proposed method could accurately detect the incipient pitting faults on two neighboring teeth in the planetary gearbox. PMID:23334609

  19. Fault detection for a diesel engine actuator - A benchmark for FDI

    Microsoft Academic Search

    M. Blanke; S. A. Bøgh; R. B. Jørgensen; R. J. Patton

    1995-01-01

    An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI). The purpose is to provide a simple, industrial system as a platform for comparison of model-based FDI methods, and for the gathering of design experience. Despite a simple system structure, FDI design is intricate when realistic obstacles are included: measurement noise. FDI performance specifications

  20. Low Overhead Built-In Testable Error Detection and Correction with Excellent Fault Coverage

    Microsoft Academic Search

    Mehdi Katoozi; Arnold Nordsieck

    1991-01-01

    A method for the design of built-in testable (BIT) error detection and correction (EDAC) circuits is presented reducing test hardware by >50%. A lp CMOS, 16-bit EDAC designed and fabricated with this technique exhibits >99% fault coverage in 10 p at 25 MHz. Built-in test impacts the speed performance by only one gate delay regardless of the size of the

  1. Hidden Markov models for fault detection in dynamic systems

    NASA Technical Reports Server (NTRS)

    Smyth, Padhraic J. (inventor)

    1993-01-01

    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) perpendicular to x), 1 less than or equal to i is less 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.

  2. 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.

  3. Improved Condition Monitoring System for Induction Machines Using a Model-Based Fault Detection Approach

    Microsoft Academic Search

    Loránd SZABÓ; Károly Ágoston BIRÓ; Dénes FODOR

    Due to their reliability, robustness and simple construction squirrel-cage induction motors are widely used in industry. However, faults like broken rotor bars, rotor eccentricity, bearing and winding faults can occur during normal operation of the motor. Techniques for the detection of these faults have been researched since more than ten years. Although hundreds of papers are published year by year

  4. Incipient bearing fault detection for three-phase Brushless DC motor drive using ANFIS

    Microsoft Academic Search

    Haitham Abu-Rub; Sk. Moin Ahmed; Atif Iqbal; Hamid A. Toliyat; Mina M. Rahimian

    2011-01-01

    ? Abstract - Incipient fault detection of electrical machine is a major task and requires intelligent diagnostic approach. Extensive research has been performed in the field of automation of fault diagnostic schemes. Among several causes of electrical machine failure the most frequent occurring fault is the mechanical bearing failure. Thus, this paper presents diagnostic technique for incipient bearing failure in

  5. 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,

  6. Instantaneous energy density as a feature for gear fault detection

    NASA Astrophysics Data System (ADS)

    Loutridis, S. J.

    2006-07-01

    In this work, energy-based features for gear fault diagnosis and prediction are proposed. The instantaneous energy density is shown to obtain high values when defected teeth are engaged. Three methods are compared in terms of sensitivity, reliability and computation effectiveness. The Wigner-Ville distribution is contrasted to the wavelet transform and the newly proposed empirical mode decomposition scheme. It is shown that all three methods are capable of a reliable prediction. An empirical law, which relates the energy content to the crack magnitude is established.

  7. On-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques

    E-print Network

    Thawonmas, Ruck

    recognised by a small insipient leakage. The development of a suitable system that is able to detectOn-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques C model-based fault detection systems in machinery improves the operational reliability of industrial

  8. 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.

  9. IMPLEMENTATION OF STOCHASTIC METHODS FOR INDUSTRIAL GAS TURBINE FAULT DIAGNOSIS

    Microsoft Academic Search

    C. Romessis; K. Mathioudakis

    2005-01-01

    Implementation of stochastic diagnostic methods for diagnosis of sensor or component faults is presented. Two industrial gas turbines are considered as test cases, one twin and one single shaft arrangement. Methods based on Probabilistic Neural Networks (PNN) and Bayesian Belief Networks (BBN), are implemented. The ability for successful diagnosis is demonstrated on specific cases of sensor malfunctions, as well as

  10. An Agreement-Based Fault Detection Mechanism for Under Water Sensor Networks

    Microsoft Academic Search

    Pu Wang; Jun Zheng; Cheng Li

    2007-01-01

    In this paper, we propose an agreement-based fault detection mechanism for detecting cluster-head failures in clustered UnderWater Sensor Networks (UWSNs). The proposed detection mechanism aims to accurately detect the failure of a cluster head in order to avoid unnecessary energy consumption caused by a mistaken detection. For this purpose, it allows each cluster member to independently detect the fault status

  11. 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.

  12. 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.

  13. Error-detection-based quantum fault tolerance against discrete Pauli noise

    E-print Network

    Reichardt, B W

    2006-01-01

    A quantum computer -- i.e., a computer capable of manipulating data in quantum superposition -- would find applications including factoring, quantum simulation and tests of basic quantum theory. Since quantum superpositions are fragile, the major hurdle in building such a computer is overcoming noise. Developed over the last couple of years, new schemes for achieving fault tolerance based on error detection, rather than error correction, appear to tolerate as much as 3-6% noise per gate -- an order of magnitude better than previous procedures. But proof techniques could not show that these promising fault-tolerance schemes tolerated any noise at all. With an analysis based on decomposing complicated probability distributions into mixtures of simpler ones, we rigorously prove the existence of constant tolerable noise rates ("noise thresholds") for error-detection-based schemes. Numerical calculations indicate that the actual noise threshold this method yields is lower-bounded by 0.1% noise per gate.

  14. Error-detection-based quantum fault tolerance against discrete Pauli noise

    E-print Network

    Ben W. Reichardt

    2006-11-30

    A quantum computer -- i.e., a computer capable of manipulating data in quantum superposition -- would find applications including factoring, quantum simulation and tests of basic quantum theory. Since quantum superpositions are fragile, the major hurdle in building such a computer is overcoming noise. Developed over the last couple of years, new schemes for achieving fault tolerance based on error detection, rather than error correction, appear to tolerate as much as 3-6% noise per gate -- an order of magnitude better than previous procedures. But proof techniques could not show that these promising fault-tolerance schemes tolerated any noise at all. With an analysis based on decomposing complicated probability distributions into mixtures of simpler ones, we rigorously prove the existence of constant tolerable noise rates ("noise thresholds") for error-detection-based schemes. Numerical calculations indicate that the actual noise threshold this method yields is lower-bounded by 0.1% noise per gate.

  15. Failure detection and fault management techniques for flush airdata sensing systems

    NASA Technical Reports Server (NTRS)

    Whitmore, Stephen A.; Moes, Timothy R.; Leondes, Cornelius T.

    1992-01-01

    Methods based on chi-squared analysis are presented for detecting system and individual-port failures in the high-angle-of-attack flush airdata sensing system on the NASA F-18 High Alpha Research Vehicle. The HI-FADS hardware is introduced, and the aerodynamic model describes measured pressure in terms of dynamic pressure, angle of attack, angle of sideslip, and static pressure. Chi-squared analysis is described in the presentation of the concept for failure detection and fault management which includes nominal, iteration, and fault-management modes. A matrix of pressure orifices arranged in concentric circles on the nose of the aircraft indicate the parameters which are applied to the regression algorithms. The sensing techniques are applied to the F-18 flight data, and two examples are given of the computed angle-of-attack time histories. The failure-detection and fault-management techniques permit the matrix to be multiply redundant, and the chi-squared analysis is shown to be useful in the detection of failures.

  16. The new fault diagnosis method of wavelet packet neural network on pump valves of reciprocating pumps

    Microsoft Academic Search

    Duan Yu-bo; Wang Xing-zhu; Han Xue-song

    2009-01-01

    Two key issues of fault diagnosis for the pump valves of reciprocating pump are extracting the fault feature information of nonstationary time variation process efficiently from system feature signals and classifying the faults feature correctly. A new method of fault feature is proposed by ordinary pressure signal (pressure in pump cylinder) as system feature signals. A diagnosis method based on

  17. Fault detection and fault tolerant control of a smart base isolation system with magneto-rheological damper

    NASA Astrophysics Data System (ADS)

    Wang, Han; Song, Gangbing

    2011-08-01

    Fault detection and isolation (FDI) in real-time systems can provide early warnings for faulty sensors and actuator signals to prevent events that lead to catastrophic failures. The main objective of this paper is to develop FDI and fault tolerant control techniques for base isolation systems with magneto-rheological (MR) dampers. Thus, this paper presents a fixed-order FDI filter design procedure based on linear matrix inequalities (LMI). The necessary and sufficient conditions for the existence of a solution for detecting and isolating faults using the H_{\\infty } formulation is provided in the proposed filter design. Furthermore, an FDI-filter-based fuzzy fault tolerant controller (FFTC) for a base isolation structure model was designed to preserve the pre-specified performance of the system in the presence of various unknown faults. Simulation and experimental results demonstrated that the designed filter can successfully detect and isolate faults from displacement sensors and accelerometers while maintaining excellent performance of the base isolation technology under faulty conditions.

  18. 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

  19. 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

  20. Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification

    NASA Technical Reports Server (NTRS)

    Wilson, Edward; Lages, Chris; Mah, Robert; Clancy, Daniel (Technical Monitor)

    2002-01-01

    When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The system uses only gyro signals to detect and identify hard, abrupt, single and multiple jet on- and off-failures. Faults are detected within one second and identified within one to five accords,

  1. Achieving Fault Detection and Performance on CMPs Gordon B. Bell, Member, IEEE, and Mikko H. Lipasti, Member, IEEE

    E-print Network

    Lipasti, Mikko H.

    is an attractive approach for improving a processor's capabilities for fault detection and fault toleranceAchieving Fault Detection and Performance on CMPs Gordon B. Bell, Member, IEEE, and Mikko H no longer be ignored. Several proposals have provided fault detec- tion and tolerance through redundantly

  2. Online sensor fault detection based on an improved strong tracking filter.

    PubMed

    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

  3. 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.

  4. An improved PCA method with application to boiler leak detection.

    PubMed

    Sun, Xi; Marquez, Horacio J; Chen, Tongwen; Riaz, Muhammad

    2005-07-01

    Principal component analysis (PCA) is a popular fault detection technique. It has been widely used in process industries, especially in the chemical industry. In industrial applications, achieving a sensitive system capable of detecting incipient faults, which maintains the false alarm rate to a minimum, is a crucial issue. Although a lot of research has been focused on these issues for PCA-based fault detection and diagnosis methods, sensitivity of the fault detection scheme versus false alarm rate continues to be an important issue. In this paper, an improved PCA method is proposed to address this problem. In this method, a new data preprocessing scheme and a new fault detection scheme designed for Hotelling's T2 as well as the squared prediction error are developed. A dynamic PCA model is also developed for boiler leak detection. This new method is applied to boiler water/steam leak detection with real data from Syncrude Canada's utility plant in Fort McMurray, Canada. Our results demonstrate that the proposed method can effectively reduce false alarm rate, provide effective and correct leak alarms, and give early warning to operators. PMID:16082787

  5. Fault-tolerant estimation

    Microsoft Academic Search

    Laurence H. Mutuel; Jason L. Speyer

    2000-01-01

    A fault-tolerant estimator is obtained from fusing the concept of fault detection with estimation. Two possible architectures are evaluated. At the center of the fault-tolerant estimation procedure is a bank of filters computing local state estimates, a residual screening scheme to isolate corrupted estimates and a method of blending untainted ones into a global minimum variance estimate, free of the

  6. Condition-based fault tree analysis (CBFTA): A new method for improved fault tree analysis (FTA), reliability and safety calculations

    Microsoft Academic Search

    Dan M. Shalev; Joseph Tiran

    2007-01-01

    Condition-based maintenance methods have changed systems reliability in general and individual systems in particular. Yet, this change does not affect system reliability analysis. System fault tree analysis (FTA) is performed during the design phase. It uses components failure rates derived from available sources as handbooks, etc. Condition-based fault tree analysis (CBFTA) starts with the known FTA. Condition monitoring (CM) methods

  7. Fault detection and isolation using interval analysis: application to vehicle monitoring

    Microsoft Academic Search

    P. Bouron; D. Meizel

    2000-01-01

    This paper gives an example of the use set membership techniques for detecting component fault and model failures and isolating the cause of the fault. Set membership estimation techniques can inherently detect model failure when the estimated set becomes empty. This property is here applied for fusing parity equations generated by an analytic redundancy study. For each parity equation, one

  8. Real time evaluation of DWT-based high impedance fault detection in EHV transmission

    Microsoft Academic Search

    Doaa khalil Ibrahim; El Sayed Tag Eldin; Essam M. Aboul-Zahab; Saber Mohamed Saleh

    2010-01-01

    It is possible to capture the required travelling wave information contained in fault transients using wavelet transform. This paper presents practical real time testing for the high impedance fault (HIF) detection algorithm based on real time accidents data. The proposed scheme is implemented for HIF detection in extra high voltage transmission lines. The classifier is based on an algorithm that

  9. Building Heterogeneous Models at Runtime to Detect Faults in Ambient-Intelligent

    E-print Network

    Paris-Sud XI, Université de

    Building Heterogeneous Models at Runtime to Detect Faults in Ambient-Intelligent Environments an approach for fault detection in ambient-intelligent environments. It proposes to compute predictions@run.time, models of com- putation, ambient intelligence 1 Introduction Ambient intelligence is a vision in which

  10. 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 aspect in the domain of advanced control of Waste Water Treatment Plants (WWTP) (Olsson & Newell 1999@dsi.unifi.it Automatic fault detection is becoming increasingly important in wastewater treatment plant operation, given

  11. Detecting Intrusion Faults in Remotely Controlled Systems Salvatore Candido and Seth Hutchinson

    E-print Network

    Hutchinson, Seth

    Detecting Intrusion Faults in Remotely Controlled Systems Salvatore Candido and Seth Hutchinson to a remote-controlled system (deemed an "intrusion fault" or "intrusion") despite attempts to conceal the intrusion. We propose adding a random perturbation to the control signal and using signal detection

  12. A Dynamic Threshold Approach to Fault Detection in Uninhabited Aerial Vehicles

    Microsoft Academic Search

    Andres E. Ortiz; Natasha A. Neogi

    The integration of UAVs into civil airspace is hampered by the inability to asses and guarantee safety and reliability properties of these systems. The paper outlines a software oriented approach for the real-time detection of faults in multi-modal hybrid systems. Online model generation of continuous variables enables the detection of multiple faults, while managing computational complexity. The aileron control loop

  13. Robust Modular Bulk Built-In Current Sensors for Detection of Transient Faults

    E-print Network

    Paris-Sud XI, Université de

    Robust Modular Bulk Built-In Current Sensors for Detection of Transient Faults Frank Sill Torres in CMOS nanometer technologies. Among the several approaches, Bulk Built-in Current Sensors (BBICS) offer of temperature and process parameters. Keywords: Built-in current sensors, concurrent detection, fault tolerance

  14. 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

  15. Model Based Fault Detection of an Electro-Hydraulic Cylinder Phanindra Garimella and Bin Yao

    E-print Network

    Yao, Bin

    on the swing-arm of a three degree of freedom hydraulic robot are presented to demonstrate the effectivenessModel Based Fault Detection of an Electro-Hydraulic Cylinder Phanindra Garimella and Bin Yao Abstract-- One of the key issues in the design of fault detection and diagnosis (FDD) schemes for hydraulic

  16. High impedance fault detection on rural electric distribution systems

    Microsoft Academic Search

    Jakov Vico; Mark Adamiak; Craig Wester; Ashish Kulshrestha

    2010-01-01

    A high impedance fault (HIF) results when an energized primary conductor comes in contact with a quasi-insulating object such as a tree, structure or equipment, or falls to the ground. The significance of these previously undetectable faults is that they represent a serious public safety hazard as well as a risk of arcing ignition of fires. A high impedance fault

  17. Probabilistic Model of Fault Detection in Quantum Circuits

    NASA Astrophysics Data System (ADS)

    Banerjee, A.; Pathak, A.

    Since the introduction of quantum computation, several protocols (such as quantum cryptography, quantum algorithm, quantum teleportation) have established quantum computing as a superior future technology. Each of these processes involves quantum circuits, which are prone to different kinds of faults. Consequently, it is important to verify whether the circuit hardware is defective or not. The systematic procedure to do so is known as fault testing. Normally testing is done by providing a set of valid input states and measuring the corresponding output states and comparing the output states with the expected output states of the perfect (fault less) circuit. This particular set of input vectors are known as test set [6]. If there exists a fault then the next step would be to find the exact location and nature of the defect. This is known as fault localization. A model that explains the logical or functional faults in the circuit is a fault model. Conventional fault models include (i) stuck at faults, (ii) bridge faults, and (iii) delay faults. These fault models have been rigorously studied for conventional irreversible circuit. But with the advent of reversible classical computing and quantum computing it has become important to enlarge the domain of the study on test vectors.

  18. 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.

  19. An Uncertainty-Based Distributed Fault Detection Mechanism for Wireless Sensor Networks

    PubMed Central

    Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

    2014-01-01

    Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio. PMID:24776937

  20. Online Fault Detection of Permanent Magnet Demagnetization for IPMSMs by Nonsingular Fast Terminal-Sliding-Mode Observer

    PubMed Central

    Zhao, Kai-Hui; Chen, Te-Fang; Zhang, Chang-Fan; He, Jing; Huang, Gang

    2014-01-01

    To prevent irreversible demagnetization of a permanent magnet (PM) for interior permanent magnet synchronous motors (IPMSMs) by flux-weakening control, a robust PM flux-linkage nonsingular fast terminal-sliding-mode observer (NFTSMO) is proposed to detect demagnetization faults. First, the IPMSM mathematical model of demagnetization is presented. Second, the construction of the NFTSMO to estimate PM demagnetization faults in IPMSM is described, and a proof of observer stability is given. The fault decision criteria and fault-processing method are also presented. Finally, the proposed scheme was simulated using MATLAB/Simulink and implemented on the RT-LAB platform. A number of robustness tests have been carried out. The scheme shows good performance in spite of speed fluctuations, torque ripples and the uncertainties of stator resistance. PMID:25490582

  1. Online fault detection of permanent magnet demagnetization for IPMSMs by nonsingular fast terminal-sliding-mode observer.

    PubMed

    Zhao, Kai-Hui; Chen, Te-Fang; Zhang, Chang-Fan; He, Jing; Huang, Gang

    2014-01-01

    To prevent irreversible demagnetization of a permanent magnet (PM) for interior permanent magnet synchronous motors (IPMSMs) by flux-weakening control, a robust PM flux-linkage nonsingular fast terminal-sliding-mode observer (NFTSMO) is proposed to detect demagnetization faults. First, the IPMSM mathematical model of demagnetization is presented. Second, the construction of the NFTSMO to estimate PM demagnetization faults in IPMSM is described, and a proof of observer stability is given. The fault decision criteria and fault-processing method are also presented. Finally, the proposed scheme was simulated using MATLAB/Simulink and implemented on the RT-LAB platform. A number of robustness tests have been carried out. The scheme shows good performance in spite of speed fluctuations, torque ripples and the uncertainties of stator resistance. PMID:25490582

  2. Method and system for fault accommodation of machines

    NASA Technical Reports Server (NTRS)

    Goebel, Kai Frank (Inventor); Subbu, Rajesh Venkat (Inventor); Rausch, Randal Thomas (Inventor); Frederick, Dean Kimball (Inventor)

    2011-01-01

    A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine. Control settings of the actual controller are adjusted, represented by the simulated controller, for controlling the actual machine, represented by the simulated machine, in response to a fault condition of the actual machine, based on the Pareto frontier-based solution space, to maximize desirable operational conditions and minimize undesirable operational conditions while operating the actual machine in a region of the solution space defined by the Pareto frontier.

  3. 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.

  4. Sensor fault detection for uninterruptible power supply (UPS) control system using fast fuzzy-neural network and immune network

    Microsoft Academic Search

    Shigeharu Taniguchi; Yasuhiko Dote

    2001-01-01

    In power electronic systems, many researchers have been investigating troubles caused by a sensor failure. Sensorless vector control of induction motor drives has attracted researchers' attention for a long time. The paper describes a sensor fault detection method for UPS current and voltage feedback systems. Once a certain sensor fails, then its influence propagates through the whole system and may

  5. Identification, Prediction and Detection of the Process Fault in a Cement Rotary Kiln by Locally Linear Neuro-Fuzzy Technique

    Microsoft Academic Search

    Masoud Sadeghian; Alireza Fatehi

    2009-01-01

    In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an

  6. 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.

  7. 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.

  8. Fault detection and identification based on combining logic and model in a wall-climbing robot

    Microsoft Academic Search

    Yong Jiang; Hongguang Wang; Lijin Fang; Mingyang Zhao

    2009-01-01

    A combined logic- and model-based approach to fault detection and identification (FDI) in a suction foot control system of\\u000a a wall-climbing robot is presented in this paper. For the control system, some fault models are derived by kinematics analysis.\\u000a Moreover, the logic relations of the system states are known in advance. First, a fault tree is used to analyze the

  9. Fault Detection and Prediction of Clocks and Timers Based on Computer Audition and Probabilistic Neural Networks

    Microsoft Academic Search

    S. Y. Chen; C. Y. Yao; G. Xiao; Y. S. Ying; W. L. Wang

    2005-01-01

    \\u000a This paper investigates the fault detection and prediction of rhythmically soniferous products, such as clocks, watches and\\u000a timers. Such products with fault cannot work steadily or probably cause malfunction. The authors extend the concept of computer\\u000a audition and establish an architectural model of product fault prediction system based on probabilistic neural networks. The\\u000a system listens to the product sound by

  10. Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

    NASA Technical Reports Server (NTRS)

    Litt, Jonathan; Kurtkaya, Mehmet; Duyar, Ahmet

    1994-01-01

    This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

  11. 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.).

  12. Model-based monitoring and fault diagnosis of fossil power plant process units using Group Method of Data Handling.

    PubMed

    Li, Fan; Upadhyaya, Belle R; Coffey, Lonnie A

    2009-04-01

    This paper presents an incipient fault diagnosis approach based on the Group Method of Data Handling (GMDH) technique. The GMDH algorithm provides a generic framework for characterizing the interrelationships among a set of process variables of fossil power plant sub-systems and is employed to generate estimates of important variables in a data-driven fashion. In this paper, ridge regression techniques are incorporated into the ordinary least squares (OLS) estimator to solve regression coefficients at each layer of the GMDH network. The fault diagnosis method is applied to feedwater heater leak detection with data from an operating coal-fired plant. The results demonstrate the proposed method is capable of providing an early warning to operators when a process fault or an equipment fault occurs in a fossil power plant. PMID:19084227

  13. High impedance fault detection methodology using wavelet transform and artificial neural networks

    Microsoft Academic Search

    Ibrahem Baqui; Inmaculada Zamora; Javier Mazón; Garikoitz Buigues

    2011-01-01

    This paper presents a new technique based on the combination of wavelet transform (WT) and artificial neural networks (ANNs) for addressing the problem of high impedance faults (HIFs) detection in electrical distribution feeders. The change in phase current waveforms caused by faults and normal switching events has been used in this methodology. The discrete wavelet transform (DWT) used decomposes the

  14. Adaptive Kalman filter and neural network based high impedance fault detection in power distribution networks

    Microsoft Academic Search

    S. R. Samantaray; P. K. Dash; S. K. Upadhyay

    2009-01-01

    This paper presents an intelligent approach for high impedance fault (HIF) detection in power distribution feeders using combined Adaptive Extended Kalman Filter (AEKF) and probabilistic neural network (PNN). The AEKF is used to estimate the different harmonic components in HIF and NF (no-fault) current signals accurately under non-linear loading condition. The estimated harmonic components are used as features to train

  15. 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

  16. 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.

  17. 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.

  18. Timing Issues of Transient Faults in Concurrent Error Detection Schemes

    E-print Network

    Paris-Sud XI, Université de

    or even intentional perturbation events. These effects ­ so-called transient faults (TFs) ­ are able-fabrication deeper- submicron technologies as well as novel classes of malicious fault injection-based attacks ­ e in this paper that timing features of a short-duration STF in logic circuits can actually provoke harmful

  19. 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

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

    SciTech Connect

    Sultan, F.F.; Swift, G.W. (Univ. of Manitoba, Dept. of Electrical and Computer Engineering, Winnipeg, Manitoba R3T 2N2 (Canada)); Fedirchuk, D.J. (Manitoba Hydro, System Operation Dept., Winnipeg, Manitoba R3C 2P4 (Canada))

    1992-10-01

    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 of normal load current disturbed by currents of faults on dry and wet soil, an arc welder, computers, and fluorescent lights.

  1. 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.

  2. Hypothesis Testing and Decision Theoretic Approach for Fault Detection in Wireless Sensor Networks

    E-print Network

    Nandi, Mrinal; Roy, Bimal; Sarkar, Santanu

    2012-01-01

    Sensor networks aim at monitoring their surroundings for event detection and object tracking. But due to failure or death of sensors, false signal can be transmitted. In this paper, we consider the problem of fault detection in wireless sensor network (WSN), in particular, addressing both the noise-related measurement error and sensor fault simultaneously in fault detection. We assume that the sensors are placed at the center of a square (or hexagonal) cell in region of interest (ROI) and, if the event occurs, it occurs at a particular cell of the ROI. We propose fault detection schemes that take into account error probabilities into the optimal event detection process. We develop the schemes under the consideration of Neyman-Pearson test and Bayes test.

  3. 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

  4. Three-dimensional Distinct Element Method (DEM) modelling of oblique-slip normal faulting

    NASA Astrophysics Data System (ADS)

    Schöpfer, Martin; Childs, Conrad; Manzocchi, Tom; Walsh, John

    2014-05-01

    Normal faults frequently exhibit a strike-slip displacement component, which can arise for example from oblique reactivation or from fault strike changes, e.g. along bends. It is well known from both natural examples and analogue experiments that fault zones developing above oblique normal faults are typically comprised of systematically stepping fault segments. However, dependencies of fault segment orientation and segmentation on fault obliquity and mechanical properties during faulting are poorly understood. For example, it is not clear whether systematically stepping fault segments link preferentially via footwall or hanging wall breaching. Moreover, the persistence of fault bends throughout mechanically layered sequences is another yet unexplored topic. Here we use three-dimensional Distinct Element Method (DEM) modelling to elucidate the geometry and kinematics of fault zones developing above oblique normal faults. We systematically vary both fault obliquity and confining pressure. Fault zone structure (e.g. segment orientations, drag, etc.) is quantified from horizon maps generated at different levels within the model. Irrespective of fault obliquity, fault zones become better localised with increasing confining pressure. Analysis of displacement partitioning at branch-points illustrates that neither footwall nor hanging wall breaching is the preferred mode of segment linkage. Fault segment orientations exhibit a systematic fault obliquity dependence, which can be rationalised using infinitesimal strain theory for transtensional shear zones. Our models therefore suggest that the orientation of fault segments developing above oblique normal faults may be used to estimate the extension direction, as suggested nearly 30 years ago by A.M. McCoss [1986, J. Struct. Geol. 8(6), p. 715-718].

  5. 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.

  6. Nucleic Acid Detection Methods

    DOEpatents

    Smith, Cassandra L. (Boston, MA); Yaar, Ron (Brookline, MA); Szafranski, Przemyslaw (Boston, MA); Cantor, Charles R. (Boston, MA)

    1998-05-19

    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 easily distinguish from nuclease uncleaved heteroduplexes by differential labeling. Probes and target can be differentially labeled with detectable labels. Matched target can be detected by cleaving resulting loops from the hybridized target and creating free 3-hydroxyl groups. These groups are recognized and extended by polymerases added into the reaction system which also adds or releases one label into solution. Analysis of the resulting products using either solid phase or solution. These methods can be used to detect characteristic nucleic acid sequences, to determine target sequence and to screen for genetic defects and disorders. Assays can be conducted on solid surfaces allowing for multiple reactions to be conducted in parallel and, if desired, automated.

  7. Nucleic acid detection methods

    DOEpatents

    Smith, C.L.; Yaar, R.; Szafranski, P.; Cantor, C.R.

    1998-05-19

    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{prime}-hydroxyl groups extended with a nucleic acid polymerase. Nuclease cleaved heteroduplexes can be easily distinguish from nuclease uncleaved heteroduplexes by differential labeling. Probes and target can be differentially labeled with detectable labels. Matched target can be detected by cleaving resulting loops from the hybridized target and creating free 3-hydroxyl groups. These groups are recognized and extended by polymerases added into the reaction system which also adds or releases one label into solution. Analysis of the resulting products using either solid phase or solution. These methods can be used to detect characteristic nucleic acid sequences, to determine target sequence and to screen for genetic defects and disorders. Assays can be conducted on solid surfaces allowing for multiple reactions to be conducted in parallel and, if desired, automated. 18 figs.

  8. 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.

  9. 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

  10. a New Online Distributed Process Fault Detection and Isolation Approach Using Potential Clustering Technique

    NASA Astrophysics Data System (ADS)

    Bahrampour, Soheil; Moshiri, Behzad; Salahshoor, Karim

    2009-08-01

    Most of process fault monitoring systems suffer from offline computations and confronting with novel faults that limit their applicabilities. This paper presents a new online fault detection and isolation (FDI) algorithm based on distributed online clustering approach. In the proposed approach, clustering algorithm is used for online detection of a new trend of time series data which indicates faulty condition. On the other hand, distributed technique is used to decompose the overall monitoring task into a series of local monitoring sub-tasks so as to locally track and capture the process faults. This algorithm not only solves the problem of online FDI, but also can handle novel faults. The diagnostic performances of the proposed FDI approach is evaluated on the Tennessee Eastman process plant as a large-scale benchmark problem.

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

    PubMed

    Zhao, Jinsong; Huang, Jianchao; Sun, Wei

    2008-11-01

    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. PMID:18255276

  12. 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).

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

    E-print Network

    , Hadamard gate, Quantum decoherence, undetectable faults, quan- tum computer hardware INTRODUCTIONc DRAFT Probability of detecting single faults in Hadamard and SWAP gates of a quantum computer is the main factor which causes fault in a quantum computer. In this article, the probability of detecting

  14. Identifiability of Additive Actuator and Sensor Faults by State Augmentation

    NASA Technical Reports Server (NTRS)

    Joshi, Suresh; Gonzalez, Oscar R.; Upchurch, Jason M.

    2014-01-01

    A class of fault detection and identification (FDI) methods for bias-type actuator and sensor faults is explored in detail from the point of view of fault identifiability. The methods use state augmentation along with banks of Kalman-Bucy filters for fault detection, fault pattern determination, and fault value estimation. A complete characterization of conditions for identifiability of bias-type actuator faults, sensor faults, and simultaneous actuator and sensor faults is presented. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have unknown biases. The fault identifiability conditions are demonstrated via numerical examples. The analytical and numerical results indicate that caution must be exercised to ensure fault identifiability for different fault patterns when using such methods.

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

    E-print Network

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

    2004-01-01

    signal conditions. E- AANNs are capable of detecting and isolating sensor faults even when the data is noisy. To locate faulty sensors in noisy situations, the difference between the E-AANN input and output must be evaluated in a range of time domain...- INTRODUCTION When sensors malfunction, control systems become unreliable. Even with the most sophisticated instruments and control algorithms, a control decision based on faulty data will likely lead to incorrect control actions. ?Sensor Fault Detection...

  16. Model-based nuclear power plant monitoring and fault detection: Theoretical foundations

    Microsoft Academic Search

    R. M. Singer; K. C. Gross; J. P. Herzog; R. W. King; S. Wegerich

    1997-01-01

    The theoretical basis and validation studies of a real-time, model-based process monitoring and fault detection system is presented. Through use of a non-linear state estimation technique coupled with a probabilistically-based statistical hypothesis test, it is possible to detect and identify sensor, component and process faults at extremely early times from changes in the stochastic characteristics of measured signals. Data from

  17. SVFD: A Versatile Online Fault Detection Scheme via Checking of Stability Violation

    Microsoft Academic Search

    Guihai Yan; Yinhe Han; Xiaowei Li

    2011-01-01

    In ultra-deep submicrometer technology, soft errors and device aging are two of the paramount reliability concerns. Al- though many studies have been done to tackle the two challenges, most take them separately so far, thereby failing to reach better performance-cost tradeoffs. To support a more efficient design tradeoff, we propose a unified fault detection scheme—stability violation-based fault detection (SVFD), by

  18. Integrated design of an observer-based fault detection system over unreliable digital channels

    Microsoft Academic Search

    Wei Li; Steven X. Ding

    2008-01-01

    In this paper, the observer-based fault detection problem over an unreliable digital channel is studied. The channel qualities, which are usually called Quality of Service (QoS), i.e. packet loss probability and quantization error, are first analyzed in the view of control engineering, and they are transferred into stochastic parameters and system uncertainties. Then it is shown that the fault detection

  19. Fault detection and diagnosis of induction motors using motor current signature analysis and a hybrid FMM-CART model.

    PubMed

    Seera, Manjeevan; Lim, Chee Peng; Ishak, Dahaman; Singh, Harapajan

    2012-01-01

    In this paper, a novel approach to detect and classify comprehensive fault conditions of induction motors using a hybrid fuzzy min-max (FMM) neural network and classification and regression tree (CART) is proposed. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. A series of real experiments is conducted, whereby the motor current signature analysis method is applied to form a database comprising stator current signatures under different motor conditions. The signal harmonics from the power spectral density are extracted as discriminative input features for fault detection and classification with FMM-CART. A comprehensive list of induction motor fault conditions, viz., broken rotor bars, unbalanced voltages, stator winding faults, and eccentricity problems, has been successfully classified using FMM-CART with good accuracy rates. The results are comparable, if not better, than those reported in the literature. Useful explanatory rules in the form of a decision tree are also elicited from FMM-CART to analyze and understand different fault conditions of induction motors. PMID:24808459

  20. Robust Fault Detection for Aircraft Using Mixed Structured Singular Value Theory and Fuzzy Logic

    NASA Technical Reports Server (NTRS)

    Collins, Emmanuel G.

    2000-01-01

    The purpose of fault detection is to identify when a fault or failure has occurred in a system such as an aircraft or expendable launch vehicle. The faults may occur in sensors, actuators, structural components, etc. One of the primary approaches to model-based fault detection relies on analytical redundancy. That is the output of a computer-based model (actually a state estimator) is compared with the sensor measurements of the actual system to determine when a fault has occurred. Unfortunately, the state estimator is based on an idealized mathematical description of the underlying plant that is never totally accurate. As a result of these modeling errors, false alarms can occur. This research uses mixed structured singular value theory, a relatively recent and powerful robustness analysis tool, to develop robust estimators and demonstrates the use of these estimators in fault detection. To allow qualitative human experience to be effectively incorporated into the detection process fuzzy logic is used to predict the seriousness of the fault that has occurred.

  1. 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...

  2. 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.

  3. A Fuzzy Reasoning Design for Fault Detection and Diagnosis of a Computer-Controlled System.

    PubMed

    Ting, Y; Lu, W B; Chen, C H; Wang, G K

    2008-03-01

    A Fuzzy Reasoning and Verification Petri Nets (FRVPNs) model is established for an error detection and diagnosis mechanism (EDDM) applied to a complex fault-tolerant PC-controlled system. The inference accuracy can be improved through the hierarchical design of a two-level fuzzy rule decision tree (FRDT) and a Petri nets (PNs) technique to transform the fuzzy rule into the FRVPNs model. Several simulation examples of the assumed failure events were carried out by using the FRVPNs and the Mamdani fuzzy method with MATLAB tools. The reasoning performance of the developed FRVPNs was verified by comparing the inference outcome to that of the Mamdani method. Both methods result in the same conclusions. Thus, the present study demonstratrates that the proposed FRVPNs model is able to achieve the purpose of reasoning, and furthermore, determining of the failure event of the monitored application program. PMID:19255619

  4. Fault detection and isolation of aircraft air data/inertial system

    NASA Astrophysics Data System (ADS)

    Berdjag, D.; Cieslak, J.; Zolghadri, A.

    2013-12-01

    A method for failure detection and isolation (FDI) for redundant aircraft sensors is presented. The outputs of the concerned sensors are involved in the computation of flight control laws, and the objective is to eliminate any fault before propagation in the control loop when selecting a unique flight parameter among a set (generally, three) of redundant measurements. The particular case of an oscillatory failure is investigated. The proposed method allows an accurate FDI of erroneous sensor and computes a consolidated parameter based on the fusion of data from remaining valid sensors. The benefits of the presented method are to enhance the data fusion process with FDI techniques which improve the performance of the fusion when only few sources (less than three) are initially valid.

  5. Detecting seismogenic stress evolution and constraining fault zone rheology in the San Andreas Fault following

    E-print Network

    Niu, Fenglin

    Fault following the 2004 Parkfield earthquake Taka'aki Taira,1 Paul G. Silver,1 Fenglin Niu,2 and Robert scatterers exhibiting clear time dependence, using pairs of earthquakes that span or follow the 2004.3, a value that is more consistent with ductile behavior, rather than frictional sliding, at the base

  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. Holocene paleoearthquakes of the Daqingshan fault detected from knickpoint identification and alluvial soil profile

    NASA Astrophysics Data System (ADS)

    He, Zhongtai; Ma, Baoqi

    2015-02-01

    Are there any effective methods to reveal paleoearthquakes on normal faults except traditional trenching technique? In this paper, we study Holocene paleoearthquakes of the Daqingshan fault which is a normal fault along the Daqingshan piedmont of Inner Mongolia in China. We identify knickpoints from stream profiles and study alluvial soil profiles to reconstruct the Holocene paleoearthquakes of the fault. From the fault's footwall we extract 25 gullies from IRS-P5 DEM data, and identify knickpoints in the profile that result from fault motion disturbing each channel. We combine the retreat distances and the knickpoint retreat rates to determine each knickpoint's forming time. We study alluvial fan outcrops that contain various paleosol sequences. As three distinct Holocene paleosols developed in the Daqingshan piedmont alluvial fans, we assume that the soil profile development was interrupted by fault activity preserved by interbedded gravel between the paleosols. The gravel layer between two adjacent paleosol layers represents material transported there after a paleoseismic event. Thus we date paleosol layers which are above and below the gravel layer to constrain paleoseismic events. Since trenches had been made by our predecessors along the fault to reveal the Holocene paleoearthquakes, we identify the Holocene paleoearthquake records from both sides of the fault, and then compare the results with the results from the trenches. The final result demonstrates that the knickpoints' sequence in the footwall and the paleosols' ages in the hanging wall correspond very closely with the Holocene paleoearthquakes along the Daqingshan piedmont fault. Methods in this paper have future application value to study paleoearthquakes on other normal faults with similar structure to the Daqingshan fault.

  8. Low current and flashing HIF detection method

    Microsoft Academic Search

    Dominik Bak; Waldemar Rebizant

    2011-01-01

    High Impedance Faults (HIFs) can differ one from another enormously starting from single flashes through arcing faults to permanent ones. New approach to HIF detection is presented in this paper allowing for identification of two latter ones. The novel protection methodology - 3D power protection scheme (3DPPS) was developed to do the job. The proposed solution is fully adaptive and

  9. Magnetometric and gravimetric surveys in fault detection over Acambay System

    NASA Astrophysics Data System (ADS)

    García-Serrano, A.; Sanchez-Gonzalez, J.; Cifuentes-Nava, G.

    2013-05-01

    In commemoration of the centennial of the Acambay intraplate earthquake of November 19th 1912, we carry out gravimetric and magnetometric surveys to define the structure of faults caused by this event. The study area is located approximately 11 km south of Acambay, in the Acambay-Tixmadeje fault system, where we performed two magnetometric surveys, the first consisting of 17 lines with a spacing of 35m between lines and 5m between stations, and the second with a total of 12 lines with the same spacing, both NW. In addition to these two lines we performed gravimetric profiles located in the central part of each magnetometric survey, with a spacing of 25m between stations, in order to correlate the results of both techniques, the lengths of such profiles were of 600m and 550m respectively. This work describes the data processing including directional derivatives, analytical signal and inversion, by means of which we obtain results of magnetic variations and anomaly traits highly correlated with those faults. It is of great importance to characterize these faults given the large population growth in the area and settlement houses on them, which involves a high risk in the security of the population, considering that these are active faults and cannot be discard earthquakes associated with them, so it is necessary for the authorities and people have relevant information to these problem.

  10. 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.

  11. 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.

  12. Tacholess Envelope Order Analysis and Its Application to Fault Detection of Rolling Element Bearings with Varying Speeds

    PubMed Central

    Zhao, Ming; Lin, Jing; Xu, Xiaoqiang; Lei, Yaguo

    2013-01-01

    Vibration analysis is an effective tool for the condition monitoring and fault diagnosis of rolling element bearings. Conventional diagnostic methods are based on the stationary assumption, thus they are not applicable to the diagnosis of bearings working under varying speed. This constraint limits the bearing diagnosis to the industrial application significantly. In order to extend the conventional diagnostic methods to speed variation cases, a tacholess envelope order analysis technique is proposed in this paper. In the proposed technique, a tacholess order tracking (TLOT) method is first introduced to extract the tachometer information from the vibration signal itself. On this basis, an envelope order spectrum (EOS) is utilized to recover the bearing characteristic frequencies in the order domain. By combining the advantages of TLOT and EOS, the proposed technique is capable of detecting bearing faults under varying speeds, even without the use of a tachometer. The effectiveness of the proposed method is demonstrated by both simulated signals and real vibration signals collected from locomotive roller bearings with faults on inner race, outer race and rollers, respectively. Analyzed results show that the proposed method could identify different bearing faults effectively and accurately under speed varying conditions. PMID:23959244

  13. Study on fault diagnostic strategy of intelligent magnetic detection microsystems

    Microsoft Academic Search

    Yongqiang Wang; Wenzhong Lou; Ningjun Fan; Jianwei Hao; Dayin Zhang

    2009-01-01

    Intelligent Magnetic Detection Microsystems (IMDM) are complex microsystems, which are used to obtain the information of motor\\u000a flux and speed in single-driveway traffic system; the microsystems have to fulfill the task in a harsh environment of field,\\u000a which would infect the reliability of system. An effective method to ensure maintenance cost and reliability is to integrate\\u000a efficient built-in-test and monitoring

  14. Robust Fault Detection Using Robust Z1 Estimation and Fuzzy Logic

    NASA Technical Reports Server (NTRS)

    Curry, Tramone; Collins, Emmanuel G., Jr.; Selekwa, Majura; Guo, Ten-Huei (Technical Monitor)

    2001-01-01

    This research considers the application of robust Z(sub 1), estimation in conjunction with fuzzy logic to robust fault detection for an aircraft fight control system. It begins with the development of robust Z(sub 1) estimators based on multiplier theory and then develops a fixed threshold approach to fault detection (FD). It then considers the use of fuzzy logic for robust residual evaluation and FD. Due to modeling errors and unmeasurable disturbances, it is difficult to distinguish between the effects of an actual fault and those caused by uncertainty and disturbance. Hence, it is the aim of a robust FD system to be sensitive to faults while remaining insensitive to uncertainty and disturbances. While fixed thresholds only allow a decision on whether a fault has or has not occurred, it is more valuable to have the residual evaluation lead to a conclusion related to the degree of, or probability of, a fault. Fuzzy logic is a viable means of determining the degree of a fault and allows the introduction of human observations that may not be incorporated in the rigorous threshold theory. Hence, fuzzy logic can provide a more reliable and informative fault detection process. Using an aircraft flight control system, the results of FD using robust Z(sub 1) estimation with a fixed threshold are demonstrated. FD that combines robust Z(sub 1) estimation and fuzzy logic is also demonstrated. It is seen that combining the robust estimator with fuzzy logic proves to be advantageous in increasing the sensitivity to smaller faults while remaining insensitive to uncertainty and disturbances.

  15. Practical Methods for Estimating Software Systems Fault Content and Location

    NASA Technical Reports Server (NTRS)

    Nikora, A.; Schneidewind, N.; Munson, J.

    1999-01-01

    Over the past several years, we have developed techniques to discriminate between fault-prone software modules and those that are not, to estimate a software system's residual fault content, to identify those portions of a software system having the highest estimated number of faults, and to estimate the effects of requirements changes on software quality.

  16. 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

  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. Robust Asynchronous Algorithms in Networks with a Fault Detection Ring

    Microsoft Academic Search

    Moshe Molcho; Shmuel Zaks

    1994-01-01

    In this paper we study asynchronous networks, in which processors may fail and recover several times during an execution. Upon recovery a processor rejoins the execution as a passive processor, with all variables initialized, except for a fault flag, which is updated by the system. In addition to the regular communication links connecting pairs of processors, the processors are connected

  19. Automatic and Scalable Fault Detection for Mobile Applications

    E-print Network

    Gummadi, Ramakrishna

    , implementation, and evaluation of VanarSena, an automated fault finder for mobile applications ("apps- ability. For mobile apps, improving reliability is less about making sure that "mission critical" software of reviews on mo- bile app stores shows that an app that crashes is likely to garner poor reviews. Mobile app

  20. 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

  1. 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.

  2. Fault diagnosis of rotating machinery with a novel statistical feature extraction and evaluation method

    NASA Astrophysics Data System (ADS)

    Li, Wei; Zhu, Zhencai; Jiang, Fan; Zhou, Gongbo; Chen, Guoan

    2015-01-01

    Fault diagnosis of rotating machinery is receiving more and more attentions. Vibration signals of rotating machinery are commonly analyzed to extract features of faults, and the features are identified with classifiers, e.g. artificial neural networks (ANNs) and support vector machines (SVMs). Due to nonlinear behaviors and unknown noises in machinery, the extracted features are varying from sample to sample, which may result in false classifications. It is also difficult to analytically ensure the accuracy of fault diagnosis. In this paper, a feature extraction and evaluation method is proposed for fault diagnosis of rotating machinery. Based on the central limit theory, an extraction procedure is given to obtain the statistical features with the help of existing signal processing tools. The obtained statistical features approximately obey normal distributions. They can significantly improve the performance of fault classification, and it is verified by taking ANN and SVM classifiers as examples. Then the statistical features are evaluated with a decoupling technique and compared with thresholds to make the decision on fault classification. The proposed evaluation method only requires simple algebraic computation, and the accuracy of fault classification can be analytically guaranteed in terms of the so-called false classification rate (FCR). An experiment is carried out to verify the effectiveness of the proposed method, where the unbalanced fault of rotor, inner race fault, outer race fault and ball fault of bearings are considered.

  3. Concurrent Fault Detection for Secure QDI Asynchronous Circuits Konrad J. Kulikowski, Mark G. Karpovsky, Alexander Taubin, Zhen Wang

    E-print Network

    Karpovsky, Mark

    advantages in providing protection against power, EMI, timing, and fault attacks [6]. Based on these trends designs. In this paper we investigate effects of faults and errors of secure asynchronous quasi delayConcurrent Fault Detection for Secure QDI Asynchronous Circuits Konrad J. Kulikowski, Mark G

  4. A ship propulsion system as a benchmark for fault-tolerant control

    Microsoft Academic Search

    Roozbeh Izadi-Zamanabadi; Mogens Blanke

    1999-01-01

    Fault-tolerant control combines fault detection and isolation techniques with supervisory control, to achieve the autonomous accommodation of faults before they develop into failures. While fault detection and isolation (FDI) methods have matured during the past decade, the extension to fault-tolerant control is a fairly new area. This paper presents a ship propulsion system as a benchmark that should be useful

  5. Laser ultrasound technology for fault detection on carbon fiber composites

    NASA Astrophysics Data System (ADS)

    Seyrkammer, Robert; Reitinger, Bernhard; Grün, Hubert; Sekelja, Jakov; Burgholzer, Peter

    2014-05-01

    The marching in of carbon fiber reinforced polymers (CFRPs) to mass production in the aeronautic and automotive industry requires reliable quality assurance methods. Laser ultrasound (LUS) is a promising nondestructive testing technique for sample inspection. The benefits compared to conventional ultrasound (US) testing are couplant free measurements and an easy access to complex shapes due to remote optical excitation and detection. Here the potential of LUS is present on composite test panels with relevant testing scenarios for industry. The results are evaluated in comparison to conventional ultrasound used in the aeronautic industry.

  6. Fault detection and isolation using sliding mode observer for uncertain Takagi-Sugeno fuzzy model

    E-print Network

    Paris-Sud XI, Université de

    Fault detection and isolation using sliding mode observer for uncertain Takagi-Sugeno fuzzy model detection and isolation (FDI) problem using a sliding mode fuzzy observer on the basis of a uncertain Takagi to synthesis observers using a set of linear matrix inequalities (LMI) conditions. Once the fuzzy observer

  7. A study of fault detection and system reconfiguration for UAV navigation system bon RBF neural network

    Microsoft Academic Search

    Yuan Dongli; Yan Jianguo; Xi Qingbiao

    2008-01-01

    In the field of aeronautics and astronautics, the guidance and navigation system play so important role that it will bring huge loss once that system do wrong. Accordingly, besides detecting carefully and completely on the ground, after in the air, it is quite necessary to detect real time and take corresponding measure when the fault is found. Due to the

  8. Design of a video system to detect and sort the faults of cigarette package

    Microsoft Academic Search

    Wenping He; Chao Qiu; Dexian Zhang

    2008-01-01

    A hardware flatform detecting and sorting the faults of cigarette package is designed by using the technology of machine vision. Algorithm and systemic software are also designed according to its characteristics. With stability and accuracy it is of some guiding value to the high speed on-line package detection.

  9. Interval-based Fault Detection and Identification applied to Global Positioning

    E-print Network

    Paris-Sud XI, Université de

    Interval-based Fault Detection and Identification applied to Global Positioning Vincent Drevelle a real-time robust positioning system based on interval analysis and constraint propagation that computes position domains, and that is able to detect and reject erroneous measurements. GPS pseudorange

  10. Fault Detection and Isolation in the Non-Toxic Orbital Maneuvering System and the Reaction Control System

    Microsoft Academic Search

    Mohammad Azam; David Pham; Fang Tu; Krishna Pattipati; Ann Patterson-Hine; Lui Wang

    In this paper, we consider the problem of test design for real-time fault detection and diagnosis in the space shuttle's non-toxic orbital maneuvering system and reaction control sys- tem (NT-OMS\\/RCS). For demonstration purposes, we restrict our attention to the aft section of the NT-OMS\\/RCS, which consists of 160 faults (each fault being either a leakage, blockage, igniter fault, or regulator

  11. Tuning and comparing fault diagnosis methods for aeronautical systems via kriging-based optimization

    NASA Astrophysics Data System (ADS)

    Marzat, J.; Piet-Lahanier, H.; Damongeot, F.; Walter, E.

    2013-12-01

    Many approaches address fault detection and isolation (FDI) based on analytical redundancy. To rank them, it is necessary to define performance indices and realistic sets of test cases on which they will be evaluated. For the ranking to be fair, each of the methods under consideration should have its internal parameters tuned optimally. The work presented uses a combination of tools developed in the context of computer experiments to achieve this tuning from a limited number of numerical evaluations. The methodology is then extended so as to provide a robust tuning in the worst-case sense.

  12. Helium isotopes as a tool for detecting concealed active faults

    Microsoft Academic Search

    Koji Umeda; Atusi Ninomiya

    2009-01-01

    A magnitude (Mj) 7.3 crustal earthquake occurred in the western Tottori area, southwest Japan, on 6 October 2000. However, there was no obvious prefaulting indication at surface of a fault corresponding to the western Tottori earthquake in 2000. This study was undertaken to elucidate the geographic distribution of 3He\\/4He ratios around the seismic source region using helium isotope data obtained

  13. Neural net application to transmission line fault detection and classification

    E-print Network

    Rikalo, Igor

    1994-01-01

    and content y: f i r Mladen Kezunovic (Chair of Committee) Ali Abur (Member) ) Karan L. Watson (Member) William . Lively (Member) Alton D. Patton (Head of Department) December 1994 Major Subject. Electrical Engineering ABSTRACT Neural Net.... Problem Statement This thesis is related to the application of neural networks (NNs) in the field of transmission line fault monitoring and analysis. The adjective neural is used mostly as an inspiration from biology and partly because of historical...

  14. Preliminary Study on Acoustic Detection of Faults Experienced by a High-Bypass Turbofan Engine

    NASA Technical Reports Server (NTRS)

    Boyle, Devin K.

    2014-01-01

    The vehicle integrated propulsion research (VIPR) effort conducted by NASA and several partners provided an unparalleled opportunity to test a relatively low TRL concept regarding the use of far field acoustics to identify faults occurring in a high bypass turbofan engine. Though VIPR Phase II ground based aircraft installed engine testing wherein a multitude of research sensors and methods were evaluated, an array of acoustic microphones was used to determine the viability of such an array to detect failures occurring in a commercially representative high bypass turbofan engine. The failures introduced during VIPR testing included commanding the engine's low pressure compressor (LPC) exit and high pressure compressor (HPC) 14th stage bleed values abruptly to their failsafe positions during steady state

  15. 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

  16. 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

  17. 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.

  18. 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...

  19. 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.

  20. Online motor fault detection and diagnosis using a hybrid FMM-CART model.

    PubMed

    Seera, Manjeevan; Lim, Chee Peng

    2014-04-01

    In this brief, a hybrid model combining the fuzzy min-max (FMM) neural network and the classification and regression tree (CART) for online motor detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. To evaluate the applicability of the proposed FMM-CART model, an evaluation with a benchmark data set pertaining to electrical motor bearing faults is first conducted. The results obtained are equivalent to those reported in the literature. Then, a laboratory experiment for detecting and diagnosing eccentricity faults in an induction motor is performed. In addition to producing accurate results, useful rules in the form of a decision tree are extracted to provide explanation and justification for the predictions from FMM-CART. The experimental outcome positively shows the potential of FMM-CART in undertaking online motor fault detection and diagnosis tasks. PMID:24807956

  1. Early detection of incipient faults in power plants using accelerated neural network learning

    SciTech Connect

    Parlos, A.G.; Jayakumar, M. (Texas A M Univ., College Station (United States)); Atiya, A. (Qantixx, Inc., Houston, TX (United States))

    1992-01-01

    An important aspect of power plant automation is the development of computer systems able to detect and isolate incipient (slowly developing) faults at the earliest possible stages of their occurrence. In this paper, the development and testing of such a fault detection scheme is presented based on recognition of sensor signatures during various failure modes. An accelerated learning algorithm, namely adaptive backpropagation (ABP), has been developed that allows the training of a multilayer perceptron (MLP) network to a high degree of accuracy, with an order of magnitude improvement in convergence speed. An artificial neural network (ANN) has been successfully trained using the ABP algorithm, and it has been extensively tested with simulated data to detect and classify incipient faults of various types and severity and in the presence of varying sensor noise levels.

  2. Fault and dyke detectability in high resolution seismic surveys for coal: a view from numerical modelling*

    NASA Astrophysics Data System (ADS)

    Zhou, Binzhong 13Hatherly, Peter

    2014-10-01

    Modern underground coal mining requires certainty about geological faults, dykes and other structural features. Faults with throws of even just a few metres can create safety issues and lead to costly delays in mine production. In this paper, we use numerical modelling in an ideal, noise-free environment with homogeneous layering to investigate the detectability of small faults by seismic reflection surveying. If the layering is horizontal, faults with throws of 1/8 of the wavelength should be detectable in a 2D survey. In a coal mining setting where the seismic velocity of the overburden ranges from 3000 m/s to 4000 m/s and the dominant seismic frequency is ~100 Hz, this corresponds to a fault with a throw of 4-5 m. However, if the layers are dipping or folded, the faults may be more difficult to detect, especially when their throws oppose the trend of the background structure. In the case of 3D seismic surveying we suggest that faults with throws as small as 1/16 of wavelength (2-2.5 m) can be detectable because of the benefits offered by computer-aided horizon identification and the improved spatial coherence in 3D seismic surveys. With dykes, we find that Berkhout's definition of the Fresnel zone is more consistent with actual experience. At a depth of 500 m, which is typically encountered in coal mining, and a 100 Hz dominant seismic frequency, dykes less than 8 m in width are undetectable, even after migration.

  3. 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

  4. The Marshall Space Flight Center Fault Detection Diagnosis and Recovery Laboratory

    NASA Technical Reports Server (NTRS)

    Burchett, Bradley T.; Gamble, Jonathan; Rabban, Michael

    2008-01-01

    The Fault Detection Diagnosis and Recovery Lab (FDDR) has been developed to support development of,fault detection algorithms for the flight computer aboard the Ares I and follow-on vehicles. It consists of several workstations using Ethernet and TCP/IP to simulate communications between vehicle sensors, flight computers, and ground based support computers. Isolation of tasks between workstations was set up intentionally to limit information flow and provide a realistic simulation of communication channels within the vehicle and between the vehicle and ground station.

  5. Shallow Faulting in Morelia, Mexico, Based on Seismic Tomography and Geodetically Detected Land Subsidence

    NASA Astrophysics Data System (ADS)

    Cabral-Cano, E.; Arciniega-Ceballos, A.; Vergara-Huerta, F.; Chaussard, E.; Wdowinski, S.; DeMets, C.; Salazar-Tlaczani, L.

    2013-12-01

    Subsidence has been a common occurrence in several cities in central Mexico for the past three decades. This process causes substantial damage to the urban infrastructure and housing in several cities and it is a major factor to be considered when planning urban development, land-use zoning and hazard mitigation strategies. Since the early 1980's the city of Morelia in Central Mexico has experienced subsidence associated with groundwater extraction in excess of natural recharge from rainfall. Previous works have focused on the detection and temporal evolution of the subsidence spatial distribution. The most recent InSAR analysis confirms the permanence of previously detected rapidly subsiding areas such as the Rio Grande Meander area and also defines 2 subsidence patches previously undetected in the newly developed suburban sectors west of Morelia at the Fraccionamiento Del Bosque along, south of Hwy. 15 and another patch located north of Morelia along Gabino Castañeda del Rio Ave. Because subsidence-induced, shallow faulting develops at high horizontal strain localization, newly developed a subsidence areas are particularly prone to faulting and fissuring. Shallow faulting increases groundwater vulnerability because it disrupts discharge hydraulic infrastructure and creates a direct path for transport of surface pollutants into the underlying aquifer. Other sectors in Morelia that have been experiencing subsidence for longer time have already developed well defined faults such as La Colina, Central Camionera, Torremolinos and La Paloma faults. Local construction codes in the vicinity of these faults define a very narrow swath along which housing construction is not allowed. In order to better characterize these fault systems and provide better criteria for future municipal construction codes we have surveyed the La Colina and Torremolinos fault systems in the western sector of Morelia using seismic tomographic techniques. Our results indicate that La Colina Fault include secondary faults at depths up to 4-8m below the surface and located up to 24m away from the main fault trace. The Torremolinos fault system includes secondary faults, which are present up to 8m deep and 12-18m away from the main fault trace. Even though the InSAR analysis provides an unsurpassed synoptic view, a higher temporal resolution observation of fault movement has been pursued using the MOIT continuously operating GPS station, which is located within 100 m from the La Colina main fault trace. GPS data is also particularly useful to decompose horizontal and vertical motion in the absence of both ascending and descending SAR data acquisitions. Observations since July 2009 show a total general displacement trend of -39mm/yr and a total horizontal differential motion of 41.8 mm/yr and -4.7mm/yr in its latitudinal and Longitudinal components respectively in respect to the motion observed at the MOGA GPS station located 5.0 km to the SSE within an area which is not affected by subsidence. In addition to the overall trend, high amplitude excursions at the MOIT station with individual residual amplitudes up to 20mm, 25mm, and 60mm in its latitudinal, longitudinal and vertical components respectively vertical are observed. The correlation of fault motion excursions in relationship to the rainfall records will be analyzed.

  6. Regional methods for mapping major faults in areas of uniform low relief, as used in the London Basin, UK

    NASA Astrophysics Data System (ADS)

    Haslam, Richard; Aldiss, Donald

    2013-04-01

    Most of the London Basin, south-eastern UK, is underlain by the Palaeogene London Clay Formation, comprising a succession of rather uniform marine clay deposits up to 150 m thick, with widespread cover of Quaternary deposits and urban development. Therefore, in this area faults are difficult to delineate (or to detect) by conventional geological surveying methods in the field, and few are shown on the geological maps of the area. However, boreholes and excavations, especially those for civil engineering works, indicate that faults are probably widespread and numerous in the London area. A representative map of fault distribution and patterns of displacement is a pre-requisite for understanding the tectonic development of a region. Moreover, faulting is an important influence on the design and execution of civil engineering works, and on the hydrogeological characteristics of the ground. This paper reviews methods currently being used to map faults in the London Basin area. These are: the interpretation of persistent scatterer interferometry (PSI) data from time-series satellite-borne radar measurements; the interpretation of regional geophysical fields (Bouguer gravity anomaly and aeromagnetic), especially in combination with a digital elevation model; and the construction and interpretation of 3D geological models. Although these methods are generally not as accurate as large-scale geological field surveys, due to the availability of appropriate data in the London Basin they provide the means to recognise and delineate more faults, and with more confidence, than was possible using traditional geological mapping techniques. Together they reveal regional structures arising during Palaeogene crustal extension and subsidence in the North Sea, followed by inversion of a Mesozoic sedimentary basin in the south of the region, probably modified by strike-slip fault motion associated with the relative northward movement of the African Plate and the Alpine orogeny. This work is distributed under the Creative Commons Attribution 3.0 Unported License together with an NERC copyright. This license does not conflict with the regulations of the Crown Copyright.

  7. 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

  8. 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

  9. Comparative analysis of neural network and regression based condition monitoring approaches for wind turbine fault detection

    NASA Astrophysics Data System (ADS)

    Schlechtingen, Meik; Ferreira Santos, Ilmar

    2011-07-01

    This paper presents the research results of a comparison of three different model based approaches for wind turbine fault detection in online SCADA data, by applying developed models to five real measured faults and anomalies. The regression based model as the simplest approach to build a normal behavior model is compared to two artificial neural network based approaches, which are a full signal reconstruction and an autoregressive normal behavior model. Based on a real time series containing two generator bearing damages the capabilities of identifying the incipient fault prior to the actual failure are investigated. The period after the first bearing damage is used to develop the three normal behavior models. The developed or trained models are used to investigate how the second damage manifests in the prediction error. Furthermore the full signal reconstruction and the autoregressive approach are applied to further real time series containing gearbox bearing damages and stator temperature anomalies. The comparison revealed all three models being capable of detecting incipient faults. However, they differ in the effort required for model development and the remaining operational time after first indication of damage. The general nonlinear neural network approaches outperform the regression model. The remaining seasonality in the regression model prediction error makes it difficult to detect abnormality and leads to increased alarm levels and thus a shorter remaining operational period. For the bearing damages and the stator anomalies under investigation the full signal reconstruction neural network gave the best fault visibility and thus led to the highest confidence level.

  10. Decentralized Detection of a Class of Non-Abrupt Faults With Application to Formations of Unmanned Airships

    Microsoft Academic Search

    N. Lechevin; C. A. Rabbath

    2009-01-01

    We propose a decentralized non-abrupt fault detection (DNaFD) scheme for leader-to-follower formations of unmanned airships. Non-abrupt faults are those that result in slow performance degradation and in undesirable drift, which can propagate from one vehicle to another, and therefore can adversely affect mission integrity, potentially destabilizing multivehicle formations, while being difficult to detect. As opposed to model-based fault detectors, which

  11. State space method of fault tree analysis with applications

    Microsoft Academic Search

    1984-01-01

    A widely used analytical tool for assessing safety, reliability, and risk both qualitatively and quantitatively for a broad spectrum of engineering systems is the fault tree. The fault tree is an assemblage of initiating events (the roots) that pass through an interconnected (branched) system of Boolean OR and AND gates, and ultimately lead to an undesirable TOP event. This tool

  12. Methods of DNA methylation detection

    NASA Technical Reports Server (NTRS)

    Maki, Wusi Chen (Inventor); Filanoski, Brian John (Inventor); Mishra, Nirankar (Inventor); Rastogi, Shiva (Inventor)

    2010-01-01

    The present invention provides for methods of DNA methylation detection. The present invention provides for methods of generating and detecting specific electronic signals that report the methylation status of targeted DNA molecules in biological samples.Two methods are described, direct and indirect detection of methylated DNA molecules in a nano transistor based device. In the direct detection, methylated target DNA molecules are captured on the sensing surface resulting in changes in the electrical properties of a nano transistor. These changes generate detectable electronic signals. In the indirect detection, antibody-DNA conjugates are used to identify methylated DNA molecules. RNA signal molecules are generated through an in vitro transcription process. These RNA molecules are captured on the sensing surface change the electrical properties of nano transistor thereby generating detectable electronic signals.

  13. Validation Methods for Fault-Tolerant avionics and control systems, working group meeting 1

    NASA Technical Reports Server (NTRS)

    1979-01-01

    The proceedings of the first working group meeting on validation methods for fault tolerant computer design are presented. The state of the art in fault tolerant computer validation was examined in order to provide a framework for future discussions concerning research issues for the validation of fault tolerant avionics and flight control systems. The development of positions concerning critical aspects of the validation process are given.

  14. 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

  15. Combined expert system/neural networks method for process fault diagnosis

    DOEpatents

    Reifman, Jaques (Westchester, IL); Wei, Thomas Y. C. (Downers Grove, IL)

    1995-01-01

    A two-level hierarchical approach for process fault diagnosis is 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.

  16. 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.

  17. Runtime Verification in Context : Can Optimizing Error Detection Improve Fault Diagnosis

    NASA Technical Reports Server (NTRS)

    Dwyer, Matthew B.; Purandare, Rahul; Person, Suzette

    2010-01-01

    Runtime verification has primarily been developed and evaluated as a means of enriching the software testing process. While many researchers have pointed to its potential applicability in online approaches to software fault tolerance, there has been a dearth of work exploring the details of how that might be accomplished. In this paper, we describe how a component-oriented approach to software health management exposes the connections between program execution, error detection, fault diagnosis, and recovery. We identify both research challenges and opportunities in exploiting those connections. Specifically, we describe how recent approaches to reducing the overhead of runtime monitoring aimed at error detection might be adapted to reduce the overhead and improve the effectiveness of fault diagnosis.

  18. Virtual Sensor Based Fault Detection and Classification on a Plasma Etch Reactor

    E-print Network

    Sofge, D A

    2007-01-01

    The SEMATECH sponsored J-88-E project teaming Texas Instruments with NeuroDyne (et al.) focused on Fault Detection and Classification (FDC) on a Lam 9600 aluminum plasma etch reactor, used in the process of semiconductor fabrication. Fault classification was accomplished by implementing a series of virtual sensor models which used data from real sensors (Lam Station sensors, Optical Emission Spectroscopy, and RF Monitoring) to predict recipe setpoints and wafer state characteristics. Fault detection and classification were performed by comparing predicted recipe and wafer state values with expected values. Models utilized include linear PLS, Polynomial PLS, and Neural Network PLS. Prediction of recipe setpoints based upon sensor data provides a capability for cross-checking that the machine is maintaining the desired setpoints. Wafer state characteristics such as Line Width Reduction and Remaining Oxide were estimated on-line using these same process sensors (Lam, OES, RFM). Wafer-to-wafer measurement of thes...

  19. 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.

  20. 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

  1. Multi-Fault Detection of Rolling Element Bearings under Harsh Working Condition Using IMF-Based Adaptive Envelope Order Analysis

    PubMed Central

    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

  2. Software Fault Tree and Colored Petri Net Based Specification, Design and Implementation of Agent-Based Intrusion Detection Systems

    Microsoft Academic Search

    Guy Helmer; Johnny Wong; Mark Slagell; Vasant Honavar; Les Miller; Yanxin Wang; Xia Wang; Natalia Stakhanova

    2001-01-01

    The integration of Software Fault Tree Analysis (SFTA) (to describe intrusions) and Colored Petri Nets (CPNs) (to specify design) is examined for an Intrusion Detection System (IDS). The IDS under development is a collection of mobile agents that detect, classify, and correlate system and network activities. Software Fault Trees (SFTs), augmented with nodes that describe trust, temporal, and contextual relationships,

  3. Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Experimental Validation (part II)

    Microsoft Academic Search

    Andrea Monteriu; Prateek Asthan; Kimon P. Valavanis; Sauro Longhi

    2007-01-01

    This paper presents implementation details of a model-based sensor fault detection and isolation system (SFDIS) applied to unmanned ground vehicles (UGVs). Structural analysis, applied to the nonlinear model of the UGV, is followed to build the residual generation module, followed by a residual evaluation module capable of detecting single and multiple sensor faults, as detailed in part I (Monteriu et

  4. 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.

  5. Fault detection and diagnostics for non-intrusive monitoring using motor harmonics

    Microsoft Academic Search

    Uzoma A. Orji; Z. Remscrim; C. Laughman; S. B. Leeb; W. Wichakool; C. Schantz; R. Cox; J. L. Kirtley; L. K. Norford

    2010-01-01

    Harmonic analysis of motor current has been used to track the speed of motors for sensorless control. Algorithms exist that track the speed of a motor given a dedicated stator current measurement, for example. Harmonic analysis has also been applied for diagnostic detection of electro-mechanical faults such as damaged bearings and rotor eccentricity. This paper demonstrates the utility of harmonic

  6. Distributed Sensor Analysis for Fault Detection in Tightly-Coupled Multi-Robot Team Tasks

    E-print Network

    Parker, Lynne E.

    Distributed Sensor Analysis for Fault Detection in Tightly-Coupled Multi-Robot Team Tasks Xingyan Li and Lynne E. Parker Proc. of IEEE International Conference on Robotics and Automation, Kobe, Japan multi-robot team tasks. While the centralized version of SAFDetection was shown to be successful

  7. 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

  8. Modeling study for high impedance fault detection in MV distribution system

    Microsoft Academic Search

    Tao Cui; Xinzhou Dong; Zhiqian Bo; Andrew Klimek; Armien Edwards

    2008-01-01

    Modeling study provides a more effective and flexible way for research of high impedance fault (HIF) detection. An accurate model which can reveal most features of HIF is very important. In this paper, based on extensive investigation into documented test results, a set of most common and agreeable features of HIF has been summarized: the arc features, the non-linearity, the

  9. Abstract: Within the model based diagnosis community, Fault Detection and Isolation (FDI) techniques for hybrid systems

    E-print Network

    Boyer, Edmond

    Abstract: Within the model based diagnosis community, Fault Detection and Isolation (FDI Networks models are obtained they are used to generate residuals and to achieve FDI without any need and Isolation (FDI) techniques [11, 26] must be implemented to safeguard the 1 with Laboratoire CRe

  10. 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 factors, such as wind speed and acoustic noise, wind parks are being mainly constructed offshore. Studies

  11. APPLICATION OF SPECTRAL KURTOSIS TO BEARING FAULT DETECTION IN INDUCTION MOTORS

    E-print Network

    Paris-Sud XI, Université de

    APPLICATION OF SPECTRAL KURTOSIS TO BEARING FAULT DETECTION IN INDUCTION MOTORS Valeriu Vrabie1 in asynchronous machines. This one-dimensional spectral measure allows to study the nature of the harmonic components of the stator current of an induction motor running at a constant rotation speed. It provides

  12. Application of Wavelets Transform to Fault Detection in Rotorcraft UAV Sensor Failure

    Microsoft Academic Search

    Jun-tong Qi; Jian-da Han

    2007-01-01

    This paper describes a novel wavelet-based approach to the detection of abrupt fault of Rotorcraft Unmanned Aerial Vehicle (RUAV) sensor system. By use of wavelet transforms that accurately localize the characteristics of a signal both in the time and frequency domains, the occurring instants of abnormal status of a sensor in the output signal can be identified by the multi-scale

  13. 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 Keywords: subduction zones marine geophysics electromagnetics conductivity a b s t r a c t Water plays-source electromagnetic imaging to map the electrical resistivity of the crust and uppermost mantle along a 220 km profile

  14. 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

  15. On thruster allocation, fault detection and accommodation issues for underwater robotic vehicles

    Microsoft Academic Search

    Giovanni Indiveri; Gianfranco Parlangeli

    The use of mono-directional thrusters on under- water vehicle poses interesting issues on actuator allocation, fault detection and accommodation. Preliminary results rel- ative to the horizontal motion of an unhabited underwater vehicle (UUV) are presented. Index Terms— Underwater remotely operated vehicles, con- trol allocation. I. INTRODUCTION The use of shallow water unhabited underwater vehicle (UUV) systems for environment monitoring is

  16. Current Sensor Fault Detection by Bilinear Observer for a Doubly Fed Induction Generator

    Microsoft Academic Search

    Kai Rothenhagen; Friedrich W. Fuchs

    2006-01-01

    A bilinear observer is presented to detect current sensor faults in a doubly fed induction generator. The state space model is derived from the voltage equations of stator and rotor. The bilinear behaviour of induction machines and its influence on the state space model is discussed. An open loop model suffers from model and parameter uncertainty. A closed loop observer

  17. Incipient fault detection and identification in process systems using artificial neural networks

    E-print Network

    Muthusami, Jayakumar

    1992-01-01

    . . . 84 30 Fault Indication for 5% Step Increase in Static Friction Using 20% Fault Severity Level Trained ANN 85 Fault Indication for 5% Step Increase in Static Friction Using 25% Fault Level Trained ANN BG 32 Fault. Indication for 8% Step Increase... in Static Friction Using 20% Fault Severity Level Trained ANN. 87 Fault Indication for 8% Step Increase in Static Friction Using 25% Fault Severity Level Trained ANN. 88 34 Fault Indication for 10% Ramp Increase in Static Friction Using 20% Fault...

  18. Detection of Fault Zones at Depth Using Low Frequency Induced Sources

    NASA Astrophysics Data System (ADS)

    Mazzoni, C.; Pytharouli, S.; Lunn, R. J.

    2013-12-01

    The locations and properties of small fault zones and fractures are of interest to industries including Radioactive Waste Disposal and Deep Underground Mining. At present there is limited knowledge regarding imaging of fault zones with sizes 1 to 100m. We explore the potential of seismic noise, such as that present in tunnels due to excavation processes, to image fractures at depth. Microseismic monitoring is a powerful tool but resolution depends on the characteristics e.g. wavelength and frequency, of the recorded seismic signals. In this study we investigate the role of those characteristics in the identification of fault zones at depth. We use finite element analysis to model a small fault zone within a crystalline host rock; a potential host rock for geological disposal. After an optimization analysis, a 25Hz short duration pulse was used to simulate a seismic source in a rock mass of dimensions 500m x 500m. The thickness and pressure wave speed (Vp) of the fault zone, its orientation, and the location of the pulse were varied. The fault core thickness was varied from <1m to 5m, Vp from 500m/s to 1500m/s while the host rock Vp remained constant at 5000m/s. Two orientations were considered for the fault zone: 1) horizontal and 2) vertical allowing two extremities to be evaluated. The location of the source was considered, 1) directly below the fault zone and 2) at some distance away from the fault zone (100m). Our analysis shows that the frequency of the pulse changes as the wave reflects and refracts due to material property changes as it propagates. The peak wave velocity on arrival at predefined monitoring points demonstrates reduction, giving an indication of attenuation. We show that the original frequency converges to a certain threshold value e.g. approximately 11Hz for a Vp of 5000m/s and 4Hz for a Vp of 500m/s. This threshold is characteristic of the material and the thickness of the layer through which the pulse is propagating. There is a strong linear relationship (R2 > 0.99) between wave propagation velocity in the rock, frequency threshold value and the distance from the seismic source at which this frequency threshold is achieved. Our results suggest that we are able to detect the presence of materials with very different properties, e.g. a fault zone within a rock mass. For example, a 1 m wide fault zone is detectable if there is at least a 30% contrast between the Vp values of the fault zone and the host rock. This requirement is not constant i.e. the minimum difference in Vp reduces as the thickness of the fault zone increases. Our results have direct implications for the novel application of seismic monitoring systems for field detection of sub-seismic scale fracture and fault zones.

  19. Research on fault diagnosis for reciprocating compressor valve using information entropy and SVM method

    Microsoft Academic Search

    Houxi Cui; Laibin Zhang; Rongyu Kang; Xinyang Lan

    2009-01-01

    A method of compressor valve fault diagnosis using information entropy and SVM is proposed in this paper. The main obstacle in the fault diagnosis focuses on the low non-linear pattern recognition performance and small sample number. Therefore, the information entropy, which is flexible and tolerant to the non-linearity problem, is applied to analyze the characteristic of the signals. SVM is

  20. Evaluation of error detection schemes using fault injection by heavy-ion radiation

    Microsoft Academic Search

    U. Gunneflo; Johan Karlsson; Jan Torin

    1989-01-01

    Several concurrent error detection schemes suitable for a watch-dog processor were evaluated by fault injection. Soft errors were induced into a MC6809E microprocessor by heavy-ion radiation from a Californium-252 source. Recordings of error behavior were used to characterize the errors as well as to determine coverage and latency for the various error detection schemes. The error recordings were used as

  1. Fault detection in railway track using piezoelectric impedance

    NASA Astrophysics Data System (ADS)

    Cremins, M.; Shuai, Qi; Xu, Jiawen; Tang, J.

    2014-04-01

    In this research, piezoelectric transducers are incorporated in an impedance-based damage detection approach for railway track health monitoring. The impedance-based damage detection approach utilizes the direct relationship between the mechanical impedance of the track and electrical impedance of the piezoelectric transducer bonded. The effect of damage is shown in the change of a healthy impedance curve to an altered, damaged curve. Using a normalized relative difference outlier analysis, the occurrences of various damages on the track are determined. Furthermore, the integration of inductive circuitry with the piezoelectric transducer is found to be able to considerably increase overall damage detection sensitivity.

  2. A Robust and Fault-Tolerant Distributed Intrusion Detection System

    E-print Network

    Sen, Jaydip

    2011-01-01

    Since it is impossible to predict and identify all the vulnerabilities of a network, and penetration into a system by malicious intruders cannot always be prevented, intrusion detection systems (IDSs) are essential entities for ensuring the security of a networked system. To be effective in carrying out their functions, the IDSs need to be accurate, adaptive, and extensible. Given these stringent requirements and the high level of vulnerabilities of the current days' networks, the design of an IDS has become a very challenging task. Although, an extensive research has been done on intrusion detection in a distributed environment, distributed IDSs suffer from a number of drawbacks e.g., high rates of false positives, low detection efficiency etc. In this paper, the design of a distributed IDS is proposed that consists of a group of autonomous and cooperating agents. In addition to its ability to detect attacks, the system is capable of identifying and isolating compromised nodes in the network thereby introduc...

  3. A delay-fault testing strategy based on the analysis of power supply transient signals is presented. The method is

    E-print Network

    Plusquellic, James

    Abstract A delay-fault testing strategy based on the analysis of power supply transient signals on a fault model that accurately abstracts some fraction (ideally all) of the analog circuit deviations introduced by defects to a set of discrete faults, that can be targeted by a set of tests and detected

  4. Method and system for controlling a permanent magnet machine during fault conditions

    DOEpatents

    Krefta, Ronald John; Walters, James E.; Gunawan, Fani S.

    2004-05-25

    Method and system for controlling a permanent magnet machine driven by an inverter is provided. The method allows for monitoring a signal indicative of a fault condition. The method further allows for generating during the fault condition a respective signal configured to maintain a field weakening current even though electrical power from an energy source is absent during said fault condition. The level of the maintained field-weakening current enables the machine to operate in a safe mode so that the inverter is protected from excess voltage.

  5. Fault detection, diagnosis, and data-driven modeling in HVAC chillers

    NASA Astrophysics Data System (ADS)

    Namburu, Setu M.; Luo, Jianhui; Azam, Mohammad; Choi, Kihoon; Pattipati, Krishna R.

    2005-05-01

    Heating, Ventilation and Air Conditioning (HVAC) systems constitute the largest portion of energy consumption equipment in residential and commercial facilities. Real-time health monitoring and fault diagnosis is essential for reliable and uninterrupted operation of these systems. Existing fault detection and diagnosis (FDD) schemes for HVAC systems are only suitable for a single operating mode with small numbers of faults, and most of the schemes are systemspecific. A generic real-time FDD scheme, applicable to all possible operating conditions, can significantly reduce HVAC equipment downtime, thus improving the efficiency of building energy management systems. This paper presents a FDD methodology for faults in centrifugal chillers. The FDD scheme compares the diagnostic performance of three data-driven techniques, namely support vector machines (SVM), principal component analysis (PCA), and partial least squares (PLS). In addition, a nominal model of a chiller that can predict system response under new operating conditions is developed using PLS. We used the benchmark data on a 90-ton real centrifugal chiller test equipment, provided by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), to demonstrate and validate our proposed diagnostic procedure. The database consists of data from sixty four monitored variables under nominal and eight fault conditions of different severities at twenty seven operating modes.

  6. Handling Software Faults with Redundancy

    Microsoft Academic Search

    Antonio Carzaniga; Alessandra Gorla; Mauro Pezzè

    2008-01-01

    Software engineering methods can increase the dependability of software systems, and yet some faults escape even the most\\u000a rigorous and methodical development process. Therefore, to guarantee high levels of reliability in the presence of faults,\\u000a software systems must be designed to reduce the impact of the failures caused by such faults, for example by deploying techniques\\u000a to detect and compensate

  7. 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.

  8. Innovation sequence application to aircraft sensor fault detection: comparison of checking covariance matrix algorithms

    PubMed

    Caliskan; Hajiyev

    2000-01-01

    In this paper, the algorithms verifying the covariance matrix of the Kalman filter innovation sequence are compared with respect to detected minimum fault rate and detection time. Four algorithms are dealt with; the algorithm verifying the trace of the covariance matrix of the innovation sequence, the algorithm verifying the sum of all elements of the inverse covariance matrix of the innovation sequence, the optimal algorithm verifying the ratio of two quadratic forms of which matrices are theoretic and selected covariance matrices of Kalman filter innovation sequence, and the algorithm verifying the generalized variance of the covariance matrix of the innovation sequence. The algorithms are implemented for longitudinal dynamics of an aircraft to detect sensor faults, and some suggestions are given on the use of the algorithms in flight control systems. PMID:10826285

  9. Detection of weak transient signals based on wavelet packet transform and manifold learning for rolling element bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Wang, Yi; Xu, Guanghua; Liang, Lin; Jiang, Kuosheng

    2015-03-01

    The kurtogram-based methods have been proved powerful and practical to detect and characterize transient components in a signal. The basic idea of the kurtogram-based methods is to use the kurtosis as a measure to discover the presence of transient impulse components and to indicate the frequency band where these occur. However, the performance of the kurtogram-based methods is poor due to the low signal-to-noise ratio. As the weak transient signal with a wide spread frequency band can be easily masked by noise. Besides, selecting signal just in one frequency band will leave out some transient features. Aiming at these shortcomings, different frequency bands signal fusion is adopted in this paper. Considering that manifold learning aims at discovering the nonlinear intrinsic structure which embedded in high dimensional data, this paper proposes a waveform feature manifold (WFM) method to extract the weak signature from waveform feature space which obtained by binary wavelet packet transform. Minimum permutation entropy is used to select the optimal parameter in a manifold learning algorithm. A simulated bearing fault signal and two real bearing fault signals are used to validate the improved performance of the proposed method through the comparison with the kurtogram-based methods. The results show that the proposed method outperforms the kurtogram-based methods and is effective in weak signature extraction.

  10. Adaptive Fault Detection on Liquid Propulsion Systems with Virtual Sensors: Algorithms and Architectures

    NASA Technical Reports Server (NTRS)

    Matthews, Bryan L.; Srivastava, Ashok N.

    2010-01-01

    Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an adaptive learning method known as Virtual Sensors. Virtual Sensors are a class of algorithms that estimate the value of a time series given other potentially nonlinearly correlated sensor readings. In the case presented here, the Virtual Sensors algorithm is based on an ensemble learning approach and takes sensor readings and control signals as input to estimate the pressure in a subsystem of the Main Propulsion System. Our results indicate that this method can detect faults in the FCV at the time when they occur. We use the standard deviation of the predictions of the ensemble as a measure of uncertainty in the estimate. This uncertainty estimate was crucial to understanding the nature and magnitude of transient characteristics during startup of the engine. This paper overviews the Virtual Sensors algorithm and discusses results on a comprehensive set of Shuttle missions and also discusses the architecture necessary for deploying such algorithms in a real-time, closed-loop system or a human-in-the-loop monitoring system. These results were presented at a Flight Readiness Review of the Space Shuttle in early 2009.

  11. Fault-Tolerant Concept Detection in Information Networks

    E-print Network

    and their properties, how can we automatically discover that Aspirin has blood-thinning properties, and thus prevents, and the other describing their chemical behavior, how can we discover whether, for ex- ample, Aspirin has blood uses of Aspirin (Acetylsalicylic acid) that have been detected by our proposed algorithm. In a nutshell

  12. A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering

    NASA Astrophysics Data System (ADS)

    Ushaq, Muhammad; Fang, Jiancheng

    2013-10-01

    Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be applied to the navigation system of aircraft or unmanned aerial vehicle (UAV).

  13. Fault detection and diagnosis for non-Gaussian stochastic distribution systems with time delays via RBF neural networks.

    PubMed

    Yi, Qu; Zhan-ming, Li; Er-chao, Li

    2012-11-01

    A new fault detection and diagnosis (FDD) problem via the output probability density functions (PDFs) for non-gausian stochastic distribution systems (SDSs) is investigated. The PDFs can be approximated by radial basis functions (RBFs) neural networks. Different from conventional FDD problems, the measured information for FDD is the output stochastic distributions and the stochastic variables involved are not confined to Gaussian ones. A (RBFs) neural network technique is proposed so that the output PDFs can be formulated in terms of the dynamic weighings of the RBFs neural network. In this work, a nonlinear adaptive observer-based fault detection and diagnosis algorithm is presented by introducing the tuning parameter so that the residual is as sensitive as possible to the fault. Stability and Convergency analysis is performed in fault detection and fault diagnosis analysis for the error dynamic system. At last, an illustrated example is given to demonstrate the efficiency of the proposed algorithm, and satisfactory results have been obtained. PMID:22902083

  14. A H-infinity Fault Detection and Diagnosis Scheme for Discrete Nonlinear System Using Output Probability Density Estimation

    SciTech Connect

    Zhang Yumin; Lum, Kai-Yew [Temasek Laboratories, National University of Singapore, Singapore 117508 (Singapore); Wang Qingguo [Depa. Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (Singapore)

    2009-03-05

    In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.

  15. Spin-system dynamics and fault detection in threshold networks

    SciTech Connect

    Kirkland, Steve; Severini, Simone [Hamilton Institute, National University of Ireland, Maynooth County Kildare (Ireland); Department of Physics and Astronomy, University College London, WC1E 6BT London (United Kingdom)

    2011-01-15

    We consider an agent on a fixed but arbitrary node of a known threshold network, with the task of detecting an unknown missing link. We obtain analytic formulas for the probability of success when the agent's tool is the free evolution of a single excitation on an XX spin system paired with the network. We completely characterize the parameters, which allows us to obtain an advantageous solution. From the results emerges an optimal (deterministic) algorithm for quantum search, from which a quadratic speedup with respect to the optimal classical analog and in line with well-known results in quantum computation is gained. When attempting to detect a faulty node, the chosen setting appears to be very fragile and the probability of success too small to be of any direct use.

  16. Spin-system dynamics and fault detection in threshold networks

    NASA Astrophysics Data System (ADS)

    Kirkland, Steve; Severini, Simone

    2011-01-01

    We consider an agent on a fixed but arbitrary node of a known threshold network, with the task of detecting an unknown missing link. We obtain analytic formulas for the probability of success when the agent’s tool is the free evolution of a single excitation on an XX spin system paired with the network. We completely characterize the parameters, which allows us to obtain an advantageous solution. From the results emerges an optimal (deterministic) algorithm for quantum search, from which a quadratic speedup with respect to the optimal classical analog and in line with well-known results in quantum computation is gained. When attempting to detect a faulty node, the chosen setting appears to be very fragile and the probability of success too small to be of any direct use.

  17. Isolability of faults in sensor fault diagnosis

    NASA Astrophysics Data System (ADS)

    Sharifi, Reza; Langari, Reza

    2011-10-01

    A major concern with fault detection and isolation (FDI) methods is their robustness with respect to noise and modeling uncertainties. With this in mind, several approaches have been proposed to minimize the vulnerability of FDI methods to these uncertainties. But, apart from the algorithm used, there is a theoretical limit on the minimum effect of noise on detectability and isolability. This limit has been quantified in this paper for the problem of sensor fault diagnosis based on direct redundancies. In this study, first a geometric approach to sensor fault detection is proposed. The sensor fault is isolated based on the direction of residuals found from a residual generator. This residual generator can be constructed from an input-output or a Principal Component Analysis (PCA) based model. The simplicity of this technique, compared to the existing methods of sensor fault diagnosis, allows for more rational formulation of the isolability concepts in linear systems. Using this residual generator and the assumption of Gaussian noise, the effect of noise on isolability is studied, and the minimum magnitude of isolable fault in each sensor is found based on the distribution of noise in the measurement system. Finally, some numerical examples are presented to clarify this approach.

  18. Fault detection using a two-model test for changes in the parameters of an autoregressive time series

    NASA Technical Reports Server (NTRS)

    Scholtz, P.; Smyth, P.

    1992-01-01

    This article describes an investigation of a statistical hypothesis testing method for detecting changes in the characteristics of an observed time series. The work is motivated by the need for practical automated methods for on-line monitoring of Deep Space Network (DSN) equipment to detect failures and changes in behavior. In particular, on-line monitoring of the motor current in a DSN 34-m beam waveguide (BWG) antenna is used as an example. The algorithm is based on a measure of the information theoretic distance between two autoregressive models: one estimated with data from a dynamic reference window and one estimated with data from a sliding reference window. The Hinkley cumulative sum stopping rule is utilized to detect a change in the mean of this distance measure, corresponding to the detection of a change in the underlying process. The basic theory behind this two-model test is presented, and the problem of practical implementation is addressed, examining windowing methods, model estimation, and detection parameter assignment. Results from the five fault-transition simulations are presented to show the possible limitations of the detection method, and suggestions for future implementation are given.

  19. Wigner-Ville distributions for detection of rotor faults in brushless DC (BLDC) motors operating under non-stationary conditions

    Microsoft Academic Search

    S. Rajagopalan; J. A. Restrepo; J. M. Aller; T. G. Habetler; R. G. Harley

    2005-01-01

    Electric motors often operate under operating conditions that are constantly changing with time. Most of such applications demand high reliability from the motor. Early detection of developing motor faults could help provide this needed reliability. While diagnostics of faults in motors operating under steady state conditions is straight forward due to the use of the well known Fourier transformation, diagnostics

  20. Sideband Algorithm for Automatic Wind Turbine Gearbox Fault Detection and Diagnosis: Preprint

    SciTech Connect

    Zappala, D.; Tavner, P.; Crabtree, C.; Sheng, S.

    2013-01-01

    Improving the availability of wind turbines (WT) is critical to minimize the cost of wind energy, especially for offshore installations. As gearbox downtime has a significant impact on WT availabilities, the development of reliable and cost-effective gearbox condition monitoring systems (CMS) is of great concern to the wind industry. Timely detection and diagnosis of developing gear defects within a gearbox is an essential part of minimizing unplanned downtime of wind turbines. Monitoring signals from WT gearboxes are highly non-stationary as turbine load and speed vary continuously with time. Time-consuming and costly manual handling of large amounts of monitoring data represent one of the main limitations of most current CMSs, so automated algorithms are required. This paper presents a fault detection algorithm for incorporation into a commercial CMS for automatic gear fault detection and diagnosis. The algorithm allowed the assessment of gear fault severity by tracking progressive tooth gear damage during variable speed and load operating conditions of the test rig. Results show that the proposed technique proves efficient and reliable for detecting gear damage. Once implemented into WT CMSs, this algorithm can automate data interpretation reducing the quantity of information that WT operators must handle.

  1. Research of high-resolution vibration signal detection technique and application to mechanical fault diagnosis

    NASA Astrophysics Data System (ADS)

    Fan, Y. S.; Zheng, G. T.

    2007-02-01

    Bilinear time-frequency transformation can possess a simultaneous high resolution both in the time domain and the frequency domain. It can be utilised to detect weak transient vibration signals generated by early mechanical faults in complex background and thus is of great importance to early mechanical fault diagnoses. It has been found that the spectrogram has low resolution, and there is strong cross-terms in Wigner-Ville distribution and frequency aliasing and information loss in Choi-Williams distribution (CWD). Hence, they cannot achieve satisfied transient signal detection results. To enhance the capability of detecting transient vibration signals, based on the analysis of exponent distribution, this paper presents some novel alias-free time-frequency distributions. These distributions can avoid the information loss in CWD while suppressing the cross-terms. Moreover, they have high simultaneous resolutions in both the time and frequency domain. Digital simulation and gearbox fault diagnosis experiments prove that these new distributions can effectively detect transient components from complicated mechanical vibration signals.

  2. FINDS: A fault inferring nonlinear detection system programmers manual, version 3.0

    NASA Technical Reports Server (NTRS)

    Lancraft, R. E.

    1985-01-01

    Detailed software documentation of the digital computer program FINDS (Fault Inferring Nonlinear Detection System) Version 3.0 is provided. FINDS is a highly modular and extensible computer program designed to monitor and detect sensor failures, while at the same time providing reliable state estimates. In this version of the program the FINDS methodology is used to detect, isolate, and compensate for failures in simulated avionics sensors used by the Advanced Transport Operating Systems (ATOPS) Transport System Research Vehicle (TSRV) in a Microwave Landing System (MLS) environment. It is intended that this report serve as a programmers guide to aid in the maintenance, modification, and revision of the FINDS software.

  3. Fault detection, isolation, and recovery for autonomous parafoils

    E-print Network

    Stoeckle, Matthew Robert

    2014-01-01

    Autonomous precision airdrop systems are widely used to deliver supplies to remote locations. This aerial delivery method provides a safety and logistical advantage over traditional ground- or helicopter-based payload ...

  4. New Techniques for Fault Detection Analysis by Injecting Additional Frequency Test

    Microsoft Academic Search

    J. Cusido; J. Rosero; L. Romeral; J. A. Ortega; A. Garcia

    2006-01-01

    Double frequency tests are used for evaluating stator windings 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) is the most widely used method for identifying faults in induction motors. MCSA focuses its efforts on the spectral analysis of stator current. Motor

  5. Applying a robust heteroscedastic probabilistic neural network toanalog fault detection and classification

    Microsoft Academic Search

    Zheng Rong Yang; Mark Zwolinski; Chris D. Chalk; Alan Christopher Williams

    2000-01-01

    The problem of distinguishing and classifying the responses of analog integrated circuits containing catastrophic faults has aroused recent interest. The problem is made more difficult when parametric variations are taken into account. Hence, statistical methods and techniques such as neural networks have been employed to automate classification. The major drawback to such techniques has been the implicit assumption that the

  6. Chaotic Extension Neural Network Theory-Based XXY Stage Collision Fault Detection Using a Single Accelerometer Sensor

    PubMed Central

    Hsieh, Chin-Tsung; Yau, Her-Terng; Wu, Shang-Yi; Lin, Huo-Cheng

    2014-01-01

    The collision fault detection of a XXY stage is proposed for the first time in this paper. The stage characteristic signals are extracted and imported into the master and slave chaos error systems by signal filtering from the vibratory magnitude of the stage. The trajectory diagram is made from the chaos synchronization dynamic error signals E1 and E2. The distance between characteristic positive and negative centers of gravity, as well as the maximum and minimum distances of trajectory diagram, are captured as the characteristics of fault recognition by observing the variation in various signal trajectory diagrams. The matter-element model of normal status and collision status is built by an extension neural network. The correlation grade of various fault statuses of the XXY stage was calculated for diagnosis. The dSPACE is used for real-time analysis of stage fault status with an accelerometer sensor. Three stage fault statuses are detected in this study, including normal status, Y collision fault and X collision fault. It is shown that the scheme can have at least 75% diagnosis rate for collision faults of the XXY stage. As a result, the fault diagnosis system can be implemented using just one sensor, and consequently the hardware cost is significantly reduced. PMID:25405512

  7. Chaotic extension neural network theory-based XXY stage collision fault detection using a single accelerometer sensor.

    PubMed

    Hsieh, Chin-Tsung; Yau, Her-Terng; Wu, Shang-Yi; Lin, Huo-Cheng

    2014-01-01

    The collision fault detection of a XXY stage is proposed for the first time in this paper. The stage characteristic signals are extracted and imported into the master and slave chaos error systems by signal filtering from the vibratory magnitude of the stage. The trajectory diagram is made from the chaos synchronization dynamic error signals E1 and E2. The distance between characteristic positive and negative centers of gravity, as well as the maximum and minimum distances of trajectory diagram, are captured as the characteristics of fault recognition by observing the variation in various signal trajectory diagrams. The matter-element model of normal status and collision status is built by an extension neural network. The correlation grade of various fault statuses of the XXY stage was calculated for diagnosis. The dSPACE is used for real-time analysis of stage fault status with an accelerometer sensor. Three stage fault statuses are detected in this study, including normal status, Y collision fault and X collision fault. It is shown that the scheme can have at least 75% diagnosis rate for collision faults of the XXY stage. As a result, the fault diagnosis system can be implemented using just one sensor, and consequently the hardware cost is significantly reduced. PMID:25405512

  8. Disk Crack Detection for Seeded Fault Engine Test

    NASA Technical Reports Server (NTRS)

    Luo, Huageng; Rodriguez, Hector; Hallman, Darren; Corbly, Dennis; Lewicki, David G. (Technical Monitor)

    2004-01-01

    Work was performed to develop and demonstrate vibration diagnostic techniques for the on-line detection of engine rotor disk cracks and other anomalies through a real engine test. An existing single-degree-of-freedom non-resonance-based vibration algorithm was extended to a multi-degree-of-freedom model. In addition, a resonance-based algorithm was also proposed for the case of one or more resonances. The algorithms were integrated into a diagnostic system using state-of-the- art commercial analysis equipment. The system required only non-rotating vibration signals, such as accelerometers and proximity probes, and the rotor shaft 1/rev signal to conduct the health monitoring. Before the engine test, the integrated system was tested in the laboratory by using a small rotor with controlled mass unbalances. The laboratory tests verified the system integration and both the non-resonance and the resonance-based algorithm implementations. In the engine test, the system concluded that after two weeks of cycling, the seeded fan disk flaw did not propagate to a large enough size to be detected by changes in the synchronous vibration. The unbalance induced by mass shifting during the start up and coast down was still the dominant response in the synchronous vibration.

  9. Fault detection of aircraft system with random forest algorithm and similarity measure.

    PubMed

    Lee, Sanghyuk; Park, Wookje; Jung, Sikhang

    2014-01-01

    Research on fault detection algorithm was developed with the similarity measure and random forest algorithm. The organized algorithm was applied to unmanned aircraft vehicle (UAV) that was readied by us. Similarity measure was designed by the help of distance information, and its usefulness was also verified by proof. Fault decision was carried out by calculation of weighted similarity measure. Twelve available coefficients among healthy and faulty status data group were used to determine the decision. Similarity measure weighting was done and obtained through random forest algorithm (RFA); RF provides data priority. In order to get a fast response of decision, a limited number of coefficients was also considered. Relation of detection rate and amount of feature data were analyzed and illustrated. By repeated trial of similarity calculation, useful data amount was obtained. PMID:25057508

  10. Energy variance criterion and threshold tuning scheme for high impedance fault detection

    Microsoft Academic Search

    Keng-Yu Lien; Shi-Lin Chen; Ching-Jung Liao; Tzong-Yih Guo; Tsair-Ming Lin; Jer-Sheng Shen

    1999-01-01

    Summary form only given as follows. This paper presents a new approach to the detection of high impedance fault (HIF). The proposed approach (or detector which implements this approach) has four distinct features. First, the detector input signal is the three-phase unbalanced current (or feeder 3I0), rather than the conventional three individual phase-currents. Secondly, the detector is designed by monitoring

  11. High impedance fault detection in distribution feeders using extended kalman filter and support vector machine

    Microsoft Academic Search

    S. R. Samantaray; P. K. Dash

    2009-01-01

    SUMMARY The paper presents an intelligent technique for high impedance fault (HIF) detection using combined extended kalman filter (EKF) and support vector machine (SVM). The proposed approach uses magnitude and phase change of fundamental, 3rd, 5th, 7th, 11th and 13th harmonic component as feature inputs to the SVM. The Gaussian kernel based SVM is trained with input sets each consists

  12. Combined EKF and SVM based High Impedance Fault detection in power distribution feeders

    Microsoft Academic Search

    S. R. Samantaray; L. N. Tripathy; P. K. Dash

    2009-01-01

    The paper presents an intelligent technique for High Impedance Fault (HIF) detection using combined Extended Kalman Filter and Support Vector Machine. The proposed approach uses magnitude and phase change of fundamental, 3rd, 5th, 7th, 11th and 13th harmonic component as feature inputs to the SVM. The Gaussian kernel based SVM is trained with input sets each consists of '12' features

  13. An Efficient Single-Fault Detection Technique for Micro-fluidic Based Biochips

    Microsoft Academic Search

    Sagarika Saha; Amlan Chakraborti; Samir Roy

    2010-01-01

    This paper presents a new fault detection technique for digital micro-fluidic based biochips. Due to recent advances in microfluidics, digital micro-fluidic biochips are revolutionizing laboratory procedures, e.g., biosensing, clinical diagnostics etc. Because of the underlying mixed-technology and mixed energy domains, biochips exhibit unique failure mechanisms and defects. Off-line and on-line test techniques are required to ensure system dependability. In this

  14. Optimization of Fault Detection/Diagnosis Model for Thermal Storage System Using AIC

    E-print Network

    Pan, S.; Zheng, M.; Nakahara, N.

    2006-01-01

    ICEBO2006, Shenzhen, China Control Systems for Energy Efficiency and Comfort, Vol. V-5-6 Optimization of Fault Detection/Diagnosis Model for Thermal Storage System Using AIC Song Pan Mingjie Zheng Nobuo Nakahara Research Laboratory... Research Laboratory Nakahara Laboratory Sanko Air Conditioning Co.,LTD. Sanko Air Conditioning Co.,LTD. Environmental Sys-Tech Nagoya, Japan Nagoya, Japan Nagoya, Japan han@sanko-air.co.jp zheng@sanko-air.co.jp pl...

  15. Dynamic Neural Network-Based Fault Detection and Isolation for Thrusters in Formation Flying of Satellites

    Microsoft Academic Search

    Arturo Valdes; Khashayar Khorasani; Liying Ma

    2009-01-01

    The objective of this paper is to develop a dynamic neural network-based fault detection and isolation (FDI) scheme for satellites\\u000a that are tasked to perform a formation flying mission. Specifically, the proposed FDI scheme is developed for Pulsed Plasma\\u000a Thrusters (PPT) that are considered to be used in satellite’s Attitude Control Subsystem (ACS). By using the relative attitudes\\u000a of satellites

  16. Observer-Based Optimal Fault Detection and Diagnosis Using Conditional Probability Distributions

    Microsoft Academic Search

    Lei Guo; Yu-Min Zhang; Hong Wang; Jian-Cheng Fang

    2006-01-01

    A new optimal fault detection and diagnosis (FDD) scheme is studied in this paper for the continuous-time stochastic dynamic systems with time delays, where the available information for the FDD is the input and the measured output probability density functions (pdf's) of the system. The square-root B-spline functional approximation technique is used to formulate the output pdf's with the dynamic

  17. Comparing Detection Methods for Software Requirements Inspections: A Replicated Experiment

    Microsoft Academic Search

    Adam A. Porter; Lawrence G. Votta; Victor R. Basili

    1995-01-01

    Software requirements specifications (SRS) are often validated manually. One such process is inspection, in which several reviewers independently analyze all or part of the specification and search for faults. These faults are then collected at a meeting of the reviewers and author(s). Usually, reviewers use Ad Hoc or Checklist methods to uncover faults. These methods force all reviewers to rely

  18. A Fault Diagnosis Approach for Rolling Bearings Based on EMD Method and Eigenvector Algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, Jinyu; Huang, Xianxiang

    Fault diagnosis of rolling bearings is still a very important and difficult research task on engineering. After analyzing the shortcomings of current bearing fault diagnosis technologies, a new approach based on Empirical Mode Decomposition (EMD) and blind equalization eigenvector algorithm (EVA) for rolling bearings fault diagnosis is proposed. In this approach, the characteristic high-frequency signal with amplitude and channel modulation of a rolling bearing with local damage is first separated from the mechanical vibration signal as an Intrinsic Mode Function (IMF) by using EMD, then the source impact vibration signal yielded by local damage is extracted by means of a EVA model and algorithm. Finally, the presented approach is used to analyze an impacting experiment and two real signals collected from rolling bearings with outer race damage or inner race damage. The results show that the EMD and EVA based approach can effectively detect rolling bearing fault.

  19. Paleostress reconstruction from calcite twin and fault-slip data using the multiple inverse method in the East Walanae fault zone: Implications for the Neogene contraction in South Sulawesi, Indonesia

    NASA Astrophysics Data System (ADS)

    Jaya, Asri; Nishikawa, Osamu

    2013-10-01

    A new approach for paleostress analysis using the multiple inverse method with calcite twin data including untwinned e-plane was performed in the East Walanae fault (EWF) zone in South Sulawesi, Indonesia. Application of untwinned e-plane data of calcite grain to constrain paleostress determination is the first attempt for this method. Stress states caused by the collision of the south-east margin of Sundaland with the Australian microcontinents during the Pliocene were successfully detected from a combination of calcite-twin data and fault-slip data. This Pliocene NE-SW-to-E-W-directed maximum compression activated the EWF as a reverse fault with a dextral component of slip with pervasive development of secondary structures in the narrow zone between Bone Mountain and Walanae Depression.

  20. An active ring fault detected at Tendürek volcano by using InSAR

    NASA Astrophysics Data System (ADS)

    Bathke, H.; Sudhaus, H.; Holohan, E. P.; Walter, T. R.; Shirzaei, M.

    2013-08-01

    ring faults are present at many ancient, deeply eroded volcanoes, they have been detected at only very few modern volcanic centers. At the so far little studied Tendürek volcano in eastern Turkey, we generated an ascending and a descending InSAR time series of its surface displacement field for the period from 2003 to 2010. We detected a large (~105?km2) region that underwent subsidence at the rate of ~1?cm/yr during this period. Source modeling results show that the observed signal fits best to simulations of a near-horizontal contracting sill located at around 4.5?km below the volcano summit. Intriguingly, the residual displacement velocity field contains a steep gradient that systematically follows a system of arcuate fractures visible on the volcano's midflanks. RapidEye satellite optical images show that this fracture system has deflected Holocene lava flows, thus indicating its presence for at least several millennia. We interpret the arcuate fracture system as the surface expression of an inherited ring fault that has been slowly reactivated during the detected recent subsidence. These results show that volcano ring faults may not only slip rapidly during eruptive or intrusive phases, but also slowly during dormant phases.

  1. Analysis of the vibratory excitation of gear systems for fault detection in rotating machinery

    SciTech Connect

    Paya, B.A.; Esat, I.I. [Brunel Univ., Uxbridge (United Kingdom); Badi, M.N.M. [Univ. of Hertfordshire, Hatfield (United Kingdom)

    1997-07-01

    The concepts of model-based fault detection for vibration condition monitoring of rotating machinery are discussed and presented in this paper. The mathematical model presented and fully developed in the earlier works is further modified so it incorporates a typical gear tooth irregularity fault. This fault was simulated on the contact line of the gear model. The results obtained from this analytical model are compared with the ones obtained from a model drive-line. The drive-line consists of a number of rotating parts including an electric motor, a gear system, and a disk brake. The gear system has two meshing spur gears which is equivalent to the analytical model. The comparison of the results are very good as some vibration frequencies of the analytical results correlates with the experimental ones. it is shown that certain vibration frequencies of a real experimental model gear system can be obtained from its analytical counterpart. It is also shown that it is possible to model a typical gear tooth fault by simulating a forcing function as a shock to the modelled system.

  2. Fault Diagnosis of Continuous Systems Using Discrete-Event Methods Matthew Daigle, Xenofon Koutsoukos, and Gautam Biswas

    E-print Network

    Koutsoukos, Xenofon D.

    Fault Diagnosis of Continuous Systems Using Discrete-Event Methods Matthew Daigle, Xenofon.j.daigle,xenofon.koutsoukos,gautam.biswas@vanderbilt.edu Abstract-- Fault diagnosis is crucial for ensuring the safe operation of complex engineering systems fault isolation in systems with complex continuous dynamics. This paper presents a novel discrete- event

  3. A novel end-to-end fault detection and localization protocol for wavelength-routed WDM networks

    NASA Astrophysics Data System (ADS)

    Zeng, Hongqing; Vukovic, Alex; Huang, Changcheng

    2005-09-01

    Recently the wavelength division multiplexing (WDM) networks are becoming prevalent for telecommunication networks. However, even a very short disruption of service caused by network faults may lead to high data loss in such networks due to the high date rates, increased wavelength numbers and density. Therefore, the network survivability is critical and has been intensively studied, where fault detection and localization is the vital part but has received disproportional attentions. In this paper we describe and analyze an end-to-end lightpath fault detection scheme in data plane with the fault notification in control plane. The endeavor is focused on reducing the fault detection time. In this protocol, the source node of each lightpath keeps sending hello packets to the destination node exactly following the path for data traffic. The destination node generates an alarm once a certain number of consecutive hello packets are missed within a given time period. Then the network management unit collects all alarms and locates the faulty source based on the network topology, as well as sends fault notification messages via control plane to either the source node or all upstream nodes along the lightpath. The performance evaluation shows such a protocol can achieve fast fault detection, and at the same time, the overhead brought to the user data by hello packets is negligible.

  4. Fault detection and isolation of PEM fuel cell system based on nonlinear analytical redundancy. An application via parity space approach

    NASA Astrophysics Data System (ADS)

    Aitouche, A.; Yang, Q.; Ould Bouamama, B.

    2011-05-01

    This paper presents a procedure dealing with the issue of fault detection and isolation (FDI) using nonlinear analytical redundancy (NLAR) technique applied in a proton exchange membrane (PEM) fuel cell system based on its mathematic model. The model is proposed and simplified into a five orders state space representation. The transient phenomena captured in the model include the compressor dynamics, the flow characteristics, mass and energy conservation and manifold fluidic mechanics. Nonlinear analytical residuals are generated based on the elimination of the unknown variables of the system by an extended parity space approach to detect and isolate actuator and sensor faults. Finally, numerical simulation results are given corresponding to a faults signature matrix.

  5. Fault-tolerant linear optics quantum computation by error-detecting quantum state transfer

    E-print Network

    Jaeyoon Cho

    2007-10-07

    A scheme for linear optical implementation of fault-tolerant quantum computation is proposed, which is based on an error-detecting code. Each computational step is mediated by transfer of quantum information into an ancilla system embedding error-detection capability. Photons are assumed to be subjected to both photon loss and depolarization, and the threshold region of their strengths for scalable quantum computation is obtained, together with the amount of physical resources consumed. Compared to currently known results, the present scheme reduces the resource requirement, while yielding a comparable threshold region.

  6. A roller bearing fault diagnosis method based on EMD energy entropy and ANN

    NASA Astrophysics Data System (ADS)

    Yu, Yang; Yu, Dejie; Cheng, Junsheng

    2006-06-01

    According to the non-stationary characteristics of roller bearing fault vibration signals, a roller bearing fault diagnosis method based on empirical mode decomposition (EMD) energy entropy is put forward in this paper. Firstly, original acceleration vibration signals are decomposed into a finite number of stationary intrinsic mode functions (IMFs), then the concept of EMD energy entropy is proposed. The analysis results from EMD energy entropy of different vibration signals show that the energy of vibration signal will change in different frequency bands when bearing fault occurs. Therefore, to identify roller bearing fault patterns, energy feature extracted from a number of IMFs that contained the most dominant fault information could serve as input vectors of artificial neural network. The analysis results from roller bearing signals with inner-race and out-race faults show that the diagnosis approach based on neural network by using EMD to extract the energy of different frequency bands as features can identify roller bearing fault patterns accurately and effectively and is superior to that based on wavelet packet decomposition and reconstruction.

  7. 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

    2010-01-01

    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 [Ed. 's note: See Appendix A-Definitions D 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 perfomu:d average to below average in detection of gear tooth surface pitting failures. The ODM sensor was successful in detecting a significant 8lDOunt 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.

  8. Automatic Channel Fault Detection and Diagnosis System for a Small Animal APD-Based Digital PET Scanner

    E-print Network

    Jonathan Charest; Jean-François Beaudoin; Jules Cadorette; Roger Lecomte; Charles-Antoine Brunet; Réjean Fontaine

    2014-06-16

    Fault detection and diagnosis is critical to many applications in order to ensure proper operation and performance over time. Positron emission tomography (PET) systems that require regular calibrations by qualified scanner operators are good candidates for such continuous improvements. Furthermore, for scanners employing one-to-one coupling of crystals to photodetectors to achieve enhanced spatial resolution and contrast, the calibration task is even more daunting because of the large number of independent channels involved. To cope with the additional complexity of the calibration and quality control procedures of these scanners, an intelligent system (IS) was designed to perform fault detection and diagnosis (FDD) of malfunctioning channels. The IS can be broken down into four hierarchical modules: parameter extraction, channel fault detection, fault prioritization and diagnosis. Of these modules, the first two have previously been reported and this paper focuses on fault prioritization and diagnosis. The purpose of the fault prioritization module is to help the operator to zero in on the faults that need immediate attention. The fault diagnosis module will then identify the causes of the malfunction and propose an explanation of the reasons that lead to the diagnosis. The FDD system was implemented on a LabPET avalanche photodiode (APD)-based digital PET scanner. Experiments demonstrated a FDD Sensitivity of 99.3 % (with a 95% confidence interval (CI) of: [98.7, 99.9]) for major faults. Globally, the Balanced Accuracy of the diagnosis for varying fault severities is 92 %. This suggests the IS can greatly benefit the operators in their maintenance task.

  9. Analysis of Space Shuttle Ground Support System Fault Detection, Isolation, and Recovery Processes and Resources

    NASA Technical Reports Server (NTRS)

    Gross, Anthony R.; Gerald-Yamasaki, Michael; Trent, Robert P.

    2009-01-01

    As part of the FDIR (Fault Detection, Isolation, and Recovery) Project for the Constellation Program, a task was designed within the context of the Constellation Program FDIR project called the Legacy Benchmarking Task to document as accurately as possible the FDIR processes and resources that were used by the Space Shuttle ground support equipment (GSE) during the Shuttle flight program. These results served as a comparison with results obtained from the new FDIR capability. The task team assessed Shuttle and EELV (Evolved Expendable Launch Vehicle) historical data for GSE-related launch delays to identify expected benefits and impact. This analysis included a study of complex fault isolation situations that required a lengthy troubleshooting process. Specifically, four elements of that system were considered: LH2 (liquid hydrogen), LO2 (liquid oxygen), hydraulic test, and ground special power.

  10. Fault finder

    DOEpatents

    Bunch, Richard H. (1614 NW. 106th St., Vancouver, WA 98665)

    1986-01-01

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

  11. An autonomous fault detection, isolation, and recovery system for a 20-kHz electric power distribution test bed

    NASA Technical Reports Server (NTRS)

    Quinn, Todd M.; Walters, Jerry L.

    1991-01-01

    Future space explorations will require long term human presence in space. Space environments that provide working and living quarters for manned missions are becoming increasingly larger and more sophisticated. Monitor and control of the space environment subsystems by expert system software, which emulate human reasoning processes, could maintain the health of the subsystems and help reduce the human workload. The autonomous power expert (APEX) system was developed to emulate a human expert's reasoning processes used to diagnose fault conditions in the domain of space power distribution. APEX is a fault detection, isolation, and recovery (FDIR) system, capable of autonomous monitoring and control of the power distribution system. APEX consists of a knowledge base, a data base, an inference engine, and various support and interface software. APEX provides the user with an easy-to-use interactive interface. When a fault is detected, APEX will inform the user of the detection. The user can direct APEX to isolate the probable cause of the fault. Once a fault has been isolated, the user can ask APEX to justify its fault isolation and to recommend actions to correct the fault. APEX implementation and capabilities are discussed.

  12. Method for detecting toxic gases

    DOEpatents

    Stetter, J.R.; Zaromb, S.; Findlay, M.W. Jr.

    1991-10-08

    A method is disclosed which is capable of detecting low concentrations of a pollutant or other component in air or other gas. This method utilizes a combination of a heating filament having a catalytic surface of a noble metal for exposure to the gas and producing a derivative chemical product from the component. An electrochemical sensor responds to the derivative chemical product for providing a signal indicative of the product. At concentrations in the order of about 1-100 ppm of tetrachloroethylene, neither the heating filament nor the electrochemical sensor is individually capable of sensing the pollutant. In the combination, the heating filament converts the benzyl chloride to one or more derivative chemical products which may be detected by the electrochemical sensor. 6 figures.

  13. A novel micro-Raman technique to detect and characterize 4H-SiC stacking faults

    NASA Astrophysics Data System (ADS)

    Piluso, N.; Camarda, M.; La Via, F.

    2014-10-01

    A novel Micro-Raman technique was designed and used to detect extended defects in 4H-SiC homoepitaxy. The technique uses above band-gap high-power laser densities to induce a local increase of free carriers in undoped epitaxies (n < 1016 at/cm-3), creating an electronic plasma that couples with the longitudinal optical (LO) Raman mode. The Raman shift of the LO phonon-plasmon-coupled mode (LOPC) increases as the free carrier density increases. Crystallographic defects lead to scattering or recombination of the free carriers which results in a loss of coupling with the LOPC, and in a reduction of the Raman shift. Given that the LO phonon-plasmon coupling is obtained thanks to the free carriers generated by the high injection level induced by the laser, we named this technique induced-LOPC (i-LOPC). This technique allows the simultaneous determination of both the carrier lifetime and carrier mobility. Taking advantage of the modifications on the carrier lifetime induced by extended defects, we were able to determine the spatial morphology of stacking faults; the obtained morphologies were found to be in excellent agreement with those provided by standard photoluminescence techniques. The results show that the detection of defects via i-LOPC spectroscopy is totally independent from the stacking fault photoluminescence signals that cover a large energy range up to 0.7 eV, thus allowing for a single-scan simultaneous determination of any kind of stacking fault. Combining the i-LOPC method with the analysis of the transverse optical mode, the micro-Raman characterization can determine the most important properties of unintentionally doped film, including the stress status of the wafer, lattice impurities (point defects, polytype inclusions) and a detailed analysis of crystallographic defects, with a high spectral and spatial resolution.

  14. A novel micro-Raman technique to detect and characterize 4H-SiC stacking faults

    SciTech Connect

    Piluso, N., E-mail: nicolo.piluso@imm.cnr.it; Camarda, M.; La Via, F. [IMM-CNR, stradale primo sole, 50, 95121 Catania (Italy)

    2014-10-28

    A novel Micro-Raman technique was designed and used to detect extended defects in 4H-SiC homoepitaxy. The technique uses above band-gap high-power laser densities to induce a local increase of free carriers in undoped epitaxies (n?faults; the obtained morphologies were found to be in excellent agreement with those provided by standard photoluminescence techniques. The results show that the detection of defects via i-LOPC spectroscopy is totally independent from the stacking fault photoluminescence signals that cover a large energy range up to 0.7?eV, thus allowing for a single-scan simultaneous determination of any kind of stacking fault. Combining the i-LOPC method with the analysis of the transverse optical mode, the micro-Raman characterization can determine the most important properties of unintentionally doped film, including the stress status of the wafer, lattice impurities (point defects, polytype inclusions) and a detailed analysis of crystallographic defects, with a high spectral and spatial resolution.

  15. Optimal fault location

    E-print Network

    Knezev, Maja

    2008-10-10

    after the accurate fault condition and location are detected. This thesis has been focusing on automated fault location procedure. Different fault location algorithms, classified according to the spatial placement of physical measurements on single ended...

  16. Optimal fault location

    E-print Network

    Knezev, Maja

    2009-05-15

    after the accurate fault condition and location are detected. This thesis has been focusing on automated fault location procedure. Different fault location algorithms, classified according to the spatial placement of physical measurements on single ended...

  17. Application of an RF Biased Langmuir Probe to Etch Reactor Chamber Matching, Fault Detection and Process Control

    NASA Astrophysics Data System (ADS)

    Keil, Douglas; Booth, Jean-Paul; Benjamin, Neil; Thorgrimsson, Chris; Brooks, Mitchell; Nagai, Mikio; Albarede, Luc; Kim, Jung

    2008-10-01

    Semiconductor device manufacturing typically occurs in an environment of both increasing equipment costs and per unit sale price shrinkage. Profitability in such a conflicted economic environment depends critically on yield, throughput and cost-of-ownership. This has resulted in increasing interest in improved fault detection, process diagnosis, and advanced process control. Achieving advances in these areas requires an integrated understanding of the basic physical principles driving the processes of interest and the realities of commercial manufacturing. Following this trend, this work examines the usefulness of an RF-biased planar Langmuir probe^1. This method delivers precise real-time (10 Hz) measurements of ion flux and tail weighted electron temperature. However, it is also mechanically non-intrusive, reliable and insensitive to contamination and deposition on the probe. Since the measured parameters are closely related to physical processes occurring at the wafer-plasma interface, significant improvements in process control, chamber matching and fault detection are achieved. Examples illustrating the improvements possible will be given. ^1J.P. Booth, N. St. J. Braithwaite, A. Goodyear and P. Barroy, Rev.Sci.Inst., Vol.71, No.7, July 2000, pgs. 2722-2727.

  18. Fault Scarp Detection Beneath Dense Vegetation Cover: Airborne Lidar Mapping of the Seattle Fault Zone, Bainbridge Island, Washington State

    NASA Technical Reports Server (NTRS)

    Harding, David J.; Berghoff, Gregory S.

    2000-01-01

    The emergence of a commercial airborne laser mapping industry is paying major dividends in an assessment of earthquake hazards in the Puget Lowland of Washington State. Geophysical observations and historical seismicity indicate the presence of active upper-crustal faults in the Puget Lowland, placing the major population centers of Seattle and Tacoma at significant risk. However, until recently the surface trace of these faults had never been identified, neither on the ground nor from remote sensing, due to cover by the dense vegetation of the Pacific Northwest temperate rainforests and extremely thick Pleistocene glacial deposits. A pilot lidar mapping project of Bainbridge Island in the Puget Sound, contracted by the Kitsap Public Utility District (KPUD) and conducted by Airborne Laser Mapping in late 1996, spectacularly revealed geomorphic features associated with fault strands within the Seattle fault zone. The features include a previously unrecognized fault scarp, an uplifted marine wave-cut platform, and tilted sedimentary strata. The United States Geologic Survey (USGS) is now conducting trenching studies across the fault scarp to establish ages, displacements, and recurrence intervals of recent earthquakes on this active fault. The success of this pilot study has inspired the formation of a consortium of federal and local organizations to extend this work to a 2350 square kilometer (580,000 acre) region of the Puget Lowland, covering nearly the entire extent (approx. 85 km) of the Seattle fault. The consortium includes NASA, the USGS, and four local groups consisting of KPUD, Kitsap County, the City of Seattle, and the Puget Sound Regional Council (PSRC). The consortium has selected Terrapoint, a commercial lidar mapping vendor, to acquire the data.

  19. Apparatus for and method of testing an electrical ground fault circuit interrupt device

    DOEpatents

    Andrews, L.B.

    1998-08-18

    An apparatus for testing a ground fault circuit interrupt device includes a processor, an input device connected to the processor for receiving input from an operator, a storage media connected to the processor for storing test data, an output device connected to the processor for outputting information corresponding to the test data to the operator, and a calibrated variable load circuit connected between the processor and the ground fault circuit interrupt device. The ground fault circuit interrupt device is configured to trip a corresponding circuit breaker. The processor is configured to receive signals from the calibrated variable load circuit and to process the signals to determine a trip threshold current and/or a trip time. A method of testing the ground fault circuit interrupt device includes a first step of providing an identification for the ground fault circuit interrupt device. Test data is then recorded in accordance with the identification. By comparing test data from an initial test with test data from a subsequent test, a trend of performance for the ground fault circuit interrupt device is determined. 17 figs.

  20. Apparatus for and method of testing an electrical ground fault circuit interrupt device

    DOEpatents

    Andrews, Lowell B. (2181-13th Ave. SW., Largo, FL 34640)

    1998-01-01

    An apparatus for testing a ground fault circuit interrupt device includes a processor, an input device connected to the processor for receiving input from an operator, a storage media connected to the processor for storing test data, an output device connected to the processor for outputting information corresponding to the test data to the operator, and a calibrated variable load circuit connected between the processor and the ground fault circuit interrupt device. The ground fault circuit interrupt device is configured to trip a corresponding circuit breaker. The processor is configured to receive signals from the calibrated variable load circuit and to process the signals to determine a trip threshold current and/or a trip time. A method of testing the ground fault circuit interrupt device includes a first step of providing an identification for the ground fault circuit interrupt device. Test data is then recorded in accordance with the identification. By comparing test data from an initial test with test data from a subsequent test, a trend of performance for the ground fault circuit interrupt device is determined.