WorldWideScience

Sample records for ground fault detection

  1. PV Systems Reliability Final Technical Report: Ground Fault Detection

    Energy Technology Data Exchange (ETDEWEB)

    Lavrova, Olga [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flicker, Jack David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Johnson, Jay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-01-01

    We have examined ground faults in PhotoVoltaic (PV) arrays and the efficacy of fuse, current detection (RCD), current sense monitoring/relays (CSM), isolation/insulation (Riso) monitoring, and Ground Fault Detection and Isolation (GFID) using simulations based on a Simulation Program with Integrated Circuit Emphasis SPICE ground fault circuit model, experimental ground faults installed on real arrays, and theoretical equations.

  2. Development Ground Fault Detecting System for D.C Voltage Line

    Energy Technology Data Exchange (ETDEWEB)

    Kim Taek Soo; Song Ung Il; Gwon, Young Dong; Lee Hyoung Kee [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

    1996-12-31

    It is necessary to keep the security of reliability and to maximize the efficiency of maintenance by prompt detection of a D.C feeder ground fault point at the built ed or a building power plants. At present, the most of the power plants are set up the ground fault indicator lamp in the monitor room. If a ground fault occurs on DC voltage feeder, a current through the ground fault relay is adjusted and the lamps have brightened while the current flows the relay coil. In order to develop such a system, it is analyzed a D.C feeder ground circuit theoretically and studied a principles which can determine ground fault point or a polarity discrimination and a phase discrimination of the line. So, the developed system through this principles can compute a resistance ground fault current and a capacitive ground fault current. It shows that the system can defect a ground fault point or a bad insulated line by measuring a power plant D.C feeder insulation resistance at the un interruptible power status, and therefore the power plant could protect an unexpected service interruption . (author). 18 refs., figs.

  3. Fault Detection and Isolation of Satellite Formations using a Ground Station Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal is for the development a fault detection and isolation (FDI) algorithm for a formation of satellites but processed at a ground station. The algorithm...

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

    Science.gov (United States)

    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.

  5. Fault Detection Using Polarimetric Single-Input-Multi-Output Ground Penetrating Radar Technique in Mason, Texas

    Science.gov (United States)

    Amara, A.; Everett, M. E.

    2014-12-01

    At the Mason Mountain Wildlife Management Area (MMWMA) near Mason, Texas, we conducted a 2D ground penetrating radar (GPR) survey using single-input-multi-output (SIMO) acquisition technique to image a Pennsylvanian high-angle normal fault. At the MMWMA, the surface geology is mapped extensively but the subsurface remains largely unknown. The main objective of our study is to develop a detailed subsurface structural image of the fault and evaluate existing hypotheses on fault development. Also, to develop and apply a new methodology based on Polarimetric SIMO acquisition geometry. This new methodology allows the subsurface structures to be viewed simultaneously from different angles and can help reduce noise caused by the heterogeneities that affect the electromagnetic waves. We used a pulseEKKO pro 200 GPR with 200 MHz antennae to acquire 8 north-south lines across the fault. Each line is 30 meters long with the transmitter starting on the Town Mountain Granite, footwall, with the receiver stepping 40 cm until the end of the line crossing the fault on to the Hickory Sandstone, hanging wall. Each pass consisted of a stationary transmitter antenna and the moving receiver antenna. The data were initially processed with standard steps including low-cut dewow filter, background subtraction filter and gain control. Advanced processing techniques include migration, phased array processing, velocity analysis, and normal moveout. We will compare the GPR results with existing geophysical datasets at the same site, including electromagnetic (EM), seismic, and seismoelectric.

  6. Detecting the single line to ground short circuit fault in the submarine’s power system using the artificial neural network

    Directory of Open Access Journals (Sweden)

    Behniafar Ali

    2013-01-01

    Full Text Available The electric marine instruments are newly inserted in the trade and industry, for which the existence of an equipped and reliable power system is necessitated. One of the features of such a power system is that it cannot have an earth system causing the protection relays not to be able to detect the single line to ground short circuit fault. While on the other hand, the occurrence of another similar fault at the same time can lead to the double line fault and thereby the tripping of relays and shortening of vital loads. This in turn endangers the personals' security and causes the loss of military plans. From the above considerations, it is inferred that detecting the single line to ground fault in the marine instruments is of a special importance. In this way, this paper intends to detect the single line to ground fault in the power systems of the marine instruments using the wavelet transform and Multi-Layer Perceptron (MLP neural network. In the numerical analysis, several different types of short circuit faults are simulated on several marine power systems and the proposed approach is applied to detect the single line to ground fault. The results are of a high quality and preciseness and perfectly demonstrate the effectiveness of the proposed approach.

  7. Inverter Ground Fault Overvoltage Testing

    Energy Technology Data Exchange (ETDEWEB)

    Hoke, Andy [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Nelson, Austin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Chakraborty, Sudipta [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Chebahtah, Justin [SolarCity Corporation, San Mateo, CA (United States); Wang, Trudie [SolarCity Corporation, San Mateo, CA (United States); McCarty, Michael [SolarCity Corporation, San Mateo, CA (United States)

    2015-08-12

    This report describes testing conducted at NREL to determine the duration and magnitude of transient overvoltages created by several commercial PV inverters during ground fault conditions. For this work, a test plan developed by the Forum on Inverter Grid Integration Issues (FIGII) has been implemented in a custom test setup at NREL. Load rejection overvoltage test results were reported previously in a separate technical report.

  8. Evaluating transmission towers potentials during ground faults

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    During ground faults on transmission lines, a number of towers near the fault are likely to acquire high potentials to ground. These tower voltages, if excessive, may present a hazard to humans and animals. This paper presents analytical methods in order to determine the transmission towers potentials during ground faults, for long and short lines. The author developed a global systematic approach to calculate these voltages, which are dependent of a number of factors. Some of the most important factors are: magnitudes of fault currents, fault location with respect to the line terminals, conductor arrangement on the tower and the location of the faulted phase, the ground resistance of the faulted tower, soil resistivity, number, material and size of ground wires. The effects of these factors on the faulted tower voltages have been also examined for different types of power lines.

  9. Detection of arcing ground fault location on a distribution network connected PV system; Hikarihatsuden renkei haidensen ni okeru koko chiryaku kukan no kenshutsuho

    Energy Technology Data Exchange (ETDEWEB)

    Sato, M.; Iwaya, K.; Morooka, Y. [Hachinohe Institute of Technology, Aomori (Japan)

    1996-10-27

    In the near future, it is supposed that a great number of small-scale distributed power sources, such as photovoltaic power generation for general houses, will be interconnected with the ungrounded neutral distribution system in Japan. When ground fault of commercial frequency once occurs, great damage is easily guessed. This paper discusses the effect of the ground fault on the ground phase current using a 6.6 kV high-voltage model system by considering the non-linear self-inductance in the line, and by considering the non-linear relation of arcing ground fault current frequency. In the present method, the remarkable difference of series resonance frequency determined by the inductance and earth capacity between the source side and load side is utilized for the detection of high-voltage arcing ground fault location. In this method, there are some cases in which the non-linear effect obtained by measuring the inductance of sound phase including the secondary winding of transformer can not be neglected. Especially, for the actual high-voltage system, it was shown that the frequency characteristics of transformer inductance for distribution should be theoretically derived in the frequency range between 2 kHz and 6 kHz. 2 refs., 5 figs., 1 tab.

  10. Ground Fault Line Selection with Improved Residual Flow Incremental Method

    Directory of Open Access Journals (Sweden)

    Wenhong Li

    2013-08-01

    Full Text Available According to the shortcoming of single-phase ground fault line selection method in the resonant grounded system such as the uncertainty of its device by fast compensation with the automatic compensation equipment, an arc suppression and residual flow incremental method is proposed to effectively choose the earth fault line. Firstly, when the single-phase ground fault occurs, the arc suppression coil parameters are adjusted to realize compensation and arc suppression. Then the arc suppression coil inductance values are modulated to make the zero-sequence current of fault line changed, at the same time, the zero-sequence current value is detected and its change will be captured to select the fault line. The simulation experiments prove that the arc grounding over voltage damage can be effectively reduced by arc suppression coil full compensation and fault line can be effectively selected by arc suppression and residual flow increment method.

  11. Fault detection and isolation in systems with parametric faults

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1999-01-01

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

  12. Fault diagnosis in neutral point indirectly grounded system based on information fusion

    Institute of Scientific and Technical Information of China (English)

    于飞; 鞠丽叶; 刘喜梅; 崔平远; 钟秋海

    2003-01-01

    In neutral point indirectly grounded systems, phase-to-ground fault is putting new demands on fault diagnosis technology. Information fusion is applied to detect the phase-to-ground fault, which integrates several sources of information, including line current, line voltage, zero sequence current and voltage, and quintic harmonic wave component. This method is testified through the simulation of Matlab. Simulation results show that the precision and reliability of the detection has been greatly increased.

  13. Final Technical Report: PV Fault Detection Tool.

    Energy Technology Data Exchange (ETDEWEB)

    King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    The PV Fault Detection Tool project plans to demonstrate that the FDT can (a) detect catastrophic and degradation faults and (b) identify the type of fault. This will be accomplished by collecting fault signatures using different instruments and integrating this information to establish a logical controller for detecting, diagnosing and classifying each fault.

  14. Static Decoupling in fault detection

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    1998-01-01

    An algebraic approach is given for a design of a static residual weighting factor in connection with fault detection. A complete parameterization is given of the weighting factor which will minimize a given performance index......An algebraic approach is given for a design of a static residual weighting factor in connection with fault detection. A complete parameterization is given of the weighting factor which will minimize a given performance index...

  15. Row fault detection system

    Science.gov (United States)

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

    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.

  16. Spatial distribution of near-fault ground motion

    Institute of Scientific and Technical Information of China (English)

    刘启方; 袁一凡; 金星

    2004-01-01

    Near-fault strong ground motion of strike-slip and dip-slip of vertical and inclined rectangular fault in half-space and layered half-space is analyzed by dislocation source model. The Fourier spectra ratio of ground motion is adopted to study the characteristics of near-fault ground motion. For both slip models, near-fault strong ground motion with high amplitude is located in a narrow belt area along the projection of the fault on the ground and mainly controlled by the sub-faults nearby. Directivity of strike-slip fault is more dominant in long period for components perpendicular to the fault, and more dominant in long period for components parallel to the fault for dip-slip fault. The deeper the location of the source is, the more slowly the amplitude of ground motion attenuates.There is obvious hanging wall effect in ground motion of inclined fault, and the spatial distribution of ground motion is asymmetric which coincides with observational data. Finally, a fitting function of spatial distribution for near-fault ground motion is proposed and compared with near source factors of the 1997 Uniform Building Code of USA.

  17. A Generalised Fault Protection Structure Proposed for Uni-grounded Low-Voltage AC Microgrids

    Science.gov (United States)

    Bui, Duong Minh; Chen, Shi-Lin; Lien, Keng-Yu; Jiang, Jheng-Lun

    2016-04-01

    This paper presents three main configurations of uni-grounded low-voltage AC microgrids. Transient situations of a uni-grounded low-voltage (LV) AC microgrid (MG) are simulated through various fault tests and operation transition tests between grid-connected and islanded modes. Based on transient simulation results, available fault protection methods are proposed for main and back-up protection of a uni-grounded AC microgrid. In addition, concept of a generalised fault protection structure of uni-grounded LVAC MGs is mentioned in the paper. As a result, main contributions of the paper are: (i) definition of different uni-grounded LVAC MG configurations; (ii) analysing transient responses of a uni-grounded LVAC microgrid through line-to-line faults, line-to-ground faults, three-phase faults and a microgrid operation transition test, (iii) proposing available fault protection methods for uni-grounded microgrids, such as: non-directional or directional overcurrent protection, under/over voltage protection, differential current protection, voltage-restrained overcurrent protection, and other fault protection principles not based on phase currents and voltages (e.g. total harmonic distortion detection of currents and voltages, using sequence components of current and voltage, 3I0 or 3V0 components), and (iv) developing a generalised fault protection structure with six individual protection zones to be suitable for different uni-grounded AC MG configurations.

  18. Wind turbine fault detection and fault tolerant control

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Johnson, Kathryn

    2013-01-01

    In this updated edition of a previous wind turbine fault detection and fault tolerant control challenge, we present a more sophisticated wind turbine model and updated fault scenarios to enhance the realism of the challenge and therefore the value of the solutions. This paper describes the challe...

  19. Fault detection using (PI) observers

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Stoustrup, J.; Shafai, B.

    The fault detection and isolation (FDI) problem in connection with Proportional Integral (PI) Observers is considered in this paper. A compact formulation of the FDI design problem using PI observers is given. An analysis of the FDI design problem is derived with respectt to the time domain...... properties. A method for design of PI observers applied to FDI is given....

  20. Fault Detection for Nonlinear Systems

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, H.H.

    1998-01-01

    The paper describes a general method for designing fault detection and isolation (FDI) systems for nonlinear processes. For a rich class of nonlinear systems, a nonlinear FDI system can be designed using convex optimization procedures. The proposed method is a natural extension of methods based...

  1. Robust fault detection filter design

    Science.gov (United States)

    Douglas, Randal Kirk

    The detection filter is a specially tuned linear observer that forms the residual generation part of an analytical redundancy system designed for model-based fault detection and identification. The detection filter has an invariant state subspace structure that produces a residual with known and fixed directional characteristics in response to a known design fault direction. In addition to a parameterization of the detection filter gain, three methods are given for improving performance in the presence of system disturbances, sensor noise, model mismatch and sensitivity to small parameter variations. First, it is shown that by solving a modified algebraic Riccati equation, a stabilizing detection filter gain is found that bounds the H-infinity norm of the transfer matrix from system disturbances and sensor noise to the detection filter residual. Second, a specially chosen expanded-order detection filter is formed with fault detection properties identical to a set of independent reduced-order filters that have no structural constraints. This result is important to the practitioner because the difficult problem of finding a detection filter insensitive to disturbances and sensor noise is converted to the easier problem of finding a set of uncoupled noise insensitive filters. Furthermore, the statistical properties of the reduced-order filter residuals are easier to find than the statistical properties of the structurally constrained detection filter residual. Third, an interpretation of the detection filter as a special case of the dual of the restricted decoupling problem leads to a new detection filter eigenstructure assignment algorithm. The new algorithm places detection filter left eigenvectors, which annihilate the detection spaces, rather than right eigenvectors, which span the detection spaces. This allows for a more flexible observer based fault detection system structure that could not be formulated as a detection filter. Furthermore, the link to the dual

  2. Single Phase-to-Ground Fault Line Identification and Section Location Method for Non-Effectively Grounded Distribution Systems Based on Signal Injection

    Institute of Scientific and Technical Information of China (English)

    PAN Zhencun; WANG Chengshan; CONG Wei; ZHANG Fan

    2008-01-01

    A diagnostic signal current trace detecting based single phase-to-ground fault line identifica- tion and section location method for non-effectively grounded distribution systems is presented in thisi oaper. A special diagnostic signal current is injected into the fault distribution system, and then it is de- tected at the outlet terminals to identify the fault line and at the sectionalizing or branching point along the fault line to locate the fault section. The method has been put into application in actual distribution network and field experience shows that it can identify the fault line and locate the fault section correctly and effectively.

  3. Expert System Detects Power-Distribution Faults

    Science.gov (United States)

    Walters, Jerry L.; Quinn, Todd M.

    1994-01-01

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

  4. Actuator Fault Detection and Diagnosis for Quadrotors

    NARCIS (Netherlands)

    Lu, P.; Van Kampen, E.-J.; Yu, B.

    2014-01-01

    This paper presents a method for fault detection and diagnosis of actuator loss of effectiveness for a quadrotor helicopter. This paper not only considers the detection of the actuator loss of effectiveness faults, but also addresses the diagnosis of the faults. The detection and estimation of the f

  5. Novelty Detection Methods and Novel Fault Class Detection

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jiafan; HUANG Zhichu; WANG Xiaoming

    2006-01-01

    The ability to detect a new fault class can be a useful feature for an intelligent fault classification and diagnosis system. We adopt two novelty detection methods, the support vector data description (SVDD) and the Parzen density estimation, to represent known fault class samples, and to detect new fault class samples. The experiments on real multi-class bearing fault data show that the SVDD can give both high novelty detection rate and target recognition rate, respectively for the prescribed 'unknown' fault samples and the known fault samples by choosing the appropriate SVDD algorithm parameters; but the Parzen density estimation only give a better novelty detection rate in our experiments.

  6. Principle and Control Design of Active Ground-Fault Arc Suppression Device for Full Compensation of Ground Current

    DEFF Research Database (Denmark)

    Wang, Wen; Zeng, Xiangjun; Yan, Lingjie;

    2017-01-01

    Traditional ground-fault arc suppression devices mainly deal with capacitive component of ground current and have weak effect on the active and harmonic ones, which limits the arc suppression performance. The capacitive current detection needed in them suffers from low accuracy and robustness....... The commonly-used large-capacity reactive component may bring about overvoltage because of possible resonance with the distributed phase-to-ground capacitance. To solve these problems, an active ground-fault arc suppression device is presented. It employs a topology based on single-phase inverter to inject...... current into the neutral without any large-capacity reactors, and thus avoids the aforementioned overvoltage. It compensates all the active, reactive and harmonic components of the ground current to reliably extinguish the ground-fault arcs. A dual-loop voltage control method is proposed to realize arc...

  7. Ground Fault Overvoltage With Inverter-Interfaced Distributed Energy Resources

    Energy Technology Data Exchange (ETDEWEB)

    Ropp, Michael; Hoke, Anderson; Chakraborty, Sudipta; Schutz, Dustin; Mouw, Chris; Nelson, Austin; McCarty, Michael; Wang, Trudie; Sorenson, Adam

    2017-04-01

    Ground Fault Overvoltage can occur in situations in which a four-wire distribution circuit is energized by an ungrounded voltage source during a single phase to ground fault. The phenomenon is well-documented with ungrounded synchronous machines, but there is considerable discussion about whether inverters cause this phenomenon, and consequently whether inverters require effective grounding. This paper examines the overvoltages that can be supported by inverters during single phase to ground faults via theory, simulation and experiment, identifies the relevant physical mechanisms, quantifies expected levels of overvoltage, and makes recommendations for optimal mitigation.

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

    DEFF Research Database (Denmark)

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

    1998-01-01

    processes and communication systems lead to demands for improved monitoring of power distribution networks so that the quality of power delivery can be kept at a controlled level. The ground fault localization method for each feeder in a network is based on the centralized frequency broadband measurement...... of three phase voltages and currents. The method consists of a feature extractor, based on a grid description of the feeder by impulse responses, and a neural network for ground fault localization. The emphasis of this paper is the feature extractor, and the detection of the time instance of a ground fault...

  9. Fault detection and isolation for complex system

    Science.gov (United States)

    Jing, Chan Shi; Bayuaji, Luhur; Samad, R.; Mustafa, M.; Abdullah, N. R. H.; Zain, Z. M.; Pebrianti, Dwi

    2017-07-01

    Fault Detection and Isolation (FDI) is a method to monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. A two wheel robot is used as a complex system in this study. The aim of the research is to construct and design a Fault Detection and Isolation algorithm. The proposed method for the fault identification is using hybrid technique that combines Kalman filter and Artificial Neural Network (ANN). The Kalman filter is able to recognize the data from the sensors of the system and indicate the fault of the system in the sensor reading. Error prediction is based on the fault magnitude and the time occurrence of fault. Additionally, Artificial Neural Network (ANN) is another algorithm used to determine the type of fault and isolate the fault in the system.

  10. 3D simulation of near-fault strong ground motion:comparison between surface rupture fault and buried fault

    Institute of Scientific and Technical Information of China (English)

    Liu Qifang; Yuan Yifan; Jin Xing

    2007-01-01

    In this paper,near-fault strong ground motions caused by a surface rupture fault(SRF)and a buried fault(BF) are numerically simulated and compared by using a time-space-decoupled,explicit finite element method combined with a multi-transmitting formula(MTF) of an artificial boundary.Prior to the comparison,verification of the explicit element method and the MTF is conducted.The comparison results show that the final dislocation of the SRF is larger than the BF for the same stress drop on the fault plane.The maximum final dislocation occurs on the fault upper line for the SRF;however,for the BF,the maximum final dislocation is located on the fault central part.Meanwhile,the PGA,PGV and PGD of long period ground motions(≤1 Hz)generated by the SRF are much higher than those of the BF in the near-fault region.The peak value of the velocity pulse generated by the SRF is also higher than the BF.Furthermore,it is found that in a very narrow region along the fault trace,ground motions caused by the SRF are much higher than by the BF.These results may explain why SRFs almost always cause heavy damage in near-fault regions compared to buried faults.

  11. Arc burst pattern analysis fault detection system

    Science.gov (United States)

    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.

  12. Fault Line Selection Method Considering Grounding Fault Angle for Distribution Network

    Institute of Scientific and Technical Information of China (English)

    Li Si-bo; Zhao Yu-lin; Li Ji-chang; Sui Tao

    2015-01-01

    In the distribution network system with its neutral point grounding via arc suppression coil, when single-phase grounding fault occurred near zero-crossing point of the phase voltage, the inaccuracy of the line selection always existed in existing methods. According to the characteristics that transient current was different between the fault feeder and other faultless feeders, wavelet transformation was performed on data of the transient current within a power frequency cycle after the fault occurred. Based on different fault angles, wavelet energy in corresponding frequency band was chosen to compare. The result was that wavelet energy in fault feeder was the largest of all, and it was larger than sum of those in other faultless feeders, when the bus broke down, the disparity between each wavelet energy was not significant. Fault line could be selected out by the criterion above. The results of MATLAB/simulink simulation experiment indicated that this method had anti-interference capacity and was feasible.

  13. New fault location system for power transmission lines using composite fiber-optic overhead ground wire (OPGW)

    Energy Technology Data Exchange (ETDEWEB)

    Urasawa, K. (Tokyo Electric Power Co., Inc. (Japan)); Kanemaru, K.; Toyota, S.; Sugiyama, K. (Hitachi Cable, Ltd., Tokyo (Japan))

    1989-10-01

    A new fault location (FL) method using composite fiber-optic overhead ground wires (OPGWs) is developed to find out where electrical faults occur on overhead power transmission lines. This method locates the fault section by detecting the current induced in the ground wire (GW), i.e. OPGW in this system. Since detected fault information is essentially uncertain, the new FL method treats the fault information oas a current distribution pattern throughout the power line, and applies Fuzzy Theory to realize the human-like manner of fault location used by electrical power engineers. It was confirmed by computer simulations that the fault section can be accurately located using this method under various conditions. This FL system has already been applied to several commercial power transmission lines and successfully located the sections where electrical faults occurred on actual power transmission lines.

  14. Fault Detection and Isolation for Spacecraft

    DEFF Research Database (Denmark)

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2002-01-01

    This article realizes nonlinear Fault Detection and Isolation for actuators, given there is no measurement of the states in the actuators. The Fault Detection and Isolation of the actuators is instead based on angular velocity measurement of the spacecraft and knowledge about the dynamics...

  15. Exact, almost and delayed fault detection

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Saberi, Ali; Stoorvogel, Anton A.;

    1999-01-01

    Considers the problem of fault detection and isolation while using zero or almost zero threshold. A number of different fault detection and isolation problems using exact or almost exact disturbance decoupling are formulated. Solvability conditions are given for the formulated design problems. Th...

  16. Fault Detection for a Diesel Engine Actuator

    DEFF Research Database (Denmark)

    Blanke, M.; Bøgh, S.A.; Jørgensen, R.B.

    1995-01-01

    An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI).......An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI)....

  17. Integration of control and fault detection

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Stoustrup, J.

    The integrated design of control and fault detection is studied. The result of the analysis is that it is possible to separate the design of the controller and the filter for fault detection in the case where the nominal model can be assumed to be fairly accurate. In the uncertain case, however...

  18. Active fault detection in MIMO systems

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2014-01-01

    The focus in this paper is on active fault detection (AFD) for MIMO systems with parametric faults. The problem of design of auxiliary inputs with respect to detection of parametric faults is investigated. An analysis of the design of auxiliary inputs is given based on analytic transfer functions...... from auxiliary input to residual outputs. The analysis is based on a singular value decomposition of these transfer functions Based on this analysis, it is possible to design auxiliary input as well as design of the associated residual vector with respect to every single parametric fault in the system...

  19. Ground-motion signature of dynamic ruptures on rough faults

    Science.gov (United States)

    Mai, P. Martin; Galis, Martin; Thingbaijam, Kiran K. S.; Vyas, Jagdish C.

    2016-04-01

    Natural earthquakes occur on faults characterized by large-scale segmentation and small-scale roughness. This multi-scale geometrical complexity controls the dynamic rupture process, and hence strongly affects the radiated seismic waves and near-field shaking. For a fault system with given segmentation, the question arises what are the conditions for producing large-magnitude multi-segment ruptures, as opposed to smaller single-segment events. Similarly, for variable degrees of roughness, ruptures may be arrested prematurely or may break the entire fault. In addition, fault roughness induces rupture incoherence that determines the level of high-frequency radiation. Using HPC-enabled dynamic-rupture simulations, we generate physically self-consistent rough-fault earthquake scenarios (M~6.8) and their associated near-source seismic radiation. Because these computations are too expensive to be conducted routinely for simulation-based seismic hazard assessment, we thrive to develop an effective pseudo-dynamic source characterization that produces (almost) the same ground-motion characteristics. Therefore, we examine how variable degrees of fault roughness affect rupture properties and the seismic wavefield, and develop a planar-fault kinematic source representation that emulates the observed dynamic behaviour. We propose an effective workflow for improved pseudo-dynamic source modelling that incorporates rough-fault effects and its associated high-frequency radiation in broadband ground-motion computation for simulation-based seismic hazard assessment.

  20. Unitary Approximations in Fault Detection Filter Design

    Directory of Open Access Journals (Sweden)

    Dušan Krokavec

    2016-01-01

    Full Text Available The paper is concerned with the fault detection filter design requirements that relax the existing conditions reported in the previous literature by adapting the unitary system principle in approximation of fault detection filter transfer function matrix for continuous-time linear MIMO systems. Conditions for the existence of a unitary construction are presented under which the fault detection filter with a unitary transfer function can be designed to provide high residual signals sensitivity with respect to faults. Otherwise, reflecting the emplacement of singular values in unitary construction principle, an associated structure of linear matrix inequalities with built-in constraints is outlined to design the fault detection filter only with a Hurwitz transfer function. All proposed design conditions are verified by the numerical illustrative examples.

  1. Transition and verification of ground fault protection method in Hokuriku Shinkansen line

    Directory of Open Access Journals (Sweden)

    Michiteru Koyanagi

    2016-01-01

    Full Text Available The electrical discharge gaps called S type horn are applied to the ground fault detection and protection in AC traction power supply system for high speed railway called Shinkansen. In this method, the earth resistance of the steel pipe pillar is an important factor for the ground fault protection by the electrical discharge. In this study, the analyses of the transient characteristics of grounding fault are carried out by using EMTP, and the ground resistance value required to trigger discharge at S type horn was calculated. Moreover, the protection effect of a discharge gap called GP the substation equipment that is a discharge gap which is inserted between rails and substation mesh is evaluated.

  2. Detecting Fan Faults in refrigerated Cabinets

    DEFF Research Database (Denmark)

    Thybo, C.; Rasmussen, B.D.; Izadi-Zamanabadi, Roozbeh

    2002-01-01

    Fault detection in supermarket refrigeration systems is an important topic due to both economic and food safety reasons. If faults can be detected and diagnosed before the system drifts outside the specified operational envelope, service costs can be reduced and in extreme cases the costly...... discarding of food products can be avoided. In the situations where the operational requirements can be met with a fault present, the system will operate with a higher energy consumption increasing the cost of operation. The objective of this study is to develop a robust method for detecting air circulation...

  3. Cell boundary fault detection system

    Science.gov (United States)

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

    2009-05-05

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

  4. Ground Surface Deformations Near a Fault-Bounded Groundwater Aquifer

    Science.gov (United States)

    Lipovsky, B.; Funning, G. J.; Ferretti, A.

    2011-12-01

    Geodetic data often reveal the presence of groundwater aquifers that are bounded by faults (Schmidt and Bürgmann, 2003; Galloway and Hoffmann, 2007; Bell et al., 2008). Whereas unrestricted groundwater aquifers exhibit a radially symmetric pattern of uplift with diffuse boundaries, aquifers that are bounded by faults have one or more sharp, linear boundaries. Interferometric synthetic aperture (InSAR) data, due to their high spatial density, are particularly well suited to observe fault bounded aquifers, and the Santa Clara Aquifer in the San Francisco Bay Area, California, constitutes an excellent example. The largest ground surface displacements in the Bay Area are due to the inflation of the Santa Clara aquifer, and InSAR data plainly show that the Santa Clara aquifer is partitioned by the Silver Creek fault. This study first develops a general model of the displacements at the surface of the Earth due to fluid diffusion through a buried permeable boundary such as a fault zone. This model is compared to InSAR data from the Silver Creek fault and we find that we are able to infer fault zone poromechanical properties from InSAR data that are comparable to in situ measurements. Our theoretical model is constrained by several geological and hydrological observations concerning the structure of fault zones. Analytical solutions are presented for the ground surface displacements due to a perfectly impermeable fault zone. This end-member family of models, however, does not fit the available data. We therefore make allowance for an arbitrarily layered, variably permeable, one-dimensional fault zone. Time-dependent ground surface deformations are calculated in the Laplace domain using an efficient semi-analytic method. This general model is applicable to other poroelastic regimes including geothermal and hydrocarbon systems. We are able to estimate fault zone hydraulic conductivity by comparing theoretical ground surface displacements in a permeable fault zone to

  5. Fault Detection and Isolation using Eigenstructure Assignment

    DEFF Research Database (Denmark)

    Jørgensen, R.B.; Patton, R.J.; Chen, J.

    1994-01-01

    The purpose of this article is to investigate the robustness to model uncertainties of observer based fault detection and isolation. The approach is designed with a straight forward dynamic nad the observer....

  6. Fault Detection and Isolation using Eigenstructure Assignment

    DEFF Research Database (Denmark)

    Jørgensen, R.B.; Patton, R.J.; Chen, J.

    1994-01-01

    The purpose of this article is to investigate the robustness to model uncertainties of observer based fault detection and isolation. The approach is designed with a straight forward dynamic nad the observer.......The purpose of this article is to investigate the robustness to model uncertainties of observer based fault detection and isolation. The approach is designed with a straight forward dynamic nad the observer....

  7. Statistical fault detection in photovoltaic systems

    KAUST Repository

    Garoudja, Elyes

    2017-05-08

    Faults in photovoltaic (PV) systems, which can result in energy loss, system shutdown or even serious safety breaches, are often difficult to avoid. Fault detection in such systems is imperative to improve their reliability, productivity, safety and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current (DC) side of PV systems is proposed. This approach combines the flexibility, and simplicity of a one-diode model with the extended capacity of an exponentially weighted moving average (EWMA) control chart to detect incipient changes in a PV system. The one-diode model, which is easily calibrated due to its limited calibration parameters, is used to predict the healthy PV array\\'s maximum power coordinates of current, voltage and power using measured temperatures and irradiances. Residuals, which capture the difference between the measurements and the predictions of the one-diode model, are generated and used as fault indicators. Then, the EWMA monitoring chart is applied on the uncorrelated residuals obtained from the one-diode model to detect and identify the type of fault. Actual data from the grid-connected PV system installed at the Renewable Energy Development Center, Algeria, are used to assess the performance of the proposed approach. Results show that the proposed approach successfully monitors the DC side of PV systems and detects temporary shading.

  8. DATA-MINING BASED FAULT DETECTION

    Institute of Scientific and Technical Information of China (English)

    Ma Hongguang; Han Chongzhao; Wang Guohua; Xu Jianfeng; Zhu Xiaofei

    2005-01-01

    This paper presents a fault-detection method based on the phase space reconstruction and data mining approaches for the complex electronic system. The approach for the phase space reconstruction of chaotic time series is a combination algorithm of multiple autocorrelation and Γ-test, by which the quasi-optimal embedding dimension and time delay can be obtained.The data mining algorithm, which calculates the radius of gyration of unit-mass point around the centre of mass in the phase space, can distinguish the fault parameter from the chaotic time series output by the tested system. The experimental results depict that this fault detection method can correctly detect the fault phenomena of electronic system.

  9. Controller modification applied for active fault detection

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Stoustrup, Jakob; Poulsen, Niels Kjølstad

    2014-01-01

    This paper is focusing on active fault detection (AFD) for parametric faults in closed-loop systems. This auxiliary input applied for the fault detection will also disturb the external output and consequently reduce the performance of the controller. Therefore, only small auxiliary inputs are used...... with the result that the detection and isolation time can be long. In this paper it will be shown, that this problem can be handled by using a modification of the feedback controller. By applying the YJBK-parameterization (after Youla, Jabr, Bongiorno and Kucera) for the controller, it is possible to modify...... the feedback controller with a minor effect on the external output in the fault free case. Further, in the faulty case, the signature of the auxiliary input can be optimized. This is obtained by using a band-pass filter for the YJBK parameter that is only effective in a small frequency range where...

  10. An Overview of Transmission Line Protection by Artificial Neural Network: Fault Detection, Fault Classification, Fault Location, and Fault Direction Discrimination

    Directory of Open Access Journals (Sweden)

    Anamika Yadav

    2014-01-01

    Full Text Available Contemporary power systems are associated with serious issues of faults on high voltage transmission lines. Instant isolation of fault is necessary to maintain the system stability. Protective relay utilizes current and voltage signals to detect, classify, and locate the fault in transmission line. A trip signal will be sent by the relay to a circuit breaker with the purpose of disconnecting the faulted line from the rest of the system in case of a disturbance for maintaining the stability of the remaining healthy system. This paper focuses on the studies of fault detection, fault classification, fault location, fault phase selection, and fault direction discrimination by using artificial neural networks approach. Artificial neural networks are valuable for power system applications as they can be trained with offline data. Efforts have been made in this study to incorporate and review approximately all important techniques and philosophies of transmission line protection reported in the literature till June 2014. This comprehensive and exhaustive survey will reduce the difficulty of new researchers to evaluate different ANN based techniques with a set of references of all concerned contributions.

  11. Fault Detection and Control of Process Systems

    Directory of Open Access Journals (Sweden)

    Vu Trieu Minh

    2007-01-01

    Full Text Available This paper develops a stochastic hybrid model-based control system that can determine online the optimal control actions, detect faults quickly in the control process, and reconfigure the controller accordingly using interacting multiple-model (IMM estimator and generalized predictive control (GPC algorithm. A fault detection and control system consists of two main parts: the first is the fault detector and the second is the controller reconfiguration. This work deals with three main challenging issues: design of fault model set, estimation of stochastic hybrid multiple models, and stochastic model predictive control of hybrid multiple models. For the first issue, we propose a simple scheme for designing faults for discrete and continuous random variables. For the second issue, we consider and select a fast and reliable fault detection system applied to the stochastic hybrid system. Finally, we develop a stochastic GPC algorithm for hybrid multiple-models controller reconfiguration with soft switching signals based on weighted probabilities. Simulations for the proposed system are illustrated and analyzed.

  12. Considerations for fault current testing of optical ground wire

    Energy Technology Data Exchange (ETDEWEB)

    Madge, R.C.; Barrett, J.S.; Maruice, C.G. (Ontario Hydro, Toronto, ON (Canada). Research Div.)

    1992-10-01

    Optical Ground Wires (OPGW) are being used more frequently by utilities. However, fault current testing of OPGW has not been fully examined. In this paper, peak component temperatures are measured for both 10 m and 60 m spans. The cable temperature decay time is measured, and is compared against a numerical model of convection and conduction losses. A numerical model is developed to predict the peak cable tension following a hit. This model can be used to establish appropriate initial cable tensions to simulate full-span faults. The issue of dynamic stresses in the form of cable whipping is reviewed. Lastly, various cable termination procedures are tested.

  13. Mechanisms for Generation of Near-Fault Ground Motion Pulses for Dip-Slip Faulting

    Science.gov (United States)

    Poiata, Natalia; Miyake, Hiroe; Koketsu, Kazuki

    2017-04-01

    We analyzed the seismological aspects of the near-fault ground motion pulses and studied the main characteristics of the rupture configuration that contribute to the pulse generation for dip-slip faulting events by performing forward simulations in broadband and low-frequency ranges for different rupture scenarios of the 2009 L'Aquila, Italy (M w 6.3) earthquake. The rupture scenarios were based on the broadband source model determined by Poiata et al. (Geophys J Int 191:224-242, 2012). Our analyses demonstrated that ground motion pulses affect spectral characteristics of the observed ground motions at longer periods, generating significantly larger seismic demands on the structures than ordinary records. The results of the rupture scenario simulations revealed the rupture directivity effect, the radial rupture propagation toward the site, and the focusing effect as the main mechanisms of the near-fault ground motion pulse generation. The predominance of one of these mechanisms depends on the location of the site relative to the causative fault plane. The analysis also provides the main candidate mechanisms for the worst-case rupture scenarios of pulse generation for the city of L'Aquila and, more generally, the hanging-wall sites located above the area of large slip (strong motion generation area).

  14. Fault Detection and Isolation in Centrifugal Pumps

    DEFF Research Database (Denmark)

    Kallesøe, Carsten

    Centrifugal pumps are used in a variety of different applications, such as water supply, wastewater, and different industrial applications. Some pump installations are crucial for the applications to work. Failures can lead to substantial economic losses and can influence the life of many people...... when they occur. Therefore, detection of faults, if possible in an early stage, and isolation of their causes are of great interest. Especially fault detection, which can be used for predictive maintenance, can decrease working expenses and increase the reliability of the application in which the pump...... is placed. The topic of this work is Fault Detection and Identification in centrifugal pumps. Different approaches are developed with special focus on robustness. Robustness with respect to disturbances, unknown parts of the system, and parameter variations are considered. All developed algorithms...

  15. Fault Detection under Fuzzy Model Uncertainty

    Institute of Scientific and Technical Information of China (English)

    Marek Kowal; Józef Korbicz

    2007-01-01

    The paper tackles the problem of robust fault detection using Takagi-Sugeno fuzzy models. A model-based strategy is employed to generate residuals in order to make a decision about the state of the process. Unfortunately, such a method is corrupted by model uncertainty due to the fact that in real applications there exists a model-reality mismatch. In order to ensure reliable fault detection the adaptive threshold technique is used to deal with the mentioned problem. The paper focuses also on fuzzy model design procedure. The bounded-error approach is applied to generating the rules for the model using available measurements. The proposed approach is applied to fault detection in the DC laboratory engine.

  16. Online Distributed Fault Detection of Sensor Measurements

    Institute of Scientific and Technical Information of China (English)

    GAO Jianliang; XU Yongjun; LI Xiaowei

    2007-01-01

    In wireless sensor networks (WSNs), a faulty sensor may produce incorrect data and transmit them to the other sensors. This would consume the limited energy and bandwidth of WSNs. Furthermore, the base station may make inappropriate decisions when it receives the incorrect data sent by the faulty sensors. To solve these problems, this paper develops an online distributed algorithm to detect such faults by exploring the weighted majority vote scheme. Considering the spatial correlations in WSNs, a faulty sensor can diagnose itself through utilizing the spatial and time information provided by its neighbor sensors. Simulation results show that even when as many as 30% of the sensors are faulty, over 95% of faults can be correctly detected with our algorithm. These results indicate that the proposed algorithm has excellent performance in detecting fault of sensor measurements in WSNs.

  17. Characteristics of near-fault ground motion containing velocity pulses

    Institute of Scientific and Technical Information of China (English)

    WEI Tao; ZHAO Feng-xin; ZHANG Yu-shan

    2006-01-01

    There are many reports about the research on near-fault velocity pulses, which focus on the generation of velocity pulse and simplify the velocity pulse so as to be used in the seismic design of structure. However few researches have put emphasis on the characteristics of near-fault ground motions containing velocity pulses, especially the characteristics relevant with the design response spectrum prescribed by the code. Through collection of a large number of near-fault records containing velocity pulses, the response spectra and the characteristic periods of records containing no pulses are compared with those of records containing pulses. Response spectra of near-fault records are compared with standard spectra given by code; furthermore, the response spectra and the characteristic periods of each earthquake are compared with that given by code. The result shows that at long periods (longer than 1.5 s), the response spectrum of pulse-containing records is bigger than the response spectrum of no-pulse-containing records; when the characteristic period of near-fault records is calculated, the method that does not fix frequency is more reasonable because the T1 and T2 have a lagging tendency; regardless of the site Ⅰ and site Ⅱ, the characteristic period of pulse-containing records is over twice bigger than the characteristic period given by the code.

  18. Nonlinear Model-Based Fault Detection for a Hydraulic Actuator

    NARCIS (Netherlands)

    Van Eykeren, L.; Chu, Q.P.

    2011-01-01

    This paper presents a model-based fault detection algorithm for a specific fault scenario of the ADDSAFE project. The fault considered is the disconnection of a control surface from its hydraulic actuator. Detecting this type of fault as fast as possible helps to operate an aircraft more cost effect

  19. Fault Detection for Shipboard Monitoring and Decision Support Systems

    DEFF Research Database (Denmark)

    Lajic, Zoran; Nielsen, Ulrik Dam

    2009-01-01

    In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection will be p...

  20. High Frequency Ground Motion from Finite Fault Rupture Simulations

    Science.gov (United States)

    Crempien, Jorge G. F.

    There are many tectonically active regions on earth with little or no recorded ground motions. The Eastern United States is a typical example of regions with active faults, but with low to medium seismicity that has prevented sufficient ground motion recordings. Because of this, it is necessary to use synthetic ground motion methods in order to estimate the earthquake hazard a region might have. Ground motion prediction equations for spectral acceleration typically have geometric attenuation proportional to the inverse of distance away from the fault. Earthquakes simulated with one-dimensional layered earth models have larger geometric attenuation than the observed ground motion recordings. We show that as incident angles of rays increase at welded boundaries between homogeneous flat layers, the transmitted rays decrease in amplitude dramatically. As the receiver distance increases away from the source, the angle of incidence of up-going rays increases, producing negligible transmitted ray amplitude, thus increasing the geometrical attenuation. To work around this problem we propose a model in which we separate wave propagation for low and high frequencies at a crossover frequency, typically 1Hz. The high-frequency portion of strong ground motion is computed with a homogeneous half-space and amplified with the available and more complex one- or three-dimensional crustal models using the quarter wavelength method. We also make use of seismic coda energy density observations as scattering impulse response functions. We incorporate scattering impulse response functions into our Green's functions by convolving the high-frequency homogeneous half-space Green's functions with normalized synthetic scatterograms to reproduce scattering physical effects in recorded seismograms. This method was validated against ground motion for earthquakes recorded in California and Japan, yielding results that capture the duration and spectral response of strong ground motion.

  1. All row, planar fault detection system

    Science.gov (United States)

    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.

  2. Fundamental problems in fault detection and identification

    DEFF Research Database (Denmark)

    Saberi, Ali; Stoorvogel, Anton A.; Sannuti, Peddapullaiah;

    1999-01-01

    For certain fundamental problems in fault detection and identification, the necessary and sufficient conditions for their solvability are derived. These conditions are weaker than the ones found in the literature, since we do not assume any particular structure for the residual generator...

  3. Analysis on effect of surface fault to site ground motion using finite element method

    Institute of Scientific and Technical Information of China (English)

    曹炳政; 罗奇峰

    2003-01-01

    Dynamic contact theory is applied to simulate the sliding of surface fault. Finite element method is used to analyze the effect of surface fault to site ground motions. Calculated results indicate that amplification effect is obvious in the area near surface fault, especially on the site that is in the downside fault. The results show that the effect of surface fault should be considered when important structure is constructed in the site with surface fault.

  4. Field Guide for Testing Existing Photovoltaic Systems for Ground Faults and Installing Equipment to Mitigate Fire Hazards

    Energy Technology Data Exchange (ETDEWEB)

    Brooks, William [Brooks Engineering, Vacaville, CA (United States); Basso, Thomas [National Renewable Energy Lab. (NREL), Golden, CO (United States); Coddington, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2015-10-01

    Ground faults and arc faults are the two most common reasons for fires in photovoltaic (PV) arrays and methods exist that can mitigate the hazards. This report provides field procedures for testing PV arrays for ground faults, and for implementing high resolution ground fault and arc fault detectors in existing and new PV system designs.

  5. Robust Fault Detection and Isolation for Stochastic Systems

    Science.gov (United States)

    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.

  6. Frequency Based Fault Detection in Wind Turbines

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2014-01-01

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

  7. Model Based Fault Detection in a Centrifugal Pump Application

    DEFF Research Database (Denmark)

    Kallesøe, Carsten; Cocquempot, Vincent; Izadi-Zamanabadi, Roozbeh

    2006-01-01

    A model based approach for fault detection in a centrifugal pump, driven by an induction motor, is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, observer design and Analytical Redundancy Relation (ARR) design. Structural consideration...... is capable of detecting four different faults in the mechanical and hydraulic parts of the pump.......A model based approach for fault detection in a centrifugal pump, driven by an induction motor, is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, observer design and Analytical Redundancy Relation (ARR) design. Structural considerations...

  8. A Digital Ground Distance Relaying Algorithm to Reduce the Effect of Fault Resistance during Single Phase to Ground and Simultaneous Faults

    Directory of Open Access Journals (Sweden)

    Mohammad Razaz

    2015-03-01

    Full Text Available This paper provides an algorithm of fault resistance compensation for digital ground distance relay considering the voltage and current transformer effects. Performance of the conventional ground distance relaying manner is adversely affected by different ground faults and also typical type, called a simultaneous open conductor and ground fault. The proposed scheme by using local-end data only, has shown satisfactory performances under wide variations in fault location, with different values of fault resistance and having positive and negative of power transfer angle. The presented method which has been carried out on the IEEE 14 bus benchmark is executed in PSCAD/EMTDC and MATLAB software, and the results show the accurate performance of mentioned configuration.

  9. An Immunology-inspired Fault Detection and Identification System

    Directory of Open Access Journals (Sweden)

    Liguo Weng

    2012-09-01

    Full Text Available This paper presents a fault detection and identification (FDI approach inspired by the immune system. The salient features of the immune system, such as adaptability, robustness, flexibility, archival memory and distributed cognition abilities, have been the valuable source of inspiration for fundamentally new methods for fault detection and identification. This research makes use of immunological concepts to develop a robust fault detection and identification mechanism, capable of detecting and classifying diverse system faults dynamically. Such an FDI mechanism also has the ability to learn and classify overlapping faults using distributed sensing. Moreover, its detection accuracy can be continuously improved during system operation. As tested by numerical simulations in which faults are represented by overlapping banana functions, the proposed algorithms are adaptive to new types of faults and overlapping faults.

  10. An effort allocation model considering different budgetary constraint on fault detection process and fault correction process

    Directory of Open Access Journals (Sweden)

    Vijay Kumar

    2016-01-01

    Full Text Available Fault detection process (FDP and Fault correction process (FCP are important phases of software development life cycle (SDLC. It is essential for software to undergo a testing phase, during which faults are detected and corrected. The main goal of this article is to allocate the testing resources in an optimal manner to minimize the cost during testing phase using FDP and FCP under dynamic environment. In this paper, we first assume there is a time lag between fault detection and fault correction. Thus, removal of a fault is performed after a fault is detected. In addition, detection process and correction process are taken to be independent simultaneous activities with different budgetary constraints. A structured optimal policy based on optimal control theory is proposed for software managers to optimize the allocation of the limited resources with the reliability criteria. Furthermore, release policy for the proposed model is also discussed. Numerical example is given in support of the theoretical results.

  11. Representation of near-fault pulse-type ground motions

    Institute of Scientific and Technical Information of China (English)

    Xie Lili; Xu Longjun; Adrian Rodriguez-Marek

    2005-01-01

    Near-fault ground motions with long-period pulses have been identified as critical in the design of structures.To aid in the representation of this special type of motion, eight simple pulses that characterize the effects of either the flingstep or forward-directivity are considered. Relationships between pulse amplitudes and velocity pulse period for different pulses are discussed. Representative ratios and peak acceleration amplification can exhibit distinctive features depending on variations in pulse duration, amplitude and the selected acceleration pulse shape. Additionally, response spectral characteristics for the equivalent pulses are identified and compared in terms of fixed PGA and PGV, respectively. Response spectra are strongly affected by the duration of pulses and the shape of the basic pulses. Finally, dynamic time history response features of a damped SDOF system subjected to pulse excitations are examined. These special aspects of pulse waveforms and their response spectra should be taken into account in the estimation of ground motions for a project site close to a fault.

  12. Broadband Ground Motion Simulations for the Puente Hills Fault System

    Science.gov (United States)

    Graves, R. W.

    2005-12-01

    Recent geologic studies have identified the seismic potential of the Puente Hills fault system. This system is comprised of multiple blind thrust segments, a portion of which ruptured in the Mw 5.9 Whittier-Narrows earthquake. Rupture of the entire system could generate a Mw 7.2 (or larger) earthquake. To assess the potential hazard posed by the fault system, we have simulated the response for several earthquake scenarios. These simulations are unprecedented in scope and scale. Broadband (0-10 Hz) ground motions are computed at 66,000 sites, covering most of the LA metropolitan region. Low frequency (f 1 Hz) motions are calculated using a stochastic approach. We consider scenarios ranging from Mw 6.7 to Mw 7.2, including both high and low stress drop events. Finite-fault rupture models for these scenarios are generated following a wavenumber filtering technique (K-2 model) that has been calibrated against recent earthquakes. In all scenarios, strong rupture directivity channels large amplitude pulses of motion directly into the Los Angeles basin, which then propagate southward as basin surface waves. Typically, the waveforms near downtown Los Angeles are dominated by a strong, concentrated pulse of motion. At Long Beach (across the LA basin from the rupture) the waveforms are dominated by late arriving longer period surface waves. The great density of sites used in the calculation allows the construction of detailed maps of various ground motion parameters (PGA, PGV, SA), as well as full animations of the propagating broadband wave field. Additionally, the broadband time histories are available for use in non-linear response analyses of built structures.

  13. A Comparative Parametric Analysis of the Ground Fault Current Distribution on Overhead Transmission Lines

    OpenAIRE

    VINTAN, M.

    2016-01-01

    The ground fault current distribution in an effectively grounded power network is affected by various factors, such as: tower footing impedances, spans lengths, configuration and parameters of overhead ground wires and power conductors, soil resistivity etc. In this paper, we comparatively analyze, using different models, the ground fault current distribution in a single circuit transmission line with one ground wire. A parametric comparative analysis was done in order to stud...

  14. Fault geometry, rupture dynamics and ground motion from potential earthquakes on the North Anatolian Fault under the Sea of Marmara

    KAUST Repository

    Oglesby, David D.

    2012-03-01

    Using the 3-D finite-element method, we develop dynamic spontaneous rupture models of earthquakes on the North Anatolian Fault system in the Sea of Marmara, Turkey, considering the geometrical complexity of the fault system in this region. We find that the earthquake size, rupture propagation pattern and ground motion all strongly depend on the interplay between the initial (static) regional pre-stress field and the dynamic stress field radiated by the propagating rupture. By testing several nucleation locations, we observe that those far from an oblique normal fault stepover segment (near Istanbul) lead to large through-going rupture on the entire fault system, whereas nucleation locations closer to the stepover segment tend to produce ruptures that die out in the stepover. However, this pattern can change drastically with only a 10° rotation of the regional stress field. Our simulations also reveal that while dynamic unclamping near fault bends can produce a new mode of supershear rupture propagation, this unclamping has a much smaller effect on the speed of the peak in slip velocity along the fault. Finally, we find that the complex fault geometry leads to a very complex and asymmetric pattern of near-fault ground motion, including greatly amplified ground motion on the insides of fault bends. The ground-motion pattern can change significantly with different hypocentres, even beyond the typical effects of directivity. The results of this study may have implications for seismic hazard in this region, for the dynamics and ground motion of geometrically complex faults, and for the interpretation of kinematic inverse rupture models.

  15. FUZZY FAULT DETECTION FOR PERMANENT MAGNET SYNCHRONOUS GENERATOR

    Directory of Open Access Journals (Sweden)

    N. Selvaganesan

    2011-07-01

    Full Text Available Faults in engineering systems are difficult to avoid and may result in serious consequences. Effective fault detection and diagnosis can improve system reliability and avoid expensive maintenance. In this paper fuzzy system based fault detection scheme for permanent magnet synchronous generator is proposed. The sequence current components like positive and negative sequence currents are used as fault indicators and given as inputs to fuzzy fault detector. Also, the fuzzy inference system is created and rule base is evaluated, relating the sequence current component to the type of faults. These rules are fired for specific changes in sequence current component and the faults are detected. The feasibility of the proposed scheme for permanent magnet synchronous generator is demonstrated for different types of fault under various operating conditions using MATLAB/Simulink.

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

    DEFF Research Database (Denmark)

    Borchersen, Anders Bech; Larsen, Jesper Abildgaard; Stoustrup, Jakob

    2014-01-01

    is to detect and handle different faults occurring in the individual turbines on farm level. The fault detection system is designed such that it takes advantage of the fact that within a wind farm several of the turbines will be operating under similar conditions. To enable this the turbines are grouped......In this paper a fault detection system and a fault tolerant controller for a wind farm model is designed and tested. The wind farm model is taken from the wind farm challenge which is a public available challenge where a wind farm consisting of nine turbines is proposed. The goal of the challenge...... in the model. All the detections are not within the requirement of the challenge thus room for improvement. To take advantage of the fault detection system a fault tolerant controller for the wind farm has been designed. The fault tolerant controller is a dispatch controller which is estimating the possible...

  17. Fault Analysis and Detection in Microgrids with High PV Penetration

    Energy Technology Data Exchange (ETDEWEB)

    El Khatib, Mohamed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hernandez Alvidrez, Javier [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ellis, Abraham [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-05-01

    In this report we focus on analyzing current-controlled PV inverters behaviour under faults in order to develop fault detection schemes for microgrids with high PV penetration. Inverter model suitable for steady state fault studies is presented and the impact of PV inverters on two protection elements is analyzed. The studied protection elements are superimposed quantities based directional element and negative sequence directional element. Additionally, several non-overcurrent fault detection schemes are discussed in this report for microgrids with high PV penetration. A detailed time-domain simulation study is presented to assess the performance of the presented fault detection schemes under different microgrid modes of operation.

  18. IMU Fault Detection Based on 2-CUSUM

    Directory of Open Access Journals (Sweden)

    Élcio Jeronimo de Oliveira

    2012-01-01

    IMU strapdown platforms using fiber optic gyros (FOG or micro electro mechanical systems (MEMSs. A way to solve this problem makes use of sensor redundancy and parity vector (PV analysis. However, the actual sensor outputs can include some anomalies, as impulsive noise which can be associated with the sensors itself or data acquisition process, committing the elementary threshold criteria as commonly used. Therefore, to overcome this problem, in this work, it is proposed an algorithm based on median filter (MF for prefiltering and chi-square cumulative sum (2-CUSUM only for fault detection (FD applied to an IMU composed by four FOGs.

  19. Fault Detection for Diesel Engine Actuator

    DEFF Research Database (Denmark)

    Blanke, M.; Bøgh, S.A.; Jørgensen, R.B.

    1994-01-01

    Feedback control systems are vulnerable to faults in control loop sensors and actuators, because feedback actions may cause abrupt responses and process damage when faults occur.......Feedback control systems are vulnerable to faults in control loop sensors and actuators, because feedback actions may cause abrupt responses and process damage when faults occur....

  20. Grounding and fault protection of the SMUD PVI array

    Science.gov (United States)

    Rosen, D.

    1983-01-01

    If large terrestrial photovoltaic (PV) power plants are to provide an economic source of generation, low-cost, reliable and easily maintainable systems must be developed. In addition, if the system is to be a central station powerplant owned and operated by an electric utility, the design must also be consistent with utility specifications and design standards. The particular solutions developed to address these issues, with regard to grounding and fault protection, for the first phase of the Sacramento Municipal Utility District's (SMUD) 100 mw(ac) PV powerplant are presented. This plant, known as PV1, is nominally rated at 1 mw(ac) and is scheduled to be in operation by the spring of 1984.

  1. Optimal Robust Fault Detection for Linear Discrete Time Systems

    Directory of Open Access Journals (Sweden)

    Nike Liu

    2008-01-01

    Full Text Available This paper considers robust fault-detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault-detection problems, such as ℋ−/ℋ∞, ℋ2/ℋ∞, and ℋ∞/ℋ∞ problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Optimal filters are also derived for many other optimization criteria and it is shown that some well-studied and seeming-sensible optimization criteria for fault-detection filter design could lead to (optimal but useless fault-detection filters.

  2. Experimental Fault Detection and Accomodation for an Agricultural Mobile Robot

    DEFF Research Database (Denmark)

    Østergaard, Kasper Zinck; Vinther, D.; Bisgaard, Morten;

    2005-01-01

    This paper presents a systematic procedure to achieve fault tolerant capability for a four-wheel driven, four-wheel steered mobile robot moving in outdoor terrain. The procedure is exemplified through the paper by applying on a compass module. Detailed methods for fault detection and fault...

  3. Fault Detection of Wind Turbines with Uncertain Parameters

    DEFF Research Database (Denmark)

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

    2012-01-01

    In this paper a set-membership approach for fault detection of a benchmark wind turbine is proposed. The benchmark represents relevant fault scenarios in the control system, including sensor, actuator and system faults. In addition we also consider parameter uncertainties and uncertainties on the...

  4. Detection of ground ice using ground penetrating radar method

    Institute of Scientific and Technical Information of China (English)

    Gennady M. Stoyanovich; Viktor V. Pupatenko; Yury A. Sukhobok

    2015-01-01

    The paper presents the results of a ground penetrating radar (GPR) application for the detection of ground ice. We com-bined a reflection traveltime curves analysis with a frequency spectrogram analysis. We found special anomalies at specific traces in the traveltime curves and ground boundaries analysis, and obtained a ground model for subsurface structure which allows the ground ice layer to be identified and delineated.

  5. Seismic Responses of Asymmetric Base-Isolated Structures under Near-Fault Ground Motion

    Institute of Scientific and Technical Information of China (English)

    YE Kun; LI Li; FANG Qin-han

    2008-01-01

    An inter-story shear model of asymmetric base-isolated structures incorporating deformation of each isolation bearing was built, and a method to simultaneously simulate bi-directional near-fault and far-field ground motions was proposed. A comparative study on the dynamic responses of asymmetric base-isolated structures under near-fault and far-field ground motions were conducted to investigate the effects of eccentricity in the isolation system and in the superstructures, the ratio of the uncoupled torsional to lateral frequency of the superstructure and the pulse period of near-fault ground motions on the nonlinear seismic response of asymmetric base-isolated structures. Numerical results show that eccentricity in the isolation system makes asymmetric base-isolated structure more sensitive to near-fault ground motions, and the pulse period of near-fault ground motions plays an import role in governing the seismic responses of asymmetric base-isolated structures.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  9. Identification of acceleration pulses in near-fault ground motion using the EMD method

    Institute of Scientific and Technical Information of China (English)

    Zhang Yushan; Hu Yuxian; Zhao Fengxin; Liang Jianwen; Yang Caihong

    2005-01-01

    In this paper, response spectral characteristics of one-, two-, and three-lobe sinusoidal acceleration pulses are investigated, and some of their basic properties are derived. Furthermore, the empirical mode decomposition (EMD) method is utilized as an adaptive filter to decompose the near-fault pulse-like ground motions, which were recorded during the September 20, 1999, Chi-Chi earthquake. These ground motions contain distinct velocity pulses, and were decomposed into high-frequency (HF) and low-frequency (LF) components, from which the corresponding HF acceleration pulse (if existing)and LF acceleration pulse could be easily identified and detected. Finally, the identified acceleration pulses are modeled by simplified sinusoidal approximations, whose dynamic behaviors are compared to those of the original acceleration pulses as well as to those of the original HF and LF acceleration components in the context of elastic response spectra. It was demonstrated that it is just the acceleration pulses contained in the near-fault pulse-like ground motion that fundamentally dominate the special impulsive dynamic behaviors of such motion in an engineering sense. The motion thus has a greater potential to cause severe damage than the far-field ground motions, i.e. they impose high base shear demands on engineering structures as well as placing very high deformation demands on long-period structures.

  10. Planetary Gearbox Fault Detection Using Vibration Separation Techniques

    Science.gov (United States)

    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.

  11. Fault detection for discrete-time switched systems with sensor stuck faults and servo inputs.

    Science.gov (United States)

    Zhong, Guang-Xin; Yang, Guang-Hong

    2015-09-01

    This paper addresses the fault detection problem of switched systems with servo inputs and sensor stuck faults. The attention is focused on designing a switching law and its associated fault detection filters (FDFs). The proposed switching law uses only the current states of FDFs, which guarantees the residuals are sensitive to the servo inputs with known frequency ranges in faulty cases and robust against them in fault-free case. Thus, the arbitrarily small sensor stuck faults, including outage faults can be detected in finite-frequency domain. The levels of sensitivity and robustness are measured in terms of the finite-frequency H- index and l2-gain. Finally, the switching law and FDFs are obtained by the solution of a convex optimization problem.

  12. Fuzzy associative memories for instrument fault detection

    Energy Technology Data Exchange (ETDEWEB)

    Heger, A.S. [New Mexico Univ., Albuquerque, NM (United States). Dept. of Chemical and Nuclear Engineering; Holbert, K.E.; Ishaque, A.M. [Arizona State Univ., Tempe, AZ (United States)

    1996-06-01

    A fuzzy logic instrument fault detection scheme is developed for systems having two or three redundant sensors. In the fuzzy logic approach the deviation between each signal pairing is computed and classified into three fuzzy sets. A rule base is created allowing the human perception of the situation to be represented mathematically. Fuzzy associative memories are then applied. Finally, a defuzzification scheme is used to find the centroid location, and hence the signal status. Real-time analyses are carried out to evaluate the instantaneous signal status as well as the long-term results for the sensor set. Instantaneous signal validation results are used to compute a best estimate for the measured state variable. The long-term sensor validation method uses a frequency fuzzy variable to determine the signal condition over a specific period. To corroborate the methodology synthetic data representing various anomalies are analyzed with both the fuzzy logic technique and the parity space approach. (Author).

  13. Fault Detection Observer Design for LSFDJ: A Factorization Approach

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-jun; WENG Zheng-xin; TIAN Zuo-hua

    2005-01-01

    Based on a new special co-inner-outer factorization, a factorization approach for design fault detection observer for LSFDJ was proposed. It is a simple state-space method and can deal with time-varying LSFDJ with sensor noise and sensor faults. The performance of the fault detection observer is optimized in an H∞ setting,where the ratio between the gains from disturbance and fault to residual respectively is minimized. The design parameters of the detection observer were given in terms of the solution to the Riccati differential equation with jumps.

  14. Model Based Incipient Fault Detection for Gear Drives

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents the method of model based incipient fault detection for gear drives,this method is based on parity space method. It can generate the robust residual that is maximally sensitive to the fault caused by the change of the parameters. The example of simulation shows the application of the method, and the residual waves have different characteristics due to different parameter changes; one can detect and isolate the fault based on the different characteristics.

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

    Science.gov (United States)

    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.

  16. Active Fault Detection Based on a Statistical Test

    DEFF Research Database (Denmark)

    Sekunda, André Krabdrup; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2016-01-01

    In this paper active fault detection of closed loop systems using dual Youla-Jabr-Bongiorno-Kucera(YJBK) parameters is presented. Until now all detector design for active fault detection using the dual YJBK parameters has been based on CUSUM detectors. Here a method for design of a matched filter...

  17. An Improved Wavelet‐Based Multivariable Fault Detection Scheme

    KAUST Repository

    Harrou, Fouzi

    2017-07-06

    Data observed from environmental and engineering processes are usually noisy and correlated in time, which makes the fault detection more difficult as the presence of noise degrades fault detection quality. Multiscale representation of data using wavelets is a powerful feature extraction tool that is well suited to denoising and decorrelating time series data. In this chapter, we combine the advantages of multiscale partial least squares (MSPLSs) modeling with those of the univariate EWMA (exponentially weighted moving average) monitoring chart, which results in an improved fault detection system, especially for detecting small faults in highly correlated, multivariate data. Toward this end, we applied EWMA chart to the output residuals obtained from MSPLS model. It is shown through simulated distillation column data the significant improvement in fault detection can be obtained by using the proposed methods as compared to the use of the conventional partial least square (PLS)‐based Q and EWMA methods and MSPLS‐based Q method.

  18. Modeling of Morelia Fault Earthquake (Mw=5.4) source fault parameters using the coseismic ground deformation and groundwater level changes data

    Science.gov (United States)

    Sarychikhina, O.; Glowacka, E.; Mellors, R. J.; Vázquez, R.

    2009-12-01

    On 24 May 2006 at 04:20 (UTC) a moderate-size (Mw=5.4) earthquake struck the Mexicali Valley, Baja California, México, roughly 30 km to the southeast of the city of Mexicali, in the vicinity of the Cerro Prieto Geothermal Field (CPGF). The earthquake occurred on the Morelia fault, one of the east-dipping normal faults in the Mexicali Valley. Locally, this earthquake was strongly felt and caused minor damage. The event created 5 km of surface rupture and down-dip displacements of up to 25-30 cm were measured at some places along this surface rupture. Associated deformation was measured by vertical crackmeter, leveling profile, and Differential Synthetic Aperture Radar Interferometry (D-InSAR). A coseismic step-like groundwater level change was detected at 7 wells. The Mw=5.4 Morelia Fault earthquake had significant scientific interest, first, because of surprisingly strong effects for an earthquake of such size; second, the variability of coseismic effects data from different ground-based and space-based techniques which allows to the better constrain of the source fault parameters. Source parameters for the earthquake were estimated using forward modeling of both surface deformation data and static volume strain change (inferred from coseismic changes in groundwater level). All ground deformation data was corrected by anthropogenic component caused by the geothermal fluid exploitation in the CPGF. Modeling was based on finite rectangular fault embedded in an elastic media. The preferred fault model has a strike, rake, and dip of (48°, -89°, 45°) and has a length of 5.2 km, width of 6.7 km, and 34 cm of uniform slip. The geodetic moment, based on the modeled fault parameters, is 1.18E+17 Nm. The model matches the observed surface deformation, expected groundwater level changes, and teleseismic moment reasonably well and explains in part why the earthquake was so strongly felt in the area.

  19. Fault detection filter design for stochastic time-delay systems with sensor faults

    Science.gov (United States)

    Li, Xiao-Jian; Yang, Guang-Hong

    2012-08-01

    This article considers the fault detection (FD) problem for a class of Itô-type stochastic time-delay systems subject to external disturbances and sensor faults. The main objective is to design a fault detection filter (FDF) such that it has prescribed levels of disturbance attenuation and fault sensitivity. Sufficient conditions for guaranteeing these levels are formulated in terms of linear matrix inequalities (LMIs), and the corresponding fault detection filter design is cast into a convex optimisation problem which can be efficiently handled by using standard numerical algorithms. In order to reduce the conservatism of filter design with mixed objectives, multi-Lyapunov functions approach is used via Projection Lemma. In addition, it is shown that our results not only include some previous conditions characterising H ∞ performance and H - performance defined for linear time-invariant (LTI) systems as special cases but also improve these conditions. Finally, two examples are employed to illustrate the effectiveness of the proposed design scheme.

  20. Fault detection and fault-tolerant control for nonlinear systems

    CERN Document Server

    Li, Linlin

    2016-01-01

    Linlin Li addresses the analysis and design issues of observer-based FD and FTC for nonlinear systems. The author analyses the existence conditions for the nonlinear observer-based FD systems to gain a deeper insight into the construction of FD systems. Aided by the T-S fuzzy technique, she recommends different design schemes, among them the L_inf/L_2 type of FD systems. The derived FD and FTC approaches are verified by two benchmark processes. Contents Overview of FD and FTC Technology Configuration of Nonlinear Observer-Based FD Systems Design of L2 nonlinear Observer-Based FD Systems Design of Weighted Fuzzy Observer-Based FD Systems FTC Configurations for Nonlinear Systems< Application to Benchmark Processes Target Groups Researchers and students in the field of engineering with a focus on fault diagnosis and fault-tolerant control fields The Author Dr. Linlin Li completed her dissertation under the supervision of Prof. Steven X. Ding at the Faculty of Engineering, University of Duisburg-Essen, Germany...

  1. A Comparative Parametric Analysis of the Ground Fault Current Distribution on Overhead Transmission Lines

    Directory of Open Access Journals (Sweden)

    VINTAN, M.

    2016-02-01

    Full Text Available The ground fault current distribution in an effectively grounded power network is affected by various factors, such as: tower footing impedances, spans lengths, configuration and parameters of overhead ground wires and power conductors, soil resistivity etc. In this paper, we comparatively analyze, using different models, the ground fault current distribution in a single circuit transmission line with one ground wire. A parametric comparative analysis was done in order to study the effects of the non-uniformity of the towers footing impedances, number of power lines spans, soil resistivity, grounding systems resistances of the terminal substations etc., on the ground fault current distribution. There are presented some useful qualitative and quantitative results obtained through a complex dedicated developed MATLAB 7.0 program.

  2. Prediction of near-field strong ground motions for scenario earthquakes on active fault

    Institute of Scientific and Technical Information of China (English)

    Wang Haiyun; Xie Lili; Tao Xiaxin; Li Jie

    2006-01-01

    A method to predict near-field strong ground motions for scenario earthquakes on active faults is proposed. First,macro-source parameters characterizing the entire source area, i.e., global source parameters, including fault length, fault width,rupture area, average slip on the fault plane, etc., are estimated by seismogeology survey, seismicity and seismic scaling laws.Second, slip distributions characterizing heterogeneity or roughness on the fault plane, i.e., local source parameters, are reproduced/evaluated by the hybrid slip model. Finally, the finite fault source model, developed from both the global and local source parameters, is combined with the stochastically synthetic technique of ground motion using the dynamic corner frequency based on seismology. The proposed method is applied to simulate the acceleration time histories on three base-rock stations during the 1994 Northridge earthquake. Comparisons between the predicted and recorded acceleration time histories show that the method is feasible and practicable.

  3. Fault detection and diagnosis of diesel engine valve trains

    Science.gov (United States)

    Flett, Justin; Bone, Gary M.

    2016-05-01

    This paper presents the development of a fault detection and diagnosis (FDD) system for use with a diesel internal combustion engine (ICE) valve train. A novel feature is generated for each of the valve closing and combustion impacts. Deformed valve spring faults and abnormal valve clearance faults were seeded on a diesel engine instrumented with one accelerometer. Five classification methods were implemented experimentally and compared. The FDD system using the Naïve-Bayes classification method produced the best overall performance, with a lowest detection accuracy (DA) of 99.95% and a lowest classification accuracy (CA) of 99.95% for the spring faults occurring on individual valves. The lowest DA and CA values for multiple faults occurring simultaneously were 99.95% and 92.45%, respectively. The DA and CA results demonstrate the accuracy of our FDD system for diesel ICE valve train fault scenarios not previously addressed in the literature.

  4. Export Methods in Fault Detection and Localization Mechanisms

    Directory of Open Access Journals (Sweden)

    Aymen Belghith

    2012-07-01

    Full Text Available Monitoring the quality of service in a multi-domain network allows providers to ensure the control of multi-domain service performance. A multi-domain service is a service that crosses multiple domains. In this paper, we propose several mechanisms for fault detection and fault localization. A fault is detected when an end-to-end contract is not respected. Faulty domains are domains that do not fulfill their Quality of Service (QoS requirements. Our three proposed fault detection and localization mechanisms (FDLM depend on the export method used. These export methods define how the measurement results are exported for analysis. We consider the periodic export, the triggered export, and a combined method. For each FDLM, we propose two sub-schemes that use different fault detection strategies. In this paper, we describe these mechanisms and evaluate their performance using Network Simulator (NS-2.

  5. Robust fault detection for switched linear systems with state delays.

    Science.gov (United States)

    Wang, Dong; Wang, Wei; Shi, Peng

    2009-06-01

    This correspondence deals with the problem of robust fault detection for discrete-time switched systems with state delays under an arbitrary switching signal. The fault detection filter is used as the residual generator, in which the filter parameters are dependent on the system mode. Attention is focused on designing the robust fault detection filter such that, for unknown inputs, control inputs, and model uncertainties, the estimation error between the residuals and faults is minimized. The problem of robust fault detection is converted into an H(infinity)-filtering problem. By a switched Lyapunov functional approach, a sufficient condition for the solvability of this problem is established in terms of linear matrix inequalities. A numerical example is provided to demonstrate the effectiveness of the proposed method.

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

    DEFF Research Database (Denmark)

    Li, Pengfei; Hu, Weihao; Liu, Juncheng;

    2016-01-01

    The angle faults of blades on wind turbines are usually included in the set angle fault and the pitch angle fault. They are occupied with a high proportion in all wind turbine faults. Compare with the traditional fault detection methods, using order tracking analysis method to detect angle faults...

  7. Bearing Fault Detection in Induction Motor-Gearbox Drivetrain

    Science.gov (United States)

    Cibulka, Jaroslav; Ebbesen, Morten K.; Robbersmyr, Kjell G.

    2012-05-01

    The main contribution in the hereby presented paper is to investigate the fault detection capability of a motor current signature analysis by expanding its scope to include the gearbox, and not only the induction motor. Detecting bearing faults outside the induction motor through the stator current analysis represents an interesting alternative to traditional vibration analysis. Bearing faults cause changes in the stator current spectrum that can be used for fault diagnosis purposes. A time-domain simulation of the drivetrain model is developed. The drivetrain system consists of a loaded single stage gearbox driven by a line-fed induction motor. Three typical bearing faults in the gearbox are addressed, i.e. defects in the outer raceway, the inner raceway, and the rolling element. The interaction with the fault is modelled by means of kinematical and mechanical relations. The fault region is modelled in order to achieve gradual loss and gain of contact. A bearing fault generates an additional torque component that varies at the specific bearing defect frequency. The presented dynamic electromagnetic dq-model of an induction motor is adjusted for diagnostic purpose and considers such torque variations. The bearing fault is detected as a phase modulation of the stator current sine wave at the expected bearing defect frequency.

  8. Seismic fragility analysis of a CANDU containment structure for near-fault ground motions

    Energy Technology Data Exchange (ETDEWEB)

    Choi, In Kil; Choun, Young Sun; Seo, Jeong Moon; Ahn, Seong Moon [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    2005-07-01

    The R. G. 1.60 spectrum used for the seismic design of Korean nuclear power plants provides a generally conservative design basis due to its broadband nature. A survey on some of the Quaternary fault segments near Korean nuclear power plants is ongoing. It is likely that these faults will be identified as active ones. If the faults are confirmed as active ones, it will be necessary to reevaluate the seismic safety of the nuclear power plants located near these faults. The probability based scenario earthquakes were identified as near-field earthquakes. In general, the near-fault ground motion records exhibit a distinctive long period pulse like time history with very high peak velocities. These features are induced by the slip of the earthquake fault. Near-fault ground motions, which have caused much of the damage in recent major earthquakes, can be characterized by a pulse-like motion that exposes the structure to a high input energy at the beginning of the motion. It is necessary to estimate the near-fault ground motion effects on the nuclear power plant structures and components located near the faults. In this study, the seismic fragility analysis of a CANDU containment structure was performed based on the results of nonlinear dynamic time-history analyses.

  9. All-to-all sequenced fault detection system

    Science.gov (United States)

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

    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.

  10. A coherency function model of ground motion at base rock corresponding to strike-slip fault

    Institute of Scientific and Technical Information of China (English)

    丁海平; 刘启方; 金星; 袁一凡

    2004-01-01

    At present, the method to study spatial variation of ground motions is statistic analysis based on dense array records such as SMART-1 array, etc. For lacking of information of ground motions, there is no coherency function model of base rock and different style site. Spatial variation of ground motions in elastic media is analyzed by deterministic method in this paper. Taking elastic half-space model with dislocation source of fault, near-field ground motions are simulated. This model takes strike-slip fault and earth media into account. A coherency function is proposed for base rock site.

  11. A Robust Fault Detection Approach for Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    Min-Ze Chen; Qi Zhao; Dong-Hua Zhou

    2006-01-01

    In this paper, we study the robust fault detection problem of nonlinear systems. Based on the Lyapunov method,a robust fault detection approach for a general class of nonlinear systems is proposed. A nonlinear observer is first provided,and a sufficient condition is given to make the observer locally stable. Then, a practical algorithm is presented to facilitate the realization of the proposed observer for robust fault detection. Finally, a numerical example is provided to show the effectiveness of the proposed approach.

  12. Distance Based Fault detection in wireless sensor network

    Directory of Open Access Journals (Sweden)

    Ayasha Siddiqua

    2013-05-01

    Full Text Available Wireless Sensor Network (WSNs have become a new information collection and monitoring solution for a variety of application. In WSN, sensor nodes have strong hardware and software restrictionin terms of processing power, memory capability, power supply and communication throughput. Due to these restrictions, fault may occur in sensor. This paper presents a distance based fault detection (DBFDmethod for wireless sensor network using the average of confidence level and sensed data of sensor node. Simulation results show that sensor nodes with permanent faults and without fault which was judged as faulty are identified with high accuracy for a wide range of fault rate, and keep false alarm rate for different levels of sensor fault model and also correct nodes are identified by accuracy.

  13. Field Guide for Testing Existing Photovoltaic Systems for Ground Faults and Installing Equipment to Mitigate Fire Hazards: November 2012 - October 2013

    Energy Technology Data Exchange (ETDEWEB)

    Brooks, W.

    2015-02-01

    Ground faults and arc faults are the two most common reasons for fires in photovoltaic (PV) arrays and methods exist that can mitigate the hazards. This report provides field procedures for testing PV arrays for ground faults, and for implementing high resolution ground fault and arc fault detectors in existing and new PV system designs.

  14. Development of attenuation relation for the near fault ground motion from the characteristic earthquake

    Institute of Scientific and Technical Information of China (English)

    SHI Bao-ping; LIU Bo-yan; ZHANG Jian

    2007-01-01

    A composite source model has been used to simulate a broadband strong ground motion with an associated fault rupture process. A scenario earthquake fault model has been used to generate 1 000 earthquake events with a magnitude of Mw8.0. The simulated results show that, for the characteristic event with a strike-slip faulting, the characteristics of near fault ground motion is strongly dependent on the rupture directivity. If the distance between the sites and fault was given, the ground motion in the forward direction (Site A) is much larger than that in the backward direction (Site C) and that close to the fault (Site B). The SH waves radiated from the fault, which corresponds to the fault-normal component plays a key role in the ground motion amplification. Corresponding to the sites A, B, and C, the statistical analysis shows that the ratio of their aPG is 2.15:1.5:1 and their standard deviations are about 0.12, 0.11, and 0.13, respectively. If these results are applied in the current probabilistic seismic hazard analysis (PSHA), then, for the lower annual frequency of exceedance of peak ground acceleration, the predicted aPG from the hazard curve could reduce by 30% or more compared with the current PSHA model used in the developing of seismic hazard map in the USA. Therefore, with a consideration of near fault ground motion caused by the rupture directivity, the regression model used in the development of the regional attenuation relation should be modified accordingly.

  15. Variation in radon exhalation from the ground on the active fault in Kobe

    Energy Technology Data Exchange (ETDEWEB)

    Yasuoka, Y.; Shinogi, M. [Kobe Pharmaceutical Univ., Kobe, Hyogo (Japan)

    1998-12-31

    Since 27 January 1997, the measurements of radon (Rn-222) exhaled from the ground have been made continuously by the use of PICO-RAD detector (Packard instrument Co.) at monitoring stations on Ashiya active fault. The fault may have been slipped by the Kobe earthquake (magnitude 7.2, 17 January 1995). The variation of relative radon exhalation on the fault was large. We guessed the large variation of relative radon exhalation on the fault was caused by not only the influence of meteorology but also the influence of other factors. (author)

  16. Simulation of near-fault bedrock strong ground-motion field by explicit finite element method

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xiao-zhi; HU Jin-jun; XIE Li-li; WANG Hai-yun

    2006-01-01

    Based on presumed active fault and corresponding model, this paper predicted the near-fault ground motion filed of a scenario earthquake (Mw=6 3/4 ) in an active fault by the explicit finite element method in combination with the source time function with improved transmitting artificial boundary and with high-frequency vibration contained.The results indicate that the improved artificial boundary is stable in numerical computation and the predicted strong ground motion has a consistent characteristic with the observed motion.

  17. Lithological and rheological constraints on fault rupture scenarios for ground motion hazard prediction. Revision 1

    Energy Technology Data Exchange (ETDEWEB)

    Foxall, W.; Hutchings, L.; Jarpe, S.

    1994-09-01

    This paper tests a new approach to predict a range of ground motion hazard at specific sites generated by earthquakes on specific faults. The approach utilizes geodynamics to link structural, lithological and Theological descriptions of the fault zones to development of fault rupture scenarios and computation of synthetic seismograms. Faults are placed within a regional geomechanical model that is used to calculate stress conditions along the fault. The approach is based upon three hypothesis: (1) An exact solution of the representation relation that u@s empirical. Green`s functions enables very accurate computation of ground motions generated by a given rupture scenario; (2) a general description of the rupture is sufficient; and (3) the structural, lithological and Theological characteristics of a fault can be used to constrain, in advance, possible future rupture histories. Ground motion hazard here refers to three-component, full wave train descriptions of displacement, velocity, and acceleration over the frequency band 0.01 to 25 Hz. Corollaries to these hypotheses are that the range of possible fault rupture histories is narrow enough to functionally constrain the range of strong ground motion predictions, and that a discreet set of rupture histories is sufficient to span the infinite combinations possible from a given range of rupture parameters.

  18. Fault Detection in Systems-A Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Ashok Kumar

    2004-04-01

    Full Text Available The task of fault detection is important when dealing with failures of crucial nature. After detection of faults in a system, it is advisable to suggest maintenance action before occurrenceof a failure. Fault detection may be done by observing various symptoms of the system during its operational stage. Sometimes, symptoms cannot be quantified easily but can be expressedin linguistic terms. Since linguistic terms are fuzzy quantifiers, these can be represented by fuzzy numbers. In this paper, two cases have been discussed, where a fault likely to affect a particular systemlsystems, is detected. In the first case, this is done by means of a compositional rule of inference. The second case is based on modified similarity measure. For both these  cases, linguistic terms have been expressed as trapezoidal fuzzy numbers

  19. Fault Management: Degradation Signature Detection, Modeling, and Processing Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Fault to Failure Progression (FFP) signature modeling and processing is a new method for applying condition-based signal data to detect degradation, to identify...

  20. Performance evaluation of fault detection methods for wastewater treatment processes.

    Science.gov (United States)

    Corominas, Lluís; Villez, Kris; Aguado, Daniel; Rieger, Leiv; Rosén, Christian; Vanrolleghem, Peter A

    2011-02-01

    Several methods to detect faults have been developed in various fields, mainly in chemical and process engineering. However, minimal practical guidelines exist for their selection and application. This work presents an index that allows for evaluating monitoring and diagnosis performance of fault detection methods, which takes into account several characteristics, such as false alarms, false acceptance, and undesirable switching from correct detection to non-detection during a fault event. The usefulness of the index to process engineering is demonstrated first by application to a simple example. Then, it is used to compare five univariate fault detection methods (Shewhart, EWMA, and residuals of EWMA) applied to the simulated results of the Benchmark Simulation Model No. 1 long-term (BSM1_LT). The BSM1_LT, provided by the IWA Task Group on Benchmarking of Control Strategies, is a simulation platform that allows for creating sensor and actuator faults and process disturbances in a wastewater treatment plant. The results from the method comparison using BSM1_LT show better performance to detect a sensor measurement shift for adaptive methods (residuals of EWMA) and when monitoring the actuator signals in a control loop (e.g., airflow). Overall, the proposed index is able to screen fault detection methods.

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

    Energy Technology Data Exchange (ETDEWEB)

    Sedighi, A.-R.; Haghifam, M.-R. [Department of Electrical Engineering, Tarbiat Modarres University, P.O. Box 14115-111, Tehran (Iran); Malik, O.P. [Department of Electrical and Computer Engineering, University of Calgary, Calgary, Alberta (Canada T2N 1N4)

    2005-09-15

    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 used for the decomposition of signals and feature extraction in both methods. In one method, GA is used for feature vector reduction and Bayes for classification. In the other method, principal component analysis (PCA) is applied for feature vector reduction and NN for classification. HIF and ILC data was acquired by experimental tests and the data for other faults was obtained by simulating a real network using EMTP. Results show that either of the proposed procedures can be used to identify HIF from other events efficiently. (author) [Bayes classifier; High impedance fault; Genetic algorithm; Neural network; Principal component analysis; Wavelet transform].

  2. Fault detection and isolation in processes involving induction machines

    Energy Technology Data Exchange (ETDEWEB)

    Zell, K.; Medvedev, A. [Control Engineering Group, Luleaa University of Technology, Luleaa (Sweden)

    1997-12-31

    A model-based technique for fault detection and isolation in electro-mechanical systems comprising induction machines is introduced. Two coupled state observers, one for the induction machine and another for the mechanical load, are used to detect and recognize fault-specific behaviors (fault signatures) from the real-time measurements of the rotor angular velocity and terminal voltages and currents. Practical applicability of the method is verified in full-scale experiments with a conveyor belt drive at SSAB, Luleaa Works. (orig.) 3 refs.

  3. Filtering, control and fault detection with randomly occurring incomplete information

    CERN Document Server

    Dong, Hongli; Gao, Huijun

    2013-01-01

    This book investigates the filtering, control and fault detection problems for several classes of nonlinear systems with randomly occurring incomplete information. It proposes new concepts, including RVNs, ROMDs, ROMTCDs, and ROQEs. The incomplete information under consideration primarily includes missing measurements, time-delays, sensor and actuator saturations, quantization effects and time-varying nonlinearities. The first part of this book focuses on the filtering, control and fault detection problems for several classes of nonlinear stochastic discrete-time systems and

  4. A Novel Method for Detection and Classification of Covered Conductor Faults

    Directory of Open Access Journals (Sweden)

    Stanislav Misak

    2016-01-01

    Full Text Available Medium-Voltage (MV overhead lines with Covered Conductors (CCs are increasingly being used around the world primarily in forested or dissected terrain areas or in urban areas where it is not possible to utilize MV cable lines. The CC is specific in high operational reliability provided by the conductor core insulation compared to Aluminium-Conductor Steel-Reinforced (ACSR overhead lines. The only disadvantage of the CC is rather the problematic detection of faults compared to the ACSR. In this work, we consider the following faults: the contact of a tree branch with a CC and the fall of a conductor on the ground. The standard protection relays are unable to detect the faults and so the faults pose a risk for individuals in the vicinity of the conductor as well as it compromises the overall safety and reliability of the MV distribution system. In this article, we continue with our previous work aimed at the method enabling detection of the faults and we introduce a method enabling a classification of the fault type. Such a classification is especially important for an operator of an MV distribution system to plan the optimal maintenance or repair the faulty conductors since the fall of a tree branch can be solved later whereas the breakdown of a conductor means an immediate action of the operator.

  5. General Fault Admittance Method Line-To-Line-To-Ground Faults In Reference And Odd Phases J.D. Sakala, J.S.J. Daka

    Directory of Open Access Journals (Sweden)

    J.D. Sakala,

    2014-02-01

    Full Text Available Line-to-line-to-ground faults are usually analysed using connection of symmetrical component networks at the fault point. As a first step, a reference phase is chosen which results in the simplest connection of the symmetrical component sequence networks for the fault. The simplest connection of symmetrical component sequence networks is a parallel one of the positive, negative and zero sequence networks when phase a of an abc phase sequence is the reference phase and the fault is taken to be between the b and c phases and ground. Putting the fault on an odd phase, say between the a and c phases and ground results in a parallel connection of the positive, negative and zero sequence networks that involve phase shifts, and the solution is more demanding. In practice, the results for the line-to-line-to-ground fault for the reference phase a may be translated to a fault on odd phases by appropriate substitution of phases. In this approach, the solution proceeds by assuming that the fault is in phases b and c and ground and that the symmetrical sequence networks are connected in parallel. The solution of the fault on b and c phases and ground is then translated to apply to the fault on odd phases, say either between phases c and a and ground or between phases a and b and ground. Alternatively, the parallel connection of the sequence networks at the fault point for the odd phases fault is solved for the symmetrical component currents and voltages.

  6. Observer Based Detection of Sensor Faults in Wind Turbines

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Nielsen, R.

    2009-01-01

    An observer based scheme is proposed to detect sensor faults in wind  turbines. In the example used for the proposed scheme the wind turbine  drive train is considered. A model of the drive train is used to  design the observer, and in this model the wind speed is an important  input, however......, if an unknown input observer the fault detection  scheme can be non dependent on the actual wind speed. The scheme  is validated on data from a more advanced and detailed simulation  model. The proposed scheme detects the sensor faults a few samples  after the beginning of the faults....

  7. A fault detection and isolation filter for discrete linear systems.

    Science.gov (United States)

    Giovanini, L; Dondo, R

    2003-10-01

    The problem of fault and/or abrupt disturbances detection and isolation for discrete linear systems is analyzed in this work. A strategy for detecting and isolating faults and/or abrupt disturbances is presented. The strategy is an extension of an already existing result in the continuous time domain to the discrete domain. The resulting detection algorithm is a Kalman filter with a special structure. The filter generates a residuals vector in such a way that each element of this vector is related with one fault or disturbance. Therefore the effects of the other faults, disturbances, and measurement noises in this element are minimized. The necessary stability and convergence conditions are briefly exposed. A numerical example is also presented.

  8. Fault detection by surface seismic scanning tunneling macroscope: Field test

    KAUST Repository

    Hanafy, Sherif M.

    2014-08-05

    The seismic scanning tunneling macroscope (SSTM) is proposed for detecting the presence of near-surface impedance anomalies and faults. Results with synthetic data are consistent with theory in that scatterers closer to the surface provide brighter SSTM profiles than those that are deeper. The SSTM profiles show superresolution detection if the scatterers are in the near-field region of the recording line. The field data tests near Gulf of Aqaba, Haql, KSA clearly show the presence of the observable fault scarp, and identify the subsurface presence of the hidden faults indicated in the tomograms. Superresolution detection of the fault is achieved, even when the 35 Hz data are lowpass filtered to the 5-10 Hz band.

  9. A fault detection service for wide area distributed computations.

    Energy Technology Data Exchange (ETDEWEB)

    Stelling, P.

    1998-06-09

    The potential for faults in distributed computing systems is a significant complicating factor for application developers. While a variety of techniques exist for detecting and correcting faults, the implementation of these techniques in a particular context can be difficult. Hence, we propose a fault detection service designed to be incorporated, in a modular fashion, into distributed computing systems, tools, or applications. This service uses well-known techniques based on unreliable fault detectors to detect and report component failure, while allowing the user to tradeoff timeliness of reporting against false positive rates. We describe the architecture of this service, report on experimental results that quantify its cost and accuracy, and describe its use in two applications, monitoring the status of system components of the GUSTO computational grid testbed and as part of the NetSolve network-enabled numerical solver.

  10. Auxiliary signal design in fault detection and diagnosis

    Science.gov (United States)

    Zhang, Xue Jun

    Fault-detection and diagnosis schemes for systems represented by linear MIMO stochastic models are developed analytically, with a focus on on the design and application of auxiliary signals. The basic principles of optimal-input design are reviewed, and consideration is given to the sequential probability ratio test (SPRT), auxiliary signals for improving SPRT fault detection, and the extension of the SPRT to multiple-hypothesis testing. Two chapters are devoted to the application of the SPRT to a model chemical plant (producing anhydrous caustic soda), including model derivation, model identification, detection of type I and type II faults, and the fault-diagnosis decision-making mechanism. Numerical results are presented in graphs and briefly characterized.

  11. Fault detection in rotor bearing systems using time frequency techniques

    Science.gov (United States)

    Chandra, N. Harish; Sekhar, A. S.

    2016-05-01

    Faults such as misalignment, rotor cracks and rotor to stator rub can exist collectively in rotor bearing systems. It is an important task for rotor dynamic personnel to monitor and detect faults in rotating machinery. In this paper, the rotor startup vibrations are utilized to solve the fault identification problem using time frequency techniques. Numerical simulations are performed through finite element analysis of the rotor bearing system with individual and collective combinations of faults as mentioned above. Three signal processing tools namely Short Time Fourier Transform (STFT), Continuous Wavelet Transform (CWT) and Hilbert Huang Transform (HHT) are compared to evaluate their detection performance. The effect of addition of Signal to Noise ratio (SNR) on three time frequency techniques is presented. The comparative study is focused towards detecting the least possible level of the fault induced and the computational time consumed. The computation time consumed by HHT is very less when compared to CWT based diagnosis. However, for noisy data CWT is more preferred over HHT. To identify fault characteristics using wavelets a procedure to adjust resolution of the mother wavelet is presented in detail. Experiments are conducted to obtain the run-up data of a rotor bearing setup for diagnosis of shaft misalignment and rotor stator rubbing faults.

  12. Convolutional Neural Network Based Fault Detection for Rotating Machinery

    Science.gov (United States)

    Janssens, Olivier; Slavkovikj, Viktor; Vervisch, Bram; Stockman, Kurt; Loccufier, Mia; Verstockt, Steven; Van de Walle, Rik; Van Hoecke, Sofie

    2016-09-01

    Vibration analysis is a well-established technique for condition monitoring of rotating machines as the vibration patterns differ depending on the fault or machine condition. Currently, mainly manually-engineered features, such as the ball pass frequencies of the raceway, RMS, kurtosis an crest, are used for automatic fault detection. Unfortunately, engineering and interpreting such features requires a significant level of human expertise. To enable non-experts in vibration analysis to perform condition monitoring, the overhead of feature engineering for specific faults needs to be reduced as much as possible. Therefore, in this article we propose a feature learning model for condition monitoring based on convolutional neural networks. The goal of this approach is to autonomously learn useful features for bearing fault detection from the data itself. Several types of bearing faults such as outer-raceway faults and lubrication degradation are considered, but also healthy bearings and rotor imbalance are included. For each condition, several bearings are tested to ensure generalization of the fault-detection system. Furthermore, the feature-learning based approach is compared to a feature-engineering based approach using the same data to objectively quantify their performance. The results indicate that the feature-learning system, based on convolutional neural networks, significantly outperforms the classical feature-engineering based approach which uses manually engineered features and a random forest classifier. The former achieves an accuracy of 93.61 percent and the latter an accuracy of 87.25 percent.

  13. Application of Fault Location Mode Based on Travelling Waves for Neutral Non-effective Grounding Systems

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    <正>Fault location for distribution feeders short circuit especially single-phase grounding fault is an important task in distribution system with non-effectively grounded neutral.Fault location mode for distribution feeders using fault generated current and voltage transient traveling waves was investigated.The characteristics of transient traveling waves resulted from each short circuit fault and their transmission disciplinarian in distribution feeders are analyzed.This paper proposed that double end travelling waves theory which measures arriving time of fault initiated surge at both ends of the monitored line is fit for distribution feeders but single end traveling waves theory not.According to different distribution feeders,on the basis of analyzing original traveling waves reflection rule in line terminal, Current-voltage mode,voltage-voltage mode and current-current mode for fault location based on traveling waves are proposed and aerial mode component of original traveling waves is used to realize fault location.Experimental test verify the feasibility and correctness of the proposed method.

  14. Optimal Sensor Allocation for Fault Detection and Isolation

    Science.gov (United States)

    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. Multi-directional fault detection system

    Science.gov (United States)

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

    2009-03-17

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

  16. Fault Characteristics and Protection Scheme of the MMC-UPFC under Different Grounding Design

    Science.gov (United States)

    Zheng, Tao; Wang, Ketan; Wu, Dan; Qi, Huanhuan

    2017-07-01

    The Unified Power Flow Controller (UPFC) based on Modular Multilevel Converter (MMC) is more suitable for high-voltage and large-capacity transmission fields. According to the actual needs of demonstration project, 3 grounding proposals were brought out and the effect of different grounding proposals to the fault characteristics and protection schemes is analyzed in detail. The conclusion that only parallel valve side star connected large resistance grounding is more advantageous in MMC-UPFC was derived.

  17. Observer Based Fault Detection and Moisture Estimating in Coal Mill

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Mataji, Babak

    2008-01-01

    In this paper an observer-based method for detecting faults and estimating moisture content in the coal in coal mills is presented. Handling of faults and operation under special conditions, such as high moisture content in the coal, are of growing importance due to the increasing requirements to......In this paper an observer-based method for detecting faults and estimating moisture content in the coal in coal mills is presented. Handling of faults and operation under special conditions, such as high moisture content in the coal, are of growing importance due to the increasing...... requirements to the general performance of power plants. Detection  of faults and moisture content estimation are consequently of high interest in the handling of the problems caused by faults and moisture content. The coal flow out of the mill is the obvious variable to monitor, when detecting non-intended drops in the coal...... flow out of the coal mill. However, this variable is not measurable. Another estimated variable is the moisture content, which is only "measurable" during steady-state operations of the coal mill. Instead, this paper suggests a method where these unknown variables are estimated based on a simple energy...

  18. Development of Fault Models for Hybrid Fault Detection and Diagnostics Algorithm: October 1, 2014 -- May 5, 2015

    Energy Technology Data Exchange (ETDEWEB)

    Cheung, Howard [Purdue Univ., West Lafayette, IN (United States); Braun, James E. [Purdue Univ., West Lafayette, IN (United States)

    2015-12-31

    This report describes models of building faults created for OpenStudio to support the ongoing development of fault detection and diagnostic (FDD) algorithms at the National Renewable Energy Laboratory. Building faults are operating abnormalities that degrade building performance, such as using more energy than normal operation, failing to maintain building temperatures according to the thermostat set points, etc. Models of building faults in OpenStudio can be used to estimate fault impacts on building performance and to develop and evaluate FDD algorithms. The aim of the project is to develop fault models of typical heating, ventilating and air conditioning (HVAC) equipment in the United States, and the fault models in this report are grouped as control faults, sensor faults, packaged and split air conditioner faults, water-cooled chiller faults, and other uncategorized faults. The control fault models simulate impacts of inappropriate thermostat control schemes such as an incorrect thermostat set point in unoccupied hours and manual changes of thermostat set point due to extreme outside temperature. Sensor fault models focus on the modeling of sensor biases including economizer relative humidity sensor bias, supply air temperature sensor bias, and water circuit temperature sensor bias. Packaged and split air conditioner fault models simulate refrigerant undercharging, condenser fouling, condenser fan motor efficiency degradation, non-condensable entrainment in refrigerant, and liquid line restriction. Other fault models that are uncategorized include duct fouling, excessive infiltration into the building, and blower and pump motor degradation.

  19. Development of Fault Models for Hybrid Fault Detection and Diagnostics Algorithm: October 1, 2014 -- May 5, 2015

    Energy Technology Data Exchange (ETDEWEB)

    Cheung, Howard; Braun, James E.

    2015-12-31

    This report describes models of building faults created for OpenStudio to support the ongoing development of fault detection and diagnostic (FDD) algorithms at the National Renewable Energy Laboratory. Building faults are operating abnormalities that degrade building performance, such as using more energy than normal operation, failing to maintain building temperatures according to the thermostat set points, etc. Models of building faults in OpenStudio can be used to estimate fault impacts on building performance and to develop and evaluate FDD algorithms. The aim of the project is to develop fault models of typical heating, ventilating and air conditioning (HVAC) equipment in the United States, and the fault models in this report are grouped as control faults, sensor faults, packaged and split air conditioner faults, water-cooled chiller faults, and other uncategorized faults. The control fault models simulate impacts of inappropriate thermostat control schemes such as an incorrect thermostat set point in unoccupied hours and manual changes of thermostat set point due to extreme outside temperature. Sensor fault models focus on the modeling of sensor biases including economizer relative humidity sensor bias, supply air temperature sensor bias, and water circuit temperature sensor bias. Packaged and split air conditioner fault models simulate refrigerant undercharging, condenser fouling, condenser fan motor efficiency degradation, non-condensable entrainment in refrigerant, and liquid line restriction. Other fault models that are uncategorized include duct fouling, excessive infiltration into the building, and blower and pump motor degradation.

  20. Application of fault factor method to fault detection and diagnosis for space shuttle main engine

    Science.gov (United States)

    Cha, Jihyoung; Ha, Chulsu; Ko, Sangho; Koo, Jaye

    2016-09-01

    This paper deals with an application of the multiple linear regression algorithm to fault detection and diagnosis for the space shuttle main engine (SSME) during a steady state. In order to develop the algorithm, the energy balance equations, which balances the relation among pressure, mass flow rate and power at various locations within the SSME, are obtained. Then using the measurement data of some important parameters of the engine, fault factors which reflects the deviation of each equation from the normal state are estimated. The probable location of each fault and the levels of severity can be obtained from the estimated fault factors. This process is numerically demonstrated for the SSME at 104% Rated Propulsion Level (RPL) by using the simulated measurement data from the mathematical models of the engine. The result of the current study is particularly important considering that the recently developed reusable Liquid Rocket Engines (LREs) have staged-combustion cycles similarly to the SSME.

  1. Development and Test of Methods for Fault Detection and Isolation

    DEFF Research Database (Denmark)

    Jørgensen, R.B.

    the thesis. The IPC offers prospects of repeated fault scenarios, and support studies in robustness issues. The thesis contributes with a numerical fault analysis representation, practical applications of existing methods for FDI, and a method for robust FDI for practical applications....... they are especiallu crucial for the entire operaiton of a closed loop system. The purpose of the thesis is to investigate, deveop, and verify methods for fault detection and isolation on control loop systems. An Industrial Position Controller, (IPC), laboratory setup is used as an application example throughout...

  2. Signal processing for solar array monitoring, fault detection, and optimization

    CERN Document Server

    Braun, Henry; Spanias, Andreas

    2012-01-01

    Although the solar energy industry has experienced rapid growth recently, high-level management of photovoltaic (PV) arrays has remained an open problem. As sensing and monitoring technology continues to improve, there is an opportunity to deploy sensors in PV arrays in order to improve their management. In this book, we examine the potential role of sensing and monitoring technology in a PV context, focusing on the areas of fault detection, topology optimization, and performance evaluation/data visualization. First, several types of commonly occurring PV array faults are considered and detection algorithms are described. Next, the potential for dynamic optimization of an array's topology is discussed, with a focus on mitigation of fault conditions and optimization of power output under non-fault conditions. Finally, monitoring system design considerations such as type and accuracy of measurements, sampling rate, and communication protocols are considered. It is our hope that the benefits of monitoring presen...

  3. Stator Fault Detection in Induction Motors by Autoregressive Modeling

    Directory of Open Access Journals (Sweden)

    Francisco M. Garcia-Guevara

    2016-01-01

    Full Text Available This study introduces a novel methodology for early detection of stator short circuit faults in induction motors by using autoregressive (AR model. The proposed algorithm is based on instantaneous space phasor (ISP module of stator currents, which are mapped to α-β stator-fixed reference frame; then, the module is obtained, and the coefficients of the AR model for such module are estimated and evaluated by order selection criterion, which is used as fault signature. For comparative purposes, a spectral analysis of the ISP module by Discrete Fourier Transform (DFT is performed; a comparison of both methodologies is obtained. To demonstrate the suitability of the proposed methodology for detecting and quantifying incipient short circuit stator faults, an induction motor was altered to induce different-degree fault scenarios during experimentation.

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

    Science.gov (United States)

    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.

  5. Fault-tolerant control for current sensors of doubly fed induction generators based on an improved fault detection method

    DEFF Research Database (Denmark)

    Li, Hui; Yang, Chao; Hu, Yaogang

    2014-01-01

    Fault-tolerant control of current sensors is studied in this paper to improve the reliability of a doubly fed induction generator (DFIG). A fault-tolerant control system of current sensors is presented for the DFIG, which consists of a new current observer and an improved current sensor fault...... detection algorithm, and fault-tolerant control system are investigated by simulation. The results indicate that the outputs of the observer and the sensor are highly coherent. The fault detection algorithm can efficiently detect both soft and hard faults in current sensors, and the fault-tolerant control...... system can effectively tolerate both types of faults. © 2013 Published by Elsevier Ltd. All rights reserved....

  6. FaultBuster: data driven fault detection and diagnosis for industrial systems

    DEFF Research Database (Denmark)

    Bergantino, Nicola; Caponetti, Fabio; Longhi, Sauro

    2009-01-01

    Efficient and reliable monitoring systems are mandatory to assure the required security standards in industrial complexes. This paper describes the recent developments of FaultBuster, a purely data-driven diagnostic system. It is designed so to be easily scalable to different monitor tasks....... Multivariate statistical models based on principal components are used to detect abnormal situations. Tailored to alarms, a probabilistic inference engine process the fault evidences to output the most probable diagnosis. Results from the DX 09 Diagnostic Challenge shown strong detection properties, while...

  7. Fault-weighted quantification method of fault detection coverage through fault mode and effect analysis in digital I&C systems

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jaehyun; Lee, Seung Jun, E-mail: sjlee420@unist.ac.kr; Jung, Wondea

    2017-05-15

    Highlights: • We developed the fault-weighted quantification method of fault detection coverage. • The method has been applied to specific digital reactor protection system. • The unavailability of the module had 20-times difference with the traditional method. • Several experimental tests will be effectively prioritized using this method. - Abstract: The one of the most outstanding features of a digital I&C system is the use of a fault-tolerant technique. With an awareness regarding the importance of thequantification of fault detection coverage of fault-tolerant techniques, several researches related to the fault injection method were developed and employed to quantify a fault detection coverage. In the fault injection method, each injected fault has a different importance because the frequency of realization of every injected fault is different. However, there have been no previous studies addressing the importance and weighting factor of each injected fault. In this work, a new method for allocating the weighting to each injected fault using the failure mode and effect analysis data was proposed. For application, the fault-weighted quantification method has also been applied to specific digital reactor protection system to quantify the fault detection coverage. One of the major findings in an application was that we may estimate the unavailability of the specific module in digital I&C systems about 20-times smaller than real value when we use a traditional method. The other finding was that we can also classify the importance of the experimental case. Therefore, this method is expected to not only suggest an accurate quantification procedure of fault-detection coverage by weighting the injected faults, but to also contribute to an effective fault injection experiment by sorting the importance of the failure categories.

  8. Generic, scalable and decentralized fault detection for robot swarms

    Science.gov (United States)

    Christensen, Anders Lyhne; Timmis, Jon

    2017-01-01

    Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system’s capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation. PMID:28806756

  9. Accounting for Fault Roughness in Pseudo-Dynamic Ground-Motion Simulations

    KAUST Repository

    Mai, Paul Martin

    2017-04-03

    Geological faults comprise large-scale segmentation and small-scale roughness. These multi-scale geometrical complexities determine the dynamics of the earthquake rupture process, and therefore affect the radiated seismic wavefield. In this study, we examine how different parameterizations of fault roughness lead to variability in the rupture evolution and the resulting near-fault ground motions. Rupture incoherence naturally induced by fault roughness generates high-frequency radiation that follows an ω−2 decay in displacement amplitude spectra. Because dynamic rupture simulations are computationally expensive, we test several kinematic source approximations designed to emulate the observed dynamic behavior. When simplifying the rough-fault geometry, we find that perturbations in local moment tensor orientation are important, while perturbations in local source location are not. Thus, a planar fault can be assumed if the local strike, dip, and rake are maintained. We observe that dynamic rake angle variations are anti-correlated with the local dip angles. Testing two parameterizations of dynamically consistent Yoffe-type source-time function, we show that the seismic wavefield of the approximated kinematic ruptures well reproduces the radiated seismic waves of the complete dynamic source process. This finding opens a new avenue for an improved pseudo-dynamic source characterization that captures the effects of fault roughness on earthquake rupture evolution. By including also the correlations between kinematic source parameters, we outline a new pseudo-dynamic rupture modeling approach for broadband ground-motion simulation.

  10. Near-fault directivity pulse-like ground motion effect on high-speed railway bridge

    Institute of Scientific and Technical Information of China (English)

    陈令坤; 张楠; 蒋丽忠; 曾志平; 陈格威; 国巍

    2014-01-01

    The vehicle-track-bridge (VTB) element was used to investigate how a high-speed railway bridge reacted when it was subjected to near-fault directivity pulse-like ground motions. Based on the PEER NAG Strong Ground Motion Database, the spatial analysis model of a vehicle-bridge system was developed, the VTB element was derived to simulate the interaction of train and bridge, and the elasto-plastic seismic responses of the bridge were calculated. The calculation results show that girder and pier top displacement, and bending moment of the pier base increase subjected to near-fault directivity pulse-like ground motion compared to far-field earthquakes, and the greater deformation responses in near-fault shaking are associated with fewer reversed cycles of loading. The hysteretic characteristics of the pier subjected to a near-fault directivity pulse-like earthquake should be explicitly expressed as the bending moment-rotation relationship of the pier base, which is characterized by the centrally strengthened hysteretic cycles at some point of the loading time-history curve. The results show that there is an amplification of the vertical deflection in the girder’s mid-span owing to the high vertical ground motion. In light of these findings, the effect of the vertical ground motion should be used to adjust the unconservative amplification constant 2/3 of the vertical-to-horizontal peak ground motion ratio in the seismic design of bridge.

  11. Sparsity-based algorithm for detecting faults in rotating machines

    Science.gov (United States)

    He, Wangpeng; Ding, Yin; Zi, Yanyang; Selesnick, Ivan W.

    2016-05-01

    This paper addresses the detection of periodic transients in vibration signals so as to detect faults in rotating machines. For this purpose, we present a method to estimate periodic-group-sparse signals in noise. The method is based on the formulation of a convex optimization problem. A fast iterative algorithm is given for its solution. A simulated signal is formulated to verify the performance of the proposed approach for periodic feature extraction. The detection performance of comparative methods is compared with that of the proposed approach via RMSE values and receiver operating characteristic (ROC) curves. Finally, the proposed approach is applied to single fault diagnosis of a locomotive bearing and compound faults diagnosis of motor bearings. The processed results show that the proposed approach can effectively detect and extract the useful features of bearing outer race and inner race defect.

  12. A preliminary study on surface ground deformation near shallow foundation induced by strike-slip faulting

    Science.gov (United States)

    Wong, Pei-Syuan; Lin, Ming-Lang

    2016-04-01

    According to investigation of recent earthquakes, ground deformation and surface rupture are used to map the influenced range of the active fault. The zones of horizontal and vertical surface displacements and different features of surface rupture are investigated in the field, for example, the Greendale Fault 2010, MW 7.1 Canterbury earthquake. The buildings near the fault rotated and displaced vertically and horizontally due to the ground deformation. Besides, the propagation of fault trace detoured them because of the higher rigidity. Consequently, it's necessary to explore the ground deformation and mechanism of the foundation induced by strike-slip faulting for the safety issue. Based on previous study from scaled analogue model of strike-slip faulting, the ground deformation is controlled by material properties, depth of soil, and boundary condition. On the condition controlled, the model shows the features of ground deformation in the field. This study presents results from shear box experiment on small-scale soft clay models subjected to strike-slip faulting and placed shallow foundations on it in a 1-g environment. The quantifiable data including sequence of surface rupture, topography and the position of foundation are recorded with increasing faulting. From the result of the experiment, first en echelon R shears appeared. The R shears rotated to a more parallel angle to the trace and cracks pulled apart along them with increasing displacements. Then the P shears crossed the basement fault in the opposite direction appears and linked R shears. Lastly the central shear was Y shears. On the other hand, the development of wider zones of rupture, higher rising surface and larger the crack area on surface developed, with deeper depth of soil. With the depth of 1 cm and half-box displacement 1.2 cm, en echelon R shears appeared and the surface above the fault trace elevated to 1.15 mm (Dv), causing a 1.16 cm-wide zone of ground-surface rupture and deformation

  13. Closed-form critical earthquake response of elastic-plastic structures on compliant ground under near-fault ground motions

    Directory of Open Access Journals (Sweden)

    Kotaro eKojima

    2016-01-01

    Full Text Available The double impulse is introduced as a substitute of the fling-step near-fault ground motion. A closed-form solution of the elastic-plastic response of a structure on compliant (flexible ground by the ‘critical double impulse’ is derived for the first time based on the solution for the corresponding structure with fixed base. As in the case of fixed-base model, only the free-vibration appears under such double impulse and the energy approach plays an important role in the derivation of the closed-form solution of a complicated elastic-plastic response on compliant ground. It is remarkable that no iteration is needed in the derivation of the critical elastic-plastic response. It is shown via the closed-form expression that, in the case of a smaller input level of double impulse to the structural strength, as the ground stiffness becomes larger, the maximum plastic deformation becomes larger. On the other hand, in the case of a larger input level of double impulse to the structural strength, as the ground stiffness becomes smaller, the maximum plastic deformation becomes larger. The criticality and validity of the proposed theory are investigated through the comparison with the response analysis to the corresponding one-cycle sinusoidal input as a representative of the fling-step near-fault ground motion. The applicability of the proposed theory to actual recorded pulse-type ground motions is also discussed.

  14. Effects and implications of fault zone heterogeneity and anisotropy on earthquake strong ground motion

    Science.gov (United States)

    Su, Wei-Jou

    This thesis consists of two parts. Part one is concerned with the effect of fault zone heterogeneity on the strong ground motion of the Loma Preita earthquake. Part two is concerned with the effect of the effective hexagonal anisotropy of a fault zone on strong ground motion. A superposition of Gaussian beams is used to analyze these problems because it can account for both the rupture history of the fault plane and the fault zone heterogeneity. We also extend this method to investigate the combined effects of the rupture process on a fault plane and medium anisotropy on the synthetic seismograms. The strong ground motion of the Loma Prieta Earthquake is synthesized using a known three-dimensional crustal model of the region, a rupture model determined under the assumption of laterally homogeneous structure, and Green's functions computed by superposition of Gaussian beams. Compared to results obtained assuming a laterally homogeneous crust, stations lying to the northeast of the rupture zone are predicted to be defocused, while stations lying to the west of the fault trace are predicted to be focused. The defocusing is caused by a zone of high velocity material between the San Andreas and Sargent faults, and the focusing is caused by a region of low velocity lying between the Zayantes and San Andreas faults. If lateral homogeneity is assumed, the net effect of the predicted focusing and defocusing is to bias estimates of the relative slip of two high slip regions found in inversions of local and teleseismic body waves. These biases are similar in magnitude to those estimated for waveform inversions from the effects of using different subsets of data and/or different misfit functions and are similar in magnitude to the effects predicted for non-linear site responses.

  15. Parameter estimation and reliable fault detection of electric motors

    Institute of Scientific and Technical Information of China (English)

    Dusan PROGOVAC; Le Yi WANG; George YIN

    2014-01-01

    Accurate model identification and fault detection are necessary for reliable motor control. Motor-characterizing parameters experience substantial changes due to aging, motor operating conditions, and faults. Consequently, motor parameters must be estimated accurately and reliably during operation. Based on enhanced model structures of electric motors that accommodate both normal and faulty modes, this paper introduces bias-corrected least-squares (LS) estimation algorithms that incorporate functions for correcting estimation bias, forgetting factors for capturing sudden faults, and recursive structures for efficient real-time implementation. Permanent magnet motors are used as a benchmark type for concrete algorithm development and evaluation. Algorithms are presented, their properties are established, and their accuracy and robustness are evaluated by simulation case studies under both normal operations and inter-turn winding faults. Implementation issues from different motor control schemes are also discussed.

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

    Science.gov (United States)

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

    2015-07-01

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

  17. A New Acoustic Emission Sensor Based Gear Fault Detection Approach

    Directory of Open Access Journals (Sweden)

    Junda Zhu

    2013-01-01

    Full Text Available In order to reduce wind energy costs, prognostics and health management (PHM of wind turbine is needed to ensure the reliability and availability of wind turbines. A gearbox is an important component of a wind turbine. Therefore, developing effective gearbox fault detection tools is important to the PHM of wind turbine. In this paper, a new acoustic emission (AE sensor based gear fault detection approach is presented. This approach combines a heterodyne based frequency reduction technique with time synchronous average (TSA and spectrum kurtosis (SK to process AE sensor signals and extract features as condition indictors for gear fault detection. Heterodyne technique commonly used in communication is first employed to preprocess the AE signals before sampling. By heterodyning, the AE signal frequency is down shifted from several hundred kHz to below 50 kHz. This reduced AE signal sampling rate is comparable to that of vibration signals. The presented approach is validated using seeded gear tooth crack fault tests on a notational split torque gearbox. The approach presented in this paper is physics based and the validation results have showed that it could effectively detect the gear faults.

  18. Data driven fault detection and isolation: a wind turbine scenario

    Directory of Open Access Journals (Sweden)

    Rubén Francisco Manrique Piramanrique

    2015-04-01

    Full Text Available One of the greatest drawbacks in wind energy generation is the high maintenance cost associated to mechanical faults. This problem becomes more evident in utility scale wind turbines, where the increased size and nominal capacity comes with additional problems associated with structural vibrations and aeroelastic effects in the blades. Due to the increased operation capability, it is imperative to detect system degradation and faults in an efficient manner, maintaining system integrity, reliability and reducing operation costs. This paper presents a comprehensive comparison of four different Fault Detection and Isolation (FDI filters based on “Data Driven” (DD techniques. In order to enhance FDI performance, a multi-level strategy is used where:  the first level detects the occurrence of any given fault (detection, while  the second identifies the source of the fault (isolation. Four different DD classification techniques (namely Support Vector Machines, Artificial Neural Networks, K Nearest Neighbors and Gaussian Mixture Models were studied and compared for each of the proposed classification levels. The best strategy at each level could be selected to build the final data driven FDI system. The performance of the proposed scheme is evaluated on a benchmark model of a commercial wind turbine. 

  19. Robust filtering and fault detection of switched delay systems

    CERN Document Server

    Wang, Dong; Wang, Wei

    2013-01-01

    Switched delay systems appear in a wide field of applications including networked control systems, power systems, memristive systems. Though the large amount of ideas with respect to such systems have generated, until now, it still lacks a framework to focus on filter design and fault detection issues which are relevant to life safety and property loss. Beginning with the comprehensive coverage of the new developments in the analysis and control synthesis for switched delay systems, the monograph not only provides a systematic approach to designing the filter and detecting the fault of switched delay systems, but it also covers the model reduction issues. Specific topics covered include: (1) Arbitrary switching signal where delay-independent and delay-dependent conditions are presented by proposing a linearization technique. (2) Average dwell time where a weighted Lyapunov function is come up with dealing with filter design and fault detection issues beside taking model reduction problems. The monograph is in...

  20. Unknown input observer based detection of sensor faults in a wind turbine

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2010-01-01

    In this paper an unknown input observer is designed to detect three different sensor fault scenarios in a specified bench mark model for fault detection and accommodation of wind turbines. In this paper a subset of faults is dealt with, it are faults in the rotor and generator speed sensors as well...... as a converter sensor fault. The proposed scheme detects the speed sensor faults in question within the specified requirements given in the bench mark model, while the converter fault is detected but not within the required time to detect....

  1. Fault Estimation and Control for a Quad-Rotor MAV Using a Polynomial Observer. Part I: Fault Detection

    OpenAIRE

    Flores Colunga, Gerardo Ramon; Aguilar-Sierra, Hipolito; Lozano, Rogelio; Salazar, Sergio

    2014-01-01

    International audience; This work addresses the problem of fault detection and diagnosis (FDD) for a quad-rotor mini aerial vehicle (MAV). Actuator faults are considered on this paper. The basic idea behind the proposed method is to estimate the faults signals using the extended state observers theory. To estimate the faults, a polynomial observer is presented by using the available measurements and know inputs of the system. In order to investigate the observability and diagnosability proper...

  2. Model-based fault detection and diagnosis in ALMA subsystems

    Science.gov (United States)

    Ortiz, José; Carrasco, Rodrigo A.

    2016-07-01

    The Atacama Large Millimeter/submillimeter Array (ALMA) observatory, with its 66 individual telescopes and other central equipment, generates a massive set of monitoring data every day, collecting information on the performance of a variety of critical and complex electrical, electronic and mechanical components. This data is crucial for most troubleshooting efforts performed by engineering teams. More than 5 years of accumulated data and expertise allow for a more systematic approach to fault detection and diagnosis. This paper presents model-based fault detection and diagnosis techniques to support corrective and predictive maintenance in a 24/7 minimum-downtime observatory.

  3. Fault Detection and Isolation using Viability Theory and Interval Observers

    Science.gov (United States)

    Ghaniee Zarch, Majid; Puig, Vicenç; Poshtan, Javad

    2017-01-01

    This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the adaptation to viability constraints of evolutions governed by complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behavior by using simple sets that approximate the exact set of possible behavior (in the parameter or state space). In this paper, fault detection is based on checking for an inconsistency between the measured and predicted behaviors using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approach.

  4. Fault Detection and Isolation and Fault Tolerant Control of Wind Turbines Using Set-Valued Observers

    DEFF Research Database (Denmark)

    Casau, Pedro; Rosa, Paulo Andre Nobre; Tabatabaeipour, Seyed Mojtaba

    2012-01-01

    and Isolation (FDI) and Fault Tolerant Control (FTC) of wind turbines, by taking advantage of the recent advances in SVO theory for model invalidation. A simple wind turbine model is presented along with possible faulty scenarios. The FDI algorithm is built on top of the described model, taking into account......Research on wind turbine Operations & Maintenance (O&M) procedures is critical to the expansion of Wind Energy Conversion systems (WEC). In order to reduce O&M costs and increase the lifespan of the turbine, we study the application of Set-Valued Observers (SVO) to the problem of Fault Detection...

  5. Hall Sensor Output Signal Fault-Detection & Safety Implementation Logic

    Directory of Open Access Journals (Sweden)

    Lee SangHun

    2016-01-01

    Full Text Available Recently BLDC motors have been popular in various industrial applications and electric mobility. Recently BLDC motors have been popular in various industrial applications and electric mobility. In most brushless direct current (BLDC motor drives, there are three hall sensors as a position reference. Low resolution hall effect sensor is popularly used to estimate the rotor position because of its good comprehensive performance such as low cost, high reliability and sufficient precision. Various possible faults may happen in a hall effect sensor. This paper presents a fault-tolerant operation method that allows the control of a BLDC motor with one faulty hall sensor and presents the hall sensor output fault-tolerant control strategy. The situations considered are when the output from a hall sensor stays continuously at low or high levels, or a short-time pulse appears on a hall sensor signal. For fault detection, identification of a faulty signal and generating a substitute signal, this method only needs the information from the hall sensors. There are a few research work on hall effect sensor failure of BLDC motor. The conventional fault diagnosis methods are signal analysis, model based analysis and knowledge based analysis. The proposed method is signal based analysis using a compensation signal for reconfiguration and therefore fault diagnosis can be fast. The proposed method is validated to execute the simulation using PSIM.

  6. Fuzzy model-based observers for fault detection in CSTR.

    Science.gov (United States)

    Ballesteros-Moncada, Hazael; Herrera-López, Enrique J; Anzurez-Marín, Juan

    2015-11-01

    Under the vast variety of fuzzy model-based observers reported in the literature, what would be the properone to be used for fault detection in a class of chemical reactor? In this study four fuzzy model-based observers for sensor fault detection of a Continuous Stirred Tank Reactor were designed and compared. The designs include (i) a Luenberger fuzzy observer, (ii) a Luenberger fuzzy observer with sliding modes, (iii) a Walcott-Zak fuzzy observer, and (iv) an Utkin fuzzy observer. A negative, an oscillating fault signal, and a bounded random noise signal with a maximum value of ±0.4 were used to evaluate and compare the performance of the fuzzy observers. The Utkin fuzzy observer showed the best performance under the tested conditions.

  7. Similarity measure application to fault detection of flight system

    Institute of Scientific and Technical Information of China (English)

    KIM J H; LEE S H; WANG Hong-mei

    2009-01-01

    Fault detection technique is introduced with similarity measure. The characteristics of conventional similarity measure based on fuzzy number are discussed. With the help of distance measure, similarity measure is constructed explicitly. The designed distance-based similarity measure is applicable to general fuzzy membership functions including non-convex fuzzy membership function, whereas fuzzy number-based similarity measure has limitation to calculate the similarity of general fuzzy membership functions. The applicability of the proposed similarity measure to general fuzzy membership structures is proven by identifying the definition. To decide fault detection of flight system, the experimental data (pitching moment coefficients and lift coefficients) are transformed into fuzzy membership functions. Distance-based similarity measure is applied to the obtained fuzzy membership functions, and similarity computation and analysis are obtained with the fault and normal operation coefficients.

  8. Fault Detection in Coal Mills used in Power Plants

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Mataji, Babak

    2006-01-01

    In order to achieve high performance and efficiency of coal-fired power plants, it is highly important to control the coal flow into the furnace 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 when they emerge. This paper deals with the second objective. Based on a simple dynamic model of the energy balance a residual is formed for the coal mill. An optimal unknown input observer is designed to estimate this residual. The estimated residual is following...... tested on measured data of a fault in a coal mill, it can hereby be concluded that this residual is very useful for detecting faults in the coal mill....

  9. A Prognostic Method for Fault Detection in Wind Turbine Drivetrains

    DEFF Research Database (Denmark)

    Nejada, Amir R.; Odgaard, Peter Fogh; Gao, Zhen

    2014-01-01

    In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermedi......In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors...... on the intermediate shafts inside the gearbox. An angular velocity error function is defined and compared in the faulty and fault-free conditions in frequency domain. Faults can be detected from the change in the energy level of the frequency spectrum of an error function. The method is demonstrated by detecting...... a dynamometer test bench and applied to the numerical gearbox model. The method is exemplified using a 750 kW wind turbine gearbox. The case study results show that defects in the high- and intermediate-speed bearings can be detected using this method. It is shown that this procedure is relatively simple, yet...

  10. Ground-motion modeling of Hayward fault scenario earthquakes, part II: Simulation of long-period and broadband ground motions

    Science.gov (United States)

    Aagaard, Brad T.; Graves, Robert W.; Rodgers, Arthur; Brocher, Thomas M.; Simpson, Robert W.; Dreger, Douglas; Petersson, N. Anders; Larsen, Shawn C.; Ma, Shuo; Jachens, Robert C.

    2010-01-01

    We simulate long-period (T>1.0–2.0 s) and broadband (T>0.1 s) ground motions for 39 scenario earthquakes (Mw 6.7–7.2) involving the Hayward, Calaveras, and Rodgers Creek faults. For rupture on the Hayward fault, we consider the effects of creep on coseismic slip using two different approaches, both of which reduce the ground motions, compared with neglecting the influence of creep. Nevertheless, the scenario earthquakes generate strong shaking throughout the San Francisco Bay area, with about 50% of the urban area experiencing modified Mercalli intensity VII or greater for the magnitude 7.0 scenario events. Long-period simulations of the 2007 Mw 4.18 Oakland earthquake and the 2007 Mw 5.45 Alum Rock earthquake show that the U.S. Geological Survey’s Bay Area Velocity Model version 08.3.0 permits simulation of the amplitude and duration of shaking throughout the San Francisco Bay area for Hayward fault earthquakes, with the greatest accuracy in the Santa Clara Valley (San Jose area). The ground motions for the suite of scenarios exhibit a strong sensitivity to the rupture length (or magnitude), hypocenter (or rupture directivity), and slip distribution. The ground motions display a much weaker sensitivity to the rise time and rupture speed. Peak velocities, peak accelerations, and spectral accelerations from the synthetic broadband ground motions are, on average, slightly higher than the Next Generation Attenuation (NGA) ground-motion prediction equations. We attribute much of this difference to the seismic velocity structure in the San Francisco Bay area and how the NGA models account for basin amplification; the NGA relations may underpredict amplification in shallow sedimentary basins. The simulations also suggest that the Spudich and Chiou (2008) directivity corrections to the NGA relations could be improved by increasing the areal extent of rupture directivity with period.

  11. Ground motion modeling of Hayward fault scenario earthquakes II:Simulation of long-period and broadband ground motions

    Energy Technology Data Exchange (ETDEWEB)

    Aagaard, B T; Graves, R W; Rodgers, A; Brocher, T M; Simpson, R W; Dreger, D; Petersson, N A; Larsen, S C; Ma, S; Jachens, R C

    2009-11-04

    We simulate long-period (T > 1.0-2.0 s) and broadband (T > 0.1 s) ground motions for 39 scenarios earthquakes (Mw 6.7-7.2) involving the Hayward, Calaveras, and Rodgers Creek faults. For rupture on the Hayward fault we consider the effects of creep on coseismic slip using two different approaches, both of which reduce the ground motions compared with neglecting the influence of creep. Nevertheless, the scenario earthquakes generate strong shaking throughout the San Francisco Bay area with about 50% of the urban area experiencing MMI VII or greater for the magnitude 7.0 scenario events. Long-period simulations of the 2007 Mw 4.18 Oakland and 2007 Mw 4.5 Alum Rock earthquakes show that the USGS Bay Area Velocity Model version 08.3.0 permits simulation of the amplitude and duration of shaking throughout the San Francisco Bay area, with the greatest accuracy in the Santa Clara Valley (San Jose area). The ground motions exhibit a strong sensitivity to the rupture length (or magnitude), hypocenter (or rupture directivity), and slip distribution. The ground motions display a much weaker sensitivity to the rise time and rupture speed. Peak velocities, peak accelerations, and spectral accelerations from the synthetic broadband ground motions are, on average, slightly higher than the Next Generation Attenuation (NGA) ground-motion prediction equations. We attribute at least some of this difference to the relatively narrow width of the Hayward fault ruptures. The simulations suggest that the Spudich and Chiou (2008) directivity corrections to the NGA relations could be improved by including a dependence on the rupture speed and increasing the areal extent of rupture directivity with period. The simulations also indicate that the NGA relations may under-predict amplification in shallow sedimentary basins.

  12. Unknown input observer based detection of sensor faults in a wind turbine

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2010-01-01

    In this paper an unknown input observer is designed to detect three different sensor fault scenarios in a specified bench mark model for fault detection and accommodation of wind turbines. In this paper a subset of faults is dealt with, it are faults in the rotor and generator speed sensors as we...

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

    Science.gov (United States)

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

    2016-03-01

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

  14. Induction motor inter turn fault detection using infrared thermographic analysis

    Science.gov (United States)

    Singh, Gurmeet; Anil Kumar, T. Ch.; Naikan, V. N. A.

    2016-07-01

    Induction motors are the most commonly used prime movers in industries. These are subjected to various environmental, thermal and load stresses that ultimately reduces the motor efficiency and later leads to failure. Inter turn fault is the second most commonly observed faults in the motors and is considered the most severe. It can lead to the failure of complete phase and can even cause accidents, if left undetected or untreated. This paper proposes an online and non invasive technique that uses infrared thermography, in order to detect the presence of inter turn fault in induction motor drive. Two methods have been proposed that detect the fault and estimate its severity. One method uses transient thermal monitoring during the start of motor and other applies pseudo coloring technique on infrared image of the motor, after it reaches a thermal steady state. The designed template for pseudo-coloring is in acquiescence with the InterNational Electrical Testing Association (NETA) thermographic standard. An index is proposed to assess the severity of the fault present in the motor.

  15. Evaluation of Wind Farm Controller based Fault Detection and Isolation

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Shafiei, Seyed Ehsan

    2015-01-01

    detection and isolation and fault tolerant control has previously been proposed. Based on this model, and international competition on wind farm FDI was organized. The contributions were presented at the IFAC World Congress 2014. In this paper the top three contributions to this competition are shortly...

  16. Adaptive partitioning PCA model for improving fault detection and isolation☆

    Institute of Scientific and Technical Information of China (English)

    Kangling Liu; Xin Jin; Zhengshun Fei; Jun Liang

    2015-01-01

    In chemical process, a large number of measured and manipulated variables are highly correlated. Principal com-ponent analysis (PCA) is widely applied as a dimension reduction technique for capturing strong correlation un-derlying in the process measurements. However, it is difficult for PCA based fault detection results to be interpreted physical y and to provide support for isolation. Some approaches incorporating process knowledge are developed, but the information is always shortage and deficient in practice. Therefore, this work proposes an adaptive partitioning PCA algorithm entirely based on operation data. The process feature space is partitioned into several sub-feature spaces. Constructed sub-block models can not only reflect the local behavior of process change, namely to grasp the intrinsic local information underlying the process changes, but also improve the fault detection and isolation through the combination of local fault detection results and reduction of smearing effect. The method is demonstrated in TE process, and the results show that the new method is much better in fault detection and isolation compared to conventional PCA method.

  17. Applying Parametric Fault Detection to a Mechanical System

    DEFF Research Database (Denmark)

    Felício, P.; Stoustrup, Jakob; Niemann, H.

    2002-01-01

    A way of doing parametric fault detection is described. It is based on the representation of parameter changes as linear fractional transformations (lfts). We describe a model with parametric uncertainty. Then a stabilizing controller is chosen and its robustness properties are studied via mu...

  18. Fault detection of a benchmark wind turbine using interval analysis

    DEFF Research Database (Denmark)

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

    2012-01-01

    is nonlinear. We use an effective wind speed estimator to estimate the effective wind speed and then using interval analysis and monotonicity of the aerodynamic torque with respect to the effective wind speed, we can apply the method to the nonlinear system. The fault detection algorithm checks the consistency...

  19. Fault detection for nonlinear systems - A standard problem approach

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1998-01-01

    The paper describes a general method for designing (nonlinear) fault detection and isolation (FDI) systems for nonlinear processes. For a rich class of nonlinear systems, a nonlinear FDI system can be designed using convex optimization procedures. The proposed method is a natural extension...

  20. Optimal input design for fault detection and diagnosis

    DEFF Research Database (Denmark)

    Sadegh, Payman; Madsen, Henrik; Holst, J.

    1995-01-01

    In the paper, the design of optimal input signals for detection and diagnosis in a stochastic dynamical system is investigated. The design is based on maximization of Kullback measure between the model under fault and the model under normal operation conditions. It is established that the optimal...

  1. DSP-Based Sensor Fault Detection and Post Fault-Tolerant Control of an Induction Motor-Based Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Bekheïra Tabbache

    2012-01-01

    Full Text Available This paper deals with sensor fault detection within a reconfigurable direct torque control of an induction motor-based electric vehicle. The proposed strategy concerns current, voltage, and speed sensors faults that are detected and followed by post fault-tolerant control to allow the vehicle continuous operation. The proposed approach is validated through experiments on an induction motor drive and simulations on an electric vehicle using a European urban and extraurban driving cycle.

  2. An application of LTR design in fault detection

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    1998-01-01

    as a standard Loop Transfer Recovery (LTR) design problem. As a consequence of the connection between LTR and FDI design, it is shown in an example how the LQG/LTR design method for full order and a proportional-integral observer can be applied with advantages in connection with FDI.......The fault detection and isolation (FDI) problem is considered in this paper. The FDI problem is formulated as a filter design problem, where the faults in the system is estimated and the disturbance acting on the system is rejected. It turns out that the filter design problem can be considered...

  3. Fault detection filter design for an anaerobic digestion process

    Energy Technology Data Exchange (ETDEWEB)

    Aubrun, C.; Garnier, O. [Univ. Henri Poincare - Nancy 1, Vandoeuvre (France); Harmand, J.; Steyer, J.P. [LBE-INRA, Narbonne (France)

    2000-05-01

    In this paper, a Fault Detection and Isolation observer based method has been applied to biological wastewater treatment process. The method is designed with a dynamic model and the observer is determined using the eigenstructure assignment approach. The efficiency of the method is demonstrated for both detection and isolation of an actuator and a sensor failure using experimental data from a pilot scale anaerobic digestion process for the treatment of an industrial wine distillery vinasses. (orig.)

  4. Bounding Ground Motions for Hayward Fault Scenario Earthquakes Using Suites of Stochastic Rupture Models

    Science.gov (United States)

    Rodgers, A. J.; Xie, X.; Petersson, A.

    2007-12-01

    The next major earthquake in the San Francisco Bay area is likely to occur on the Hayward-Rodgers Creek Fault system. Attention on the southern Hayward section is appropriate given the upcoming 140th anniversary of the 1868 M 7 rupture coinciding with the estimated recurrence interval. This presentation will describe ground motion simulations for large (M > 6.5) earthquakes on the Hayward Fault using a recently developed elastic finite difference code and high-performance computers at Lawrence Livermore National Laboratory. Our code easily reads the recent USGS 3D seismic velocity model of the Bay Area developed in 2005 and used for simulations of the 1906 San Francisco and 1989 Loma Prieta earthquakes. Previous work has shown that the USGS model performs very well when used to model intermediate period (4-33 seconds) ground motions from moderate (M ~ 4-5) earthquakes (Rodgers et al., 2008). Ground motions for large earthquakes are strongly controlled by the hypocenter location, spatial distribution of slip, rise time and directivity effects. These are factors that are impossible to predict in advance of a large earthquake and lead to large epistemic uncertainties in ground motion estimates for scenario earthquakes. To bound this uncertainty, we are performing suites of simulations of scenario events on the Hayward Fault using stochastic rupture models following the method of Liu et al. (Bull. Seism. Soc. Am., 96, 2118-2130, 2006). These rupture models have spatially variable slip, rupture velocity, rise time and rake constrained by characterization of inferred finite fault ruptures and expert opinion. Computed ground motions show variability due to the variability in rupture models and can be used to estimate the average and spread of ground motion measures at any particular site. This work was performed under the auspices of the U.S. Department of Energy by University of California Lawrence Livermore National Laboratory under contract No.W-7405-Eng-48. This is

  5. Ground-Motion Simulations of Scenario Earthquakes on the Hayward Fault

    Energy Technology Data Exchange (ETDEWEB)

    Aagaard, B; Graves, R; Larsen, S; Ma, S; Rodgers, A; Ponce, D; Schwartz, D; Simpson, R; Graymer, R

    2009-03-09

    We compute ground motions in the San Francisco Bay area for 35 Mw 6.7-7.2 scenario earthquake ruptures involving the Hayward fault. The modeled scenarios vary in rupture length, hypocenter, slip distribution, rupture speed, and rise time. This collaborative effort involves five modeling groups, using different wave propagation codes and domains of various sizes and resolutions, computing long-period (T > 1-2 s) or broadband (T > 0.1 s) synthetic ground motions for overlapping subsets of the suite of scenarios. The simulations incorporate 3-D geologic structure and illustrate the dramatic increase in intensity of shaking for Mw 7.05 ruptures of the entire Hayward fault compared with Mw 6.76 ruptures of the southern two-thirds of the fault. The area subjected to shaking stronger than MMI VII increases from about 10% of the San Francisco Bay urban area in the Mw 6.76 events to more than 40% of the urban area for the Mw 7.05 events. Similarly, combined rupture of the Hayward and Rodgers Creek faults in a Mw 7.2 event extends shaking stronger than MMI VII to nearly 50% of the urban area. For a given rupture length, the synthetic ground motions exhibit the greatest sensitivity to the slip distribution and location inside or near the edge of sedimentary basins. The hypocenter also exerts a strong influence on the amplitude of the shaking due to rupture directivity. The synthetic waveforms exhibit a weaker sensitivity to the rupture speed and are relatively insensitive to the rise time. The ground motions from the simulations are generally consistent with Next Generation Attenuation ground-motion prediction models but contain long-period effects, such as rupture directivity and amplification in shallow sedimentary basins that are not fully captured by the ground-motion prediction models.

  6. Sinusoidal synthesis based adaptive tracking for rotating machinery fault detection

    Science.gov (United States)

    Li, Gang; McDonald, Geoff L.; Zhao, Qing

    2017-01-01

    This paper presents a novel Sinusoidal Synthesis Based Adaptive Tracking (SSBAT) technique for vibration-based rotating machinery fault detection. The proposed SSBAT algorithm is an adaptive time series technique that makes use of both frequency and time domain information of vibration signals. Such information is incorporated in a time varying dynamic model. Signal tracking is then realized by applying adaptive sinusoidal synthesis to the vibration signal. A modified Least-Squares (LS) method is adopted to estimate the model parameters. In addition to tracking, the proposed vibration synthesis model is mainly used as a linear time-varying predictor. The health condition of the rotating machine is monitored by checking the residual between the predicted and measured signal. The SSBAT method takes advantage of the sinusoidal nature of vibration signals and transfers the nonlinear problem into a linear adaptive problem in the time domain based on a state-space realization. It has low computation burden and does not need a priori knowledge of the machine under the no-fault condition which makes the algorithm ideal for on-line fault detection. The method is validated using both numerical simulation and practical application data. Meanwhile, the fault detection results are compared with the commonly adopted autoregressive (AR) and autoregressive Minimum Entropy Deconvolution (ARMED) method to verify the feasibility and performance of the SSBAT method.

  7. Fault detection and diagnosis using neural network approaches

    Science.gov (United States)

    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.

  8. Fault Detection and Isolation (Fdi Via Neural Networks

    Directory of Open Access Journals (Sweden)

    Neeraj Prakash Srivastava,

    2014-01-01

    Full Text Available Recent approaches to fault detection and isolation for dynamic systems using methods of integrating quantitative and qualitative model information, based upon soft computing (SC methods are used. In this study, the use of SC methods is considered an important extension to the quantitative model-based approach for residual generation in FDI. When quantitative models are not readily available, a correctly trained neural network (NN can be used as a non-linear dynamic model of the system. However, the neural network does not easily provide insight into model. This main difficulty can be overcome using qualitative modeling or rule-based inference methods. The paper presents the properties of several methods of combining quantitative and qualitative system information and their practical value for fault diagnosis of Neural network. Keywords: Soft computing methods, fault-diagnosis, FDI

  9. Strong Ground Motion Evaluation for an Active Fault System by the Empirical Green Function Method

    Energy Technology Data Exchange (ETDEWEB)

    Choi, In Kil; Choun, Young Sun [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of); Shiba, Yoshiaki; Ohtori, Yasuki [Central Research Institute of Electric Power Industry, Chiba (Japan)

    2005-07-01

    In an area with a high seismic activity, a design earthquake ground motion is generally determined empirically by investigating the historical records concerning damaging events. But it is difficult in Korea to obtain such seismic records that reflect the local characteristics because of the low seismic activity. A geological survey on the active faults near the sites of nuclear power plants has been carried out recently, and the segmentation, slip rate and the latest activity of the fault system are partly revealed. It will be significant for the advanced seismic design of nuclear facilities to utilize the information derived from these geological investigations and evaluate the strong ground motions. In this study, the empirical Green's function method (EFGM) was used to simulate strong ground motions from an active fault system in Korea. The source models are assumed by using the information obtained from the geological survey and the trench investigation on the fault system. Finally, the applicability of this approach to Korea was estimated.

  10. Procedure of evaluating parameters of inland earthquakes caused by long strike-slip faults for ground motion prediction

    Science.gov (United States)

    Ju, Dianshu; Dan, Kazuo; Fujiwara, Hiroyuki; Morikawa, Nobuyuki

    2016-04-01

    We proposed a procedure of evaluating fault parameters of asperity models for predicting strong ground motions from inland earthquakes caused by long strike-slip faults. In order to obtain averaged dynamic stress drops, we adopted the formula obtained by dynamic fault rupturing simulations for surface faults of the length from 15 to 100 km, because the formula of the averaged static stress drops for circular cracks, commonly adopted in existing procedures, cannot be applied to surface faults or long faults. The averaged dynamic stress drops were estimated to be 3.4 MPa over the entire fault and 12.2 MPa on the asperities, from the data of 10 earthquakes in Japan and 13 earthquakes in other countries. The procedure has a significant feature that the average slip on the seismic faults longer than about 80 km is constant, about 300 cm. In order to validate our proposed procedure, we made a model for a 141 km long strike-slip fault by our proposed procedure for strike-slip faults, predicted ground motions, and showed that the resultant motions agreed well with the records of the 1999 Kocaeli, Turkey, earthquake (Mw 7.6) and with the peak ground accelerations and peak ground velocities by the GMPE of Si and Midorikawa (1999).

  11. Battery Fault Detection with Saturating Transformers

    Science.gov (United States)

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

    2013-01-01

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

  12. Land subsidence, Ground Fissures and Buried Faults: InSAR Monitoring of Ciudad Guzmán (Jalisco, Mexico

    Directory of Open Access Journals (Sweden)

    Carlo Alberto Brunori

    2015-07-01

    Full Text Available We study land subsidence processes and the associated ground fissuring, affecting an active graben filled by thick unconsolidated deposits by means of InSAR techniques and fieldwork. On 21 September 2012, Ciudad Guzmán (Jalisco, Mexico was struck by ground fissures of about 1.5 km of length, causing the deformation of the roads and the propagation of fissures in adjacent buildings. The field survey showed that fissures alignment is coincident with the escarpments produced on 19 September 1985, when a strong earthquake with magnitude 8.1 struck central Mexico. In order to detect and map the spatio-temporal features of the processes that led to the 2012 ground fissures, we applied InSAR multi-temporal techniques to process ENVISAT-ASAR and RADARSAT-2 satellite SAR images acquired between 2003 and 2012. We detect up to 20 mm/year of subsidence of the northwestern part of Ciudad Guzmán. These incremental movements are consistent with the ground fissures observed in 2012. Based on interferometric results, field data and 2D numerical model, we suggest that ground deformations and fissuring are due to the presence of areal subsidence correlated with variable sediment thickness and differential compaction, partly driven by the exploitation of the aquifers and controlled by the distribution and position of buried faults.

  13. Simulation of Near-Fault High-Frequency Ground Motions from the Representation Theorem

    Science.gov (United States)

    Beresnev, Igor A.

    2017-07-01

    "What is the maximum possible ground motion near an earthquake fault?" is an outstanding question of practical significance in earthquake seismology. In establishing a possible theoretical cap on extreme ground motions, the representation integral of elasticity, providing an exact, within limits of applicability, solution for fault radiation at any frequency, is an under-utilized tool. The application of a numerical procedure leading to synthetic ground displacement, velocity, and acceleration time histories to modeling of the record at the Lucerne Valley hard-rock station, uniquely located at 1.1 km from the rupture of the M w 7.2 Landers, California event, using a seismologically constrained temporal form of slip on the fault, reveals that the shape of the displacement waveform can be modeled closely, given the simplicity of the theoretical model. High precision in the double integration, as well as carefully designed smoothing and filtering, are necessary to suppress the numerical noise in the high-frequency (velocity and acceleration) synthetic motions. The precision of the integration of at least eight decimal digits ensures the numerical error in the displacement waveforms generally much lower than 0.005% and reduces the error in the peak velocities and accelerations to the levels acceptable to make the representation theorem a reliable tool in the practical evaluation of the magnitude of maximum possible ground motions in a wide-frequency range of engineering interest.

  14. Nonlinear observer based fault detection and isolation for a momentum wheel

    DEFF Research Database (Denmark)

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2001-01-01

    This article realizes nonlinear Fault Detection and Isolation for a momentum wheel. The Fault Detection and Isolation is based on a Failure Mode and Effect Analysis, which states which faults might occur and can be detected. The algorithms presented in this paper are based on a geometric approach...... toachieve nonlinear Fault Detection and Isolation. The proposed algorithms are tested in a simulation study and the pros and cons of the algorithm are discussed....

  15. PCB Fault Detection Using Image Processing

    Science.gov (United States)

    Nayak, Jithendra P. R.; Anitha, K.; Parameshachari, B. D., Dr.; Banu, Reshma, Dr.; Rashmi, P.

    2017-08-01

    The importance of the Printed Circuit Board inspection process has been magnified by requirements of the modern manufacturing environment where delivery of 100% defect free PCBs is the expectation. To meet such expectations, identifying various defects and their types becomes the first step. In this PCB inspection system the inspection algorithm mainly focuses on the defect detection using the natural images. Many practical issues like tilt of the images, bad light conditions, height at which images are taken etc. are to be considered to ensure good quality of the image which can then be used for defect detection. Printed circuit board (PCB) fabrication is a multidisciplinary process, and etching is the most critical part in the PCB manufacturing process. The main objective of Etching process is to remove the exposed unwanted copper other than the required circuit pattern. In order to minimize scrap caused by the wrongly etched PCB panel, inspection has to be done in early stage. However, all of the inspections are done after the etching process where any defective PCB found is no longer useful and is simply thrown away. Since etching process costs 0% of the entire PCB fabrication, it is uneconomical to simply discard the defective PCBs. In this paper a method to identify the defects in natural PCB images and associated practical issues are addressed using Software tools and some of the major types of single layer PCB defects are Pattern Cut, Pin hole, Pattern Short, Nick etc., Therefore the defects should be identified before the etching process so that the PCB would be reprocessed. In the present approach expected to improve the efficiency of the system in detecting the defects even in low quality images

  16. The Response of Long-Span Bridges to Low Frequency, Near-Fault Earthquake Ground Motions

    Energy Technology Data Exchange (ETDEWEB)

    McCallen, David; Astaneh-Asl, A.; Larsen, S.C.; Hutchings, Larry

    2009-02-27

    Historical seismic hazard characterizations did not include earthquake ground motion waveforms at frequencies below approximately 0.2 Hz (5 seconds period). This resulted from limitations in early strong motion instrumentation and signal processing techniques, a lack of measurements in the near-field of major earthquakes and therefore no observational awareness, and a delayed understanding in the engineering community of the potential significance of these types of motions. In recent years, there is a growing recognition of the relevance of near-fault, low frequency motions, particularly for long-period structures such as large bridges. This paper describes a computationally based study of the effects of low frequency (long-period) near-fault motions on long-span bridge response. The importance of inclusion of these types of motions for long span cable supported bridges is demonstrated using actual measured broad-band, near-fault motions from large earthquakes.

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

    Science.gov (United States)

    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

  18. Nonlinear observer based fault detection and isolation for a momentum wheel

    DEFF Research Database (Denmark)

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2001-01-01

    This article realizes nonlinear Fault Detection and Isolation for a momentum wheel. The Fault Detection and Isolation is based on a Failure Mode and Effect Analysis, which states which faults might occur and can be detected. The algorithms presented in this paper are based on a geometric approach...

  19. Analysis of ground fault current distribution along nonuniform multi-section lines

    Energy Technology Data Exchange (ETDEWEB)

    Buccheri, P.L.; Mangione, S. [Department of Electrical, Electronic and Telecommunication Engineering, Universita degli Studi di Palermo, Viale delle Scienze, 90128 Palermo (Italy)

    2008-09-15

    In case of a substation supplied by a combined overhead-cable line, most of the ground fault current flows through the cable sheaths and discharges into the soil surrounding the point of discontinuity, where cables are connected to the overhead line. In the paper a new method is presented for computing the ground fault current distribution in case of feeding line consisting of two or more different sections, i.e. part overhead and part underground cable. Besides the calculation of the earth current at the fault location, the leakage current at the transit/transition stations as well as at the overhead line towers can be evaluated, in order to ensure proper safety conditions. Based on the two-port theory, the method allows to take into account all the relevant conductively and inductively coupled parameters which take part to the fault current distribution. A computer program based on the proposed method has been developed and some application examples are reported. (author)

  20. Faults

    Data.gov (United States)

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

  1. Ultimate Strength of Fixed Offshore Platforms Subjected to Near-Fault Earthquake Ground Vibration

    OpenAIRE

    Hesam Sharifian; Khosro Bargi; Mohamad Zarrin

    2015-01-01

    The pile foundation nonlinearity and its influence on the ultimate capacity of fixed platforms have not comprehensively been covered by previous researchers. In this study, the seismic behavior and capacity of a newly designed and installed Jacket Type Offshore Platform (JTOP) located in the Persian Gulf is investigated by conducting Incremental Dynamic Analysis (IDA) using a suit of near-fault ground motions. Additionally, two modified models of the original platform are created by slightly ...

  2. Digital electronic engine control fault detection and accommodation flight evaluation

    Science.gov (United States)

    Baer-Ruedhart, J. L.

    1984-01-01

    The capabilities and performance of various fault detection and accommodation (FDA) schemes in existing and projected engine control systems were investigated. Flight tests of the digital electronic engine control (DEEC) in an F-15 aircraft show discrepancies between flight results and predictions based on simulation and altitude testing. The FDA methodology and logic in the DEEC system, and the results of the flight failures which occurred to date are described.

  3. Automatic fault detection on BIPV systems without solar irradiation data

    CERN Document Server

    Leloux, Jonathan; Luna, Alberto; Desportes, Adrien

    2014-01-01

    BIPV systems are small PV generation units spread out over the territory, and whose characteristics are very diverse. This makes difficult a cost-effective procedure for monitoring, fault detection, performance analyses, operation and maintenance. As a result, many problems affecting BIPV systems go undetected. In order to carry out effective automatic fault detection procedures, we need a performance indicator that is reliable and that can be applied on many PV systems at a very low cost. The existing approaches for analyzing the performance of PV systems are often based on the Performance Ratio (PR), whose accuracy depends on good solar irradiation data, which in turn can be very difficult to obtain or cost-prohibitive for the BIPV owner. We present an alternative fault detection procedure based on a performance indicator that can be constructed on the sole basis of the energy production data measured at the BIPV systems. This procedure does not require the input of operating conditions data, such as solar ...

  4. Ground Motions in the Near Field of the November 3, 2002 Denali Fault, Alaska, Earthquake

    Science.gov (United States)

    Ellsworth, W. L.; Celebi, M.; Evans, J. R.; Jensen, E. G.; Metz, M. C.; Nyman, D. J.; Roddick, J. W.; Stephens, C. D.; Spudich, P. A.

    2003-12-01

    A free-field strong-motion recording of the Denali Fault, Alaska, Earthquake was obtained by Alyeska Pipeline Service Company just 3 km from where the Denali Fault slipped over 5 m horizontally and 1 m vertically in the earthquake. The instrument was part of the monitoring and control system for the Trans-Alaska Pipeline and was located at Pump Station 10, approximately 84 km east of the epicenter. After correction for a 0.1 Hz high-pass filter, we recover a fault-parallel permanent displacement of the instrument of 2.3 m. Dynamic ground motions during the earthquake have relatively low acceleration (0.39 g) and very high velocity (1.86 m/s). The most intense motions occurred during a 1.5 s interval generated by the propagation of the rupture front past the site. Growth of the fault-parallel displacement is nearly monotonic, with over half of the permanent displacement occurring during this 1.5 s interval. Preliminary modeling suggests that the rupture velocity exceeded the shear wave velocity near the instrument, and that the peak slip velocity on the fault exceeds several m/s. The low accelerations and high velocities observed near the fault in this earthquake agree with observations from other recent large-magnitude earthquakes. Following the earthquake, the permanent displacement of the support structure for the pipeline and other geodetic reference points was determined by GPS survey along more than 50 miles of the pipeline route. These permanent displacement data display a clear signature of elastic rebound, with displacement amplitudes decreasing with increasing distance from the fault trace. The best-fitting model consisting of a uniform dislocation in an elastic half-space has 6 m of right-lateral fault slip from the surface to a depth of 11 km. This model predicts 2.4 m of displacement at Pump Station 10, in good agreement with the strong motion displacement measurement. At the fault crossing, additional displacements were determined from orthographically

  5. Sliding mode fault detection and fault-tolerant control of smart dampers in semi-active control of building structures

    Science.gov (United States)

    Yeganeh Fallah, Arash; Taghikhany, Touraj

    2015-12-01

    Recent decades have witnessed much interest in the application of active and semi-active control strategies for seismic protection of civil infrastructures. However, the reliability of these systems is still in doubt as there remains the possibility of malfunctioning of their critical components (i.e. actuators and sensors) during an earthquake. This paper focuses on the application of the sliding mode method due to the inherent robustness of its fault detection observer and fault-tolerant control. The robust sliding mode observer estimates the state of the system and reconstructs the actuators’ faults which are used for calculating a fault distribution matrix. Then the fault-tolerant sliding mode controller reconfigures itself by the fault distribution matrix and accommodates the fault effect on the system. Numerical simulation of a three-story structure with magneto-rheological dampers demonstrates the effectiveness of the proposed fault-tolerant control system. It was shown that the fault-tolerant control system maintains the performance of the structure at an acceptable level in the post-fault case.

  6. Fuzzy-Expert Diagnostics for Detecting and Locating Internal Faults in Three Phase Induction Motors

    Institute of Scientific and Technical Information of China (English)

    DONG Mingchui; CHEANG Takson; SEKAR Booma Devi; CHAN Sileong

    2008-01-01

    Internal faults in three phase induction motors can result in serious performance degradation and eventual system failures if not properly detected and treated in time. Artificial intelligence techniques, the core of soft-computing, have numerous advantages over conventional fault diagnostic approaches; therefore, a soft-computing system was developed to detect and diagnose electric motor faults. The fault diagnostic system for three-phase induction motors samples the fault symptoms and then uses a fuzzy-expert forward inference model to identify the fault. This paper describes how to define the membership functions and fuzzy sets based on the fault symptoms and how to construct the hierarchical fuzzy inference nets with the propagation of probabilities concerning the uncertainty of faults. The designed hierarchical fuzzy inference nets efficiently detect and diagnose the fault type and exact location in a three phase induction motor. The validity and effectiveness of this approach is clearly shown from obtained testing results.

  7. Bearing Fault Detection Using Artificial Neural Networks and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Samanta B

    2004-01-01

    Full Text Available A study is presented to compare the performance of bearing fault detection using three types of artificial neural networks (ANNs, namely, multilayer perceptron (MLP, radial basis function (RBF network, and probabilistic neural network (PNN. The time domain vibration signals of a rotating machine with normal and defective bearings are processed for feature extraction. The extracted features from original and preprocessed signals are used as inputs to all three ANN classifiers: MLP, RBF, and PNN for two-class (normal or fault recognition. The characteristic parameters like number of nodes in the hidden layer of MLP and the width of RBF, in case of RBF and PNN along with the selection of input features, are optimized using genetic algorithms (GA. For each trial, the ANNs are trained with a subset of the experimental data for known machine conditions. The ANNs are tested using the remaining set of data. The procedure is illustrated using the experimental vibration data of a rotating machine with and without bearing faults. The results show the relative effectiveness of three classifiers in detection of the bearing condition.

  8. Method for detecting an open-switch fault in a grid-connected NPC inverter system

    DEFF Research Database (Denmark)

    Choi, Ui-Min; Jeong, Hae-Gwang; Lee, Kyo-Beum;

    2012-01-01

    This paper proposes a fault-detection method for an open-switch fault in the switches of grid-connected neutral-point-clamped inverter systems. The proposed method can not only detect the fault condition but also identify the location of the faulty switch. In the proposed method, which is designed...

  9. Fault detection and accommodation via neural network and variable structure control

    Institute of Scientific and Technical Information of China (English)

    Hao YANG; Bin JIANG

    2007-01-01

    This paper proposes a novel idea that classifies faults into two different kinds: serious faults and small faults,and treats them with different strategies respectively. A kind of artificial neural network (ANN) is proposed for detecting serious faults, and variable structure (VS) model-following control is constructed for accommodating small faults. The proposed framework takes both advantages of qualitative way and quantitative way of fault detection and accommodation.Moreover, the uncertainty case is investigated and the VS controller is modified. Simulation results of a remotely piloted aircraft with control actuator failures illustrate the performance of the developed algorithm.

  10. Potential of Electrical Resistivity Tomography to Detect Fault Zones in Limestone and Argillaceous Formations in the Experimental Platform of Tournemire, France

    Science.gov (United States)

    Gélis, C.; Revil, A.; Cushing, M. E.; Jougnot, D.; Lemeille, F.; Cabrera, J.; de Hoyos, A.; Rocher, M.

    2010-11-01

    The Experimental platform of Tournemire (Aveyron, France) developed by IRSN (French Institute for Radiological Protection and Nuclear Safety) is located in a tunnel excavated in a clay-rock formation interbedded between two limestone formations. A well-identified regional fault crosscuts this subhorizontal sedimentary succession, and a subvertical secondary fault zone is intercepted in the clay-rock by drifts and boreholes in the tunnel at a depth of about 250 m. A 2D electrical resistivity survey was carried out along a 2.5 km baseline, and a takeout of 40 m was used to assess the potential of this method to detect faults from the ground surface. In the 300 m-thick zone investigated by the survey, electrical resistivity images reveal several subvertical low-resistivity discontinuities. One of these discontinuities corresponds to the position of the Cernon fault, a major regional fault. One of the subvertical conductive discontinuities crossing the upper limestone formation is consistent with the prolongation towards the ground surface of the secondary fault zone identified in the clay-rock formation from the tunnel. Moreover, this secondary fault zone corresponds to the upward prolongation of a subvertical fault identified in the lower limestone using a 3D high-resolution seismic reflection survey. This type of large-scale electrical resistivity survey is therefore a useful tool for identifying faults in superficial layers from the ground surface and is complementary to 3D seismic reflection surveys.

  11. A New Method of Ground Fault Location in 2 × 25 kV Railway Power Supply Systems

    Directory of Open Access Journals (Sweden)

    Jesús Serrano

    2017-03-01

    Full Text Available Owing to the installation of autotransformers at regular intervals along the line, distance protection relays cannot be used with the aim of locating ground faults in 2 × 25 kV railway power supply systems. The reason is that the ratio between impedance and distance to the fault point is not linear in these electrification systems, unlike in 1 × 25 kV power systems. Therefore, the location of ground faults represents a complicated task in 2 × 25 kV railway power supply systems. Various methods have been used to localize the ground fault position in 2 × 25 kV systems. The method described here allows the location of a ground fault to be economically found in an accurate way in real time, using the modules of the circulating currents in different autotransformers when the ground fault occurs. This method first needs to know the subsection and the conductor (catenary or feeder with the defect, then localizes the ground fault’s position.

  12. Fault and meal detection by redundant continuous glucose monitors and the unscented Kalman filter

    DEFF Research Database (Denmark)

    Mahmoudi, Zeinab; Nørgaard, Kirsten; Poulsen, Niels Kjølstad

    2017-01-01

    The purpose of this study is to develop a method for detecting and compensating the anomalies of continuous glucose monitoring (CGM) sensors as well as detecting unannounced meals. Both features, sensor fault detection/correction and meal detection, are necessary to have a reliable artificial...... is in terms of a patient simulation model, where the model in the detector is the same as the patient simulation model used for evaluation of the detector. The detection module consists of two CGM sensors, two fault detectors, a fault isolator, and an adaptive unscented Kalman filter (UKF). Two types...... of sensor faults, i.e., drift and pressure induced sensor attenuation (PISA), are simulated by a Gaussian random walk model. Each of the fault detectors has a local UKF that receives the signal from the associated sensor, detects faults, and finally tunes the adaptive UKF. A fault isolator that accepts data...

  13. Synthetic seismograms of ground motion near earthquake fault using simulated Green's function method

    Institute of Scientific and Technical Information of China (English)

    ZHAO Zhixin; ZHAO Zhao; XU Jiren; Ryuji Kubota

    2006-01-01

    Seismograms near source fault were synthesized using the hybrid empirical Green's function method where he discretely simulated seismic waveforms are used for Green's functions instead of the observed waveforms of small earthquakes. The Green's function seismic waveforms for small earthquake were calculated by solving wave equation using the pseudo-spectral method with the staggered grid real FFT strategy under a detailed 2-D velocity structure in Kobe region. Magnitude and seismic moment of simulated Green's function waveforms were firstly determined by using the relationship between fault length and corner frequency of source spectrum. The simulated Green's function waveforms were employed to synthesize seismograms of strong ground motion near the earthquake fault. The synthetic seismograms of the target earthquake were performed based on the model with multiple source rupture processes. The results suggest that synthesized seismograms coincide well with observed seismic waveforms of the 1995 Hyogo-ken Nanbu earthquake. The simulated Green's function method is very useful for prediction of the strong ground motion in region without observed seismic waveforms.The present technique spreads application field of the empirical Green's function method.

  14. Impact of SSSC on Measured Impedance in Single Phase to Ground Fault Condition on 220 kV Transmission Line

    Directory of Open Access Journals (Sweden)

    Mohamed ZELLAGUI

    2012-08-01

    Full Text Available This paper presents and compares the impact of SSSC on measured impedance for single phase to ground fault condition. The presence of Static Synchronous SSSC on a transmission line has a great influence on the ZRelay in distance protection. The protection of the high voltage 220 kV single circuit transmission line in eastern Algerian electrical transmission networks is affected in the case with resistance fault RF. The paper investigate the effect of Static Synchronous Series Compensator (SSSC on the measured impedance (Relay taking into account the distance fault point (n and fault resistance (RF. The resultants simulation is performed in MATLAB software environment.

  15. Fault Diagnosis for Actuators in a Class of Nonlinear Systems Based on an Adaptive Fault Detection Observer

    Directory of Open Access Journals (Sweden)

    Runxia Guo

    2016-01-01

    Full Text Available The problem of actuators’ fault diagnosis is pursued for a class of nonlinear control systems that are affected by bounded measurement noise and external disturbances. A novel fault diagnosis algorithm has been proposed by combining the idea of adaptive control theory and the approach of fault detection observer. The asymptotical stability of the fault detection observer is guaranteed by setting the adaptive adjusting law of the unknown fault vector. A theoretically rigorous proof of asymptotical stability has been given. Under the condition that random measurement noise generated by the sensors of control systems and external disturbances exist simultaneously, the designed fault diagnosis algorithm is able to successfully give specific estimated values of state variables and failures rather than just giving a simple fault warning. Moreover, the proposed algorithm is very simple and concise and is easy to be applied to practical engineering. Numerical experiments are carried out to evaluate the performance of the fault diagnosis algorithm. Experimental results show that the proposed diagnostic strategy has a satisfactory estimation effect.

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

    Directory of Open Access Journals (Sweden)

    Wonhee Lee

    2014-02-01

    Full Text Available 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.

  17. Latest Progress of Fault Detection and Localization in Complex Electrical Engineering

    Science.gov (United States)

    Zhao, Zheng; Wang, Can; Zhang, Yagang; Sun, Yi

    2014-01-01

    In the researches of complex electrical engineering, efficient fault detection and localization schemes are essential to quickly detect and locate faults so that appropriate and timely corrective mitigating and maintenance actions can be taken. In this paper, under the current measurement precision of PMU, we will put forward a new type of fault detection and localization technology based on fault factor feature extraction. Lots of simulating experiments indicate that, although there are disturbances of white Gaussian stochastic noise, based on fault factor feature extraction principal, the fault detection and localization results are still accurate and reliable, which also identifies that the fault detection and localization technology has strong anti-interference ability and great redundancy.

  18. Delineating Concealed Faults within Cogdell Oil Field via Earthquake Detection

    Science.gov (United States)

    Aiken, C.; Walter, J. I.; Brudzinski, M.; Skoumal, R.; Savvaidis, A.; Frohlich, C.; Borgfeldt, T.; Dotray, P.

    2016-12-01

    Cogdell oil field, located within the Permian Basin of western Texas, has experienced several earthquakes ranging from magnitude 1.7 to 4.6, most of which were recorded since 2006. Using the Earthscope USArray, Gan and Frohlich [2013] relocated some of these events and found a positive correlation in the timing of increased earthquake activity and increased CO2 injection volume. However, focal depths of these earthquakes are unknown due to 70 km station spacing of the USArray. Accurate focal depths as well as new detections can delineate subsurface faults and establish whether earthquakes are occurring in the shallow sediments or in the deeper basement. To delineate subsurface fault(s) in this region, we first detect earthquakes not currently listed in the USGS catalog by applying continuous waveform-template matching algorithms to multiple seismic data sets. We utilize seismic data spanning the time frame of 2006 to 2016 - which includes data from the U.S. Geological Survey Global Seismographic Network, the USArray, and the Sweetwater, TX broadband and nodal array located 20-40 km away. The catalog of earthquakes enhanced by template matching reveals events that were well recorded by the large-N Sweetwater array, so we are experimenting with strategies for optimizing template matching using different configurations of many stations. Since earthquake activity in the Cogdell oil field is on-going (a magnitude 2.6 occurred on May 29, 2016), a temporary deployment of TexNet seismometers has been planned for the immediate vicinity of Cogdell oil field in August 2016. Results on focal depths and detection of small magnitude events are pending this small local network deployment.

  19. Spatial Based Integrated Assessment of Bedrock and Ground Motions, Fault Offsets, and Their Effects for the October-November 2002 Earthquake Sequence on the Denali Fault, Alaska

    Science.gov (United States)

    Vinson, T. S.; Carlson, R.; Hansen, R.; Hulsey, L.; Ma, J.; White, D.; Barnes, D.; Shur, Y.

    2003-12-01

    A National Science Foundation (NSF) Small Grant Exploratory Research Grant was awarded to the University of Alaska Fairbanks to archive bedrock and ground motions and fault offsets and their effects for the October-November 2002 earthquake sequence on the Denali Fault, Alaska. The scope of work included the accumulation of all strong motion records, satellite imagery, satellite remote sensing data, aerial and ground photographs, and structural response (both measured and anecdotal) that would be useful to achieve the objective. Several interesting data sets were archived including ice cover, lateral movement of stream channels, landslides, avalanches, glacial fracturing, "felt" ground motions, and changes in water quantity and quality. The data sources may be spatially integrated to provide a comprehensive assessment of the bedrock and ground motions and fault offsets for the October-November 2002 earthquake sequence. In the aftermath of the October-November 2002 earthquake sequence on the Denali fault, the Alaskan engineering community expressed a strong interest to understand why their structures and infrastructure were not substantially damaged by the ground motions they experienced during the October-November 2002 Earthquake Sequence on the Denali Fault. The research work proposed under this NSF Grant is a necessary prerequisite to this understanding. Furthermore, the proposed work will facilitate a comparison of Denali events with the Loma Prieta and recent Kocelli and Dozce events in Turkey, all of which were associated with strike-slip faulting. Finally, the spatially integrated data will provide the basis for research work that is truly innovative. For example, is may be possible to predict the observed (1) landsliding and avalanches, (2) changes in water quantity and quality, (3) glacial fracturing, and (4) the widespread liquefaction and lateral spreading, which occurred along the Tok cutoff and Northway airport, with the bedrock and ground motions and

  20. Robust Nonlinear Analytic Redundancy for Fault Detection and Isolation in Mobile Robot

    Institute of Scientific and Technical Information of China (English)

    Bibhrajit Halder; Nilanjan Sarkar

    2007-01-01

    A robust nonlinear analytical redundancy (RNLAR) technique is presented to detect and isolate actuator and sensor faults in a mobile robot. Both model-plant-mismatch (MPM) and process disturbance are considered during fault detection. The RNLAR is used to design primary residual vectors (PRV), which are highly sensitive to the faults and less sensitive to MPM and process disturbance, for sensor and actuator fault detection. The PRVs are then transformed into a set of structured residual vectors (SRV) for fault isolation. Experimental results on a Pioneer 3-DX mobile robot are presented to justify the effectiveness of the RNLAR scheme.

  1. Source Rupture Process and Near-Fault Ground Motions of the 2016 Kumamoto Earthquake Sequence Estimated from Strong Motion Data

    Science.gov (United States)

    Asano, K.; Iwata, T.

    2016-12-01

    The 2016 Kumamoto earthquake sequence started with an MJMA 6.5 foreshock on April 14, 2016 occurring along the northern part of the Hinagu fault, central Kyushu, Japan, and the MJMA 7.3 mainshock occurred just 28 h after the foreshock. Both events brought severe ground motions to the near-source region. We analyzed the kinematic source rupture processes of the foreshock and mainshock by the multiple time window linear waveform inversion using strong motion data (e.g., Hartzell and Heaton, 1983). The foreshock (Mw 6.1) was characterized by right-lateral strike-slip occurring on a nearly vertical fault plane along the northern part of the Hinagu fault, and it had two large-slip areas: one near the hypocenter and another at a shallow depth. These two large-slip areas mainly contribute ground motions in the near-source area. For the analysis of the mainshock, we assumed a fault geometry changing strike and dip angles along the Hinagu and Futagawa faults in accordance with the surface ruptures mapped by emergency field surveys (Kumahara et al., 2016). We assigned point sources densely with an interval of 0.2 km on the assumed fault planes in order to reproduce appropriately near-fault ground motions, and estimated spatiotemporal slip history, which was discretized with an interval of 1.8 km on the fault planes. The estimated source model reveals that the rupture of the mainshock started at a northwest-dipping fault plane along the Hinagu fault, which is close to the vertical fault plane of the foreshock, and almost continuously propagated across the junction of the Hinagu and Futagawa faults. Then the rupture propagated northeastward along the Futagawa fault, and stopped to rupture in the western part of the Aso caldera. The significant slip with 3-5 m were observed on the Futagawa fault, and shallowest part has slip ranging from 1 to 2 m. We also tried to reproduce ground motions observed at some near-fault strong motion stations, which recorded significant coseismic

  2. Fault detection and isolation of sensors in aeration control systems.

    Science.gov (United States)

    Carlsson, Bengt; Zambrano, Jesús

    2016-01-01

    In this paper, we consider the problem of fault detection (FD) and isolation in the aeration system of an activated sludge process. For this study, the dissolved oxygen in each aerated zone is assumed to be controlled automatically. As the basis for an FD method we use the ratio of air flow rates into different zones. The method is evaluated in two scenarios: using the Benchmark Simulation Model no. 1 (BSM1) by Monte Carlo simulations and using data from a wastewater treatment plant. The FD method shows good results for a correct and early FD and isolation.

  3. IMPROVING SOLUTIONS OF EQUIPMENT’S RELIABILITY FOR DETECTION OF GROUNDING LINES

    Directory of Open Access Journals (Sweden)

    PĂCUREANU I.

    2015-12-01

    Full Text Available The paper has three parts, in the first one, is presented the theoretical concepts that refer on the grounding lines fault, the treating mode, and implemented solutions for their detection in electric stations. In the second part is presented the result of the operational reliability analyse in period of 2011 – 2015, as in the final part of the paper are given the conclusions and identified solutions regarding the improving of operational reliability of the protection equipment of detection of grounding lines.

  4. Internal Leakage Fault Detection and Tolerant Control of Single-Rod Hydraulic Actuators

    Directory of Open Access Journals (Sweden)

    Jianyong Yao

    2014-01-01

    Full Text Available The integration of internal leakage fault detection and tolerant control for single-rod hydraulic actuators is present in this paper. Fault detection is a potential technique to provide efficient condition monitoring and/or preventive maintenance, and fault tolerant control is a critical method to improve the safety and reliability of hydraulic servo systems. Based on quadratic Lyapunov functions, a performance-oriented fault detection method is proposed, which has a simple structure and is prone to implement in practice. The main feature is that, when a prescribed performance index is satisfied (even a slight fault has occurred, there is no fault alarmed; otherwise (i.e., a severe fault has occurred, the fault is detected and then a fault tolerant controller is activated. The proposed tolerant controller, which is based on the parameter adaptive methodology, is also prone to realize, and the learning mechanism is simple since only the internal leakage is considered in parameter adaptation and thus the persistent exciting (PE condition is easily satisfied. After the activation of the fault tolerant controller, the control performance is gradually recovered. Simulation results on a hydraulic servo system with both abrupt and incipient internal leakage fault demonstrate the effectiveness of the proposed fault detection and tolerant control method.

  5. Hazard-consistent ground motions generated with a stochastic fault-rupture model

    Energy Technology Data Exchange (ETDEWEB)

    Nishida, Akemi, E-mail: nishida.akemi@jaea.go.jp [Center for Computational Science and e-Systems, Japan Atomic Energy Agency, 178-4-4, Wakashiba, Kashiwa, Chiba 277-0871 (Japan); Igarashi, Sayaka, E-mail: igrsyk00@pub.taisei.co.jp [Technology Center, Taisei Corporation, 344-1 Nase-cho, Totsuka-ku, Yokohama 245-0051 (Japan); Sakamoto, Shigehiro, E-mail: shigehiro.sakamoto@sakura.taisei.co.jp [Technology Center, Taisei Corporation, 344-1 Nase-cho, Totsuka-ku, Yokohama 245-0051 (Japan); Uchiyama, Yasuo, E-mail: yasuo.uchiyama@sakura.taisei.co.jp [Technology Center, Taisei Corporation, 344-1 Nase-cho, Totsuka-ku, Yokohama 245-0051 (Japan); Yamamoto, Yu, E-mail: ymmyu-00@pub.taisei.co.jp [Technology Center, Taisei Corporation, 344-1 Nase-cho, Totsuka-ku, Yokohama 245-0051 (Japan); Muramatsu, Ken, E-mail: kmuramat@tcu.ac.jp [Department of Nuclear Safety Engineering, Tokyo City University, 1-28-1 Tamazutsumi, Setagaya-ku, Tokyo 158-8557 (Japan); Takada, Tsuyoshi, E-mail: takada@load.arch.t.u-tokyo.ac.jp [Department of Architecture, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

    2015-12-15

    obtain these acceleration deviations. A similar tendency can be found for some other seismic-source characteristics, meaning that ground motions obtained in this study cannot be generated by simulations of deterministic fault-rupture models with averaged seismic-source characteristics. Generated ground motions incorporate differences between each seismic-source characteristic, and they are effectively available for PRAs of structures.

  6. Evidence for ground-rupturing earthquakes on the Northern Wadi Araba fault at the archaeological site of Qasr Tilah, Dead Sea Transform fault system, Jordan

    Science.gov (United States)

    Haynes, Jeremy M.; Niemi, Tina M.; Atallah, Mohammad

    2006-10-01

    The archaeological site of Qasr Tilah, in the Wadi Araba, Jordan is located on the northern Wadi Araba fault segment of the Dead Sea Transform. The site contains a Roman-period fort, a late Byzantine Early Umayyad birkeh (water reservoir) and aqueduct, and agricultural fields. The birkeh and aqueduct are left-laterally offset by coseismic slip across the northern Wadi Araba fault. Using paleoseismic and archaeological evidence collected from a trench excavated across the fault zone, we identified evidence for four ground-rupturing earthquakes. Radiocarbon dating from key stratigraphic horizons and relative dating using potsherds constrains the dates of the four earthquakes from the sixth to the nineteenth centuries. Individual earthquakes were dated to the seventh, ninth and eleventh centuries. The fault strand that slipped during the most recent event (MRE) extends to just below the modern ground surface and juxtaposes alluvial-fan sediments that lack in datable material with the modern ground surface, thus preventing us from dating the MRE except to constrain the event to post-eleventh century. These data suggest that the historical earthquakes of 634 or 659/660, 873, 1068, and 1546 probably ruptured this fault segment.

  7. Truffes Detection Using Ground Penetration Radar

    Directory of Open Access Journals (Sweden)

    Ali Aydın

    2015-12-01

    Full Text Available Honaz Mountain (Denizli-SW Turkey has a mild and humid climate and it produces a rich flora in the area. As a natural consequence thereof, the study area offers a rich mushroom potential that is a rising economic value. In recent years, Ground Penetration Radar (GPR is a relatively modern and effective and widely utilized technique for shallow subsurface exploration. GPR with 250 Hz antenna was employed to trace the tubers in Honaz Mountain area. To elucidate how the mushroom can reflect the signals, mineral composition of the mushrooms has been analysed. Percentage of K, Na, Ca, Mg, Fe, Al, P, S, Si, Cl minerals were significantly different from that of earth. This difference in element composition seems to cause the reflection of the signals. A large number of mushroom grooving areas have been detected during the study. The observed GPR data have been confirmed by the physical excavation. The study proposes that this method can be effectively employed to detect the natural mushrooms in the ground.

  8. Near fault broadband ground motion simulation with empirical Green's functions: the Upper Rhine Graben case study

    Science.gov (United States)

    Del Gaudio, Sergio; Hok, Sébastian; Causse, Mathieu; Festa, Gaetano; Lancieri, Maria

    2016-04-01

    A fundamental stage in seismic hazard assessment is the prediction of realistic ground motion for potential future earthquakes. To do so, one of the steps is to make an estimation of the expected ground motion level and this is commonly done by the use of ground motion prediction equations (GMPEs). Nevertheless GMPEs do not represent the whole variety of source processes and this can lead to incorrect estimates for some specific case studies, such as in the near-fault range because of the lack of records of large earthquakes at short distances. In such cases, ground motion simulations can be a valid tool to complement prediction equations for scenario studies, provided that both source and propagation are accurately described and uncertainties properly addressed. Such simulations, usually referred to as "blind", require the generation of a population of ground motion records that represent the natural variability of the source process for the target earthquake scenario. In this study we performed simulations using the empirical Green's function technique, which consists in using records of small earthquakes as the medium transfer function provided the availability of small earthquakes located close to the target fault and recorded at the target site. The main advantage of this technique is that it does not require a detailed knowledge of the propagation medium, which is not always possible, but requires availability of high quality records of small earthquakes in the target area. We couple this empirical approach with a k-2 kinematic source model, which naturally let us to introduce high frequency in the source description. Here we present an application of our technique to the Upper Rhine Graben. This is an active seismic region with a moderate rate of seismicity and for which it is interesting to provide ground motion estimation in the vicinity of the faults to be compared with estimations traditionally provided by GMPEs in a seismic hazard evaluation study. We

  9. The influence of faulting on ground movement due to coalmining: the UK and European experience

    Energy Technology Data Exchange (ETDEWEB)

    Heltewell, E.G.

    1988-01-01

    It has been recognised from the time of the earliest investigations into coal mining subsidence that geological faults can play a significant role in determining the nature of ground movement resulting from coal extraction. However, the limited research undertaken on this aspect has been spasmodic yet wide ranging and has resulted in the findings being published in diverse sources. The paper summarises the evidence and conclusions of observers in the UK and Europe and therefore reveals the present state of knowledge in this aspect of coal mining subsidence. 18 refs., 2 figs.

  10. Detecting Hidden Faults and Other Lineations with UAVSAR

    Science.gov (United States)

    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

  11. DPHM: A FAULT DETECTION PROTOCOL BASED ON HEARTBEAT OF MULTIPLE MASTER-NODES

    Institute of Scientific and Technical Information of China (English)

    Dong Jian; Zuo Decheng; Liu Hongwei; Yang Xiaozong

    2007-01-01

    In most of fault detection algorithms of distributed system, fault model is restricted to fault of process, and link failure is simply masked, or modeled by process failure. Both methods can soon use up system resource and potentially reduce the availability of system. A fault Detection Protocol based on Heartbeat of multiple Master-nodes (DPHM) is proposed, which can immediately and accurately detect and locate faulty links by adopting voting and electing mechanism among master-nodes. Thus,DPHM can effectively improve availability of system. In addition, in contrast with other detection protocols, DPHM reduces greatly the detection cost due to the structure of master-nodes.

  12. Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.

    Science.gov (United States)

    Abbaspour, Alireza; Aboutalebi, Payam; Yen, Kang K; Sargolzaei, Arman

    2017-03-01

    A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies.

  13. FSN-based fault modelling for fault detection and troubleshooting in CANDU stations

    Energy Technology Data Exchange (ETDEWEB)

    Nasimi, E., E-mail: elnara.nasimi@brucepower.com [Bruce Power LLP., Tiverton, Ontario(Canada); Gabbar, H.A. [Univ. of Ontario Inst. of Tech., Oshawa, Ontario (Canada)

    2013-07-01

    An accurate fault modeling and troubleshooting methodology is required to aid in making risk-informed decisions related to design and operational activities of current and future generation of CANDU designs. This paper presents fault modeling approach using Fault Semantic Network (FSN) methodology with risk estimation. Its application is demonstrated using a case study of Bruce B zone-control level oscillations. (author)

  14. Active Fault Detection and Isolation for Hybrid Systems

    DEFF Research Database (Denmark)

    Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas

    2009-01-01

    An algorithm for active fault detection and isolation is proposed. In order to observe the failure hidden due to the normal operation of the controllers or the systems, an optimization problem based on minimization of test signal is used. The optimization based method imposes the normal and fault...... to the two tank bench mark example in presence of two faults....

  15. Fault Detection and Isolation for a Supermarket Refrigeration System - Part One

    DEFF Research Database (Denmark)

    Yang, Zhenyu; Rasmussen, Karsten B.; Kieu, Anh T.

    2011-01-01

    Fault Detection and Isolation (FDI) using the Kalman Filter (KF) technique for a supermarket refrigeration system is explored. Four types of sensor fault scenarios, namely drift, offset, freeze and hard-over, are considered for two temperature sensors, and one type of parametric fault scenario...

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

    Directory of Open Access Journals (Sweden)

    B. S. Anami

    2013-06-01

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

  17. Fault Detection and Isolation Using Analytical Redundancy Relations for the Ship Propulsion Benchmark

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh

    The prime objective of Fault-tolerant Control (FTC) systems is to handle faults and discrepancies using appropriate accommodation policies. The issue of obtaining information about various parameters and signals, which have to be monitored for fault detection purposes, becomes a rigorous task wit...... is illustrated on the ship propulsion benchmark....

  18. Application of fractal theory in detecting low current faults of power distribution system in coal mines

    Institute of Scientific and Technical Information of China (English)

    LIU Jian-hua; LIANG Rui; WANG Chong-lin; FAN Di-peng

    2009-01-01

    Single-phase low current grounding faults areoften seen in power distribution system of coal mines. These faults are difficult to reliably identify. We propose a new method of single-phase ground fault protection based upon a discernible matrix of the fractal dimension associated with line currents. The method builds on existing selective protection methods. Faulted feeders are distinguished using differences in the zero-sequence transient current fractal dimension. The current signals were first processed through a fast Fourier transform and then the characteristics of a faulted line were identified using a discernible matrix. The method of calculation is illustrated. The results show that the method involves simple calculations, is easy to do and is highly accurate. It is, therefore, suitable for distribution networks having different neutral grounding modes.

  19. Fault Detection and Correction for the Solar Dynamics Observatory Attitude Control System

    Science.gov (United States)

    Starin, Scott R.; Vess, Melissa F.; Kenney, Thomas M.; Maldonado, Manuel D.; Morgenstern, Wendy M.

    2007-01-01

    The Solar Dynamics Observatory is an Explorer-class mission that will launch in early 2009. The spacecraft will operate in a geosynchronous orbit, sending data 24 hours a day to a devoted ground station in White Sands, New Mexico. It will carry a suite of instruments designed to observe the Sun in multiple wavelengths at unprecedented resolution. The Atmospheric Imaging Assembly includes four telescopes with focal plane CCDs that can image the full solar disk in four different visible wavelengths. The Extreme-ultraviolet Variability Experiment will collect time-correlated data on the activity of the Sun's corona. The Helioseismic and Magnetic Imager will enable study of pressure waves moving through the body of the Sun. The attitude control system on Solar Dynamics Observatory is responsible for four main phases of activity. The physical safety of the spacecraft after separation must be guaranteed. Fine attitude determination and control must be sufficient for instrument calibration maneuvers. The mission science mode requires 2-arcsecond control according to error signals provided by guide telescopes on the Atmospheric Imaging Assembly, one of the three instruments to be carried. Lastly, accurate execution of linear and angular momentum changes to the spacecraft must be provided for momentum management and orbit maintenance. In thsp aper, single-fault tolerant fault detection and correction of the Solar Dynamics Observatory attitude control system is described. The attitude control hardware suite for the mission is catalogued, with special attention to redundancy at the hardware level. Four reaction wheels are used where any three are satisfactory. Four pairs of redundant thrusters are employed for orbit change maneuvers and momentum management. Three two-axis gyroscopes provide full redundancy for rate sensing. A digital Sun sensor and two autonomous star trackers provide two-out-of-three redundancy for fine attitude determination. The use of software to maximize

  20. Stochastic Resonance algorithms to enhance damage detection in bearing faults

    Directory of Open Access Journals (Sweden)

    Castiglione Roberto

    2015-01-01

    Full Text Available Stochastic Resonance is a phenomenon, studied and mainly exploited in telecommunication, which permits the amplification and detection of weak signals by the assistance of noise. The first papers on this technique are dated early 80 s and were developed to explain the periodically recurrent ice ages. Other applications mainly concern neuroscience, biology, medicine and obviously signal analysis and processing. Recently, some researchers have applied the technique for detecting faults in mechanical systems and bearings. In this paper, we try to better understand the conditions of applicability and which is the best algorithm to be adopted for these purposes. In fact, to get the methodology profitable and efficient to enhance the signal spikes due to fault in rings and balls/rollers of bearings, some parameters have to be properly selected. This is a problem since in system identification this procedure should be as blind as possible. Two algorithms are analysed: the first exploits classical SR with three parameters mutually dependent, while the other uses Woods-Saxon potential, with three parameters yet but holding a different meaning. The comparison of the performances of the two algorithms and the optimal choice of their parameters are the scopes of this paper. Algorithms are tested on simulated and experimental data showing an evident capacity of increasing the signal to noise ratio.

  1. Fault detection in processes represented by PLS models using an EWMA control scheme

    KAUST Repository

    Harrou, Fouzi

    2016-10-20

    Fault detection is important for effective and safe process operation. Partial least squares (PLS) has been used successfully in fault detection for multivariate processes with highly correlated variables. However, the conventional PLS-based detection metrics, such as the Hotelling\\'s T and the Q statistics are not well suited to detect small faults because they only use information about the process in the most recent observation. Exponentially weighed moving average (EWMA), however, has been shown to be more sensitive to small shifts in the mean of process variables. In this paper, a PLS-based EWMA fault detection method is proposed for monitoring processes represented by PLS models. The performance of the proposed method is compared with that of the traditional PLS-based fault detection method through a simulated example involving various fault scenarios that could be encountered in real processes. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS method.

  2. RESEARCH ON EXPERT SYSTEM OF FAULT DETECTION AND DIAGNOSING FOR PNEUMATIC SYSTEM OF AUTOMATIC PRODUCTION LINE

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Fault detection and diagnosis for pneumatic system of automatic production line are studied. An expert system using fuzzy-neural network and pneumatic circuit fault diagnosis instrument are designed. The mathematical model of various pneumatic faults and experimental device are built. In the end, some experiments are done, which shows that the expert system using fuzzy-neural network can diagnose fast and truly fault of pneumatic circuit.

  3. Thermal mapping: the hydrothermal system of a volcano used to map faults and palaeostructures within stratified ground. The Yasur-Yenkahe volcanic complex (Vanuatu)

    Science.gov (United States)

    Amin Douillet, Guilhem; Peltier, Aline; Finizola, Anthony; Brothelande, Elodie; Garaebiti, Esline

    2014-05-01

    Subsurface thermal measurements provide a valuable tool to map hydrothermal-fluid release zones in activevolcanic areas. On explosive volcanoes, where ash fall layers deposit parallel to the ground surface, hydrothermal fluids are trapped in the stratification due to the variations in permeability in deposits of the different explosive phases. Thermal fluids thus travel parallel to the surface close to the ground. This horizontal flux can only escape when faults break the seals of stratification. On the Yasur-Yenkahe volcanic complex (Tanna Island, Vanuatu archipelago), fumaroles andhot springs abound, signs of upraising heat fluxes associated to a well-developed hydrothermal activity. Combinationof high resolution mapping of ground thermal anomalies with geomorphological analysis allows thecharacterization of the structural relationships between the active Yasur volcano and the Yenkahe resurgent dome. A complex system of heat release and hydrothermal fluid circulation below the Yasur-Yenkahe complex isevidenced. Circulation, though propagating vertically as a whole, is funneled by stratification. Thus, the main thermal fluid release is almost exclusively concentrated along structural limits that break the seals inducedby the stratified nature of the ground. Three types of medium/high temperature anomalies have beenevidenced: (1) broad hydrothermalized areas linked with planar stratification that favor lateral spreading,(2) linear segments that represent active faults, and (3) arcuate segments related to paleo-crater rims. Thelimit between the Yasur volcano and the Yenkahe resurgent dome is characterized by an active fault systemaccommodating both the rapid uplift of the Yenkahe block and the overloading induced by the volcanoweight. In such a setting, faults converge below the cone of Yasur, which acts as a focus for the faults. Evidenceof such structures, sometimes hidden in the landscape but detected by thermal measurements, iscritical for risk assessment of

  4. Fault Detection, Isolation, and Accommodation for LTI Systems Based on GIMC Structure

    Directory of Open Access Journals (Sweden)

    D. U. Campos-Delgado

    2008-01-01

    Full Text Available In this contribution, an active fault-tolerant scheme that achieves fault detection, isolation, and accommodation is developed for LTI systems. Faults and perturbations are considered as additive signals that modify the state or output equations. The accommodation scheme is based on the generalized internal model control architecture recently proposed for fault-tolerant control. In order to improve the performance after a fault, the compensation is considered in two steps according with a fault detection and isolation algorithm. After a fault scenario is detected, a general fault compensator is activated. Finally, once the fault is isolated, a specific compensator is introduced. In this setup, multiple faults could be treated simultaneously since their effect is additive. Design strategies for a nominal condition and under model uncertainty are presented in the paper. In addition, performance indices are also introduced to evaluate the resulting fault-tolerant scheme for detection, isolation, and accommodation. Hard thresholds are suggested for detection and isolation purposes, meanwhile, adaptive ones are considered under model uncertainty to reduce the conservativeness. A complete simulation evaluation is carried out for a DC motor setup.

  5. Faults detection approach using PCA and SOM algorithm in PMSG-WT system

    Directory of Open Access Journals (Sweden)

    Mohamed Lamine FADDA

    2016-07-01

    Full Text Available In this paper, a new approach for faults detection in observable data system wind turbine - permanent magnet synchronous generator (WT-PMSG, the studying objective, illustrate the combination (SOM-PCA to build Multi-local-PCA models faults detection in system (WT-PMSG, the performance of the method suggested to faults detection in system data, finding good results in simulation experiment.

  6. Study on Fault Detection and PCB Picture-Location Method of Logic Circuit

    Directory of Open Access Journals (Sweden)

    Mingping Xia

    2013-05-01

    Full Text Available The main content of logic circuit fault detection includes describing circuit to be diagnosed, determining fault and circuit initial information, generating circuit location test set. In this study, LASAR is used to carry out the logic circuit simulation so as to create such documents as fault dictionary, node truth value table, etc. for the preparation of fault detection. Due to the limitation of circuit observability and testing vectors, the diagnosis program can not accurately locate the fault just once in the process of diagnosis because the circuit is complex and users are not quite familiarity with the circuit. Therefore, the new circuit-fault-detection technology incorporates techniques of PCB picture-location so that the users can locate the fault quickly and accurately.

  7. Ground penetrating radar for asparagus detection

    Science.gov (United States)

    Seyfried, Daniel; Schoebel, Joerg

    2016-03-01

    Ground penetrating radar is a promising technique for detection of buried objects. Recently, radar has more and more been identified to provide benefits for a plurality of applications, where it can increase efficiency of operation. One of these fields is the industrial automatic harvesting process of asparagus, which is performed so far by cutting the soil ridge at a certain height including all the asparagus spears and subsequently sieving the latter out of the soil. However, the height where the soil is cut is a critical parameter, since a wrong value leads to either damage of the roots of the asparagus plants or to a reduced crop yield as a consequence of too much biomass remaining in the soil. In this paper we present a new approach which utilizes ground penetrating radar for non-invasive sensing in order to obtain information on the optimal height for cutting the soil. Hence, asparagus spears of maximal length can be obtained, while keeping the roots at the same time undamaged. We describe our radar system as well as the subsequent digital signal processing steps utilized for extracting the information required from the recorded radar data, which then can be fed into some harvesting unit for setting up the optimal cutting height.

  8. Fault Detection in Complex Distribution Network Based on Hilbert-Huang Transform

    Directory of Open Access Journals (Sweden)

    Zhongjian Kang

    2013-01-01

    Full Text Available Traditional distribution network fault location methods often cannot be effectively applied for the structure of the branch in complex distribution network. A new accurate fault location for the single-phase-ground fault in complex distribution network with structure of the branch based on Hilbert-Huang transform was proposed in this paper. First, the distribution network was modeled. The faults on each branch were simulated. The energy characteristics under the branch in a particular frequency band were identified by HHT. Then these energy characteristics were used to train artificial neural networks (ANN.When the energy characteristics of actual fault are inputted, the trained neural network can output the malfunction branch. When the fault branch was determined, using the online fault feature matching method, combined with the genetic algorithm, the precise determination of the distance to fault location in the fault branch can be completed. With combinations of signal processing-Hilbert-Huang transform, artificial neural network and genetic algorithm, the entirely new method was proposed to deal with the problem of fault location in distribution network in this article. The results showed that the method has a good precision and apply to the small current grounding system.

  9. A Novel Arc Fault Detector for Early Detection of Electrical Fires

    Directory of Open Access Journals (Sweden)

    Kai Yang

    2016-04-01

    Full Text Available Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires.

  10. A new private communication scheme based on the idea of fault detection and identification

    Energy Technology Data Exchange (ETDEWEB)

    Chen Maoyin [Department of Automation, Tsinghua University, Beijing 100084 (China)]. E-mail: maoyinchen@163.com; Zhou Donghua [Department of Automation, Tsinghua University, Beijing 100084 (China); Shang Yun [College of Mathematics and Information Science, Shaanxi Normal University, Xi' an 710062 (China)

    2006-02-27

    By use of the idea of fault detection and identification, this Letter proposes a new scheme to resolve the problem of chaotic private communication. From the point of view of fault detection and identification the scalar message signal hidden in the chaotic systems can be regarded as the component fault signal, thereby it can be detected and recovered using the model-based methods of fault detection and identification. The famous Duffing oscillator is used to illustrate and verify the effectiveness of this scheme.

  11. Discrete wavelet transform-based fault diagnosis for driving system of pipeline detection robot arm

    Institute of Scientific and Technical Information of China (English)

    Deng Huiyu; Wang Xinli; Ma Peisun

    2005-01-01

    A real-time wavelet multi-resolution analysis (MRA)-based fault detection algorithm is proposed. The first stage detailed MRA signals extracted from the original signals were used as the criteria for fault detection. By measuring sharp variations in the detailed MRA signals, faults in the motor driving system of pipeline detection robot arm could be detected. The fault type was then identified by comparison of the three-phase MRA sharp variations. The effects of the faults were examined. The simulation results show that this algorithm is effective and robust, it is promising for fault detection in a robot's joint driving system. The method is simple, rapid and it can operate in real time.

  12. Design of H(infinity) robust fault detection filter for linear uncertain time-delay systems.

    Science.gov (United States)

    Bai, Leishi; Tian, Zuohua; Shi, Songjiao

    2006-10-01

    In this paper, the robust fault detection filter design problem for linear time-delay systems with both unknown inputs and parameter uncertainties is studied. Using a multiobjective optimization technique, a new performance index is introduced, which takes into account the robustness of the fault detection filter against disturbances and sensitivity to faults simultaneously. The reference residual model is then designed based on this performance index to formulate the robust fault detection filter design problem as an H(infinity) model-matching problem. By applying robust H(infinity) optimization control technique, the existence condition of the robust fault detection filter for linear time-delay systems with both unknown inputs and parameter uncertainties is presented in terms of linear matrix inequality formulation, independently of time delay. In order to detect the fault, an adaptive threshold which depends on the inputs is finally determined. An illustrative design example is used to demonstrate the validity of the proposed approach.

  13. A Component Based Approach to Industrial Fault Detection and Accommodation

    DEFF Research Database (Denmark)

    Blanke, M.

    1996-01-01

    This paper presents a new method for design of fault handling as a supervisory part of a control system.......This paper presents a new method for design of fault handling as a supervisory part of a control system....

  14. Industrial Actuator Benchmark for Fault Detection and Isolation

    DEFF Research Database (Denmark)

    Blanke, M.; Patton, R.J.

    1995-01-01

    Feedback control systems are vulnerable to faults within the control loop, because feedback actions may cause abrupt responses and......Feedback control systems are vulnerable to faults within the control loop, because feedback actions may cause abrupt responses and...

  15. Modeling, Detection, and Disambiguation of Sensor Faults for Aerospace Applications

    Data.gov (United States)

    National Aeronautics and Space Administration — Sensor faults continue to be a major hurdle for sys- tems health management to reach its full potential. At the same time, few recorded instances of sensor faults...

  16. Near-fault ground motions with prominent acceleration pulses: pulse characteristics and ductility demand

    Institute of Scientific and Technical Information of China (English)

    Mai Tong; Vladimir Rzhevsky; Dai Junwu; George C Lee; Qi Jincheng; Qi Xiaozhai

    2007-01-01

    Major earthquakes of last 15 years (e.g., Northridge 1994, Kobe 1995 and Chi-Chi 1999) have shown that many near-fault ground motions possess prominent acceleration pulses. Some of the prominent ground acceleration pulses are related to large ground velocity pulses, others are caused by mechanisms that are totally different from those causing the velocity pulses or fling steps. Various efforts to model acceleration pulses have been reported in the literature. In this paper, research results from a recent study of acceleration pulse prominent ground motions and an analysis of structural damage induced by acceleration pulses are summarized. The main results of the study include: (1) temporal characteristics of acceleration pulses; (2) ductility demand spectrum of simple acceleration pulses with respect to equivalent classes of dynamic systems and pulse characteristic parameters; and (3) estimation of fundamental period change under the excitation of strong acceleration pulses. By using the acceleration pulse induced linear acceleration spectrum and the ductility demand spectrum,a simple procedure has been developed to estimate the ductility demand and the fundamental period change of a reinforced concrete (RC) structure under the impact of a strong acceleration pulse.

  17. Evaluation of fault-normal/fault-parallel directions rotated ground motions for response history analysis of an instrumented six-story building

    Science.gov (United States)

    Kalkan, Erol; Kwong, Neal S.

    2012-01-01

    According to regulatory building codes in United States (for example, 2010 California Building Code), at least two horizontal ground-motion components are required for three-dimensional (3D) response history analysis (RHA) of buildings. For sites within 5 km of an active fault, these records should be rotated to fault-normal/fault-parallel (FN/FP) directions, and two RHA analyses should be performed separately (when FN and then FP are aligned with the transverse direction of the structural axes). It is assumed that this approach will lead to two sets of responses that envelope the range of possible responses over all nonredundant rotation angles. This assumption is examined here using a 3D computer model of a six-story reinforced-concrete instrumented building subjected to an ensemble of bidirectional near-fault ground motions. Peak responses of engineering demand parameters (EDPs) were obtained for rotation angles ranging from 0° through 180° for evaluating the FN/FP directions. It is demonstrated that rotating ground motions to FN/FP directions (1) does not always lead to the maximum responses over all angles, (2) does not always envelope the range of possible responses, and (3) does not provide maximum responses for all EDPs simultaneously even if it provides a maximum response for a specific EDP.

  18. Distributed Fault Detection Based on Credibility and Cooperation for WSNs in Smart Grids.

    Science.gov (United States)

    Shao, Sujie; Guo, Shaoyong; Qiu, Xuesong

    2017-04-28

    Due to the increasingly important role in monitoring and data collection that sensors play, accurate and timely fault detection is a key issue for wireless sensor networks (WSNs) in smart grids. This paper presents a novel distributed fault detection mechanism for WSNs based on credibility and cooperation. Firstly, a reasonable credibility model of a sensor is established to identify any suspicious status of the sensor according to its own temporal data correlation. Based on the credibility model, the suspicious sensor is then chosen to launch fault diagnosis requests. Secondly, the sending time of fault diagnosis request is discussed to avoid the transmission overhead brought about by unnecessary diagnosis requests and improve the efficiency of fault detection based on neighbor cooperation. The diagnosis reply of a neighbor sensor is analyzed according to its own status. Finally, to further improve the accuracy of fault detection, the diagnosis results of neighbors are divided into several classifications to judge the fault status of the sensors which launch the fault diagnosis requests. Simulation results show that this novel mechanism can achieve high fault detection ratio with a small number of fault diagnoses and low data congestion probability.

  19. Detection of Partial Demagnetization Fault in PMSMs Operating under Nonstationary Conditions

    DEFF Research Database (Denmark)

    Wang, Chao; Delgado Prieto, Miguel; Romeral, Luis

    2016-01-01

    Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold-Kalman F......Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold......-Kalman Filter is proposed to detect the partial demagnetization fault in PMSMs running at nonstationary conditions. Amplitude of envelope of the fault characteristic orders is used as fault indictor. Experimental results verify the superiority of the proposed method on partial demagnetization online fault...... detection of PMSMs under various speed and load conditions....

  20. Kinematic source model for simulation of near-fault ground motion field using explicit finite element method

    Institute of Scientific and Technical Information of China (English)

    Zhang Xiaozhi; Hu Jinjun; Xie Lili; Wang Haiyun

    2006-01-01

    This paper briefly reviews the characteristics and major processes of the explicit finite element method in modeling the near-fault ground motion field. The emphasis is on the finite element-related problems in the finite fault source modeling. A modified kinematic source model is presented, in which vibration with some high frequency components is introduced into the traditional slip time function to ensure that the source and ground motion include sufficient high frequency components. The model presented is verified through a simple modeling example. It is shown that the predicted near-fault ground motion field exhibits similar characteristics to those observed in strong motion records, such as the hanging wall effect, vertical effect, fling step effect and velocity pulse effect, etc.

  1. Thrust faulting and 3D ground deformation of the 3 July 2015 Mw 6.4 Pishan, China earthquake from Sentinel-1A radar interferometry

    Science.gov (United States)

    Sun, Jianbao; Shen, Zheng-Kang; Li, Tao; Chen, Jie

    2016-06-01

    Boosted by the launch of Sentinel-1A radar satellite from the European Space Agency (ESA), we now have the opportunity of fast, full and multiple coverage of the land based deformation field of earthquakes. Here we use the data to investigate a strong earthquake struck Pishan, western China on July 3, 2015. The earthquake fault is blind and no ground break features are found on-site, thus Synthetic Aperture Radar (SAR) data give full play to its technical advantage for the recovery of coseismic deformation field. By using the Sentinel-1A radar data in the Interferometric Wide Swath mode, we obtain 3 tracks of InSAR data over the struck region, and resolve the 3D ground deformation generated by the earthquake. Then the Line-of-Sight (LOS) InSAR data are inverted for the slip-distribution of the seismogenic fault. The final model shows that the earthquake is completely blind with pure-thrust motion. The maximum slip is 0.48 m at a depth of 7 km, consistent with the depth estimate from seismic reflection data. In particular, the inverted model is also compatible with a south-dipping fault ramp among a group of fault interfaces detected by the seismic reflection profile over the region. The seismic moment obtained equals to a Mw 6.4 earthquake. The Pishan earthquake ruptured the frontal part of the thrust ramps under the Slik anticline, and unloaded the coulomb stress of them. However, it may have loaded stress to the back-thrust above the thrust ramps by 1-4 bar, and promoted it for future failure. Moreover, the stress loading on the west side of the earthquake fault is much larger than that on the east side, indicating a higher risk for failure to the west of the Zepu fault.

  2. Nonlinear Statistical Process Monitoring and Fault Detection Using Kernel ICA

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xi; YAN Wei-wu; ZHAO Xu; SHAO Hui-he

    2007-01-01

    A novel nonlinear process monitoring and fault detection method based on kernel independent component analysis (ICA) is proposed. The kernel ICA method is a two-phase algorithm: whitened kernel principal component (KPCA) plus ICA. KPCA spheres data and makes the data structure become as linearly separable as possible by virtue of an implicit nonlinear mapping determined by kernel. ICA seeks the projection directions in the KPCA whitened space, making the distribution of the projected data as non-gaussian as possible. The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed process monitoring method based on kernel ICA can effectively capture the nonlinear relationship in process variables. Its performance significantly outperforms monitoring method based on ICA or KPCA.

  3. Anomaly Detection for Next-Generation Space Launch Ground Operations

    Science.gov (United States)

    Spirkovska, Lilly; Iverson, David L.; Hall, David R.; Taylor, William M.; Patterson-Hine, Ann; Brown, Barbara; Ferrell, Bob A.; Waterman, Robert D.

    2010-01-01

    NASA is developing new capabilities that will enable future human exploration missions while reducing mission risk and cost. The Fault Detection, Isolation, and Recovery (FDIR) project aims to demonstrate the utility of integrated vehicle health management (IVHM) tools in the domain of ground support equipment (GSE) to be used for the next generation launch vehicles. In addition to demonstrating the utility of IVHM tools for GSE, FDIR aims to mature promising tools for use on future missions and document the level of effort - and hence cost - required to implement an application with each selected tool. One of the FDIR capabilities is anomaly detection, i.e., detecting off-nominal behavior. The tool we selected for this task uses a data-driven approach. Unlike rule-based and model-based systems that require manual extraction of system knowledge, data-driven systems take a radically different approach to reasoning. At the basic level, they start with data that represent nominal functioning of the system and automatically learn expected system behavior. The behavior is encoded in a knowledge base that represents "in-family" system operations. During real-time system monitoring or during post-flight analysis, incoming data is compared to that nominal system operating behavior knowledge base; a distance representing deviation from nominal is computed, providing a measure of how far "out of family" current behavior is. We describe the selected tool for FDIR anomaly detection - Inductive Monitoring System (IMS), how it fits into the FDIR architecture, the operations concept for the GSE anomaly monitoring, and some preliminary results of applying IMS to a Space Shuttle GSE anomaly.

  4. On Line Current Monitoring and Application of a Residual Method for Eccentricity Fault Detection

    Directory of Open Access Journals (Sweden)

    METATLA, A.

    2011-02-01

    Full Text Available This work concerns the monitoring and diagnosis of faults in induction motors. We develop an approach based on residual analysis of stator currents to detect and diagnose faults eccentricity static, dynamic and mixed in three phase induction motor. To simulate the behavior of motor failure, a model is proposed based on the approach of magnetically coupled coils. The simulation results show the importance of the approach applied for the detection and diagnosis of fault in three phase induction motor.

  5. Fault detection and diagnosis in a food pasteurization process with Hidden Markov Models

    OpenAIRE

    Tokatlı, Figen; Cinar, Ali

    2004-01-01

    Hidden Markov Models (HMM) are used to detect abnormal operation of dynamic processes and diagnose sensor and actuator faults. The method is illustrated by monitoring the operation of a pasteurization plant and diagnosing causes of abnormal operation. Process data collected under the influence of faults of different magnitude and duration in sensors and actuators are used to illustrate the use of HMM in the detection and diagnosis of process faults. Case studies with experimental data from a ...

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

    DEFF Research Database (Denmark)

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

    1998-01-01

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

  7. Actuator Fault Detection for Sampled-Data Systems in H∞ Setting

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-jun; WENG Zheng-xin; TIAN Zuo-hua

    2005-01-01

    Actuator fault detection for sampled-data systems was investigated from the viewpoint of jump systems.With the aid of a prior frequency information on fault, such a problem is converted to an augmented H∞ filtering problem. A simple state-space approach is then proposed todeal with sampled-data actuator fault detection problem. Compared with the existed approaches, the proposed approach allows parameters of the sampled-data system being time-varying with consideration of measurement noise.

  8. Wavelet Based Fault Detection, Classification in Transmission System with TCSC Controllers

    Directory of Open Access Journals (Sweden)

    G.Satyanarayana,

    2015-08-01

    Full Text Available This paper presents simulation results of the application of distance relays for the protection of transmission systems employing flexible alternating current transmission controllers such as Thyristor Controlled Series Capacitor (TCSC. The complete digital simulation of TCSC within a transmission system is performed in the MATLAB/Simulink environment using the Power System Block set (PSB. This paper presents an efficient method based on wavelet transforms both fault detection and classification which is almost independent of fault impedance, fault location and fault inception angle of transmission line fault currents with FACTS controllers.

  9. A Survey on Distributed Filtering and Fault Detection for Sensor Networks

    Directory of Open Access Journals (Sweden)

    Hongli Dong

    2014-01-01

    Full Text Available In recent years, theoretical and practical research on large-scale networked systems has gained an increasing attention from multiple disciplines including engineering, computer science, and mathematics. Lying in the core part of the area are the distributed estimation and fault detection problems that have recently been attracting growing research interests. In particular, an urgent need has arisen to understand the effects of distributed information structures on filtering and fault detection in sensor networks. In this paper, a bibliographical review is provided on distributed filtering and fault detection problems over sensor networks. The algorithms employed to study the distributed filtering and detection problems are categorised and then discussed. In addition, some recent advances on distributed detection problems for faulty sensors and fault events are also summarized in great detail. Finally, we conclude the paper by outlining future research challenges for distributed filtering and fault detection for sensor networks.

  10. A New Fault-tolerant Switched Reluctance Motor with reliable fault detection capability

    DEFF Research Database (Denmark)

    Lu, Kaiyuan

    2014-01-01

    while no extra search coil is actually needed. The motor itself is able to continue to work under any faulted conditions, providing fault-tolerant features. The working principle, performance evaluation of this motor will be demonstrated in this paper and Finite Element Analysis results are provided....

  11. New algorithm to detect modules in a fault tree for a PSA

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Woo Sik [Sejong University, Seoul (Korea, Republic of)

    2015-05-15

    A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This paper presents a new linear time algorithm to detect modules of large fault trees. The size of cut sets can be substantially reduced by replacing independent subtrees in a fault tree with super-components. Chatterjee and Birnbaum developed properties of modules, and demonstrated their use in the fault tree analysis. Locks expanded the concept of modules to non-coherent fault trees. Independent subtrees were manually identified while coding a fault tree for computer analysis. However, nowadays, the independent subtrees are automatically identified by the fault tree solver. A Dutuit and Rauzy (DR) algorithm to detect modules of a fault tree for coherent or non-coherent fault tree was proposed in 1996. It has been well known that this algorithm quickly detects modules since it is a linear time algorithm. The new algorithm minimizes computational memory and quickly detects modules. Furthermore, it can be easily implemented into industry fault tree solvers that are based on traditional Boolean algebra, binary decision diagrams (BDDs), or Zero-suppressed BDDs. The new algorithm employs only two scalar variables in Eqs. to that are volatile information. After finishing the traversal and module detection of each node, the volatile information is destroyed. Thus, the new algorithm does not employ any other additional computational memory and operations. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.

  12. Broadband Strong Ground Motion Simulation For a Potential Mw 7.1 Earthquake on The Enriquillo Fault in Haiti

    Science.gov (United States)

    Douilly, R.; Mavroeidis, G. P.; Calais, E.

    2015-12-01

    The devastating 2010 Haiti earthquake showed the need to be more vigilant toward mitigation for future earthquakes in the region. Previous studies have shown that this earthquake did not occur on the Enriquillo Fault, the main plate boundary fault running through the heavily populated Port-au-Prince region, but on the nearby and previously unknown Léogâne transpressional fault. Slip on that fault has increased stresses on the Enriquillo Fault mostly in the region closer to Port-au-Prince, the most populated city of the country. Here we investigate the ground shaking level in this region if a rupture similar to the Mw 7.0 2010 Haiti earthquake occurred on the Enriquillo fault. We use a finite element method and assumptions on regional stress to simulate low frequency dynamic rupture propagation for a 53 km long segment. We introduce some heterogeneity by creating two slip patches with shear traction 10% greater than the initial shear traction on the fault. The final slip distribution is similar in distribution and magnitude to previous finite fault inversions for the 2010 Haiti earthquake. The high-frequency ground motion components are calculated using the specific barrier model, and the hybrid synthetics are obtained by combining the low-frequencies (f 1Hz) from the stochastic simulation using matched filtering at a crossover frequency of 1 Hz. The average horizontal peak ground acceleration, computed at several sites of interest through Port-au-Prince, has a value of 0.35g. We also compute response spectra at those sites and compare them to the spectra from the microzonation study.

  13. Fault reactivation and ground uplift assessment at a prospective German CO2 storage site

    Science.gov (United States)

    Röhmann, Lina; Tillner, Elena; Kempka, Thomas; Magri, Fabien; Kühn, Michael

    2013-04-01

    The geological storage of CO2 in deep saline aquifers is seen as a promising measure for reducing anthropogenic greenhouse gas emissions into the atmosphere. However, generally large-scale pressure build-up as a result of CO2 injection may impact the mechanical behaviour of reservoir, caprock and existing faults. Caprock fracturing, ground uplift, reactivation of faults or induced seismicity are inherent risks that may pose potential health, security and environmental hazards. Within the frame of the present study we investigated the geomechanical response of a deep saline aquifer and the surrounding rocks to CO2 storage at a prospective German CO2 storage site by coupled hydromechanical simulations. Changes in the initial stress field due to pressure build-up as a result of CO2 injection allow assessment of potential fault reactivation and magnitude of ground uplift. For this purpose, a 3D geological structural model covering an area of about 100 km x 100 km in the southeastern part of the State of Brandenburg was implemented. In a first step, stratigraphic contour lines and major fault lines were digitised based on the GeotIS online cartography of the Northeast German Basin as well as geological maps of the German State of Brandenburg, using the Petrel software package [1-3]. The 3D regional-scale model comprises several stratigraphic units down to the Zechstein. Afterwards, a stratigraphic correlation, depth adjustment and thickness correction of the different units were performed based on existing borehole data from the study area. Borehole and literature data were further used for model parameterisation. Subsequently, the model was gridded in Petrel and transferred into the reservoir simulator TOUGH2-MP to perform large-scale numerical multi-phase multi-component (CO2, NaCl, H2O) flow simulations. Furthermore, the gridded model was applied in the geomechanical simulator FLAC3D to identify changes in the recent stress field and deformation resulting from the

  14. Robust Fault Detection for a Class of Uncertain Nonlinear Systems Based on Multiobjective Optimization

    Directory of Open Access Journals (Sweden)

    Bingyong Yan

    2015-01-01

    Full Text Available A robust fault detection scheme for a class of nonlinear systems with uncertainty is proposed. The proposed approach utilizes robust control theory and parameter optimization algorithm to design the gain matrix of fault tracking approximator (FTA for fault detection. The gain matrix of FTA is designed to minimize the effects of system uncertainty on residual signals while maximizing the effects of system faults on residual signals. The design of the gain matrix of FTA takes into account the robustness of residual signals to system uncertainty and sensitivity of residual signals to system faults simultaneously, which leads to a multiobjective optimization problem. Then, the detectability of system faults is rigorously analyzed by investigating the threshold of residual signals. Finally, simulation results are provided to show the validity and applicability of the proposed approach.

  15. Minimum Error Entropy Filter for Fault Detection of Networked Control Systems

    OpenAIRE

    Guolian Hou; Mifeng Ren; Lilong Du; Jianhua Zhang

    2012-01-01

    In this paper, fault detection of networked control systems with random delays, packet dropout and noises is studied. The filter is designed using a minimum error entropy criterion. The residual generated by the filter is then evaluated to detect faults in networked control systems. An illustrative networked control system is used to verify the effectiveness of the proposed approach.

  16. Minimum Error Entropy Filter for Fault Detection of Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Guolian Hou

    2012-03-01

    Full Text Available In this paper, fault detection of networked control systems with random delays, packet dropout and noises is studied. The filter is designed using a minimum error entropy criterion. The residual generated by the filter is then evaluated to detect faults in networked control systems. An illustrative networked control system is used to verify the effectiveness of the proposed approach.

  17. Wind Turbine Fault Detection based on Artificial Neural Network Analysis of SCADA Data

    DEFF Research Database (Denmark)

    Herp, Jürgen; S. Nadimi, Esmaeil

    2015-01-01

    Slowly developing faults in wind turbine can, when not detected and fixed on time, cause severe damage and downtime. We are proposing a fault detection method based on Artificial Neural Networks (ANN) and the recordings from Supervisory Control and Data Acquisition (SCADA) systems installed in wind...

  18. The Way of Reducing Current Values in Optical Ground Wires at Asymmetrical Faults on Overhead Transmission Lines

    Directory of Open Access Journals (Sweden)

    Egamnazarov Georgiy

    2016-12-01

    Full Text Available Given the fact that the installing costs of an optical ground wire on overhead lines directly depend on its cross-section, which in turn depends on the level of fault current it should withstand, in order to reduce these current values in the optical ground wire, I suggested performing its isolated descents from the end towers of the line with its transition to an optical cable. The research was carried out on the example of a 500 kV overhead line in the National Electric Power Grid. The Method of Symmetrical Components for calculating asymmetrical fault currents was not used; therefore, calculations were carried out on the base of presenting the line as a multi-wire system for the considered case as a five-wire system (optical ground wire, steel ground wire, and three phase wires. Such approach allows taking into account the initial asymmetry of the line parameters and modeling any kind of asymmetrical faults. The analyses of calculated results were performed. The conclusive evidence that the optical ground wire isolated descents from the end towers of the line give the possibility of reducing the level of maximal fault current distribution values in it and therefore its cross section, is presented.

  19. Intelligent Fault Diagnosis in a Power Distribution Network

    Directory of Open Access Journals (Sweden)

    Oluleke O. Babayomi

    2016-01-01

    Full Text Available This paper presents a novel method of fault diagnosis by the use of fuzzy logic and neural network-based techniques for electric power fault detection, classification, and location in a power distribution network. A real network was used as a case study. The ten different types of line faults including single line-to-ground, line-to-line, double line-to-ground, and three-phase faults were investigated. The designed system has 89% accuracy for fault type identification. It also has 93% accuracy for fault location. The results indicate that the proposed technique is effective in detecting, classifying, and locating low impedance faults.

  20. Real-time fault detection method based on belief rule base for aircraft navigation system

    Institute of Scientific and Technical Information of China (English)

    Zhao Xin; Wang Shicheng; Zhang Jinsheng; Fan Zhiliang; Min Haibo

    2013-01-01

    Real-time and accurate fault detection is essential to enhance the aircraft navigation system's reliability and safety.The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults.On account of this reason,we propose an online detection solution based on non-analytical model.In this article,the navigation system fault detection model is established based on belief rule base (BRB),where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output.To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update,a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization (EM) algorithm.Furthermore,the proposed method is verified by navigation experiment.Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model.The output of the detection model can track the fault state very well,and the faults can be diagnosed in real time and accurately.In addition,the detection ability,especially in the probability of false detection,is superior to offline optimization method,and thus the system reliability has great improvement.

  1. Displacement response analysis of base-isolated buildings subjected to near-fault ground motions with velocity pulse

    Science.gov (United States)

    He, Qiumei; Li, Xiaojun; Yang, Yu; Liu, Aiwen; Li, Yaqi

    2016-04-01

    In order to study the influence of the velocity pulse to seismic displacement response of base-isolated buildings and the differences of the influent of the two types of near-fault ground motions with velocity pulse to seismic response of base-isolated buildings, the seismic responses are analyzed by three dimensional finite element models for three base-isolated buildings, 4 stories, 9 stories and 14 stories. In this study, comparative analyses were done for the seismic displacement responses of the base-isolated structures under 6 near-fault ground motion records with velocity pulse and no velocity pulse, in which, 6 artificial ground motion time histories with same elastic response spectrum as the 6 near-fault ground motion records are used as the ground motion with no velocity pulse. This study indicates that under the ground motions with velocity pulse the seismic displacement response of base-isolated buildings is significantly increased than the ground motions with no velocity pulse. To the median-low base-isolated buildings, the impact of forward directivity pulses is bigger than fling-step pulses. To the high base-isolated buildings, the impact of fling-step pulses is bigger than forward directivity pulses. The fling-step pulses lead to large displacement response in the lower stories. This work has been supported by the National Natural Science Foundation of China (Grant No.51408560)

  2. Construction of adaptive redundant multiwavelet packet and its application to compound faults detection of rotating machinery

    Institute of Scientific and Technical Information of China (English)

    CHEN JingLong; ZI YanYang; HE ZhengJia; WANG XiaoDong

    2012-01-01

    It is significant to detect the fault type and assess the fault level as early as possible for avoiding catastrophic accidents.Due to diversity and complexity,the compound faults detection of rotating machinery under non-stationary operation turns to be a challenging task.Multiwavelet with two or more base functions may match two or more features of compound faults,which may supply a possible solution to compound faults detection.However,the fixed basis functions of multiwavelet transform,which are not related with the vibration signal,may reduce the accuracy of compound faults detection.Moreover,the decomposition results of multiwavelet transform not being own time-invariant is harmful to extract the features of periodical impulses.Furthermore,multiwavelet transform only focuses on the multi-resolution analysis in the low frequency band,and may leave out the useful features of compound faults.To overcome these shortcomings,a novel method called adaptive redundant multiwavelet packet (ARMP) is proposed based on the two-scale similarity transforms.Besides,the relative energy ratio at the characteristic frequency of the concerned component is computed to select the sensitive frequency bands of multiwavelet packet coefficients.The proposed method was used to analyze the compound faults of rolling element beating.The results showed that the proposed method could enhance the ability of compound faults detection of rotating machinery.

  3. Fault Detection and Isolation of Wind Energy Conversion Systems using Recurrent Neural Networks

    Directory of Open Access Journals (Sweden)

    N. Talebi

    2014-07-01

    Full Text Available Reliability of Wind Energy Conversion Systems (WECSs is greatly important regarding to extract the maximum amount of available wind energy. In order to accurately study WECSs during occurrence of faults and to explore the impact of faults on each component of WECSs, a detailed model is required in which mechanical and electrical parts of WECSs are properly involved. In addition, a Fault Detection and Isolation System (FDIS is required by which occurred faults can be diagnosed at the appropriate time in order to ensure safe system operation and avoid heavy economic losses. This can be performed by subsequent actions through fast and accurate detection and isolation of faults. In this paper, by utilizing a comprehensive dynamic model of the WECS, an FDIS is presented using dynamic recurrent neural networks. In industrial processes, dynamic neural networks are known as a good mathematical tool for fault detection. Simulation results show that the proposed FDIS detects faults of the generator's angular velocity sensor, pitch angle sensors and pitch actuators appropriately. The suggested FDIS is capable to detect and isolate the faults shortly while owing very low false alarms rate. The presented FDIS scheme can be used to identify faults in other parts of the WECS.

  4. Robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels

    Institute of Scientific and Technical Information of China (English)

    Niu Erzhuo; Wang Qing; Dong Chaoyang

    2014-01-01

    The observer-based robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels and norm bounded modeling uncertainties are addressed. The network of unmanned vehicles is modeled as a discrete-time uncertain Markovian jump system. Based on the model, a residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of linear matrix inequality. Furthermore, a time domain optimization approach is proposed to improve the performance of the fault detection system. The problem of detecting small faults can be formulated as an optimization problem and its solution is given. For preventing false alarms, a new adaptive threshold function is established. The combined fault detection and optimization algorithm and the adaptive threshold are then applied to a network of highly maneuverable technology vehicles to illustrate the effective-ness of the proposed approach.

  5. Advanced Ground Systems Maintenance Anomaly Detection Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This project will develop the capability to identify anomalous conditions (indications to potential impending system failure) in ground system operations before such...

  6. A Design of Finite Memory Residual Generation Filter for Sensor Fault Detection

    Science.gov (United States)

    Kim, Pyung Soo

    2017-04-01

    In the current paper, a residual generation filter with finite memory structure is proposed for sensor fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite measurements and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noisefree systems. The proposed residual generation filter is specified to the digital filter structure for the amenability to hardware implementation. Finally, to illustrate the capability of the proposed residual generation filter, extensive simulations are performed for the discretized DC motor system with two types of sensor faults, incipient soft bias-type fault and abrupt bias-type fault. In particular, according to diverse noise levels and windows lengths, meaningful simulation results are given for the abrupt bias-type fault.

  7. DWT based bearing fault detection in induction motor using noise cancellation

    Directory of Open Access Journals (Sweden)

    K.C. Deekshit Kompella

    2016-12-01

    Full Text Available This paper presents an approach to detect the bearing faults experienced by induction machine using motor current signature analysis (MCSA. At the incipient stage of bearing fault, the current signature analysis has shown poor performance due to domination of pre fault components in the stator current. Therefore, in this paper domination of pre fault components is suppressed using noise cancellation by Wiener filter. The spectral analysis is carried out using discrete wavelet transform (DWT. The fault severity is estimated by calculating fault indexing parameter of wavelet coefficients. It is further proposed that, the fault indexing parameter of power spectral density (PSD based wavelet coefficients gives better results. The proposed method is examined using simulation and experiment on 2.2 kW test bed.

  8. S2-Project: Near-fault earthquake ground motion simulation in the Sulmona alluvial basin

    Science.gov (United States)

    Faccioli, E.; Stupazzini, M.; Galadini, F.; Gori, S.

    2008-12-01

    Quarteroni and co- workers, starting from 1996, and the computational code GeoELSE (http://GeoELSE.stru.polimi.it/). Finally, numerical results are compared with available data and attenuation relationships of peak values of ground motion in the near-fault regions elsewhere. Based on the results of this work, the unfavorable interaction between fault rupture, radiation mechanism and complex geological conditions may give rise to large values of peak ground velocity (exceeding 1 m/s) even in low-to-moderate seismicity areas, and therefore increase considerably the level of seismic risk, especially in highly populated and industrially active regions, such as the Central Italy.

  9. Application of H-Infinity Fault Detection to Model-Scale Autonomous Aircraft

    Science.gov (United States)

    Vasconcelos, J. F.; Rosa, P.; Kerr, Murray; Latorre Sierra, Antonio; Recupero, Cristina; Hernandez, Lucia

    2015-09-01

    This paper describes the development of a fault detection system for a model scale autonomous aircraft. The considered fault scenario is defined by malfunctions in the elevator, namely bias and stuck-in-place of the surface. The H∞ design methodology is adopted, with an LFT description of the aircraft longitudinal dynamics, that allows for fault detection explicitly synthesized for a wide range of operating airspeeds. The obtained filter is validated in two stages: in a Functional Engineering Simulator (FES), providing preliminary results of the filter performance; and with experimental data, collected in field tests with actual injection of faults in the elevator surface.

  10. Fault detection of a Five-Phase Permanent-Magnet Machine

    DEFF Research Database (Denmark)

    Bianchini, Claudio; Matzen, Torben N.; Bianchi, Nicola;

    2008-01-01

    The paper focuses on the fault detection of a five-phase Permanent-Magnet (PM) machine. This machine has been de-signed for fault tolerant applications, and it is characterised by a mutual inductance equal to zero and a high self inductance, with the purpose to limit the short circuit current....... The effects of a limited number of short-circuited turns were investigated by theoretical and Finite Element (FE) analysis, and then a procedure for fault detection has been proposed, focusing on the severity of the fault (i.e. the number of short-circuited turns and the related current)....

  11. Engineering characteristics of near-fault vertical ground motions and their effect on the seismic response of bridges

    Institute of Scientific and Technical Information of China (English)

    Li Xinle; Dou Huijuan; Zhu Xi

    2007-01-01

    A wide variety of near-fault strong ground motion records were collected from various tectonic environments worldwide and were used to study the peak value ratio and response spectrum ratio of the vertical to horizontal component of ground motion,focusing on the effect of earthquake magnitude,site conditions,pulse duration,and statistical component.The results show that both the peak value ratio and response spectrum ratio are larger than the 2/3 value prescribed in existing seismic codes,and the relationship between the vertical and horizontal ground motions is comparatively intricate.In addition,the effect of the near-fault ground motions on bridge performance is analyzed,considering both the material nonlinear characteristics and the P~△ effect.

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

    Science.gov (United States)

    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.

  13. A New UKF Based Fault Detection Method in Non-linear Systems

    Institute of Scientific and Technical Information of China (English)

    GE Zhe-xue; YANG Yong-min; HU Zheng

    2006-01-01

    To detect the bias fault in stochastic non-linear dynamic systems, a new Unscented Kalman Filtering(UKF) based real-time recursion detection method is brought forward with the consideration of the flaws of traditional Extended Kalman Filtering(EKF). It uses the UKF as the residual generation method and the Weighted-Sum Squared Residual (WSSR) as the fault detection strategy. The simulation results are provided which demonstrate better effectiveness and a higher detection ratio of the developed methods.

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

    Directory of Open Access Journals (Sweden)

    Mehdi Shadaram

    2010-10-01

    Full Text Available 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.

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

    Institute of Scientific and Technical Information of China (English)

    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 a wall-climbing robot is presented in this paper. For the control system, some fault models are derived by kinematics analysis. Moreover, the logic relations of the system states are known in advance. First, a fault tree is used to analyze the system by evaluating the basic events (elementary causes), which can lead to a root event (a particular fault). Then, a multiple-model adaptive estimation algorithm is used to detect and identify the model-known faults. Finally, based on the system states of the robot and the results of the estimation, the model-unknown faults are also identified using logical reasoning. Experiments show that the proposed approach based on the combination of logical reasoning and model estimating is efficient in the FDI of the robot.

  16. A Novel Approach of Impulsive Signal Extraction for Early Fault Detection of Rolling Element Bearing

    Directory of Open Access Journals (Sweden)

    Hu Aijun

    2017-01-01

    Full Text Available The fault signals of rolling element bearing are often characterized by the presence of periodic impulses, which are modulated high-frequency harmonic components. The features of early fault in rolling bearing are very weak, which are often masked by background noise. The impulsiveness of the vibration signal has affected the identification of characteristic frequency for the early fault detection of the bearing. In this paper, a novel approach based on morphological operators is presented for impulsive signal extraction of early fault in rolling element bearing. The combination Top-Hat (CTH is proposed to extract the impulsive signal and enhance the impulsiveness of the bearing fault signal, and the envelope analysis is applied to reveal the fault-related signatures. The impulsive extraction performance of the proposed CTH is compared with that of finite impulse response filter (FIR by analyzing the simulated bearing fault signals, and the result indicates that the CTH is more effective in extracting impulsive signals. The method is evaluated using real fault signals from defective bearings with early rolling element fault and early fault located on the outer race. The results show that the proposed method is able to enhance the impulsiveness of early bearing fault signals.

  17. A correlation based fault detection method for short circuits in battery packs

    Science.gov (United States)

    Xia, Bing; Shang, Yunlong; Nguyen, Truong; Mi, Chris

    2017-01-01

    This paper presents a fault detection method for short circuits based on the correlation coefficient of voltage curves. The proposed method utilizes the direct voltage measurements from the battery cells, and does not require any additional hardware or effort in modeling during fault detection. Moreover, the inherent mathematical properties of the correlation coefficient ensure the robustness of this method as the battery pack ages or is imbalanced in real applications. In order to apply this method online, the recursive moving window correlation coefficient calculation is adopted to maintain the detection sensitivity to faults during operation. An additive square wave is designed to prevent false positive detections when the batteries are at rest. The fault isolation can be achieved by identifying the overlapped cell in the correlation coefficients with fault flags. Simulation and experimental results validated the feasibility and demonstrated the advantages of this method.

  18. A Novel Approach for Eccentricity Fault Detection in Squirrel Cage Induction Motors

    Directory of Open Access Journals (Sweden)

    Mehdi Ahmadi

    2013-01-01

    Full Text Available In this paper, static eccentricity fault detection in induction motors is studied. Two dimensional finite element method (2D-FEM is used for faultless and eccentric condition modeling in induction motors. Also current and speed signals are compared in two experimental and simulation cases for model validating. For fault detection, fast Fourier transform is used at first. In this method, high order harmonics with small amplitude can alarms the fault occurrence. For this reason, the fault detection process is difficult.To overcome these drawbacks, it is suggested that two test coils contrive around the air-gap. So, any changes in air-gap can be detected easily. Moreover this test coils are used in open circuit case. So, these test coils do not effect on motor dynamics. Also, the results show that modulated voltage can be alarm the fault occurrence, type and percent well.

  19. Application of a Fault Detection and Isolation System on a Rotary Machine

    Directory of Open Access Journals (Sweden)

    Silvia M. Zanoli

    2013-01-01

    Full Text Available The paper illustrates the design and the implementation of a Fault Detection and Isolation (FDI system to a rotary machine like a multishaft centrifugal compressor. A model-free approach, that is, the Principal Component Analysis (PCA, has been employed to solve the fault detection issue. For the fault isolation purpose structured residuals have been adopted while an adaptive threshold has been designed in order to detect and to isolate the faults. To prove the goodness of the proposed FDI system, historical data of a nitrogen centrifugal compressor employed in a refinery plant are considered. Tests results show that detection and isolation of single as well as multiple faults are successfully achieved.

  20. A first approach on fault detection and isolation for cardiovascular anomalies detection

    KAUST Repository

    Ledezma, Fernando

    2015-07-01

    In this paper, we use an extended version of the cardiovascular system\\'s state space model presented by [1] and propose a fault detection and isolation methodology to study the problem of detecting cardiovascular anomalies that can originate from variations in physiological parameters and deviations in the performance of the heart\\'s mitral and aortic valves. An observer-based approach is discussed as the basis of the method. The approach contemplates a bank of Extended Kalman Filters to achieve joint estimation of the model\\'s states and parameters and to detect malfunctions in the valves\\' performance. © 2015 American Automatic Control Council.

  1. Fault Detection and Isolation for a Supermarket Refrigeration System - Part One

    DEFF Research Database (Denmark)

    Yang, Zhenyu; Rasmussen, Karsten B.; Kieu, Anh T.;

    2011-01-01

    Fault Detection and Isolation (FDI) using the Kalman Filter (KF) technique for a supermarket refrigeration system is explored. Four types of sensor fault scenarios, namely drift, offset, freeze and hard-over, are considered for two temperature sensors, and one type of parametric fault scenario, n....... The test results show that the EKF-based FDI method generally performances better and faster than the KF-based method does. However, both methods can not handle the isolation between sensor faults and parametric fault.......Fault Detection and Isolation (FDI) using the Kalman Filter (KF) technique for a supermarket refrigeration system is explored. Four types of sensor fault scenarios, namely drift, offset, freeze and hard-over, are considered for two temperature sensors, and one type of parametric fault scenario...... isolation purpose, a bank of KFs arranged by splitting measurements is constructed for sensor fault isolation, while the Multi-Model Adaptive Estimation (MMAE) method is employed to handle parametric fault isolation. All these approaches are extended and checked by using Extended KF technique afterwards...

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

    Science.gov (United States)

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

    2013-07-01

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

  3. LiDAR-derived measurements of slip in the most recent ground-rupturing earthquakes along elements of the San Andreas fault system

    Science.gov (United States)

    Haddad, D. E.; Madden, C.; Salisbury, J. B.; Arrowsmith, R.; Weldon, R. J.

    2011-12-01

    Tectonically displaced geomorphic markers record the surface manifestation of earthquake-induced ground ruptures. Of particular interest to earthquake forecast models is the slip produced during the most recent ground-rupturing earthquake. High-resolution digital topography from light detection and ranging (LiDAR) is a powerful tool for measuring the most recent meter-scale slip along fault zones. We present surface slip measurements of recent ground-rupturing earthquakes along the Garlock, Owens Valley, Elsinore, and Blackwater-Calico fault zones. Fault scarp traces were mapped using LiDAR-derived digital elevation models (DEMs), local topographic gradient and relief maps, and aerial photography. An individual slip measurement was made for each offset feature by iteratively reconstructing the topography on either side of the fault and finding the best-matching vertically backslipped value. A goodness-of-fit approach was then used to calculate the best laterally backslipped displacement using a combination of vertical backslip, horizontal backslip, and topographic scaling. Along-strike, reach-averaged surface displacement distributions of the most recent earthquakes were then generated from the LiDAR-derived offsets and compared to published field-derived offset measurements. For the eastern section of the Garlock fault, our LiDAR-derived offsets compared well with those measured in the field and attained an R2 value of 0.88 with reach-averaged slip in the last event of 4.19 m ±0.69 m for the Searles Valley area (2.67 km reach), 4.65 m +0.76/-0.92 m for the Pilot Knob Valley area (24.68 km reach), and 3.45 m +0.82/-0.87 m for the Leach Lake and Avawatz Mountains areas (12.65 km reach), computed from a total of 129 offsets. Our results show that LiDAR-derived offset measurements compare well with field measurements in the comprehensive documentation of along-strike surface slip distributions of the most recent earthquake. Furthermore, our results demonstrate the

  4. Fault detection and diagnosis for refrigerator from compressor sensor

    Energy Technology Data Exchange (ETDEWEB)

    Keres, Stephen L.; Gomes, Alberto Regio; Litch, Andrew D.

    2016-12-06

    A refrigerator, a sealed refrigerant system, and method are provided where the refrigerator includes at least a refrigerated compartment and a sealed refrigerant system including an evaporator, a compressor, a condenser, a controller, an evaporator fan, and a condenser fan. The method includes monitoring a frequency of the compressor, and identifying a fault condition in the at least one component of the refrigerant sealed system in response to the compressor frequency. The method may further comprise calculating a compressor frequency rate based upon the rate of change of the compressor frequency, wherein a fault in the condenser fan is identified if the compressor frequency rate is positive and exceeds a condenser fan fault threshold rate, and wherein a fault in the evaporator fan is identified if the compressor frequency rate is negative and exceeds an evaporator fan fault threshold rate.

  5. Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches

    KAUST Repository

    Harrou, Fouzi

    2017-09-18

    This study reports the development of an innovative fault detection and diagnosis scheme to monitor the direct current (DC) side of photovoltaic (PV) systems. Towards this end, we propose a statistical approach that exploits the advantages of one-diode model and those of the univariate and multivariate exponentially weighted moving average (EWMA) charts to better detect faults. Specifically, we generate array\\'s residuals of current, voltage and power using measured temperature and irradiance. These residuals capture the difference between the measurements and the predictions MPP for the current, voltage and power from the one-diode model, and use them as fault indicators. Then, we apply the multivariate EWMA (MEWMA) monitoring chart to the residuals to detect faults. However, a MEWMA scheme cannot identify the type of fault. Once a fault is detected in MEWMA chart, the univariate EWMA chart based on current and voltage indicators is used to identify the type of fault (e.g., short-circuit, open-circuit and shading faults). We applied this strategy to real data from the grid-connected PV system installed at the Renewable Energy Development Center, Algeria. Results show the capacity of the proposed strategy to monitors the DC side of PV systems and detects partial shading.

  6. Rupture Process of the 2003 Bam, Iran, Earthquake: Did Shallow Asperities on a Fresh Fault Cause Extreme Ground Motions?

    Science.gov (United States)

    Miyake, H.; Koketsu, K.; Mostafaei, H.

    2004-12-01

    The Bam, Iran, earthquake on December 26, 2003 caused heavy damage to the city of Bam including the historic heritage of Arg-e-Bam. This Mw6.5 earthquake rupture created fresh faults 5 km westward away from the Bam fault. The Bam strong-motion station recorded 992 gal in the UD component and two directivity pulses in the horizontal components with a dominant frequency of 1 Hz. We inferred the rupture process of the 2003 Bam earthquake from strong motion data observed by BHRC, together with teleseismic data to constrain global features of the source. Waveform inversions using teleseismic data (e.g. Yamanaka, 2003; Yagi, 2003) have suggested the existence of a shallow asperity. Nakamura et al. (2004) estimated aftershock distribution with vertical dipping that superimposed the fresh faults, not the Bam fault. They proposed fault planes consisting N-S alignment with northward branches beneath the city of Bam. Our preliminary analyses show that two directivity pulses are created by northward rupture near the hypocenter and north-eastward rupture beneath the city. Recent earthquakes occurred on immature faults with shallow asperities have also generated localized extreme-strong motions (e.g., 2003 Miyagi-ken Hokubu, Japan, with Mw6.1; 2000 Tottori, Japan, with Mw6.6). Larger fracture energy is expected for shallow asperities on immature faults than those on mature faults. For example, the 2000 Tottori earthquake has several times larger fracture energy than expected by the scaling between seismic moment and fracture energy. When considering the energy budget, are radiated energy from the immature faults enough to generate the extreme ground motions? Detailed source process inversions might be able to answer this question.

  7. Aircraft Fault Detection Using Real-Time Frequency Response Estimation

    Science.gov (United States)

    Grauer, Jared A.

    2016-01-01

    A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

  8. Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition

    Science.gov (United States)

    Georgoulas, George; Loutas, Theodore; Stylios, Chrysostomos D.; Kostopoulos, Vassilis

    2013-12-01

    Aiming at more efficient fault diagnosis, this research work presents an integrated anomaly detection approach for seeded bearing faults. Vibration signals from normal bearings and bearings with three different fault locations, as well as different fault sizes and loading conditions are examined. The Empirical Mode Decomposition and the Hilbert Huang transform are employed for the extraction of a compact feature set. Then, a hybrid ensemble detector is trained using data coming only from the normal bearings and it is successfully applied for the detection of any deviation from the normal condition. The results prove the potential use of the proposed scheme as a first stage of an alarm signalling system for the detection of bearing faults irrespective of their loading condition.

  9. New method for online interturn faults detection in power transformer with using probabilistic neural network

    Directory of Open Access Journals (Sweden)

    S. hajiaghasi

    2014-07-01

    Full Text Available In recent years with notice increase reliability in power system and Intelligent Systems and also notice that transformers are one of the main part of the transmission and distribution systems, online monitoring of these equipment in power system are require. In this paper, a new method for online interturn fault detection base on leakage flux in power transformer are propose. When an interturn fault occur the symmetry of flux destruction and leakage flux increase or decrease and for various location and severity of fault leakage flux is different and it can be used for fault detection. In this paper for measure these flux we using search coils that mounted on HV winding. To fault detection and classify we using probabilistic neural network. and for decrease the information volume PCA is used. The simulation results are compare and verified with experimental result and show that this propose method is very good.

  10. Design of parametric fault detection systems:An H-infinity optimization approach

    Institute of Scientific and Technical Information of China (English)

    Maiying ZHONG; Chuanfeng MA; Steven X.DING

    2005-01-01

    Problems related to the design of observer-based parametric fault detection (PFD) systems are studied.The core of our study is to first describe the faults occurring in system actuators,sensors and components in the form of additive parameter deviations,then to transform the PFD problems into a similar additive fault setup,based on which an optimal observer-based optimization fault detection approach is proposed.A constructive solution optimal in the sense of minimizing a certain performance index is developed.The main results consist of defining parametric fault detectability,formulating a PFD optimization problem and its solution.A numerical example to demonstrate the effectiveness of the proposed approach is provided.

  11. Deconvolution effect of near-fault earthquake ground motions on stochastic dynamic response of tunnel-soil deposit interaction systems

    Directory of Open Access Journals (Sweden)

    K. Hacıefendioğlu

    2012-04-01

    Full Text Available The deconvolution effect of the near-fault earthquake ground motions on the stochastic dynamic response of tunnel-soil deposit interaction systems are investigated by using the finite element method. Two different earthquake input mechanisms are used to consider the deconvolution effects in the analyses: the standard rigid-base input and the deconvolved-base-rock input model. The Bolu tunnel in Turkey is chosen as a numerical example. As near-fault ground motions, 1999 Kocaeli earthquake ground motion is selected. The interface finite elements are used between tunnel and soil deposit. The mean of maximum values of quasi-static, dynamic and total responses obtained from the two input models are compared with each other.

  12. Wind Turbine Fault Detection based on Artificial Neural Network Analysis of SCADA Data

    DEFF Research Database (Denmark)

    Herp, Jürgen; S. Nadimi, Esmaeil

    2015-01-01

    Slowly developing faults in wind turbine can, when not detected and fixed on time, cause severe damage and downtime. We are proposing a fault detection method based on Artificial Neural Networks (ANN) and the recordings from Supervisory Control and Data Acquisition (SCADA) systems installed in wi...... detection upon a generalized-likelihood-test. An upper and a lower control bounds are established for x and y respectively, given a minimum false alarm probability η based on the statistical characteristics of the data....

  13. FABRIC FAULT DETECTION USING IMAGE PROCESSING WITH ATMEL MICROCONTROLLER

    Directory of Open Access Journals (Sweden)

    R.THILEPA,

    2010-11-01

    Full Text Available In this paper it is explained how a faulty fabric image is processed through a microcontroller. If there is any fault how it is identified through this ATMEL microcontroller by the circuit operation. For programming the controller Atmel program is used. In addition to that a stepper motor is connected in the output. This motor operates if there is no fault and fails if the fault is identified. This can be implemented in states like Tamilnadu so that the textile field’s income may be increased in an enormous way which in turn raises the country’s income [7].

  14. Fault detection and diagnosis for compliance monitoring in international supply chains

    NARCIS (Netherlands)

    Wang, Yuxin; Tian, Yifu; Teixeira, André; Hulstijn, Joris; Tan, Yao-Hua

    Currently international supply chains are facing risks concerning faults in compliance, such as altering shipping documentations, fictitious inventory, and inter-company manipulations. In this paper a method to detect and diagnose fault scenarios regarding customs compliance in supply chains is

  15. Fault detection and diagnosis for compliance monitoring in international supply chains

    NARCIS (Netherlands)

    Wang, Yuxin; Tian, Yifu; Teixeira, André; Hulstijn, Joris; Tan, Yao-Hua

    2016-01-01

    Currently international supply chains are facing risks concerning faults in compliance, such as altering shipping documentations, fictitious inventory, and inter-company manipulations. In this paper a method to detect and diagnose fault scenarios regarding customs compliance in supply chains is prop

  16. Design of a Fault Detection and Isolation System for Intelligent Vehicle Navigation System

    Directory of Open Access Journals (Sweden)

    Wei Huang

    2015-01-01

    Full Text Available This paper deals with the design of a fault detection and isolation (FDI system for an intelligent vehicle, a vehicle equipped with advanced driver assistance system (ADAS. The ADASs are outfitted with sensors for acquiring various information about the vehicle and its surroundings. Since these sensors are sensitive to faults, an efficient FDI system should be developed. The designed FDI system is comprised of three parts: a detection part, a decision part, and a fault management part. The detection part applies a generalized observer scheme (GOS. In the GOS, there is bank of extended Kalman filters (EKFs, each excited by all except one sensor measurement. The residual generated from the measurement update of each EKF is therefore sensitive to all sensor faults but one. This way, the fault sensitivity pattern of the residual makes it possible to detect a fault and locate the faulty sensor. The designed FDI system has been implemented and tested off-line with actual experiment data. Good results have been obtained with diagnosing individual sensor faults and outputting fault-free vehicle states.

  17. Robust fault detection in bond graph framework using interval analysis and Fourier-Motzkin elimination technique

    Science.gov (United States)

    Jha, Mayank Shekhar; Chatti, Nizar; Declerck, Philippe

    2017-09-01

    This paper addresses the fault diagnosis problem of uncertain systems in the context of Bond Graph modelling technique. The main objective is to enhance the fault detection step based on Interval valued Analytical Redundancy Relations (named I-ARR) in order to overcome the problems related to false alarms, missed alarms and robustness issues. These I-ARRs are a set of fault indicators that generate the interval bounds called thresholds. A fault is detected once the nominal residuals (point valued part of I-ARRs) exceed the thresholds. However, the existing fault detection method is limited to parametric faults and it presents various limitations with regards to estimation of measurement signal derivatives, to which I-ARRs are sensitive. The novelties and scientific interest of the proposed methodology are: (1) to improve the accuracy of the measurements derivatives estimation by using a dedicated sliding mode differentiator proposed in this work, (2) to suitably integrate the Fourier-Motzkin Elimination (FME) technique within the I-ARRs based diagnosis so that measurements faults can be detected successfully. The latter provides interval bounds over the derivatives which are included in the thresholds. The proposed methodology is studied under various scenarios (parametric and measurement faults) via simulations over a mechatronic torsion bar system.

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

    DEFF Research Database (Denmark)

    Schlechtingen, Meik; Santos, Ilmar

    2011-01-01

    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 ...

  19. Sensor fault detection and isolation over wireless sensor network based on hardware redundancy

    Science.gov (United States)

    Hao, Jingjing; Kinnaert, Michel

    2017-01-01

    In order to diagnose sensor faults with small magnitude in wireless sensor networks, distinguishability measures are defined to indicate the performance for fault detection and isolation (FDI) at each node. A systematic method is then proposed to determine the information to be exchanged between nodes to achieve FDI specifications while limiting the computation complexity and communication cost.

  20. DETECTION OF INCIPIENT LOCALIZED GEAR FAULTS IN GEARBOX BY COMPLEX CONTINUOUS WAVELET TRANSFORM

    Institute of Scientific and Technical Information of China (English)

    Han Zhennan; Xiong Shibo; Li Jinbao

    2003-01-01

    As far as the vibration signal processing is concerned, composition of vibration signal resulting from incipient localized faults in gearbox is too weak to be detected by traditional detecting technology available now. The method, which includes two steps: vibration signal from gearbox is first processed by synchronous average sampling technique and then it is analyzed by complex continuous wavelet transform to diagnose gear fault, is introduced. Two different kinds of faults in the gearbox, i.e.shaft eccentricity and initial crack in tooth fillet, are detected and distinguished from each other successfully.

  1. Observer-based and Regression Model-based Detection of Emerging Faults in Coal Mills

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Lin, Bao; Jørgensen, Sten Bay

    2006-01-01

    In order to improve the reliability of power plants it is important to detect fault as fast as possible. Doing this it is interesting to find the most efficient method. Since modeling of large scale systems is time consuming it is interesting to compare a model-based method with data driven ones....... In this paper three different fault detection approaches are compared using a example of a coal mill, where a fault emerges. The compared methods are based on: an optimal unknown input observer, static and dynamic regression model-based detections. The conclusion on the comparison is that observer-based scheme...

  2. A New Method for the Detections of Multiple Faults Using Binary Decision Diagrams

    Institute of Scientific and Technical Information of China (English)

    PAN Zhongliang; CHEN Ling; ZHANG Guangzhao

    2006-01-01

    With the complexity of integrated circuits is continually increasing, a local defect in circuits may cause multiple faults. The behavior of a digital circuit with a multiple fault may significantly differ from that of a single fault. A new method for the detection of multiple faults in digital circuits is presented in this paper, the method is based on binary decision diagram (BDD). First of all, the BDDs for the normal circuit and faulty circuit are built respectively. Secondly, a test BDD is obtained by the XOR operation of the BDDs corresponds to normal circuit and faulty circuit. In the test BDD, each input assignment that leads to the leaf node labeled 1 is a test vector of multiple faults. Therefore, the test set of multiple faults is generated by searching for the type of input assignments in the test BDD. Experimental results on some digital circuits show the feasibility of the approach presented in this paper.

  3. Rotor Faults Detection in Induction Motor by Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Neelam Mehala

    2009-12-01

    Full Text Available Motor current signature analysis has been successfully used for fault diagnosis in induction motors. However, this method does not always achieve good results when the speed or the load torque is not constant, because this cause variation on the motor slip and fast Fourier transform problems appear due to non-stationary signal. This paper experimentally describes the effects of rotor broken bar fault in the stator current of induction motor operating under non-constant load conditions. To achieve this, broken rotor bar fault is eplicated in a laboratory and its effect on the motor current has been studied. To diagnose the broken rotor bar fault, a new approach based on wavelet transform is applied by using ‘Labview 8.2 software’ of National Instrument (NI. The diagnosis procedure was performed by using the virtual instruments. The theoretical basis of proposed method is proved by laboratory tests.

  4. Application of D-S Evidence Fusion Method in the Fault Detection of Temperature Sensor

    Directory of Open Access Journals (Sweden)

    Zheng Dou

    2014-01-01

    Full Text Available Due to the complexity and dangerousness of drying process, the fault detection of temperature sensor is very difficult and dangerous in actual working practice and the detection effectiveness is not satisfying. For this problem, in this paper, based on the idea of information fusion and the requirements of D-S evidence method, a D-S evidence fusion structure with two layers was introduced to detect the temperature sensor fault in drying process. The first layer was data layer to establish the basic belief assignment function of evidence which could be realized by BP Neural Network. The second layer was decision layer to detect and locate the sensor fault which could be realized by D-S evidence fusion method. According to the numerical simulation results, the working conditions of sensors could be described effectively and accurately by this method, so that it could be used to detect and locate the sensor fault.

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  6. DYNAMIC SOFTWARE TESTING MODELS WITH PROBABILISTIC PARAMETERS FOR FAULT DETECTION AND ERLANG DISTRIBUTION FOR FAULT RESOLUTION DURATION

    Directory of Open Access Journals (Sweden)

    A. D. Khomonenko

    2016-07-01

    Full Text Available Subject of Research.Software reliability and test planning models are studied taking into account the probabilistic nature of error detection and discovering. Modeling of software testing enables to plan the resources and final quality at early stages of project execution. Methods. Two dynamic models of processes (strategies are suggested for software testing, using error detection probability for each software module. The Erlang distribution is used for arbitrary distribution approximation of fault resolution duration. The exponential distribution is used for approximation of fault resolution discovering. For each strategy, modified labeled graphs are built, along with differential equation systems and their numerical solutions. The latter makes it possible to compute probabilistic characteristics of the test processes and states: probability states, distribution functions for fault detection and elimination, mathematical expectations of random variables, amount of detected or fixed errors. Evaluation of Results. Probabilistic characteristics for software development projects were calculated using suggested models. The strategies have been compared by their quality indexes. Required debugging time to achieve the specified quality goals was calculated. The calculation results are used for time and resources planning for new projects. Practical Relevance. The proposed models give the possibility to use the reliability estimates for each individual module. The Erlang approximation removes restrictions on the use of arbitrary time distribution for fault resolution duration. It improves the accuracy of software test process modeling and helps to take into account the viability (power of the tests. With the use of these models we can search for ways to improve software reliability by generating tests which detect errors with the highest probability.

  7. APPROACH TO FAULT ON-LINE DETECTION AND DIAGNOSIS BASED ON NEURAL NETWORKS FOR ROBOT IN FMS

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    Based on radial basis function (RBF) neural networks, the healthy working model of each sub-system of robot in FMS is established. A new approach to fault on-line detection and diagnosis according to neural networks model is presented. Fault double detection based on neural network model and threshold judgement and quick fault identification based on multi-layer feedforward neural networks are applied, which can meet quickness and reliability of fault detection and diagnosis for robot in FMS.

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

    Science.gov (United States)

    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.

  9. ASCS Online Fault Detection and Isolation Based on an Improved MPCA

    Institute of Scientific and Technical Information of China (English)

    PENG Jianxin; LIU Haiou; HU Yuhui; XI Junqiang; CHEN Huiyan

    2014-01-01

    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 (T2) 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 T2 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.

  10. Mine-hoist fault-condition detection based on the wavelet packet transform and kernel PCA

    Institute of Scientific and Technical Information of China (English)

    XIA Shi-xiong; NIU Qiang; ZHOU Yong; ZHANG Lei

    2008-01-01

    A new algorithm was developed to correctly identify fault conditions and accurately monitor fault development in a mine hoist. The new method is based on the Wavelet Packet Transform (WPT) and kernel PCA (Kernel Principal Component Analysis, KPCA). For non-linear monitoring systems the key to fault detection is the extracting of main features. The wavelet packet transform is a novel technique of signal processing that possesses excellent characteristics of time-frequency localization. It is suitable for analysing time-varying or transient signals. KPCA maps the original input features into a higher dimension feature space through a non-linear mapping. The principal components are then found in the higher dimension feature space. The KPCA transformation was applied to extracting the main nonlinear features from experimental fault feature data after wavelet packet transformation. The results show that the proposed method affords credible fault detection and identification.

  11. Dynamic Reconstruction-Based Fuzzy Neural Network Method for Fault Detection in Chaotic System

    Institute of Scientific and Technical Information of China (English)

    YANG Hongying; YE Hao; WANG Guizeng

    2008-01-01

    This paper presents a method for detecting weak fault signals in chaotic systems based on the chaotic dynamics reconstruction technique and the fuzzy neural system (FNS). The Grassberger-Procaccia algorithm and least squares regression were used to calculate the correlation dimension for the model order estimate. Based on the model order, an appropriately structured FNS model was designed to predict system faults. Through reasonable analysis of predicted errors, the disturbed signal can be extracted efficiently and correctly from the chaotic background. Satisfactory results were obtained by using several kinds of simula-tive faults which were extracted from the practical chaotic fault systems. Experimental results demonstra tethat the proposed approach has good prediction accuracy and can deal with data having a -40 dB signal to noise ratio (SNR). The low SNR requirement makes the approach a powerful tool for early fault detection.

  12. Fault Detection and Diagnosis in Process Data Using Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Fang Wu

    2014-01-01

    Full Text Available For the complex industrial process, it has become increasingly challenging to effectively diagnose complicated faults. In this paper, a combined measure of the original Support Vector Machine (SVM and Principal Component Analysis (PCA is provided to carry out the fault classification, and compare its result with what is based on SVM-RFE (Recursive Feature Elimination method. RFE is used for feature extraction, and PCA is utilized to project the original data onto a lower dimensional space. PCA T2, SPE statistics, and original SVM are proposed to detect the faults. Some common faults of the Tennessee Eastman Process (TEP are analyzed in terms of the practical system and reflections of the dataset. PCA-SVM and SVM-RFE can effectively detect and diagnose these common faults. In RFE algorithm, all variables are decreasingly ordered according to their contributions. The classification accuracy rate is improved by choosing a reasonable number of features.

  13. Closed-form dynamic stability criterion for elastic-plastic structures under near-fault ground motions

    Directory of Open Access Journals (Sweden)

    Kotaro eKojima

    2016-03-01

    Full Text Available A dynamic stability criterion for elastic-plastic structures under near-fault ground motions is derived in closed-form. A negative post-yield stiffness is treated in order to consider the P-delta effect. The double impulse is used as a substitute of the fling-step near-fault ground motion. Since only the free-vibration appears under such double impulse, the energy approach plays a critical role in the derivation of the closed-form solution of a complicated elastic-plastic response of structures with the P-delta effect. It is remarkable that no iteration is needed in the derivation of the closed-form dynamic stability criterion on the critical elastic-plastic response. It is shown via the closed-form expression that several patterns of unstable behaviors exist depending on the ratio of the input level of the double impulse to the structural strength and on the ratio of the negative post-yield stiffness to the initial elastic stiffness. The validity of the proposed dynamic stability criterion is investigated by the numerical response analysis for structures under double impulses with stable or unstable parameters. Furthermore the reliability of the proposed theory is tested through the comparison with the response analysis to the corresponding one-cycle sinusoidal input as a representative of the fling-step near-fault ground motion. The applicability of the proposed theory to actual recorded pulse-type ground motions is also discussed.

  14. Cross-correlation-based detection and characterisation of microseismicity adjacent to the locked, late-interseismic Alpine Fault, South Westland, New Zealand

    Science.gov (United States)

    Chamberlain, Calum J.; Boese, Carolin M.; Townend, John

    2017-01-01

    The Alpine Fault is inferred on paleoseismological grounds to produce magnitude 8 earthquakes approximately every 330 yrs and to have last ruptured almost 300 yrs ago in 1717 AD. Despite approximately 90% of its typical interseismic period having elapsed since the last major earthquake, the Alpine Fault exhibits little present-day microseismicity and no geodetic evidence for shallow creep. Determining the mechanical state of the fault ahead of a future earthquake is a key objective of several studies, including the Deep Fault Drilling Project (DFDP). Here we use a network of borehole seismometers installed in conjunction with DFDP to detect and characterise low-magnitude seismicity adjacent to the central section of the Alpine Fault. We employ matched-filter detection techniques, automated cross-correlation phase picking, and singular value decomposition-derived magnitude estimation to construct a high-precision catalogue of 283 earthquakes within 5 km of the fault trace in an otherwise seismically quiet zone. The newly recognised seismicity occurs in non-repeating, spatially and temporally limited sequences, similar to sequences previously documented using standard methods but at significantly lower magnitudes of ML < 1.8. These earthquakes are not clustered on a single distinctive structure, and we infer that they are distributed throughout a highly fractured zone surrounding the Alpine Fault. Focal mechanisms computed for 13 earthquakes using manual polarity picks exhibit predominantly strike-slip faulting, consistent with focal mechanisms observed further from the fault. We conclude that the Alpine Fault is locked and accumulating strain throughout the seismogenic zone at this location.

  15. Significance of rotating ground motions on nonlinear behavior of symmetric and asymmetric buildings in near fault sites

    Science.gov (United States)

    Kalkan, Erol; ,

    2012-01-01

    Building codes in the U.S. require at least two horizontal ground motion components for three-dimensional (3D) response history analysis (RHA) of structures. For sites within 5 km of an active fault, these records should be rotated to fault-normal/fault-parallel (FN/FP) directions, and two RHA analyses should be performed separately (when FN and then FP are aligned with transverse direction of the structural axes). It is assumed that this approach will lead to two sets of responses that envelope the range of possible responses over all non-redundant rotation angles. This assumption is examined here using 3D computer models of a single-story structure having symmetric (that is, torsionally-stiff) and asymmetric (that is, torsionally flexible) layouts subjected to an ensemble of bi-directional near-fault strong ground motions with and without apparent velocity pulses. In this parametric study, the elastic vibration period of the structures is varied from 0.2 to 5 seconds, and yield strength reduction factors R is varied from a value that leads to linear-elastic design to 3 and 5. The influence that the rotation angle of the ground motion has on several engineering demand parameters (EDPs) is examined in linear-elastic and nonlinear-inelastic domains to form a benchmark for evaluating the use of the FN/FP directions as well as the maximum-direction (MD) ground motion, a new definition of horizontal ground motions for use in the seismic design of structures according to the 2009 NEHRP Provisions and Commentary.

  16. Weak fault detection and health degradation monitoring using customized standard multiwavelets

    Science.gov (United States)

    Yuan, Jing; Wang, Yu; Peng, Yizhen; Wei, Chenjun

    2017-09-01

    Due to the nonobvious symptoms contaminated by a large amount of background noise, it is challenging to beforehand detect and predictively monitor the weak faults for machinery security assurance. Multiwavelets can act as adaptive non-stationary signal processing tools, potentially viable for weak fault diagnosis. However, the signal-based multiwavelets suffer from such problems as the imperfect properties missing the crucial orthogonality, the decomposition distortion impossibly reflecting the relationships between the faults and signatures, the single objective optimization and independence for fault prognostic. Thus, customized standard multiwavelets are proposed for weak fault detection and health degradation monitoring, especially the weak fault signature quantitative identification. First, the flexible standard multiwavelets are designed using the construction method derived from scalar wavelets, seizing the desired properties for accurate detection of weak faults and avoiding the distortion issue for feature quantitative identification. Second, the multi-objective optimization combined three dimensionless indicators of the normalized energy entropy, normalized singular entropy and kurtosis index is introduced to the evaluation criterions, and benefits for selecting the potential best basis functions for weak faults without the influence of the variable working condition. Third, an ensemble health indicator fused by the kurtosis index, impulse index and clearance index of the original signal along with the normalized energy entropy and normalized singular entropy by the customized standard multiwavelets is achieved using Mahalanobis distance to continuously monitor the health condition and track the performance degradation. Finally, three experimental case studies are implemented to demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed method can quantitatively identify the fault signature of a slight rub on

  17. Automatic Supervision And Fault Detection In PV System By Wireless Sensors With Interfacing By Labview Program

    Directory of Open Access Journals (Sweden)

    Yousra M Abbas

    2015-08-01

    Full Text Available In this work a wireless monitoring system are designed for automatic detection localization fault in photovoltaic system. In order to avoid the use of modeling and simulation of the PV system we detected the fault by monitoring the output of each individual photovoltaic panel connected in the system by Arduino and transmit this data wirelessly to laptop then interface it by LabVIEW program which made comparison between this data and the measured data taking from reference module at the same condition. The proposed method is very simple but effective detecting and diagnosing the main faults of a PV system and was experimentally validated and has demonstrated its effectiveness in the detection and diagnosing of main faults present in the DC side of PV system.

  18. Unweighted Betweenness Centrality for Critical Fault Detection for Cascading Outage Assessment

    DEFF Research Database (Denmark)

    Petersen, Pauli Fríðheim; Jóhannsson, Hjörtur; Nielsen, Arne Hejde

    2016-01-01

    This paper analyses the possible use of unweighted betweenness centrality instead of weighted betweenness centrality, for critical fault detection for assessment of cascading failures. As unweighted betweenness centrality is significantly faster to compute, the possible use of this will significa...

  19. Framework for the Design and Implementation of Fault Detection and Isolation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — SySense, Inc. proposes to develop a framework for the design and implementation of fault detection and isolation (FDI) systems. The framework will include protocols...

  20. Model-based fault detection of blade pitch system in floating wind turbines

    Science.gov (United States)

    Cho, S.; Gao, Z.; Moan, T.

    2016-09-01

    This paper presents a model-based scheme for fault detection of a blade pitch system in floating wind turbines. A blade pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be detected at the early stage to prevent failures. To detect faults of blade pitch actuators and sensors, an appropriate observer should be designed to estimate the states of the system. Residuals are generated by a Kalman filter and a threshold based on H optimization, and linear matrix inequality (LMI) is used for residual evaluation. The proposed method is demonstrated in a case study that bias and fixed output in pitch sensors and stuck in pitch actuators. The simulation results show that the proposed method detects different realistic fault scenarios of wind turbines under the stochastic external winds.

  1. Self-healing of single-phase grounding fault for power distribution lines%配电线路单相接地故障自愈方案

    Institute of Scientific and Technical Information of China (English)

    施慎行; 董新洲; 吴家华; 沈冬

    2012-01-01

    A self-healing scheme is presented for the single-phase grounding fault of distribution lines,which consists of four parts:fault detection, faulty feeder selection, faulty section identification and faulty feeder isolation. The fault detection is based on the open-delta-side voltages of PT. A single-phase grounding fault is identified when the measured voltage is greater than the setting value. The faulty feeder selection is based on the current traveling waves. The feeder with different traveling wave polarity is selected as the faulty one. The faulty section identification is based on the synthesized results of faulty feeder selection. After the faulty feeder is selected,close the interconnection switch at the load side first,then open its incoming switch and isolate the power source side of faulty. Simulative results show that the scheme realizes the automatic quick isolation of single-phase grounding fault without power loss of load.%针对配电线路的单相接地故障,提出了故障自愈方案.方案包括单相接地故障检测、故障选线、故障区段识别和接地线路隔离4个部分.故障检测基于母线上的电压互感器开口三角侧电压,当测量电压大于整定值时,判断系统中发生了单相接地故障;故障选线基于线路上的电流行波,极性与众不同的电流行波所在线路为接地线路;故障区段识别基于故障选线的综合结果;选出故障母线后,先闭合接地线路负荷侧的联络开关,再打开接地线路负荷侧进线开关,最后隔离接地线路电源侧.仿真结果表明,所提自愈方案可实现单相接地故障自动快速隔离,故障隔离过程中负荷不失电.

  2. Ground-Based Detection of Exoatmospheric Calcium

    Science.gov (United States)

    Rojo, Patricio M.; Astudillo-Defru, Nicola

    2014-11-01

    Data acquired with HDS@Subaru for HD209458b is re-analyzed. A new pipeline performs an automated search for the exoatmospheric presence of several elements without any a-priori assumptions on its existence or strength. We analyzed thousands of lines in the full spectral range of this optical echelle spectrograph using a robust method to correct for the telluric contamination. We recover previous detections of Sodium and Halpha, and present the first strong detection of Calcium in an Extrasolar Atmosphere as well as the tentative detection of other elements. The Calcium detection is in disagreement with theoretical thermal-equilibrium models.

  3. Safety issues in PV systems: Design choices for a secure fault detection and for preventing fire risk

    Directory of Open Access Journals (Sweden)

    M.C. Falvo

    2015-05-01

    Full Text Available Photovoltaic systems have played a key role over the last decade in the evolution of the electricity sector. In terms of safety design, it’s important to consider that a PV plant constitutes a special system of generation, where the Direct Current (DC presence results in changes to the technical rules. Moreover, if certain electrical faults occur, the plant is a possible source of fire. Choices regarding the grounding of the generator and its protection devices are fundamental for a design that evaluates fire risk. The subject of the article is the analysis of the relation between electrical phenomena in PV systems and the fire risk related to ensuring appropriate fault detection by the electrical protection system. A description of a grid-connected PV system is followed firstly by a comparison of the design solutions provided by International Standards, and secondly by an analysis of electrical phenomena which may trigger a fire. A study of two existing PV systems, where electrical faults have resulted in fires, is then presented. The study highlights the importance of checking all possible failure modes in a PV system design phase, to assess fire risk in advance. Some guidelines for the mitigation of electrical faults that may result in a fire are finally provided.

  4. Fault detection for a class of Markov jump systems with unknown disturbances

    Institute of Scientific and Technical Information of China (English)

    Shuping HE; Fei LIU

    2009-01-01

    An optimized fault detection observer is designed for a class of Markov jump systems with unknown disturbances.By reconstructing the system,the residual error dynamic characteristics of unknown input and fault signals,including unknown disturbances and modeling error are obtained.The energy norm indexes of disturbance and fault signals of the residual error are selected separately to reflect the restraint of disturbance and the sensitivity of faults,and the design of the fault detection observer is described as an optimization problem.By using the constructed Lyapunov function and linear matrix inequalities,a sufficient condition that the solution to the fault detection observer exists is given and proved,and an optimized design approach is presented.The designed observer makes the systems have stochastic stability and better capability of restraining disturbances,and the given norm index is satisfied.Simulation results demonstrate that the proposed observer can detect the faults sensitively,and the influence of unknown distur-bance on residual error can be restrained to a given range.

  5. Robust PCA-Based Abnormal Traffic Flow Pattern Isolation and Loop Detector Fault Detection

    Institute of Scientific and Technical Information of China (English)

    JIN Xuexiang; ZHANG Yi; LI Li; HU Jianming

    2008-01-01

    One key function of intelligent transportation systems is to automatically detect abnormal traffic phenomena and to help further investigations of the cause of the abnormality. This paper describes a robust principal components analysis (RPCA)-based abnormal traffic flow pattern isolation and loop detector fault detection method. The results show that RPCA is a useful tool to distinguish regular traffic flow from abnor-mal traffic flow patterns caused by accidents and loop detector faults. This approach gives an effective traffic flow data pre-processing method to reduce the human effort in finding potential loop detector faults. The method can also be used to further investigate the causes of the abnormality.

  6. Detection of Naturally Occurring Gear and Bearing Faults in a Helicopter Drivetrain

    Science.gov (United States)

    2014-01-01

    Annual Forum, Montreal, Canada, 2002. 3. Samuel, P. D.; Pines, D. J. A Review of Vibration Based Techniques for Helicopter Transmission Diagnostics...Detection of Naturally Occurring Gear and Bearing Faults in a Helicopter Drivetrain by Kelsen E. LaBerge, Eric C. Ames, and Brian D. Dykas...5066 ARL-TR-6795 January 2014 Detection of Naturally Occurring Gear and Bearing Faults in a Helicopter Drivetrain Kelsen E. LaBerge

  7. Fused Empirical Mode Decomposition and MUSIC Algorithms for Detecting Multiple Combined Faults in Induction Motors

    Directory of Open Access Journals (Sweden)

    D. Camarena-Martinez

    2015-02-01

    Full Text Available Detection of failures in induction motors is one of the most important concerns in industry. An unexpected fault in the induction motors can cause a loss of financial resources and waste of time that most companies cannot afford. The contribution of this paper is a fusion of the Empirical Mode Decomposition (EMD and Multiple Signal Classification (MUSIC methodologies for detection of multiple combined faults which provides an accurate and effective strategy for the motor condition diagnosis.

  8. Detection and Quantization of Bearing Fault in Direct Drive Wind Turbine via Comparative Analysis

    Directory of Open Access Journals (Sweden)

    Wei Teng

    2016-01-01

    Full Text Available Bearing fault is usually buried by intensive noise because of the low speed and heavy load in direct drive wind turbine (DDWT. Furthermore, varying wind speed and alternating loads make it difficult to quantize bearing fault feature that indicates the degree of deterioration. This paper presents the application of multiscale enveloping spectrogram (MuSEnS and cepstrum to detect and quantize bearing fault in DDWT. MuSEnS can manifest fault modulation information adaptively based on the capacity of complex wavelet transform, which enables the weak bearing fault in DDWT to be detected. Cepstrum can calculate the average interval of periodic components in frequency domain and is suitable for quantizing bearing fault feature under varying operation conditions due to the logarithm weight on the power spectrum. Through comparing a faulty DDWT with a normal one, the bearing fault feature is evidenced and the quantization index is calculated, which show a good application prospect for condition monitoring and fault diagnosis in real DDWT.

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

    Science.gov (United States)

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

  10. Evaluation of faults and their effect on ground-water flow southwest of Frenchman Flat, Nye and Clark counties, Nevada: a digital database

    Science.gov (United States)

    McKee, Edwin H.; Wickham, Thomas A.; Wheeler, Karen L.

    1998-01-01

    Ground-water flow through the region south and west of Frenchman Flat, in the Ash Meadows subbasin of the Death Valley ground-water flow system, is controlled mostly by faults which arrange the distribution of permeable and impermeable rocks. In addition, most permeability is along fractures caused by faulting in carbonate rocks. Large faults are more likely to reach the potentiometric surface as deep as 325 meters below the ground surface and are more likely to effect the flow path than small faults. This study concentrated on identifying large faults, especially where they cut carbonate rocks. Small faults, however, may develop as much permeability as large faults if they are penetrative and are part of an anastomosing fault_zone. The overall pattern of faults and joints at the ground surface in the Spotted and Specter Ranges is an indication of the fracture system at the depth of the water table. Most of the faults in these ranges are west-southwest-striking, high-angle faults, 100 to 3,500 meters long, with 10 to 300 meters of displacement. Many of them, such as those in the Spotted Range and Rock Valley are left-lateral strike-slip faults that are conjugate to the NW-striking right-lateral faults of the Las Vegas Valley shear zone. These faults control the ground-water flow path, which runs west-southwest beneath the Spotted Range, Mercury Valley and the Specter Range. The Specter Range thrust is a significant geologic structure with respect to ground- water flow. This regional thrust fault emplaces siliceous clastic strata into the north central and western parts of the Specter Range. These rocks act as a barrier that confines ground- water flow to the southern part of the range, directing it southwestward toward springs at Ash Meadows. These siliceous clastic aquitard rocks and overlying Cenozoic deposits probably also block westward flow of ground-water in Rock Valley, diverting it southward to the flow path beneath the southern part of the Specter Range.

  11. Repetitive transients extraction algorithm for detecting bearing faults

    Science.gov (United States)

    He, Wangpeng; Ding, Yin; Zi, Yanyang; Selesnick, Ivan W.

    2017-02-01

    Rolling-element bearing vibrations are random cyclostationary. This paper addresses the problem of noise reduction with simultaneous components extraction in vibration signals for faults diagnosis of bearing. The observed vibration signal is modeled as a summation of two components contaminated by noise, and each component composes of repetitive transients. To extract the two components simultaneously, an approach by solving an optimization problem is proposed in this paper. The problem adopts convex sparsity-based regularization scheme for decomposition, and non-convex regularization is used to further promote the sparsity but preserving the global convexity. A synthetic example is presented to illustrate the performance of the proposed approach for repetitive feature extraction. The performance and effectiveness of the proposed method are further demonstrated by applying to compound faults and single fault diagnosis of a locomotive bearing. The results show the proposed approach can effectively extract the features of outer and inner race defects.

  12. Potential fault region detection in TFDS images based on convolutional neural network

    Science.gov (United States)

    Sun, Junhua; Xiao, Zhongwen

    2016-10-01

    In recent years, more than 300 sets of Trouble of Running Freight Train Detection System (TFDS) have been installed on railway to monitor the safety of running freight trains in China. However, TFDS is simply responsible for capturing, transmitting, and storing images, and fails to recognize faults automatically due to some difficulties such as such as the diversity and complexity of faults and some low quality images. To improve the performance of automatic fault recognition, it is of great importance to locate the potential fault areas. In this paper, we first introduce a convolutional neural network (CNN) model to TFDS and propose a potential fault region detection system (PFRDS) for simultaneously detecting four typical types of potential fault regions (PFRs). The experimental results show that this system has a higher performance of image detection to PFRs in TFDS. An average detection recall of 98.95% and precision of 100% are obtained, demonstrating the high detection ability and robustness against various poor imaging situations.

  13. Fine-scale delineation of the location of and relative ground shaking within the San Andreas Fault zone at San Andreas Lake, San Mateo County, California

    Science.gov (United States)

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

    2013-01-01

    extensional stresses on built structures within the fault zone. Such differential movement and resulting distortion of built structures appear to have occurred between fault traces at the gatewell near the southern end of San Andreas Lake during the 1906 San Francisco earthquake (Schussler, 1906). In addition to the three fault traces within the main 1906 surface rupture zone, our data indicate at least one additional fault trace (or zone) about 80 meters northeast of the main 1906 surface rupture zone. Because ground shaking also can damage structures, we used fault-zone guided waves to investigate ground shaking within the fault zones relative to ground shaking outside the fault zones. Peak ground velocity (PGV) measurements from our guided-wave study indicate that ground shaking is greater at each of the surface fault traces, varying with the frequency of the seismic data and the wave type (P versus S). S-wave PGV increases by as much as 5–6 times at the fault traces relative to areas outside the fault zone, and P-wave PGV increases by as much as 3–10 times. Assuming shaking increases linearly with increasing earthquake magnitude, these data suggest strong shaking may pose a significant hazard to built structures that extend across the fault traces. Similarly complex fault structures likely underlie other strike-slip faults (such as the Hayward, Calaveras, and Silver Creek Faults) that intersect structures of the water delivery system, and these fault structures similarly should be investigated.

  14. Evidence of Multiple Ground-rupturing Earthquakes in the Past 4000 Years along the Pasuruan Fault, East Java, Indonesia

    Science.gov (United States)

    Marliyani, G. I.; Arrowsmith, R.; Helmi, H.

    2015-12-01

    Instrumental and historical records of earthquakes, supplemented by paleoeseismic constraints can help reveal the earthquake potential of an area. The Pasuruan fault is a high angle normal fault with prominent youthful scarps cutting young deltaic sediments in the north coast of East Java, Indonesia and may pose significant hazard to the densely populated region. This fault has not been considered a significant structure, and mapped as a lineament with no sense of motion. Information regarding past earthquakes along this fault is not available. The fault is well defined both in the imagery and in the field as a ~13km long, 2-50m-high scarp. Open and filled fractures and natural exposures of the south-dipping fault plane indicate normal sense of motion. We excavated two fault-perpendicular trenches across a relay ramp identified during our surface mapping. Evidence for past earthquakes (documented in both trenches) includes upward fault termination with associated fissure fills, colluvial wedges and scarp-derived debris, folding, and angular unconformities. The ages of the events are constrained by 23 radiocarbon dates on detrital charcoal. We calibrated the dates using IntCal13 and used Oxcal to build the age model of the events. Our preliminary age model indicates that since 2006±134 B.C., there has been at least five ground rupturing earthquakes along the fault. The oldest event identified in the trench however, is not well-dated. Our modeled 95th percentile ranges of the next four earlier earthquakes (and their mean) are A.D. 1762-1850 (1806), A.D. 1646-1770 (1708), A.D. 1078-1648 (1363), and A.D. 726-1092 (909), yielding a rough recurrence rate of 302±63 yrs. These new data imply that Pasuruan fault is more active than previously thought. Additional well-dated earthquakes are necessary to build a solid earthquake recurrence model. Rupture along the whole section implies a minimum earthquake magnitude of 6.3, considering 13km as the minimum surface rupture

  15. Multi fault detection of the roller bearing using the wavelet transformand principal component analysis

    Directory of Open Access Journals (Sweden)

    Jaafar Khalaf Ali, Qusai Talib Abdulwahab, Sajjad Nayyef Abdul kareem

    2016-01-01

    Full Text Available Vibration monitoring and analysis techniques are the key features of successful predictive and proactive maintenance programs. In this work, advanced vibration analysis techniques like Wavelet transform, Principle Component Analysis (PCA and Squared Prediction Error (SPE have been used to detect the faults in bearing. Discrete Wavelet Transforms (DWT decomposes signal to high and low frequencies. PCA is employed to extract important feature and reduce dimension. SPE is used to detect the bearing faults. The experimental data is collected from SpectraQuest's Machine Fault Simulator (MFS-4 apparatus. In this study, four rollers were bearing defects (ball defect, outer race defect, inner race defect and combined defect for 1" and 3/4" bearing. From the results, the suggestion techniques can be used to detect multi-faults in the bearings. The results show that the best wavelet function is Coiflets4 in this method.

  16. Observer-based fault detection scheme for a class of discrete time-delay systems

    Institute of Scientific and Technical Information of China (English)

    Zhong Maiying(钟麦英); Zhang Chenghui(张承慧); Ding Steven X; Lam James

    2004-01-01

    In this contribution, robust fault detection problems for discrete time-delay systems with l2-norm bounded un-known inputs are studied. The basic idea of our study is first to introduce a state-memoryless observer-based fault detec-tion filter (FDF) as the residual generator and then to formulate such a FDF design problem as an H∞ optimization prob-lem in the sense of increasing the sensitivity of residual to the faults, while simultaneously enhancing the robustness of residual to unknown input as well as plant input. The main results consist of the formulation of such a residual generation optimization problem, solvability conditions and the derivation of an analytic solution. The residual evaluation problem is also considered, which includes the determination of residual evaluation function and threshold. A numerical example is used to demonstrate the proposed fault detection scheme.

  17. Fault detection and diagnosis in nonlinear systems a differential and algebraic viewpoint

    CERN Document Server

    Martinez-Guerra, Rafael

    2014-01-01

    The high reliability required in industrial processes has created the necessity of detecting abnormal conditions, called faults, while processes are operating. The term fault generically refers to any type of process degradation, or degradation in equipment performance because of changes in the process's physical characteristics, process inputs or environmental conditions. This book is about the fundamentals of fault detection and diagnosis in a variety of nonlinear systems which are represented by ordinary differential equations. The fault detection problem is approached from a differential algebraic viewpoint, using residual generators based upon high-gain nonlinear auxiliary systems (‘observers’). A prominent role is played by the type of mathematical tools that will be used, requiring knowledge of differential algebra and differential equations. Specific theorems tailored to the needs of the problem-solving procedures are developed and proved. Applications to real-world problems, both with constant an...

  18. Robust fault detection for switched positive linear systems with time-varying delays.

    Science.gov (United States)

    Xiang, Mei; Xiang, Zhengrong

    2014-01-01

    This paper investigates the problem of robust fault detection for a class of switched positive linear systems with time-varying delays. The fault detection filter is used as the residual generator, in which the filter parameters are dependent on the system mode. Attention is focused on designing the positive filter such that, for model uncertainties, unknown inputs and the control inputs, the error between the residual and fault is minimized. The problem of robust fault detection is converted into a positive L1 filtering problem. Subsequently, by constructing an appropriate multiple co-positive type Lyapunov-Krasovskii functional, as well as using the average dwell time approach, sufficient conditions for the solvability of this problem are established in terms of linear matrix inequalities (LMIs). Two illustrative examples are provided to show the effectiveness and applicability of the proposed results.

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

    Science.gov (United States)

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

    2015-01-01

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

  20. Fault Detection and Recovery for Full Range of Hydrogen Sensor Based on Relevance Vector Machine

    Institute of Scientific and Technical Information of China (English)

    Kai Song; Bing Wang; Ming Diao; Hongquan Zhang; Zhenyu Zhang

    2015-01-01

    In order to improve the reliability of hydrogen sensor, a novel strategy for full range of hydrogen sensor fault detection and recovery is proposed in this paper. Three kinds of sensors are integrated to realize the measurement for full range of hydrogen concentration based on relevance vector machine ( RVM ) . Failure detection of hydrogen sensor is carried out by using the variance detection method. When a sensor fault is detected, the other fault⁃free sensors can recover the fault data in real⁃time by using RVM predictor accounting for the relevance of sensor data. Analysis, together with both simulated and experimental results, a full⁃range hydrogen detection and hydrogen sensor self⁃validating experiment is presented to demonstrate that the proposed strategy is superior at accuracy and runtime compared with the conventional methods. Results show that the proposed methodology provides a better solution to the full range of hydrogen detection and the reliability improvement of hydrogen sensor.

  1. Application of Uncertainty Reasoning Theory to satellite Fault Detection and Diagnosis

    Institute of Scientific and Technical Information of China (English)

    YangTianshe; LiHuaizu; SunYanbong

    2004-01-01

    Reasoning theories are divided into certainty reasoning theories and uncertainty reasoning theories.Now,only certainty reason-ing theories use to deitcs are used to detect and diagnose satellite faults.However,in practice,it is difficult to detect and diagnose some faults of the satellite autiomatically only by use of ccrtainty.Fortunately.uncerlainty Reasoning theories are applied to detect and diagnose satellite faults.Uncertainty reasoning theories include several kinds of theories,such as inclusion degree theory,rough set theory,evidence reasoning theory,probabilisticresoning theory,fuzzy,fuzzy reasoningteory,and so on.Inclusion degree theory.rough set theory and evidence reasoning theory are three advanced ones,Based on these three theories respectively.the audhor introduces three new methods to detect and diagnose satellite faults in this paper.It is shown that the methods,suitable for detecting and diagnosing satellite faults,especially uncertainty faults,can remedy the defects of the current methods.

  2. Detecting intermittent resistive faults in digital CMOS circuits

    NARCIS (Netherlands)

    Ebrahimi, Hassan; Kerkhoff, Hans G.; Rohani, A.

    2016-01-01

    Interconnection reliability threats dependability of highly critical electronic systems. One of most challenging interconnection-induced reliability threats are intermittent resistive faults (IRFs). The occurrence rate of this kind of defects can take e.g. one month, and the duration of defects can

  3. Optimal Threshold Functions for Fault Detection and Isolation

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, H.; Harbo, Anders La-Cour

    2003-01-01

    Fault diagnosis systems usually comprises two parts: a filtering part and a decision part, the latter typically based on threshold functions. In this paper, systematic ways to choose the threshold values are proposed. Two different test functions for the filtered signals are discussed and a method...

  4. Fault Detection and Isolation using Multi Objective Controller Design Techniques

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1996-01-01

    Abstract: This paper describes a method for designing fault detectionand isolation filters. The method is multi objective in the sense thatit follows optimization with arbitrarily mixed criteria specified ine.g. the QTR H-infinity or the QTR H^2 norm. Moreover,the involved optimization yields less...

  5. Fault Detection and Localization Method for Modular Multilevel Converters

    DEFF Research Database (Denmark)

    Deng, Fujin; Chen, Zhe; Khan, Mohammad Rezwan;

    2015-01-01

    in the MMC. The proposed method can be implemented with less computational intensity and complexity, even in case that multiple SMs faults occur in a short time interval. The proposed method is not only implemented in simulations with professional tool PSCAD/EMTDC, but also verified with a down-scale MMC...

  6. Similarity ratio analysis for early stage fault detection with optical emission spectrometer in plasma etching process.

    Science.gov (United States)

    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.

  7. Similarity ratio analysis for early stage fault detection with optical emission spectrometer in plasma etching process.

    Directory of Open Access Journals (Sweden)

    Jie Yang

    Full Text Available 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.

  8. Fault Diagnosis and Detection in Industrial Motor Network Environment Using Knowledge-Level Modelling Technique

    Directory of Open Access Journals (Sweden)

    Saud Altaf

    2017-01-01

    Full Text Available In this paper, broken rotor bar (BRB fault is investigated by utilizing the Motor Current Signature Analysis (MCSA method. In industrial environment, induction motor is very symmetrical, and it may have obvious electrical signal components at different fault frequencies due to their manufacturing errors, inappropriate motor installation, and other influencing factors. The misalignment experiments revealed that improper motor installation could lead to an unexpected frequency peak, which will affect the motor fault diagnosis process. Furthermore, manufacturing and operating noisy environment could also disturb the motor fault diagnosis process. This paper presents efficient supervised Artificial Neural Network (ANN learning technique that is able to identify fault type when situation of diagnosis is uncertain. Significant features are taken out from the electric current which are based on the different frequency points and associated amplitude values with fault type. The simulation results showed that the proposed technique was able to diagnose the target fault type. The ANN architecture worked well with selecting of significant number of feature data sets. It seemed that, to the results, accuracy in fault detection with features vector has been achieved through classification performance and confusion error percentage is acceptable between healthy and faulty condition of motor.

  9. Ultimate Strength of Fixed Offshore Platforms Subjected to Near-Fault Earthquake Ground Vibration

    Directory of Open Access Journals (Sweden)

    Hesam Sharifian

    2015-01-01

    Full Text Available The pile foundation nonlinearity and its influence on the ultimate capacity of fixed platforms have not comprehensively been covered by previous researchers. In this study, the seismic behavior and capacity of a newly designed and installed Jacket Type Offshore Platform (JTOP located in the Persian Gulf is investigated by conducting Incremental Dynamic Analysis (IDA using a suit of near-fault ground motions. Additionally, two modified models of the original platform are created by slightly increasing the diameter of the pile foundation and also softening the jacket part for evaluating the importance of the pile foundation and seismic soil-pile structure interaction on the dynamic characteristics of the JTOPs. Valuable discussions are provided to explore various aspects of the dynamic behavior of JTOPs by presenting individual and multirecords IDA curves using effective Engineering Demand Parameters (EDPs. Comparing the results of the three platform collapse fragility curves, it is concluded that the pile foundation plays a very important role in the dynamic response of offshore platforms and can drastically alter the ultimate strength of the platform together with its collapse capacity. It is observed that the proportional distribution of nonlinear behavior in the pile foundation and jacket part is the key factor in the enhancement of the ultimate strength of JTOPs. On the basis of the results derived from this paper, it is recommended that some basic requirements should be developed in order to ensure that the coupling ductility of pile foundation and jacket part is optimized during the design process. Furthermore, according to the findings from this study, some practice recommendations are presented to be devised within the design step.

  10. A Novel High-Frequency Voltage Standing-Wave Ratio-Based Grounding Electrode Line Fault Supervision in Ultra-High Voltage DC Transmission Systems

    Directory of Open Access Journals (Sweden)

    Yufei Teng

    2017-03-01

    Full Text Available In order to improve the fault monitoring performance of grounding electrode lines in ultra-high voltage DC (UHVDC transmission systems, a novel fault monitoring approach based on the high-frequency voltage standing-wave ratio (VSWR is proposed in this paper. The VSWR is defined considering a lossless transmission line, and the characteristics of the VSWR under different conditions are analyzed. It is shown that the VSWR equals 1 when the terminal resistance completely matches the characteristic impedance of the line, and when a short circuit fault occurs on the grounding electrode line, the VSWR will be greater than 1. The VSWR will approach positive infinity under metallic earth fault conditions, whereas the VSWR in non-metallic earth faults will be smaller. Based on these analytical results, a fault supervision criterion is formulated. The effectiveness of the proposed VSWR-based fault supervision technique is verified with a typical UHVDC project established in Power Systems Computer Aided Design/Electromagnetic Transients including DC(PSCAD/EMTDC. Simulation results indicate that the proposed strategy can reliably identify the grounding electrode line fault and has strong anti-fault resistance capability.

  11. Gear-box fault detection using time-frequency based methods

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2015-01-01

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

  12. Fault Detection based on MCSA for a 400Hz Asynchronous Motor for Airborne Applications

    Directory of Open Access Journals (Sweden)

    Steffen Haus

    2013-01-01

    Full Text Available Future health monitoring concepts in different fields of engineering require reliable fault detection to avoid unscheduled machine downtime. Diagnosis of electrical induction machines for industrial applications is widely discussed in literature. In aviation industry, this topic is still only rarely discussed.A common approach to health monitoring for electrical induction machines is to use Motor Current Signature Analysis (MCSA based on a Fast Fourier Transform (FFT. Research results on this topic are available for comparatively large motors, where the power supply is typically based on 50Hz alternating current, which is the general power supply frequency for industrial applications.In this paper, transferability to airborne applications, where the power supply is 400Hz, is assessed. Three phase asynchronous motors are used to analyse detectability of different motor faults. The possibility to transfer fault detection results from 50Hz to 400Hz induction machines is the main question answered in this research work. 400Hz power supply frequency requires adjusted motor design, causing increased motor speed compared to 50Hz supply frequency. The motor used for experiments in this work is a 800W motor with 200V phase to phase power supply, powering an avionic fan. The fault cases to be examined are a bearing fault, a rotor unbalance, a stator winding fault, a broken rotor bar and a static air gap eccentricity. These are the most common faults in electrical induction machines which can cause machine downtime. The focus of the research work is the feasibility of the application of MCSA for small scale, high speed motor design, using the Fourier spectra of the current signal.Detectability is given for all but the bearing fault, although rotor unbalance can only be detected in case of severe damage level. Results obtained in the experiments are interpreted with respect to the motor design. Physical interpretation are given in case the results differ

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

    Science.gov (United States)

    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.

  14. A geometric approach for fault detection and isolation of stator short circuit failure in a single asynchronous machine

    KAUST Repository

    Khelouat, Samir

    2012-06-01

    This paper deals with the problem of detection and isolation of stator short-circuit failure in a single asynchronous machine using a geometric approach. After recalling the basis of the geometric approach for fault detection and isolation in nonlinear systems, we will study some structural properties which are fault detectability and isolation fault filter existence. We will then design filters for residual generation. We will consider two approaches: a two-filters structure and a single filter structure, both aiming at generating residuals which are sensitive to one fault and insensitive to the other faults. Some numerical tests will be presented to illustrate the efficiency of the method.

  15. Caldecott 4th bore tunnel project: influence of ground water flows and inflows triggered by tectonic fault zones?

    Science.gov (United States)

    Neuhuber, G.; G. Neuhuber1, W. Klary1, A. Nitschke1, B. Thapa2, Chris Risden3, T. Crampton4, D. Zerga5

    2011-12-01

    nearly perpendicular, separating different geological units were expected along the 4th Bore alignment. This paper will describe encountered ground conditions adjacent to the fault contact where rock conditions are influenced to an extent of 5ft to 85ft from the contact. This paper will also compare the anticipated inflow of 55gpm within 100ft of the top heading excavation and fault zones inflow rates up to 110gpm to the actual measured maximum inflow into the tunnel of150gpm away from fault zones to a maximum inflow between 60gpm and 100gpm near fault zones. In presence of fault zones the water inflow is significant lower than expected and in absence of fault zones higher inflow rates as expected were measured. This paper will discuss the influence of fault zones on the water inflow - or are rock properties and lithology more significant?

  16. Robust fault detection of wind energy conversion systems based on dynamic neural networks.

    Science.gov (United States)

    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.

  17. Methodology for fault detection in induction motors via sound and vibration signals

    Science.gov (United States)

    Delgado-Arredondo, Paulo Antonio; Morinigo-Sotelo, Daniel; Osornio-Rios, Roque Alfredo; Avina-Cervantes, Juan Gabriel; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene de Jesus

    2017-01-01

    Nowadays, timely maintenance of electric motors is vital to keep up the complex processes of industrial production. There are currently a variety of methodologies for fault diagnosis. Usually, the diagnosis is performed by analyzing current signals at a steady-state motor operation or during a start-up transient. This method is known as motor current signature analysis, which identifies frequencies associated with faults in the frequency domain or by the time-frequency decomposition of the current signals. Fault identification may also be possible by analyzing acoustic sound and vibration signals, which is useful because sometimes this information is the only available. The contribution of this work is a methodology for detecting faults in induction motors in steady-state operation based on the analysis of acoustic sound and vibration signals. This proposed approach uses the Complete Ensemble Empirical Mode Decomposition for decomposing the signal into several intrinsic mode functions. Subsequently, the frequency marginal of the Gabor representation is calculated to obtain the spectral content of the IMF in the frequency domain. This proposal provides good fault detectability results compared to other published works in addition to the identification of more frequencies associated with the faults. The faults diagnosed in this work are two broken rotor bars, mechanical unbalance and bearing defects.

  18. Active Fault Detection and Isolation for Hybrid Systems

    DEFF Research Database (Denmark)

    Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas;

    2009-01-01

    models predicted outputs such that their discrepancies are observable by passive fault diagnosis technique. Isolation of different faults is done by implementation a bank of Extended Kalman Filter (EKF) where the convergence criterion for EKF is confirmed by Genetic Algorithm (GA). The method is applied......An algorithm for active fault detection and isolation is proposed. In order to observe the failure hidden due to the normal operation of the controllers or the systems, an optimization problem based on minimization of test signal is used. The optimization based method imposes the normal and faulty...

  19. Detection and Diagnosis of Gear Fault By the Single Gear Tooth Analysis Technique

    Institute of Scientific and Technical Information of China (English)

    MENG Tao; LIAO Ming-fu

    2003-01-01

    This paper presents a procedure of single gear tooth analysis for early detection and diagnosis of gear faults. The objective of this procedure is to develop a method for more sensitive detection of the incipient faults and locating the faults in the gear. The main idea of the single gear tooth analysis is that the vibration signals collected with a high sampling rate are divided into a number of segments with the same time interval. The number of signal segments is equal to that of the gear teeth. The analysis of individual segments reveals more sensitively the changes of the vibration signals in both time and frequency domain caused by gear faults. In addition, the location of a failed tooth can be indicated in terms of the position of the segment that deviates from the normal segments. An experimental investigation verified the advantages of the single gear tooth analysis.

  20. An Imperfect-debugging Fault-detection Dependent-parameter Software

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Software reliability growth models (SRGMs) incorporating the imperfect debugging and learning phenomenon of developers have recently been developed by many researchers to estimate software reliability measures such as the number of remaining faults and software reliability. However, the model parameters of both the fault content rate function and fault detection rate function of the SRGMs are often considered to be independent from each other. In practice, this assumption may not be the case and it is worth to investigate what if it is not. In this paper, we aim for such study and propose a software reliability model connecting the imperfect debugging and learning phenomenon by a common parameter among the two functions, called the imperfect-debugging fault-detection dependent-parameter model. Software testing data collected from real applications are utilized to illustrate the proposed model for both the descriptive and predictive power by determining the non-zero initial debugging process.

  1. Robust recurrent neural network modeling for software fault detection and correction prediction

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Q.P. [Quality and Innovation Research Centre, Department of Industrial and Systems Engineering, National University of Singapore, Singapore 119260 (Singapore)]. E-mail: g0305835@nus.edu.sg; Xie, M. [Quality and Innovation Research Centre, Department of Industrial and Systems Engineering, National University of Singapore, Singapore 119260 (Singapore)]. E-mail: mxie@nus.edu.sg; Ng, S.H. [Quality and Innovation Research Centre, Department of Industrial and Systems Engineering, National University of Singapore, Singapore 119260 (Singapore)]. E-mail: isensh@nus.edu.sg; Levitin, G. [Israel Electric Corporation, Reliability and Equipment Department, R and D Division, Aaifa 31000 (Israel)]. E-mail: levitin@iec.co.il

    2007-03-15

    Software fault detection and correction processes are related although different, and they should be studied together. A practical approach is to apply software reliability growth models to model fault detection, and fault correction process is assumed to be a delayed process. On the other hand, the artificial neural networks model, as a data-driven approach, tries to model these two processes together with no assumptions. Specifically, feedforward backpropagation networks have shown their advantages over analytical models in fault number predictions. In this paper, the following approach is explored. First, recurrent neural networks are applied to model these two processes together. Within this framework, a systematic networks configuration approach is developed with genetic algorithm according to the prediction performance. In order to provide robust predictions, an extra factor characterizing the dispersion of prediction repetitions is incorporated into the performance function. Comparisons with feedforward neural networks and analytical models are developed with respect to a real data set.

  2. Detection and classification of winding faults in windmill generators using Wavelet Transform and ANN

    Energy Technology Data Exchange (ETDEWEB)

    Gketsis, Zacharias E.; Zervakis, Michalis E.; Stavrakakis, George [Department of Electronics and Computer Engineering, Technical University of Crete, Chania 73100 (Greece)

    2009-11-15

    This paper exploits the Wavelet Transform (WT) analysis along with Artificial Neural Networks (ANN) for the diagnosis of electrical machines winding faults. A novel application is presented exploring the problem of automatically identifying short circuits of windings, which often appear during machine manufacturing and operation. Such faults are usually resulting from electrodynamics forces generated during the flow of large short circuit currents, as well as forces occurring when the machines are transported. The early detection and classification of winding failures is of particular importance, as these kinds of defects can lead to winding damage due to overheating, imbalance, etc. Application results and investigations of windmill generator winding turn-to-turn faults between adjacent winding wires are presented. The ANN approach is proven effective in detecting and classifying faults based on WT features extracted from high frequency measurements of the admittance, current, or voltage responses. (author)

  3. Fault detection and diagnosis for compliance monitoring in international supply chains

    OpenAIRE

    2016-01-01

    Currently international supply chains are facing risks concerning faults in compliance, such as altering shipping documentations, fictitious inventory, and inter-company manipulations. In this paper a method to detect and diagnose fault scenarios regarding customs compliance in supply chains is proposed. This method forms part of a general approach called model-based auditing, which is based on a normative meta-model of the movement of money and goods or services. The modeling framework is pr...

  4. Detecting eccentricity faults in a PMSM in non-stationary conditions

    OpenAIRE

    Javier Rosero García; José Luis Romeral; Esteban Rosero García

    2012-01-01

    Permanent magnet alternating current machines are being widely used in applications demanding high and rugged performance, such as industrial automation and the aerospace and automotive industries. This paper presents a study of a permanent magnet synchronous machine (PMSM) running in eccentricity; these machines’ condition monitoring and fault detection would provide added value and they are also assuming growing importance. This paper investigates the effect of eccentricity faults on PMSM m...

  5. Technique for optimal placement of transducers for fault detection in rotating machines

    OpenAIRE

    2013-01-01

    Online fault detection and diagnosis of rotating machinery requires a number of transducers that can be significantly expensive for industrial processes. The sensitivity of various transducers and their appropriate positioning are dependent on different types of fault conditions. It is critical to formulate a method to systematically determine the effectiveness of transducer locations for monitoring the condition of a machine. In this article, number of independent sources analysis is used as...

  6. Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation.

    Science.gov (United States)

    Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

    2016-07-01

    Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes.

  7. An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction

    Science.gov (United States)

    Zhang, Yan; Tang, Baoping; Liu, Ziran; Chen, Rengxiang

    2016-02-01

    Fault diagnosis of rolling element bearings is important for improving mechanical system reliability and performance. Vibration signals contain a wealth of complex information useful for state monitoring and fault diagnosis. However, any fault-related impulses in the original signal are often severely tainted by various noises and the interfering vibrations caused by other machine elements. Narrow-band amplitude demodulation has been an effective technique to detect bearing faults by identifying bearing fault characteristic frequencies. To achieve this, the key step is to remove the corrupting noise and interference, and to enhance the weak signatures of the bearing fault. In this paper, a new method based on adaptive wavelet filtering and spectral subtraction is proposed for fault diagnosis in bearings. First, to eliminate the frequency associated with interfering vibrations, the vibration signal is bandpass filtered with a Morlet wavelet filter whose parameters (i.e. center frequency and bandwidth) are selected in separate steps. An alternative and efficient method of determining the center frequency is proposed that utilizes the statistical information contained in the production functions (PFs). The bandwidth parameter is optimized using a local ‘greedy’ scheme along with Shannon wavelet entropy criterion. Then, to further reduce the residual in-band noise in the filtered signal, a spectral subtraction procedure is elaborated after wavelet filtering. Instead of resorting to a reference signal as in the majority of papers in the literature, the new method estimates the power spectral density of the in-band noise from the associated PF. The effectiveness of the proposed method is validated using simulated data, test rig data, and vibration data recorded from the transmission system of a helicopter. The experimental results and comparisons with other methods indicate that the proposed method is an effective approach to detecting the fault-related impulses

  8. Fault detection of a spur gear using vibration signal with multivariable statistical parameters

    Directory of Open Access Journals (Sweden)

    Songpon Klinchaeam

    2014-10-01

    Full Text Available This paper presents a condition monitoring technique of a spur gear fault detection using vibration signal analysis based on time domain. Vibration signals were acquired from gearboxes and used to simulate various faults on spur gear tooth. In this study, vibration signals were applied to monitor a normal and various fault conditions of a spur gear such as normal, scuffing defect, crack defect and broken tooth. The statistical parameters of vibration signal were used to compare and evaluate the value of fault condition. This technique can be applied to set alarm limit of the signal condition based on statistical parameter such as variance, kurtosis, rms and crest factor. These parameters can be used to set as a boundary decision of signal condition. From the results, the vibration signal analysis with single statistical parameter is unclear to predict fault of the spur gears. The using at least two statistical parameters can be clearly used to separate in every case of fault detection. The boundary decision of statistical parameter with the 99.7% certainty ( 3   from 300 referenced dataset and detected the testing condition with 99.7% ( 3   accuracy and had an error of less than 0.3 % using 50 testing dataset.

  9. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor

    2016-08-01

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

  10. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor

    2016-08-26

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

  11. Rolling Bearing Fault Detection Based on the Teager Energy Operator and Elman Neural Network

    Directory of Open Access Journals (Sweden)

    Hongmei Liu

    2013-01-01

    Full Text Available This paper presents an approach to bearing fault diagnosis based on the Teager energy operator (TEO and Elman neural network. The TEO can estimate the total mechanical energy required to generate signals, thereby resulting in good time resolution and self-adaptability to transient signals. These attributes reflect the advantage of detecting signal impact characteristics. To detect the impact characteristics of the vibration signals of bearing faults, we used the TEO to extract the cyclical impact caused by bearing failure and applied the wavelet packet to reduce the noise of the Teager energy signal. This approach also enabled the extraction of bearing fault feature frequencies, which were identified using the fast Fourier transform of Teager energy. The feature frequencies of the inner and outer faults, as well as the ratio of resonance frequency band energy to total energy in the Teager spectrum, were extracted as feature vectors. In order to avoid a frequency leak error, the weighted Teager spectrum around the fault frequency was extracted as feature vector. These vectors were then used to train the Elman neural network and improve the robustness of the diagnostic algorithm. Experimental results indicate that the proposed approach effectively detects bearing faults under variable conditions.

  12. Fault Detection and Localization in Transmission Lines with a Static Synchronous Series Compensator

    Directory of Open Access Journals (Sweden)

    REYES-ARCHUNDIA, E.

    2015-08-01

    Full Text Available This paper proposes a fault detection and localization method for power transmission lines with a Static Synchronous Series Compensator (SSSC. The algorithm is based on applying a modal transformation to the current and voltage signals sampled at high frequencies. Then, the wavelet transform is used for calculating the current and voltage traveling waves, avoiding low frequency interference generated by the system and the SSSC. Finally, by using reflectometry principles, straightforward expressions for fault detection and localization in the transmission line are derived. The algorithm performance was tested considering several study cases, where some relevant parameters such as voltage compensation level, fault resistance and fault inception angle are varied. The results indicate that the algorithm can be successfully be used for fault detection and localization in transmission lines compensated with a SSSC. The estimated error in calculating the distance to the fault is smaller than 1% of the transmission line length. The test system is simulated in PSCAD platform and the algorithm is implemented in MATLAB software.

  13. Fault Detection Enhancement in Rolling Element Bearings via Peak-Based Multiscale Decomposition and Envelope Demodulation

    Directory of Open Access Journals (Sweden)

    Hua-Qing Wang

    2014-01-01

    Full Text Available Vibration signals of rolling element bearings faults are usually immersed in background noise, which makes it difficult to detect the faults. Wavelet-based methods being used commonly can reduce some types of noise, but there is still plenty of room for improvement due to the insufficient sparseness of vibration signals in wavelet domain. In this work, in order to eliminate noise and enhance the weak fault detection, a new kind of peak-based approach combined with multiscale decomposition and envelope demodulation is developed. First, to preserve effective middle-low frequency signals while making high frequency noise more significant, a peak-based piecewise recombination is utilized to convert middle frequency components into low frequency ones. The newly generated signal becomes so smoother that it will have a sparser representation in wavelet domain. Then a noise threshold is applied after wavelet multiscale decomposition, followed by inverse wavelet transform and backward peak-based piecewise transform. Finally, the amplitude of fault characteristic frequency is enhanced by means of envelope demodulation. The effectiveness of the proposed method is validated by rolling bearings faults experiments. Compared with traditional wavelet-based analysis, experimental results show that fault features can be enhanced significantly and detected easily by the proposed method.

  14. Detecting and isolating faults of an air-handling unit using on- line diagnostic tests

    Energy Technology Data Exchange (ETDEWEB)

    Pakanen, J. [VTT Building Technology, Espoo (Finland). Building Services and Fire Technology

    1996-12-31

    On-line diagnostic testing is one choice, when practical and robust fault detection and isolation methods are considered for automated processes. Performing a test means exciting a process by means of prescribed input signals, supervising responses and comparing results with a process model. An on-line diagnostic test is repeated similarly every time, in similar process conditions, making modelling an uncomplicated task. Fault detection is a direct consequence of the comparison, but fault isolation is based on elementary constraints, decomposed from the process model. A rough description of a fault can be achieved by heuristic reasoning, which enables application of the method in practice. A more specified fault description is accomplished by learning from old solutions. The reasoner accumulates information making decisions of the classifier gradually more precise through acquired experience. The method is best for successive installations, in which knowledge can be cumulated. On-line diagnostic tests are generic in character, but in this paper they are configured for an air handling unit of an office building and applied in its preheating subprocess. The paper presents the development, simulation and field tests of the fault detection and isolation method and its configuration as a part of a diagnostic system. (orig.) (35 refs.)

  15. Fault Detection of a Wheelset Bearing Based on Appropriately Sparse Impulse Extraction

    Directory of Open Access Journals (Sweden)

    Jianming Ding

    2017-01-01

    Full Text Available Convolution sparse representation (CSR is a novel compressive sensing technique proposed in 2016 and provides an excellent framework for extracting the impulses induced by bearing faults and the unevenness of wheel tread. However, its sparsity performance on extracting impulses is sensitive to the improper penalty parameter. So, a novel fault detection method, appropriately sparse impulse extraction, is proposed based on the combination of CSR, estimating the number of atom types (ENA, and crest factor. The type of atoms embedded in vibration signals is estimated by ENA. Aiming at the different types of atoms, the impulses with different sparse characteristic are spanned by CSR with different penalty parameters. The appropriately sparse impulses are selected for fault detection based on the maximal crest factor. The simulation validation, experiment verification, and practical application are conducted to validate the effectiveness of the proposed appropriately sparse impulses extraction. These results show that the proposed appropriately sparse impulse extraction not only can obtain fault-characteristic frequency and its harmonics for fault judgment but also describes the dynamic behaviour between elementary defects and their matching surfaces. In addition, the proposed appropriately sparse impulse extraction can isolate the impulses with different types of atoms and is very suitable for detecting the wheelset bearing faults.

  16. A Novel Protection Method for Single Line-to-Ground Faults in Ungrounded Low-Inertia Microgrids

    Directory of Open Access Journals (Sweden)

    Liuming Jing

    2016-06-01

    Full Text Available This paper proposes a novel protection method for single line-to-ground (SLG faults in ungrounded low-inertia microgrids. The proposed method includes microgrid interface protection and unit protection. The microgrid interface protection is based on the difference between the zero-sequence voltage angle and the zero-sequence current angle at the microgrid interconnection transformer for fast selection of the faulty feeder. The microgrid unit protection is based on a comparison of the three zero-sequence current phase directions at each junction point of load or distributed energy resources. Methods are also included to locate the minimum fault section. The fault section location technology operates according to the coordination of microgrid unit protection. The proposed method responds to SLG faults that may occur in both the grid and the microgrid. Simulations of an ungrounded low-inertia microgrid with a relay model were carried out using Power System Computer Aided Design (PSCAD/Electromagnetic Transients including DC (EMTDC.

  17. Improved Data-based Fault Detection Strategy and Application to Distillation Columns

    KAUST Repository

    Madakyaru, Muddu

    2017-01-31

    Chemical and petrochemical processes require continuous monitoring to detect abnormal events and to sustain normal operations. Furthermore, process monitoring enhances productivity, efficiency, and safety in process industries. Here, we propose an innovative statistical approach that exploits the advantages of multiscale partial least squares (MSPLS) models and generalized likelihood ratio (GLR) tests for fault detection in processes. Specifically, we combine an MSPLS algorithm with wavelet analysis to create our modeling framework. Then, we use GLR hypothesis testing based on the uncorrelated residuals obtained from the MSPLS model to improve fault detection. We use simulated distillation column data to evaluate the MSPLS-based GLR chart. Results show that our MSPLS-based GLR method is more powerful than the PLS-based Q and GLR method and MSPLS-based Q method, especially in early detection of small faults with abrupt or incipient behavior.

  18. A hybrid fault detection and isolation strategy for a team of cooperating unmanned vehicles

    Science.gov (United States)

    Tousi, M. M.; Khorasani, K.

    2015-01-01

    In this paper, a hybrid fault detection and isolation (FDI) methodology is developed for a team of cooperating unmanned vehicles. The proposed approach takes advantage of the cooperative nature of the team to detect and isolate relatively low-severity actuator faults that are otherwise not detectable and isolable by the vehicles themselves individually. The approach is hybrid and consists of both low-level (agent/team level) and high-level [discrete-event systems (DES) level] FDI modules. The high-level FDI module is formulated in the DES supervisory control framework, whereas the low-level FDI module invokes classical FDI techniques. By properly integrating the two FDI modules, a larger class of faults can be detected and isolated as compared to the existing techniques in the literature that rely on each level separately. Simulation results for a team of five unmanned aerial vehicles are also presented to demonstrate the effectiveness and capabilities of our proposed methodology.

  19. Distributed Fault Detection and Isolation for Flocking in a Multi-robot System with Imperfect Communication

    Directory of Open Access Journals (Sweden)

    Shao Shiliang

    2014-06-01

    Full Text Available In this paper, we focus on distributed fault detection and isolation (FDI for a multi-robot system where multiple robots execute a flocking task. Firstly, we propose a fault detection method based on the local-information-exchange and sensor-measurement technologies to cover cases of both perfect communication and imperfect communication. The two detection technologies can be adaptively selected according to the packet loss rate (PLR. Secondly, we design a fault isolation method, considering a situation in which faulty robots still influence the behaviours of other robots. Finally, a complete FDI scheme, based on the proposed detection and isolation methods, is simulated in various scenarios. The results demonstrate that our FDI scheme is effective.

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

    Directory of Open Access Journals (Sweden)

    Byung Eun Lee

    2014-09-01

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

  1. Implementation of a high-impedance fault detection algorithm. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Balser, S.J.; Lawrence, D.J.; Caprino, B.; Delaney, L.

    1985-05-01

    A digital computer based algorithm was developed to detect high impedance faults on distribution systems using statistical methods. The algorithm is written in PL/M 86 and PASCAL and implemented on an INTEL SYS380 microcomputer system, designed to operate in real time and interface with acquisition software. The report contains a description of the calculation procedures comprising the detection algorithm, implementation requirements, and test results for algorithm verification. A discussion of hardware limitations and an estimation of fault detection rate based on historical records is also presented.

  2. Fault detection based on H∞ states observer for networked control systems

    Institute of Scientific and Technical Information of China (English)

    Zhu Zhangqing; Jiao Xiaocheng

    2009-01-01

    The influence of random short time-delay to networked control systems (NCS) is changed into an unknown bounded uncertain part. Without changing the structure of the system, an H∞ states observer is designed for NCS with short time-delay. Based on the designed states observer, a robust fault detection approach is proposed for NCS. In addition, an optimization method for the selection of the detection threshold is introduced for better tradeoff between the robustness and the sensitivity. Finally, some simulation results demonstrate that the presented states observer is robust and the fault detection for NCS is effective.

  3. Compressive Sensing of Roller Bearing Faults via Harmonic Detection from Under-Sampled Vibration Signals.

    Science.gov (United States)

    Tang, Gang; Hou, Wei; Wang, Huaqing; Luo, Ganggang; Ma, Jianwei

    2015-10-09

    The Shannon sampling principle requires substantial amounts of data to ensure the accuracy of on-line monitoring of roller bearing fault signals. Challenges are often encountered as a result of the cumbersome data monitoring, thus a novel method focused on compressed vibration signals for detecting roller bearing faults is developed in this study. Considering that harmonics often represent the fault characteristic frequencies in vibration signals, a compressive sensing frame of characteristic harmonics is proposed to detect bearing faults. A compressed vibration signal is first acquired from a sensing matrix with information preserved through a well-designed sampling strategy. A reconstruction process of the under-sampled vibration signal is then pursued as attempts are conducted to detect the characteristic harmonics from sparse measurements through a compressive matching pursuit strategy. In the proposed method bearing fault features depend on the existence of characteristic harmonics, as typically detected directly from compressed data far before reconstruction completion. The process of sampling and detection may then be performed simultaneously without complete recovery of the under-sampled signals. The effectiveness of the proposed method is validated by simulations and experiments.

  4. Fault Detection of Inline Reciprocating Diesel Engine: A Mass and Gas-Torque Approach

    Directory of Open Access Journals (Sweden)

    S. H. Gawande

    2012-01-01

    Full Text Available Early fault detection and diagnosis for medium-speed diesel engines are important to ensure reliable operation throughout the course of their service. This work presents an investigation of the diesel engine combustion-related fault detection capability of crankshaft torsional vibrations. Proposed methodology state the way of early fault detection in the operating six-cylinder diesel engine. The model of six cylinders DI Diesel engine is developed appropriately. As per the earlier work by the same author the torsional vibration amplitudes are used to superimpose the mass and gas torque. Further mass and gas torque analysis is used to detect fault in the operating engine. The DFT of the measured crankshaft’s speed, under steady-state operating conditions at constant load shows significant variation of the amplitude of the lowest major harmonic order. This is valid both for uniform operating and faulty conditions and the lowest harmonic orders may be used to correlate its amplitude to the gas pressure torque and mass torque for a given engine. The amplitudes of the lowest harmonic orders (0.5, 1, and 1.5 of the gas pressure torque and mass torque are used to map the fault. A method capable to detect faulty cylinder of operating Kirloskar diesel engine of SL90 Engine-SL8800TA type is developed, based on the phases of the lowest three harmonic orders.

  5. E-core transverse flux machine with integrated fault detection system

    DEFF Research Database (Denmark)

    Rasmussen, Peter Omand; Runólfsson, Gunnar; Thorsdóttir, Thórunn Ágústa;

    2011-01-01

    circuit faults have been developed. For other types of machines the single and partial turn short circuit is very difficult to deal with and requires normally very comprehensive detection and calculation schemes. The developed detection algorithm combined with the E-core transverse flux machine...

  6. Observer-based Fault Detection and Isolation for Nonlinear Systems

    DEFF Research Database (Denmark)

    Lootsma, T.F.

    . Then the geometric approach is applied to a nonlinear ship propulsion system benchmark. The calculations and application results are presented in detail to give an illustrative example. The obtained subsystems are considered for the design of nonlinear observers in order to obtain FDI. Additionally, an adaptive...... for the observers designed for the ship propulsion system. Furthermore, it stresses the importance of the time-variant character of the linearization along a trajectory. It leads to a different stability analysis than for linearization at one operation point. Finally, the preliminary concept of (actuator) fault...

  7. Application of Residual-Based EWMA Control Charts for Detecting Faults in Variable-Air-Volume Air Handling Unit System

    OpenAIRE

    Haitao Wang

    2016-01-01

    An online robust fault detection method is presented in this paper for VAV air handling unit and its implementation. Residual-based EWMA control chart is used to monitor the control processes of air handling unit and detect faults of air handling unit. In order to provide a level of robustness with respect to modeling errors, control limits are determined by incorporating time series model uncertainty in EWMA control chart. The fault detection method proposed was tested and validated using re...

  8. The ground truth about metadata and community detection in networks

    CERN Document Server

    Peel, Leto; Clauset, Aaron

    2016-01-01

    Across many scientific domains, there is common need to automatically extract a simplified view or a coarse-graining of how a complex system's components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called \\textit{ground truth} communities. This works well in synthetic networks with planted communities because such networks' links are formed explicitly based on the planted communities. However, there are no planted communities in real world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. Here, we show that metadata are not the same as ground truth, and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch the...

  9. Comprehensive bearing condition monitoring algorithm for incipient fault detection using acoustic emission

    Directory of Open Access Journals (Sweden)

    Amit R. Bhende

    2014-09-01

    Full Text Available The bearing reliability plays major role in obtaining the desired performance of any machine. A continuous condition monitoring of machine is required in certain applications where failure of machine leads to loss of production, human safety and precision. Machine faults are often linked to the bearing faults. Condition monitoring of machine involves continuous watch on the performance of bearings and predicting the faults of bearing before it cause any adversity. This paper investigates an experimental study to diagnose the fault while bearing is in operation. An acoustic emission technique is used in the experimentation. An algorithm is developed to process various types of signals generated from different bearing defects. The algorithm uses time domain analysis along with combination low frequency analysis technique such as fast Fourier transform and high frequency envelope detection. Two methods have adopted for envelope detection which are Hilbert transform and order analysis. Experimental study is carried out for deep groove ball bearing cage defect. Results show the potential effectiveness of the proposed algorithm to determine presence of fault, exact location and severity of fault.

  10. Bispectrum of stator phase current for fault detection of induction motor.

    Science.gov (United States)

    Treetrong, Juggrapong; Sinha, Jyoti K; Gu, Fengshu; Ball, Andrew

    2009-07-01

    A number of research studies has shown that faults in a stator or rotor generally show sideband frequencies around the mains frequency (50 Hz) and at higher harmonics in the spectrum of the Motor Current Signature Analysis (MCSA). However in the present experimental studies such observations have not been seen, but any fault either in the stator or the rotor may distort the sinusoidal response of the motor RPM and the mains frequency so the MCSA response may contain a number of harmonics of the motor RPM and the mains frequency. Hence the use of a higher order spectrum (HOS), namely the bispectrum of the MCSA has been proposed here because it relates both amplitude and phase of number of the harmonics in a signal. It has been observed that it not only detects early faults but also indicates the severity of the fault to some extent.

  11. Robust unknown input observer design for state estimation and fault detection using linear parameter varying model

    Science.gov (United States)

    Li, Shanzhi; Wang, Haoping; Aitouche, Abdel; Tian, Yang; Christov, Nicolai

    2017-01-01

    This paper proposes a robust unknown input observer for state estimation and fault detection using linear parameter varying model. Since the disturbance and actuator fault is mixed together in the physical system, it is difficult to isolate the fault from the disturbance. Using the state transforation, the estimation of the original state becomes to associate with the transform state. By solving the linear matrix inequalities (LMIs)and linear matrix equalities (LMEs), the parameters of the UIO can be obtained. The convergence of the UIO is also analysed by the Layapunov theory. Finally, a wind turbine system with disturbance and actuator fault is tested for the proposed method. From the simulations, it demonstrates the effectiveness and performances of the proposed method.

  12. Design of a novel knowledge-based fault detection and isolation scheme.

    Science.gov (United States)

    Zhao, Qing; Xu, Zhihan

    2004-04-01

    In this paper, a real-time fault detection and isolation (FDI) scheme for dynamical systems is developed, by integrating the signal processing technique with neural network design. Wavelet analysis is applied to capture the fault-induced transients of the measured signals in real-time, and the decomposed signals are pre-processed to extract details about a fault. A Regional Self-Organizing feature Map (R-SOM) neural network is synthesized to classify the fault types. The R-SOM neural network adopts two regions adjustment in the learning algorithm, thus it has high precision in clustering and matching, especially when the noise, disturbance and other uncertainties exist in the systems. As a result, the proposed FDI scheme is robust and accurate. The design is implemented on a stirred tank system and satisfactory online testing results are obtained.

  13. Improved nonlinear fault detection strategy based on the Hellinger distance metric: Plug flow reactor monitoring

    KAUST Repository

    Harrou, Fouzi

    2017-03-18

    Fault detection has a vital role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. This paper proposes an innovative multivariate fault detection method that can be used for monitoring nonlinear processes. The proposed method merges advantages of nonlinear projection to latent structures (NLPLS) modeling and those of Hellinger distance (HD) metric to identify abnormal changes in highly correlated multivariate data. Specifically, the HD is used to quantify the dissimilarity between current NLPLS-based residual and reference probability distributions obtained using fault-free data. Furthermore, to enhance further the robustness of these methods to measurement noise, and reduce the false alarms due to modeling errors, wavelet-based multiscale filtering of residuals is used before the application of the HD-based monitoring scheme. The performances of the developed NLPLS-HD fault detection technique is illustrated using simulated plug flow reactor data. The results show that the proposed method provides favorable performance for detection of faults compared to the conventional NLPLS method.

  14. Fault detection of excavator's hydraulic system based on dynamic principal component analysis

    Institute of Scientific and Technical Information of China (English)

    HE Qing-hua; HE Xiang-yu; ZHU Jian-xin

    2008-01-01

    In order to improve reliability of the excavator's hydraulic system, a fault detection approach based on dynamic principal component analysis(PCA) was proposed. Dynamic PCA is an extension of PCA, which can effectively extract the dynamic relations among process variables. With this approach, normal samples were used as training data to develop a dynamic PCA model in the first step. Secondly, the dynamic PCA model decomposed the testing data into projections to the principal component subspace(PCS) and residual subspace(RS). Thirdly, T2 statistic and Q statistic performed as indexes of fault detection in PCS and RS, respectively.Several simulated faults were introduced to validate the approach. The results show that the dynamic PCA model developed is able to detect overall faults by using T2 statistic and Q statistic. By simulation analysis, the proposed approach achieves an accuracy of 95% for 20 test sample sets, which shows that the fault detection approach can be effectively applied to the excavator's hydraulic system.

  15. GMDH and neural networks applied in monitoring and fault detection in sensors in nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia, Guarulhos, SP (Brazil); Pereira, Iraci Martinez; Silva, Antonio Teixeira e, E-mail: martinez@ipen.b, E-mail: teixeira@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

    In this work a new monitoring and fault detection methodology was developed using GMDH (Group Method of Data Handling) algorithm and artificial neural networks (ANNs) which was applied in the IEA-R1 research reactor at IPEN. The monitoring and fault detection system was developed in two parts: the first was dedicated to preprocess information, using GMDH algorithm; and the second to the process information using ANNs. The preprocess information was divided in two parts. In the first part, the GMDH algorithm was used to generate a better database estimate, called matrix z, which was used to train the ANNs. In the second part the GMDH was used to study the best set of variables to be used to train the ANNs, resulting in a best monitoring variable estimative. The methodology was developed and tested using five different models: one theoretical model and for models using different sets of reactor variables. After an exhausting study dedicated to the sensors monitoring, the fault detection in sensors was developed by simulating faults in the sensors database using values of +5%, +10%, +15% and +20% in these sensors database. The good results obtained through the present methodology shows the viability of using GMDH algorithm in the study of the best input variables to the ANNs, thus making possible the use of these methods in the implementation of a new monitoring and fault detection methodology applied in sensors. (author)

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

    Science.gov (United States)

    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.

  17. Ground-motion modeling of Hayward fault scenario earthquakes, part I: Construction of the suite of scenarios

    Science.gov (United States)

    Aagaard, Brad T.; Graves, Robert W.; Schwartz, David P.; Ponce, David A.; Graymer, Russell W.

    2010-01-01

    We construct kinematic earthquake rupture models for a suite of 39 Mw 6.6-7.2 scenario earthquakes involving the Hayward, Calaveras, and Rodgers Creek faults. We use these rupture models in 3D ground-motion simulations as discussed in Part II (Aagaard et al., 2010) to provide detailed estimates of the shaking for each scenario. We employ both geophysical constraints and empirical relations to provide realistic variation in the rupture dimensions, slip heterogeneity, hypocenters, rupture speeds, and rise times. The five rupture lengths include portions of the Hayward fault as well as combined rupture of the Hayward and Rodgers Creek faults and the Hayward and Calaveras faults. We vary rupture directivity using multiple hypocenters, typically three per rupture length, yielding north-to-south rupture, bilateral rupture, and south-to-north rupture. For each rupture length and hypocenter, we consider multiple random distributions of slip. We use two approaches to account for how aseismic creep might reduce coseismic slip. For one subset of scenarios, we follow the slip-predictable approach and reduce the nominal slip in creeping regions according to the creep rate and time since the most recent earthquake, whereas for another subset of scenarios we apply a vertical gradient to the nominal slip in creeping regions. The rupture models include local variations in rupture speed and use a ray-tracing algorithm to propagate the rupture front. Although we are not attempting to simulate the 1868 Hayward fault earthquake in detail, a few of the scenarios are designed to have source parameters that might be similar to this historical event.

  18. Fault detection and optimization for networked control systems with uncertain time-varying delay

    Institute of Scientific and Technical Information of China (English)

    Qing Wang; Zhaolei Wang; Chaoyang Dong; Erzhuo Niu

    2015-01-01

    The observer-based robust fault detection filter design and optimization for networked control systems (NCSs) with uncer-tain time-varying delays are addressed. The NCSs with uncertain time-varying delays are modeled as parameter-uncertain systems by the matrix theory. Based on the model, an observer-based residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of the linear matrix inequality. Furthermore, a time domain opti-mization approach is proposed to improve the performance of the fault detection system. To prevent the false alarms, a new thresh-old function is established, and the solution of the optimization problem is given by using the singular value decomposition (SVD) of the matrix. A numerical example is provided to il ustrate the effectiveness of the proposed approach.

  19. Effective confidence interval estimation of fault-detection process of software reliability growth models

    Science.gov (United States)

    Fang, Chih-Chiang; Yeh, Chun-Wu

    2016-09-01

    The quantitative evaluation of software reliability growth model is frequently accompanied by its confidence interval of fault detection. It provides helpful information to software developers and testers when undertaking software development and software quality control. However, the explanation of the variance estimation of software fault detection is not transparent in previous studies, and it influences the deduction of confidence interval about the mean value function that the current study addresses. Software engineers in such a case cannot evaluate the potential hazard based on the stochasticity of mean value function, and this might reduce the practicability of the estimation. Hence, stochastic differential equations are utilised for confidence interval estimation of the software fault-detection process. The proposed model is estimated and validated using real data-sets to show its flexibility.

  20. Broken Bar Fault Detection in IM Operating Under No-Load Condition

    Directory of Open Access Journals (Sweden)

    RELJIC, D.

    2016-11-01

    Full Text Available This paper presents a novel method for broken rotor bar detection in a squirrel-cage induction motor (IM. The proposed method applies a single-phase AC voltage as a test signal on motor terminals, resulting in a stator backward-rotating magnetic field. The field ultimately causes additional current components in the stator windings whose magnitudes depend on the broken bar fault severity, even if the motor is unloaded. This allows robust broken bar fault detection based only on standard motor current signature analysis (MCSA technique. The proposed fault detection method is at first verified via simulations, using an IM model based on finite element analysis (FEA and multiple coupled circuit approach (MCCA. The subsequent experimental investigations have shown good agreement with both theoretical predictions and simulation results.

  1. Open-switch fault detection method of an NPC converter for wind turbine systems

    DEFF Research Database (Denmark)

    Lee, June-Seok; Lee, Kyo-Beum; Blaabjerg, Frede

    2013-01-01

    In wind turbine generation (WTG) systems, the neutral-point-clamped (NPC) topology is widely used as the part of a back-to-back converter since the three-level NPC topology has more advantages than the conventional two-level inverter especially for high power. There are twelve switches in the NPC...... topology and an open-switch fault of the NPC converter leads to current distortion and the torque ripple in the system. Furthermore, WTG systems can breakdown in the worst case by this ripple. To improve the reliability of WTG systems, an open-switch fault detection method is required. The open......-switch detection method of the NPC converter is different from that of the NPC inverter due to the different current paths of the NPC converter. This paper proposes the open-switch fault detection method of the NPC converter connected the permanent-magnet synchronous generator (PMSG). Moreover, the open...

  2. Data-driven fault detection for industrial processes canonical correlation analysis and projection based methods

    CERN Document Server

    Chen, Zhiwen

    2017-01-01

    Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed. Contents A New Index for Performance Evaluation of FD Methods CCA-based FD Method for the Monitoring of Stationary Processes Projection-based FD Method for the Monitoring of Dynamic Processes Benchmark Study and Real-Time Implementat...

  3. Nuclear power plant sensor fault detection using singular value decomposition-based method

    Indian Academy of Sciences (India)

    SHYAMAPADA MANDAL; N SAIRAM; S SRIDHAR; P SWAMINATHAN

    2017-09-01

    In a nuclear power plant, periodic sensor calibration is necessary to ensure the correctness of measurements. Those sensors which have gone out of calibration can lead to malfunction of the plant, possibly causing a loss in revenue or damage to equipment. Continuous sensor status monitoring is desirable to assure smooth running of the plant and reduce maintenance costs associated with unnecessary manual sensor calibrations.In this paper, a method is proposed to detect and identify any degradation of sensor performance. The validation process consists of two steps: (i) residual generation and (ii) fault detection by residual evaluation.Singular value decomposition (SVD) and Euclidean distance (ED) methods are used to generate the residual and evaluate the fault on the residual space, respectively. This paper claims that SVD-based fault detection method isbetter than the well-known principal component analysis-based method. The method is validated using data from fast breeder test reactor.

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

    Science.gov (United States)

    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

  5. STRONG GROUND MOTION PREDICTION OF URUMQI ACTIVE FAULT%乌鲁木齐市活断层强地面运动预测研究

    Institute of Scientific and Technical Information of China (English)

    沈军; 宋和平; 赵伯明

    2009-01-01

    The paper introduced the strong ground motion prediction results based on seismo-tectonic model of Urumqi active fault. During detecting active fault and assessing earthquake risk in Urumqi, two seismo-tectonics models were set. They were thrust nappe structure in front of northern Tienshan Mountain and in west side of Bogeda arcuate structure respectively. The possible max-magnitude of the former was about 7.5 and that of the latter was about 7.0, so the analytical or computational model was established. According to analysis result of microtremor observation, combined with shallow seismic exploration, geological map, topographic map and borehole data, the underground three dimensional speed model was founded. The statistical Green function, 3D finite-difference and hybrid computation methods were used to research ground motion in target area. The prediction result showed the structure of fault, mode of fault failure and three dimensional speed model influenced the distribution of ground motion obviously. The ground motion was evident along fault front, basin margin, in the area with thicker covering layer and front of fault failure.%介绍了基于乌鲁木齐活断层发震构造模型的强地面运动的预测结果.该项工作是在乌鲁木齐城区开展的活断层探测与地震危险性评价的基础上,设定了两个发震构造,分别为北天山山前逆冲推覆构造和博格达弧西翼逆冲推覆构造,前者可能最大地震震级为7.5级,后者为7.0级,据此建立了分析计算模型.根据地脉动观测分析结果,结合浅层地震勘探、地质图、地形图和钻孔资料,建立了地下三维速度模型,采用统计学的格林函数法、三维有限差分法和混合计算方法,对目标区的地震动进行了预测研究.预测结果表明,断层的结构、破裂方式和三维速度模型对地震动的分布具有显著的影响.沿断层前缘、盆地边缘、覆盖层较厚的地区,以及断层破裂的前方地震动比较显著.

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

    Institute of Scientific and Technical Information of China (English)

    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 representation of the signal. Once the instants are detected, the distribution differences of the signal energy on all decomposed wavelet scales of the signal before and after the instants are used to claim and classify the sensor faults.

  7. Sensor fault detection and isolation in doubly-fed induction generators accounting for parameter variations

    Energy Technology Data Exchange (ETDEWEB)

    Galvez-Carrillo, Manuel; Kinnaert, Michel [Dept. of Control Engineering and System Analysis, Universite Libre de Bruxelles (ULB), 50 Av. F.D. Roosevelt, CP 165/55, B-1050 Brussels (Belgium)

    2011-05-15

    A fault detection and isolation (FDI) system for monitoring rotor current sensors in a doubly-fed induction generator (DFIG) for wind turbine applications is presented. The FDI system is designed so that the effect of parameter variations (resistances and inductances) is minimized. The residual generation is based on the generalized observer scheme (GOS) including parameter estimation. A decision system made of a combination of vector CUSUM (Cumulative sum) algorithms is used to process the residual vector and to achieve detection and isolation of incipient (small magnitude) faults. The approach is validated using signals obtained from a simulated vector-controlled DFIG. (author)

  8. A Desk-top tutorial Demonstration of Model-based Fault Detection and Diagnosis

    OpenAIRE

    Shi, John Z.; Elshanti, Ali; Gu, Fengshou; Ball, Andrew

    2007-01-01

    In this paper, a demonstration on the model-based approach for fault detection has been presented. The aim of this demo is to provide students a desk-top tool to start learning model-based approach. The demo works on a traditional three-tank system. After a short review of the model-based approach, this paper emphasizes on two difficulties often asked by students when they start learning model-based approach: how to develop a system model and how to generate residual for fault detection. The ...

  9. Architecture for Intrusion Detection System with Fault Tolerance Using Mobile Agent

    Directory of Open Access Journals (Sweden)

    Chintan Bhatt

    2011-10-01

    Full Text Available This paper is a survey of the work, done for making an IDS fault tolerant.Architecture of IDS that usesmobile Agent provides higher scalability. Mobile Agent uses Platform for detecting Intrusions using filterAgent, co-relater agent, Interpreter agent and rule database. When server (IDS Monitor goes down,other hosts based on priority takes Ownership. This architecture uses decentralized collection andanalysis for identifying Intrusion. Rule sets are fed based on user-behaviour or applicationbehaviour.This paper suggests that intrusion detection system (IDS must be fault tolerant; otherwise, theintruder may first subvert the IDS then attack the target system at will.

  10. On Optimal Fault Detection for Discrete-time Markovian Jump Linear Systems

    Institute of Scientific and Technical Information of China (English)

    LI Yue-Yang; ZHONG Mai-Ying

    2013-01-01

    This paper deals with the problem of fault detection for discrete-time Markovian jump linear systems (MJLS).Using an observer-based fault detection filter (FDF) as a residual generator,the design of the FDF is formulated as an optimization problem for maximizing stochastic H_/H∞ or H∞/H∞ performance index.With the aid of an operator optimization method,it is shown that a unified optimal solution can be derived by solving a coupled Riccati equation.Numerical examples are given to show the effectiveness of the proposed method.

  11. Testing of ground fault relay response during the energisation of megawatt range electric boilers in thermal power plants

    DEFF Research Database (Denmark)

    Silva, Filipe Miguel Faria da; Bak, Claus Leth; Davidsen, Troels

    2015-01-01

    , during the energisation of a boiler. A special case for concern was the presence of an electric arc between the electrodes of the boiler and the water in the boiler during approximately 2s at the energisation, which can in theory be seen as a ground fault by the relay. The voltage and current transient......Large controllable loads may support power systems with an increased penetration of fluctuating renewable energy, by providing a rapid response to a change in the power production. Megawatt range electric boilers are an example of such controllable loads, capable of change rapidly...

  12. Detection of Stator Winding Fault in Induction Motor Using Fuzzy Logic with Optimal Rules

    Directory of Open Access Journals (Sweden)

    Hamid Fekri Azgomi

    2013-04-01

    Full Text Available Induction motors are critical components in many industrial processes. Therefore, swift, precise and reliable monitoring and fault detection systems are required to prevent any further damages. The online monitoring of induction motors has been becoming increasingly important. The main difficulty in this task is the lack of an accurate analytical model to describe a faulty motor. A fuzzy logic approach may help to diagnose traction motor faults. This paper presents a simple method for the detection of stator winding faults (which make up 38% of induction motor failures based on monitoring the line/terminal current amplitudes. In this method, fuzzy logic is used to make decisions about the stator motor condition. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. The motor condition is described using linguistic variables. Fuzzy subsets and the corresponding membership functions describe stator current amplitudes. A knowledge base, comprising rule and data bases, is built to support the fuzzy inference. Simulation results are presented to verify the accuracy of motor’s fault detection and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis.

  13. Model-based robust estimation and fault detection for MEMS-INS/GPS integrated navigation systems

    Directory of Open Access Journals (Sweden)

    Miao Lingjuan

    2014-08-01

    Full Text Available In micro-electro-mechanical system based inertial navigation system (MEMS-INS/global position system (GPS integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation (RE and fault detection (FD. A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.

  14. Model-based robust estimation and fault detection for MEMS-INS/GPS integrated navigation systems

    Institute of Scientific and Technical Information of China (English)

    Miao Lingjuan; Shi Jing

    2014-01-01

    In micro-electro-mechanical system based inertial navigation system (MEMS-INS)/global position system (GPS) integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust esti-mation (RE) and fault detection (FD). A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing pri-ori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range;with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of distur-bances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.

  15. Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

    Science.gov (United States)

    Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

    2016-12-08

    This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

  16. Simple random sampling-based probe station selection for fault detection in wireless sensor networks.

    Science.gov (United States)

    Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

    2011-01-01

    Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate.

  17. Fault Detection of Wind Turbines with Uncertain Parameters: A Set-Membership Approach

    Directory of Open Access Journals (Sweden)

    Thomas Bak

    2012-07-01

    Full Text Available In this paper a set-membership approach for fault detection of a benchmark wind turbine is proposed. The benchmark represents relevant fault scenarios in the control system, including sensor, actuator and system faults. In addition we also consider parameter uncertainties and uncertainties on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach is used generate a set that contains all states consistent with the past measurements and the given model of the wind turbine including uncertainties and noise. This set represents all possible states the system can be in if not faulty. If the current measurement is not consistent with this set, a fault is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness of the proposed method compared to other proposed methods applied to the same problem. An advantage of the proposed method is that there is no need for threshold design, and it does not produce positive false alarms. In the case where uncertainty on the torque lookup table is introduced, some faults are not detectable. Previous research has not addressed this uncertainty. The method proposed here requires equal or less detection time than previous results.

  18. Sliding mode observer based incipient sensor fault detection with application to high-speed railway traction device.

    Science.gov (United States)

    Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui

    2016-07-01

    This paper considers incipient sensor fault detection issue for a class of nonlinear systems with "observer unmatched" uncertainties. A particular fault detection sliding mode observer is designed for the augmented system formed by the original system and incipient sensor faults. The designed parameters are obtained using LMI and line filter techniques to guarantee that the generated residuals are robust to uncertainties and that sliding motion is not destroyed by faults. Then, three levels of novel adaptive thresholds are proposed based on the reduced order sliding mode dynamics, which effectively improve incipient sensor faults detectability. Case study of on the traction system in China Railway High-speed is presented to demonstrate the effectiveness of the proposed incipient senor faults detection schemes.

  19. Application of Ground Penitrating Radar Method in Pipe Laying Detection

    Institute of Scientific and Technical Information of China (English)

    史付生; 赵学军; 宁书年; 宋喜林; 何亚伟

    2003-01-01

    Ground Penetrating Radar method was used in detecting the flaws of underground pipeline. The GPR layer disturbing image was summarized by using a rational method in fieldwork and the in-door interpretation of data. The mark radar images of disturbance of slight, middle, and strong were obtained. The result shows that the radar method can not only determine the position of the concrete pipeline underground, but it can detect the laying quality of pipeline as well.

  20. Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor

    Directory of Open Access Journals (Sweden)

    Furqan Asghar

    2016-01-01

    Full Text Available Recently, electrical drives generally associate inverter and induction machine. Therefore, inverter must be taken into consideration along with induction motor in order to provide a relevant and efficient diagnosis of these systems. Various faults in inverter may influence the system operation by unexpected maintenance, which increases the cost factor and reduces overall efficiency. In this paper, fault detection and diagnosis based on features extraction and neural network technique for three-phase inverter is presented. Basic purpose of this fault detection and diagnosis system is to detect single or multiple faults efficiently. Several features are extracted from the Clarke transformed output current and used in neural network as input for fault detection and diagnosis. Hence, some simulation study as well as hardware implementation and experimentation is carried out to verify the feasibility of the proposed scheme. Results show that the designed system not only detects faults easily, but also can effectively differentiate between multiple faults. These results prove the credibility and show the satisfactory performance of designed system. Results prove the supremacy of designed system over previous feature extraction fault systems as it can detect and diagnose faults in a single cycle as compared to previous multicycles detection with high accuracy.

  1. FAULT DETECTION FOR MULTIPLE-VALUED LOGIC CIRCUITS WITH FANOUT-FREE

    Institute of Scientific and Technical Information of China (English)

    Pan Zhongliang

    2004-01-01

    The single fault and multiple fault detections for multiple-valued logic circuits are studied in this paper. Firstly, it is shown that the cardinality of optimal single fault test set for fanout-free m-valued circuits with n primary inputs is not more than n + 1, for linear tree circuits is two, and for multiplication modulo circuits is two if n is an odd number or if n is an even number and m > 3, where the optimal test set of a circuit has minimal number of test vectors. Secondly,it is indicated that the cardinality of optimal multiple fault test set for linear tree circuits with n primary inputs is 1 + [n/(m - 1)], for multiplication modulo circuits is n+ 1, for fanout-free circuits that consist of 2-input linear tree circuits and 2-input multiplication modulo circuits is not greater than n+ 1, where [x] denotes the smallest integer greater than or equal to x. Finally,the single fault location approaches of linear tree circuits and multiplication modulo circuits are presented, and all faults in the two types of circuits can be located by using a test set with n + 1 vectors.

  2. The ground truth about metadata and community detection in networks.

    Science.gov (United States)

    Peel, Leto; Larremore, Daniel B; Clauset, Aaron

    2017-05-01

    Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system's components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks' links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures.

  3. Incipient Stator Insulation Fault Detection of Permanent Magnet Synchronous Wind Generators Based on Hilbert–Huang Transformation

    DEFF Research Database (Denmark)

    Wang, Chao; Liu, Xiao; Chen, Zhe

    2014-01-01

    Incipient stator winding fault in permanent magnet synchronous wind generators (PMSWGs) is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic. This paper simulates the incipient stator winding faults at different degree...... of insulation degradation of one turn in the winding of a PMSWG. Cosimulation method by combining finite element model and external circuits is used. Hilbert–Huang transformation is applied to detect the very early stage fault in interturn insulation by analyzing the stator current. Detection results show...

  4. Fault Detection and Isolation for a Supermarket Refrigeration System - Part Two

    DEFF Research Database (Denmark)

    Yang, Zhenyu; Rasmussen, Karsten B.; Kieu, Anh T.;

    2011-01-01

    be isolated by using a bank of UIOs. Thereby, a complete FDI approach is proposed by combining the Extended-Kalman-Filter (EKF) and UIO methods, after an extensive comparison of KF-, EKF- and UIO-based FDI methods is carried out. The simulation tests show that the complete FDI approach has a good......The Fault Detection and Isolation (FDI) using the Unknown Input Observer (UIO) for a supermarket refrigeration system is investigated. The original system's state $T_{goods}$ (temp. of the goods) is regarded as a system unknown input in this study, so that the FDI decision is not disturbed...... by the system uncertainties relevant to this state dynamic and the original system disturbance $Q_{airload}$ (the thermal feature of the air). It has been observed that a single UIO has a very good detection capability for concerned sensor and parametric faults. However, only the parametric fault can...

  5. Fault detection approach based on Bond Graph observers: Hydraulic System Case Study

    Directory of Open Access Journals (Sweden)

    Ghada Saoudi

    2016-10-01

    Full Text Available The present paper deals with a bond graph procedure to design graphical observers for fault detection purpose. First of all, a bond Graph approach to build a graphical proportional observer is shown. The estimators’ performance for fault detection purpose is improved using a residual sensitivity analysis to actuator, structural and parametric faults. For uncertain bond graph models in linear fractional transformation LFT, the method is extended to build a graphical proportional-integralPI observer more robust to the presence of parameter uncertainties. The proposed methods allows the computing of the gain matrix graphically using causal paths and loops on the bond graph model of the system. As application, the method is used over a hydraulic system. The simulation results show the dynamic behavior of system variables and the performance of the developed graphical observers

  6. Robust Fault Detection of Linear Uncertain Time-Delay Systems Using Unknown Input Observers

    Directory of Open Access Journals (Sweden)

    Saeed Ahmadizadeh

    2013-01-01

    Full Text Available This paper deals with the problem of fault detection for linear uncertain time-delay systems. The proposed method for Luenberger observers is developed for unknown input observers (UIOs, and a novel procedure for the design of residual based on UIOs is presented. The design procedure is carried out based on the model matching approach which minimizes the difference between generated residuals by the optimal observer and those by the designed observer in the presence of uncertainties. The optimal observer is designed for the ideal system and works so that the fault effect is maximized while the exogenous disturbances and noise effects are minimized. This observer can give disturbance decoupling in the presence of noise and uncertainties for linear uncertain time-delay systems. The developed method is applied to a numerical example, and the simulation results show that the proposed approach is able to detect faults reliably in the presence of modeling errors, disturbances, and noise.

  7. Fault Detection Based on Tracking Differentiator Applied on the Suspension System of Maglev Train

    Directory of Open Access Journals (Sweden)

    Hehong Zhang

    2015-01-01

    Full Text Available A fault detection method based on the optimized tracking differentiator is introduced. It is applied on the acceleration sensor of the suspension system of maglev train. It detects the fault of the acceleration sensor by comparing the acceleration integral signal with the speed signal obtained by the optimized tracking differentiator. This paper optimizes the control variable when the states locate within or beyond the two-step reachable region to improve the performance of the approximate linear discrete tracking differentiator. Fault-tolerant control has been conducted by feedback based on the speed signal acquired from the optimized tracking differentiator when the acceleration sensor fails. The simulation and experiment results show the practical usefulness of the presented method.

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

    Science.gov (United States)

    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.

  9. Source parameters of the 2013, Ms 7.0, Lushan earthquake and the characteristics of the near-fault strong ground motion

    Science.gov (United States)

    Zhao, Fengfan; Meng, Lingyuan

    2016-04-01

    The April 20, 2013 Ms 7.0, earthquake in Lushan city, Sichuan province of China occurred as the result of east-west oriented reverse-type motion on a north-south striking fault. The source location suggests the event occurred on the Southern part of Longmenshan fault at a depth of 13km. The maximum intensity is up to VIII to IX at Boxing and Lushan city, which are located in the meizoseismal area. In this study, we analyzed the dynamic source process with the source mechanism and empirical relationships, estimated the strong ground motion in the near-fault field based on the Brune's circle model. A dynamical composite source model (DCSM) has been developed to simulate the near-fault strong ground motion with associated fault rupture properties at Boxing and Lushan city, respectively. The results indicate that the frictional undershoot behavior in the dynamic source process of Lushan earthquake, which is actually different from the overshoot activity of the Wenchuan earthquake. Moreover, we discussed the characteristics of the strong ground motion in the near-fault field, that the broadband synthetic seismogram ground motion predictions for Boxing and Lushan city produced larger peak values, shorter durations and higher frequency contents. It indicates that the factors in near-fault strong ground motion was under the influence of higher effect stress drop and asperity slip distributions on the fault plane. This work is financially supported by the Natural Science Foundation of China (Grant No. 41404045) and by Science for Earthquake Resilience of CEA (XH14055Y).

  10. Artificial neural network-based all-sky power estimation and fault detection in photovoltaic modules

    Science.gov (United States)

    Jazayeri, Kian; Jazayeri, Moein; Uysal, Sener

    2017-04-01

    The development of a system for output power estimation and fault detection in photovoltaic (PV) modules using an artificial neural network (ANN) is presented. Over 30,000 healthy and faulty data sets containing per-minute measurements of PV module output power (W) and irradiance (W/m2) along with real-time calculations of the Sun's position in the sky and the PV module surface temperature, collected during a three-month period, are fed to different ANNs as training paths. The first ANN being trained on healthy data is used for PV module output power estimation and the second ANN, which is trained on both healthy and faulty data, is utilized for PV module fault detection. The proposed PV module-level fault detection algorithm can expectedly be deployed in broader PV fleets by taking developmental considerations. The machine-learning-based automated system provides the possibility of all-sky real-time monitoring and fault detection of PV modules under any meteorological condition. Utilizing the proposed system, any power loss caused by damaged cells, shading conditions, accumulated dirt and dust on module surface, etc., is detected and reported immediately, potentially yielding increased reliability and efficiency of the PV systems and decreased support and maintenance costs.

  11. Simulation Research of Fault Model of Detecting Rotor Dynamic Eccentricity in Brushless DC Motor Based on Motor Current Signature Analysis

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The Brushless Direct Current (BLDC) motor is widely used in aerospace area, CNC machines and servo systems that require the high control accuracy Once the faults occur in the motor, it will cause great damage to the whole system. Mechanical faults are common in electric machines, and account for up to 50%-60% of the faults. Approximately, 80% of the mechanical faults lead to the eccentricity. So it is necessary to monitor the health condition of the motor to ensure the faults can be detected earlier and measures will be taken to imorove the reliability.

  12. Traveling wave effect on the seismic response of a steel arch bridge subjected to near fault ground motions

    Institute of Scientific and Technical Information of China (English)

    Xu Yan; George C Lee

    2007-01-01

    In the 1990s, several major earthquakes occurred throughout the world, with a common observation that near fault ground motion (NFGM) characteristics had a distinct impact on causing damage to civil engineering structures that could not be predicted by using far field ground motions. Since then, seismic responses of structures under NFGMs have been extensively examined, with most of the studies focusing on structures with relatively short fundamental periods, where the traveling wave effect does not need to be considered. However, for long span bridges, especially arch bridges, the traveling wave (only time delay considered) effect may be very distinct and is therefore important. In this paper, the results from a case study on the seismic response of a steel arch bridge under selected NFGMs is presented by considering the traveling wave effect with variable apparent velocities. The effects of fling step and long period pulses of NFGMs on the seismic responses of the arch bridge are also discussed.

  13. Tectonic Setting of the Gravity Fault and Implications for Ground-Water Resources in the Death Valley Region, Nevada and California

    Science.gov (United States)

    Blakely, R. J.; Sweetkind, D. S.; Faunt, C. C.; Jansen, J. R.; McPhee, D. K.; Morin, R. L.

    2007-12-01

    The Amargosa trough, extending south from Crater Flat basin to the California-Nevada state line, is believed to be a transtensional basin accommodated in part by strike-slip displacement on the northwest-striking State Line fault and normal displacement on the north-striking Gravity fault. The Gravity fault, lying along the eastern margin of the Amargosa trough, was first recognized in the 1970s on the basis of correlations between gravity anomalies and a prominent spring line in Amargosa Valley. The Gravity fault causes an inflection in water-table levels, similar to other (but not all) normal faults in the area. Pools along the spring line, some of which lie within Death Valley National Park and Ash Meadows Wildlife Refuge, include endemic species potentially threatened by increasing agricultural activities in Amargosa Valley immediately to the west, where water tables are declining. Most of the springs and pools lie east of the Gravity fault, however, and it is important to understand the role that the Gravity fault plays in controlling ground-water flow. We have conducted a variety of geophysical investigations at various scales to better understand the tectonic framework of the Amargosa Desert and support new ground-water-flow models. Much of our focus has been on the tectonic interplay of the State Line, Gravity, and other faults in the area using gravity, ground-magnetic, audiomagnetotelluric (AMT), and time-domain electromagnetic (TEM) surveys. With 1250 new gravity measurements from Ash Meadows and Stewart Valley, we have developed a revised three-dimensional crustal model of the Amargosa trough constrained by well information and geologic mapping. The model predicts approximately 2 km of vertical offset on the Gravity fault but also suggests a complex structural framework. The fault is conventionally seen as a simple, down-to-the-west normal fault juxtaposing permeable pre-Tertiary carbonate rocks to the east against less permeable Tertiary sediments to

  14. A Self-Learning Sensor Fault Detection Framework for Industry Monitoring IoT

    Directory of Open Access Journals (Sweden)

    Yu Liu

    2013-01-01

    Full Text Available Many applications based on Internet of Things (IoT technology have recently founded in industry monitoring area. Thousands of sensors with different types work together in an industry monitoring system. Sensors at different locations can generate streaming data, which can be analyzed in the data center. In this paper, we propose a framework for online sensor fault detection. We motivate our technique in the context of the problem of the data value fault detection and event detection. We use the Statistics Sliding Windows (SSW to contain the recent sensor data and regress each window by Gaussian distribution. The regression result can be used to detect the data value fault. Devices on a production line may work in different workloads and the associate sensors will have different status. We divide the sensors into several status groups according to different part of production flow chat. In this way, the status of a sensor is associated with others in the same group. We fit the values in the Status Transform Window (STW to get the slope and generate a group trend vector. By comparing the current trend vector with history ones, we can detect a rational or irrational event. In order to determine parameters for each status group we build a self-learning worker thread in our framework which can edit the corresponding parameter according to the user feedback. Group-based fault detection (GbFD algorithm is proposed in this paper. We test the framework with a simulation dataset extracted from real data of an oil field. Test result shows that GbFD detects 95% sensor fault successfully.

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  16. Detection and Modeling of High-Dimensional Thresholds for Fault Detection and Diagnosis

    Science.gov (United States)

    He, Yuning

    2015-01-01

    Many Fault Detection and Diagnosis (FDD) systems use discrete models for detection and reasoning. To obtain categorical values like oil pressure too high, analog sensor values need to be discretized using a suitablethreshold. Time series of analog and discrete sensor readings are processed and discretized as they come in. This task isusually performed by the wrapper code'' of the FDD system, together with signal preprocessing and filtering. In practice,selecting the right threshold is very difficult, because it heavily influences the quality of diagnosis. If a threshold causesthe alarm trigger even in nominal situations, false alarms will be the consequence. On the other hand, if threshold settingdoes not trigger in case of an off-nominal condition, important alarms might be missed, potentially causing hazardoussituations. In this paper, we will in detail describe the underlying statistical modeling techniques and algorithm as well as the Bayesian method for selecting the most likely shape and its parameters. Our approach will be illustrated by several examples from the Aerospace domain.

  17. Electromagnetic and acoustic bimodality for the detection and localization of electrical arc faults

    Science.gov (United States)

    Vasile, C.; Ioana, C.; Digulescu, A.; Candel, I.

    2016-12-01

    Electrical arc faults pose an important problem to electrical installations worldwide, be it production facilities or distribution systems. In this context, it is easy to assess the economic repercussions of such a fault, when power supply is cut off downstream of its location, while also realizing that an early detection of the on-site smaller scale faults would be of great benefit. This articles serves as a review of the current state-of-the-art work that has been carried out on the subject of detection and localization of electrical arc faults, by exploiting the bimodality of this phenomenon, which generates simultaneously electromagnetic and acoustic waves, propagating in a free space path. En experimental setup has been defined, to demonstrate principles stated in previous works by the authors, and signal processing methods have been used in order to determine the DTOA (difference-of-time-of-arrival) of the acoustic signals, which allows localization of the transient fault. In the end there is a discussion regarding the results and further works, which aims to validate this approach in more real-life applications.

  18. Smart Sensor for Online Detection of Multiple-Combined Faults in VSD-Fed Induction Motors

    Science.gov (United States)

    Garcia-Ramirez, Armando G.; Osornio-Rios, Roque A.; Granados-Lieberman, David; Garcia-Perez, Arturo; Romero-Troncoso, Rene J.

    2012-01-01

    Induction motors fed through variable speed drives (VSD) are widely used in different industrial processes. Nowadays, the industry demands the integration of smart sensors to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can be produce severe damages. The combined fault identification in induction motors is a demanding task, but it has been rarely considered in spite of being a common situation, because it is difficult to identify two or more faults simultaneously. This work presents a smart sensor for online detection of simple and multiple-combined faults in induction motors fed through a VSD in a wide frequency range covering low frequencies from 3 Hz and high frequencies up to 60 Hz based on a primary sensor being a commercially available current clamp or a hall-effect sensor. The proposed smart sensor implements a methodology based on the fast Fourier transform (FFT), RMS calculation and artificial neural networks (ANN), which are processed online using digital hardware signal processing based on field programmable gate array (FPGA).

  19. Fault Detection and Recovery in Wireless Sensor Network Using Clustering

    Directory of Open Access Journals (Sweden)

    Abolfazl Akbari

    2011-02-01

    Full Text Available Some WSN by a lot of immobile node and with the limited energy and without furthercharge of energy. Whereas extension of many sensor nodes and their operation. Hence it isnormal.unactive nodes miss their communication in network, hence split the network. For avoidance splitof network, we proposed a fault recovery corrupted node and Self Healing is necessary. In this Thesis, wedesign techniques to maintain the cluster structure in the event of failures caused by energy-drainednodes. Initially, node with the maximum residual energy in a cluster becomes cluster heed and node withthe second maximum residual energy becomes secondary cluster heed. Later on, selection of cluster heedand secondary cluster heed will be based on available residual energy. We use Matlab software assimulation platform quantities. like, energy consumption at cluster and number of clusters is computed inevaluation of proposed algorithm. Eventually we evaluated and compare this proposed method againstprevious method and we demonstrate our model is better optimization than other method such asVenkataraman, in energy consumption rate.

  20. Robust fault detection and isolation technique for single-input/single-output closed-loop control systems that exhibit actuator and sensor faults

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Alavi, S. M. Mahdi; Hayes, M. J.

    2008-01-01

    ) a graphical environment is provided for the design of fault detection (FD) filter, which is intuitively appealing from an engineering perspective. The FD filter can easily be obtained by manually shaping the frequency response into the complex plane. The question of interaction between actuator and sensor...... fault residuals is also considered. It is discussed how the actuator and sensor faults are distinguished from each other by appropriately defining FDI threshold values. The efficiency of the proposed method is demonstrated on a single machine infinite bus power system wherein a stabilised coordinate...

  1. Analytical investigations of seismic responses for reinforced concrete bridge columns subjected to strong near-fault ground motion

    Institute of Scientific and Technical Information of China (English)

    Chin-Kuo Su; Yu-Chi Sung; Shuenn-Yih Chang; Chao-Hsun Huang

    2007-01-01

    Strong near-fault ground motion, usually caused by the fault-rupture and characterized by a pulse-like velocitywave form, often causes dramatic instantaneous seismic energy (Jadhav and Jangid 2006). Some reinforced concrete (RC)bridge columns, even those built according to ductile design principles, were damaged in the 1999 Chi-Chi earthquake.Thus, it is very important to evaluate the seismic response of a RC bridge column to improve its seismic design and prevent future damage. Nonlinear time history analysis using step-by-step integration is capable of tracing the dynamic response of a structure during the entire vibration period and is able to accommodate the pulsing wave form. However; the accuracy of the numerical results is very sensitive to the modeling of the nonlinear load-deformation relationship of the structural member.FEMA 273 and ATC-40 provide the modeling parameters for structural nonlinear analyses of RC beams and RC columns.They use three parameters to define the plastic rotation angles and a residual strength ratio to describe the nonlinear loaddeformation relationship of an RC member. Structural nonlinear analyses are performed based on these parameters. This method provides a convenient way to obtain the nonlinear seismic responses of RC structures. However, the accuracy of the numerical solutions might be further improved. For this purpose, results from a previous study on modeling of the static pushover analyses for RC bridge columns (Sung et al. 2005) is adopted for the nonlinear time history analysis presented herein to evaluate the structural responses excited by a near-fault ground motion. To ensure the reliability of this approach,the numerical results were compared to experimental results. The results confirm that the proposed approach is valid.

  2. System identification aided design of observer-based fault detection systems; Prozessidentifikations-basierter Entwurf beobachtergestuetzter Fehlerdetektionssysteme

    Energy Technology Data Exchange (ETDEWEB)

    Ding, S.X. [Fachgebiet Automatisierungstechnik und komplexe Systeme, Univ. Duisburg-Essen, Duisburg (Germany); Zhang Ping; Heyden, D. [Fakultaet Ingenieurwissenschaften an der Univ. Duisburg-Essen (Germany); Huang Biao [Dept. of Chemical and Materials Engineering, Univ. of Alberta (Canada); Ding, E.L. [Fachbereich Technische Physik, Fachhochschule Gelsenkirchen, Gelsenkirchen (Germany)

    2004-07-01

    This paper deals with problems of observer-based fault detection. An approach is presented, which enables the design of observer-based residual generators based on the process measurement or test data. The basic idea behind this approach is integrating the identification of the so-called fault detection model into the design of observer-based residual generators. (orig.)

  3. A Novel Approach to Detect Symmetrical Faults Occurring During Power Swings by Using Abrupt change of Impedance Trajectory

    DEFF Research Database (Denmark)

    Khodaparast, Jalal; Silva, Filipe Miguel Faria da; Bak, Claus Leth;

    2017-01-01

    The main purpose of power swing blocking is to distinguish faults from power swings. However, faults occurred during a power swing should still be detected and cleared promptly. This paper proposes an index based on detecting abrupt jump of impedance trajectory by utilization of predicting capabi...

  4. Karhunen Loeve Basis Used for Detection of Gearbox Faults in a Wind Turbine

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2014-01-01

    provided to the control system. In this paper a Karhunen-Loeve basis approach is designed for detecting changes in frequency response from rotating parts like a gearbox. The potential of this method is shown by applying it to an established Wind Turbine FDI and FTC Benchmark model. These faults...

  5. Closed-loop fault detection for full-envelope flight vehicle with measurement delays

    Directory of Open Access Journals (Sweden)

    Wang Zhaolei

    2015-06-01

    Full Text Available A closed-loop fault detection problem is investigated for the full-envelope flight vehicle with measurement delays, where the flight dynamics are modeled as a switched system with delayed feedback signals. The mode-dependent observer-based fault detection filters and state estimation feedback controllers are derived by considering the delays’ impact on the control system and fault detection system simultaneously. Then, considering updating lags of the controllers/filters’ switching signals which are introduced by the delayed measurement of altitude and Mach number, an asynchronous H∞ analysis method is proposed and the system model is further augmented to be an asynchronously switched time-delay system. Also, the global stability and desired performance of the augmented system are guaranteed by combining the switched delay-dependent Lyapunov–Krasovskii functional method with the average dwell time method (ADT, and the delay-dependent existing conditions for the controllers and fault detection filters are obtained in the form of the linear matrix inequalities (LMIs. Finally, numerical example based on the hypersonic vehicles and highly maneuverable technology (HiMAT vehicle is given to demonstrate the merits of the proposed method.

  6. On-demand thread-level fault detection in a concurrent programming environment

    NARCIS (Netherlands)

    Fu, J.; Yang, Q.; Poss, R.; Jesshope, C.R.; Zhang, C.; Jeschke, H.; Silvén, O.

    2013-01-01

    The vulnerability of multi-core processors is increasing due to tighter design margins and greater susceptibility to interference. Moreover, concurrent programming environments are the norm in the exploitation of multi-core systems. In this paper, we present an on-demand thread-level fault detection

  7. A Fault Detection Mechanism in a Data-flow Scheduled Multithreaded Processor

    NARCIS (Netherlands)

    Fu, J.; Yang, Q.; Poss, R.; Jesshope, C.R.; Zhang, C.

    2014-01-01

    This paper designs and implements the Redundant Multi-Threading (RMT) in a Data-flow scheduled MultiThreaded (DMT) multicore processor, called Data-flow scheduled Redundant Multi-Threading (DRMT). Meanwhile, It presents Asynchronous Output Comparison (AOC) for RMT techniques to avoid fault detection

  8. Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches

    DEFF Research Database (Denmark)

    Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam

    2009-01-01

    In this paper nonlinear fault detection for in-service monitoring and decision support systems for ships will be presented. The ship is described as a nonlinear system, and the stochastic wave elevation and the associated ship responses are conveniently modelled in frequency domain...

  9. Transient Monitoring Function–Based Fault Detection for Inverter-Interfaced Microgrids

    DEFF Research Database (Denmark)

    Sadeghkhani, Iman; Esmail Hamedani Golshan, Mohamad; Mehrizi-Sani, Ali;

    2017-01-01

    conditions from normal load switching events and is effective for various inverter topologies (i.e., three/four-leg), main current limiting strategies, and all reference frames of the multi-loop control system. The merits of the proposed fault detection scheme are demonstrated through several time...

  10. Robust fault detection of linear systems using a computationally efficient set-membership method

    DEFF Research Database (Denmark)

    Tabatabaeipour, Mojtaba; Bak, Thomas

    2014-01-01

    In this paper, a computationally efficient set-membership method for robust fault detection of linear systems is proposed. The method computes an interval outer-approximation of the output of the system that is consistent with the model, the bounds on noise and disturbance, and the past...

  11. Application of black-box models to HVAC systems for fault detection

    NARCIS (Netherlands)

    Peitsman, H.C.; Bakker, V.E.

    1996-01-01

    This paper describes the application of black-box models for fault detection and diagnosis (FDD) in heating, ventilat-ing, and air-conditioning (HVAC) systems. In this study, mul-tiple-input/single-output (MISO) ARX models and artificial neural network (ANN) models are used. The ARX models are exami

  12. Application of black-box models to HVAC systems for fault detection

    NARCIS (Netherlands)

    Peitsman, H.C.; Bakker, V.E.

    1996-01-01

    This paper describes the application of black-box models for fault detection and diagnosis (FDD) in heating, ventilat-ing, and air-conditioning (HVAC) systems. In this study, mul-tiple-input/single-output (MISO) ARX models and artificial neural network (ANN) models are used. The ARX models are

  13. On-demand thread-level fault detection in a concurrent programming environment

    NARCIS (Netherlands)

    Fu, J.; Yang, Q.; Poss, R.; Jesshope, C.R.; Zhang, C.; Jeschke, H.; Silvén, O.

    2013-01-01

    The vulnerability of multi-core processors is increasing due to tighter design margins and greater susceptibility to interference. Moreover, concurrent programming environments are the norm in the exploitation of multi-core systems. In this paper, we present an on-demand thread-level fault detection

  14. Model-based fault detection for generator cooling system in wind turbines using SCADA data

    DEFF Research Database (Denmark)

    Borchersen, Anders Bech; Kinnaert, Michel

    2016-01-01

    In this work, an early fault detection system for the generator cooling of wind turbines is presented and tested. It relies on a hybrid model of the cooling system. The parameters of the generator model are estimated by an extended Kalman filter. The estimated parameters are then processed by an ...

  15. Remote Detection of the Electric Field Change Induced at the Seismic Wave Front from the Start of Fault Rupturing

    Directory of Open Access Journals (Sweden)

    Yukio Fujinawa

    2011-01-01

    Full Text Available Seismic waves are generally observed through the measurement of undulating elastic ground motion. We report the remote detection of the Earth's electric field variations almost simultaneously with the start of fault rupturing at about 100 km from the fault region using a special electric measurement. The rare but repeated detection indicates that the phenomenon is real. The characteristic time of diffusion is almost instantaneous, that is, less than 1 second to travel 100 km, more than ten times faster than ordinary seismic P wave propagation. We suggest that the measured electric field changes are produced by the electrokinetic effect through increased pore water pressure of the seismic pulse. It is also suggested that the long range propagation is due to the surface wave mode confined near the interface of the different conductivity. The length scale of the finite strength of the electric field is 16 km, 160 km for electric conductivity of 0.01, 0.001, Sm−1, respectively. This phenomenon suggests a new seismic sensing method and a new earthquake early warning system providing more seconds of lead time.

  16. Support vector data description for detecting the air-ground interface in ground penetrating radar signals

    Science.gov (United States)

    Wood, Joshua; Wilson, Joseph

    2011-06-01

    In using GPR images for landmine detection it is often useful to identify the air-ground interface in the GRP signal for alignment purposes. A common simple technique for doing this is to assume that the highest return in an A-scan is from the reflection due to the ground and to use that as the location of the interface. However there are many situations, such as the presence of nose clutter or shallow sub-surface objects, that can cause the global maximum estimate to be incorrect. A Support Vector Data Description (SVDD) is a one-class classifier related to the SVM which encloses the class in a hyper-sphere as opposed to using a hyper-plane as a decision boundary. We apply SVDD to the problem of detection of the air-ground interface by treating each sample in an A-scan, with some number of leading and trailing samples, as a feature vector. Training is done using a set of feature vectors based on known interfaces and detection is done by creating feature vectors from each of the samples in an A-scan, applying the trained SVDD to them and selecting the one with the least distance from the center of the hyper-sphere. We compare this approach with the global maximum approach, examining both the performance on human truthed data and how each method affects false alarm and true positive rates when used as the alignment method in mine detection algorithms.

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

    Science.gov (United States)

    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 δ -domain, and a threshold function is given. By applying the scaled small gain theorem and choosing a Lyapunov-Krasovskii functional in δ -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.

  18. Three-dimensional simulations of ground motions in the Seattle region for earthquakes in the Seattle fault zone

    Science.gov (United States)

    Frankel, A.; Stephenson, W.

    2000-01-01

    We used the 3D finite-difference method to model observed seismograms of two earthquakes (ML 4.9 and 3.5) in the Seattle region and to simulate ground motions for hypothetical M 6.5 and M 5.0 earthquakes on the Seattle fault, for periods greater than 2 sec. A 3D velocity model of the Seattle Basin was constructed from studies that analyzed seismic-reflection surveys, borehole logs, and gravity and aeromagnetic data. The observations and the simulations highlight the importance of the Seattle Basin on long-period ground motions. For earthquakes occurring just south of the basin, the edge of the basin and the variation of the thickness of the Quaternary deposits in the basin produce much larger surface waves than expected from flat-layered models. The data consist of seismograms recorded by instruments deployed in Seattle by the USGS and the University of Washington (UW). The 3D simulation reproduces the peak amplitude and duration of most of the seismograms of the June 1997 Bremerton event (ML 4.9) recorded in Seattle. We found the focal mechanism for this event that best fits the observed seismograms in Seattle by combining Green's functions determined from the 3D simulations for the six fundamental moment couples. The February 1997 event (ML 3.5) to the south of the Seattle Basin exhibits a large surface-wave arrival at UW whose amplitude is matched by the synthetics in our 3D velocity model, for a source depth of 9 km. The M 6.5 simulations incorporated a fractal slip distribution on the fault plane. These simulations produced the largest ground motions in an area that includes downtown Seattle. This is mainly caused by rupture directed up dip toward downtown, radiation pattern of the source, and the turning of S waves by the velocity gradient in the Seattle basin. Another area of high ground motion is located about 13 km north of the fault and is caused by an increase in the amplitude of higher-mode Rayleigh waves caused by the thinning of the Quaternary

  19. Choice Of Input Data Type Of Artificial Neural Network To Detect Faults In Alternative Current Systems

    Directory of Open Access Journals (Sweden)

    T. Benslimane

    2006-01-01

    Full Text Available This paper present a study on different input data types of ANN used to detect faults such as over-voltage in AC systems (AC network , induction motor. The input data of ANN are AC voltage and current. In no fault condition, voltage and current are sinusoidal. The input data of the ANN may be the instantaneous values of voltage and current, their RMS values or their average values after been rectified. In this paper we presented different characteristics of each one of these data. A digital software C++ simulation program was developed and simulation results were presented.

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

    Science.gov (United States)

    Hanson, Matt

    1990-01-01

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

  1. Fault Detection and Diagnosis of Railway Point Machines by Sound Analysis

    Directory of Open Access Journals (Sweden)

    Jonguk Lee

    2016-04-01

    Full Text Available Railway point devices act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Point failure can significantly affect railway operations, with potentially disastrous consequences. Therefore, early detection of anomalies is critical for monitoring and managing the condition of rail infrastructure. We present a data mining solution that utilizes audio data to efficiently detect and diagnose faults in railway condition monitoring systems. The system enables extracting mel-frequency cepstrum coefficients (MFCCs from audio data with reduced feature dimensions using attribute subset selection, and employs support vector machines (SVMs for early detection and classification of anomalies. Experimental results show that the system enables cost-effective detection and diagnosis of faults using a cheap microphone, with accuracy exceeding 94.1% whether used alone or in combination with other known methods.

  2. Simultaneous fault detection and control for stochastic time-delay systems

    Science.gov (United States)

    Meng, Xian-Ji; Yang, Guang-Hong

    2014-05-01

    This paper is concerned with the simultaneous fault detection and control problem for Itô-type stochastic time-delay systems. A full-order dynamic output feedback controller is designed to achieve the desired control and detection objectives. The main contributions of this paper are as follows: (1) for stochastic time-delay systems, the controller design with multiple objectives can be addressed by employing the multiple Lyapunov functions approach, (2) the dynamic output feedback controller synthesis conditions described by linear matrix inequalities (LMIs) are derived and (3) within the proposed fault detection and control framework, a better integrated control and detection performance can be obtained. Some numerical examples including the comparison results are presented to show the advantages of the proposed method.

  3. Fault Detection and Diagnosis of Railway Point Machines by Sound Analysis.

    Science.gov (United States)

    Lee, Jonguk; Choi, Heesu; Park, Daihee; Chung, Yongwha; Kim, Hee-Young; Yoon, Sukhan

    2016-04-16

    Railway point devices act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Point failure can significantly affect railway operations, with potentially disastrous consequences. Therefore, early detection of anomalies is critical for monitoring and managing the condition of rail infrastructure. We present a data mining solution that utilizes audio data to efficiently detect and diagnose faults in railway condition monitoring systems. The system enables extracting mel-frequency cepstrum coefficients (MFCCs) from audio data with reduced feature dimensions using attribute subset selection, and employs support vector machines (SVMs) for early detection and classification of anomalies. Experimental results show that the system enables cost-effective detection and diagnosis of faults using a cheap microphone, with accuracy exceeding 94.1% whether used alone or in combination with other known methods.

  4. Detection of Sensor Faults in Small Helicopter UAVs Using Observer/Kalman Filter Identification

    Directory of Open Access Journals (Sweden)

    Guillermo Heredia

    2011-01-01

    Full Text Available Reliability is a critical issue in navigation of unmanned aerial vehicles (UAVs since there is no human pilot that can react to any abnormal situation. Due to size and cost limitations, redundant sensor schemes and aeronautical-grade navigation sensors used in large aircrafts cannot be installed in small UAVs. Therefore, other approaches like analytical redundancy should be used to detect faults in navigation sensors and increase reliability. This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters based on analytical redundancy. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the Observer/Kalman Filter Identification (OKID method. The OKID method is able to identify the system and an observer with properties similar to a Kalman filter, directly from input-output experimental data. Results are similar to the Kalman filter, but, with the proposed method, there is no need to estimate neither system matrices nor sensor and process noise covariance matrices. The system has been tested with real helicopter flight data, and the results compared with other methods.

  5. An adaptive confidence limit for periodic non-steady conditions fault detection

    Science.gov (United States)

    Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

    2016-05-01

    System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

  6. A METHOD TO IMPROVE RELIABILITY OF GEARBOX FAULT DETECTION WITH ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    P.V. Srihari

    2010-12-01

    Full Text Available Fault diagnosis of gearboxes plays an important role in increasing the availability of machinery in condition monitoring. An effort has been made in this work to develop an artificial neural networks (ANN based fault detection system to increase reliability. Two prominent fault conditions in gears, worn-out and broken teeth, are simulated and five feature parameters are extracted based on vibration signals which are used as input features to the ANN based fault detection system developed in MATLAB, a three layered feed forward network using a back propagation algorithm. This ANN system has been trained with 30 sets of data and tested with 10 sets of data. The learning rate and number of hidden layer neurons are varied individually and the optimal training parameters are found based on the number of epochs. Among the five different learning rates used the 0.15 is deduced to be optimal one and at that learning rate the number of hidden layer neurons of 9 was the optimal one out of the three values considered. Then keeping the training parameters fixed, the number of hidden layers is varied by comparing the performance of the networks and results show the two and three hidden layers have the best detection accuracy.

  7. Study on Immune Relevant Vector Machine Based Intelligent Fault Detection and Diagnosis Algorithm

    Directory of Open Access Journals (Sweden)

    Zhong-hua Miao

    2013-01-01

    Full Text Available An immune relevant vector machine (IRVM based intelligent classification method is proposed by combining the random real-valued negative selection (RRNS algorithm and the relevant vector machine (RVM algorithm. The method proposed is aimed to handle the training problem of missing or incomplete fault sampling data and is inspired by the “self/nonself” recognition principle in the artificial immune systems. The detectors, generated by the RRNS, are treated as the “nonself” training samples and used to train the RVM model together with the “self” training samples. After the training succeeds, the “nonself” detection model, which requires only the “self” training samples, is obtained for the fault detection and diagnosis. It provides a general way solving the problems of this type and can be applied for both fault detection and fault diagnosis. The standard Fisher's Iris flower dataset is used to experimentally testify the proposed method, and the results are compared with those from the support vector data description (SVDD method. Experimental results have shown the validity and practicability of the proposed method.

  8. H-/H∞ fault detection observer design based on generalized output for polytopic LPV system

    Science.gov (United States)

    Zhou, Meng; Rodrigues, Mickael; Shen, Yi; Theilliol, Didier

    2017-01-01

    This paper proposes an H-/H∞ fault detection observer design method by using generalized output for a class of polytopic linear parameter-varying (LPV) system. First, with the aid of the relative degree of output, a new output vector is generated by gathering the original and its time derivative. The actuator fault is introduced into the measurement equation of the new system. An H-/H∞ observer is designed for the new LPV polytopic system to guarantee the robustness against disturbances and to improve the fault sensitivity, simultaneously. The existence conditions of the H-/H∞ observer are given and solved by a set of linear matrix inequalities (LMIs). Finally simulation results are given to illustrate the effectiveness of the proposed method.

  9. A windowing and mapping strategy for gear tooth fault detection of a planetary gearbox

    Science.gov (United States)

    Liang, Xihui; Zuo, Ming J.; Liu, Libin

    2016-12-01

    When there is a single cracked tooth in a planet gear, the cracked tooth is enmeshed for very short time duration in comparison to the total time of a full revolution of the planet gear. The fault symptom generated by the single cracked tooth may be very weak. This study aims to develop a windowing and mapping strategy to interpret the vibration signal of a planetary gear at the tooth level. The fault symptoms generated by a single cracked tooth of the planet gear of interest can be extracted. The health condition of the planet gear can be assessed by comparing the differences among the signals of all teeth of the planet gear. The proposed windowing and mapping strategy is tested with both simulated vibration signals and experimental vibration signals. The tooth signals can be successfully decomposed and a single tooth fault on a planet gear can be effectively detected.

  10. Comparative Study of Parametric and Non-parametric Approaches in Fault Detection and Isolation

    DEFF Research Database (Denmark)

    Katebi, S.D.; Blanke, M.; Katebi, M.R.

    This report describes a comparative study between two approaches to fault detection and isolation in dynamic systems. The first approach uses a parametric model of the system. The main components of such techniques are residual and signature generation for processing and analyzing. The second...... approach is non-parametric in the sense that the signature analysis is only dependent on the frequency or time domain information extracted directly from the input-output signals. Based on these approaches, two different fault monitoring schemes are developed where the feature extraction and fault decision...... algorithms employed are adopted from the template matching in pattern recognition. Extensive simulation studies are performed to demonstrate satisfactory performance of the proposed techniques. The advantages and disadvantages of each approach are discussed and analyzed....

  11. Performance of wavelet analysis and neural network for detection and diagnosis of rotating machine fault

    Science.gov (United States)

    Kang, Shanlin; Kang, Yuzhe; Chen, Jingwei

    2008-10-01

    A novel approach combining wavelet transform with neural network is proposed for vibration fault diagnosis of turbo-generator set in power system. The multi-resolution analysis technology is used to acquire the feature vectors which are applied to train and test the neural network. Feature extraction involves preliminary processing of measurements to obtain suitable parameters which reveal weather an interesting pattern is emerging. The feature extraction technique is needed for preliminary processing of recorded time-series vibrations over a long period of time to obtain suitable parameters. The neural network parameters are determined by means of the recursive orthogonal least squares algorithm. In network training procedure, much simulation and practical samples are utilized to verify and test the network performance. And according to the output result, the fault pattern can be recognized. The actual applications show that the method is effective for detection and diagnosis of rotating machine fault and the experiment result is correct.

  12. Detecting eccentricity faults in a PMSM in non-stationary conditions

    Directory of Open Access Journals (Sweden)

    Javier Rosero García

    2012-04-01

    Full Text Available Permanent magnet alternating current machines are being widely used in applications demanding high and rugged performance, such as industrial automation and the aerospace and automotive industries. This paper presents a study of a permanent magnet synchronous machine (PMSM running in eccentricity; these machines’ condition monitoring and fault detection would provide added value and they are also assuming growing importance. This paper investigates the effect of eccentricity faults on PMSM motors’ current spectrum with a view to developing an effective condition-monitoring scheme using two-dimensional (2-D finite element analysis (FEA. Stator current induced harmonics were investigated for fault conditions and advanced signal analysis involved continuous and discrete wavelet transforms. Simulation and experimental results are presented to substantiate that the proposed method worked over a wide speed range for motor operation and that it provided an effective tool for diagnosing PMSM operating condition.

  13. Computation of a Reference Model for Robust Fault Detection and Isolation Residual Generation

    Directory of Open Access Journals (Sweden)

    Emmanuel Mazars

    2008-01-01

    Full Text Available This paper considers matrix inequality procedures to address the robust fault detection and isolation (FDI problem for linear time-invariant systems subject to disturbances, faults, and polytopic or norm-bounded uncertainties. We propose a design procedure for an FDI filter that aims to minimize a weighted combination of the sensitivity of the residual signal to disturbances and modeling errors, and the deviation of the faults to residual dynamics from a fault to residual reference model, using the ℋ∞-norm as a measure. A key step in our procedure is the design of an optimal fault reference model. We show that the optimal design requires the solution of a quadratic matrix inequality (QMI optimization problem. Since the solution of the optimal problem is intractable, we propose a linearization technique to derive a numerically tractable suboptimal design procedure that requires the solution of a linear matrix inequality (LMI optimization. A jet engine example is employed to demonstrate the effectiveness of the proposed approach.

  14. Ground-based Nuclear Detonation Detection (GNDD) Technology Roadmap

    Energy Technology Data Exchange (ETDEWEB)

    Casey, Leslie A.

    2014-01-13

    This GNDD Technology Roadmap is intended to provide guidance to potential researchers and help management define research priorities to achieve technology advancements for ground-based nuclear explosion monitoring science being pursued by the Ground-based Nuclear Detonation Detection (GNDD) Team within the Office of Nuclear Detonation Detection in the National Nuclear Security Administration (NNSA) of the U.S. Department of Energy (DOE). Four science-based elements were selected to encompass the entire scope of nuclear monitoring research and development (R&D) necessary to facilitate breakthrough scientific results, as well as deliver impactful products. Promising future R&D is delineated including dual use associated with the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Important research themes as well as associated metrics are identified along with a progression of accomplishments, represented by a selected bibliography, that are precursors to major improvements to nuclear explosion monitoring.

  15. Development and evaluation of virtual refrigerant mass flow sensors for fault detection and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Woohyun; Braun, J.

    2016-03-05

    Refrigerant mass flow rate is an important measurement for monitoring equipment performance and enabling fault detection and diagnostics. However, a traditional mass flow meter is expensive to purchase and install. A virtual refrigerant mass flow sensor (VRMF) uses a mathematical model to estimate flow rate using low-cost measurements and can potentially be implemented at low cost. This study evaluates three VRMFs for estimating refrigerant mass flow rate. The first model uses a compressor map that relates refrigerant flow rate to measurements of inlet and outlet pressure, and inlet temperature measurements. The second model uses an energy-balance method on the compressor that uses a compressor map for power consumption, which is relatively independent of compressor faults that influence mass flow rate. The third model is developed using an empirical correlation for an electronic expansion valve (EEV) based on an orifice equation. The three VRMFs are shown to work well in estimating refrigerant mass flow rate for various systems under fault-free conditions with less than 5% RMS error. Each of the three mass flow rate estimates can be utilized to diagnose and track the following faults: 1) loss of compressor performance, 2) fouled condenser or evaporator filter, 3) faulty expansion device, respectively. For example, a compressor refrigerant flow map model only provides an accurate estimation when the compressor operates normally. When a compressor is not delivering the expected flow due to a leaky suction or discharge valve or other internal fault, the energy-balance or EEV model can provide accurate flow estimates. In this paper, the flow differences provide an indication of loss of compressor performance and can be used for fault detection and diagnostics.

  16. Stochastic Change Detection based on an Active Fault Diagnosis Approach

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2007-01-01

    output from the system. The classical CUSUM (cumulative sum) method will be modified such that it will be able to detect change in the signature from the auxiliary input signal in the (error) output signal. It will be shown how it is possible to apply both the gain as well as the phase change...... of the output vector in the CUSUM test....

  17. Detecting topological order in a ground state wave function

    OpenAIRE

    2005-01-01

    A large class of topological orders can be understood and classified using the string-net condensation picture. These topological orders can be characterized by a set of data (N, d_i, F^{ijk}_{lmn}, \\delta_{ijk}). We describe a way to detect this kind of topological order using only the ground state wave function. The method involves computing a quantity called the ``topological entropy'' which directly measures the quantum dimension D = \\sum_i d^2_i.

  18. Analysis on Application Status of the Existing Single-Phase Grounding Fault Indicator%单相接地故障指示器的应用

    Institute of Scientific and Technical Information of China (English)

    吴军汝; 李宝树; 梁仕斌; 田庆生; 代云洪

    2014-01-01

    通过研究现有应用的“暂态综合判据法”和“信号源注入法”检测原理,发现这两种方法适用于配电网常见的中性点不接地和经消弧线圈接地系统,且动作准确性高于其他检测原理,应结合故障指示器的原理及网架结构的复杂程度,选择与配网相适应的检测原理及设备。然后通过对故障指示器的应用现状分析,给出了故障指示器系统自身功能扩展及该系统接入配电自动化系统的发展方向的建议。%Studying the exsiting application “transient synthesis criterion method” and “signal injection method” detection principle,found that the two methods is suitable for the common distribution network neutral point grounding and arc-supptession coil ground system� And the accuracy is higher than other principle� We shoud combine the principle of fault indicator with the com-plexity of the space truss structure to select appropriate principle and equipment to distribution network� Then through analyzing the present situation of fault indicator gives the proposal of development direction which is about system itself function extension and acc-sess to the distribution automation system.

  19. Energy-Efficient Fault-Tolerant Dynamic Event Region Detection in Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Enemark, Hans-Jacob; Zhang, Yue; Dragoni, Nicola

    2015-01-01

    Fault-tolerant event detection is fundamental to wireless sensor network applications. Existing approaches usually adopt neighborhood collaboration for better detection accuracy, while need more energy consumption due to communication. Focusing on energy efficiency, this paper makes an improvement...... its detection decision based on decisions received from its spatial and temporal neighbors, to local non-communicative decision making. The simulation results demonstrate that the improved algorithm does not degrade the detection accuracy of the original algorithm, while it has better energy...... efficiency with the number of messages exchanged in the network decreased....

  20. Multiple fault separation and detection by joint subspace learning for the health assessment of wind turbine gearboxes

    Science.gov (United States)

    Du, Zhaohui; Chen, Xuefeng; Zhang, Han; Zi, Yanyang; Yan, Ruqiang

    2017-09-01

    The gearbox of a wind turbine (WT) has dominant failure rates and highest downtime loss among all WT subsystems. Thus, gearbox health assessment for maintenance cost reduction is of paramount importance. The concurrence of multiple faults in gearbox components is a common phenomenon due to fault induction mechanism. This problem should be considered before planning to replace the components of the WT gearbox. Therefore, the key fault patterns should be reliably identified from noisy observation data for the development of an effective maintenance strategy. However, most of the existing studies focusing on multiple fault diagnosis always suffer from inappropriate division of fault information in order to satisfy various rigorous decomposition principles or statistical assumptions, such as the smooth envelope principle of ensemble empirical mode decomposition and the mutual independence assumption of independent component analysis. Thus, this paper presents a joint subspace learning-based multiple fault detection (JSL-MFD) technique to construct different subspaces adaptively for different fault patterns. Its main advantage is its capability to learn multiple fault subspaces directly from the observation signal itself. It can also sparsely concentrate the feature information into a few dominant subspace coefficients. Furthermore, it can eliminate noise by simply performing coefficient shrinkage operations. Consequently, multiple fault patterns are reliably identified by utilizing the maximum fault information criterion. The superiority of JSL-MFD in multiple fault separation and detection is comprehensively investigated and verified by the analysis of a data set of a 750 kW WT gearbox. Results show that JSL-MFD is superior to a state-of-the-art technique in detecting hidden fault patterns and enhancing detection accuracy.