Sample records for active fault detection

  1. Controller modification applied for active fault detection

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


    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...

  2. Active fault detection in MIMO systems

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad


    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...

  3. Active Fault Detection Based on a Statistical Test

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


    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...

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

    Yeganeh Fallah, Arash; Taghikhany, Touraj


    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.

  5. Active Fault Detection and Isolation for Hybrid Systems

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


    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...

  6. Stochastic Change Detection based on an Active Fault Diagnosis Approach

    Poulsen, Niels Kjølstad; Niemann, Hans Henrik


    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....

  7. Smac–Fdi: A Single Model Active Fault Detection and Isolation System for Unmanned Aircraft

    Ducard Guillaume J.J.


    Full Text Available This article presents a single model active fault detection and isolation system (SMAC-FDI which is designed to efficiently detect and isolate a faulty actuator in a system, such as a small (unmanned aircraft. This FDI system is based on a single and simple aerodynamic model of an aircraft in order to generate some residuals, as soon as an actuator fault occurs. These residuals are used to trigger an active strategy based on artificial exciting signals that searches within the residuals for the signature of an actuator fault. Fault isolation is carried out through an innovative mechanism that does not use the previous residuals but the actuator control signals directly. In addition, the paper presents a complete parameter-tuning strategy for this FDI system. The novel concepts are backed-up by simulations of a small unmanned aircraft experiencing successive actuator failures. The robustness of the SMAC-FDI method is tested in the presence of model uncertainties, realistic sensor noise and wind gusts. Finally, the paper concludes with a discussion on the computational efficiency of the method and its ability to run on small microcontrollers.

  8. Fault detection and isolation in systems with parametric faults

    Stoustrup, Jakob; Niemann, Hans Henrik


    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...

  9. Active fault diagnosis by temporary destabilization

    Niemann, Hans Henrik; Stoustrup, Jakob


    An active fault diagnosis method for parametric or multiplicative faults is proposed. The method periodically adds a term to the controller that for a short period of time renders the system unstable if a fault has occurred, which facilitates rapid fault detection. An illustrative example is given....

  10. A Sensor Fault Detection Methodology applied to Piezoelectric Active Systems in Structural Health Monitoring Applications

    Tibaduiza, D.; Anaya, M.; Forero, E.; Castro, R.; Pozo, F.


    Damage detection is the basis of the damage identification task in Structural Health Monitoring. A good damage detection process can ensure the adequate work of a SHM System because allows to know early information about the presence of a damage in a structure under evaluation. However this process is based on the premise that all sensors are well installed and they are working properly, however, it is not true all the time. Problems such as debonding, cuts and the use of the sensors under different environmental and operational conditions result in changes in the vibrational response and a bad functioning in the SHM system. As a contribution to evaluate the state of the sensors in a SHM system, this paper describes a methodology for sensor fault detection in a piezoelectric active system. The methodology involves the use of PCA for multivariate analysis and some damage indices as pattern recognition technique and is tested in a blade from a wind turbine where different scenarios are evaluated including sensor cuts and debonding.

  11. Active fault detection and isolation of discrete-time linear time-varying systems: a set-membership approach

    Tabatabaeipour, Mojtaba


    Active fault detection and isolation (AFDI) is used for detection and isolation of faults that are hidden in the normal operation because of a low excitation signal or due to the regulatory actions of the controller. In this paper, a new AFDI method based on set-membership approaches is proposed...... un-falsified, the AFDI method is used to generate an auxiliary signal that is injected into the system for detection and isolation of faults that remain otherwise hidden or non-isolated using passive FDI (PFDI) methods. Having the set-valued estimation of the states for each model, the proposed AFDI...... method finds an optimal input signal that guarantees FDI in a finite time horizon. The input signal is updated at each iteration in a decreasing receding horizon manner based on the set-valued estimation of the current states and un-falsified models at the current sample time. The problem is solved...

  12. Rapprochement between Active Fault Diagnosis and Change Detection in ARMAX Systems

    Poulsen, Niels Kjølstad; Niemann, Hans Henrik


    The connection between AFD (Active Fault Diagnosis), ARMAX systems and RST controllers etc. are considered in this paper. It is shown that the applied setup in modern AFD for closed loop systems can be considered as a generalization of the setup used in connection with traditional methods for sys...... for system identification and controller design in the polynomial setting....

  13. Final Technical Report: PV Fault Detection Tool.

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


    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. Detection of active faults using EMR-Technique and Cerescope at Landau area in central Upper Rhine Graben, SW Germany

    Hagag, Wael; Obermeyer, Hennes


    Two conjugate sets of active faults oriented NNE-SSW and NNW-SSE have been detected at Landau area in SW Germany. These faults follow the old trends of the rift-related structures predominating in the Upper Rhine Graben (URG), which originated during Late Eocene-Miocene time. Linear and horizontal measurements were performed by using the Cerescope device and interpreted, applying the Electromagnetic Radiation (EMR) Technique. Linear EMR-profiles were helpful for mapping active faults, while the main horizontal stress (σH, N to NNE) was easily identified with EMR-horizontal measurements. Reactivation of rift-related structures of the Upper Rhine Graben at Landau area produces a new system of active shallow fractures following old trends, and has been detected through the present study by Cerescope applying the EMR-Technique. The present results imply that the Enhanced Geothermal System (EGS) to the south of Landau has a great impact on reactivation of the pre-existing rift-related faults by mechanical hydro-fracturing occurring within the reservoir rocks underneath the area.

  15. Row fault detection system

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


    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. Comparison between different methodologies for detecting radon in soil along an active fault: The case of the Pernicana fault system, Mt. Etna (Italy)

    Giammanco, S. [Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania, Piazza Roma, 2, 95123 Catania (Italy); Imme, G.; Mangano, G.; Morelli, D. [Dipartimento di Fisica e Astronomia, Universita degli Studi di Catania, via S.Sofia, 64, 95123 Catania (Italy); Neri, M. [Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania, Piazza Roma, 2, 95123 Catania (Italy)], E-mail:


    Three different methodologies were used to measure Radon ({sup 222}Rn) in soil, based on both passive and active detection system. The first technique consisted of solid-state nuclear track detectors (SSNTD), CR-39 type, and allowed integrated measurements. The second one consisted of a portable device for short time measurements. The last consisted of a continuous measurement device for extended monitoring, placed in selected sites. Soil {sup 222}Rn activity was measured together with soil Thoron ({sup 220}Rn) and soil carbon dioxide (CO{sub 2}) efflux, and it was compared with the content of radionuclides in the rocks. Two different soil-gas horizontal transects were investigated across the Pernicana fault system (NE flank of Mount Etna), from November 2006 to April 2007. The results obtained with the three methodologies are in a general agreement with each other and reflect the tectonic settings of the investigated study area. The lowest {sup 222}Rn values were recorded just on the fault plane, and relatively higher values were recorded a few tens of meters from the fault axis on both of its sides. This pattern could be explained as a dilution effect resulting from high rates of soil CO{sub 2} efflux. Time variations of {sup 222}Rn activity were mostly linked to atmospheric influences, whereas no significant correlation with the volcanic activity was observed. In order to further investigate regional radon distributions, spot measurements were made to identify sites having high Rn emissions that could subsequently be monitored for temporal radon variations. SSNTD measurements allow for extended-duration monitoring of a relatively large number of sites, although with some loss of temporal resolution due to their long integration time. Continuous monitoring probes are optimal for detailed time monitoring, but because of their expense, they can best be used to complement the information acquired with SSNTD in a network of monitored sites.

  17. Active fault diagnosis in closed-loop uncertain systems

    Niemann, Hans Henrik


    Fault diagnosis of parametric faults in closed-loop uncertain systems by using an auxiliary input vector is considered in this paper, i.e. active fault diagnosis (AFD). The active fault diagnosis is based directly on the socalled fault signature matrix, related to the YJBK (Youla, Jabr, Bongiorno...... and Kucera) parameterization. Conditions are given for exact detection and isolation of parametric faults in closed-loop uncertain systems....

  18. Wind turbine fault detection and fault tolerant control

    Odgaard, Peter Fogh; Johnson, Kathryn


    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 for Nonlinear Systems

    Stoustrup, Jakob; Niemann, H.H.


    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...

  20. Fault detection using (PI) observers

    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....

  1. Robust fault detection filter design

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

    Vijay Kumar


    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.

  3. Actuator Fault Detection and Diagnosis for Quadrotors

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


    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

  4. Active Fault Isolation in MIMO Systems

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad


    Active fault isolation of parametric faults in closed-loop MIMO system s are considered in this paper. The fault isolation consists of two steps. T he first step is group- wise fault isolation. Here, a group of faults is isolated from other pos sible faults in the system. The group-wise fault iso...

  5. Novelty Detection Methods and Novel Fault Class Detection

    ZHANG Jiafan; HUANG Zhichu; WANG Xiaoming


    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. Arc burst pattern analysis fault detection system

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


    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.

  7. Fault Detection for a Diesel Engine Actuator

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


    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)....

  8. Exact, almost and delayed fault detection

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


    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...

  9. Fault Detection and Isolation for Spacecraft

    Jensen, Hans-Christian Becker; Wisniewski, Rafal


    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...

  10. Seismic attribute detection of faults and fluid pathways within an active strike-slip shear zone: New insights from high-resolution 3D P-Cable™ seismic data along the Hosgri Fault, offshore California

    Kluesner, Jared; Brothers, Daniel


    Poststack data conditioning and neural-network seismic attribute workflows are used to detect and visualize faulting and fluid migration pathways within a 13.7 km2 13.7 km2 3D P-Cable™ seismic volume located along the Hosgri Fault Zone offshore central California. The high-resolution 3D volume used in this study was collected in 2012 as part of Pacific Gas and Electric’s Central California Seismic Imaging Project. Three-dimensional seismic reflection data were acquired using a triple-plate boomer source (1.75 kJ) and a short-offset, 14-streamer, P-Cable system. The high-resolution seismic data were processed into a prestack time-migrated 3D volume and publically released in 2014. Postprocessing, we employed dip-steering (dip and azimuth) and structural filtering to enhance laterally continuous events and remove random noise and acquisition artifacts. In addition, the structural filtering was used to enhance laterally continuous edges, such as faults. Following data conditioning, neural-network based meta-attribute workflows were used to detect and visualize faults and probable fluid-migration pathways within the 3D seismic volume. The workflow used in this study clearly illustrates the utility of advanced attribute analysis applied to high-resolution 3D P-Cable data. For example, results from the fault attribute workflow reveal a network of splayed and convergent fault strands within an approximately 1.3 km wide shear zone that is characterized by distinctive sections of transpressional and transtensional dominance. Neural-network chimney attribute calculations indicate that fluids are concentrated along discrete faults in the transtensional zones, but appear to be more broadly distributed amongst fault bounded anticlines and structurally controlled traps in the transpressional zones. These results provide high-resolution, 3D constraints on the relationships between strike-slip fault mechanics, substrate deformation, and fluid migration along an active

  11. Fault tolerant control based on active fault diagnosis

    Niemann, Hans Henrik


    An active fault diagnosis (AFD) method will be considered in this paper in connection with a Fault Tolerant Control (FTC) architecture based on the YJBK parameterization of all stabilizing controllers. The architecture consists of a fault diagnosis (FD) part and a controller reconfiguration (CR...

  12. Unitary Approximations in Fault Detection Filter Design

    Dušan Krokavec


    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.

  13. Detection of precursory slips on a fault by the quiescence and activation of seismicity relative to the ETAS model and by the anomalous trend of the geodetic time series of distances between GPS stations around the fault

    Ogata, Y.


    This paper is concerned with the detection of precursory slip on a rupturing fault, supported by both seismic and geodetic records. Basically, the detection relies on the principle that, assuming precursory slip on the rupturing fault, the seismic activity around the fault should be enhanced or reduced in the zones where increment of the Coulomb failure stress (CFS) is positive or negative, respectively. However, any occurring event also affects the stress changes in neighboring regions, which can trigger further aftershock clusters. Whereas such stress transfers are too difficult to be computed precisely, due to the unknown complex fault system, the ordinary short-term occurrence rate of earthquakes in a region is easily predicted using the ETAS model of triggering seismicity; and any anomalous seismic activity, such as quiescence and activation, can be quantified by identifying a significant deviation from the predicted rate. Such anomalies are revealed to have occurred during several years leading up to the 2004 Chuetsu Earthquake of M6.8, central Honshu, and also the 2005 Western Fukuoka-Ken-Oki Earthquake of M7.0, Kyushu, Japan. Quiescence and activation in the regions coincided with negative and positive increments of the CFS, respectively, and were probably transferred from possible aseismic slips on the focal fault plane. Such slips are further supported by transient crustal movement around the source preceding the rupture. Time series records of the baseline distances between the permanent GPS stations deviated from the predicted trends, with the deviations consistent with the coseismic horizontal displacements of the stations due to these earthquakes. References Ogata, Y. (2006) Report of the Coordinating Committee for Earthquake Prediction, 76 (to appear, in Japanese).

  14. Detecting Fan Faults in refrigerated Cabinets

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


    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...

  15. Cell boundary fault detection system

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


    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.

  16. Geophysical characterization of buried active faults: the Concud Fault (Iberian Chain, NE Spain)

    Pueyo Anchuela, Óscar; Lafuente, Paloma; Arlegui, Luis; Liesa, Carlos L.; Simón, José L.


    The Concud Fault is a 14-km-long active fault that extends close to Teruel, a city with about 35,000 inhabitants in the Iberian Range (NE Spain). It shows evidence of recurrent activity during Late Pleistocene time, posing a significant seismic hazard in an area of moderate-to-low tectonic rates. A geophysical survey was carried out along the mapped trace of the southern branch of the Concud Fault to evaluate the geophysical signature from the fault and the location of paleoseismic trenches. The survey identified a lineation of inverse magnetic dipoles at residual and vertical magnetic gradient, a local increase in apparent conductivity, and interruptions of the underground sediment structure along GPR profiles. The origin of these anomalies is due to lateral contrast between both fault blocks and the geophysical signature of Quaternary materials located above and directly south of the fault. The spatial distribution of anomalies was successfully used to locate suitable trench sites and to map non-exposed segments of the fault. The geophysical anomalies are related to the sedimentological characteristics and permeability differences of the deposits and to deformation related to fault activity. The results illustrate the usefulness of geophysics to detect and map non-exposed faults in areas of moderate-to-low tectonic activity where faults are often covered by recent pediments that obscure geological evidence of the most recent earthquakes. The results also highlight the importance of applying multiple geophysical techniques in defining the location of buried faults.

  17. Fault Detection and Isolation using Eigenstructure Assignment

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


    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....

  18. InSAR measurements around active faults: creeping Philippine Fault and un-creeping Alpine Fault

    Fukushima, Y.


    Recently, interferometric synthetic aperture radar (InSAR) time-series analyses have been frequently applied to measure the time-series of small and quasi-steady displacements in wide areas. Large efforts in the methodological developments have been made to pursue higher temporal and spatial resolutions by using frequently acquired SAR images and detecting more pixels that exhibit phase stability. While such a high resolution is indispensable for tracking displacements of man-made and other small-scale structures, it is not necessarily needed and can be unnecessarily computer-intensive for measuring the crustal deformation associated with active faults and volcanic activities. I apply a simple and efficient method to measure the deformation around the Alpine Fault in the South Island of New Zealand, and the Philippine Fault in the Leyte Island. I use a small-baseline subset (SBAS) analysis approach (Berardino, et al., 2002). Generally, the more we average the pixel values, the more coherent the signals are. Considering that, for the deformation around active faults, the spatial resolution can be as coarse as a few hundred meters, we can severely 'multi-look' the interferograms. The two applied cases in this study benefited from this approach; I could obtain the mean velocity maps on practically the entire area without discarding decorrelated areas. The signals could have been only partially obtained by standard persistent scatterer or single-look small-baseline approaches that are much more computer-intensive. In order to further increase the signal detection capability, it is sometimes effective to introduce a processing algorithm adapted to the signal of interest. In an InSAR time-series processing, one usually needs to set the reference point because interferograms are all relative measurements. It is difficult, however, to fix the reference point when one aims to measure long-wavelength deformation signals that span the whole analysis area. This problem can be


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


    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.

  20. Recognition of Active Faults and Stress Field

    Azuma, T.


    Around the plate-boundary region, the directions of maximum and minimum stress related to the plate motion is one of the key for the recognition of active faults. For example, it is typical idea that there are many N-S trading reverse faults, NE-SW and NW-SE trending strike slip faults and less normal faults (only near volcanoes) in Japan, where the compressional stress with E-W direction is dominant caused by the motion of the subduction of the Pacific Plate beneath the North American Plate. After the 2011 Tohoku earthquake (Mj 9.0), however, many earthquakes with the mechanism of the normal fault type occurred in the coastal region of the northern-east Japan. On 11th April 2011, the Fukushima Hamadori Earthquake (Mj 7.0) occurred accompanying surface faults along two faults, the Idosawa fault and the Yunotake fault, that recognized as active faults by the Research Group for Active Fault of Japan (1980, 1991). It impacted on active fault study by the reason of not only the appearance of two traces of significant surface faults with maximum displacement up to 2.1 m, but also the reactivation of the normal faults under the E-W compressional stress field. When we identify the active faults, it is one of the key whether the direction of slip on the fault consists with the stress field in that area or not. And there is a technique to recognized whether the fault is active or not by using the data of the direction of stress in the field and the geometry of the fault plane. Though it is useful for the fault in the rock without overlain Quaternary deposits, we should care that the active faults may react caused by the temporal stress condition after the generation of large earthquakes.

  1. Active Fault Research (1996); Katsudanso kenkyu (1996)



    This is a general collection of papers dealing with the research of active faults. In Japan, since very heavy damage was produced by the Hyogoken-Nambu earthquake of January, 1955, discussion of active faults has promptly grown very active. In relation to the said earthquake, detailed maps of earthquake faults that emerged in the same, trench investigations of the Awajishima surface fault rupture related to the same, and the circumstances of the southern and northern ends of the Nojima earthquake fault are reported. Discussion is made about the re-examination of precaution faults and the possibility of the presence of C-class active faults, dealing with the entirety of Japan. Itemized discussion covers the fossil liquefaction observed on the campus of Hokkaido University, fault outcrop at the geological boundary west of Hanamaki and at the western edge of the Kitakami lowland, morphology at the Median Tectonic Line active fault system Iyo fault, fault outcrop discovered at the Iwakuni active fault system Otake fault, and the Kokura Higashi fault and the topography surrounding it (northern part of Kyushu) are introduced. Furthermore, there are reports on the F1 fault and neotectonics in the Tan-Lu fracture zone in the Linyi area, Shandong Province, eastern part of China.

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

    Anamika Yadav


    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.

  3. Fault Detection under Fuzzy Model Uncertainty

    Marek Kowal; Józef Korbicz


    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.

  4. Online Distributed Fault Detection of Sensor Measurements

    GAO Jianliang; XU Yongjun; LI Xiaowei


    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.

  5. Fault Detection and Isolation in Centrifugal Pumps

    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...

  6. Fault Detection for Shipboard Monitoring and Decision Support Systems

    Lajic, Zoran; Nielsen, Ulrik Dam


    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...

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

    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)


    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.

  8. Active fault diagnosis by controller modification

    Stoustrup, Jakob; Niemann, Hans Henrik


    Two active fault diagnosis methods for additive or parametric faults are proposed. Both methods are based on controller reconfiguration rather than on requiring an exogenous excitation signal, as it is otherwise common in active fault diagnosis. For the first method, it is assumed that the system...... in a way that guarantees the continuity of transition and global stability using a recent result on observer parameterization. An illustrative example inspired by a field study of a drag racing vehicle is given. For the second method, an active fault diagnosis method for parametric faults is proposed...

  9. All row, planar fault detection system

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


    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.

  10. Fundamental problems in fault detection and identification

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


    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...

  11. Robust Fault Detection and Isolation for Stochastic Systems

    George, Jemin; Gregory, Irene M.


    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.

  12. Hydrogen release: new indicator of fault activity.

    Wakita, H; Nakamura, Y; Kita, I; Fujii, N; Notsu, K


    The hydrogen concentration in soil gas has been measured in the area around the Yamasaki Fault, one of the active faults in southwestern Japan. Degassing of a significant amount of hydrogen (up to more than 3 percent by volume) has been observed for sites along the fault zone. The hydrogen concentration in soil gas at sites away from the fault zone was about 0.5 part per million, almost the same as that found in the atmosphere. The spatial distribution of sites with high hydrogen concentrations is quite systematic. A hypothesis on the production of hydrogen by fault movements is postulated.

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

    Jianyong Yao


    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.

  14. Frequency Based Fault Detection in Wind Turbines

    Odgaard, Peter Fogh; Stoustrup, Jakob


    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...

  15. Model Based Fault Detection in a Centrifugal Pump Application

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


    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...

  16. An Immunology-inspired Fault Detection and Identification System

    Liguo Weng


    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.

  17. Active Fault Exploration and Seismic Hazard Assessment in Fuzhou City

    Zhu Jinfang; Han Zhujun; Huang Zonglin; Xu Xiwei; Zheng Rongzhang; Fang Shengmin; Bai Denghai; Wang Guangcai; Min Wei; Wen Xueze


    It has been proven by a number of earthquake case studies that an active fault-induced earthquake beneath a city can be devastating. It is an urgent issue for seismic hazard reduction to explore the distribution of active faults beneath the urban area and identify the seismic source and the risks underneath. As a pilot project of active fault exploration in China, the project, entitled "Active fault exploration and seismic hazard assessment in Fuzhou City",started in early 2001 and passed the check before acceptance of China Earthquake Administration in August 2004. The project was aimed to solve a series of scientific issues such as fault location, dating, movement nature, deep settings, seismic risk and hazard,preparedness of earthquake prevention and disaster reduction, and etc. by means of exploration and assessment of active faults by stages, i.e., the preliminary survey and identification of active faults in target area, the exploration of deep seismotectonic settings, the risk evaluation of active seismogenic faults, the construction of geographic information system of active faults, and so on. A lot of exploration methods were employed in the project such as the detection of absorbed mercury, free mercury and radon in soil, the geological radar,multi-channel DC electrical method, tsansient electromagnetic method, shallow seismic refraction and reflection, effect contrast of explored sources, and various sounding experiments, to establish the buried Quaternary standard section of the Fuzhou basin. By summing up, the above explorations and experiments have achieved the following results and conclusions:(1) The results of the synthetic pilot project of active fault exploration in Fuzhou City demonstrate that, on the basis of sufficient collection, sorting out and analysis of geological,geophysical and borehole data, the best method for active fault exploration (location) and seismic risk assessnent (dating and characterizing) in urban area is the combination

  18. Techniques for Surveying Urban Active Faults by Seismic Methods

    Xu Mingcai; Gao Jinghua; Liu Jianxun; Rong Lixin


    Using the seismic method to detect active faults directly below cities is an irreplaceable prospecting technique. The seismic method can precisely determine the fault position. Seismic method itself can hardly determine the geological age of fault. However, by considering in connection with the borehole data and the standard geological cross-section of the surveyed area, the geological age of reflected wave group can be qualitatively (or semi-quantitatively)determined from the seismic depth profile. To determine the upper terminal point of active faults directly below city, it is necessary to use the high-resolution seismic reflection technique.To effectively determine the geometric feature of deep faults, especially to determine the relation between deep and shallow fracture structures, the seismic reflection method is better than the seismic refraction method.

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

    D. U. Campos-Delgado


    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.

  20. A setup for active fault diagnosis

    Niemann, Hans Henrik


    A setup for active fault diagnosis (AFD) of parametric faults in dynamic systems is formulated in this paper. It is shown that it is possible to use the same setup for both open loop systems, closed loop systems based on a nominal feedback controller as well as for closed loop systems based...


    N. Selvaganesan


    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.

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

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


    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...

  3. IMU Fault Detection Based on 2-CUSUM

    Élcio Jeronimo de Oliveira


    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.

  4. Fault Detection for Diesel Engine Actuator

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


    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....

  5. Optimal Robust Fault Detection for Linear Discrete Time Systems

    Nike Liu


    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.

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

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


    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...

  7. Fault Detection of Wind Turbines with Uncertain Parameters

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


    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...

  8. Planetary Gearbox Fault Detection Using Vibration Separation Techniques

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


    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.

  9. Illuminating Northern California’s Active Faults

    Prentice, Carol S.; Crosby, Christopher J.; Whitehill, Caroline S.; Arrowsmith, J. Ramon; Furlong, Kevin P.; Philips, David A.


    Newly acquired light detection and ranging (lidar) topographic data provide a powerful community resource for the study of landforms associated with the plate boundary faults of northern California (Figure 1). In the spring of 2007, GeoEarthScope, a component of the EarthScope Facility construction project funded by the U.S. National Science Foundation, acquired approximately 2000 square kilometers of airborne lidar topographic data along major active fault zones of northern California. These data are now freely available in point cloud (x, y, z coordinate data for every laser return), digital elevation model (DEM), and KMZ (zipped Keyhole Markup Language, for use in Google EarthTM and other similar software) formats through the GEON OpenTopography Portal ( Importantly, vegetation can be digitally removed from lidar data, producing high-resolution images (0.5- or 1.0-meter DEMs) of the ground surface beneath forested regions that reveal landforms typically obscured by vegetation canopy (Figure 2)

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

    Joshi, Suresh M.


    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.

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

    Zhong, Guang-Xin; Yang, Guang-Hong


    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

    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)


    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

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


    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


    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. Active fault research in India: achievements and future perspective

    Mithila Verma


    Full Text Available This paper provides a brief overview of the progress made towards active fault research in India. An 8 m high scarp running for more than 80 km in the Rann of Kachchh is the classical example of the surface deformation caused by the great earthquake (1819 Kachchh earthquake. Integration of geological/geomorphic and seismological data has led to the identification of 67 active faults of regional scale, 15 in the Himalaya, 17 in the adjoining foredeep with as many as 30 neotectonic faults in the stable Peninsular India. Large-scale trenching programmes coupled with radiometric dates have begun to constraint the recurrence period of earthquakes; of the order of 500–1000 years for great earthquakes in the Himalaya and 10,000 years for earthquakes of >M6 in the Peninsular India. The global positioning system (GPS data in the stand alone manner have provided the fault parameters and length of rupture for the 2004 Andaman Sumatra earthquakes. Ground penetration radar (GPR and interferometric synthetic aperture radar (InSAR techniques have enabled detection of large numbers of new active faults and their geometries. Utilization of modern technologies form the central feature of the major programme launched by the Ministry of Earth Sciences, Government of India to prepare geographic information system (GIS based active fault maps for the country.

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

    Hajiyev, Ch


    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.

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

    Li, Xiao-Jian; Yang, Guang-Hong


    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.

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

    Li, Linlin


    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...

  19. Fault detection and diagnosis of diesel engine valve trains

    Flett, Justin; Bone, Gary M.


    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.

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

    Wang, Dong; Wang, Wei; Shi, Peng


    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.

  1. Export Methods in Fault Detection and Localization Mechanisms

    Aymen Belghith


    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.

  2. Remarks on Urban Active Fault Exploration and Assessment of Fault Activity

    Deng Qidong; Lu Zaoxun; Yang Zhu'en


    According to the practice of urban active fault exploration and associated fault activity assessment conducted in recent years, this paper summarizes the problems encountered in geological, geomorphological, geochemical and geophysical surveys, and proposes the following means and suggestions to solve these problems. To determine the most recent faults or fault zones, emphasis should be placed on identifying the youngest active faults and offset geomorphology. To understand the history of faulting and to discover the latest offset event, it is suggested that geophysical prospecting, drilling and trenching be conducted on one profile.Because of significant uncertainties in late Quaternary dating, we advise systematic sampling and the use of multiple dating methods. Shallow seismic reflection has been proven to be the most useful method in urban active fault exploration. However, there is a pressing need to increase the quality of data acquisition and processing to obtain high resolution images so as to enhance our ability to identify active faults. The combination of seismic P-wave reflection and S-wave reflection methods is proved to be a powerful means to investigate the tectonic environments of the deep crust.

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

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


    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...

  4. Active fault traces along Bhuj Fault and Katrol Hill Fault, and trenching survey at Wandhay, Kachchh, Gujarat, India

    Michio Morino; Javed N Malik; Prashant Mishra; Chandrashekhar Bhuiyan; Fumio Kaneko


    Several new active fault traces were identified along Katrol Hill Fault (KHF).A new fault (named as Bhuj Fault,BF)that extends into the Bhuj Plain was also identified.These fault traces were identified based on satellite photo interpretation and field survey.Trenches were excavated to identify the paleoseismic events,pattern of faulting and the nature of deformation.New active fault traces were recognized about 1 km north of the topographic boundary between the Katrol Hill and the plain area.The fault exposure along the left bank of Khari River with 10 m wide shear zone in the Mesozoic rocks and showing displacement of the overlying Quaternary deposits is indicative of continued tectonic activity along the ancient fault.The E-W trending active fault traces along the KHF in the western part changes to NE-SW or ENE-WSW near Wandhay village. Trenching survey across a low scarp near Wandhay village reveals three major fault strands F1, F2,and F3.These fault strands displaced the older terrace deposits comprising Sand,Silt and Gravel units along with overlying younger deposits from units 1 to 5 made of gravel,sand and silt. Stratigraphic relationship indicates at least three large magnitude earthquakes along KHF during Late Holocene or recent historic past.

  5. Bearing Fault Detection in Induction Motor-Gearbox Drivetrain

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


    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.

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

    Carlsson, Bengt; Zambrano, Jesús


    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.

  7. All-to-all sequenced fault detection system

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


    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.

  8. A Robust Fault Detection Approach for Nonlinear Systems

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


    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.

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

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


    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...

  10. Distance Based Fault detection in wireless sensor network

    Ayasha Siddiqua


    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.

  11. Active Faulting and Quaternary Landforms Deformation Related to the Nain Fault

    Abolghasem Gourabi


    Full Text Available Problem statement: Landforms developed across terrain defining boundary the Nain fault have imprints of recent tectonic activity in the west region of Central Iran. Depositional landforms such as alluvial fans bear signatures of later phases of tectonic activity in the form of faulting of alluvial fan deposits and development of fault traces and scarps within 100 km long and a NW-SE-trending zone, 1000-2000 m wide. Approach: We are addressing the neotectonic landforms based on detailed field work carried out in the Nain exposed active fault segments which brought forward some outstanding morphtectonic evidence of quaternary tectonically activities. Tectonic geomorphology applied to the Nain fault suggests recent subsurface activity along the Nain fault and an interconnecting faulting network of roughly NW-SE-trending, right-lateral, strike-slip segments and mostly NW-SE-oriented, transtensional to normal faults. Results: Evidence for recent activity is provided by faulted Pleistocene-Holocene deposits, fresh scarps in Late Quaternary deposits, 8-15 m lateral offsets locally affecting the drainage pattern of the area, ground creeping, aligning of series of spring faults, deflected streams and fault trace over recent alluvial fans. The existences of strike-slip faults system in the Nain area can be implications for seismic hazard. Conclusion: Motion along these structures suggests, in fact, that cumulative displacements include normal, transtensional and strike-slip components. Based on all evidence of active tectonics, earthquake risk and occurrence area is significant.

  12. Active fault survey on the Tanlu fault zone in Laizhou Bay

    WANG Zhi-cai; YANG Xi-ha; LI Chang-chuan; DENG Qi-dong; DU Xian-song; CHAO Hong-tai; WU Zi-quan; XIAO Lan-xi; SUN Zhao-ming; MIN Wei; LING Hong


    Shallow-depth acoustic reflection profiling survey has been conducted on the Tanlu fault zone in Laizhou Bay. It is found that the Tanlu fault zone is obviously active during the late Quaternary and it is still the dominating structure in this region. The Tanlu fault zone consists of two branches. The KL3 fault of the western branch is composed of several high angle normal faults which had been active during the period from the latest Pleistocene to early Holocene, dissected by a series of northeast or approximate east-west trending fault which leaped sediment of the late Pleistocene. The Longkou fault of the eastern branch consists of two right-laterally stepped segments. Late Quaternary offsets and growth strata developed along the Tanlu fault zone verify that the fault zone retained active in the latest Pleistocene to the early Holocene. The Anqiu-Juxian fault that passes through the middle of Shandong and corresponds to the Longkou fault is composed of a series of right-laterally stepped segments. The active faults along the eastern branch of the Tanlu fault zone from the Laizhou bay to the north of Anqiu make up a dextral simple shear deformation zone which is characterized by right-lateral strike-slip movement with dip-slip component during the late Quaternary.

  13. Lateral migration of fault activity in Weihe basin

    冯希杰; 戴王强


    Lateral migration of fault activity in Weihe basin is a popular phenomenon and its characteristics are also typical.Taking the activity migrations of Wangshun Mountain piedmont fault toward Lishan piedmont fault and Weinan platform front fault, Dabaopi-Niujiaojian fault toward Shenyusi-Xiaojiazhai fault, among a serial of NE-trending faults from Baoji city to Jingyang County as examples, their migration time and process are analyzed and discussed in the present paper. It is useful for further understanding the structure development and physiognomy evolution history of Weihe basin.

  14. Active probing based Internet service fault management in uncertain and noisy environment

    CHU LingWei; ZOU ShiHong; CHENG ShiDuan; WANG WenDong


    In Internet service fault management based on active probing, uncertainty and noises will affect service fault management. In order to reduce the impact, chal lenges of Internet service fault management are analyzed in this paper. Bipartite Bayesian network is chosen to model the dependency relationship between faults and probes, binary symmetric channel is chosen to model noises, and a service fault management approach using active probing is proposed for such an environment. This approach is composed of two phases: fault detection and fault diagnosis. In first phase, we propose a greedy approximation probe selection algorithm (GAPSA), which selects a minimal set of probes while remaining a high probability of fault detection. In second phase, we propose a fault diagnosis probe selection algorithm (FDPSA), which selects probes to obtain more system information based on the symptoms observed in previous phase. To deal with dynamic fault set caused by fault recovery mechanism, we propose a hypothesis inference algorithm based on fault persistent time statistic (FPTS). Simulation results prove the validity and efficiency of our approach.

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

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


    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.

  16. Fault Detection in Systems-A Fuzzy Approach

    Ashok Kumar


    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

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

    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...

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

    Dong, Hongli; Gao, Huijun


    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

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

    Odgaard, Peter Fogh; Shafiei, Seyed Ehsan


    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......In the process of lowering cost of energy of power generated by wind turbines, some focus has been drawn towards fault detection and isolation and as well as fault tolerant control of wind turbines with the purpose of increasing reliability and availability of the wind turbines. Most modern wind...

  20. Fault detection and isolation in processes involving induction machines

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


    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.

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

    Giovanini, L; Dondo, R


    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.

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

    Hanafy, Sherif M.


    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.

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

    Stelling, P.


    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.

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

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


    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.

  5. Convolutional Neural Network Based Fault Detection for Rotating Machinery

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


    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.

  6. Optimal Sensor Allocation for Fault Detection and Isolation

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


    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.

  7. Multi-directional fault detection system

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


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

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

    Odgaard, Peter Fogh; Mataji, Babak


    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...

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

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


    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.

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

    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...

  11. Stator Fault Detection in Induction Motors by Autoregressive Modeling

    Francisco M. Garcia-Guevara


    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.

  12. Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

    Fei Song; Shiyin Qin


    This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywhe...

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

    Cheung, Howard; Braun, James E.


    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.

  14. Detecting and Characterizing Active Thrust Fault and Deep-Seated Landslides in Dense Forest Areas of Southern Taiwan Using Airborne LiDAR DEM

    Rou-Fei Chen


    Full Text Available Steep topographic reliefs and heavy vegetation severely limit visibility when examining geological structures and surface deformations in the field or when detecting these features with traditional approaches, such as aerial photography and satellite imagery. However, a light detection and ranging (LiDAR-derived digital elevation model (DEM, which is directly related to the bare ground surface, is successfully employed to map topographic signatures with an appropriate scale and accuracy and facilitates measurements of fine topographic features. This study demonstrates the efficient use of 1-m-resolution LiDAR for tectonic geomorphology in forested areas and to identify a fault, a deep-seated landslide, and the regional cleavage attitude in southern Taiwan. Integrated approaches that use grayscale slope images, openness with a tint color slope visualization, the three-dimensional (3D perspective of a red relief image map, and a field investigation are employed to identify the aforementioned features. In this study, the previously inferred Meilongshan Fault is confirmed as a NE–SW-trending, eastern dipping thrust with at least a 750 m-wide deformation zone. The site where future paleoseismological studies should be performed has been identified, and someone needs to work further on this site. Signatures of deep-seated landslides, such as double ridges, trenches, main escarpments, and extension cracks, are successfully differentiated in LiDAR DEM images through the use of different visualization techniques. Systematic parallel and continuous lineaments in the images are interpreted as the regional cleavage attitude of cleavage, and a field investigation confirms this interpretation.

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

    Button, Robert M.


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

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

    Li, Hui; Yang, Chao; Hu, Yaogang


    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....

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

    Bergantino, Nicola; Caponetti, Fabio; Longhi, Sauro


    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...

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

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


    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.

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

    Rubén Francisco Manrique Piramanrique


    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. 

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

    Junda Zhu


    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.

  1. Parameter estimation and reliable fault detection of electric motors

    Dusan PROGOVAC; Le Yi WANG; George YIN


    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.

  2. Robust filtering and fault detection of switched delay systems

    Wang, Dong; Wang, Wei


    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...

  3. Quaternary Geology and Surface Faulting Hazard: Active and Capable Faults in Central Apennines, Italy

    Falcucci, E.; Gori, S.


    The 2009 L'Aquila earthquake (Mw 6.1), in central Italy, raised the issue of surface faulting hazard in Italy, since large urban areas were affected by surface displacement along the causative structure, the Paganica fault. Since then, guidelines for microzonation were drew up that take into consideration the problem of surface faulting in Italy, and laying the bases for future regulations about related hazard, similarly to other countries (e.g. USA). More specific guidelines on the management of areas affected by active and capable faults (i.e. able to produce surface faulting) are going to be released by National Department of Civil Protection; these would define zonation of areas affected by active and capable faults, with prescriptions for land use planning. As such, the guidelines arise the problem of the time interval and general operational criteria to asses fault capability for the Italian territory. As for the chronology, the review of the international literature and regulatory allowed Galadini et al. (2012) to propose different time intervals depending on the ongoing tectonic regime - compressive or extensional - which encompass the Quaternary. As for the operational criteria, the detailed analysis of the large amount of works dealing with active faulting in Italy shows that investigations exclusively based on surface morphological features (e.g. fault planes exposition) or on indirect investigations (geophysical data), are not sufficient or even unreliable to define the presence of an active and capable fault; instead, more accurate geological information on the Quaternary space-time evolution of the areas affected by such tectonic structures is needed. A test area for which active and capable faults can be first mapped based on such a classical but still effective methodological approach can be the central Apennines. Reference Galadini F., Falcucci E., Galli P., Giaccio B., Gori S., Messina P., Moro M., Saroli M., Scardia G., Sposato A. (2012). Time

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

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


    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...

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

    Ortiz, José; Carrasco, Rodrigo A.


    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.

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

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


    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.

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

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


    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...

  8. Mine-Hoist Active Fault Tolerant Control System and Strategy

    WANG Zhi-jie; WANG Yao-cai; MENG Jiang; ZHAO Peng-cheng; CHANG Yan-wei


    Based on fault diagnosis and fault tolerant technologies, the mine-hoist active fault-tolerant control system (MAFCS) is presented with corresponding strategies,, which includes the fault diagnosis module (FDM), the dynamic library (DL) and the fault-tolerant control module (FCM). When a fault is judged from some sensor by FDM, FCM reconfigure the state of MAFCS by calling the parameters from all sub libraries in DL, in order to ensure the reliability and safety of mine hoist. The simulating result shows that, MAFCS is of certain intelligence, which can adopt the corresponding control strategies according to different fault modes, even when there are quite difference between the real data and the prior fault modes.

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

    Lee SangHun


    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.

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

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


    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.

  11. Similarity measure application to fault detection of flight system

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


    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.

  12. Fault Detection in Coal Mills used in Power Plants

    Odgaard, Peter Fogh; Mataji, Babak


    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....

  13. Active Fault Characterization in the Urban Area of Vienna

    Decker, Kurt; Grupe, Sabine; Hintersberger, Esther


    The identification of active faults that lie beneath a city is of key importance for seismic hazard assessment. Fault mapping and characterization in built-up areas with strong anthropogenic overprint is, however, a challenging task. Our study of Quaternary faults in the city of Vienna starts from the re-assessment of a borehole database of the municipality containing several tens of thousands of shallow boreholes. Data provide tight constraints on the geometry of Quaternary deposits and highlight several locations with fault-delimited Middle to Late Pleistocene terrace sediments of the Danube River. Additional information is obtained from geological descriptions of historical outcrops which partly date back to about 1900. The latter were found to be particularly valuable by providing unprejudiced descriptions of Quaternary faults, sometimes with stunning detail. The along-strike continuations of some of the identified faults are further imaged by industrial 2D/3D seismic acquired outside the city limits. The interpretation and the assessment of faults identified within the city benefit from a very well constrained tectonic model of the active Vienna Basin fault system which derived from data obtained outside the city limits. This data suggests that the urban faults are part of a system of normal faults compensating fault-normal extension at a releasing bend of the sinistral Vienna Basin Transfer Fault. Slip rates estimated for the faults in the city are in the range of several hundredths of millimetres per year and match the slip rates of normal faults that were trenched outside the city. The lengths/areas of individual faults estimated from maps and seismic reach up to almost 700 km² suggesting that all of the identified faults are capable of producing earthquakes with magnitudes M>6, some with magnitudes up to M~6.7.

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

    Odgaard, Peter Fogh; Stoustrup, Jakob


    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...

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

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


    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.

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

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


    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.

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

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


    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...

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

    Stoustrup, Jakob; Niemann, Hans Henrik


    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...

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

    Kangling Liu; Xin Jin; Zhengshun Fei; Jun Liang


    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.

  20. Applying Parametric Fault Detection to a Mechanical System

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


    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...

  1. Optimal input design for fault detection and diagnosis

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


    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...

  2. Active current control in wind power plants during grid faults

    Martinez, Jorge; Kjær, Phillip C.; Rodriguez, Pedro;


    , wind turbines usually have solutions that enable the turbines to control the generation of reactive power during faults. This paper addresses the importance of using an optimal injection of active current during faults in order to fulfil these grid codes. This is of relevant importance for severe......Modern wind power plants are required and designed to ride through faults in electrical networks, subject to fault clearing. Wind turbine fault current contribution is required from most countries with a high amount of wind power penetration. In order to comply with such grid code requirements...... faults, causing low voltages at the point of common coupling. As a consequence, a new wind turbine current controller for operation during faults is proposed. It is shown that to achieve the maximum transfer of reactive current at the point of common coupling, a strategy for optimal setting of the active...

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

    Bekheïra Tabbache


    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.

  4. An application of LTR design in fault detection

    Niemann, Hans Henrik


    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...

  5. Active faulting in the Birjand region of NE Iran

    Walker, R. T.; Khatib, M. M.


    We use satellite imagery and field observations to investigate the distribution of active faults around Birjand in eastern Iran to determine how the transition between conjugate zones of faulting can be accommodated by diffuse active faulting. In the south of the study area, right-lateral strike-slip faults of the Sistan Suture Zone end in thrusts which die away westward from the strike-slip faults. These thrust terminations appear to allow a northward change to E-W thrusting in central parts of the study area. The introduction of E-W thrusting is, in turn, likely to facilitate a change to E-W left-lateral faulting north of the study region. The relatively diffuse pattern of active faulting at Birjand relates to the regional transition between N-S and E-W strike-slip faulting in northeast Iran, which involves a change from nonrotational to rotational deformation. The change from N-S to E-W faulting is likely to result from the orientation of preexisting structures in Iran and western Afghanistan, which are roughly parallel to the active fault zones. The features described at Birjand also show the influence of preexisting structure on the location and style of active faulting at a local scale, with the position of individual faults apparently controlled by inherited geological weaknesses. Very few modern earthquakes have occurred in the region of Birjand and yet destructive events are known from the historical record. The large number of active faults mapped in this study pose a substantial seismic hazard to Birjand and surrounding regions.

  6. Fault detection filter design for an anaerobic digestion process

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


    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.)

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

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


    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.

  8. Fault Detection and Isolation (Fdi Via Neural Networks

    Neeraj Prakash Srivastava,


    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. Fault detection and diagnosis using neural network approaches

    Kramer, Mark A.


    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.

  10. Active Tectonics Revealed by River Profiles along the Puqu Fault

    Ping Lu,; Yu Shang


    The Puqu Fault is situated in Southern Tibet. It is influenced by the eastward extrusion of Northern Tibet and carries the clockwise rotation followed by the southward extrusion. Thus, the Puqu Fault is bounded by the principal dynamic zones and the tectonic evolution remains active alongside. This study intends to understand the tectonic activity in the Puqu Fault Region from the river profiles obtained from the remotely sensed satellite imagery. A medium resolution Digital Elevation Model (...

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

    Jensen, Hans-Christian Becker; Wisniewski, Rafal


    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....

  12. Dynamic Output Feedback Based Active Decentralized Fault-Tolerant Control for Reconfigurable Manipulator with Concurrent Failures

    Yuanchun Li


    Full Text Available The goal of this paper is to describe an active decentralized fault-tolerant control (ADFTC strategy based on dynamic output feedback for reconfigurable manipulators with concurrent actuator and sensor failures. Consider each joint module of the reconfigurable manipulator as a subsystem, and treat the fault as the unknown input of the subsystem. Firstly, by virtue of linear matrix inequality (LMI technique, the decentralized proportional-integral observer (DPIO is designed to estimate and compensate the sensor fault online; hereafter, the compensated system model could be derived. Then, the actuator fault is estimated similarly by another DPIO using LMI as well, and the sufficient condition of the existence of H∞ fault-tolerant controller in the dynamic output feedback is presented for the compensated system model. Furthermore, the dynamic output feedback controller is presented based on the estimation of actuator fault to realize active fault-tolerant control. Finally, two 3-DOF reconfigurable manipulators with different configurations are employed to verify the effectiveness of the proposed scheme in simulation. The main advantages of the proposed scheme lie in that it can handle the concurrent faults act on the actuator and sensor on the same joint module, as well as there is no requirement of fault detection and isolation process; moreover, it is more feasible to the modularity of the reconfigurable manipulator.

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

    Jensen, Hans-Christian Becker; Wisniewski, Rafal


    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...

  14. Multilayer stress from gravity and its tectonic implications in urban active fault zone: A case study in Shenzhen, South China

    Xu, Chuang; Wang, Hai-hong; Luo, Zhi-cai; Ning, Jin-sheng; Liu, Hua-liang


    It is significant to identify urban active faults for human life and social sustainable development. The ordinary methods to detect active faults, such as geological survey, artificial seismic exploration, and electromagnetic exploration, are not convenient to be carried out in urban area with dense buildings. It is also difficult to supply information about vertical extension of the deeper faults by these methods. Gravity, reflecting the mass distribution of the Earth's interior, provides an alternative way to detect faults, which is more efficient and convenient for urban active fault detection than the aforementioned techniques. Based on the multi-scale decomposition of gravity anomalies, a novel method to invert multilayer horizontal tectonic stresses is proposed. The inverted multilayer stress fields are further used to infer the distribution and stability of the main faults. In order to validate our method, the multilayer stress fields in the Shenzhen fault zone are calculated as a case study. The calculated stress fields show that their distribution is controlled significantly by the strike of the main faults and can be used to derive depths of the faults. The main faults in Shenzhen may range from 4 km to 20 km in the depth. Each layer of the crust is nearly equipressure since the horizontal tectonic stress has small amplitude. It indicates that the main faults in Shenzhen are relatively stable and have no serious impact on planning and construction of the city.

  15. Spacing and strength of active continental strike-slip faults

    Zuza, Andrew V.; Yin, An; Lin, Jessica; Sun, Ming


    Parallel and evenly-spaced active strike-slip faults occur widely in nature across diverse tectonic settings. Despite their common existence, the fundamental question of what controls fault spacing remains unanswered. Here we present a mechanical model for the generation of parallel strike-slip faults that relates fault spacing to the following parameters: (1) brittle-crust thickness, (2) fault strength, (3) crustal strength, and (4) crustal stress state. Scaled analogue experiments using dry sand, dry crushed walnut shells, and viscous putty were employed to test the key assumptions of our quantitative model. The physical models demonstrate that fault spacing (S) is linearly proportional to brittle-layer thickness (h), both in experiments with only brittle materials and in two-layer trials involving dry sand overlying viscous putty. The S / h slope in the two-layer sand-putty experiments may be controlled by the (1) rheological/geometric properties of the viscous layer, (2) effects of distributed basal loading caused by the viscous shear of the putty layer, and/or (3) frictional interaction at the sand-putty interface (i.e., coupling between the viscous and brittle layers). We tentatively suggest that this third effect exerts the strongest control on fault spacing in the analogue experiments. By applying our quantitative model to crustal-scale strike-slip faults using fault spacing and the seismogenic-zone thickness obtained from high-resolution earthquake-location data, we estimate absolute fault friction of active strike-slip faults in Asia and along the San Andreas fault system in California. We show that the average friction coefficient of strike-slip faults in the India-Asia collisional orogen is lower than that of faults in the San Andreas fault system. Weaker faults explain why deformation penetrates >3500 km into Asia from the Himalaya and why the interior of Asia is prone to large (M > 7.0) devastating earthquakes along major intra-continental strike

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

    Baer-Ruedhart, J. L.


    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.

  17. Faulting processes in active faults - Evidences from TCDP and SAFOD drill core samples

    Janssen, C.; Wirth, R.; Wenk, H. -R.; Morales, L.; Naumann, R.; Kienast, M.; Song, S. -R.; Dresen, G. [UCB; (GFZ); (NTU)


    The microstructures, mineralogy and chemistry of representative samples collected from the cores of the San Andreas Fault drill hole (SAFOD) and the Taiwan Chelungpu-Fault Drilling project (TCDP) have been studied using optical microscopy, TEM, SEM, XRD and XRF analyses. SAFOD samples provide a transect across undeformed host rock, the fault damage zone and currently active deforming zones of the San Andreas Fault. TCDP samples are retrieved from the principal slip zone (PSZ) and from the surrounding damage zone of the Chelungpu Fault. Substantial differences exist in the clay mineralogy of SAFOD and TCDP fault gouge samples. Amorphous material has been observed in SAFOD as well as TCDP samples. In line with previous publications, we propose that melt, observed in TCDP black gouge samples, was produced by seismic slip (melt origin) whereas amorphous material in SAFOD samples was formed by comminution of grains (crush origin) rather than by melting. Dauphiné twins in quartz grains of SAFOD and TCDP samples may indicate high seismic stress. The differences in the crystallographic preferred orientation of calcite between SAFOD and TCDP samples are significant. Microstructures resulting from dissolution–precipitation processes were observed in both faults but are more frequently found in SAFOD samples than in TCDP fault rocks. As already described for many other fault zones clay-gouge fabrics are quite weak in SAFOD and TCDP samples. Clay-clast aggregates (CCAs), proposed to indicate frictional heating and thermal pressurization, occur in material taken from the PSZ of the Chelungpu Fault, as well as within and outside of the SAFOD deforming zones, indicating that these microstructures were formed over a wide range of slip rates.

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

    Leloux, Jonathan; Luna, Alberto; Desportes, Adrien


    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 ...

  19. Geophysical characteristics of active faults in Hanshin district; Katsudanso chosa eno butsuri tansa no tekiyosei

    Koreishi, Y.; Fujita, J.; Nakahigashi, H.; Asakawa, S.; Senna, S.; Ishigaki, K. [Dia Consultants Company, Tokyo (Japan)


    This paper reports the result of experiments on applicability of the geophysical investigation methods described below to investigation on active faults. The experiments were carried out in the vicinity of trenches excavated along the Nojima fault in Awaji Island and the Arima-Takatsuki tectonic line on the northern edge of the Osaka plains. Underground radar investigation is capable of identifying positions and shapes of faults and detecting difference of several ten centimeters in the levels of geological strata by applying such processing as velocity filter migration to original records that are affected largely by multiple reflections. Two-dimensional specific resistance investigation can recognize the remarkably abnormal structures in specific resistance if a clay stratum exists along a fault, and can identify fault positions and apparent inclination of faults. Investigation using S-wave reflection in a very shallow ground bed may be capable of verifying precisely fault positions if there is a noticeable change in a structure with a fault as a boundary. However, if the displacement is small, the method can identify only some signs that suggest existence of a fault. 1 ref., 4 figs., 1 tab.

  20. Fault Diagnosis in a Centrifugal Pump Using Active Magnetic Bearings

    Rainer Nordmann


    compared to state-of-the-art diagnostic tools which are only based on the measurement of the systems outputs, i.e., displacements. In this article, the different steps of the model-based diagnosis, which are modeling, generation of significant features, respectively symptoms, fault detection, and the diagnosis procedure itself are presented and in particular, it is shown how an exemplary fault is detected and identified.

  1. Faults

    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...

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

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


    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.

  3. Fault and graben growth along active magmatic divergent plate boundaries in Iceland and Ethiopia

    Trippanera, D.


    Recent studies highlight the importance of annual-scale dike-induced rifting episodes in developing normal faults and graben along the active axis of magmatic divergent plate boundaries (MDPB). However, the longer-term (102-105 years) role of diking on the cumulative surface deformation and evolution of MDPB is not yet well understood. To better understand the longer-term normal faults and graben along the axis of MDPB, we analyze fissure swarms in Iceland and Ethiopia. We first focus on the simplest case of immature fissure swarms, with single dike-fed eruptive fissures; these consist of a <1 km wide graben bordered by normal faults with displacement up to a few meters, consistent with theoretical models and geodetic data. A similar structural pattern is found, with asymmetric and multiple graben, within wider mature fissure swarms, formed by several dike-fed eruptive fissures. We then consider the lateral termination of normal faults along these graben, to detect their upward or downward propagation. Most faults terminate as open fractures on flat surface, suggesting downward fault propagation; this is consistent with recent experiments showing dike-induced normal faults propagating downward from the surface. However, some normal faults also terminate as open fractures on monoclines, which resemble fault propagation folds; this suggests upward propagation of reactivated buried faults, promoted by diking. These results suggest that fault growth and graben development, as well as the longer-term evolution of the axis of MDPB, may be explained only through dike emplacement and that any amagmatic faulting is not necessary.

  4. Insurance Applications of Active Fault Maps Showing Epistemic Uncertainty

    Woo, G.


    Insurance loss modeling for earthquakes utilizes available maps of active faulting produced by geoscientists. All such maps are subject to uncertainty, arising from lack of knowledge of fault geometry and rupture history. Field work to undertake geological fault investigations drains human and monetary resources, and this inevitably limits the resolution of fault parameters. Some areas are more accessible than others; some may be of greater social or economic importance than others; some areas may be investigated more rapidly or diligently than others; or funding restrictions may have curtailed the extent of the fault mapping program. In contrast with the aleatory uncertainty associated with the inherent variability in the dynamics of earthquake fault rupture, uncertainty associated with lack of knowledge of fault geometry and rupture history is epistemic. The extent of this epistemic uncertainty may vary substantially from one regional or national fault map to another. However aware the local cartographer may be, this uncertainty is generally not conveyed in detail to the international map user. For example, an area may be left blank for a variety of reasons, ranging from lack of sufficient investigation of a fault to lack of convincing evidence of activity. Epistemic uncertainty in fault parameters is of concern in any probabilistic assessment of seismic hazard, not least in insurance earthquake risk applications. A logic-tree framework is appropriate for incorporating epistemic uncertainty. Some insurance contracts cover specific high-value properties or transport infrastructure, and therefore are extremely sensitive to the geometry of active faulting. Alternative Risk Transfer (ART) to the capital markets may also be considered. In order for such insurance or ART contracts to be properly priced, uncertainty should be taken into account. Accordingly, an estimate is needed for the likelihood of surface rupture capable of causing severe damage. Especially where a

  5. Quaternary strike-slip crustal deformation around an active fault based on paleomagnetic analysis: a case study of the Enako fault in central Japan

    Kimura, Haruo; Itoh, Yasuto; Tsutsumi, Hiroyuki


    To evaluate cumulative strike-slip deformation around an active fault, we carried out tectonic geomorphic investigations of the active right-lateral strike-slip Enako fault in central Japan and paleomagnetic investigations of the Kamitakara pyroclastic flow deposit (KPFD; 0.6 Ma welded tuff) distributed around the fault. Tectonic geomorphic study revealed that the strike-slip displacement on the fault is ca. 150 m during the past 600 ka. We carried out measurements of paleomagnetic directions and anisotropy of magnetic susceptibility (AMS) within the pyroclastic flow deposit. Stable primary magnetic directions at each sampling site are well clustered and the AMS fabric is very oblate. We then applied tilt correction of paleomagnetic directions at 15 sites using tilting data obtained by the AMS property and orientations of eutaxitic structures. Within a distance of about 500 m from the fault trace, differential clockwise rotations were detected; the rotation angle is larger for zones closer to the fault. Because of this relation and absence of block boundary faults, a continuous deformation model explains the crustal deformation in the study area. The calculated minimum value of strike-slip displacement associated with this deformation detected within the shear zone is 210 m. The sum of this and offset on the Enako fault is 360 m and the slip rate is estimated at 0.6 mm/year.

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

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


    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...

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

    Hao YANG; Bin JIANG


    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.

  8. Active fault tolerant control of piecewise affine systems with reference tracking and input constraints

    Gholami, M.; Cocquempot, V.; Schiøler, H.;


    performance of the faulty system are held. The design of the supervisory scheme is not considered here. The set of controllers is composed of a normal controller for the fault-free case, an active fault detection and isolation controller for isolation and identification of the faults, and a set of passive...... the reference signal while the control inputs are bounded. The PFTC problem is transformed into a feasibility problem of a set of LMIs. The method is applied on a large-scale live-stock ventilation model....

  9. Structural Analysis Extended with Active Fault Isolation - Methods and Algorithms

    Gelso, Esteban R.; Blanke, Mogens


    on system inputs can considerably enhance fault isolability. This paper investigates this possibility of active fault isolation from a structural point of view. While such extension of the structural analysis approach was suggested earlier, algorithms and case studies were needed to explore this theory....... The paper develops algorithms for investigation of the possibilities of active structural isolation and it offers illustrative examples and a larger case study to explore the properties of active structural isolability ideas....

  10. Research of Earthquake Potential from Active Fault Observation in Taiwan

    Chien-Liang, C.; Hu, J. C.; Liu, C. C.; En, C. K.; Cheng, T. C. T.


    We utilize GAMIT/GLOBK software to estimate the precise coordinates for continuous GPS (CGPS) data of Central Geological Survey (CGS, MOEA) in Taiwan. To promote the software estimation efficiency, 250 stations are divided by 8 subnets which have been considered by station numbers, network geometry and fault distributions. Each of subnets include around 50 CGPS and 10 international GNSS service (IGS) stations. After long period of data collection and estimation, a time series variation can be build up to study the effect of earthquakes and estimate the velocity of stations. After comparing the coordinates from campaign-mode GPS sites and precise leveling benchmarks with the time series from continuous GPS stations, the velocity field is consistent with previous measurement which show the reliability of observation. We evaluate the slip rate and slip deficit rate of active faults in Taiwan by 3D block model DEFNODE. First, to get the surface fault traces and the subsurface fault geometry parameters, and then establish the block boundary model of study area. By employing the DEFNODE technique, we invert the GPS velocities for the best-fit block rotate rates, long term slip rates and slip deficit rates. Finally, the probability analysis of active faults is to establish the flow chart of 33 active faults in Taiwan. In the past two years, 16 active faults in central and northern Taiwan have been assessed to get the recurrence interval and the probabilities for the characteristic earthquake occurred in 30, 50 and 100 years.

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

    Runxia Guo


    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.

  12. Active Fault Diagnosis in Sampled-data Systems

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad


    The focus in this paper is on active fault diagnosis (AFD) in closed-loop sampleddata systems. Applying the same AFD architecture as for continuous-time systems does not directly result in the same set of closed-loop matrix transfer functions. For continuous-time systems, the LFT (linear fractional...... transformation) structure in the connection between the parametric faults and the matrix transfer function (also known as the fault signature matrix) applied for AFD is not directly preserved for sampled-data system. As a consequence of this, the AFD methods cannot directly be applied for sampled-data systems....... Two methods are considered in this paper to handle the fault signature matrix for sampled-data systems such that standard AFD methods can be applied. The first method is based on a discretization of the system such that the LFT structure is preserved resulting in the same LFT structure in the fault...

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

    Wonhee Lee


    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.

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

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


    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.

  15. Can cosmic ray exposure dating reveal the normal faulting activity of the Cordillera Blanca Fault, Peru?

    L.L. Siame


    Full Text Available The build-up of in situ-produced cosmogenic 10Be within bedrock scarps and escarpments associated to the Cordillera Blanca Normal Fault, Peru, was measured to evaluate, through Cosmic Ray Exposure dating, its normal faulting activity. The highest mountain peaks in Peru belong to the 210 km-long, NW- striking, Cordillera Blanca. Along its western border, the Cordillera Blanca Normal Fault is responsible for a vertical relief over 4.4 km, whose prominent 2 km high escarpment is characterized by ~1 km-high triangular facets corresponding to vertical displacements cumulated during the last 1-2 million years. At a more detailed scale, this fault system exhibits continuous geomorphic evidence of repeated displacements, underlined by 2 to 70 m-high scarps, corresponding to vertical displacements cumulated since Late Pleistocene and Holocene periods. Although microseismicity occurs along the Cordillera Blanca Normal Fault, no major historical or instrumental earthquake has been recorded since the beginning of the Spanish settlement in the 16th century. To evaluate the vertical slip rate along the major 90 km-long central segment of the Cordillera Blanca Normal Fault, the Quaternary fault escarpment (i.e., triangular facet, as well as the bedrock fault scarp, have been sampled for 10Be Cosmic Ray Exposure dating. Even if the uppermost part of the triangular facets have been resurfaced by the Last Glacial Maximum glaciers, our results allow to estimate a vertical slip-rate of 3±1 mm/yr, and suggest at least 2 seismic events during the last 3000 years.

  16. Identification of Active Faults by Aerial Photograph Interpretation and Case

    Lee, J.R.; Chang, C.J.; Choi, W.H.; Yun, K.H.; Park, D.H.; Shin, S.H. [Korea Electric Power Research Institute, Taejon (Korea)


    This report is the technical memo of the research project entitled ''Development of Technology of Advanced Seismic Safety Assessment for NPP sites''. The purposes of this report are to describe analysis methods of photographic characteristics related with active faults, to identify active faults by aerial photograph interpretation and to review case studies. (author). 27 refs., 165 figs., 8 tabs.

  17. Recent activity of Chihe segment of Tanlu fault zone

    姚大全; 刘加灿


    By means of differentiation of remote sensing image, field seismo-geological survey, analysis on drilling exploration materials, sampling and dating of rock samples, combined with seismicity and microscopic tectonic analysis, this paper studies the recent activity of Chihe segment of the Tanlu fault zone. The result indicates that the Chihe fault segment undergoes the deformation alternately in the mode of stick slip and creep during Late Quaternary, and its recent activity is mainly creep.

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

    Bibhrajit Halder; Nilanjan Sarkar


    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.

  19. The Best Combination Methods and Applied Research of Seismic Prospecting for Active Faults in Urban Areas


    This paper introduces briefly the basic principles of various seismic prospecting techniques and working methods according to nationwide practices of seismic prospecting of active faults beneath big cities in recent years. Furthermore, it analyzes the application range of different seismic prospecting methods, main achievements and solved problems, and discusses the best combination of seismic exploration methods for detecting crustal structures and locating the faults used in the present stage, that is, to trace faults which are at depths of hundred of meters underground using shallow seismic investigation, to detect the faults which are above basement (at a depth of kilometers) using high resolution refraction sounding, and the deep crustal faults using combined seismic prospecting methods of reflection seismic sounding and wide-angle reflection/refraction sounding, and furthermore, to use the 3-D deep seismic sounding method to obtain 3-D velocity structures beneath urban areas. Thus, we can get information about fault attitude and distribution at different depths and a complete image of faults from their shallow part to deep part using the combined seismic exploration method. Some application examples are presented in the article.

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

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


    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

  1. A Comparison Between Data Mining Prediction Algorithms for Fault Detection(Case study: Ahanpishegan co.)

    Amooee, Golriz; Bagheri-Dehnavi, Malihe


    In the current competitive world, industrial companies seek to manufacture products of higher quality which can be achieved by increasing reliability, maintainability and thus the availability of products. On the other hand, improvement in products lifecycle is necessary for achieving high reliability. Typically, maintenance activities are aimed to reduce failures of industrial machinery and minimize the consequences of such failures. So the industrial companies try to improve their efficiency by using different fault detection techniques. One strategy is to process and analyze previous generated data to predict future failures. The purpose of this paper is to detect wasted parts using different data mining algorithms and compare the accuracy of these algorithms. A combination of thermal and physical characteristics has been used and the algorithms were implemented on Ahanpishegan's current data to estimate the availability of its produced parts. Keywords: Data Mining, Fault Detection, Availability, Predictio...

  2. Detecting Hidden Faults and Other Lineations with UAVSAR

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


    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


    Dong Jian; Zuo Decheng; Liu Hongwei; Yang Xiaozong


    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.

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

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


    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.

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

    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....


    B. S. Anami


    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.

  7. A Study on the Quaternary Activity of the Tianjin Fault

    Shao Yongxin; Li Zhenhai; Chen Yukun; Ren Feng; Yao Zhengquan


    The Tianjin fault includes South Tianjin fault and North Tianjin fault.Based on the results of artiffcial seismic exploration,fonr borehole profiles were laid out respectively west of Jinghai county town,Chaomidian village of Xiqing district,Xiaonanhe village of Xiqing district and Zhutoudian village of Ninghe implement the exploration of these faults.Through identification of microfossils.the locations of marine beds in boreholes were obtained in this work,and through stratigraphic dating,the ages of the first,second and third marine beds were determined.Through strata correlation with the marine beds as key marker beds and integrating with the test results of paleo geomagnetism of boreholes BZ2 and TN3,the activity in the North and South Tianjin faults was analyzed and studied.The results indicate that there is no evidence of movement of the South Tianjin fault since the Late Pleistocene,but may have had weak activity before the Middle Pleistocene.No evidence of activity in the North Tianjin fanit was found since the Late Pleistocene either,but might have been active in the early stage of the Early Pleistocene.These show that the activity of the South Tianjin fault is stronger than that of the North Tianjin fault.At the same time,we find that the second,third and fourth marine beds are lacking to some extent in difierent areas.So.before they are used in strata correlation,the age of marine beds must be determined,otherwise the results of strata correlation may lead to errors.For the second marine bed,where there has been dispute about its age,we consider the age to be about 70ka.

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

    Castiglione Roberto


    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.

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

    Harrou, Fouzi


    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.



    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.

  11. Secondary Fault Activity of the North Anatolian Fault near Avcilar, Southwest of Istanbul: Evidence from SAR Interferometry Observations

    Faqi Diao


    Full Text Available Strike-slip faults may be traced along thousands of kilometers, e.g., the San Andreas Fault (USA or the North Anatolian Fault (Turkey. A closer look at such continental-scale strike faults reveals localized complexities in fault geometry, associated with fault segmentation, secondary faults and a change of related hazards. The North Anatolian Fault displays such complexities nearby the mega city Istanbul, which is a place where earthquake risks are high, but secondary processes are not well understood. In this paper, long-term persistent scatterer interferometry (PSI analysis of synthetic aperture radar (SAR data time series was used to precisely identify the surface deformation pattern associated with the faulting complexity at the prominent bend of the North Anatolian Fault near Istanbul city. We elaborate the relevance of local faulting activity and estimate the fault status (slip rate and locking depth for the first time using satellite SAR interferometry (InSAR technology. The studied NW-SE-oriented fault on land is subject to strike-slip movement at a mean slip rate of ~5.0 mm/year and a shallow locking depth of <1.0 km and thought to be directly interacting with the main fault branch, with important implications for tectonic coupling. Our results provide the first geodetic evidence on the segmentation of a major crustal fault with a structural complexity and associated multi-hazards near the inhabited regions of Istanbul, with similarities also to other major strike-slip faults that display changes in fault traces and mechanisms.

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

    Mohamed Lamine FADDA


    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.

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

    Mingping Xia


    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.

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

    Kai Yang


    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.

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

    Deng Huiyu; Wang Xinli; Ma Peisun


    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.

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

    Bai, Leishi; Tian, Zuohua; Shi, Songjiao


    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.

  17. Open-circuit fault detection and tolerant operation for a parallel-connected SAB DC-DC converter

    Park, Kiwoo; Chen, Zhe


    This paper presents an open-circuit fault detection method and its tolerant control strategy for a Parallel-Connected Single Active Bridge (PCSAB) dc-dc converter. The structural and operational characteristics of the PCSAB converter lead to several advantages especially for high power applications....... By paralleling modular converters, the power and current ratings of each modular converter can be lowered and by interleaving the switching patterns, the input and output current ripples can be significantly reduced without increasing switching losses or device stresses. Apart from these, the PCSAB converter...... of the converter unaffected or to improve the quality of the output current under the fault condition. The feasibility of the proposed fault detection and fault-tolerant methods are verified by simulations and experiments....

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

    Blanke, M.


    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....

  19. Industrial Actuator Benchmark for Fault Detection and Isolation

    Blanke, M.; Patton, R.J.


    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...

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

    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...

  1. Active faulting in apparently stable peninsular India: Rift inversion and a Holocene-age great earthquake on the Tapti Fault

    Copley, Alex; Mitra, Supriyo; Sloan, R. Alastair; Gaonkar, Sharad; Reynolds, Kirsty


    We present observations of active faulting within peninsular India, far from the surrounding plate boundaries. Offset alluvial fan surfaces indicate one or more magnitude 7.6-8.4 thrust-faulting earthquakes on the Tapti Fault (Maharashtra, western India) during the Holocene. The high ratio of fault displacement to length on the alluvial fan offsets implies high stress-drop faulting, as has been observed elsewhere in the peninsula. The along-strike extent of the fan offsets is similar to the thickness of the seismogenic layer, suggesting a roughly equidimensional fault rupture. The subsiding footwall of the fault is likely to have been responsible for altering the continental-scale drainage pattern in central India and creating the large west flowing catchment of the Tapti river. A preexisting sedimentary basin in the uplifting hanging wall implies that the Tapti Fault was active as a normal fault during the Mesozoic and has been reactivated as a thrust, highlighting the role of preexisting structures in determining the rheology and deformation of the lithosphere. The slip sense of faults and earthquakes in India suggests that deformation south of the Ganges foreland basin is driven by the compressive force transmitted between India and the Tibetan Plateau. The along-strike continuation of faulting to the east of the Holocene ruptures we have studied represents a significant seismic hazard in central India.

  2. The relationship of near-surface active faulting to megathrust splay fault geometry in Prince William Sound, Alaska

    Finn, S.; Liberty, L. M.; Haeussler, P. J.; Northrup, C.; Pratt, T. L.


    We interpret regionally extensive, active faults beneath Prince William Sound (PWS), Alaska, to be structurally linked to deeper megathrust splay faults, such as the one that ruptured in the 1964 M9.2 earthquake. Western PWS in particular is unique; the locations of active faulting offer insights into the transition at the southern terminus of the previously subducted Yakutat slab to Pacific plate subduction. Newly acquired high-resolution, marine seismic data show three seismic facies related to Holocene and older Quaternary to Tertiary strata. These sediments are cut by numerous high angle normal faults in the hanging wall of megathrust splay. Crustal-scale seismic reflection profiles show splay faults emerging from 20 km depth between the Yakutat block and North American crust and surfacing as the Hanning Bay and Patton Bay faults. A distinct boundary coinciding beneath the Hinchinbrook Entrance causes a systematic fault trend change from N30E in southwestern PWS to N70E in northeastern PWS. The fault trend change underneath Hinchinbrook Entrance may occur gradually or abruptly and there is evidence for similar deformation near the Montague Strait Entrance. Landward of surface expressions of the splay fault, we observe subsidence, faulting, and landslides that record deformation associated with the 1964 and older megathrust earthquakes. Surface exposures of Tertiary rocks throughout PWS along with new apatite-helium dates suggest long-term and regional uplift with localized, fault-controlled subsidence.

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

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


    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.

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

    Tokatlı, Figen; Cinar, Ali


    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 ...

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

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


    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....

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

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


    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.

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



    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.

  8. Machine Fault Detection Based on Filter Bank Similarity Features Using Acoustic and Vibration Analysis

    Mauricio Holguín-Londoño


    Full Text Available Vibration and acoustic analysis actively support the nondestructive and noninvasive fault diagnostics of rotating machines at early stages. Nonetheless, the acoustic signal is less used because of its vulnerability to external interferences, hindering an efficient and robust analysis for condition monitoring (CM. This paper presents a novel methodology to characterize different failure signatures from rotating machines using either acoustic or vibration signals. Firstly, the signal is decomposed into several narrow-band spectral components applying different filter bank methods such as empirical mode decomposition, wavelet packet transform, and Fourier-based filtering. Secondly, a feature set is built using a proposed similarity measure termed cumulative spectral density index and used to estimate the mutual statistical dependence between each bandwidth-limited component and the raw signal. Finally, a classification scheme is carried out to distinguish the different types of faults. The methodology is tested in two laboratory experiments, including turbine blade degradation and rolling element bearing faults. The robustness of our approach is validated contaminating the signal with several levels of additive white Gaussian noise, obtaining high-performance outcomes that make the usage of vibration, acoustic, and vibroacoustic measurements in different applications comparable. As a result, the proposed fault detection based on filter bank similarity features is a promising methodology to implement in CM of rotating machinery, even using measurements with low signal-to-noise ratio.

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



    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.

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

    Hongli Dong


    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.

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

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


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

    Lu, Kaiyuan


    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....

  13. Active faulting on the Wallula fault within the Olympic-Wallowa Lineament (OWL), eastern Washington State

    Sherrod, B. L.; Lasher, J. P.; Barnett, E. A.


    Several studies over the last 40 years focused on a segment of the Wallula fault exposed in a quarry at Finley, Washington. The Wallula fault is important because it is part of the Olympic-Wallowa lineament (OWL), a ~500-km-long topographic and structural lineament extending from Vancouver Island, British Columbia to Walla Walla, Washington that accommodates Basin and Range extension. The origin and nature of the OWL is of interest because it contains potentially active faults that are within 50 km of high-level nuclear waste facilities at the Hanford Site. Mapping in the 1970's and 1980's suggested the Wallula fault did not offset Holocene and late Pleistocene deposits and is therefore inactive. New exposures of the Finley quarry wall studied here suggest otherwise. We map three main packages of rocks and sediments in a ~10 m high quarry exposure. The oldest rocks are very fine grained basalts of the Columbia River Basalt Group (~13.5 Ma). The next youngest deposits include a thin layer of vesicular basalt, white volcaniclastic deposits, colluvium containing clasts of vesicular basalt, and indurated paleosols. A distinct angular unconformity separates these vesicular basalt-bearing units from overlying late Pleistocene flood deposits, two colluvium layers containing angular clasts of basalt, and Holocene tephra-bearing loess. A tephra within the loess likely correlates to nearby outcrops of Mazama ash. We recognize three styles of faults: 1) a near vertical master reverse or oblique fault juxtaposing very fine grained basalt against late Tertiary-Holocene deposits, and marked by a thick (~40 cm) vertical seam of carbonate cemented breccia; 2) subvertical faults that flatten upwards and displace late Tertiary(?) to Quaternary(?) soils, colluvium, and volcaniclastic deposits; and 3) flexural slip faults along bedding planes in folded deposits in the footwall. We infer at least two Holocene earthquakes from the quarry exposure. The first Holocene earthquake deformed

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

    Guolian Hou; Mifeng Ren; Lilong Du; Jianhua Zhang


    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.

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

    Guolian Hou


    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.

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

    Bingyong Yan


    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.

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

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


    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.

  18. Fault activation by hydraulic fracturing in western Canada

    Bao, Xuewei; Eaton, David W.


    Hydraulic fracturing has been inferred to trigger the majority of injection-induced earthquakes in western Canada, in contrast to the Midwestern United States, where massive saltwater disposal is the dominant triggering mechanism. A template-based earthquake catalog from a seismically active Canadian shale play, combined with comprehensive injection data during a 4-month interval, shows that earthquakes are tightly clustered in space and time near hydraulic fracturing sites. The largest event [moment magnitude (MW) 3.9] occurred several weeks after injection along a fault that appears to extend from the injection zone into crystalline basement. Patterns of seismicity indicate that stress changes during operations can activate fault slip to an offset distance of >1 km, whereas pressurization by hydraulic fracturing into a fault yields episodic seismicity that can persist for months.

  19. On infinite horizon active fault diagnosis for a class of non-linear non-Gaussian systems

    Punčochár Ivo


    Full Text Available The paper considers the problem of active fault diagnosis for discrete-time stochastic systems over an infinite time horizon. It is assumed that the switching between a fault-free and finitely many faulty conditions can be modelled by a finite-state Markov chain and the continuous dynamics of the observed system can be described for the fault-free and each faulty condition by non-linear non-Gaussian models with a fully observed continuous state. The design of an optimal active fault detector that generates decisions and inputs improving the quality of detection is formulated as a dynamic optimization problem. As the optimal solution obtained by dynamic programming requires solving the Bellman functional equation, approximate techniques are employed to obtain a suboptimal active fault detector.

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

    N. Talebi


    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.

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

    CHEN JingLong; ZI YanYang; HE ZhengJia; WANG XiaoDong


    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.

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

    Niu Erzhuo; Wang Qing; Dong Chaoyang


    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.

  3. Geophysical survey on trench excavation of active faults; Butsuri tansa to katsudanso trench chosa

    Kanayama, S.; Hasegawa, S.; Tsuruta, S. [Shikoku Research Inst. Inc., Kagawa (Japan); Kawakami, H. [Yonden Consultants Co. Inc., Kagawa (Japan)


    This paper describes cases of geophysical survey used for investigation on a few active faults, and future requirements thereof to help develop active fault surveys. Seismic exploration using the reflection method on the Nagao fault revealed distinct existence of a reverse fault with southward inclination of about 50 degrees. A crush zone caused by this fault was recognized also in the granite base. A few small crush zones in reverse direction to the main fault were found in granite in upper base of the fault, which were thought secondary to activities of the main fault. Seismic exploration using the reflection method was performed on the Iyo fault in the central tectonic line to identify underground structures of the Iyo fault and the Gunchu fault, by which the location of the Iyo fault was verified. The Chichio fault in the central tectonic line was explored by using the {rho}a-{rho}u method, and the Okamura fault in the central tectonic line by using the specific resistance imaging method. The length of a fault per action, which is always a problem, or the problem of fault groups acting associatively could not be discussed if structural analysis of ground of great depths is omitted, when estimating scales of earthquakes from active faults. 18 refs., 10 figs.

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

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


    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.

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

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


    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)....

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

    K.C. Deekshit Kompella


    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.

  7. Identification of recently active faults and folds in Java, Indonesia

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


    We analyze the spatial pattern of active deformation in Java, Indonesia with the aim of characterizing the deformation of the upper plate of the subduction zone in this region. The lack of detailed neotectonic studies in Java is mostly because of its relatively low rate of deformation in spite of significant historical seismic activity. In addition, the abundance of young volcanic materials as well as the region's high precipitation rate and vegetation cover obscure structural relationships and prevent reliable estimates of offset along active faults as well as exhumed intra-arc faults. Detailed maps of active faults derived from satellite and field-based neotectonic mapping, paleoseismic data, as well as new data on the fault kinematics and estimates of orientation of principal stresses from volcano morphology characterize recently active faults and folds. The structures in West Java are dominated by strike-slip faulting, while Central and northern part of East Java are dominated by folds and thrusting with minor normal faulting. The structures vary in length from hundreds meters to tens of kilometers and mainly trend N75°E, N8°E with some minor N45°W. Our preliminary mapping indicates that there are no large scale continuous structures in Java, and that instead deformation is distributed over wide areas along small structures. We established several paleoseismic sites along some of the identified structures. We excavated two shallow trenches along the Pasuruan fault, a normal fault striking NW-SE that forms a straight 13 km scarp cutting Pleistocene deltaic deposits of the north shore of East Java. The trenches exposed faulted and folded fluvial, alluvial and colluvial strata that record at least four ground-rupturing earthquakes since the Pleistocene. The Pasuruan site proves its potential to provide a paleoseismic record rarely found in Java. Abundant Quaternary volcanoes are emplaced throughout Java; most of the volcanoes show elongation in N100°E and N20

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

    Wang, Bright L.


    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.

  9. Insights into correlation between satellite infrared information and fault activities


    Tectonic activities are accompanied with material movement and energy transfer, which definitely change the state of thermal radiation on the ground. Thus it is possible to infer present-day tectonic activities based on variations of the thermal radiation state on the ground. The received satellite infrared information is, however, likely influenced by many kinds of factors. Therefore, the first problem that needs to be solved is to extract information on tectonic activities and eliminate effects of external (non-tectonic) factors. In this study, we firstly make a review of the current studies on this subject, and then present the technical approach and our research goal.Using the data of 20 years from the infrared band of the satellite of National Oceanic and Atmospheric Administration (NOAA) and the method we have developed, we investigate fault activities in western China. The results show that the areas with high residual values of land surface brightness temperature (LSBT), which is presumably related to faultings in space, accord usually with the locations of followed major earthquakes. The times of their value growing are also roughly consistent with the beginning of active periods of earthquakes.The low frequency component fields of the LSBT, acquired from wavelet analysis, exhibit well the spatial distributions of active faults.The "heat penetrability index" (HPI) related with enhancement of subsurface thermal information has been expressed well for the backgrounds of accelerated tectonic motions, and some correlations exist between HPI and the local faulting and seismicity. This study provides a new approach to study temporal-spatial evolution of recent activities of faults and their interactions.

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

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


    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.

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

    Ledezma, Fernando


    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.

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

    Mehdi Shadaram


    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.

  13. Active Tectonics Revealed by River Profiles along the Puqu Fault

    Ping Lu


    Full Text Available The Puqu Fault is situated in Southern Tibet. It is influenced by the eastward extrusion of Northern Tibet and carries the clockwise rotation followed by the southward extrusion. Thus, the Puqu Fault is bounded by the principal dynamic zones and the tectonic evolution remains active alongside. This study intends to understand the tectonic activity in the Puqu Fault Region from the river profiles obtained from the remotely sensed satellite imagery. A medium resolution Digital Elevation Model (DEM, 20 m was generated from an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER stereo pair of images and the stream network in this region was extracted from this DEM. The indices of slope and drainage area were subsequently calculated from this ASTER DEM. Based on the stream power law, the area-slope plots of the streams were delineated to derive the indices of channel concavity and steepness, which are closely related to tectonic activity. The results show the active tectonics varying significantly along the Puqu Fault, although the potential influence of glaciations may exist. These results are expected to be useful for a better understanding of tectonic evolution in Southeastern Tibet.

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

    Yong JIANG; Hongguang WANG; Lijin FANG; Mingyang ZHAO


    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.

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

    Silvia M. Zanoli


    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.

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

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


    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.

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

    Mehdi Ahmadi


    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.

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

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


    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...

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

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


    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.

  20. Fault detection and diagnosis for refrigerator from compressor sensor

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


    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.

  1. Information Based Fault Diagnosis

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad


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

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

    Grauer, Jared A.


    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.

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

    Maiying ZHONG; Chuanfeng MA; Steven X.DING


    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.

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

    S. hajiaghasi


    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.

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

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


    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.

  6. Active fault diagnosis based on stochastic tests

    Poulsen, Niels Kjølstad; Niemann, Hans Henrik


    or an error output from the system. The classical cumulative sum (CUSUM) test will be modified with respect to the AFD approach applied. The CUSUM method will be altered such that it will be able to detect a change in the signature from the auxiliary input signal in an (error) output signal. It will be shown...... how it is possible to apply both the gain and the phase change of the output signal in CUSUM tests. The method is demonstrated using an example....

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

    Herp, Jürgen; S. Nadimi, Esmaeil


    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....

  8. Stator fault detection for multi-phase machines with multiple reference frames transformation

    Bianchini, Claudio; Fornasiero, Emanuele; Matzen, T.N.;


    The paper focuses on a new diagnostic index for fault detection of a five-phase permanent-magnet machine. This machine has been designed for fault tolerant applications, and it is characterized by a mutual inductance equal to zero and a high self inductance, in order to limit the short-circuit cu...

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

    Hao, Jingjing; Kinnaert, Michel


    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.

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

    Schlechtingen, Meik; Santos, Ilmar


    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 ...

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

    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 prop

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

    Wei Huang


    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.


    Han Zhennan; Xiong Shibo; Li Jinbao


    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.

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

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


    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...

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

    PAN Zhongliang; CHEN Ling; ZHANG Guangzhao


    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.

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

    Zheng Dou


    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.

  17. Rotor Faults Detection in Induction Motor by Wavelet Analysis

    Neelam Mehala


    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.



    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.


    A. D. Khomonenko


    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.

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

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


    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.

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

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


    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.

  2. Earthquake Probability Assessment for the Active Faults in Central Taiwan: A Case Study

    Yi-Rui Lee


    Full Text Available Frequent high seismic activities occur in Taiwan due to fast plate motions. According to the historical records the most destructive earthquakes in Taiwan were caused mainly by inland active faults. The Central Geological Survey (CGS of Taiwan has published active fault maps in Taiwan since 1998. There are 33 active faults noted in the 2012 active fault map. After the Chi-Chi earthquake, CGS launched a series of projects to investigate the details to better understand each active fault in Taiwan. This article collected this data to develop active fault parameters and referred to certain experiences from Japan and the United States to establish a methodology for earthquake probability assessment via active faults. We consider the active faults in Central Taiwan as a good example to present the earthquake probability assessment process and results. The appropriate “probability model” was used to estimate the conditional probability where M ≥ 6.5 and M ≥ 7.0 earthquakes. Our result shows that the highest earthquake probability for M ≥ 6.5 earthquake occurring in 30, 50, and 100 years in Central Taiwan is the Tachia-Changhua fault system. Conversely, the lowest earthquake probability is the Chelungpu fault. The goal of our research is to calculate the earthquake probability of the 33 active faults in Taiwan. The active fault parameters are important information that can be applied in the following seismic hazard analysis and seismic simulation.

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

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


    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.

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

    Fang Wu


    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.

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

    YANG Hongying; YE Hao; WANG Guizeng


    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.

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

    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...

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

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


    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...

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

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


    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.

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

    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...

  10. Lateral propagation of active normal faults throughout pre-existing fault zones: an example from the Southern Apennines, Italy

    Agosta, Fabrizio; Prosser, Giacomo; Ivo Giano, Salvatore


    The main active structures in the Southern Apennines are represented by a set of NW-trending normal faults, which are mainly located in the axial sector of the chain. Evidences arising from neotectonics and seismology show activity of a composite seismic source, the Irpinia - Agri Valley, located across the Campania-Basilicata border. This seismic source is made up of two right-stepping, individual seismic sources forming a relay ramp. Each individual seismic source consists of a series of nearly parallel normal fault segments. The relay ramp area, located around the Vietri di Potenza town, is bounded by two seismic segments, the San Gregorio Magno Fault, to the NW, and the Pergola-Melandro Fault, to the SE. The possible interaction between the two right-stepping fault segments has not been proven yet, since the fault system of the area has never been analyzed in detail. This work is aimed at assessing the geometry of such fault system, inferring the relative age of the different fault sets by studying the crosscutting relationships, characterizing the micromechanics of fault rocks associated to the various fault sets, and understanding the modalities of lateral propagation of the two bounding fault segments. Crosscutting relationships are recognized by combining classical geological mapping with morphotectonic methods. This latter approach, which include the analysis of aerial photographs and field inspection of quaternary slope deposits, is used to identify the most recent structures among those cropping out in the field area. In the relay ramp area, normal faults crosscut different tectonic units of the Apennine chain piled up, essentially, during the Middle to Late Miocene. The topmost unit (only few tens of meter-thick) consists of a mélange containing blocks of different lithologies in a clayish matrix. The intermediate thrust sheet consists of 1-1.5 km-thick platform carbonates of late Triassic-Jurassic age, with dolomites at the base and limestones at the

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

    Shuping HE; Fei LIU


    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.

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


    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

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

    JIN Xuexiang; ZHANG Yi; LI Li; HU Jianming


    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.

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

    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


    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.

  15. The Activity of Liaocheng-Lankao Buried Fault During the Quaternary——An Important Buried Active Fault in the Eastern China Plain

    Xiang Hongfa; Wang Xuechao; Hao Shujian; Zhang Hui; Guo Shunmin; Li Jinzhao; Li Hongwu; Lin Yuanwu; Zhang Wanxia


    On the basis of locating by the geochemical prospecting, shallow seismic sounding, drilling,geological profiling, and neogeochronological dating, we first found out the dislocation amount along the Liaocheng-Lankao buried fault since the Quaternary and the age of its latest activity phase and determined that the upper break point by the fault dislocation reaches 20 m below the surface. The latest activity phase was in the early Holocene and the fault is a shallow-buried active fault. An average dislocation rate along the fault is 0.12 mm/a since the Quaternary.Thus, it is a buried active fault with intermediate to strong movement strength in the eastern China.

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

    Wei Teng


    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.

  17. Repetitive transients extraction algorithm for detecting bearing faults

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


    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.

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

    Sun, Junhua; Xiao, Zhongwen


    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.

  19. Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

    Fei Song


    Full Text Available This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywheel is activated to counteract the fault effect and ensure that the satellite is working safely and reliably. The active disturbance rejection approach is employed to design the controller, which handles input information with tracking differentiator, estimates system uncertainties with extended state observer, and generates control variables by state feedback and compensation. The designed active disturbance rejection controller is robust to both internal dynamics and external disturbances. The bandwidth parameter of extended state observer is optimized by the artificial bee colony algorithm so as to improve the performance of attitude control system. A series of simulation experiment results demonstrate the performance superiorities of the proposed robust fault-tolerant control algorithm.

  20. Active fault segments as potential earthquake sources: Inferences from integrated geophysical mapping of the Magadi fault system, southern Kenya Rift

    Kuria, Z. N.; Woldai, T.; van der Meer, F. D.; Barongo, J. O.


    Southern Kenya Rift has been known as a region of high geodynamic activity expressed by recent volcanism, geothermal activity and high rate of seismicity. The active faults that host these activities have not been investigated to determine their subsurface geometry, faulting intensity and constituents (fluids, sediments) for proper characterization of tectonic rift extension. Two different models of extension direction (E-W to ESE-WNW and NW-SE) have been proposed. However, they were based on limited field data and lacked subsurface investigations. In this research, we delineated active fault zones from ASTER image draped on ASTER DEM, together with relocated earthquakes. Subsequently, we combined field geologic mapping, electrical resistivity, ground magnetic traverses and aeromagnetic data to investigate the subsurface character of the active faults. Our results from structural studies identified four fault sets of different age and deformational styles, namely: normal N-S; dextral NW-SE; strike slip ENE-WSW; and sinistral NE-SW. The previous studies did not recognize the existence of the sinistral oblique slip NE-SW trending faults which were created under an E-W extension to counterbalance the NW-SE faults. The E-W extension has also been confirmed from focal mechanism solutions of the swarm earthquakes, which are located where all the four fault sets intersect. Our findings therefore, bridge the existing gap in opinion on neo-tectonic extension of the rift suggested by the earlier authors. Our results from resistivity survey show that the southern faults are in filled with fluid (0.05 and 0.2 Ωm), whereas fault zones to the north contain high resistivity (55-75 Ωm) material. The ground magnetic survey results have revealed faulting activity within active fault zones that do not contain fluids. In addition, the 2D inversion of the four aero-magnetic profiles (209 km long) revealed: major vertical to sub vertical faults (dipping 75-85° east or west); an

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

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


    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.

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

    Martinez-Guerra, Rafael


    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...

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

    Xiang, Mei; Xiang, Zhengrong


    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.

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

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


    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.

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

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


    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.

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

    YangTianshe; LiHuaizu; SunYanbong


    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.

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

    Stoustrup, Jakob; Niemann, Hans Henrik


    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...

  8. Fault Detection and Localization Method for Modular Multilevel Converters

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


    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...

  9. Optimal Threshold Functions for Fault Detection and Isolation

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


    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...

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

    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.

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

    Yang, Jie; McArdle, Conor; Daniels, Stephen


    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.

  12. The Garzon fault: active southwestern boundary of the Caribbean plate in Colombia

    Chorowicz, J.; Chotin, P.; Guillande, R.


    We propose active right-lateral strike-slip motion on the Garzon fault zone of the Neiva basin, Colombia, based on the identification of two active right-stepping releasing bend basins along the fault using stereoscopic analysis of 1/250000 SPOT images. The Garzon fault connects the Bocono-Pamplona-Guaicaramo fault zones of Venezuela and Colombia with the Romeral, Dolores and Guayaquil faults of Colombia. Together these faults form a continuous, active right-lateral fault between accreted terranes in northwestern South America and a more stable South America plate. We infer 5-km right-lateral offset of the Garzon fault based on the width of the Algeciras releasing bend basin.

  13. Safety enhancement of oil trunk pipeline crossing active faults on Sakhalin Island

    Tishkina, E.; Antropova, N.; Korotchenko, T.


    The article explores the issues concerning safety enhancement of pipeline active fault crossing on Sakhalin Island. Based on the complexity and analysis results, all the faults crossed by pipeline system are classified into five categories - from very simple faults to extremely complex ones. The pipeline fault crossing design is developed in accordance with the fault category. To enhance pipeline safety at fault crossing, a set of methods should be applied: use of pipes of different safety classes and special trench design in accordance with soil permeability characteristics.

  14. Searching for Seismically Active Faults in the Gulf of Cadiz

    Custodio, S.; Antunes, V.; Arroucau, P.


    The repeated occurrence of large magnitude earthquakes in southwest Iberia in historical and instrumental times suggests the presence of active fault segments in the region. However, due to an apparently diffuse seismicity pattern defining a broad region of distributed deformation west of Gibraltar Strait, the question of the location, dimension and geometry of such structures is still open to debate. We recently developed a new algorithm for earthquake location in 3D complex media with laterally varying interface depths, which allowed us to relocate 2363 events having occurred from 2007 to 2013, using P- and S-wave catalog arrival times obtained from the Portuguese Meteorological Institute (IPMA, Instituto Portugues do Mar e da Atmosfera), for a study area lying between 8.5˚W and 5˚W in longitude and 36˚ and 37.5˚ in latitude. The most remarkable change in the seismicity pattern after relocation is an apparent concentration of events, in the North of the Gulf of Cadiz, along a low angle northward-dipping plane rooted at the base of the crust, which could indicate the presence of a major fault. If confirmed, this would be the first structure clearly illuminated by seismicity in a region that has unleashed large magnitude earthquakes. Here, we present results from the joint analysis of focal mechanism solutions and waveform similarity between neighboring events from waveform cross-correlation in order to assess whether those earthquakes occur on the same fault plane.

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

    Odgaard, Peter Fogh; Stoustrup, Jakob


    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...

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

    Saud Altaf


    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.

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

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


    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.

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

    Steffen Haus


    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

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

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


    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.

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

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


    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.

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

    Khelouat, Samir


    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.

  2. Active fault and other geological studies for seismic assessment: present state and problems

    Kakimi, Toshihiro [Nuclear Power Engineering Corp., Tokyo (Japan)


    Evaluation system of earthquakes from an active fault is, in Japan, based on the characteristic earthquake model of a wide sense that postulates essentially the same (nearly the maximum) magnitude and recurrence interval during the recent geological times. Earthquake magnitude M is estimated by empirical relations among M, surface rupture length L, and surface fault displacement D per event of the earthquake faults on land in Japan. Recurrence interval R of faulting/earthquake is calculated from D and the long-term slip rate S of a fault as R=D/S. Grouping or segmentation of complicatedly distributed faults is an important, but difficult problem in order to distinguish a seismogenic fault unit corresponding to an individual characteristic earthquake. If the time t of the latest event is obtained, the `cautiousness` of a fault can be judged from R-t or t/R. According to this idea, several faults whose t/R exceed 0.5 have been designated as the `precaution faults` having higher probability of earthquake occurrence than the others. A part of above evaluation has been introduced at first into the seismic-safety examination system of NPPs in 1978. According to the progress of research on active faults, the weight of interest in respect to the seismic hazard assessment shifted gradually from the historic data to the fault data. Most of recent seismic hazard maps have been prepared in consideration with active faults on land in Japan. Since the occurrence of the 1995 Hyogoken-Nanbu earthquake, social attention has been concentrated upon the seismic hazard due to active faults, because this event was generated from a well-known active fault zone that had been warned as a `precaution fault`. In this paper, a few recent topics on other geological and geotechnical researches aiming at improving the seismic safety of NPPs in Japan were also introduced. (J.P.N.)

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

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


    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.

  4. Comparative Study of Parametric and Non-parametric Approaches in Fault Detection and Isolation

    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...

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

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


    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.

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

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


    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)

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


    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.

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

    MENG Tao; LIAO Ming-fu


    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.

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

    Javier Rosero García; José Luis Romeral; Esteban Rosero García


    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...

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


    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...

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


    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...

  12. Dense seismic networks as a tool to characterize active faulting in regions of slow deformation

    Custódio, Susana; Arroucau, Pierre; Carrilho, Fernando; Cesca, Simone; Dias, Nuno; Matos, Catarina; Vales, Dina


    The theory of plate tectonics states that the relative motion between lithospheric plates is accommodated at plate boundaries, where earthquakes occur on long faults. However, earthquakes with a wide range of magnitudes also occur both off plate boundaries, in intra-plate settings, and along discontinuous, diffuse plate boundaries. These settings are characterized by low rates of lithospheric deformation. A fundamental limitation in the study of slowly deforming regions is the lack of high-quality observations. In these regions, earthquake catalogs have traditionally displayed diffuse seismicity patterns. The location, geometry and activity rate of faults - all basic parameters for understanding fault dynamics - are usually poorly known. The dense seismic networks deployed in the last years around the world have opened new windows in observational seismology. Although high-magnitude earthquakes are rare in regions of slow deformation, low-magnitude earthquakes are well observable on the time-scale of these deployments. In this presentation, we will show how data from dense seismic deployments can be used to characterize faulting in regions of slow deformation. In particular, we will present the case study of western Iberia, a region undergoing low-rate deformation and which has generated some of the largest earthquakes in Europe, both intraplate (mainland) and interplate (offshore). The methods that we employ include automated earthquake detection methods to lower the completeness magnitude of catalogs, earthquake relocations, focal mechanisms patterns, waveform similarity and clustering analysis.

  13. Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation.

    Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed


    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.

  14. Fault detection of a spur gear using vibration signal with multivariable statistical parameters

    Songpon Klinchaeam


    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.

  15. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor


    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.

  16. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings: Preprint

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor


    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.

  17. Rolling Bearing Fault Detection Based on the Teager Energy Operator and Elman Neural Network

    Hongmei Liu


    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.

  18. Fault Detection and Localization in Transmission Lines with a Static Synchronous Series Compensator



    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.

  19. Fault Detection Enhancement in Rolling Element Bearings via Peak-Based Multiscale Decomposition and Envelope Demodulation

    Hua-Qing Wang


    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.

  20. An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction

    Zhang, Yan; Tang, Baoping; Liu, Ziran; Chen, Rengxiang


    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

  1. Aftershocks illuminate the 2011 Mineral, Virginia, earthquake causative fault zone and nearby active faults

    Horton, Jr., J. Wright; Shah, Anjana K.; McNamara, Daniel E.; Snyder, Stephen L.; Carter, Aina M


    Deployment of temporary seismic stations after the 2011 Mineral, Virginia (USA), earthquake produced a well-recorded aftershock sequence. The majority of aftershocks are in a tabular cluster that delineates the previously unknown Quail fault zone. Quail fault zone aftershocks range from ~3 to 8 km in depth and are in a 1-km-thick zone striking ~036° and dipping ~50°SE, consistent with a 028°, 50°SE main-shock nodal plane having mostly reverse slip. This cluster extends ~10 km along strike. The Quail fault zone projects to the surface in gneiss of the Ordovician Chopawamsic Formation just southeast of the Ordovician–Silurian Ellisville Granodiorite pluton tail. The following three clusters of shallow (illuminate other faults. (1) An elongate cluster of early aftershocks, ~10 km east of the Quail fault zone, extends 8 km from Fredericks Hall, strikes ~035°–039°, and appears to be roughly vertical. The Fredericks Hall fault may be a strand or splay of the older Lakeside fault zone, which to the south spans a width of several kilometers. (2) A cluster of later aftershocks ~3 km northeast of Cuckoo delineates a fault near the eastern contact of the Ordovician Quantico Formation. (3) An elongate cluster of late aftershocks ~1 km northwest of the Quail fault zone aftershock cluster delineates the northwest fault (described herein), which is temporally distinct, dips more steeply, and has a more northeastward strike. Some aftershock-illuminated faults coincide with preexisting units or structures evident from radiometric anomalies, suggesting tectonic inheritance or reactivation.

  2. Incipient Stator Insulation Fault Detection of Permanent Magnet Synchronous Wind Generators Based on Hilbert–Huang Transformation

    Wang, Chao; Liu, Xiao; Chen, Zhe


    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 i...

  3. Improved Data-based Fault Detection Strategy and Application to Distillation Columns

    Madakyaru, Muddu


    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.

  4. A hybrid fault detection and isolation strategy for a team of cooperating unmanned vehicles

    Tousi, M. M.; Khorasani, K.


    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.

  5. Implementation of a high-impedance fault detection algorithm. Final report

    Balser, S.J.; Lawrence, D.J.; Caprino, B.; Delaney, L.


    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.

  6. Fault detection based on H∞ states observer for networked control systems

    Zhu Zhangqing; Jiao Xiaocheng


    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.

  7. Compressive Sensing of Roller Bearing Faults via Harmonic Detection from Under-Sampled Vibration Signals.

    Tang, Gang; Hou, Wei; Wang, Huaqing; Luo, Ganggang; Ma, Jianwei


    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.

  8. Fault Detection of Inline Reciprocating Diesel Engine: A Mass and Gas-Torque Approach

    S. H. Gawande


    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.

  9. Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer

    Byung Eun Lee


    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.

  10. E-core transverse flux machine with integrated fault detection system

    Rasmussen, Peter Omand; Runólfsson, Gunnar; Thorsdóttir, Thórunn Ágústa;


    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...

  11. Application of Residual-Based EWMA Control Charts for Detecting Faults in Variable-Air-Volume Air Handling Unit System

    Haitao Wang


    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...

  12. Observer-based Fault Detection and Isolation for Nonlinear Systems

    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...

  13. Comprehensive bearing condition monitoring algorithm for incipient fault detection using acoustic emission

    Amit R. Bhende


    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.

  14. The northwest trending north Boquerón Bay-Punta Montalva Fault Zone; A through going active fault system in southwestern Puerto Rico

    Roig‐Silva, Coral Marie; Asencio, Eugenio; Joyce, James


    The North Boquerón Bay–Punta Montalva fault zone has been mapped crossing the Lajas Valley in southwest Puerto Rico. Identification of the fault was based upon detailed analysis of geophysical data, satellite images, and field mapping. The fault zone consists of a series of Cretaceous bedrock faults that reactivated and deformed Miocene limestone and Quaternary alluvial fan sediments. The fault zone is seismically active (local magnitude greater than 5.0) with numerous locally felt earthquakes. Focal mechanism solutions suggest strain partitioning with predominantly east–west left-lateral displacements with small normal faults striking mostly toward the northeast. Northeast-trending fractures and normal faults can be found in intermittent streams that cut through the Quaternary alluvial fan deposits along the southern margin of the Lajas Valley, an east–west-trending 30-km-long fault-controlled depression. Areas of preferred erosion within the alluvial fan trend toward the west-northwest parallel to the onland projection of the North Boquerón Bay fault. The North Boquerón Bay fault aligns with the Punta Montalva fault southeast of the Lajas Valley. Both faults show strong southward tilting of Miocene strata. On the western end, the Northern Boquerón Bay fault is covered with flat-lying Holocene sediments, whereas at the southern end the Punta Montalva fault shows left-lateral displacement of stream drainage on the order of a few hundred meters.

  15. GMDH and neural networks applied in monitoring and fault detection in sensors in nuclear power plants

    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)


    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 detection of excavator's hydraulic system based on dynamic principal component analysis

    HE Qing-hua; HE Xiang-yu; ZHU Jian-xin


    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.

  17. Improved nonlinear fault detection strategy based on the Hellinger distance metric: Plug flow reactor monitoring

    Harrou, Fouzi


    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.

  18. Bispectrum of stator phase current for fault detection of induction motor.

    Treetrong, Juggrapong; Sinha, Jyoti K; Gu, Fengshu; Ball, Andrew


    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.

  19. Design of a novel knowledge-based fault detection and isolation scheme.

    Zhao, Qing; Xu, Zhihan


    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.

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

    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)


    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].

  1. Robust unknown input observer design for state estimation and fault detection using linear parameter varying model

    Li, Shanzhi; Wang, Haoping; Aitouche, Abdel; Tian, Yang; Christov, Nicolai


    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.

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

    Zhou, Binzhong 13Hatherly, Peter


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

  3. Fault detection and optimization for networked control systems with uncertain time-varying delay

    Qing Wang; Zhaolei Wang; Chaoyang Dong; Erzhuo Niu


    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.

  4. Open-switch fault detection method of an NPC converter for wind turbine systems

    Lee, June-Seok; Lee, Kyo-Beum; Blaabjerg, Frede


    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...

  5. Data-driven fault detection for industrial processes canonical correlation analysis and projection based methods

    Chen, Zhiwen


    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...

  6. Broken Bar Fault Detection in IM Operating Under No-Load Condition

    RELJIC, D.


    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.

  7. Effective confidence interval estimation of fault-detection process of software reliability growth models

    Fang, Chih-Chiang; Yeh, Chun-Wu


    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.

  8. Tsunamigenic potential of Mediterranean fault systems and active subduction zones

    Petricca, Patrizio; Babeyko, Andrey


    Since the North East Atlantic and Mediterranean Tsunami Warning System (NEAMTWS) is under development by the European scientific community, it becomes necessary to define guidelines for the characterization of the numerous parameters must be taken into account in a fair assessment of the risk. Definition of possible tectonic sources and evaluation of their potential is one of the principal issues. In this study we systematically evaluate tsunamigenic potential of up-to-now known real fault systems and active subduction interfaces in the NEAMTWS region. The task is accomplished by means of numerical modeling of tsunami generation and propagation. We have simulated all possible uniform-slip ruptures populating fault and subduction interfaces with magnitudes ranging from 6.5 up to expected Mmax. A total of 15810 individual ruptures were processed. For each rupture, a tsunami propagation scenario was computed in linear shallow-water approximation on 1-arc minute bathymetric grid (Gebco_08) implying normal reflection boundary conditions. Maximum wave heights at coastal positions (totally - 23236 points of interest) were recorded for four hours of simulation and then classified according to currently adopted warning level thresholds. The resulting dataset allowed us to classify the sources in terms of their tsunamigenic potential as well as to estimate their minimum tsunamigenic magnitude. Our analysis shows that almost every source in the Mediterranean Sea is capable to produce local tsunami at the advisory level (i.e., wave height > 20 cm) starting from magnitude values of Mw=6.6. In respect to the watch level (wave height > 50 cm), the picture is less homogeneous: crustal sources in south-west Mediterranean as well as East-Hellenic arc need larger magnitudes (around Mw=7.0) to trigger watch levels even at the nearby coasts. In the context of the regional warning (i.e., source-to-coast distance > 100 km) faults also behave more heterogeneously in respect to the minimum

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

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


    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

  10. Architecture for Intrusion Detection System with Fault Tolerance Using Mobile Agent

    Chintan Bhatt


    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.

  11. On Optimal Fault Detection for Discrete-time Markovian Jump Linear Systems

    LI Yue-Yang; ZHONG Mai-Ying


    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.

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

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


    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.

  13. Sensor fault detection and isolation in doubly-fed induction generators accounting for parameter variations

    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)


    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)

  14. A Desk-top tutorial Demonstration of Model-based Fault Detection and Diagnosis

    Shi, John Z.; Elshanti, Ali; Gu, Fengshou; Ball, Andrew


    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 ...

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

    Jun-tong Qi; Jian-da Han


    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.

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

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


    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...

  17. Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

    Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng


    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.

  18. Detection of Stator Winding Fault in Induction Motor Using Fuzzy Logic with Optimal Rules

    Hamid Fekri Azgomi


    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.

  19. Simple random sampling-based probe station selection for fault detection in wireless sensor networks.

    Huang, Rimao; Qiu, Xuesong; Rui, Lanlan


    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.

  20. Model-based robust estimation and fault detection for MEMS-INS/GPS integrated navigation systems

    Miao Lingjuan


    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.

  1. Model-based robust estimation and fault detection for MEMS-INS/GPS integrated navigation systems

    Miao Lingjuan; Shi Jing


    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.

  2. Fault Detection of Wind Turbines with Uncertain Parameters: A Set-Membership Approach

    Thomas Bak


    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.

  3. Sliding mode observer based incipient sensor fault detection with application to high-speed railway traction device.

    Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui


    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.

  4. Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor

    Furqan Asghar


    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.

  5. Delineating active faults by using integrated geophysical data at northeastern part of Cairo, Egypt

    Sultan Awad Sultan Araffa


    Full Text Available Geophysical techniques such as gravity, magnetic and seismology are perfect tools for detecting subsurface structures of local, regional as well as of global scales. The study of the earthquake records can be used for differentiating the active and non active fault elements. In the current study more than 2200 land magnetic stations have been measured by using two proton magnetometers. The data is corrected for diurnal variations and then reduced by IGRF. The corrected data have been interpreted by different techniques after filtering the data to separate shallow sources (basaltic sheet from the deep sources (basement complex. Both Euler deconvolution and 3-D magnetic modeling have been carried out. The results of our interpretation have indicated that the depth to the upper surface of basaltic sheet ranges from less than 10–600 m, depth to the lower surface ranges from 60 to 750 m while the thickness of the basaltic sheet varies from less than 10–450 m. Moreover, gravity measurements have been conducted at the 2200 stations using a CG-3 gravimeter. The measured values are corrected to construct a Bouguer anomaly map. The least squares technique is then applied for regional residual separation. The third order of least squares is found to be the most suitable to separate the residual anomalies from the regional one. The resultant third order residual gravity map is used to delineate the structural fault systems of different characteristic trends. The trends are a NW–SE trend parallel to that of Gulf of Suez, a NE–SW trend parallel to the Gulf of Aqaba and an E–W trend parallel to the trend of Mediterranean Sea. Taking seismological records into consideration, it is found that most of 24 earthquake events recorded in the study area are located on fault elements. This gives an indication that the delineated fault elements are active.


    Pan Zhongliang


    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.

  7. Fault Detection Based on Tracking Differentiator Applied on the Suspension System of Maglev Train

    Hehong Zhang


    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

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


    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. Robust Fault Detection of Linear Uncertain Time-Delay Systems Using Unknown Input Observers

    Saeed Ahmadizadeh


    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.

  10. Voltage Based Detection Method for High Impedance Fault in a Distribution System

    Thomas, Mini Shaji; Bhaskar, Namrata; Prakash, Anupama


    High-impedance faults (HIFs) on distribution feeders cannot be detected by conventional protection schemes, as HIFs are characterized by their low fault current level and waveform distortion due to the nonlinearity of the ground return path. This paper proposes a method to identify the HIFs in distribution system and isolate the faulty section, to reduce downtime. This method is based on voltage measurements along the distribution feeder and utilizes the sequence components of the voltages. Three models of high impedance faults have been considered and source side and load side breaking of the conductor have been studied in this work to capture a wide range of scenarios. The effect of neutral grounding of the source side transformer is also accounted in this study. The results show that the algorithm detects the HIFs accurately and rapidly. Thus, the faulty section can be isolated and service can be restored to the rest of the consumers.

  11. Fault Detection and Isolation for a Supermarket Refrigeration System - Part Two

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


    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...

  12. Fault detection approach based on Bond Graph observers: Hydraulic System Case Study

    Ghada Saoudi


    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

  13. Detection and Modeling of High-Dimensional Thresholds for Fault Detection and Diagnosis

    He, Yuning


    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.

  14. A Self-Learning Sensor Fault Detection Framework for Industry Monitoring IoT

    Yu Liu


    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. Simulation Research of Fault Model of Detecting Rotor Dynamic Eccentricity in Brushless DC Motor Based on Motor Current Signature Analysis


    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.

  16. Increasing the Probability of Fault Detection in Non Perfect Inspection Model of Delay Time Analysis with Compromise on Inspection Time

    Babu Chellappachetty


    Full Text Available This study separates the real inspection content (soft portion within the total maintenance inspection activity and attempts to repeat the same some additional number of times during actual inspection. Effect of repetition of soft portion on inspection related time, fault detection probability and the consequence variable of down time per unit time is analyzed. Statistical test proves that both the inspection time and probability of fault detection has nearly same rate of influence on the consequence variable though in opposite direction. A factor ω is introduced to account for the proportion of soft portion over the maintenance inspection time. As the number of repetitions of soft portion is increased for a given value of ω, it is found from analysis that the new set of inspection time and probability of fault detection improves downtime per unit time until an optimum number of repetitions is reached. Improvement is better as the value of ω is on the lower side. The practitioner is to take this possibility of soft repeatable portion of maintenance inspection time into account while estimating these two input parameters when employing delay time methodology as a preventive maintenance strategy.

  17. Fault diagnosis of downhole drilling incidents using adaptive observers and statistical change detection

    Willersrud, Anders; Blanke, Mogens; Imsland, Lars


    Downhole abnormal incidents during oil and gas drilling causes costly delays, any may also potentially lead to dangerous scenarios. Dierent incidents willcause changes to dierent parts of the physics of the process. Estimating thechanges in physical parameters, and correlating these with changes...... expectedfrom various defects, can be used to diagnose faults while in development.This paper shows how estimated friction parameters and ow rates can de-tect and isolate the type of incident, as well as isolating the position of adefect. Estimates are shown to be subjected to non......-Gaussian,t-distributednoise, and a dedicated multivariate statistical change detection approach isused that detects and isolates faults by detecting simultaneous changes inestimated parameters and ow rates. The properties of the multivariate di-agnosis method are analyzed, and it is shown how detection and false alarmprobabilities...

  18. Adaptive FTC based on Control Allocation and Fault Accommodation for Satellite Reaction Wheels

    Baldi, P.; Blanke, Mogens; P. Castaldi; Mimmo, N.; S. Simani


    This paper proposes an active fault tolerant control scheme to cope with faults or failures affecting the flywheel spin rate sensors or satellite reaction wheel motors. The active fault tolerant control system consists of a fault detection and diagnosis module along with a control allocationand fault accommodation module directly exploiting the on-line fault estimates. The use of the nonlinear geometric approach and radial basis function neural networks allows to obtain a precise fault isolat...

  19. Electromagnetic and acoustic bimodality for the detection and localization of electrical arc faults

    Vasile, C.; Ioana, C.; Digulescu, A.; Candel, I.


    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.

  20. Smart Sensor for Online Detection of Multiple-Combined Faults in VSD-Fed Induction Motors

    Garcia-Ramirez, Armando G.; Osornio-Rios, Roque A.; Granados-Lieberman, David; Garcia-Perez, Arturo; Romero-Troncoso, Rene J.


    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).

  1. Fault Detection and Recovery in Wireless Sensor Network Using Clustering

    Abolfazl Akbari


    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.

  2. A Novel Approach to Detect Symmetrical Faults Occurring During Power Swings by Using Abrupt change of Impedance Trajectory

    Khodaparast, Jalal; Silva, Filipe Miguel Faria da; Bak, Claus Leth;


    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...

  3. System identification aided design of observer-based fault detection systems; Prozessidentifikations-basierter Entwurf beobachtergestuetzter Fehlerdetektionssysteme

    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)


    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.)

  4. Application of black-box models to HVAC systems for fault detection

    Peitsman, H.C.; Bakker, V.E.


    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

  5. Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches

    Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam


    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...

  6. Model-based fault detection for generator cooling system in wind turbines using SCADA data

    Borchersen, Anders Bech; Kinnaert, Michel


    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...

  7. Closed-loop fault detection for full-envelope flight vehicle with measurement delays

    Wang Zhaolei


    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.

  8. Robust fault detection of linear systems using a computationally efficient set-membership method

    Tabatabaeipour, Mojtaba; Bak, Thomas


    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...

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

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


    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...

  10. On-demand thread-level fault detection in a concurrent programming environment

    Fu, J.; Yang, Q.; Poss, R.; Jesshope, C.R.; Zhang, C.; Jeschke, H.; Silvén, O.


    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

  11. A Fault Detection Mechanism in a Data-flow Scheduled Multithreaded Processor

    Fu, J.; Yang, Q.; Poss, R.; Jesshope, C.R.; Zhang, C.


    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

  12. Transient Monitoring Function–Based Fault Detection for Inverter-Interfaced Microgrids

    Sadeghkhani, Iman; Esmail Hamedani Golshan, Mohamad; Mehrizi-Sani, Ali;


    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...

  13. Karhunen Loeve Basis Used for Detection of Gearbox Faults in a Wind Turbine

    Odgaard, Peter Fogh; Stoustrup, Jakob


    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...

  14. The characteristics of Quaternary activity of faults in the sea area near the Yangtze River mouth

    章振铨; 火恩杰; 刘昌森; 王锋


    By shallow seismic prospecting, it is showed that the faults in the sea area near the Yangtze River mouth are mainly the NE and NW-trending faults. The main activity time of fault is Pliocene to Early Pleistocene, and the latest activity is up to Middle Pleistocene. The maximum of fault is generally several tens meters with the throw decreased upward. The dislocation near the bottom of Middle Pleistocene is 12~13 m. The average vertical displacement rate is on a level of 10-3 mm/a.

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

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


    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.

  16. Fault Detection and Diagnosis of Railway Point Machines by Sound Analysis.

    Lee, Jonguk; Choi, Heesu; Park, Daihee; Chung, Yongwha; Kim, Hee-Young; Yoon, Sukhan


    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.

  17. Fault Detection and Diagnosis of Railway Point Machines by Sound Analysis

    Jonguk Lee


    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.

  18. Simultaneous fault detection and control for stochastic time-delay systems

    Meng, Xian-Ji; Yang, Guang-Hong


    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.

  19. Choice Of Input Data Type Of Artificial Neural Network To Detect Faults In Alternative Current Systems

    T. Benslimane


    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

    Hanson, Matt


    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. Preservation of amorphous ultrafine material: A proposed proxy for slip during recent earthquakes on active faults

    Hirono, Tetsuro; Asayama, Satoru; Kaneki, Shunya; Ito, Akihiro


    The criteria for designating an “Active Fault” not only are important for understanding regional tectonics, but also are a paramount issue for assessing the earthquake risk of faults that are near important structures such as nuclear power plants. Here we propose a proxy, based on the preservation of amorphous ultrafine particles, to assess fault activity within the last millennium. X-ray diffraction data and electron microscope observations of samples from an active fault demonstrated the preservation of large amounts of amorphous ultrafine particles in two slip zones that last ruptured in 1596 and 1999, respectively. A chemical kinetic evaluation of the dissolution process indicated that such particles could survive for centuries, which is consistent with the observations. Thus, preservation of amorphous ultrafine particles in a fault may be valuable for assessing the fault’s latest activity, aiding efforts to evaluate faults that may damage critical facilities in tectonically active zones.

  2. Holocene activity and paleoseismicity of the Selaha Fault, southeastern segment of the strike-slip Xianshuihe Fault Zone, Tibetan Plateau

    Yan, Bing; Lin, Aiming


    In this study we examine the Holocene activity, including slip rate and paleoseismicity, of the Selaha Fault, a branch of the left-lateral strike-slip Xianshuihe Fault Zone located along the southeastern segment of the Ganzhi-Yushu-Xianshuihe Fault System (GYXFS) of the Tibetan Plateau. Interpretation of high-resolution images and field investigations reveal that the Selaha Fault is characterized by left-lateral strike-slip faulting with an average horizontal slip-rate of 9.0 mm/year during the Holocene. Trench excavations and 14C dating results show that at least three morphogenic earthquakes occurred during the past millennium; the most recent event occurred in the past 450 years and corresponds to the 1786 M 7.75 earthquake. The penultimate seismic event (E2) occurred in the period between 560 and 820 year BP (i.e., 1166-1428 CE) and is probably associated with the 1327 M 7.5 earthquake. The antepenultimate event (E3) is inferred to have occurred in the period between 820 ± 30 and 950 ± 30 year BP. Our results confirm that the Selaha Fault, as a portion of the GYXFS, plays an important role as a tectonic boundary in releasing the strain energy accumulated during the northeastward motion of the Tibetan Plateau in response to the ongoing northward penetration of the Indian Plate into the Eurasian Plate. The strain energy is released in the form of repeated large earthquakes that are recorded by strike-slip displacements of stream channels and alluvial fans.

  3. Study on Anti-Disturbance and High-Resolution Shallow Seismic Exploration of Active Faults in Urban Regions

    Pan Jishun; Zhang Xiankang; Liu Baojin; Fan Shengming; Wang Fuyun; Duan Yonghong; Zhang Hongqiang


    The significance of detection of urban active faults and the general situation concerning detection of urban active faults in the world are briefly introduced. In a brief description of the basic principles of anti-disturbance and high-resolution shallow seismic exploration, the stress is put on the excitation of seismic sources, the performance of digital seismographs, receiving mode and conditions, geometry as well as data acquisition, processing and interpretation in the anti-disturbance and high-resolution shallow seismic exploration of urban active faults. The study indicates that a controlled seismic source with a linear or nonlinear frequency-conversion scanning function and the relevant seismographs must be used in data acquisition, as well as working methods for small group interval, small offset, multi-channel receiving, short-array and high-frequency detectors for receiving are used. Attention should be paid to the application of techniques for static correction of refraction, noise suppressing, high-precision analysis of velocity, wavelet compressing, zero-phasing of wavelet and pre-stacking migration to data processing and interpretation. Finally, some cases of anti-disturbance and high-resolution shallow seismic exploration of urban active faults are present in the paper.


    M. G. Mel’nikov


    Full Text Available The study is focused on earthquake migrations along active faults in seismic zones of Mongolia. The earthquake migrations are interpreted as a result of the influence of deformational waves. Vector velocities and other parameters of the deformational waves are studied. Based on data from largescale maps, local faults are compared, and differences and similarities of parameters of waves related to faults of different ranks are described.

  5. An adaptive confidence limit for periodic non-steady conditions fault detection

    Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong


    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.


    P.V. Srihari


    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. Detection of Sensor Faults in Small Helicopter UAVs Using Observer/Kalman Filter Identification

    Guillermo Heredia


    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.

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

    Javier Rosero García


    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.

  9. Performance of wavelet analysis and neural network for detection and diagnosis of rotating machine fault

    Kang, Shanlin; Kang, Yuzhe; Chen, Jingwei


    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.

  10. A windowing and mapping strategy for gear tooth fault detection of a planetary gearbox

    Liang, Xihui; Zuo, Ming J.; Liu, Libin


    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.

  11. H-/H∞ fault detection observer design based on generalized output for polytopic LPV system

    Zhou, Meng; Rodrigues, Mickael; Shen, Yi; Theilliol, Didier


    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.

  12. Computation of a Reference Model for Robust Fault Detection and Isolation Residual Generation

    Emmanuel Mazars


    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.

  13. Development and evaluation of virtual refrigerant mass flow sensors for fault detection and diagnostics

    Kim, Woohyun; Braun, J.


    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.

  14. Linear Quadratic Controller with Fault Detection in Compact Disk Players

    Vidal, Enrique Sanchez; Hansen, K.G.; Andersen, R.S.


    The design of the positioning controllers in Optical Disk Drives are today subjected to a trade off between an acceptable suppression of external disturbances and an acceptable immunity against surfaces defects. In this paper an algorithm is suggested to detect defects of the disk surface combined...... with an observer and a Linear Quadratic Regulator. As a result, the mentioned trade off is minimized and the playability of the tested compact disk player is considerably enhanced....

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

    Wang Haiyun; Xie Lili; Tao Xiaxin; Li Jie


    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.

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

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


    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)

  17. Novel active fault-tolerant control scheme and its application to a double inverted pendulum system


    On the basis of the gain-scheduled H∞ design strategy,a novel active fault-tolerant control scheme is proposed.Under the assumption that the effects of faults on the state-space matrices of systems can be of affine parameter dependence,a reconfigurable robust H∞ linear parameter varying controller is developed.The designed controller is a function of the fault effect factors that can be derived online by using a well-trained neural network.To demonstrate the effectiveness of the proposed method,a double inverted pendulum system,with a fault in the motor tachometer loop,is considered.

  18. Fault Detection for Non-Gaussian Stochastic Systems with Time-Varying Delay

    Tao Li


    Full Text Available Fault detection (FD for non-Gaussian stochastic systems with time-varying delay is studied. The available information for the addressed problem is the input and the measured output probability density functions (PDFs of the system. In this framework, firstly, by constructing an augmented Lyapunov functional, which involves some slack variables and a tuning parameter, a delay-dependent condition for the existence of FD observer is derived in terms of linear matrix inequality (LMI and the fault can be detected through a threshold. Secondly, in order to improve the detection sensitivity performance, the optimal algorithm is applied to minimize the threshold value. Finally, paper-making process example is given to demonstrate the applicability of the proposed approach.

  19. Improved Kernel PLS-based Fault Detection Approach for Nonlinear Chemical Processes

    王丽; 侍洪波


    In this paper, an improved nonlinear process fault detection method is proposed based on modified ker-nel partial least squares (KPLS). By integrating the statistical local approach (SLA) into the KPLS framework, two new statistics are established to monitor changes in the underlying model. The new modeling strategy can avoid the Gaussian distribution assumption of KPLS. Besides, advantage of the proposed method is that the kernel latent variables can be obtained directly through the eigen value decomposition instead of the iterative calculation, which can improve the computing speed. The new method is applied to fault detection in the simulation benchmark of the Tennessee Eastman process. The simulation results show superiority on detection sensitivity and accuracy in com-parison to KPLS monitoring.

  20. Vibration-Based Adaptive Novelty Detection Method for Monitoring Faults in a Kinematic Chain

    Jesus Adolfo Cariño-Corrales


    Full Text Available This paper presents an adaptive novelty detection methodology applied to a kinematic chain for the monitoring of faults. The proposed approach has the premise that only information of the healthy operation of the machine is initially available and fault scenarios will eventually develop. This approach aims to cover some of the challenges presented when condition monitoring is applied under a continuous learning framework. The structure of the method is divided into two recursive stages: first, an offline stage for initialization and retraining of the feature reduction and novelty detection modules and, second, an online monitoring stage to continuously assess the condition of the machine. Contrary to classical static feature reduction approaches, the proposed method reformulates the features by employing first a Laplacian Score ranking and then the Fisher Score ranking for retraining. The proposed methodology is validated experimentally by monitoring the vibration measurements of a kinematic chain driven by an induction motor. Two faults are induced in the motor to validate the method performance to detect anomalies and adapt the feature reduction and novelty detection modules to the new information. The obtained results show the advantages of employing an adaptive approach for novelty detection and feature reduction making the proposed method suitable for industrial machinery diagnosis applications.

  1. Fault detection and isolation for a full-scale railway vehicle suspension with multiple Kalman filters

    Jesussek, Mathias; Ellermann, Katrin


    Reliability and dependability in complex mechanical systems can be improved by fault detection and isolation (FDI) methods. These techniques are key elements for maintenance on demand, which could decrease service cost and time significantly. This paper addresses FDI for a railway vehicle: the mechanical model is described as a multibody system, which is excited randomly due to track irregularities. Various parameters, like masses, spring- and damper-characteristics, influence the dynamics of the vehicle. Often, the exact values of the parameters are unknown and might even change over time. Some of these changes are considered critical with respect to the operation of the system and they require immediate maintenance. The aim of this work is to detect faults in the suspension system of the vehicle. A Kalman filter is used in order to estimate the states. To detect and isolate faults the detection error is minimised with multiple Kalman filters. A full-scale train model with nonlinear wheel/rail contact serves as an example for the described techniques. Numerical results for different test cases are presented. The analysis shows that for the given system it is possible not only to detect a failure of the suspension system from the system's dynamic response, but also to distinguish clearly between different possible causes for the changes in the dynamical behaviour.

  2. The application of three-component scattering wave seismic imaging in detecting city active fault in Ji district,Tianjin city%三分量地震散射波成像在天津蓟县城市活断层探测中的应用

    张保卫; 沈鸿雁


    在精细解决近地表地质问题方面,三分量地震探测技术具有明显的优势。笔者基于点散射地震-地质模型,推导出多分量散射波时距方程,在建立多分量散射波成像原理的基础上,对天津蓟县城市活断层探测的三分量地震资料进行处理。成像结果表明,基岩面的波组特征明显、构造内幕特征较丰富,而且基岩面附近的小断层发育。通过研究,基本明确了该地区基岩与第四系土层的接触关系,探明了山前断裂情况和基岩面附近的地质结构特征。%Three-component ( 3C) seismic technology to fine solve the near-surface geological problems has obvious advantages. Based on the point scattering seismic-geological model, we deduced multi-component scattering wave time-distance equation. On the basis of establishing the multi-component scattering wave imaging principle, we processed the 3C seismic data for the detecting city active fault in Jixian of Tianjin. Imaging results show that the wave group characteristics of the bedrock surface are obvious, insider structural fea-tures are rich, and minor faults near the bedrock surface are more development. Through this study, the contact relationship between the bedrock and Quaternary soil in the region is basic cleared, and the piedmont fault conditions and the geological structure of bedrock near the surface have been clear surveyed.

  3. Model-Based Fault Detection and Isolation of a Liquid-Cooled Frequency Converter on a Wind Turbine

    Peng Li


    Full Text Available With the rapid development of wind energy technologies and growth of installed wind turbine capacity in the world, the reliability of the wind turbine becomes an important issue for wind turbine manufactures, owners, and operators. The reliability of the wind turbine can be improved by implementing advanced fault detection and isolation schemes. In this paper, an observer-based fault detection and isolation method for the cooling system in a liquid-cooled frequency converter on a wind turbine which is built up in a scalar version in the laboratory is presented. A dynamic model of the scale cooling system is derived based on energy balance equation. A fault analysis is conducted to determine the severity and occurrence rate of possible component faults and their end effects in the cooling system. A method using unknown input observer is developed in order to detect and isolate the faults based on the developed dynamical model. The designed fault detection and isolation algorithm is applied on a set of measured experiment data in which different faults are artificially introduced to the scaled cooling system. The experimental results conclude that the different faults are successfully detected and isolated.

  4. Determination of paleoseismic activity over a large time-scale: Fault scarp dating with 36Cl

    Mozafari Amiri, Nasim; Tikhomirov, Dmitry; Sümer, Ökmen; Özkaymak, Çaǧlar; Uzel, Bora; Ivy-Ochs, Susan; Vockenhuber, Christof; Sözbilir, Hasan; Akçar, Naki


    Bedrock fault scarps are the most direct evidence of past earthquakes to reconstruct seismic activity in a large time-scale using cosmogenic 36Cl dating if built in carbonates. For this method, a surface along the fault scarp with a minimum amount of erosion is required to be chosen as an ideal target point. The section of the fault selected for sampling should cover at least two meters of the fault surface from the lower part of the scarp, where intersects with colluvium wedge. Ideally, sampling should be performed on a continuous strip along the direction of the fault slip direction. First, samples of 10 cm high and 15 cm wide are marked on the fault surface. Then, they are collected using cutters, hammer and chisel in a thickness of 3 cm. The main geometrical factors of scarp dip, scarp height, top surface dip and colluvium dip are also measured. Topographic shielding in the sampling spot is important to be estimated as well. Moreover, density of the fault scarp and colluvium are calculated. The physical and chemical preparations are carried in laboratory for AMS and chemical analysis of the samples. A Matlab® code is used for modelling of seismically active periods based on increasing production rate of 36Cl following each rupture, when a buried section of a fault is exposed. Therefore, by measuring the amount of cosmogenic 36Cl versus height, the timing of major ruptures and their offsets are determined. In our study, Manastır, Mugırtepe and Rahmiye faults in Gediz graben, Priene-Sazlı, Kalafat and Yavansu faults in Büyük Menderes graben and Ören fault in Gökava half-graben have been examined in the seismically active region of Western Turkey. Our results reconstruct at least five periods of high seismic activity during the Holocene time, three of which reveal seismic ruptures beyond the historical pre-existing data.

  5. A method for detection and location of high resistance earth faults

    Haenninen, S.; Lehtonen, M. [VTT Energy, Espoo (Finland); Antila, E. [ABB Transmit Oy (Finland)


    In the first part of this presentation, the theory of earth faults in unearthed and compensated power systems is briefly presented. The main factors affecting the high resistance fault detection are outlined and common practices for earth fault protection in present systems are summarized. The algorithms of the new method for high resistance fault detection and location are then presented. These are based on the change of neutral voltage and zero sequence currents, measured at the high voltage / medium voltage substation and also at the distribution line locations. The performance of the method is analyzed, and the possible error sources discussed. Among these are, for instance, switching actions, thunder storms and heavy snow fall. The feasibility of the method is then verified by an analysis based both on simulated data, which was derived using an EMTP-ATP simulator, and by real system data recorded during field tests at three substations. For the error source analysis, some real case data recorded during natural power system events, is also used

  6. A Two-Stage Compression Method for the Fault Detection of Roller Bearings

    Huaqing Wang


    Full Text Available Data measurement of roller bearings condition monitoring is carried out based on the Shannon sampling theorem, resulting in massive amounts of redundant information, which will lead to a big-data problem increasing the difficulty of roller bearing fault diagnosis. To overcome the aforementioned shortcoming, a two-stage compressed fault detection strategy is proposed in this study. First, a sliding window is utilized to divide the original signals into several segments and a selected symptom parameter is employed to represent each segment, through which a symptom parameter wave can be obtained and the raw vibration signals are compressed to a certain level with the faulty information remaining. Second, a fault detection scheme based on the compressed sensing is applied to extract the fault features, which can compress the symptom parameter wave thoroughly with a random matrix called the measurement matrix. The experimental results validate the effectiveness of the proposed method and the comparison of the three selected symptom parameters is also presented in this paper.

  7. Fault detection of sensors in nuclear reactors using self-organizing maps

    Barbosa, Paulo Roberto; Tiago, Graziela Marchi [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Sao Paulo, SP (Brazil); Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Guarulhos, SP (Brazil); Pereira, Iraci Martinez, E-mail: martinez@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)


    In this work a Fault Detection System was developed based on the self-organizing maps methodology. This method was applied to the IEA-R1 research reactor at IPEN using a database generated by a theoretical model of the reactor. The IEA-R1 research reactor is a pool type reactor of 5 MW, cooled and moderated by light water, and uses graphite and beryllium as reflector. The theoretical model was developed using the Matlab Guide toolbox. The equations are based in the IEA-R1 mass and energy inventory balance and physical as well as operational aspects are taken into consideration. In order to test the model ability for fault detection, faults were artificially produced. As the value of the maximum calibration error for special thermocouples is +- 0.5 deg C, it had been inserted faults in the sensor signals with the purpose to produce the database considered in this work. The results show a high percentage of correct classification, encouraging the use of the technique for this type of industrial application. (author)

  8. Improving Fault Detection in Modified Code——A Study from the Telecommunication Industry

    Piotr Tomaszewski; Lars Lundberg; H(a)kan Grahn


    Many software systems are developed in a number of consecutive releases. In each release not only new codeis added but also existing code is often modified. In this study we show that the modified code can be an important sourceof faults. Faults are widely recognized as one of the major cost drivers in software projects. Therefore, we look for methodsthat improve the fault detection in the modified code. We propose and evaluate a number of prediction models that increasethe efficiency of fault detection. To build and evaluate our models we use data collected from two large telecommunicationsystems produced by Ericsson. We evaluate the performance of our models by applying them both to a different release ofthe system than the one they are built on and to a different system. The performance of our models is compared to theperformance of the theoretical best model, a simple model based on size, as well as to analyzing the code in a random order(not using any model). We find that the use of our models provides a significant improvement over not using any model atall and over using a simple model based on the class size. The gain offered by our models corresponds to 38~57% of thetheoretical maximum gain.

  9. Simultaneous State and Parameter Estimation Based Actuator Fault Detection and Diagnosis for an Unmanned Helicopter

    Wu Chong


    Full Text Available Simultaneous state and parameter estimation based actuator fault detection and diagnosis (FDD for single-rotor unmanned helicopters (UHs is investigated in this paper. A literature review of actuator FDD for UHs is given firstly. Based on actuator healthy coefficients (AHCs, which are introduced to represent actuator faults, a combined dynamic model is established with the augmented state containing both the flight state and AHCs. Then the actuator fault detection and diagnosis problem is transformed into a general nonlinear estimation one: given control inputs and the measured flight state contaminated by measurement noises, estimate both the flight state and AHCs recursively in each time-step, which is also known as the simultaneous state and parameter estimation problem. The estimated AHCs can further be used for fault tolerant control (FTC. Based on the existing widely used nonlinear estimation methods such as the unscented Kalman filter (UKF and the extended set-membership filter (ESMF, three kinds of adaptive schemes (KF-UKF, MIT-UKF and MIT-ESMF are proposed by our team to improve the actuator FDD performance. A comprehensive comparative study on these different estimation methods is given in detail to illustrate their advantages and disadvantages when applied to unmanned helicopter actuator FDD.

  10. Active Fault Diagnosis for Hybrid Systems Based on Sensitivity Analysis and EKF

    Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas


    An active fault diagnosis approach for different kinds of faults is proposed. The input of the approach is designed off-line based on sensitivity analysis such that the maximum sensitivity for each individual system parameter is obtained. Using maximum sensitivity, results in a better precision i...

  11. Active Fault Diagnosis and Assessment for Aircraft Health Management Project

    National Aeronautics and Space Administration — To address the NASA LaRC need for innovative methods and tools for the diagnosis of aircraft faults and failures, Physical Optics Corporation (POC) proposes to...

  12. Sparse maximum harmonics-to-noise-ratio deconvolution for weak fault signature detection in bearings

    Miao, Yonghao; Zhao, Ming; Lin, Jing; Xu, Xiaoqiang


    De-noising and enhancement of the weak fault signature from the noisy signal are crucial for fault diagnosis, as features are often very weak and masked by the background noise. Deconvolution methods have a significant advantage in counteracting the influence of the transmission path and enhancing the fault impulses. However, the performance of traditional deconvolution methods is greatly affected by some limitations, which restrict the application range. Therefore, this paper proposes a new deconvolution method, named sparse maximum harmonics-noise-ratio deconvolution (SMHD), that employs a novel index, the harmonics-to-noise ratio (HNR), to be the objective function for iteratively choosing the optimum filter coefficients to maximize HNR. SMHD is designed to enhance latent periodic impulse faults from heavy noise signals by calculating the HNR to estimate the period. A sparse factor is utilized to further suppress the noise and improve the signal-to-noise ratio of the filtered signal in every iteration step. In addition, the updating process of the sparse threshold value and the period guarantees the robustness of SMHD. On this basis, the new method not only overcomes the limitations associated with traditional deconvolution methods, minimum entropy deconvolution (MED) and maximum correlated kurtosis deconvolution (MCKD), but visual inspection is also better, even if the fault period is not provided in advance. Moreover, the efficiency of the proposed method is verified by simulations and bearing data from different test rigs. The results show that the proposed method is effective in the detection of various bearing faults compared with the original MED and MCKD.

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

    Jiang, Hongkai; Xia, Yong; Wang, Xiaodong


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

  14. Robust fault detection for discrete-time Markovian jump systems with mode-dependent time-delays

    Hongru WANG; Changhong WANG; Shaoshuai MOU; Huijun GAO


    This paper investigates a fault detection problem for a class of discrete-time Markovian jump systems with norm-bounded uncertainties and mode-dependent time-delays. Attention is focused on constructing the residual generator based on the filter of which its parameters matrices are dependent on the system mode, that is, the fault detection filter is a Markovian jump system as well. The design of fault detection filter is reduced to H-infinity filtering problem by using H-infinity control theory, which can guarantee the difference between the residual and the fault (or, more generally weighted fault) as small as possible in the context of enhancing the robustness of residual to modeling errors, control inputs and unknown inputs. Sufficient condition for the existence of the above filters is established by means of linear matrix inequalities, which can be readily solved by using standard numerical software. A numerical example is given to illustrate the feasibility of the proposed method.

  15. Model-Based Fault Detection and Isolation of a Liquid-Cooled Frequency Converter on a Wind Turbine

    Li, Peng; Odgaard, Peter Fogh; Stoustrup, Jakob


    system is derived based on energy balance equation. A fault analysis is conducted to determine the severity and occurrence rate of possible component faults and their end effects in the cooling system. A method using unknown input observer is developed in order to detect and isolate the faults based......With the rapid development of wind energy technologies and growth of installed wind turbine capacity in the world, the reliability of the wind turbine becomes an important issue for wind turbine manufactures, owners, and operators. The reliability of the wind turbine can be improved by implementing...... advanced fault detection and isolation schemes. In this paper, an observer-based fault detection and isolation method for the cooling system in a liquid-cooled frequency converter on a wind turbine which is built up in a scalar version in the laboratory is presented. A dynamic model of the scale cooling...

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

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


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

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

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


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

  18. A study on real-time fault monitoring detection method of bearing using the infrared thermography

    Kim, Won Tae [School of Mechanical and Automotive Engineering, Kongju National University, Kongju (Korea, Republic of); Kim, Ho Jong; Hong, Dong Pyo [School of Mechanical System Engineering, Chonbuk Nationa University, Jeonju (Korea, Republic of)


    Since real-time monitoring system like a fault early detection has been very important, infrared thermography technique as a new diagnosis method was proposed. This study is focused on the damage detection and temperature characteristic analysis of ball bearing using the non-destructive infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with the frequency data of the existing. As results, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally it was confirmed that the infrared technique was useful for real-time detection of the bearing damages.

  19. Co-seismic Faults and Geological Hazards and Incidence of Active Fault of Wenchuan Ms 8.0 Earthquake, Sichuan, China

    MA Yinsheng; LONG Changxing; TAN Chengxuan; WANG Tao; GONG Mingquan; LIAO Chunting; WU Manlu; SHI Wei; DU Jianjun; PAN Feng


    There are two co-seismic faults which developed when the Wenchuan earthquake happened. One occurred along the active fault zone in the central Longmen Mts. and the other in the front of Longmen Mts. The length of which is more than 270 km and about 80 km respectively. The co-seismic fault shows a reverse flexure belt with strike of N45°-60°E in the ground, which caused uplift at its northwest side and subsidence at the southeast. The fault face dips to the northwest with a dip angle ranging from 50° to 60°. The vertical offset of the co-seismic fault ranges 2.5-3.0 m along the Yingxiu-Beichuan co-seismic fault, and 1.5-1.1 m along the Doujiangyan-Hanwang fault. Movement of the co-seismic fault presents obvious segmented features along the active fault zone in central Longmen Mts. For instance, in the section from Yingxiu to Leigu town, thrust without evident slip occurred; while from Beichuan to Qingchuan, thrust and dextral strike-slip take place. Main movement along the front Longmen Mts. shows thrust without slip and segmented features. The area of earthquake intensity more than IX degree and the distribution of secondary geological hazards occurred along the hanging wall of co-seismic faults, and were consistent with the area of aftershock, and its width is less than 40km from co-seismic faults in the hanging wail. The secondary geological hazards, collapses, landslides, debris flows et al., concentrated in the hanging wall of co-seismic fault within 0--20 km from co-seismic fault.

  20. A Framework and Classification for Fault Detection Approaches in Wireless Sensor Networks with an Energy Efficiency Perspective

    Zhang, Yue; Dragoni, Nicola; Wang, Jiangtao


    Wireless Sensor Networks (WSNs) are more and more considered a key enabling technology for the realisation of the Internet of Things (IoT) vision. With the long term goal of designing fault-tolerant IoT systems, this paper proposes a fault detection framework for WSNs with the perspective of energy...

  1. Detection of intermittent resistive faults in electronic systems based on the mixed-signal boundary-scan standard

    Kerkhoff, Hans G.; Ebrahimi, Hassan


    In avionics, like glide computers, the problem of No Faults Found (NFF) is a very serious and extremely costly affair. The rare occurrences and short bursts of these faults are the most difficult ones to detect and diagnose in the testing arena. Several techniques are now being developed in ICs by u

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

    Reichardt, B W


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

  3. A microprocessor-based digital feeder monitor with high-impedance fault detection

    Patterson, R.; Tyska, W. [GE Protection and Control, Malvern, PA (United States); Russell, B.D. [Texas A& M Univ., College Station, TX (United States)] [and others


    The high impedance fault detection technology developed at Texas A&M University after more than a decade of research, funded in large part by the Electric Power Research Institute, has been incorporated into a comprehensive monitoring device for overhead distribution feeders. This digital feeder monitor (DFM) uses a high waveform sampling rate for the ac current and voltage inputs in conjunction with a high-performance reduced instruction set (RISC) microprocessor to obtain the frequency response required for arcing fault detection and power quality measurements. Expert system techniques are employed to assure security while maintaining dependability. The DFM is intended to be applied at a distribution substation to monitor one feeder. The DFM is packaged in a non-drawout case which fits the panel cutout for a GE IAC overcurrent relay to facilitate retrofits at the majority of sites were electromechanical overcurrent relays already exist.

  4. Fault Detection for Wireless Networked Control Systems with Stochastic Switching Topology and Time Delay

    Pengfei Guo


    Full Text Available This paper deals with the fault detection problem for a class of discrete-time wireless networked control systems described by switching topology with uncertainties and disturbances. System states of each individual node are affected not only by its own measurements, but also by other nodes’ measurements according to a certain network topology. As the topology of system can be switched in a stochastic way, we aim to design H∞ fault detection observers for nodes in the dynamic time-delay systems. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are acquired to guarantee the existence of the filters satisfying the H∞ performance constraint, and observer gains are derived by solving linear matrix inequalities. Finally, an illustrated example is provided to verify the effectiveness of the theoretical results.

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

    Chin-Tsung Hsieh


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

  6. Spatial and temporal variation of palaeoseismic activity at an intraplate, historically quiescent structure: The Concud fault (Iberian Chain, Spain)

    Lafuente, Paloma; Arlegui, Luis E.; Liesa, Carlos L.; Pueyo, Óscar; Simón, José L.


    Several faults in the Teruel and Jiloca grabens (Iberian Chain, NE Spain), particularly the targeted Concud fault, show evidences of recent, continuous activity, despite their scarce instrumental and historic seismic record. Three trenches are studied in two locations (central and southeastern sectors of the Concud fault, respectively). After comparing with previous works, we reconstruct a palaeoseismic succession with nine events distributed along a maximum time lapse bracketed between 81.6 and 14.0 ka. This succession involves an average recurrence interval of 7.4 ± 2.8 ka, with individual interseismic periods between 4 and 11 ka. The calculated coseismic displacements range from 0.6 to 2.7 m, with an average value of 1.9 m that results in a slip rate of 0.26 mm/a. Due to the incomplete sedimentary record for Holocene times, we cannot affirm that the youngest event detected was actually the last one. We conjecture that some other events may have occurred during the period between 15.0 and 3.4 ka. Temporal and spatial variations have been detected in palaeoseismic activity, specifically in the distribution of coseismic displacements. First, a non-steady slip rate is evidenced during Plio-Pleistocene times: a long-term tendency towards increasing slip rate is modulated in detail by the occurrence of minor cycles, as the sequence of increasing/decreasing activity recorded within the studied time window suggests. Secondly, an asymmetric distribution of coseismic slip along the fault trace is observed, paralleling the distribution of total fault throw, which shows an absolute maximum close to the southeastern tip. A combination of factors is proposed to explain this: branching of the main fault; dominant, remote-stress-driven slip towards N 220° E on the NW-SE fault segment; guided movement on the passive, NNW-SSE segment giving rise to an oblique roll-over monocline; and decoupling of the hanging-wall block owing to the transverse Los Mansuetos-Valdecebro fault

  7. Geomorphic features of active faults around the Kathmandu Valley, Nepal, and no evidence of surface rupture associated with the 2015 Gorkha earthquake along the faults

    Kumahara, Yasuhiro; Chamlagain, Deepak; Upreti, Bishal Nath


    The M7.8 April 25, 2015, Gorkha earthquake in Nepal was produced by a slip on the low-angle Main Himalayan Thrust, a décollement below the Himalaya that emerges at the surface in the south as the Himalayan Frontal Thrust (HFT). The analysis of the SAR interferograms led to the interpretations that the event was a blind thrust and did not produce surface ruptures associated with the seismogenic fault. We conducted a quick field survey along four active faults near the epicentral area around the Kathmandu Valley (the Jhiku Khola fault, Chitlang fault, Kulekhani fault, Malagiri fault and Kolphu Khola fault) from July 18-22, 2015. Those faults are located in the Lesser Himalaya on the hanging side of the HFT. Based on our field survey carried out in the area where most typical tectonic landforms are developed, we confirmed with local inhabitants the lack of any new surface ruptures along these faults. Our observations along the Jhiku Khola fault showed that the fault had some definite activities during the Holocene times. Though in the past it was recognized as a low-activity thrust fault, our present survey has revealed that it has been active with a predominantly right-lateral strike-slip with thrust component. A stream dissecting a talus surface shows approximately 7-m right-lateral offset, and a charcoal sample collected from the upper part of the talus deposit yielded an age of 870 ± 30 y.B.P, implying that the talus surface formed close to 870 y.B.P. Accordingly, a single or multiple events of the fault must have occurred during the last 900 years, and the slip rate we estimate roughly is around 8 mm/year. The fault may play a role to recent right-lateral strike-slip tectonic zone across the Himalayan range. Since none of the above faults showed any relationship corresponding to the April 25 Gorkha earthquake, it is possibility that a potential risk of occurrence of large earthquakes does exist close to the Kathmandu Valley due to movements of these active

  8. Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train


    A fault detection approach based on nonlinear robust observer is designed for the networked suspension control system of Maglev train with random induced time delay. First, considering random bounded time-delay and external disturbance, the nonlinear model of the networked suspension control system is established. Then, a nonlinear robust observer is designed using the input of the suspension gap. And the estimate error is proved to be bounded with arbitrary precision by adopting an appropria...

  9. Fault detection in digital and analog circuits using an i(DD) temporal analysis technique

    Beasley, J.; Magallanes, D.; Vridhagiri, A.; Ramamurthy, Hema; Deyong, Mark


    An i(sub DD) temporal analysis technique which is used to detect defects (faults) and fabrication variations in both digital and analog IC's by pulsing the power supply rails and analyzing the temporal data obtained from the resulting transient rail currents is presented. A simple bias voltage is required for all the inputs, to excite the defects. Data from hardware tests supporting this technique are presented.

  10. Fault detection thermal storage system by expert system using fuzzy abduction

    Yamada, Koichi [Yamatake-Honeywell Co., Ltd, Yokohama (Japan). Advanced Technology Center; Kamimura, Kazuyuki [Yamatake-Honeywell Co., Ltd., Tokyo (Japan). Building Systems Div.


    Fuzzy abduction is a procedure for deriving fuzzy sets of hypotheses which explain a given fuzzy set of events using a set of rules with a truth value. The derived fuzzy sets of hypotheses are called fuzzy explanations. This presentation starts with discussion about diagnosis using conventional expert systems and that using fuzzy relational equations. Then, it proposes a new approach using a fuzzy abduction, and applies the technique to fault detection of a thermal storage system. (orig.)

  11. Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System.

    Wang, Yu-Long; Shi, Peng; Lim, Cheng-Chew; Liu, Yuan


    This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered H ∞ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.




    Full Text Available Vulnerable and critical mechanical systems are bearings and drive belts. Signal analysis of vibration highlights the changes in root mean square, the frequency spectrum (frequencies and amplitudes in the time- frequency (Short Time Fourier Transform and Wavelet Transform, are the most used method for faults diagnosis and location of rotating machinery. This article presents the results of an experimental study applied on a di agnostic platform of rotating machinery through three Wavelet methods: (Discrete Wavelet Transform -DWT, Continuous Wavelet Transform -CWT, Wavelet Packet Transform -WPT with different mother wavelet. Wavelet Transform is used to decompose the original sig nal into sub -frequency band signals in order to obtain multiple data series at different resolutions and to identify faults appearing in the complex rotation systems. This paper investigates the use of different mother wavelet functions for drive belts and bearing fault diagnosis. The results demonstrate the possibility of using different mother wavelets in rotary systems diagnosis detecting and locating in this way the faults in bearings and drive belts.

  13. 3D Seismic Flexure Analysis for Subsurface Fault Detection and Fracture Characterization

    Di, Haibin; Gao, Dengliang


    Seismic flexure is a new geometric attribute with the potential of delineating subtle faults and fractures from three-dimensional (3D) seismic surveys, especially those overlooked by the popular discontinuity and curvature attributes. Although the concept of flexure and its related algorithms have been published in the literature, the attribute has not been sufficiently applied to subsurface fault detection and fracture characterization. This paper provides a comprehensive study of the flexure attribute, including its definition, computation, as well as geologic implications for evaluating the fundamental fracture properties that are essential to fracture characterization and network modeling in the subsurface, through applications to the fractured reservoir at Teapot Dome, Wyoming (USA). Specifically, flexure measures the third-order variation of the geometry of a seismic reflector and is dependent on the measuring direction in 3D space; among all possible directions, flexure is considered most useful when extracted perpendicular to the orientation of dominant deformation; and flexure offers new insights into qualitative/quantitative fracture characterization, with its magnitude indicating the intensity of faulting and fracturing, its azimuth defining the orientation of most-likely fracture trends, and its sign differentiating the sense of displacement of faults and fractures.

  14. Automatic characteristic frequency association and all-sideband demodulation for the detection of a bearing fault

    Firla, Marcin; Li, Zhong-Yang; Martin, Nadine; Pachaud, Christian; Barszcz, Tomasz


    This paper proposes advanced signal-processing techniques to improve condition monitoring of operating machines. The proposed methods use the results of a blind spectrum interpretation that includes harmonic and sideband series detection. The first contribution of this study is an algorithm for automatic association of harmonic and sideband series to characteristic fault frequencies according to a kinematic configuration. The approach proposed has the advantage of taking into account a possible slip of the rolling-element bearings. In the second part, we propose a full-band demodulation process from all sidebands that are relevant to the spectral estimation. To do so, a multi-rate filtering process in an iterative schema provides satisfying precision and stability over the targeted demodulation band, even for unsymmetrical and extremely narrow bands. After synchronous averaging, the filtered signal is demodulated for calculation of the amplitude and frequency modulation functions, and then any features that indicate faults. Finally, the proposed algorithms are validated on vibration signals measured on a test rig that was designed as part of the European Innovation Project 'KAStrion'. This rig simulates a wind turbine drive train at a smaller scale. The data show the robustness of the method for localizing and extracting a fault on the main bearing. The evolution of the proposed features is a good indicator of the fault severity.

  15. Application of Calcite Veins to Study of Newly-activated Faulting

    刘行松; 史兰斌; 唐汉军; 林传勇; 何永年


    The study of period and chronology of fault activity in major worksites in an area with exposed basement rocks is quite difficult. The authors have applied the combinative techniques of field investigation, microscopic observation and isotopic dating to studying the calcite veins filled in the fault zones in several major engineering regions and got successful results. The following conclusions are reached: (i) The last period of strong activity of fault F8 in the Tianshengqiao Hydropower Station, Nanpan River is 200 ka B. P. , and there has been, no obvious activity since 150 ka. (ii) The last period of strong activity for 5 faults in Shixiali Reservoir, Yangyuan County, Hebei Province is 200-300 ka B. P. , and there has been no obvious activity since 200 ka. The research results provide a sound basis of engineering geology for project designers.

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

    Lue Chen


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

  17. Use of Fourier Transformation for Detection of Faults in Underground Power Cables

    Abhishek Pandey; Nicolas H. Younan


    An analysis of underground power cables is performed using Fourier analysis with the objective of detecting fault and average life of the cables. Three types of cables are used in this experiment: a normal cable, a shorted cable, and a cable with holes. The impedance in each case is computed and Fourier transformation is applied so that the re- suiting impedance magnitude and impedance phase can be examined in the frequency domain. Various windowing tech- niques are applied to the experimental data to eliminate any interference. Fourier analysis is then applied to the imped- ance data calculated from both the sending end voltage and differential voltage. This analysis reveals differences in the frequency response of the three different types of a cable and can eventually be used as a measure for fault detection. Preliminary results reveal the differences in the frequency response. Accordingly, Fourier type methods can be effectively used as low cost and viable solutions to identify and detect faults in underground cables.

  18. A Frequency-Weighted Energy Operator and complementary ensemble empirical mode decomposition for bearing fault detection

    Imaouchen, Yacine; Kedadouche, Mourad; Alkama, Rezak; Thomas, Marc


    Signal processing techniques for non-stationary and noisy signals have recently attracted considerable attentions. Among them, the empirical mode decomposition (EMD) which is an adaptive and efficient method for decomposing signals from high to low frequencies into intrinsic mode functions (IMFs). Ensemble EMD (EEMD) is proposed to overcome the mode mixing problem of the EMD. In the present paper, the Complementary EEMD (CEEMD) is used for bearing fault detection. As a noise-improved method, the CEEMD not only overcomes the mode mixing, but also eliminates the residual of added white noise persisting into the IMFs and enhance the calculation efficiency of the EEMD method. Afterward, a selection method is developed to choose relevant IMFs containing information about defects. Subsequently, a signal is reconstructed from the sum of relevant IMFs and a Frequency-Weighted Energy Operator is tailored to extract both the amplitude and frequency modulations from the selected IMFs. This operator outperforms the conventional energy operator and the enveloping methods, especially in the presence of strong noise and multiple vibration interferences. Furthermore, simulation and experimental results showed that the proposed method improves performances for detecting the bearing faults. The method has also high computational efficiency and is able to detect the fault at an early stage of degradation.

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

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


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

  20. The offshore Yangsan fault activity in the Quaternary, SE Korea: Analysis of high-resolution seismic profiles

    Kim, Han-Joon; Moon, Seonghoon; Jou, Hyeong-Tae; Lee, Gwang Hoon; Yoo, Dong Geun; Lee, Sang Hoon; Kim, Kwang Hee


    The NNE-trending dextral Yangsan fault is a > 190-km-long structure in the Korean Peninsula traced to the southeastern coast. The scarcity of Quaternary deposits onland precludes any detailed investigation of the Quaternary activity and structure of the Yangsan fault using seismic reflection profiling. We acquired offshore high-resolution seismic profiles to investigate the extension of the Yangsan fault and constrain its Quaternary activity using stratigraphic markers. The seismic profiles reveal a NNE-trending fault system consisting of a main fault and an array of subsidiary faults that displaced Quaternary sequences. Stratigraphic analysis of seismic profiles indicates that the offshore faults were activated repeatedly in the Quaternary. The up-to-the-east sense of throw on the main fault and plan-view pattern of the fault system are explained by dextral strike-slip faulting. The main fault, when projected toward the Korean Peninsula along its strike, aligns well with the Yangsan fault. We suggest that the offshore fault system is a continuation of the Yangsan fault and has spatial correlation with weak but ongoing seismicity.

  1. Robust fault detection and isolation technique for single-input/single-output closed-loop control systems that exhibit actuator and sensor faults

    Izadi-Zamanabadi, Roozbeh; Alavi, S. M. Mahdi; Hayes, M. J.


    An integrated quantitative feedback design and frequency-based fault detection and isolation (FDI) approach is presented for single-input/single-output systems. A novel design methodology, based on shaping the system frequency response, is proposed to generate an appropriate residual signal that ...

  2. Fault Detection and Location by Static Switches in Microgrids Using Wavelet Transform and Adaptive Network-Based Fuzzy Inference System

    Ying-Yi Hong


    Full Text Available Microgrids are a highly efficient means of embedding distributed generation sources in a power system. However, if a fault occurs inside or outside the microgrid, the microgrid should be immediately disconnected from the main grid using a static switch installed at the secondary side of the main transformer near the point of common coupling (PCC. The static switch should have a reliable module implemented in a chip to detect/locate the fault and activate the breaker to open the circuit immediately. This paper proposes a novel approach to design this module in a static switch using the discrete wavelet transform (DWT and adaptive network-based fuzzy inference system (ANFIS. The wavelet coefficient of the fault voltage and the inference results of ANFIS with the wavelet energy of the fault current at the secondary side of the main transformer determine the control action (open or close of a static switch. The ANFIS identifies the faulty zones inside or outside the microgrid. The proposed method is applied to the first outdoor microgrid test bed in Taiwan, with a generation capacity of 360.5 kW. This microgrid test bed is studied using the real-time simulator eMegaSim developed by Opal-RT Technology Inc. (Montreal, QC, Canada. The proposed method based on DWT and ANFIS is implemented in a field programmable gate array (FPGA by using the Xilinx System Generator. Simulation results reveal that the proposed method is efficient and applicable in the real-time control environment of a power system.

  3. Active Fault Tolerant Control of Livestock Stable Ventilation System

    Gholami, Mehdi


    Modern stables and greenhouses are equipped with different components for providing a comfortable climate for animals and plant. A component malfunction may result in loss of production. Therefore, it is desirable to design a control system, which is stable, and is able to provide an acceptable......). In the FTC part of the thesis, first a passive fault tolerant controller (PFTC) based on state feed-back is proposed for discretetime PWA systems. only actuator faults are considered. By dissipativity theory and H1 analysis, the problem is cast as a set of linear matrix inequalities (LMIs). In the next...

  4. A New Fault Detection Method Using End-to-End Data and Sequential Testing for Computer Networks

    Mohammad Sadeq Garshasbi


    Full Text Available Fault localization, a central part of network fault management, is a process of deducing the exact source of a failure from a set of observed failure indications. in the network, end systems and hosts communicate through routers and links connecting them. When a link or a router faces with a fault, the information sent through these components will be damaged. Hence, faulty components in a network need to be detected and repaired to sustain the health of the network. In this paper we introduce an end to end method that detect and repair the faulty components in the network. The proposed method is a heuristic algorithm that uses the embedded information retrieved from disseminated data over the network to detect and repair faulty components. Simulation results show that our heuristic scheme only requires testing a very small set of network components to detect and repair all faults in the network.

  5. Application of the Continuous-Discrete Extended Kalman Filter for Fault Detection in Continuous Glucose Monitors for Type 1 Diabetes

    Mahmoudi, Zeinab; Boiroux, Dimitri; Hagdrup, Morten


    The purpose of this study is the online detection of faults and anomalies of a continuous glucose monitor (CGM). We simulated a type 1 diabetes patient using the Medtronic virtual patient model. The model is a system of stochastic differential equations and includes insulin pharmacokinetics......, insulin-glucose interaction, and carbohydrate absorption. We simulated and detected two types of CGM faults, i.e., spike and drift. A fault was defined as a CGM value in any of the zones C, D, and E of the Clarke error grid analysis classification. Spike was modelled by a binomial distribution, and drift...... was modelled by a Gaussian random walk. We used a continuous-discrete extended Kalman filter for the fault detection, based on the statistical tests of the filter innovation and the 90-min prediction residuals of the sensor measurements. The spike detection had a sensitivity of 93% and a specificity of 100...

  6. Health Monitoring of Offshore Wind Turbines Online Fault Detection and Identification Module Test Case: Pitch Offset

    Perisic, Nevena; Pedersen, Bo Juul; Kirkegaard, Poul Henning

    LACobserver is a model based health monitoring (HM) system for wind turbines (WTGs) which provides an intuitive engineering link between load and strength parameters. The present work demonstrates a newly developed LACobserver Fault Detection and Identification (FDI) module for online detection...... of pitch offset and corresponding root causes. Blade-to-blade pitch offset slowly degrade the WTG performance and results in lower WTG annual energy production and higher structural loads. Thus, a FDI strategy will increase wind turbine efficiency, performance and operational lifetime....

  7. Fault detection method for railway wheel flat using an adaptive multiscale morphological filter

    Li, Yifan; Zuo, Ming J.; Lin, Jianhui; Liu, Jianxin


    This study explores the capacity of the morphology analysis for railway wheel flat fault detection. A dynamic model of vehicle systems with 56 degrees of freedom was set up along with a wheel flat model to calculate the dynamic responses of axle box. The vehicle axle box vibration signal is complicated because it not only contains the information of wheel defect, but also includes track condition information. Thus, how to extract the influential features of wheels from strong background noise effectively is a typical key issue for railway wheel fault detection. In this paper, an algorithm for adaptive multiscale morphological filtering (AMMF) was proposed, and its effect was evaluated by a simulated signal. And then this algorithm was employed to study the axle box vibration caused by wheel flats, as well as the influence of track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method was verified by bench testing. Research results demonstrate that the AMMF extracts the influential characteristic of axle box vibration signals effectively and can diagnose wheel flat faults in real time.

  8. A SVM framework for fault detection of the braking system in a high speed train

    Liu, Jie; Li, Yan-Fu; Zio, Enrico


    In April 2015, the number of operating High Speed Trains (HSTs) in the world has reached 3603. An efficient, effective and very reliable braking system is evidently very critical for trains running at a speed around 300 km/h. Failure of a highly reliable braking system is a rare event and, consequently, informative recorded data on fault conditions are scarce. This renders the fault detection problem a classification problem with highly unbalanced data. In this paper, a Support Vector Machine (SVM) framework, including feature selection, feature vector selection, model construction and decision boundary optimization, is proposed for tackling this problem. Feature vector selection can largely reduce the data size and, thus, the computational burden. The constructed model is a modified version of the least square SVM, in which a higher cost is assigned to the error of classification of faulty conditions than the error of classification of normal conditions. The proposed framework is successfully validated on a number of public unbalanced datasets. Then, it is applied for the fault detection of braking systems in HST: in comparison with several SVM approaches for unbalanced datasets, the proposed framework gives better results.

  9. Hybrid Intelligent System to Perform Fault Detection on BIS Sensor During Surgeries

    Casteleiro-Roca, José-Luis; Calvo-Rolle, José Luis; Méndez Pérez, Juan Albino; Roqueñí Gutiérrez, Nieves; de Cos Juez, Francisco Javier


    This paper presents a new fault detection system in hypnotic sensors used for general anesthesia during surgery. Drug infusion during surgery is based on information received from patient monitoring devices; accordingly, faults in sensor devices can put patient safety at risk. Our research offers a solution to cope with these undesirable scenarios. We focus on the anesthesia process using intravenous propofol as the hypnotic drug and employing a Bispectral Index (BISTM) monitor to estimate the patient’s unconsciousness level. The method developed identifies BIS episodes affected by disturbances during surgery with null clinical value. Thus, the clinician—or the automatic controller—will not take those measures into account to calculate the drug dose. Our method compares the measured BIS signal with expected behavior predicted by the propofol dose provider and the electromyogram (EMG) signal. For the prediction of the BIS signal, a model based on a hybrid intelligent system architecture has been created. The model uses clustering combined with regression techniques. To validate its accuracy, a dataset taken during surgeries with general anesthesia was used. The proposed fault detection method for BIS sensor measures has also been verified using data from real cases. The obtained results prove the method’s effectiveness. PMID:28106793

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

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


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

  11. Fault diagnosis of active magnetic bearings based on Gaussian GLRT detector

    Nagel, Leon; Galeazzi, Roberto; Voigt, Andreas Jauernik


    generalized likelihood ratio test is proposed for detecting faults striking the electromagnet. The detector is capable of detecting and isolating the occurrence of faults in e.g. the windings of bearing by tracking changes in the mean value of a Gaussian distribution. The statistical distribution...... of the residuals in non faulty condition is characterized by experimental data of a full-scale bearing-rotor system. Verification of the detection performance is done through simulated data of a nonlinear model of the magnetic bearing calibrated against the real system....

  12. Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train

    Yun Li


    Full Text Available A fault detection approach based on nonlinear robust observer is designed for the networked suspension control system of Maglev train with random induced time delay. First, considering random bounded time-delay and external disturbance, the nonlinear model of the networked suspension control system is established. Then, a nonlinear robust observer is designed using the input of the suspension gap. And the estimate error is proved to be bounded with arbitrary precision by adopting an appropriate parameter. When sensor faults happen, the residual between the real states and the observer outputs indicates which kind of sensor failures occurs. Finally, simulation results using the actual parameters of CMS-04 maglev train indicate that the proposed method is effective for maglev train.

  13. Direct detection of near-surface faults by migration of back-scattered surface waves

    Yu, Han


    We show that diffraction stack migration can be used to estimate the distribution of near-surface faults. The assumption is that near-surface faults generate detectable back-scattered surface waves from impinging surface waves. The processing steps are to isolate the back-scattered surface waves, and then migrate them by diffraction migration using the surface wave velocity as the migration velocity. Instead of summing events along trial quasi-hyperbolas, surface wave migration sums events along trial quasi-linear trajectories that correspond to the moveout of back-scattered surface waves. A deconvolution filter derived from the data can be used to collapse a dispersive arrival into a non-dispersive event. Results with synthetic data and field records validate the feasibility of this method. Applying this method to USArray data or passively recorded exploration data might open new opportunities in mapping tectonic features over the extent of the array.

  14. Simultaneous Fault Detection and Sensor Selection for Condition Monitoring of Wind Turbines

    Wenna Zhang


    Full Text Available Data collected from the supervisory control and data acquisition (SCADA system are used widely in wind farms to obtain operation and performance information about wind turbines. The paper presents a three-way model by means of parallel factor analysis (PARAFAC for wind turbine fault detection and sensor selection, and evaluates the method with SCADA data obtained from an operational farm. The main characteristic of this new approach is that it can be used to simultaneously explore measurement sample profiles and sensors profiles to avoid discarding potentially relevant information for feature extraction. With K-means clustering method, the measurement data indicating normal, fault and alarm conditions of the wind turbines can be identified, and the sensor array can be optimised for effective condition monitoring.

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

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


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

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

    Imaouchen Yacine


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

  17. Design of robust fault detection filter for nonlinear time-delay systems

    BAI Lei-shi; HE Li-ming; TIAN Zuo-hua; SHI Song-jiao


    In this paper, the robust fault detection filter (RFDF) design problems are studied for nonlinear time-delay systems with unknown inputs. First, a reference residual model is introduced to formulate the RFDF design problem as an H∞model-matching problem. Then appropriate input/output selection matrices are introduced to extend a performance index to the time-delay systems in time domain. The reference residual model designed according to the performance index is an optimal residual generator, which takes into account the robustness against disturbances and sensitivity to faults simultaneously. Applying robust H∞ optimization control technique, the existence conditions of the RFDF for nonlinear time-delay systems with unknown inputs are presented in terms of linear matrix inequality (LMI) formulation, independently of time delay. An illustrative design example is used to demonstrate the validity and applicability of the proposed approach.

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

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


    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.

  19. Gear Fault Detection Effectiveness as Applied to Tooth Surface Pitting Fatigue Damage

    Lewicki, David G.; Dempsey, Paula J.; Heath, Gregory F.; Shanthakumaran, Perumal


    A study was performed to evaluate fault detection effectiveness as applied to gear-tooth-pitting-fatigue damage. Vibration and oil-debris monitoring (ODM) data were gathered from 24 sets of spur pinion and face gears run during a previous endurance evaluation study. Three common condition indicators (RMS, FM4, and NA4 [Ed. 's note: See Appendix A-Definitions D were deduced from the time-averaged vibration data and used with the ODM to evaluate their performance for gear fault detection. The NA4 parameter showed to be a very good condition indicator for the detection of gear tooth surface pitting failures. The FM4 and RMS parameters perfomu:d average to below average in detection of gear tooth surface pitting failures. The ODM sensor was successful in detecting a significant 8lDOunt of debris from all the gear tooth pitting fatigue failures. Excluding outliers, the average cumulative mass at the end of a test was 40 mg.

  20. Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set

    Jinna Li


    Full Text Available A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. Just-in-time (JIT detection method and k-nearest neighbor (KNN rule-based statistical process control (SPC approach are integrated to construct a flexible and adaptive detection scheme for the control process with nonlinear, dynamic, and multimodal cases. Mahalanobis distance, representing the correlation among samples, is used to simplify and update the raw data set, which is the first merit in this paper. Based on it, the control limit is computed in terms of both KNN rule and SPC method, such that we can identify whether the current data is normal or not by online approach. Noted that the control limit obtained changes with updating database such that an adaptive fault detection technique that can effectively eliminate the impact of data drift and shift on the performance of detection process is obtained, which is the second merit in this paper. The efficiency of the developed method is demonstrated by the numerical examples and an industrial case.

  1. Fault detection, isolation, and diagnosis of status self-validating gas sensor arrays.

    Chen, Yin-Sheng; Xu, Yong-Hui; Yang, Jing-Li; Shi, Zhen; Jiang, Shou-da; Wang, Qi


    The traditional gas sensor array has been viewed as a simple apparatus for information acquisition in chemosensory systems. Gas sensor arrays frequently undergo impairments in the form of sensor failures that cause significant deterioration of the performance of previously trained pattern recognition models. Reliability monitoring of gas sensor arrays is a challenging and critical issue in the chemosensory system. Because of its importance, we design and implement a status self-validating gas sensor array prototype to enhance the reliability of its measurements. A novel fault detection, isolation, and diagnosis (FDID) strategy is presented in this paper. The principal component analysis-based multivariate statistical process monitoring model can effectively perform fault detection by using the squared prediction error statistic and can locate the faulty sensor in the gas sensor array by using the variables contribution plot. The signal features of gas sensor arrays for different fault modes are extracted by using ensemble empirical mode decomposition (EEMD) coupled with sample entropy (SampEn). The EEMD is applied to adaptively decompose the original gas sensor signals into a finite number of intrinsic mode functions (IMFs) and a residual. The SampEn values of each IMF and the residual are calculated to reveal the multi-scale intrinsic characteristics of the faulty sensor signals. Sparse representation-based classification is introduced to identify the sensor fault type for the purpose of diagnosing deterioration in the gas sensor array. The performance of the proposed strategy is compared with other different diagnostic approaches, and it is fully evaluated in a real status self-validating gas sensor array experimental system. The experimental results demonstrate that the proposed strategy provides an excellent solution to the FDID of status self-validating gas sensor arrays.

  2. Holocene activities of the Taigu fault zone,Shanxi Province, and their relations with the 1303 Hongdong M=8 earthquake

    谢新生; 江娃利; 王焕贞; 冯西英


    The Taigu fault zone is one of the major 12 active boundary faults of the Shanxi fault-depression system, locatedon the eastern boundary of the Jinzhong basin. As the latest investigation indicated, the fault zone had dislocatedgully terrace of the f1rst order, forming fault-scarp in front of the loess mesa. It has been discovered in many placesin ground surface and trenches that Holocene deposits were dislocated. The latest activity was the 1303 Hongdongearthquake M=8, the fault appeared as right-lateral strike-slip with normal faulting. During that earthquake, theTaigu fault together with the Mianshan western-side fault on the Lingshi upheaval and the Huoshan pediment faulton the eastern boundary of the Linfen basin was being active, forming a surface rupture belt of 160 km in length.Moreover, the Taigu fault were active in the mid-stage of Holocene and near 7 700 aB.P. From these we learnt that,in Shanxi fault-depression system, the run-through activity of two boundary faults of depression-basins mightgenerate great earthquake with M=8.

  3. Fault-tolerant Supervisory Control

    Izadi-Zamanabadi, Roozbeh

    The main purpose of this work has been to achieve active fault-tolerance in control systems, defined as a methodology where fault detection and isolation techniques are combined with supervisory control to achieve autonomous accommodation of faults before they develop into failures. The aim...... control algorithms. The drawback is, however, that these control systems have become more vulnerable to even simple faults in instrumentation. On the other hand, due to cost-optimality requirements, an extensive use of hardware redundancy has been prohibited. Nevertheless, the dependency and availability...... could be increased through enhancing control systems' ability to on-line perform fault detection and reconfiguration when a fault occurs and before a safety system shuts-down the entire process. The main contributions of this research effort are development and experimentation with methodologies...

  4. Implementation and testing of a fault detection software tool for improving control system performance in a large commercial building

    Salsbury, T.I.; Diamond, R.C.


    This paper describes a model-based, feedforward control scheme that can detect faults in the controlled process and improve control performance over traditional PID control. The tool uses static simulation models of the system under control to generate feed-forward control action, which acts as a reference of correct operation. Faults that occur in the system cause discrepancies between the feedforward models and the controlled process. The scheme facilitates detection of faults by monitoring the level of these discrepancies. We present results from the first phase of tests on a dual-duct air-handling unit installed in a large office building in San Francisco. We demonstrate the ability of the tool to detect a number of preexisting faults in the system and discuss practical issues related to implementation.

  5. Sensor and Actuator Fault Detection and Isolation in Nonlinear System using Multi Model Adaptive Linear Kalman Filter

    M. Manimozhi


    Full Text Available Fault Detection and Isolation (FDI using Linear Kalman Filter (LKF is not sufficient for effective monitoring of nonlinear processes. Most of the chemical plants are nonlinear in nature while operating the plant in a wide range of process variables. In this study we present an approach for designing of Multi Model Adaptive Linear Kalman Filter (MMALKF for Fault Detection and Isolation (FDI of a nonlinear system. The uses a bank of adaptive Kalman filter, with each model based on different fault hypothesis. In this study the effectiveness of the MMALKF has been demonstrated on a spherical tank system. The proposed method is detecting and isolating the sensor and actuator soft faults which occur sequentially or simultaneously.

  6. A Fault Detection and Isolation Scheme Based on Parity Space Method for Discrete Time-delay System

    WANG Hong-yu; TIAN Zuo-hua; SHI Song-jiao; WENG Zheng-xin


    A Fault detection and isolation (FDI) scheme for discrete time-delay system is proposed in this paper, which can not only detect but also isolate the faults. A time delay operator ▽ is introduced to resolve the problem brought by the time-delay system. The design and computation for the FDI system is carried by computer math tool Maple, which can easily deal with the symbolic computation. Residuals in the form of parity space can be deduced from the recursion of the system equations. Further mote, a generalized residual set is created using the freedom of the parity space redundancy. Thus, both fault detection and fault isolation have been accomplished. The proposed method has been verified by a numerical example.

  7. EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan


    A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.

  8. A Wireless Sensor System for Real-Time Monitoring and Fault Detection of Motor Arrays

    Medina-García, Jonathan; Sánchez-Rodríguez, Trinidad; Galán, Juan Antonio Gómez; Delgado, Aránzazu; Gómez-Bravo, Fernando; Jiménez, Raúl


    This paper presents a wireless fault detection system for industrial motors that combines vibration, motor current and temperature analysis, thus improving the detection of mechanical faults. The design also considers the time of detection and further possible actions, which are also important for the early detection of possible malfunctions, and thus for avoiding irreversible damage to the motor. The remote motor condition monitoring is implemented through a wireless sensor network (WSN) based on the IEEE 802.15.4 standard. The deployed network uses the beacon-enabled mode to synchronize several sensor nodes with the coordinator node, and the guaranteed time slot mechanism provides data monitoring with a predetermined latency. A graphic user interface offers remote access to motor conditions and real-time monitoring of several parameters. The developed wireless sensor node exhibits very low power consumption since it has been optimized both in terms of hardware and software. The result is a low cost, highly reliable and compact design, achieving a high degree of autonomy of more than two years with just one 3.3 V/2600 mAh battery. Laboratory and field tests confirm the feasibility of the wireless system. PMID:28245623

  9. Detecting Blind Fault with Fractal and Roughness Factors from High Resolution LiDAR DEM at Taiwan

    Cheng, Y. S.; Yu, T. T.


    There is no obvious fault scarp associated with blind fault. The traditional method of mapping this unrevealed geological structure is the cluster of seismicity. Neither the seismic event nor the completeness of cluster could be captured by network to chart the location of the entire possible active blind fault within short period of time. High resolution DEM gathered by LiDAR could denote actual terrain information despite the existence of plantation. 1-meter interval DEM of mountain region at Taiwan is utilized by fractal, entropy and roughness calculating with MATLAB code. By jointing these handing, the regions of non-sediment deposit are charted automatically. Possible blind fault associated with Chia-Sen earthquake at southern Taiwan is served as testing ground. GIS layer help in removing the difference from various geological formation, then multi-resolution fractal index is computed around the target region. The type of fault movement controls distribution of fractal index number. The scale of blind fault governs degree of change in fractal index. Landslide induced by rainfall and/or earthquake possesses larger degree of geomorphology alteration than blind fault; special treatment in removing these phenomena is required. Highly weathered condition at Taiwan should erase the possible trace remained upon DEM from the ruptured of blind fault while reoccurrence interval is higher than hundreds of years. This is one of the obstacle in finding possible blind fault at Taiwan.

  10. Research of the Late Quaternary Recent Activity of the Middle Segment of Kouquan Fault

    Xu Wei; Liu Xudong; Zhang Shimin


    Systematic research of the characteristics of late Quaternary activity of the middle part of Kouquan fault has been done through conducting 1:50000 geologic mapping combining with remote sensing interpretation of spot imaging, field validating and chronology research of the research area. Studies suggest that the middle part of Kouquan fault has had strong activity since the late Quaternary which controls the tectonic evolvement of the nearby mountains and Datong basin. The recent activity of this fault has faulted the sandy gravel layers of T1 terrace and the lower part of dark loessial soils over the terrace on the north of Chanfang village. The maximum vertical displacement is over 3m in the area between Xiaoyukou village and Louzikou village, and to the south of Dayukou village and the north of Emaokou village, the displacement decreases to 0. 5m and 0. 25m respectively. Based on the recent faulted landforms and combined with dating, we determined the age of recent activity of the fault in the research area to be between 7. 71ka B.P. to 3. 00 ka B.P. Discussions are made on this in combination with previous research.

  11. Tools for Evaluating Fault Detection and Diagnostic Methods for HVAC Secondary Systems

    Pourarian, Shokouh

    Although modern buildings are using increasingly sophisticated energy management and control systems that have tremendous control and monitoring capabilities, building systems routinely fail to perform as designed. More advanced building control, operation, and automated fault detection and diagnosis (AFDD) technologies are needed to achieve the goal of net-zero energy commercial buildings. Much effort has been devoted to develop such technologies for primary heating ventilating and air conditioning (HVAC) systems, and some secondary systems. However, secondary systems, such as fan coil units and dual duct systems, although widely used in commercial, industrial, and multifamily residential buildings, have received very little attention. This research study aims at developing tools that could provide simulation capabilities to develop and evaluate advanced control, operation, and AFDD technologies for these less studied secondary systems. In this study, HVACSIM+ is selected as the simulation environment. Besides developing dynamic models for the above-mentioned secondary systems, two other issues related to the HVACSIM+ environment are also investigated. One issue is the nonlinear equation solver used in HVACSIM+ (Powell's Hybrid method in subroutine SNSQ). It has been found from several previous research projects (ASRHAE RP 825 and 1312) that SNSQ is especially unstable at the beginning of a simulation and sometimes unable to converge to a solution. Another issue is related to the zone model in the HVACSIM+ library of components. Dynamic simulation of secondary HVAC systems unavoidably requires an interacting zone model which is systematically and dynamically interacting with building surrounding. Therefore, the accuracy and reliability of the building zone model affects operational data generated by the developed dynamic tool to predict HVAC secondary systems function. The available model does not simulate the impact of direct solar radiation that enters a zone

  12. Estimating the detectability of faults in 3D-seismic data - A valuable input to Induced Seismic Hazard Assessment (ISHA)

    Goertz, A.; Kraft, T.; Wiemer, S.; Spada, M.


    In the past several years, some geotechnical operations that inject fluid into the deep subsurface, such as oil and gas development, waste disposal, and geothermal energy development, have been found or suspected to cause small to moderate sized earthquakes. In several cases the largest events occurred on previously unmapped faults, within or in close vicinity to the operated reservoirs. The obvious conclusion drawn from this finding, also expressed in most recently published best practice guidelines and recommendations, is to avoid injecting into faults. Yet, how certain can we be that all faults relevant to induced seismic hazard have been identified, even around well studied sites? Here we present a probabilistic approach to assess the capability of detecting faults by means of 3D seismic imaging. First, we populate a model reservoir with seed faults of random orientation and slip direction. Drawing random samples from a Gutenberg-Richter distribution, each seed fault is assigned a magnitude and corresponding size using standard scaling relations based on a circular rupture model. We then compute the minimum resolution of a 3D seismic survey for given acquisition parameters and frequency bandwidth. Assuming a random distribution of medium properties and distribution of image frequencies, we obtain a probability that a fault of a given size is detected, or respectively overlooked, by the 3D seismic. Weighting the initial Gutenberg-Richter fault size distribution with the probability of imaging a fault, we obtain a modified fault size distribution in the imaged volume from which we can constrain the maximum magnitude to be considered in the seismic hazard assessment of the operation. We can further quantify the value of information associated with the seismic image by comparing the expected insured value loss between the image-weighted and the unweighted hazard estimates.

  13. Soil-gas helium and surface-waves detection of fault zones in granitic bedrock

    G K Reddy; T Seshunarayana; Rajeev Menon; P Senthil Kumar


    Fracture and fault networks are conduits that facilitate groundwater movement in hard-rock terrains.Soil-gas helium emanometry has been utilized in Wailapally watershed,near Hyderabad in southern India,for the detection of fracture and fault zones in a granite basement terrain having a thin regolith.Based on satellite imagery and geologic mapping,three sites were selected for detailed investigation.High spatial resolution soil-gas samples were collected at every one meter at a depth of <1.5m along 100 m long profiles (3 in number).In addition,deep shear-wave images were also obtained using the multichannel analysis of surface waves.The study clearly indicates several soil-gas helium anomalies (above 200 ppb)along the pro files,where the shear-wave velocity images also show many near-surface vertical low velocity zones.We thus interpret that the soil-gas helium anomalous zones and the vertical low-velocity zones are probable traces of fault/fracture zones that could be efficient natural recharge zones and potential groundwater conduits.The result obtained from this study demonstrates the efficacy of an integrated approach of soil-gas helium and the seismic methods for mapping groundwater resource zones in granite/gneiss provinces.

  14. Predictive Modeling of a Two-Stage Gearbox towards Fault Detection

    Edward J. Diehl


    Full Text Available This paper presents a systematic approach to the modeling and analysis of a benchmark two-stage gearbox test bed to characterize gear fault signatures when processed with harmonic wavelet transform (HWT analysis. The eventual goal of condition monitoring is to be able to interpret vibration signals from nonstationary machinery in order to identify the type and severity of gear damage. To advance towards this goal, a lumped-parameter model that can be analyzed efficiently is developed which characterizes the gearbox vibratory response at the system level. The model parameters are identified through correlated numerical and experimental investigations. The model fidelity is validated first by spectrum analysis, using constant speed experimental data, and secondly by HWT analysis, using nonstationary experimental data. Model prediction and experimental data are compared for healthy gear operation and a seeded fault gear with a missing tooth. The comparison confirms that both the frequency content and the predicted, relative response magnitudes match with physical measurements. The research demonstrates that the modeling method in combination with the HWT data analysis has the potential for facilitating successful fault detection and diagnosis for gearbox systems.

  15. Analysis of Dynamics in Multiphysics Modelling of Active Faults

    Sotiris Alevizos


    Full Text Available Instabilities in Geomechanics appear on multiple scales involving multiple physical processes. They appear often as planar features of localised deformation (faults, which can be relatively stable creep or display rich dynamics, sometimes culminating in earthquakes. To study those features, we propose a fundamental physics-based approach that overcomes the current limitations of statistical rule-based methods and allows a physical understanding of the nucleation and temporal evolution of such faults. In particular, we formulate the coupling between temperature and pressure evolution in the faults through their multiphysics energetic process(es. We analyse their multiple steady states using numerical continuation methods and characterise their transient dynamics by studying the time-dependent problem near the critical Hopf points. We find that the global system can be characterised by a homoclinic bifurcation that depends on the two main dimensionless groups of the underlying physical system. The Gruntfest number determines the onset of the localisation phenomenon, while the dynamics are mainly controlled by the Lewis number, which is the ratio of energy diffusion over mass diffusion. Here, we show that the Lewis number is the critical parameter for dynamics of the system as it controls the time evolution of the system for a given energy supply (Gruntfest number.

  16. Active Crustal Faults in the Forearc Region, Guerrero Sector of the Mexican Subduction Zone

    Gaidzik, Krzysztof; Ramírez-Herrera, Maria Teresa; Kostoglodov, Vladimir


    This work explores the characteristics and the seismogenic potential of crustal faults on the overriding plate in an area of high seismic hazard associated with the occurrence of subduction earthquakes and shallow earthquakes of the overriding plate. We present the results of geomorphic, structural, and fault kinematic analyses conducted on the convergent margin between the Cocos plate and the forearc region of the overriding North American plate, within the Guerrero sector of the Mexican subduction zone. We aim to determine the active tectonic processes in the forearc region of the subduction zone, using the river network pattern, topography, and structural data. We suggest that in the studied forearc region, both strike-slip and normal crustal faults sub-parallel to the subduction zone show evidence of activity. The left-lateral offsets of the main stream courses of the largest river basins, GPS measurements, and obliquity of plate convergence along the Cocos subduction zone in the Guerrero sector suggest the activity of sub-latitudinal left-lateral strike-slip faults. Notably, the regional left-lateral strike-slip fault that offsets the Papagayo River near the town of La Venta named "La Venta Fault" shows evidence of recent activity, corroborated also by GPS measurements (4-5 mm/year of sinistral motion). Assuming that during a probable earthquake the whole mapped length of this fault would rupture, it would produce an event of maximum moment magnitude Mw = 7.7. Even though only a few focal mechanism solutions indicate a stress regime relevant for reactivation of these strike-slip structures, we hypothesize that these faults are active and suggest two probable explanations: (1) these faults are characterized by long recurrence period, i.e., beyond the instrumental record, or (2) they experience slow slip events and/or associated fault creep. The analysis of focal mechanism solutions of small magnitude earthquakes in the upper plate, for the period between 1995

  17. Continental Dynamics in High Tibetan Plateau: Normal Faulting Type Earthquake Activities and Mechanisms

    Xu Jiren; Zhao Zhixin


    Various earthquake fault types were analyzed for this study on the crust movement in the high region of the Tibetan plateau by analyzing mechanism solutions and stress fields. The results show that a lot of normal faulting type earthquakes are concentrated in the central High Tibetan plateau. Many of them are nearly perfect normal fault events. The strikes of the fault planes of normal faulting earthquakes are almost in an N-S direction based on the analyses of the Wulff stereonet diagrams of fault plane solutions. It implies that the dislocation slip vectors of the normal faulting type events have quite great components in the E-W direction. The extensions probably are an eastward extensional motion, being mainly a tectonic active regime in the plateau altitudes. The tensional stress in the E-W or NWW-SEE direction predominates earthquake occurrences in the normal event region of the central plateau. The eastward extensional motion in the high Tibetan plateau is attributable to the gravitational collapse of the high plateau and the eastward extrusion of hotter mantle materials beneath the east boundary of the plateau. Extensional motions from the relaxation of the topography and/or gravitational collapse in the high plateau hardly occurred along the N-S direction. The obstruction for the plateau to move eastward is rather weak.

  18. Eocene activity on the Western Sierra Fault System and its role incising Kings Canyon, California

    Sousa, Francis J.; Farley, Kenneth A.; Saleeby, Jason; Clark, Marin


    Combining new and published apatite (U-Th)/He and apatite 4He/3He data from along the Kings River canyon, California we rediscover a west-down normal fault on the western slope of the southern Sierra Nevada, one of a series of scarps initially described by Hake (1928) which we call the Western Sierra Fault System. Integrating field observations with apatite (U-Th)/He data, we infer a single fault trace 30 km long, and constrain the vertical offset across this fault to be roughly a kilometer. Thermal modeling of apatite 4He/3He data documents a pulse of footwall cooling near the fault and upstream in the footwall at circa 45-40 Ma, which we infer to be the timing of a kilometer-scale incision pulse resulting from the fault activity. In the context of published data from the subsurface of the Sacramento and San Joaquin Valleys, our data from the Western Sierra Fault System suggests an Eocene tectonic regime dominated by low-to-moderate magnitude extension, surface uplift, and internal structural deformation of the southern Sierra Nevada and proximal Great Valley forearc.

  19. A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles.

    Xu, Jun; Wang, Jing; Li, Shiying; Cao, Binggang


    Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists.

  20. A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles

    Xu, Jun; Wang, Jing; Li, Shiying; Cao, Binggang


    Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists. PMID:27548183