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Sample records for active fault detection

  1. Active fault detection in MIMO systems

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2014-01-01

    from auxiliary input to residual outputs. The analysis is based on a singular value decomposition of these transfer functions Based on this analysis, it is possible to design auxiliary input as well as design of the associated residual vector with respect to every single parametric fault in the system......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...

  2. Controller modification applied for active fault detection

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

    2014-01-01

    This paper is focusing on active fault detection (AFD) for parametric faults in closed-loop systems. This auxiliary input applied for the fault detection will also disturb the external output and consequently reduce the performance of the controller. Therefore, only small auxiliary inputs are used...... modify the feedback controller with a minor effect on the external output in the fault free case. Further, in the faulty case, the signature of the auxiliary input can be optimized. This is obtained by using a band-pass filter for the YJBK parameter that is only effective in a small frequency range where...... the frequency for the auxiliary input is selected. This gives that it is possible to apply an auxiliary input with a reduced amplitude. An example is included to show the results....

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

    Yeganeh Fallah, Arash; Taghikhany, Touraj

    2015-12-01

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

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

    Wilson, Edward (Inventor)

    2008-01-01

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

  5. Active Fault Detection and Isolation for Hybrid Systems

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

    2009-01-01

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

  6. Active Fault Isolation in MIMO Systems

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2014-01-01

    isolation is based directly on the input/output s ignals applied for the fault detection. It is guaranteed that the fault group includes the fault that had occurred in the system. The second step is individual fault isolation in the fault group . Both types of isolation are obtained by applying dedicated......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...

  7. Network Power Fault Detection

    Siviero, Claudio

    2013-01-01

    Network power fault detection. At least one first network device is instructed to temporarily disconnect from a power supply path of a network, and at least one characteristic of the power supply path of the network is measured at a second network device connected to the network while the at least one first network device is temporarily disconnected from the network

  8. Fault detection and isolation in systems with parametric faults

    Stoustrup, Jakob; Niemann, Hans Henrik

    1999-01-01

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

  9. 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)

    2015-12-01

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

  10. Fault detection in photovoltaic systems

    Nilsson, David

    2014-01-01

    This master’s thesis concerns three different areas in the field of fault detection in photovoltaic systems.Previous studies have concerned homogeneous systems with a large set of parameters being observed,while this study is focused on a more restrictive case. The first problem is to discover immediate faults occurring in solar panels. A new online algorithm is developed based on similarity measures with in a single installation. It performs reliably and is able to detect all significant fau...

  11. Static Decoupling in fault detection

    Niemann, Hans Henrik

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

  12. Fault Detection for Automotive Shock Absorber

    Hernandez-Alcantara, Diana; Morales-Menendez, Ruben; Amezquita-Brooks, Luis

    2015-11-01

    Fault detection for automotive semi-active shock absorbers is a challenge due to the non-linear dynamics and the strong influence of the disturbances such as the road profile. First obstacle for this task, is the modeling of the fault, which has been shown to be of multiplicative nature. Many of the most widespread fault detection schemes consider additive faults. Two model-based fault algorithms for semiactive shock absorber are compared: an observer-based approach and a parameter identification approach. The performance of these schemes is validated and compared using a commercial vehicle model that was experimentally validated. Early results shows that a parameter identification approach is more accurate, whereas an observer-based approach is less sensible to parametric uncertainty.

  13. Measurement Testing of Radon Gas for Fault Activity Detection in Rahtawu Muria, Pati

    The radon surface can be used to investigates not only for environment but also to be develop in an earth application. The investigation is carried out at the Rahtawu fault, that includes, to the Pati regency which is located 40 km South of ULA. The objective of study to measure the radon released from the fracture zone activities. RDA equipment is being used to measure the radon gas released. The result shown that the high value of radon is 311 cpm with the background of 18 cpm, whereas the low value falls at 0 cpm. The tattoo value are influenced by the soil condition, tattoo time, hardness, weather, soil/stone porosity and fault possession. (author)

  14. 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....

  15. Fault detection and fault-tolerant control using sliding modes

    Alwi, Halim; Tan, Chee Pin

    2011-01-01

    ""Fault Detection and Fault-tolerant Control Using Sliding Modes"" is the first text dedicated to showing the latest developments in the use of sliding-mode concepts for fault detection and isolation (FDI) and fault-tolerant control in dynamical engineering systems. It begins with an introduction to the basic concepts of sliding modes to provide a background to the field. This is followed by chapters that describe the use and design of sliding-mode observers for FDI using robust fault reconstruction. The development of a class of sliding-mode observers is described from first principles throug

  16. Exact, almost and delayed fault detection

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

    1999-01-01

    Considers the problem of fault detection and isolation while using zero or almost zero threshold. A number of different fault detection and isolation problems using exact or almost exact disturbance decoupling are formulated. Solvability conditions are given for the formulated design problems. The...... l-step delayed fault detection problem is also considered for discrete-time systems....

  17. Fault detection using genetic programming

    Zhang, Liang; B. Jack, Lindsay; Nandi, Asoke K.

    2005-03-01

    Genetic programming (GP) is a stochastic process for automatically generating computer programs. GP has been applied to a variety of problems which are too wide to reasonably enumerate. As far as the authors are aware, it has rarely been used in condition monitoring (CM). In this paper, GP is used to detect faults in rotating machinery. Featuresets from two different machines are used to examine the performance of two-class normal/fault recognition. The results are compared with a few other methods for fault detection: Artificial neural networks (ANNs) have been used in this field for many years, while support vector machines (SVMs) also offer successful solutions. For ANNs and SVMs, genetic algorithms have been used to do feature selection, which is an inherent function of GP. In all cases, the GP demonstrates performance which equals or betters that of the previous best performing approaches on these data sets. The training times are also found to be considerably shorter than the other approaches, whilst the generated classification rules are easy to understand and independently validate.

  18. Fundamental problems in fault detection and identification

    Saberi, A.; Stoorvogel, A. A.; Sannuti, P.;

    2000-01-01

    A number of different fundamental problems in fault detection and fault identification are formulated in this paper. The fundamental problems include exact, almost, generic and class-wise fault detection and identification. Necessary and sufficient conditions for the solvability of the fundamental...

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

    Gao, Qing; Dong, Daoyi; Petersen, Ian R.

    2015-01-01

    This paper aims to determine the fault tolerant quantum filter and fault detection equation for a class of open quantum systems coupled to a laser field that is subject to stochastic faults. In order to analyze this class of open quantum systems, we propose a quantum-classical Bayesian inference method based on the definition of a so-called quantum-classical conditional expectation. It is shown that the proposed Bayesian inference approach provides a convenient tool to simultaneously derive t...

  20. Aluminium Process Fault Detection and Diagnosis

    Nazatul Aini Abd Majid; Taylor, Mark P; Chen, John J. J.; Brent R. Young

    2015-01-01

    The challenges in developing a fault detection and diagnosis system for industrial applications are not inconsiderable, particularly complex materials processing operations such as aluminium smelting. However, the organizing into groups of the various fault detection and diagnostic systems of the aluminium smelting process can assist in the identification of the key elements of an effective monitoring system. This paper reviews aluminium process fault detection and diagnosis systems and propo...

  1. A new fault detection method for computer networks

    Over the past few years, fault detection for computer networks has attracted extensive attentions for its importance in network management. Most existing fault detection methods are based on active probing techniques which can detect the occurrence of faults fast and precisely. But these methods suffer from the limitation of traffic overhead, especially in large scale networks. To relieve traffic overhead induced by active probing based methods, a new fault detection method, whose key is to divide the detection process into multiple stages, is proposed in this paper. During each stage, only a small region of the network is detected by using a small set of probes. Meanwhile, it also ensures that the entire network can be covered after multiple detection stages. This method can guarantee that the traffic used by probes during each detection stage is small sufficiently so that the network can operate without severe disturbance from probes. Several simulation results verify the effectiveness of the proposed method

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

    Gelso, Esteban R.; Blanke, Mogens

    2009-01-01

    Isolability of faults is a key issue in fault diagnosis whether the aim is maintenance or active fault-tolerant control. It is often encountered that while faults are detectable, they are only group-wise isolable from a usual diagnostic point of view. However, active injection of test signals 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...

  3. Fault Detection for a Diesel Engine Actuator

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

    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)....

  4. Integration of control and fault detection

    Niemann, Hans Henrik; Stoustrup, J.

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

  5. Illuminating Northern California's Active Faults

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

    2009-02-01

    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 Earth™ and other similar software) formats through the GEON OpenTopography Portal (http://www.OpenTopography.org/data). 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).

  6. 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

    2016-01-01

    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

  7. Faults in clays their detection and properties

    Baldi, G.; Carabelli, E.; Chiantore, V.; Colombo, P.F.; Gruszka, A.; Pensieri, R.; Superbo, S.; Gera, F.

    1991-12-31

    The `Faults in clays project`, a cooperative research effort between Ismes and Enea of Italy and BGS and Exeter University of the UK, has been aimed at assessing and improving the resolution capability of some high resolution geophysical techniques for the detection of discontinuities in clay formations. All Ismes activities have been carried out in Italy: they consisted in the search of one or more sites - faulted clay formations - suitable for the execution of geophysical and geotechnical investigations, in the execution of such tests and in additional geological surveys and laboratory (geotechnical and geochemical) testing. The selected sites were two quarries in plio-pleistocenic clay formations in central Italy where faults had been observed. The greatest part of the research work has been carried out in the Orte site where also two 90 m boreholes have been drilled and cored. Geophysical work at Orte consisted of vertical electrical soundings (VESs) and horizontal electrical lines (HELs), four high resolution seismic reflection lines, and in-hole and cross-hole logs. Laboratory activities were geotechnical characterization and permeability tests, and measurements of disequilibrium in the uranium decay series. At Narni, where Exeter University sampled soil gases for geochemical analyses, the geophysical work consisted in a geo-electrical survey (five VESs and two HELs), and in two high resolution reflection seismic lines. Additional investigations included a structural geology survey. The main conclusion of the research is that current geophysical techniques do not have a resolution capacity sufficient to detect the existence and determine the characteristics of faults in deep homogeneous clay formations.

  8. Faults in clays their detection and properties

    The 'Faults in clays project', a cooperative research effort between Ismes and Enea of Italy and BGS and Exeter University of the UK, has been aimed at assessing and improving the resolution capability of some high resolution geophysical techniques for the detection of discontinuities in clay formations. All Ismes activities have been carried out in Italy: they consisted in the search of one or more sites - faulted clay formations - suitable for the execution of geophysical and geotechnical investigations, in the execution of such tests and in additional geological surveys and laboratory (geotechnical and geochemical) testing. The selected sites were two quarries in plio-pleistocenic clay formations in central Italy where faults had been observed. The greatest part of the research work has been carried out in the Orte site where also two 90 m boreholes have been drilled and cored. Geophysical work at Orte consisted of vertical electrical soundings (VESs) and horizontal electrical lines (HELs), four high resolution seismic reflection lines, and in-hole and cross-hole logs. Laboratory activities were geotechnical characterization and permeability tests, and measurements of disequilibrium in the uranium decay series. At Narni, where Exeter University sampled soil gases for geochemical analyses, the geophysical work consisted in a geo-electrical survey (five VESs and two HELs), and in two high resolution reflection seismic lines. Additional investigations included a structural geology survey. The main conclusion of the research is that current geophysical techniques do not have a resolution capacity sufficient to detect the existence and determine the characteristics of faults in deep homogeneous clay formations

  9. Fault detection, isolation and reconfiguration in FTMP Methods and experimental results. [fault tolerant multiprocessor

    Lala, J. H.

    1983-01-01

    The Fault-Tolerant Multiprocessor (FTMP) is a highly reliable computer designed to meet a goal of 10 to the -10th failures per hour and built with the objective of flying an active-control transport aircraft. Fault detection, identification, and recovery software is described, and experimental results obtained by injecting faults in the pin level in the FTMP are presented. Over 21,000 faults were injected in the CPU, memory, bus interface circuits, and error detection, masking, and error reporting circuits of one LRU of the multiprocessor. Detection, isolation, and reconfiguration times were recorded for each fault, and the results were found to agree well with earlier assumptions made in reliability modeling.

  10. Aluminium Process Fault Detection and Diagnosis

    Nazatul Aini Abd Majid

    2015-01-01

    Full Text Available The challenges in developing a fault detection and diagnosis system for industrial applications are not inconsiderable, particularly complex materials processing operations such as aluminium smelting. However, the organizing into groups of the various fault detection and diagnostic systems of the aluminium smelting process can assist in the identification of the key elements of an effective monitoring system. This paper reviews aluminium process fault detection and diagnosis systems and proposes a taxonomy that includes four key elements: knowledge, techniques, usage frequency, and results presentation. Each element is explained together with examples of existing systems. A fault detection and diagnosis system developed based on the proposed taxonomy is demonstrated using aluminium smelting data. A potential new strategy for improving fault diagnosis is discussed based on the ability of the new technology, augmented reality, to augment operators’ view of an industrial plant, so that it permits a situation-oriented action in real working environments.

  11. Efficient Sensor Fault Detection Using Group Testing

    Lo, Chun; Bai, Yechao; Liu, Mingyan; Lynch, Jerome P.

    2015-01-01

    When faulty sensors are rare in a network, diagnosing sensors individually is inefficient. This study introduces a novel use of concepts from group testing and Kalman filtering in detecting these rare faulty sensors with significantly fewer number of tests. By assigning sensors to groups and performing Kalman filter-based fault detection over these groups, we obtain binary detection outcomes, which can then be used to recover the fault state of all sensors. We first present this method using ...

  12. Detecting Fan Faults in refrigerated Cabinets

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

    2002-01-01

    Fault detection in supermarket refrigeration systems is an important topic due to both economic and food safety reasons. If faults can be detected and diagnosed before the system drifts outside the specified operational envelope, service costs can be reduced and in extreme cases the costly...... faults in display cabinets under the wide operational conditions that display cabinets are exposed to. The approach described uses a non- linear parity equation comparing the heat transfer rates of the air and the refrigerant. The paper presents the detection method and discusses the application of the...

  13. Fault Detection and Isolation for Spacecraft

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2002-01-01

    This article realizes nonlinear Fault Detection and Isolation for actuators, given there is no measurement of the states in the actuators. The Fault Detection and Isolation of the actuators is instead based on angular velocity measurement of the spacecraft and knowledge about the dynamics of the...... satellite. The algorithms presented in this paper are based on a geometric approach to achieve nonlinear Fault Detection and Isolation. The proposed algorithms are tested in a simulation study and the pros and cons of the algorithms are discussed....

  14. Fault Detection and Isolation using Eigenstructure Assignment

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

    1994-01-01

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

  15. Verification-based Software-fault Detection

    Gladisch, Christoph David

    2011-01-01

    Software is used in many safety- and security-critical systems. Software development is, however, an error-prone task. In this dissertation new techniques for the detection of software faults (or software "bugs") are described which are based on a formal deductive verification technology. The described techniques take advantage of information obtained during verification and combine verification technology with deductive fault detection and test generation in a very unified way.

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

    Fukushima, Y.

    2013-12-01

    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

  17. 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.

    2015-12-01

    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.

  18. Linear discriminant analysis for welding fault detection

    This work presents a new method for real time welding fault detection in industry based on Linear Discriminant Analysis (LDA). A set of parameters was calculated from one second blocks of electrical data recorded during welding and based on control data from reference welds under good conditions, as well as faulty welds. Optimised linear combinations of the parameters were determined with LDA and tested with independent data. Short arc welds in overlap joints were studied with various power sources, shielding gases, wire diameters, and process geometries. Out-of-position faults were investigated. Application of LDA fault detection to a broad range of welding procedures was investigated using a similarity measure based on Principal Component Analysis. The measure determines which reference data are most similar to a given industrial procedure and the appropriate LDA weights are then employed. Overall, results show that Linear Discriminant Analysis gives an effective and consistent performance in real-time welding fault detection.

  19. DATA-MINING BASED FAULT DETECTION

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

    2005-01-01

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

  20. Reset Tree-Based Optical Fault Detection

    Howon Kim

    2013-05-01

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

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

    Anamika Yadav

    2014-01-01

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

  2. 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...

  3. Online Distributed Fault Detection of Sensor Measurements

    GAO Jianliang; XU Yongjun; LI Xiaowei

    2007-01-01

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

  4. Preliminaries of probabilistic hierarchical fault detection

    Jirsa, Ladislav; Pavelková, Lenka; Dedecius, Kamil

    Prague: Institute of Information Theory and Automation, 2013 - (Guy, T.; Kárný, M.) ISBN 978-80-903834-8-7. [The 3rd International Workshop on Scalable Decision Making: Uncertainty, Imperfection, Deliberation held in conjunction with ECML/PKDD 2013. Prague (CZ), 23.09.2013-23.09.2013] R&D Projects: GA MŠk 7D12004; GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Fault detection * FDI * probabilistic logic * system health Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2013/AS/jirsa-preliminaries of probabilistic hierarchical fault detection.pdf

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

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

    2011-01-01

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

  6. 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)

    2016-01-01

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

  7. Fault Detection for Shipboard Monitoring and Decision Support Systems

    Lajic, Zoran; Nielsen, Ulrik Dam

    2009-01-01

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

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

    Lootsma, T.F.

    2001-01-01

    With the rise in automation the increase in fault detectionand isolation & reconfiguration is inevitable. Interest in fault detection and isolation (FDI) for nonlinear systems has grown significantly in recent years. The design of FDI is motivated by the need for knowledge about occurring faults in fault-tolerant control systems (FTC systems). The idea of FTC systems is to detect, isolate, and handle faults in such a way that the systems can still perform in a required manner. One prefers...

  9. Robust Fault Detection and Isolation for Stochastic Systems

    George, Jemin; Gregory, Irene M.

    2010-01-01

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

  10. Model Based Fault Detection in a Centrifugal Pump Application

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

    2006-01-01

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

  11. RepTFD: Replay Based Transient Fault Detection

    Li, Lei; Chen, Tianshi; Chen, Yunji; Li, Ling; Wu, Ruiyang

    2012-01-01

    The advances in IC process make future chip multiprocessors (CMPs) more and more vulnerable to transient faults. To detect transient faults, previous core-level schemes provide redundancy for each core separately. As a result, they may leave transient faults in the uncore parts, which consume over 50% area of a modern CMP, escaped from detection. This paper proposes RepTFD, the first core-level transient fault detection scheme with 100% coverage. Instead of providing redundancy for each core ...

  12. Detection of ''beading faults'' in welded tubes

    In the steel tube industry the word ''beading'' refers to a highly localised leak affecting the welded zone. During the pneumatic test its flow rate is generally very low no more than a few thousandths of a mm3/second. Detection of such a fault by this test is consequently slow, and those which are choked or at the limit of leakage may escape detection. For greater safety, the tube technician is now using non-destructive testing methods such as eddy-currents and ultrasonics

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

    Lootsma, T.F.

    -tolerance can be applied to ordinary industrial processes that are not categorized as high risk applications, but where high availability is desirable. The quality of fault-tolerant control is totally dependent on the quality of the underlying algorithms. They detect possible faults, and later reconfigure......With the rise in automation the increase in fault detectionand isolation & reconfiguration is inevitable. Interest in fault detection and isolation (FDI) for nonlinear systems has grown significantly in recent years. The design of FDI is motivated by the need for knowledge about occurring faults in...... fault-tolerant control systems (FTC systems). The idea of FTC systems is to detect, isolate, and handle faults in such a way that the systems can still perform in a required manner. One prefers reduced performance after occurrence of a fault to the shut down of (sub-) systems. Hence, the idea of fault...

  14. 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

    2005-01-01

    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

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

    Lu, Kaiyuan

    2014-01-01

    For reliable fault detection, often, search coils are used in many fault-tolerant drives. The search coils occupy extra slot space. They are normally open-circuited and are not used for torque production. This degrades the motor performance, increases the cost and manufacture complexity. A new...... Fault-Tolerant Switched Reluctance (FTSR) motor is proposed in this paper. A unique feature of this special design is that it allows use of the unexcited phase coils as search coils for fault detection. Therefore this new motor has all the advantages of using search coils for reliable fault detection...

  16. Techniques for Surveying Urban Active Faults by Seismic Methods

    Xu Mingcai; Gao Jinghua; Liu Jianxun; Rong Lixin

    2005-01-01

    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.

  17. Exact, almost and delayed fault detection: An observer based approach

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

    1999-01-01

    This paper consider the problem of fault detection and isolation in continuous- and discrete-time systems while using zero or almost zero threshold. A number of different fault detections and isolation problems using exact or almost exact disturbance decoupling are formulated. Solvability...... conditions are given for the formulated design problems together with methods for appropriate design of observer based fault detectors. The l-step delayed fault detection problem is also considered for discrete-time systems . Moreover, certain indirect fault detection methods such as unknown input observers...

  18. Analysis of fault detection method based on predictive filter approach

    LI Ji; ZHANG Hongyue

    2005-01-01

    A new detection method for component faults based on predictive filters together with the fault detectability, false alarm rate, missed alarm rate and upper bound of detection time are proposed. The efficiency of the method is illustrated by a simulation example of a second-order system. It is shown that the fault detection method using predictive filters has a small delay, a low false alarm rate and a low missed alarm rate. Furthermore the filter can give accurate estimates of states even after a fault occurs. The real-time estimation provided by this method can also be used for fault tolerant control.

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

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

    2014-01-01

    is to detect and handle different faults occurring in the individual turbines on farm level. The fault detection system is designed such that it takes advantage of the fact that within a wind farm several of the turbines will be operating under similar conditions. To enable this the turbines are...... occurring 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......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...

  20. Fault Detection on the Software Implementation of CLEFIA Lightweight Cipher

    Wei Li

    2012-08-01

    Full Text Available CLEFIA is an efficient lightweight cipher that delivers advanced copyright protection and authentication in computer networks. It is also applied in the secure protocol for transmission including SSL and TLS. Since it was proposed in 2007, some work about its security against differential fault analysis has been devoted to reducing the number of faults and to improving the time complexity of this attack. This attack is very efficient when a single fault is injected into the last several rounds of the CLEFIA, and it allows to recover the whole secret key. Thus, it is an open question whether detecting the faults injected into the CLEFIA with low overhead of space and time tolerance. In this paper, we present a fault detection of the CLEFIA block cipher in the single-byte fault model. Our result in this study could detect the faults with negligible cost when faults are even injected into the last four rounds. 

  1. FUZZY FAULT DETECTION FOR PERMANENT MAGNET SYNCHRONOUS GENERATOR

    N. Selvaganesan

    2011-07-01

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

  2. Fault tolerant filtering and fault detection for quantum systems driven by fields in single photon states

    Gao, Qing; Dong, Daoyi; Petersen, Ian R.; Rabitz, Herschel

    2016-06-01

    The purpose of this paper is to solve the fault tolerant filtering and fault detection problem for a class of open quantum systems driven by a continuous-mode bosonic input field in single photon states when the systems are subject to stochastic faults. Optimal estimates of both the system observables and the fault process are simultaneously calculated and characterized by a set of coupled recursive quantum stochastic differential equations.

  3. Fault detection in mechanical systems based on subspace features

    Nguyen, Viet Ha; Rutten, Christophe; Golinval, Jean-Claude

    2010-01-01

    In the field of structural health monitoring or machine condition monitoring, the activation of nonlinear dynamic behavior complicates the procedure of damage or fault detection. Principal Component Analysis (PCA) is known as an efficient method for damage diagnosis. However, two drawbacks of PCA are the assumption of the linearity of the system and the need of many sensors. This article presents industrial applications of two possible extensions of PCA: Null subspace analysis (NSA) and Kerne...

  4. Bearing fault detection with application to PHM Data Challenge

    Anton Urevc

    2011-01-01

    Full Text Available Mechanical faults in production lines can result in partial or total breakdown of a production line, destruction of equipment and even catastrophes. Implementation of an adequate fault detection system represents an important step towards early detection of such faults, thus reducing the risk of unexpected failures. Traditionally, fault detection process is done by comparing the observed machine state with a set of historical data representing the fault--free state. However, such historical data are rarely available. In such cases, the fault detection process is performed by examining whether a particular pre--modeled fault signature can be matched within the signals acquired from the monitored machine. In this paper we propuse a solution to a problem of fault detection without any prior data, presented at PHM'09 Data Challenge. The solution is based on a two step algorithm. The first step, based on the spectral kurtosis method, is used to determine whether a particular experimental run is likely to contain a faulty element. In case of a positive decision, fault isolation procedure is applied as the second step. The fault isolation procedure was based on envelope analysis of filtered vibration signals. The filtering of the vibration signals was performed in the frequency band that maximizes the spectral kurtosis. The effectiveness of the proposed approach was evaluated for bearing fault detection, on the vibration data obtained from the PHM'09 Data Challenge.

  5. Additional Fault Detection Test Case Prioritization

    Ritika Jain

    2013-07-01

    Full Text Available Regression testing is used to confirm that previous bugs have been fixed and that new bugs have not been introduced. Thus regression testing is done during maintenance phase and applied whenever a new version of a program is obtained by modifying an existing version. To perform a regression testing a set of new test cases and old test cases that were previously developed by software engineers are reused. This test suite is exhaustive in nature and it may take long time to rerun all test cases. Thus regression testing is too expensive and the number of test cases increases stridently as the software evolves. In present work, an additional fault detection test case prioritization technique is presented that prioritizes test cases in regression test suite based on number of concealed faults detected by test cases. Both noncost cognizant and cost cognizant prioritization of test cases have been performed using proposed technique and efficiency of prioritized suite is assessed using APFD and APFDc metric respectively.

  6. Undestructive fault detection of power transformers through the transfer function

    In this paper, we present a new undestructive fault detection method for power transformers. The proposed method is based on changes of the pattern of transfer functions according to various faults of power transformers. While the sweep signal is put into the secondary side of the transformer, we measure currents and voltages on the primary and secondary sides. The transfer function founded by the signal processing of measured signals is compared so that how it deviate from the normal transfer function. Based on these data, the fault detection algorithm determine in which phase the faults occur and identify the type of faults by calculating the change of the transfer function.

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

    Khukhuudei, M.; Khukhuudei, U.

    2014-12-01

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

  8. Spatial radon anomalies on active faults in California

    Radon emanation has been observed to be anomalously high along active faults in many parts of the world. We tested this relationship by conducting and repeating soil-air radon surveys with a portable radon meter across several faults in California. The results confirm the existence of fault-associated radon anomalies, which show characteristic features that may be related to fault structures but vary in time due to other environmental changes, such as rainfall. Across two creeping faults in San Juan Bautista and Hollister, the radon anomalies showed prominent double peaks straddling the fault-gouge zone during dry summers, but the peak-to-background ratios diminished after significant rain fall during winter. Across a locked segment of the San Andreas fault near Olema, the anomaly has a single peak located several meters southwest of the slip zone associated with the 1906 San Francisco earthquake. Across two fault segments that ruptured during the magnitude 7.5 Landers earthquake in 1992, anomalously high radon concentration was found in the fractures three weeks after the earthquake. We attribute the fault-related anomalies to a slow vertical gas flow in or near the fault zones. Radon generated locally in subsurface soil has a concentration profile that increases three orders of magnitude from the surface to a depth of several meters; thus an upward flow that brings up deeper and radon-richer soil air to the detection level can cause a significantly higher concentration reading. This explanation is consistent with concentrations of carbon dioxide and oxygen, measured in soil-air samples collected during one of the surveys. (Author)

  9. Hybrid fault tolerance techniques to detect transient faults in embedded processors

    Azambuja, José Rodrigo; Becker, Jürgen

    2014-01-01

    This book describes fault tolerance techniques based on software and hardware to create hybrid techniques. They are able to reduce overall performance degradation and increase error detection when associated with applications implemented in embedded processors. Coverage begins with an extensive discussion of the current state-of-the-art in fault tolerance techniques. The authors then discuss the best trade-off between software-based and hardware-based techniques and introduce novel hybrid techniques. Proposed techniques increase existing fault detection rates up to 100%, while maintaining low performance overheads in area and application execution time. • Discusses the effects of radiation on modern integrated circuits; • Provides a comprehensive overview of state-of-the art fault tolerance techniques based on software, hardware, and hybrid techniques; • Introduces novel hybrid fault tolerance techniques for reconfigurable FPGAs and ASICs; • Performs fault injection campaigns by simulation, bitstream ...

  10. Series Arc Fault Detection Algorithm Based on Autoregressive Bispectrum Analysis

    Kai Yang

    2015-10-01

    Full Text Available Arc fault is one of the most critical reasons for electrical fires. Due to the diversity, randomness and concealment of arc faults in low-voltage circuits, it is difficult for general methods to protect all loads from series arc faults. From the analysis of many series arc faults, a large number of high frequency signals generated in circuits are found. These signals are easily affected by Gaussian noise which is difficult to be eliminated as a result of frequency aliasing. Thus, a novel detection algorithm is developed to accurately detect series arc faults in this paper. Initially, an autoregressive model of the mixed high frequency signals is modelled. Then, autoregressive bispectrum analysis is introduced to analyze common series arc fault features. The phase information of arc fault signal is preserved using this method. The influence of Gaussian noise is restrained effectively. Afterwards, several features including characteristic frequency, fluctuation of phase angles, diffused distribution and incremental numbers of bispectrum peaks are extracted for recognizing arc faults. Finally, least squares support vector machine is used to accurately identify series arc faults from the load states based on these frequency features of bispectrum. The validity of the algorithm is experimentally verified obtaining arc fault detection rate above 97%.

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

    Li, Linlin

    2016-01-01

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

  12. Detection of Fault Location in Transmission Lines using Wavelet Transform

    Shilpi Sahu

    2013-09-01

    Full Text Available This paper presents a technique to detect the location of the different faults on a transmission lines for quick and reliable operation of protection schemes. The simulation is developed in MATLAB to generate the fundamental component of the transient voltage and current simultaneously both in time and frequency domain. One cycle of waveform, covering pre-fault and post-fault information is abstracted for analysis. The discrete wavelet transform (DWT is used for data preprocessing. It is applied for decomposition of fault transients, because of its ability to extract information from the transient signal, simultaneously both in time and frequency domain. MATLAB software is used to simulate different operating and fault conditions on high voltage transmission line, namely single phase to ground fault, line to line fault, double line to ground and three phase short circuit.

  13. Export Methods in Fault Detection and Localization Mechanisms

    Aymen Belghith

    2012-07-01

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

  14. Fault detection and diagnosis of diesel engine valve trains

    Flett, Justin; Bone, Gary M.

    2016-05-01

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

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

    Deng Qidong; Lu Zaoxun; Yang Zhu'en

    2008-01-01

    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.

  16. Detection of Fault Location in Transmission Lines using Wavelet Transform

    Shilpi Sahu

    2013-01-01

    This paper presents a technique to detect the location of the different faults on a transmission lines for quick and reliable operation of protection schemes. The simulation is developed in MATLAB to generate the fundamental component of the transient voltage and current simultaneously both in time and frequency domain. One cycle of waveform, covering pre-fault and post-fault information is abstracted for analysis. The discrete wavelet transform (DWT) is used for data preprocessing. It is app...

  17. Bearing Fault Detection in Induction Motor-Gearbox Drivetrain

    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.

  18. 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

    2008-06-01

    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.

  19. Active tectonics of Himalayan Frontal Fault system

    Thakur, V. C.

    2013-04-01

    In the Sub-Himalayan zone, the frontal Siwalik range abuts against the alluvial plain with an abrupt physiographic break along the Himalayan Frontal Thrust (HFT), defining the present-day tectonic boundary between the Indian plate and the Himalayan orogenic prism. The frontal Siwalik range is characterized by large active anticline structures, which were developed as fault propagation and fault-bend folds in the hanging wall of the HFT. Fault scarps showing surface ruptures and offsets observed in excavated trenches indicate that the HFT is active. South of the HFT, the piedmont zone shows incipient growth of structures, drainage modification, and 2-3 geomorphic depositional surfaces. In the hinterland between the HFT and the MBT, reactivation and out-of-sequence faulting displace Late Quaternary-Holocene sediments. Geodetic measurements across the Himalaya indicate a ~100-km-wide zone, underlain by the Main Himalayan Thrust (MHT), between the HFT and the main microseismicity belt to north is locked. The bulk of shortening, 15-20 mm/year, is consumed aseismically at mid-crustal depth through ductile by creep. Assuming the wedge model, reactivation of the hinterland faults may represent deformation prior to wedge attaining critical taper. The earthquake surface ruptures, ≥240 km in length, interpreted on the Himalayan mountain front through paleoseismology imply reactivation of the HFT and may suggest foreland propagation of the thrust belt.

  20. Risk-based fault detection using Self-Organizing Map

    The complexity of modern systems is increasing rapidly and the dominating relationships among system variables have become highly non-linear. This results in difficulty in the identification of a system's operating states. In turn, this difficulty affects the sensitivity of fault detection and imposes a challenge on ensuring the safety of operation. In recent years, Self-Organizing Maps has gained popularity in system monitoring as a robust non-linear dimensionality reduction tool. Self-Organizing Map is able to capture non-linear variations of the system. Therefore, it is sensitive to the change of a system's states leading to early detection of fault. In this paper, a new approach based on Self-Organizing Map is proposed to detect and assess the risk of fault. In addition, probabilistic analysis is applied to characterize the risk of fault into different levels according to the hazard potential to enable a refined monitoring of the system. The proposed approach is applied on two experimental systems. The results from both systems have shown high sensitivity of the proposed approach in detecting and identifying the root cause of faults. The refined monitoring facilitates the determination of the risk of fault and early deployment of remedial actions and safety measures to minimize the potential impact of fault. - Highlights: • A new approach based on Self-Organizing Map is proposed to detect faults. • Integration of fault detection with risk assessment methodology. • Fault risk characterization into different levels to enable focused system monitoring

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

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

    2014-01-01

    In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the...... 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...

  2. Research of Gear Fault Detection in Morphological Wavelet Domain

    Hong, Shi; Fang-jian, Shan; Bo, Cong; Wei, Qiu

    2016-02-01

    For extracting mutation information from gear fault signal and achieving a valid fault diagnosis, a gear fault diagnosis method based on morphological mean wavelet transform was designed. Morphological mean wavelet transform is a linear wavelet in the framework of morphological wavelet. Decomposing gear fault signal by this morphological mean wavelet transform could produce signal synthesis operators and detailed synthesis operators. For signal synthesis operators, it was just close to orginal signal, and for detailed synthesis operators, it contained fault impact signal or interference signal and could be catched. The simulation experiment result indicates that, compared with Fourier transform, the morphological mean wavelet transform method can do time-frequency analysis for original signal, effectively catch impact signal appears position; and compared with traditional linear wavelet transform, it has simple structure, easy realization, signal local extremum sensitivity and high denoising ability, so it is more adapted to gear fault real-time detection.

  3. Distance Based Fault detection in wireless sensor network

    Ayasha Siddiqua

    2013-05-01

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

  4. A summary of the active fault investigation in the extension sea area of Kikugawa fault and the Nishiyama fault , N-S direction fault in south west Japan

    Abe, S.

    2010-12-01

    In this study, we carried out two sets of active fault investigation by the request from Ministry of Education, Culture, Sports, Science and Technology in the sea area of the extension of Kikugawa fault and the Nishiyama fault. We want to clarify the five following matters about both active faults based on those results. (1)Fault continuity of the land and the sea. (2) The length of the active fault. (3) The division of the segment. (4) Activity characteristics. In this investigation, we carried out a digital single channel seismic reflection survey in the whole area of both active faults. In addition, a high-resolution multichannel seismic reflection survey was carried out to recognize the detailed structure of a shallow stratum. Furthermore, the sampling with the vibrocoring to get information of the sedimentation age was carried out. The reflection profile of both active faults was extremely clear. The characteristics of the lateral fault such as flower structure, the dispersion of the active fault were recognized. In addition, from analysis of the age of the stratum, it was recognized that the thickness of the sediment was extremely thin in Holocene epoch on the continental shelf in this sea area. It was confirmed that the Kikugawa fault extended to the offing than the existing results of research by a result of this investigation. In addition, the width of the active fault seems to become wide toward the offing while dispersing. At present, we think that we can divide Kikugawa fault into some segments based on the distribution form of the segment. About the Nishiyama fault, reflection profiles to show the existence of the active fault was acquired in the sea between Ooshima and Kyushu. From this result and topographical existing results of research in Ooshima, it is thought that Nishiyama fault and the Ooshima offing active fault are a series of structure. As for Ooshima offing active fault, the upheaval side changes, and a direction changes too. Therefore, we

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

    Abolghasem Gourabi

    2011-01-01

    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.

  6. Lateral migration of fault activity in Weihe basin

    冯希杰; 戴王强

    2004-01-01

    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.

  7. Lateral migration of fault activity in Weihe basin

    Feng, Xi-Jie; Dai, Wang-Qiang

    2004-03-01

    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.

  8. 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...

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

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

    of the measurement with a closed set that is computed based on the past measurements and a model of the system. If the measurement is not consistent with this set, a fault is detected. The result demonstrates effectiveness of the method for fault detection of the benchmark wind turbine.......This paper investigates a state estimation set- membership approach for fault detection of a benchmark wind turbine. The main challenges in the benchmark are high noise on the wind speed measurement and the nonlinearities in the aerodynamic torque such that the overall model of the turbine 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...

  10. Exhumation history of an active fault to constrain a fault-based seismic hazard scenario: the Pizzalto fault (central Apennines, Italy) example.

    Tesson, Jim; Pace, Bruno; Benedetti, Lucilla; Visini, Francesco; Delli Rocioli, Mattia; Didier, Bourles; Karim, keddadouche; Gorges, Aumaitre

    2016-04-01

    A prerequisite to constrain fault-based and time-dependent earthquake rupture forecast models is to acquire data on the past large earthquake frequency on an individual seismogenic source and to compare all the recorded occurrences in the active fault-system. We investigated the Holocene seismic history of the Pizzalto normal fault, a 13 km long fault segment belonging to the Pizzalto-Rotella-Aremogna fault system in the Apennines (Italy). We collected 44 samples on the Holocene exhumed Pizzalto fault plane and analyzed their 36Cl and rare earth elements content. Conjointly used, the 36Cl and REE concentrations show that at least 6 events have exhumed 4.4 m of the fault scarp between 3 and 1 ka BP, the slip per event ranging from 0.3 to 1.2 m. No major events have been detected over the last 1 ka. The Rotella-Aremogna-Pizzalto fault system has a clustered earthquake behaviour with a mean recurrence time of 1.2 ka and a low to moderate probability (ranging from 4% to 26%) of earthquake occurrence over the next 50 years. We observed similarities between seismic histories of several faults belonging to two adjacent fault systems. This could again attest that non-random processes occurring in the release of the strain accumulated on faults, commonly referred to as fault interactions and leading to apparent synchronization. If these processes were determined as being the main parameter controlling the occurrence of earthquakes, it would be crucial to take them into account in seismic hazard models.

  11. Integration Techniques of Fault Detection and Isolation Using Interval Observers

    Meseguer Amela, Jordi

    2009-01-01

    An interval observer has been illustrated to be a suitable approach to detect and isolate faults affecting complex dynamical industrial systems. Concerning fault detection, interval observation is an appropriate passive robust strategy to generate an adaptive threshold to be used in residual evaluation when model uncertainty is located in parameters (interval model). In such approach, the observer gain is a key parameter since it determines the time evolution of the residual sensitiv...

  12. Fault detection and isolation in processes involving induction machines

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

    1997-12-31

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

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

    Odgaard, Peter Fogh; Shafiei, Seyed Ehsan

    2015-01-01

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

  14. Correlating hardware fault detection information from distributed control systems to isolate and diagnose a fault in pressurised water reactors

    Cilliers, Anthonie Christoffel

    2013-01-01

    Early fault identification systems enable detecting and diagnosing early onset faults or fault causes which allow maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. We have shown (Cilliers and Mulder, 2012) that detecting faults early during transient operation in NPPs is possible when coupled with a reliable reference to compare plant measu...

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

    Bergantino, Nicola; Caponetti, Fabio; Longhi, Sauro

    2009-01-01

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

  16. Observer Based Detection of Sensor Faults in Wind Turbines

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

    2009-01-01

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

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

    Stelling, P.

    1998-06-09

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

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

    Hanafy, Sherif M.

    2014-08-05

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

  19. Designing Expert System for Detecting Faults in Cloud Environment

    Marzieh Shabdiz

    2013-11-01

    Full Text Available Many fault detection techniques for detecting faults in rule bases system have appeared in the literature. These techniques assume that the rule base is static. This paper presents a new approach by designing Expert system for detecting faults in dynamic environment, such as cloud. Cloud resources are usually not only shared by multiple users but are also dynamically re-allocated per demand. Therefore, rules may be added/deleted in response to certain events happening in the integrated system being controlled by the rules. The approach makes use of spanning trees and Complementary sets to check a dynamic rule base for different kinds of faults underlying directed graph and devises a new method with scripting language on web based tools. This is performed as rules are being added to the dynamic rule base one at a time without the need to rebuild the structures and update rules and paths by expert system.

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

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

    2016-05-01

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

  1. 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

    2016-09-01

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

  2. Bearings fault detection using inference tools

    Prieto, Miguel Delgado; Roura, Jordi Cusidó i; Martínez, Jose Luis Romeral

    2011-01-01

    The most used electric machine in the industry is the Induction Motor (IM), due to its simplicity and reduced cost. The analysis of the origin of IMs failures exhibits that the bearings are the major source of fault, and even a common cause of degradation in other kinds of motors as Permanent Magnet Synchronous Machines.

  3. Wavelet Packet based Detection of Surface Faults on Compact Discs

    Odgaard, Peter Fogh; Stoustrup, Jakob; Wickerhauser, Mladen Victor

    2006-01-01

    use of dedicated filters adapted to remove the faults from the measurements. In this paper detection using wavelet packet filters is demonstrated. The filters are designed using the joint best basis method. Detection using these filters shows a distinct improvement compared to detection using ordinary...

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

    Nordmann Rainer; Aenis Martin

    2004-01-01

    The number of rotors running in active magnetic bearings (AMBs) has increased over the last few years. These systems offer a great variety of advantages compared to conventional systems. The aim of this article is to use the AMBs together with a developed built-in software for identification, fault detection, and diagnosis in a centrifugal pump. A single-stage pump representing the turbomachines is investigated. During full operation of the pump, the AMBs are used as actuators to generate def...

  5. Fault detection and reliability, knowledge based and other approaches

    These proceedings are split up into four major parts in order to reflect the most significant aspects of reliability and fault detection as viewed at present. The first part deals with knowledge-based systems and comprises eleven contributions from leading experts in the field. The emphasis here is primarily on the use of artificial intelligence, expert systems and other knowledge-based systems for fault detection and reliability. The second part is devoted to fault detection of technological systems and comprises thirteen contributions dealing with applications of fault detection techniques to various technological systems such as gas networks, electric power systems, nuclear reactors and assembly cells. The third part of the proceedings, which consists of seven contributions, treats robust, fault tolerant and intelligent controllers and covers methodological issues as well as several applications ranging from nuclear power plants to industrial robots to steel grinding. The fourth part treats fault tolerant digital techniques and comprises five contributions. Two papers, one on reactor noise analysis, the other on reactor control system design, are indexed separately. (author)

  6. Automated Fault Detection for DIII-D Tokamak Experiments

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

  7. Enhanced Fault Detection and Isolation in Modern Flight Actuators

    Ossmann, Daniel

    2013-01-01

    Due to their central location in the control system, actuation systems of primary control surfaces in modern, augmented aircraft must show an increased reliability. A traditional approach is based on hardware redundancy. In this way, modern actuation systems of one single control surface consist of up to two actuators and three sensors. These different dynamic subsystems are all prone to faults themselves and can be monitored. This paper presents the setup of a fault detection and diagnosis (...

  8. Advanced Information Processing System - Fault detection and error handling

    Lala, J. H.

    1985-01-01

    The Advanced Information Processing System (AIPS) is designed to provide a fault tolerant and damage tolerant data processing architecture for a broad range of aerospace vehicles, including tactical and transport aircraft, and manned and autonomous spacecraft. A proof-of-concept (POC) system is now in the detailed design and fabrication phase. This paper gives an overview of a preliminary fault detection and error handling philosophy in AIPS.

  9. Applying Parametric Fault Detection to a Mechanical System

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

    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. Th...... parameter changes (faults) are estimated based on estimates of the fictitious signals that enter the delta block in the lft. These signal estimators are designed by H-infinity techniques. The chosen example is an inverted pendulum....

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

    Button, Robert M.

    2004-01-01

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

  11. Distance Based Fault detection in wireless sensor network

    Ayasha Siddiqua; Shikha Swaroop; Prashant Krishan; Sandip Mandal

    2013-01-01

    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 (DBFD)method for wireless sensor network using the average of confidence level and sensed data of sensor n...

  12. Measurements of soil gas radon in active fault systems: A case study along the North and East anatolian fault systems in Turkey

    We have used solid-state nuclear track detectors (CR-39) in order to determine the profile of the soil radon in district areas of the North and East Anatolian active fault systems in Turkey. It has been shown that the radon anomalies among the fault zones are relatively high in the fault line while dramatically decreases by going away from the lines. Radon concentrations in both active fault systems ranged from 4.3 to 9.8kBqm-3. The average radon concentration levels in the North Anatolian Fault System are relatively higher than the East Anatolian Fault System. Radon measurement technique is proved to be a good tool for detection and mapping of the active fault zone, and also in the case of continuous monitoring of radon anomalies connected with earthquake events

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

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

    2015-12-31

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

  14. Sensor Fault Detection and Diagnosis for autonomous vehicles

    Realpe Miguel

    2015-01-01

    Full Text Available In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor.

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

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

    2016-05-01

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

  16. Correlating hardware fault detection information from distributed control systems to isolate and diagnose a fault in pressurised water reactors

    Highlights: ► Attempt was to use available resources at a nuclear plant in a value added fashion. ► Includes plant measurement data and plant training and engineering simulator capabilities. ► Correlating fault detection data for systems to develop of a deterministic fault identifications system. ► After implementing a host of data manipulation algorithms, the results provided more information on the fault than expected. - Abstract: Early fault identification systems enable detecting and diagnosing early onset faults or fault causes which allow maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. We have shown (Cilliers and Mulder, 2012) that detecting faults early during transient operation in NPPs is possible when coupled with a reliable reference to compare plant measurements with during transients. The problem introduced by the distributed application of control systems operating independently to keep the plant operating within the safe operating boundaries was solved by re-introducing the fault information it into the measurement data, thereby improving plant diagnostic performance. This paper introduces the use of improved fault detection information received from all distributed systems in the plant control system and correlating the information to not only detect the fault but also to diagnose it based on the location and magnitude of the fault cause

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

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

    2015-07-01

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

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

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

    2016-01-01

    has many advantages, such as easy implementation and high system reliability. Because of using Power Spectral Density method (PSD) or Fast Fourier Transform (FFT) method cannot get clear fault characteristic frequencies, this kind of faults should be detected by an effective method. This paper......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...

  19. Nondestructive detection system of faults in fuses using radioisotope

    A system is developed to show the viability of non-destructive detection of the faults of explosive safety fuses which are manufactured by Fabrica da Estrela do Ministerio do Exercito. The faults are detected by an ion-chamber based on the variation of the intensity of the beta particles that penetrate the fuse which passes through a collimator. The beta particles are emitted by Strontium-90 + Yttrium-90 encapsulated in either stainless steel or aluminum. The concept of 'bucking Voltage' is applied to differentiate electronically the signal generated by the ion-chamber. (author)

  20. Gear Fault Detection Based on Teager-Huang Transform

    Hui Li

    2010-01-01

    Full Text Available Gear fault detection based on Empirical Mode Decomposition (EMD and Teager Kaiser Energy Operator (TKEO technique is presented. This novel method is named as Teager-Huang transform (THT. EMD can adaptively decompose the vibration signal into a series of zero mean Intrinsic Mode Functions (IMFs. TKEO can track the instantaneous amplitude and instantaneous frequency of the Intrinsic Mode Functions at any instant. The experimental results provide effective evidence that Teager-Huang transform has better resolution than that of Hilbert-Huang transform. The Teager-Huang transform can effectively diagnose the fault of the gear, thus providing a viable processing tool for gearbox defect detection and diagnosis.

  1. Detecting Faults By Use Of Hidden Markov Models

    Smyth, Padhraic J.

    1995-01-01

    Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).

  2. Multimode Process Fault Detection Using Local Neighborhood Similarity Analysis☆

    Xiaogang Deng; Xuemin Tian

    2014-01-01

    Traditional data driven fault detection methods assume unimodal distribution of process data so that they often perform not wel in chemical process with multiple operating modes. In order to monitor the multimode chemical process effectively, this paper presents a novel fault detection method based on local neighborhood similarity analysis (LNSA). In the proposed method, prior process knowledge is not required and only the multimode normal operation data are used to construct a reference dataset. For online monitoring of process state, LNSA applies moving window technique to obtain a current snapshot data window. Then neighborhood searching technique is used to acquire the corresponding local neighborhood data window from the reference dataset. Similarity analysis between snapshot and neighborhood data windows is performed, which includes the calculation of principal component analysis (PCA) similarity factor and distance similarity factor. The PCA similarity factor is to capture the change of data direction while the distance similarity factor is used for monitoring the shift of data center position. Based on these similarity factors, two monitoring statistics are built for multimode process fault detection. Final y a simulated continuous stirred tank system is used to demonstrate the effectiveness of the proposed method. The simulation results show that LNSA can detect multimode process changes effectively and performs better than traditional fault detection methods.

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

    Lee SangHun

    2016-01-01

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

  4. Vibration based fault detection techniques for mechanical structures

    Fault detection techniques for mechanical structures and their application are becoming more important in recent years in the field of structure health monitoring. The intention of this paper is to present available state of the art methods that could be implemented in mechanical structures. Global based methods that contribute on detection, isolation and analysis of fault from changes in vibration characteristics of the structure are presented. Techniques are based on the idea that modal frequencies, mode shapes and modal damping as model properties of the structure can be determine as function of physical properties. In addition, if a fault appears in mechanical structure, this can be recognized as changes in the physical properties, which leads to cause changes in the modal properties of the structure. (Author)

  5. Fault Detection in Coal Mills used in Power Plants

    Odgaard, Peter Fogh; Mataji, Babak

    2006-01-01

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

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

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

    2012-01-01

    account process disturbances, uncertainty and sensor noise. The FTC strategy takes advantage of the proposed FDI algorithm, enabling the controller reconfiguration shortly after fault events. Additionally, a robust controller is designed so as to increase the wind turbine's performance during low severity......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...... 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...

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

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

    2010-01-01

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

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

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

    2016-03-01

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

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

    Narayan, Anand P.

    1998-07-01

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

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

    Trippanera, D.; Acocella, V.; Ruch, J.; Abebe, B.

    2015-11-01

    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 dike-fed eruptive fissures. We then consider the lateral termination of normal faults along these grabens 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.

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

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

    2016-07-01

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

  12. Active Fault Characterization in the Urban Area of Vienna

    Decker, Kurt; Grupe, Sabine; Hintersberger, Esther

    2016-04-01

    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.

  13. Uranium groundwater anomalies and active normal faulting

    The ability to predict earthquakes is one of the greatest challenges for Earth Sciences. Radon has been suggested as one possible precursor, and its groundwater anomalies associated with earthquakes and water-rock interactions were proposed in several seismogenic areas worldwide as due to possible transport of radon through microfractures, or due to crustal gas fluxes along active faults. However, the use of radon as a possible earthquake's precursor is not clearly linked to crustal deformation. It is shown in this paper that uranium groundwater anomalies, which were observed in cataclastic rocks crossing the underground Gran Sasso National Laboratory, can be used as a possible strain meter in domains where continental lithosphere is subducted. Measurements evidence clear, sharp anomalies from July, 2008 to the end of March, 2009, related to a preparation phase of the seismic swarm, which occurred near L'Aquila, Italy, from October, 2008 to April, 2009. On April 6th, 2009 an earthquake (Mw = 6.3) occurred at 01:33 UT in the same area, with normal faulting on a NW-SE oriented structure about 15 km long, dipping toward SW. In the framework of the geophysical and geochemical models of the area, these measurements indicate that uranium may be used as a possible strain meter in extensional tectonic settings similar to those where the L'Aquila earthquake occurred. (author)

  14. Battery Fault Detection with Saturating Transformers

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

    2013-01-01

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

  15. Fault detection in rotating machines by vibration signal processing techniques

    D'Elia, Gianluca

    2008-01-01

    Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are...

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

    Odgaard, Peter Fogh; Mataji, Babak

    2008-01-01

    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......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 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...

  17. Active faults of the Baikal depression

    Levi, K.G.; Miroshnichenko, A.I.; San'kov, V. A.; Babushkin, S.M.; Larkin, G.V.; Badardinov, A.A.; Wong, H.K.; Colman, S.; Delvaux, D.

    1997-01-01

    The Baikal depression occupies a central position in the system of the basins of the Baikal Rift Zone and corresponds to the nucleus from which the continental lithosphere began to open. For different reasons, the internal structure of the Lake Baikal basin remained unknown for a long time. In this article, we present for the first time a synthesis of the data concerning the structure of the sedimentary section beneath Lake Baikal, which were obtained by complex seismic and structural investigations, conducted mainly from 1989 to 1992. We make a brief description of the most interesting seismic profiles which provide a rough idea of a sedimentary unit structure, present a detailed structural interpretation and show the relationship between active faults in the lake, heat flow anomalies and recent hydrothermalism.

  18. Fault mirrors in seismically active fault zones: A fossil of small earthquakes at shallow depths

    Kuo, Li-Wei; Song, Sheng-Rong; Suppe, John; Yeh, En-Chao

    2016-03-01

    Fault mirrors (FMs) are naturally polished and glossy fault slip surfaces that can record seismic deformation at shallow depths. They are important for investigating the processes controlling dynamic fault slip. We characterize FMs in borehole samples from the hanging wall damage zone of the active Hsiaotungshi reverse fault, Taiwan. Here we report the first documented occurrence of the combination of silica gel and melt patches coating FMs, with the silica gel resembling those observed on experimentally formed FMs that were cataclastically generated. In addition, the melt patches, which are unambiguous indicators of coseismic slip, suggest that the natural FMs were produced at seismic rates, presumably resulting from flash heating at asperities on the slip surfaces. Since flash heating is efficient at small slip, we propose that these natural FMs represent fossils of small earthquakes, formed in either coseismic faulting and folding or aftershock deformation in the active Taiwan fold-and-thrust belt.

  19. Electrical Structure of the Shallow Part of the Atotsugawa Fault, Central Japan: Detecting en Echelon Structure in the Fault Zone

    Yamashita, F.; Kubo, A.; Yamada, R.; Omura, K.

    2005-12-01

    Dense VLF-MT and TDEM surveys were carried out to image the electrical structure of a region interpreted as a creeping segment of the Atotsugawa Fault, central Japan. The Atotsugawa Fault is an active fault with a length of 60-70 km and a strike of approximately N60°E. The fault type is a right-lateral strike-slip. The most significant characteristic of this fault is a possible existence of creeping segment. In the central region, the stable slip with a rate of 1.5 mm/year was found by the observation of baseline change (Geographical Survey Institute, 1997). However, such slip has not been found at the southwestern region. Therefore, the central region is considered to be a creeping segment. In the creeping segment, many fault outcrops were found on the right bank of the Atotsu-gawa River that runs along the fault. Strikes of shear planes in outcrops were observed to be N30°-47°E, which is apparently different from that of the Atotsugawa fault. This observation suggested the existence of en echelon structure, which is the cluster of small shear zones oblique to main fault. Investigation of the nature of the en echelon structure will help us to understand the growth history of the Atotsugawa fault and the mechanisms of creeping phenomenon. Because a fracture zone usually includes much water, we can detect it as a low resistivity zone. In order to image the detailed structure of echelon, we carried out the electromagnetic surveys; VLF-MT and TDEM survey as a preliminary and main investigation, respectively. The results of VLF-MT survey has been reported by Yamashita et al. (2005), and therefore we don_ft refer to the results here. We acquired data at 10000 points with airborne TDEM survey, and over 4000 data were selectively used for modeling the subsurface structure. Apparent resistivity at each point was modeled assuming 1-D structure that consists of 30 and 70 m thick layers on a semi-infinite basement (three layers in total). Because over 4000 survey points

  20. Fault recovery characteristics of the fault tolerant multi-processor

    Padilla, Peter A.

    1990-01-01

    The fault handling performance of the fault tolerant multiprocessor (FTMP) was investigated. Fault handling errors detected during fault injection experiments were characterized. In these fault injection experiments, the FTMP disabled a working unit instead of the faulted unit once every 500 faults, on the average. System design weaknesses allow active faults to exercise a part of the fault management software that handles byzantine or lying faults. It is pointed out that these weak areas in the FTMP's design increase the probability that, for any hardware fault, a good LRU (line replaceable unit) is mistakenly disabled by the fault management software. It is concluded that fault injection can help detect and analyze the behavior of a system in the ultra-reliable regime. Although fault injection testing cannot be exhaustive, it has been demonstrated that it provides a unique capability to unmask problems and to characterize the behavior of a fault-tolerant system.

  1. Sensor fault detection using the Mahalanobis distance

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

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

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2001-01-01

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

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

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2001-01-01

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

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

    Yuanchun Li

    2015-01-01

    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.

  5. Fault detection in IRIS reactor secondary loop using inferential models

    The development of fault detection algorithms is well-suited for remote deployment of small and medium reactors, such as the IRIS, and the development of new small modular reactors (SMR). However, an extensive number of tests are still to be performed for new engineering aspects and components that are not yet proven technology in the current PWRs, and present some technological challenges for its deployment since many of its features cannot be proven until a prototype plant is built. In this work, an IRIS plant simulation platform was developed using a Simulink® model. The dynamic simulation was utilized in obtaining inferential models that were used to detect faults artificially added to the secondary system simulations. The implementation of data-driven models and the results are discussed. (author)

  6. An adaptive envelope spectrum technique for bearing fault detection

    In this work, an adaptive envelope spectrum (AES) technique is proposed for bearing fault detection, especially for analyzing signals with transient events. The proposed AES technique first modulates the signal using the empirical mode decomposition to formulate the representative intrinsic mode functions (IMF), and then a novel IMF reconstruction method is proposed based on a correlation analysis of the envelope spectra. The reconstructed signal is post-processed by using an adaptive filter to enhance impulsive signatures, where the filter length is optimized by the proposed sparsity analysis technique. Bearing health conditions are diagnosed by examining bearing characteristic frequency information on the envelope power spectrum. The effectiveness of the proposed fault detection technique is verified by a series of experimental tests corresponding to different bearing conditions. (paper)

  7. Fault Detection and Isolation in Multiple MEMS-IMUs Configurations

    Guerrier, Stéphane; Waegli, Adrian; Skaloud, Jan; Victoria-Feser, Maria-Pia

    2012-01-01

    This research presents methods for detecting and isolating faults in multiple MEMS-IMU configurations. First, geometric configurations with n sensor triads are investigated. It is proofed that the relative orientation between sensor triads is irrelevant to system optimality in the absence of failures. Then, the impact of sensor failure or decreased performance is investigated. Three FDI approaches (i.e. the parity space method, Mahalanobis distance method and its direct robustification) are r...

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

    Leloux, Jonathan; Luna, Alberto; Desportes, Adrien

    2014-01-01

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

  9. Benchmarking an expert fault detection and diagnostic system on the Three Mile Island accident event sequence

    Cilleirs, A.C.

    2013-01-01

    Early fault identification systems enable detecting and diagnosing early onset faults or fault causes which allow maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. We have shown (Cilliers and Mulder, 2012) that detecting faults early during transient operation in NPPs is possible when coupled with a reliable reference to compare...

  10. Detection of stator winding fault in induction motor using instantaneous power signature analysis

    KÜÇÜKER, AHMET; BAYRAK, Mehmet

    2015-01-01

    Stator interturn faults are one of the most common faults occurring in induction motors. Early detection of interturn short circuit is important to reduce repair costs. Axial leakage monitoring, zero-sequence components, negative sequence current, and motor current signature analysis have been used for fault detection in early states. In the paper, the instantaneous power signature analysis technique is used to detect these faults, and experimental results for healthy and faulty motors are sh...

  11. SVD and Hankel matrix based de-noising approach for ball bearing fault detection and its assessment using artificial faults

    Golafshan, Reza; Yuce Sanliturk, Kenan

    2016-03-01

    Ball bearings remain one of the most crucial components in industrial machines and due to their critical role, it is of great importance to monitor their conditions under operation. However, due to the background noise in acquired signals, it is not always possible to identify probable faults. This incapability in identifying the faults makes the de-noising process one of the most essential steps in the field of Condition Monitoring (CM) and fault detection. In the present study, Singular Value Decomposition (SVD) and Hankel matrix based de-noising process is successfully applied to the ball bearing time domain vibration signals as well as to their spectrums for the elimination of the background noise and the improvement the reliability of the fault detection process. The test cases conducted using experimental as well as the simulated vibration signals demonstrate the effectiveness of the proposed de-noising approach for the ball bearing fault detection.

  12. Fault detection system for Argentine Research Reactor instrumentation

    Polenta, Héctor P.; Bernard, John A.; Ray, Asok

    1993-01-01

    The design and implementation of a redundancy management scheme for the on-line detection and isolation of faulty sensors is presented. Such a device is potentially useful in reactor-powered spacecraft for enhancing the processing capabilities of the main computer. The fault detection device can be used as an integral part of intelligent instrumentation systems. The device has been built using an 8-bit microcontroller and commercially available electronic hardware. The software is completely portable. The operation of this device has been successfully demonstrated for real-time validation of sensor data on Argentina's RA-1 Research Reactor.

  13. Fault detection system for Argentine Research Reactor instrumentation

    The design and implementation of a redundancy management scheme for the on-line detection and isolation of faulty sensors is presented. Such a device is potentially useful in reactor-powered spacecraft for enhancing the processing capabilities of the main computer. The fault detection device can be used as an integral part of intelligent instrumentation systems. The device has been built using an 8-bit microcontroller and commercially available electronic hardware. The software is completely portable. The operation of this device has been successfully demonstrated for real-time validation of sensor data on Argentina's RA-1 Research Reactor

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

    B. Samanta

    2004-03-01

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

  15. 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...

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

    Trippanera, D.

    2015-10-08

    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.

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

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

    2012-01-01

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

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

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

    1998-01-01

    The paper gives an introduction and an overview of the field of fault detection and isolation for control systems. The summary of analytical (quantitative model-based) methodds and their implementation are presented. The focus is given to mthe analytical model-based fault-detection and fault...

  19. Quaternary seismo-tectonic activity of the Polochic Fault, Guatemala

    Authemayou, Christine; Brocard, Gilles; TEYSSIER, Christian; Suski, Barbara; Cosenza, Beatriz; Moran-Ical, Sergio; Gonzalez-Veliz, Claussen Walther; Aguilar-Hengstenberg, Miguel Angel; Holliger, Klaus

    2012-01-01

    The Polochic-Motagua fault system is part of the sinistral transform boundary between the North American and Caribbean plates in Guatemala and the associated seismic activity poses a threat to ∼70% of the country's population. The aim of this study is to constrain the Late Quaternary activity of the Polochic fault by determining the active structure geometry and quantifying recent displacement rates as well as paleo-seismic events. Slip rates have been estimated from offsets of Quaternary vol...

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

    Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas

    2011-01-01

    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 in...... the estimation of the corresponding parameter. The fault detection and isolation is done by comparing the nominal parameters with those estimated by Extended Kalman Filter (EKF). In study, Gaussian noise is used as the input disturbance as well as the measurement noise for simulation. The method is...

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

    Mingping Xia

    2013-01-01

    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 f...

  2. Stator Interturn Fault Detection in Permanent-Magnet Machines Using PWM Ripple Current Measurement

    Sen, B.; Wang, J.

    2016-01-01

    This paper proposes a novel method of interturn fault detection based on measurement of pulsewidth modulation (PWM) ripple current. The method uses the ripple current generated by the switching inverter as a means to detect interturn fault. High-frequency (HF) impedance behavior of healthy and faulted windings is analyzed and modeled, and ripple current signature due to interturn faults is quantified. A simple analog circuit is designed to extract the PWM ripple current via a bandpass (BP) fi...

  3. Adapting plant measurement data to improve hardware fault detection performance in pressurised water reactors

    Cilliers, Anthonie Christoffel; Mulder, Eben Johan

    2012-01-01

    With the fairly recent adoption of digital control and instrumentation systems in the nuclear industry a lot of research now focus on the development expert fault identification systems. The fault identification systems enable detecting early onset faults of fault causes which allows maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. Dete...

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

    Runxia Guo

    2016-01-01

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

  5. Fault-Tolerant Control using Adaptive Time-Frequency Method in Bearing Fault Detection for DFIG Wind Energy System

    Suratsavadee Koonlaboon KORKUA

    2015-02-01

    Full Text Available With the advances in power electronic technology, doubly-fed induction generators (DFIG have increasingly drawn the interest of the wind turbine industry. To ensure the reliable operation and power quality of wind power systems, the fault-tolerant control for DFIG is studied in this paper. The fault-tolerant controller is designed to maintain an acceptable level of performance during bearing fault conditions. Based on measured motor current data, an adaptive statistical time-frequency method is then used to detect the fault occurrence in the system; the controller then compensates for faulty conditions. The feature vectors, including frequency components located in the neighborhood of the characteristic fault frequencies, are first extracted and then used to estimate the next sampling stator side current, in order to better perform the current control. Early fault detection, isolation and successful reconfiguration would be very beneficial in a wind energy conversion system. The feasibility of this fault-tolerant controller has been proven by means of mathematical modeling and digital simulation based on Matlab/Simulink. The simulation results of the generator output show the effectiveness of the proposed fault-tolerant controller.

  6. Monitoring and diagnosis for sensor fault detection using GMDH methodology

    The fault detection and diagnosis system is an Operator Support System dedicated to specific functions that alerts operators to sensors and actuators fault problems, and guide them in the diagnosis before the normal alarm limits are reached. Operator Support Systems appears to reduce panels complexity caused by the increase of the available information in nuclear power plants control room. In this work a Monitoring and Diagnosis System was developed based on the GMDH (Group Method of Data Handling) methodology. The methodology was applied to the IPEN research reactor IEA-R1. The system performs the monitoring, comparing GMDH model calculated values with measured values. The methodology developed was firstly applied in theoretical models: a heat exchanger model and an IPEN reactor theoretical model. The results obtained with theoretical models gave a base to methodology application to the actual reactor operation data. Three GMDH models were developed for actual operation data monitoring: the first one using just the thermal process variables, the second one was developed considering also some nuclear variables, and the third GMDH model considered all the reactor variables. The three models presented excellent results, showing the methodology utilization viability in monitoring the operation data. The comparison between the three developed models results also shows the methodology capacity to choose by itself the best set of input variables for the model optimization. For the system diagnosis implementation, faults were simulated in the actual temperature variable values by adding a step change. The fault values correspond to a typical temperature descalibration and the result of monitoring faulty data was then used to build a simple diagnosis system based on fuzzy logic. (author)

  7. Evidence against Late Quaternary activity along the Northern Karakoram Fault

    Robinson, A. C.; Owen, L. A.; Hedrick, K.; Blisniuk, K.; Sharp, W. D.; Chen, J.; Schoenbohm, L. M.; Imrecke, D. B.; Yuan, Z.; Li, W.

    2012-12-01

    Although the entire 1000 km long Karakoram fault has long been interpreted to be active, recent work based primarily on interpretation of satellite imagery suggests that the northern end of the fault, where it enters the Pamir mountains, is inactive. We present field observations and geochronologic data from the southern end of the Tashkurgan valley, in the Pamir, on the Karakoram fault where it splits into two identifiable strands; an eastern strand which is the main trace of the Karakoram fault, and a western strand called the Achiehkopai fault. These results support the interpretation that the northern Karakoram fault is currently inactive, and has been for at least 200 ka: 1) Near the village of Dabudaer in the southern Tashkurgan valley the main trace of the Karakoram fault is orthogonally cut by a narrow incised valley with no observed lateral offset across the fault. Within this valley, a strath terrace ~50 m above the active drainage which overlies the main trace of the Karakoram fault which is capped by a carbonate cemented conglomerate. U-series analyses of carbonate cement from a correlative deposit located several km away yields a minimum depositional age of 76±12 ka. This age is coeval with the local Tashkurgan glacial stage we dated using Be-10 surface exposure dating (66±10 ka; Owen et al., 2012, Quaternary Science Reviews) suggesting both the conglomerate and strath terrace formed during this glacial stage. 2) ~25 km south of Dabudar, the main trace of the Karakoram projects beneath Tashkurgan glacial stage moraine and fluvial-glacial deposits which similarly show no evidence of disturbance by strike-slip deformation. Both of the above results demonstrate the main trace of the Karakoram fault has been inactive since at least ~70 ka. 3) Both the Karakoram and Achiehkopai faults are overlain by older Dabudaer glacial stage moraine deposits which are interpreted to be at least as old as the penultimate glacial, but may be >200 ka based on our Be-10

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

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

    2014-01-01

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

  9. Fault or frac? Source mechanism and B-value detection of fault fracturing - A Barnett case study

    De La Pena, A.; Wessels, S.A.; Gunnell, A.R.; Numa, K.J.; Williams-Stroud, S.; Eisner, Leo; Thornton, M.; Mueller, M.

    New York: Curran Associates, 2011, s. 545-549. ISBN 978-1-61782-966-6. [European Association of Geoscientists and Engineers Conference and Exhibition 2011 /73./ - Incorporating SPE EUROPEC 2011. Vienna (AT), 23.05.2011-26.05.2011] Institutional research plan: CEZ:AV0Z30460519 Keywords : B value * fault activity * fault event Subject RIV: DC - Siesmology, Volcanology, Earth Structure

  10. Distributed Fault-Tolerant Event Region Detection of Wireless Sensor Networks

    Dyi-Rong Duh; Ssu-Pei Li; Victor W. Cheng

    2013-01-01

    This work provides a distributed fault-tolerant event region detection algorithm for wireless sensor networks. The proposed algorithm can identify faulty and fault-free sensors and ignore the abnormal readings to avoid false alarm. Moreover, every event region can also be detected and identified. Simulation results show that fault detection accuracy (FDA) is greater than 92%, false alarm rate (FAR) is near 0%, and event detection accuracy (EDA) is greater than 99% under uniform distribution. ...

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

    Amooee, Golriz; Bagheri-Dehnavi, Malihe

    2012-01-01

    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...

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

    L.L. Siame

    2006-12-01

    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.

  13. FAULT DETECTION IN SWITCHED RELUCTANCE MOTOR DRIVES USING DISCRETE WAVELET TRANSFORM AND K-MEANS CLUSTERING

    V. S. Chandrika

    2014-01-01

    Full Text Available This study presents a novel method of detection of inter turn shorts based on k means clustering technique. In addition to inter turn short detection, the other faults like open, short, phase to phase faults and DC volt-age faults are detected through wavelet transforms and k means clustering. Open and short faults are classified using artificial neural network. All other faults are classified using Support Vector Machines (SVM. Switched reluctance motors are very popular in these days, because of ease in manufacturing and operation. Though an electronic circuit can detect the faults like open and short, the classification cannot be done effectively with electronic circuitry. More over an intelligent method can easily identify the fault and classify and hence the root cause of the fault may be guessed and rectified using this method of classification. This is highly possible with the time localization property of the wavelet transforms. So instant of fault occurrence can be detected along with the type of fault. The information used to include this intelligence in the system are just current waveforms, flux waveforms and torque waveforms. Inter turn shorts are very critical for a long run operation of the motor. Moreover, the early detection minimizes the faulty operation time and ensures the plant stability and saves the life of motor too. Hence an integrated system to detect the major faults under a simulation model has been proposed in this study.

  14. 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.

    2013-12-01

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

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

    2007-01-01

    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.

  16. Improvement of Matrix Converter Drive Reliability by Online Fault Detection and a Fault-Tolerant Switching Strategy

    Nguyen-Duy, Khiem; Liu, Tian-Hua; Chen, Der-Fa

    2011-01-01

    The matrix converter system is becoming a very promising candidate to replace the conventional two-stage ac/dc/ac converter, but system reliability remains an open issue. The most common reliability problem is that a bidirectional switch has an open-switch fault during operation. In this paper, a...... matrix converter driving a speed-controlled permanent-magnet synchronous motor is examined under a single open-switch fault. First, a new fault-detection method is proposed using only the motor currents. Second, a novel fault-tolerant switching strategy is presented. By treating the matrix converter as a...... two-stage rectifier/inverter, existing modulation techniques for the inverter stage can be reused, whereas the rectifier stage is modified by control to counteract the fault. However, the proposed techniques require no additional hardware devices or circuit modifications to the matrix converter...

  17. Important factors affecting fault detection coverage in probabilistic safety assessment of digital instrumentation and control systems

    As digital instrumentation and control (I and C) systems are gradually introduced into nuclear power plants (NPPs), concerns about the I and C systems’ reliability and safety are growing. Fault detection coverage is one of the most critical factors in the probabilistic safety assessment (PSA) of digital I and C systems. To correctly estimate the fault detection coverage, it is first necessary to identify important factors affecting it. From experimental results found in the literature and the authors’ experience in fault injection experiments on digital systems, four system-related factors and four fault-related factors are identified as important factors affecting the fault detection coverage. A fault injection experiment is performed to demonstrate the dependency of fault detection coverage on some of the identified important factors. The implications of the experimental results on the estimation of fault detection coverage for the PSA of digital I and C systems are also explained. The set of four system-related factors and four fault-related factors is expected to provide a framework for systematically comparing and analyzing various fault injection experiments and the resultant estimations on fault detection coverage of digital I and C systems in NPPs. (author)

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

    Nakahara, Nobuo

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

  19. The ground-fault detection system for DIII-D

    This paper presents a discussion of the ground-fault detecting systems on the DIII-D tokamak. The subsystems that must be monitored for an inadvertent ground include the toroidal and poloidal coil systems, the vacuum vessel, and the coil support structures. In general, one point of each coil is tied to coil/power supply ground through a current limiting resistor. For ground protection the current through this resistor is monitored using a dynamically feedback balanced Hall probe transducer from LEM Industries. When large inductive currents flow in closed loops near the the tokamak, the result is undesirable magnetic error fields in the plasma region and noise generation on signal cables. Therefore, attention must be paid to avoid closed loops in the design of the coil and vessel support structure. For DIII-D a concept of dual insulating breaks and a single-point ground for all structure elements was used to satisfy this requirement. The integrity of the support structure is monitored by a system which continuously attempts to couple a variable frequency waveform onto these single-point grounds. The presence of an additional ground completes the circuit resulting in current flow. A Rogowski coil is then used to track the unwanted ground path in order to eliminate it. Details of the ground fault detection circuitry, and a description of its operation will be presented

  20. The ground-fault detection system for DIII-D

    This paper presents a discussion of the ground-fault detection systems on the DIII-D tokamak. The subsystems that must be monitored for an inadvertent ground include the toroidal and poloidal coil systems, the vacuum vessel, and the coil support structures. In general, one point of each coil is tied to coil/power supply ground through a current limiting resistor. For ground protection the current through this resistor is monitored using a dynamically feedback balanced Hall probe transducer from LEM Industries. When large inductive currents flow in closed loops near the tokamak, the result is undesirable magnetic error fields in the plasma region and noise generation on signal cables. Therefore, attention must be paid to avoid closed loops in the design of the coil and vessel support structure. For DIII-D a concept of dual insulating breaks and a single-point ground for all structure elements was used to satisfy this requirement. The integrity of the support structure is monitored by a system which continuously attempts to couple a variable frequency waveform onto these single-point grounds. The presence of an additional ground completes the circuit resulting in current flow. A Rogowski coil is then used to track the unwanted ground path in order to eliminate it. Details of the ground fault detection circuitry, and a description of its operation will be presented. 2 refs., 7 figs

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

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

    2011-01-01

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

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

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

    2015-09-01

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

  3. An application of decentralized estimation in a fault detection problem

    Tadić Predrag R.

    2009-01-01

    Full Text Available This paper presents a design of a decentralized fault detection and isolation (FDI filter by means of an overlapping decentralized estimation algorithm based on a consensus strategy. An efficient solution to the FDI problem can be obtained by an adequate system decomposition into overlapping subsystems and the construction of local FDI estimators aimed at achieving the desired performance. The general aspects and properties of a consensus based estimator are described in the first part of the paper. An applicability of such an estimator to an FDI problem in a large scale system is discussed next. Namely, a case study related to the detection of fire dissymmetry in a thermal power plant boiler is presented, including the process description and identification procedure, comparison between the results obtained by local and decentralized estimators and conclusions concerning their validity.

  4. Active Fault Tolerant Control of Livestock Stable Ventilation System

    Gholami, Mehdi

    2011-01-01

    of the hybrid model are estimated by a recursive estimation algorithm, the Extended Kalman Filter (EKF), using experimental data which was provided by an equipped laboratory. Two methods for active fault diagnosis are proposed. The AFD methods excite the system by injecting a so-called excitation...... degraded performance even in the faulty case. In this thesis, we have designed such controllers for climate control systems for livestock buildings in three steps: Deriving a model for the climate control system of a pig-stable. Designing a active fault diagnosis (AFD) algorithm for different kinds of...... fault. Designing a fault tolerant control scheme for the climate control system. In the first step, a conceptual multi-zone model for climate control of a live-stock building is derived. The model is a nonlinear hybrid model. Hybrid systems contain both discrete and continuous components. The parameters...

  5. Detecting tangential dislocations on planar faults from traction free surface observations

    We propose in this paper robust reconstruction methods for tangential dislocations on planar faults. We assume that only surface observations are available, and that a traction free condition applies at that surface. This study is an extension to the full three dimensions of Ionescu and Volkov (2006 Inverse Problems 22 2103). We also explore in this present paper the possibility of detecting slow slip events (such as silent earthquakes, or earthquake nucleation phases) from GPS observations. Our study uses extensively an asymptotic estimate for the observed surface displacement. This estimate is first used to derive what we call the moments reconstruction method. Then it is also used for finding necessary conditions for a surface displacement field to have been caused by a slip on a fault. These conditions lead to the introduction of two parameters: the activation factor and the confidence index. They can be computed from the surface observations in a robust fashion. They indicate whether a measured displacement field is due to an active fault. We also infer a second, combined, reconstruction technique blending least square minimization and the moments method. We carefully assess how our reconstruction method is affected by the sensitivity of the observation apparatus and the stepsize for the grid of surface observation points. The maximum permissible stepsize for such a grid is computed for different values of fault depth and orientation. Finally we present numerical examples of reconstruction of faults. We demonstrate that our combined method is sharp, robust and computationally inexpensive. We also note that this method performs satisfactorily for shallow faults, despite the fact that our asymptotic formula deteriorates in that case

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

    N. Talebi; M.A. Sadrnia; A. Darabi

    2014-01-01

    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 appropr...

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

    Yang, Kai; Zhang, Rencheng; Yang, Jianhong; Liu, Canhua; Chen, Shouhong; Zhang, Fujiang

    2016-01-01

    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. PMID:27070618

  8. Quaternary seismo-tectonic activity of the Polochic Fault, Guatemala

    Authemayou, Christine; Brocard, Gilles; Teyssier, Christian; Suski, Barbara; Cosenza, Beatriz; MoráN-Ical, Sergio; GonzáLez-VéLiz, Claussen Walther; Aguilar-Hengstenberg, Miguel Angel; Holliger, Klaus

    2012-07-01

    The Polochic-Motagua fault system is part of the sinistral transform boundary between the North American and Caribbean plates in Guatemala and the associated seismic activity poses a threat to ˜70% of the country's population. The aim of this study is to constrain the Late Quaternary activity of the Polochic fault by determining the active structure geometry and quantifying recent displacement rates as well as paleo-seismic events. Slip rates have been estimated from offsets of Quaternary volcanic markers and alluvial fan using in situ cosmogenic 36Cl exposure dating. Holocene left-lateral slip rate and Mid-Pleistocene vertical slip rate have been estimated to 4.8 ± 2.3 mm/y and 0.3 ± 0.06 mm/y, respectively, on the central part of the Polochic fault. The horizontal slip rate is within the range of longer-term geological slip rates and short-term GPS-based estimates. In addition, the non-negligible vertical motion participates in the uplift of the block north of the fault and seems to be a manifestation of the regional, far-field stress regime. We excavated the first trench for paleo-seismological study on the Polochic fault in which we distinguish four large paleo-seismic events since 17 ky during which the Polochic fault ruptured the ground surface.

  9. Fault detection of planetary gearboxes using new diagnostic parameters

    Planetary gearboxes are commonly used in modern industry because of their large transmission ratio and strong load-bearing capacity. They generally work under heavy load and tough working environment and therefore their key components including sun gear, planet gears, ring gear, etc are subject to severe pitting and fatigue crack. Planetary gearboxes significantly differ from fixed-axis gearboxes and exhibit unique behavior, which invalidates the use of the diagnostic parameters developed and suitable for fixed-axis gearboxes. Therefore, there is a need to develop parameters specifically for detecting and diagnosing faults of planetary gearboxes. In this study, two diagnostic parameters are proposed based on the examination of the vibration characteristics of planetary gearboxes in both time and frequency domains. One is the root mean square of the filtered signal (FRMS) and the other is the normalized summation of positive amplitudes of the difference spectrum between the unknown signal and the healthy signal (NSDS). To test the proposed diagnostic parameters, we conducted experiments on a planetary gearbox test rig with sun gear faults including a cracked tooth and a pitted tooth. The vibration signals were measured under different motor speeds. The proposed parameters are compared with the existing parameters reported in the literature. The comparison results show the proposed diagnostic parameters perform better than others. (paper)

  10. 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...

  11. Connecting the Yakima fold and thrust belt to active faults in the Puget Lowland, Washington

    Blakely, Richard J.; Sherrod, Brian L.; Weaver, Craig S.; Wells, Ray E.; Rohay, Alan C.; Barnett, Elizabeth A.; Knepprath, Nichole E.

    2011-07-01

    High-resolution aeromagnetic surveys of the Cascade Range and Yakima fold and thrust belt (YFTB), Washington, provide insights on tectonic connections between forearc and back-arc regions of the Cascadia convergent margin. Magnetic surveys were measured at a nominal altitude of 250 m above terrain and along flight lines spaced 400 m apart. Upper crustal rocks in this region have diverse magnetic properties, ranging from highly magnetic rocks of the Miocene Columbia River Basalt Group to weakly magnetic sedimentary rocks of various ages. These distinctive magnetic properties permit mapping of important faults and folds from exposures to covered areas. Magnetic lineaments correspond with mapped Quaternary faults and with scarps identified in lidar (light detection and ranging) topographic data and aerial photography. A two-dimensional model of the northwest striking Umtanum Ridge fault zone, based on magnetic and gravity data and constrained by geologic mapping and three deep wells, suggests that thrust faults extend through the Tertiary section and into underlying pre-Tertiary basement. Excavation of two trenches across a prominent scarp at the base of Umtanum Ridge uncovered evidence for bending moment faulting possibly caused by a blind thrust. Using aeromagnetic, gravity, and paleoseismic evidence, we postulate possible tectonic connections between the YFTB in eastern Washington and active faults of the Puget Lowland. We suggest that faults and folds of Umtanum Ridge extend northwestward through the Cascade Range and merge with the Southern Whidbey Island and Seattle faults near Snoqualmie Pass 35 km east of Seattle. Recent earthquakes (MW ≤ 5.3) suggest that this confluence of faults may be seismically active today.

  12. SIMD-Swift: Improving Performance of Swift Fault Detection

    Oleksenko, Oleksii

    2016-01-01

    The general tendency in modern hardware is an increase in fault rates, which is caused by the decreased operation voltages and feature sizes. Previously, the issue of hardware faults was mainly approached only in high-availability enterprise servers and in safety-critical applications, such as transport or aerospace domains. These fields generally have very tight requirements, but also higher budgets. However, as fault rates are increasing, fault tolerance solutions are starting to be also re...

  13. The Lake Edgar Fault: an active fault in Southwestern Tasmania, Australia, with repeated displacement in the Quaternary

    Jensen, V; Gibson, G; R. Van Dissen; McCue, K.; Boreham, B.

    2003-01-01

    The Lake Edgar Fault in Western Tasmania, Australia is marked by a prominent fault scarp and is a recently reactivated fault initially of Cambrian age. The scarp has a northerly trend and passes through the western abutment of the Edgar Dam, a saddle dam on Lake Pedder. The active fault segment displaces geologically young river and glacial deposits. It is 29 ± 4 km long, and dips to the west. Movement on the fault has ruptured the ground surface at least twice within the ...

  14. Benchmarking an expert fault detection and diagnostic system on the Three Mile Island accident event sequence

    Highlights: • Attempt was to use available resources at a nuclear plant in a value added fashion. • Includes plant measurement data and plant training and engineering simulator capabilities. • Correlating fault detection data for systems to develop of a deterministic fault identifications system. • After implementing a host of data manipulation algorithms, the results provided more information on the fault than expected. • TMI benchmark results in value added to the operator and system. - Abstract: Early fault identification systems enable detecting and diagnosing early onset faults or fault causes which allow maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. We have shown (Cilliers and Mulder, 2012) that detecting faults early during transient operation in NPPs is possible when coupled with a reliable reference to compare plant measurements with during transients. We have also shown (Cilliers, 2013) that by correlating the fault detection information as received from distributed systems it is possible to diagnose the faults in terms of location and magnitude. This paper makes use of the techniques and processes developed in the previous papers and apply it to a case study of the Three Mile Island accident. In this way we can determine how the improved information available could present the operator with a better idea to the state of the plant during situations where a combination of faults and transients prevents the operator and conventional systems to recognise the abnormal behaviour

  15. Model-based fault detection and isolation of a PWR nuclear power plant using neural networks

    The proper and timely fault detection and isolation of industrial plant is of premier importance to guarantee the safe and reliable operation of industrial plants. The paper presents application of a neural networks-based scheme for fault detection and isolation, for the pressurizer of a PWR nuclear power plant. The scheme is constituted by 2 components: residual generation and fault isolation. The first component generates residuals via the discrepancy between measurements coming from the plant and a nominal model. The neutral network estimator is trained with healthy data collected from a full-scale simulator. For the second component detection thresholds are used to encode the residuals as bipolar vectors which represent fault patterns. These patterns are stored in an associative memory based on a recurrent neutral network. The proposed fault diagnosis tool is evaluated on-line via a full-scale simulator detected and isolate the main faults appearing in the pressurizer of a PWR. (orig.)

  16. Design of a bilinear fault detection observer for singular bilinear systems

    Zhanshan WANG; Huaguang ZHANG

    2007-01-01

    A bilinear fault detection observer is proposed for a class of continuous time singular bilinear systems subject to unknown input disturbance and fault.By singular value decomposition on the original system,a bilinear fault detection observer is proposed for the decomposed system via an algebraic Riccati equation,and the domain of attraction of the state estimation error is estimated.A design procedure is presented to determine the fault detection threshold.A model of flexible joint robot is used to demonstrate the effectiveness of the proposed method.

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

    METATLA, A.

    2011-02-01

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

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

    METATLA, A.; BENZAHIOUL, S.; BAHI, T.; Lefebvre, D.

    2011-01-01

    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 induct...

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

    Hongli Dong

    2014-01-01

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

  20. Active tectonics west of New Zealand's Alpine Fault: South Westland Fault Zone activity shows Australian Plate instability

    De Pascale, Gregory P.; Chandler-Yates, Nicholas; Dela Pena, Federico; Wilson, Pam; May, Elijah; Twiss, Amber; Cheng, Che

    2016-04-01

    The 300 km long South Westland Fault Zone (SWFZ) is within the footwall of the Central Alpine Fault (<20 km away) and has 3500 m of dip-slip displacement, but it has been unknown if the fault is active. Here the first evidence for SWFZ thrust faulting in the "stable" Australian Plate is shown with cumulative dip-slip displacements up to 5.9 m (with 3 m throw) on Pleistocene and Holocene sediments and gentle hanging wall anticlinal folding. Cone penetration test (CPT) stratigraphy shows repeated sequences within the fault scarp (consistent with thrusting). Optically stimulated luminescence (OSL) dating constrains the most recent rupture post-12.1 ± 1.7 ka with evidence for three to four events during earthquakes of at least Mw 6.8. This study shows significant deformation is accommodated on poorly characterized Australian Plate structures northwest of the Alpine Fault and demonstrates that major active and seismogenic structures remain uncharacterized in densely forested regions on Earth.

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

    G.Satyanarayana,

    2015-08-01

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

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

    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

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

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

    2015-05-15

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

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

    Herp, Jürgen; S. Nadimi, Esmaeil

    2015-01-01

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

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

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

    2013-01-01

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

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

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

    2016-01-01

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

  7. Identification of active faults in Abruzzo area (central Italy) through the analysis of geological, seismological and gravimetric data

    Luiso, Paola; Paoletti, Valeria; Gaudiosi, Germana; Nappi, Rosa; Cella, Federico; Fedi, Maurizio

    2016-04-01

    Identification of active faults in abruzzo area (central italy) through the analysis of geological, seismological and gravimetric data The aim of this study is to identify and constrain the geometry of the seismogenic structures (active, outcropping and buried fault systems) of the Abruzzo area (central Italy), through an integrated analysis of geo-structural, seismic and gravimetric data. We generated three thematic: "faults", "earthquakes" and "gravimetric" data: i) The fault dataset consists of data extracted from the available structural and geological maps (ITHACA catalogue; the "Neotectonic Map of Italy" 1:500.000; several geological sheets 1:50.000 from ISPRA CARG project; the Geological Map 1:100.000 Sheet 1), and many geological studies. ii) The earthquakes datasets was created by merging the data from historical and instrumental Catalogues (CPTI04 and CPTI11; ISIDE - INGV). iii) The gravimetric datasets consists in the Multiscale Derivative Analysis (MDA) of the Bouguer anomaly map of the area, whose maxima show the presence of density lineaments. The merge of these datasets in GIS environment, highlighted four possible scenarios of correlation between faults, earthquakes and MDA maxima: 1) the existence of active faults, revealed by a strong correlation between epicentral location of seismic clusters, fault positions and MDA maxima; 2) the existence of buried active faults, highlighted by a good correlation between MDA maxima and epicentral positions, without correspondence with faults known from geological data; 3) the existence of inactive or silent faults, detected by the presence of faults reported in the geological datasets and literature which are associated with MDA maxima, without correlation of earthquakes; 4) the existence of faults not correlated with MDA maxima; this could be due to faults putting in contact two lithologies with a similar density. A comparison between seismic hypocentral locations and the fault geometry retrieved by DEXP

  8. Abnormal fault-recovery characteristics of the fault-tolerant multiprocessor uncovered using a new fault-injection methodology

    Padilla, Peter A.

    1991-03-01

    An investigation was made in AIRLAB of the fault handling performance of the Fault Tolerant MultiProcessor (FTMP). Fault handling errors detected during fault injection experiments were characterized. In these fault injection experiments, the FTMP disabled a working unit instead of the faulted unit once in every 500 faults, on the average. System design weaknesses allow active faults to exercise a part of the fault management software that handles Byzantine or lying faults. Byzantine faults behave such that the faulted unit points to a working unit as the source of errors. The design's problems involve: (1) the design and interface between the simplex error detection hardware and the error processing software, (2) the functional capabilities of the FTMP system bus, and (3) the communication requirements of a multiprocessor architecture. These weak areas in the FTMP's design increase the probability that, for any hardware fault, a good line replacement unit (LRU) is mistakenly disabled by the fault management software.

  9. Experimental studies on intelligent fault detection and diagnosis using sensor networks on mechanical pneumatic systems

    Zhang, Kunbo; Kao, Imin; Kambli, Sachin; Boehm, Christian

    2008-03-01

    Fault is a undesirable factor in any mechanical/pneumatic system. It affects the efficiency of system operation and reduces economic benefit in industry. The early detection and diagnosis of faults in a mechanical system becomes important for preventing failure of equipment and loss of productivity and profits. In this paper, we present our ongoing research results on intelligent fault detections and diagnosis (FDD) on mechanical/ pneumatic systems. Using data from sensors and sensor network in an integrated industrial system, our proposed FDD methodology provides the analysis of necessary sensory information (for example, flow rates and pressure, as well as other digital sensor data) for the detection and diagnosis of system fault. In this experimental study, the leakage of pneumatic cylinder was the "fault." It was shown that the FDD analysis was able to make diagnosis of leakage both in location and size of the fault. In addition, the systematic fault and localized faults can be detected separately. The proposed wavelet method gives rise to the fingerprint analysis to recognize the patterns of the flow rate and pressure data - a very useful tool in intelligent fault detection and diagnosis.

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

    N. Talebi

    2014-07-01

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

  11. Numerical simulation of fractal interface effect of mining-caused activation of fault

    Xie Heping; Zhao Jianfeng; Yu Guangming

    2002-01-01

    Mining-caused activation of fault is an important research subject in mining science. In the past, the influences of geometrical morphology of fault surface on the activation have not been revealed. In view of the fractal character of fault surface, the self-affine fractal curves and geological-mining models with these kinds of fractal fault surface are constructed in order to numerically simulate the mining-caused activation phenomenon of fractal fault surface, and the law of influence of fr...

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

    Punčochár Ivo

    2014-12-01

    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.

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

    Wang, Bright L.

    2011-01-01

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

  14. POD Model Reconstruction for Gray-Box Fault Detection

    Park, Han; Zak, Michail

    2007-01-01

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

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

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

  16. Fault Detection on the Software Implementation of CLEFIA Lightweight Cipher

    Wei Li; Dawu Gu; Xiaoling Xia; Ya Liu; Zhiqiang Liu

    2012-01-01

    CLEFIA is an efficient lightweight cipher that delivers advanced copyright protection and authentication in computer networks. It is also applied in the secure protocol for transmission including SSL and TLS. Since it was proposed in 2007, some work about its security against differential fault analysis has been devoted to reducing the number of faults and to improving the time complexity of this attack. This attack is very efficient when a single fault is injected into the last several round...

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

    Diaz Ledezma, F.

    2015-07-01

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

  18. From experiment to design -- Fault characterization and detection in parallel computer systems using computational accelerators

    Yim, Keun Soo

    This dissertation summarizes experimental validation and co-design studies conducted to optimize the fault detection capabilities and overheads in hybrid computer systems (e.g., using CPUs and Graphics Processing Units, or GPUs), and consequently to improve the scalability of parallel computer systems using computational accelerators. The experimental validation studies were conducted to help us understand the failure characteristics of CPU-GPU hybrid computer systems under various types of hardware faults. The main characterization targets were faults that are difficult to detect and/or recover from, e.g., faults that cause long latency failures (Ch. 3), faults in dynamically allocated resources (Ch. 4), faults in GPUs (Ch. 5), faults in MPI programs (Ch. 6), and microarchitecture-level faults with specific timing features (Ch. 7). The co-design studies were based on the characterization results. One of the co-designed systems has a set of source-to-source translators that customize and strategically place error detectors in the source code of target GPU programs (Ch. 5). Another co-designed system uses an extension card to learn the normal behavioral and semantic execution patterns of message-passing processes executing on CPUs, and to detect abnormal behaviors of those parallel processes (Ch. 6). The third co-designed system is a co-processor that has a set of new instructions in order to support software-implemented fault detection techniques (Ch. 7). The work described in this dissertation gains more importance because heterogeneous processors have become an essential component of state-of-the-art supercomputers. GPUs were used in three of the five fastest supercomputers that were operating in 2011. Our work included comprehensive fault characterization studies in CPU-GPU hybrid computers. In CPUs, we monitored the target systems for a long period of time after injecting faults (a temporally comprehensive experiment), and injected faults into various types of

  19. High Frequency Monitoring of the Aigion Fault Activity

    Cornet, Francois; Bourouis, Seid

    2013-04-01

    In 2007, a high frequency monitoring system was deployed in the 1000 m deep AIG10 well that intersects the Aigion fault at a depth of 760 m. This active 15 km long fault is located on the south shore of the Corinth rift, some 40 km east from Patras, in western central Greece. The borehole intersects quaternary sediments down to 495 m, then cretaceous and tertiary heavily tectonized deposits from the Pindos nappe. Below the fault encountered at 760 m, the borehole remains within karstic limestone of the Gavrovo Tripolitza nappe. The monitoring system involved two geophones located some 15 m above the fault, and two hydrophones located respectively at depths equal to 500 m and 250 m. The frequency domain for the data acquisition system ranged from a few Hz to 2500 Hz. The seismic velocity structure close to the borehole was determined through both sonic logs and vertical seismic profiles. This monitoring system has been active during slightly over six months and has recorded signals from microseismic events that occurred in the rift, the location of which was determined thanks to the local 11 stations, three components, short period (2 Hz), monitoring system. In addition, the borehole monitoring system has recorded more than 1000 events not identified with the regional network. Events were precisely correlated with pressure variations associated with two human interventions. These extremely low magnitude events occurred at distances that reached at least up to 1500 m from the well. They were associated, some ten days later, with some local rift activity. A tentative model is proposed that associates local short slip instabilities in the upper part of the fault close to the well, with a longer duration pore pressure diffusion process. Results demonstrate that the Aigion fault is continuously creeping down to a depth at least equal to 5 km but probably deeper.

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

    Mehdi Shadaram

    2010-10-01

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

  1. Active Fault Diagnosis in Sampled-data Systems

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2015-01-01

    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...

  2. Observer and data-driven model based fault detection in Power Plant Coal Mills

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

    2008-01-01

    This paper presents and compares model-based and data-driven fault detection approaches for coal mill systems. The first approach detects faults with an optimal unknown input observer developed from a simplified energy balance model. Due to the time-consuming effort in developing a first principles...... model with motor power as the controlled variable, data-driven methods for fault detection are also investigated. Regression models that represent normal operating conditions (NOCs) are developed with both static and dynamic principal component analysis and partial least squares methods. The residual...... between process measurement and the NOC model prediction is used for fault detection. A hybrid approach, where a data-driven model is employed to derive an optimal unknown input observer, is also implemented. The three methods are evaluated with case studies on coal mill data, which includes a fault...

  3. A novel method for high-performance fault detection of induction machine

    Su, Hua; Kim, Yeong-Min; Chong, Kil To

    2005-12-01

    Induction machine is probably the most commonly utilized electromechanical device in modern society. However, there are many undesirable problems arising in the machine operation of industrial plants. It is desirable for early detection and diagnosis of incipient faults for online condition monitoring, product quality assurance, and improved operational efficiency of induction motors. In this paper, a high-performance residual-based novel method is developed for induction machine fault detection, using Fourier-based signal processing for steady-state vibration signals. The proposed approach uses only motor vibration measurements without the nameplate information. The reference model in spectra is obtained statistically to represent the healthy condition. The effectiveness of the proposed approach in detecting a wide range of mechanical and electrical faults is demonstrated through staged motor faults, and it is shown that a robust and reliable induction machine fault detection system has been produced.

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

    Silvia M. Zanoli

    2013-01-01

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

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

    Yong JIANG; Hongguang WANG; Lijin FANG; Mingyang ZHAO

    2009-01-01

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

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

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

  7. Process fault detection and non-linear time series analysis for anomaly detection in safeguards

    The paper discusses process fault detection and non-linear time series analysis, which are applied to the analysis for vector-valued and single-valued time series data. Model based process fault detection methods for analysing simulated, multivariate, time series data from a three-tank system are investigated. The model predictions are compared with simulated measurements of the same variables to form residual vectors that are tested for the presence of faults (possible diversions in safeguards terminology). Two methods are evaluated, testing all individual residuals with a univariate z score and testing all variables simultaneously with the Mahalanobis distance, for their ability to detect loss of material from two different leak scenarios from the three-tank system: a leak without replacement and a leak with replacement of the lost volume. Non-linear time series analysis tools have been compared with the linear methods popularized by Box and Jenkins. The paper compares prediction results using three non-linear and two linear modelling methods on each of six simulated time series: two non-linear and four linear time series. The non-linear methods performed better at predicting the non-linear time series and did as well as the linear methods at predicting the linear values. (author). 10 refs, 5 figs, 1 tab

  8. Study and Design of Diaphragm Pump Vibration Detection Fault Diagnosis System Based on FFT

    Jia Yin; Jiande Wu; Xuyi Yuan; Xiaodong Wang; Yugang Fan

    2013-01-01

    This study has proposed a fault diagnosis system based on vibration detection. The system mainly includes four modules: signal acquisition module, signal processing module, state identification module, fault diagnosis and alarm module. The system uses CMSS 2200 acceleration sensor to collect vibration signals, processing spectrum with FFT (Fast Fourier Transform) which is used effectively in current industry and finally achieve fault diagnosis and prediction for diaphragm pump. Through collec...

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

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

    2012-01-01

    Induction motors fed through variable speed drives (VSD) are widely used in different industrial processes. Nowadays, the industry demands the integration of smart sensors to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can be produce severe damages. The combined fault identification in induction motors is a demanding task, but it has been rarely considered in spite of being a comm...

  10. A fault detection and isolation scheme for industrial systems based on multiple operating models

    Rodrigues, Mickael; THEILLIOL, DIDIER; Adam Medina, Manuel; Sauter, Dominique

    2008-01-01

    In this paper, a fault diagnosis method is developed for systems described by multi- models. The main contribution consists in the design of a new Fault Detection and Isolation scheme (FDI) through an adaptive filter for such systems. Based on the assumption that dynamic behavior of the process is described by a multi-model approach around different operating points, a set of residual is established in order to generate weighting functions robust to faults. These robust weighting functions ar...

  11. Three Phase Induction Motor Faults Detection by Using Radial Basis Function Neural Network

    Abd Alla, Ahmed N.

    2006-01-01

    In the present study the Artificial Neural Network (ANN) technique for the detection of (bearing and stator inter turn faults) incipient faults in an induction motor bas been explored. Radial basis function approach has been used for ANN Training and test. Three phase instantaneous currents and angular velocity depending on rotor speed are utilized in proposed approach. An experimental setup is used to implement an online fault defector

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

    Grauer, Jared A.

    2016-01-01

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

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

    Borchersen, Anders Bech; Kinnaert, Michel

    2016-01-01

    In this work, an early fault detection system for the generator cooling of wind turbines is presented and tested. It relies on a hybrid model of the cooling system. The parameters of the generator model are estimated by an extended Kalman filter. The estimated parameters are then processed by an...... appropriate statistical change detection algorithm in order to detect faults in the cooling system. To validate the method, it has been tested on 3 years of historical data from 43 turbines. During the testing period, 16 faults occurred; 15 of these were detected by the developed method, and one false alarm...... was issued. This is an improvement compared with the current system that gives 15 detections and more than 10 false alarms. In some cases, the method detects the fault a long time before the turbine reports an alarm. A further advantage of the method is that it is based on supervisory control and data...

  14. Active fault diagnosis based on stochastic tests

    Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2008-01-01

    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....

  15. Fault Detection of Reciprocating Compressors using a Model from Principles Component Analysis of Vibrations

    Ahmed, M.; Gu, F.; Ball, A. D.

    2012-05-01

    Traditional vibration monitoring techniques have found it difficult to determine a set of effective diagnostic features due to the high complexity of the vibration signals originating from the many different impact sources and wide ranges of practical operating conditions. In this paper Principal Component Analysis (PCA) is used for selecting vibration feature and detecting different faults in a reciprocating compressor. Vibration datasets were collected from the compressor under baseline condition and five common faults: valve leakage, inter-cooler leakage, suction valve leakage, loose drive belt combined with intercooler leakage and belt loose drive belt combined with suction valve leakage. A model using five PCs has been developed using the baseline data sets and the presence of faults can be detected by comparing the T2 and Q values from the features of fault vibration signals with corresponding thresholds developed from baseline data. However, the Q -statistic procedure produces a better detection as it can separate the five faults completely.

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

    S. hajiaghasi

    2014-07-01

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

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

    Yu Liu; Yang Yang; Xiaopeng Lv; Lifeng Wang

    2013-01-01

    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 ...

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

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2015-01-01

    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...... is neglectable compared with the fault developing time....

  19. Information Based Fault Diagnosis

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2008-01-01

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

  20. 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....

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

    Schlechtingen, Meik; Santos, Ilmar

    2011-01-01

    This paper presents the research results of a comparison of three different model based approaches for wind turbine fault detection in online SCADA data, by applying developed models to five real measured faults and anomalies. The regression based model as the simplest approach to build a normal...

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

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

    2016-01-01

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

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

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

    2006-01-01

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

  4. Fault Detection and Diagnosis for Brine to Water Heat Pump Systems

    Vecchio, Daniel

    2014-01-01

    The overall objective of this thesis is to develop methods for fault detection and diagnosis for ground source heat pumps that can be used by servicemen to assist them to accurately detect and diagnose faults during the operation of the heat pump. The aim of this thesis is focused to develop two fault detection and diagnosis methods, sensitivity ratio and data-driven using principle component analysis. For the sensitivity ratio method model, two semi-empirical models for heat pump unit were b...

  5. Using unknown input observers for robust adaptive fault detection in vector second-order systems

    Demetriou, Michael A.

    2005-03-01

    The purpose of this manuscript is to construct natural observers for vector second-order systems by utilising unknown input observer (UIO) methods. This observer is subsequently used for a robust fault detection scheme and also as an adaptive detection scheme for a certain class of actuator faults wherein the time instance and characteristics of an incipient actuator fault are detected. Stability of the adaptive scheme is provided by a parameter-dependent Lyapunov function for second-order systems. Numerical example on a mechanical system describing an automobile suspension system is used to illustrate the theoretical results.

  6. Application of Schlumberger transverse profiling method to detecting a strike fault

    2006-01-01

    Because it is difficult to detect a strike fault, its physical properties are discussed in this paper. Using physical simulation, numerical modeling and the in situ data, the differences between the apparent resistivity of low resistivity model obtained by transverse profiling method (TPM) whose electrode array is vertical to the profile and those by longitudinal profiling method (LPM) whose electrode array is parallel to the profile are analyzed, respectively. Our results show that the former has much marked amplitudes of anomaly. Therefore, TPM can be used to detect a strike fault more effectively and locate it more precisely, and is expected to be a new approach for detecting a sliding fault.

  7. Application of novelty detection methods to health monitoring and typical fault diagnosis of a turbopump

    Novelty detection is the identification of deviations from a training set. It is suitable for monitoring the health of mechanical systems where it usually is impossible to know every potential fault. In this paper, two novelty detectors are presented. The first detector which integrates One-Class Support Vector Machine (OCSVM) with an incremental clustering algorithm is designed for health monitoring of the turbopump, while the second one which is trained on sensor fault samples is designed to recognize faults from sensors and faults actually from the turbopump. Analysis results showed that these two detectors are both sensitive and efficient for the health monitoring of the turbopump.

  8. A Proposition for Geodetic Recording of Active Fault Zones

    Ladislav Placer; Božo Koler

    2007-01-01

    Establishing recent displacements along faults is an important and delicate task. Larger faults are accompanied by broader fault zones that require a specific approach to geodetic measurements of fault block displacements. The vector of fault block displacements, or resultant, is a vector sum of differential displacements within the fault zone. For the purposes of recording the displacements we propose the stabilization of a geodetic network of points positioned in fault blocks...

  9. Finding Active Faults in a Glaciated and Forested Landscape: the Southern Whidbey Island Fault, Washington

    Blakely, R. J.; Sherrod, B. L.; Wells, R. E.; Weaver, C. S.

    2004-12-01

    The Puget Lowland, Washington, lies within the Cascadia forearc and is underlain by at least six seismically active and regionally significant crustal faults that together accommodate several mm/yr of net north-south shortening. The surface expression of pre-15-ka slip on Puget Lowland faults has been largely scoured away or covered by glacial deposits, and younger fault geomorphology is often concealed by vegetation and urban development. High-resolution aeromagnetic and lidar surveys, followed by geologic site investigations, have identified and confirmed late Holocene deformation on each of these mostly concealed but potentially hazardous faults. Most geomorphic features identified in lidar data are closely associated with linear magnetic anomalies that reflect the underlying basement structure of the fault and help map its full extent. The southern Whidbey Island fault (SWIF) is a case in point. The northwest-striking SWIF was mapped previously using borehole data and potential-field anomalies on Whidbey Island and marine seismic-reflection surveys beneath surrounding waterways. Gravity inversions and aeromagnetic mapping suggest that the SWIF extends at least 50 km southeast, from Vancouver Island to the Washington mainland, and transitions along its length from northeast-side-down beneath Puget Sound to northeast-side-up on the mainland. Abrupt subsidence at a coastal marsh on south-central Whidbey Island suggests that the SWIF experienced a MW 6.5 to 7.0 earthquake about 3 ka. Southeast of Whidbey Island, a hypothesized southeastward projection of the SWIF makes landfall between the cities of Seattle and Everett. Linear, northwest-striking magnetic anomalies in this mainland region do coincide with this hypothesized projection, are low in amplitude, and are best illuminated in residual magnetic fields. The most prominent of the residual magnetic anomalies extends at least 16 km, lies approximately on strike with the SWIF on Whidbey Island, and passes within

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

    Nandi, Mrinal; Roy, Bimal; Sarkar, Santanu

    2012-01-01

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

  11. A New Method for Node Fault Detection in Wireless Sensor Networks

    Peng Jiang

    2009-02-01

    Full Text Available Wireless sensor networks (WSNs are an important tool for monitoring distributed remote environments. As one of the key technologies involved in WSNs, node fault detection is indispensable in most WSN applications. It is well known that the distributed fault detection (DFD scheme checks out the failed nodes by exchanging data and mutually testing among neighbor nodes in this network., but the fault detection accuracy of a DFD scheme would decrease rapidly when the number of neighbor nodes to be diagnosed is small and the node’s failure ratio is high. In this paper, an improved DFD scheme is proposed by defining new detection criteria. Simulation results demonstrate that the improved DFD scheme performs well in the above situation and can increase the fault detection accuracy greatly.

  12. Metric Learning Method Aided Data-Driven Design of Fault Detection Systems

    Guoyang Yan

    2014-01-01

    Full Text Available Fault detection is fundamental to many industrial applications. With the development of system complexity, the number of sensors is increasing, which makes traditional fault detection methods lose efficiency. Metric learning is an efficient way to build the relationship between feature vectors with the categories of instances. In this paper, we firstly propose a metric learning-based fault detection framework in fault detection. Meanwhile, a novel feature extraction method based on wavelet transform is used to obtain the feature vector from detection signals. Experiments on Tennessee Eastman (TE chemical process datasets demonstrate that the proposed method has a better performance when comparing with existing methods, for example, principal component analysis (PCA and fisher discriminate analysis (FDA.

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

    PAN Zhongliang; CHEN Ling; ZHANG Guangzhao

    2006-01-01

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

  14. A proposal of surveying and evaluating system of active faults for earthquake assessment

    1. Paleoseismology of the Itoigawa-Shizuoka Tectonic Line active fault system: We investigated co-seismic faulting activity of the Itoigawa-Shizuoka Tectonic Line active fault system (ISTL) to clarify behavioral segmentation of long and massive faults. Geomorphologic and geologic surveys, trench excavation, and seismic reflection survey in the southern to central parts of ISTL revealed paleoseismologic faulting events occurred in the last thousands years and characteristics of geometric, structural, and geomorphologic segments. Each paleoseismic event, co-seismic displacement of deposit, average slip rate, and recurrence intervals suggest that the latest paleo-earthquake occurred in 1700 cal y BP and involved multiple segments in the Okaya to the Shimotsuburai faults. The estimated surface rupture length for this event is up to 77 km or possibly up to 94 km long. The another latest event occurred after 1200 cal y BP at the Ichinose fault and adjacent active faults. In addition, ca. 1200 cal y BP event at the Gofukuji fault occurred and involved multiple segments in the northern ISTL. Behavioral boundaries of these distinctive paleoseismic events were present in segment boundaries of geometric characters and slip rate variation. In the ISTL, geometric segmentation and slip-rate variation likely coincide with the estimated behavioral segmentation. Therefore, this finding suggests that geometric segment and slip-rate variation play an important role to determine the size of the maximum behavioral segment. 2. Active fault study on the 1999 Taiwan Chichi Earthquake area: The earthquake fault was appeared along the Chelungpu Fault while the 1999 Chichi Earthquake has occurred. The N-S striking fault has been recognized as an active fault, however E-W direction earthquake fault has not been described before the earthquake as an active fault. The later fault appeared just beneath the Shihkang Dam and the dam was destroyed by the fault. This study revealed that the E

  15. Sonobuoy array measurements of active faulting on the Gorda Ridge

    Jones, P.R.; Johnson, S.H.

    1978-07-10

    The observed mismatch between the topography and the epicenter pattern associated with the Gorda Ridge spreading center was studied with two small arrays of four sonobuoys each deployed over the rift valley at 42/sup 0/37'N and 43/sup 0/N. Observed microearthquake activity originates from the crestal region and supports earlier suggestions of systematic mislocation of teleseismically determined epicenters on the Gorda Ridge. The observed seismic activity, which includes swarm events, averaged 3.5 events per hour over a total array recording time of 19.3 hours. Located microearthquakes originated from the median valley floor, valley walls, and crestal mountains. Other events, whose location could not be computed, appeared to originate from the surrounding crestal mountains with a predominance of events from west of the intersection of the Gorda Ridge and the Blanco fracture zone. Of 69 events detected, 5 were suitable fro the calculation of focal depth. Focal depths at the intersection of the Gorda Ridge and Blanco fracture zone are 6.5-10 km below a 3.5-km datum, while those farther to the south at a linear portion of the ridge range in depth from 2.5 to 6.5 km below datum. This may imply more rapid cooling near the fracture zone. A composite fault plane solution for three events on the eastern valley wall indicates movement on a high angle, with the inner wall moving upward with respect to the crestal mountains. This is the first direct evidence for uplift of median valley walls, a process which must occur if median valleys are steady state features of slowly spreading ridges.

  16. Fault detection and isolation for self powered neutron detectors based on Principal Component Analysis

    Highlights: • The methodology of Principal Component Analysis (PCA) is utilized to detect faults occurred in self powered neutron detectors. • The square prediction error based on the PCA model is employed to detect the SPND fault. • The Detector Validity Index (DVI) based on the reconstruction is employed to isolate the faulty SPND. • The fault detection and isolation scheme is validated with four types of simulated SPND faults. - Abstract: The self powered neutron detectors (SPNDs) play an important role in nuclear reactor monitoring. The 3-D power distribution and parameters used to evaluate the operation condition of reactor and the margin of safety can be determined using the measurement of SPNDs through power mapping procedure. Faulty SPNDs that are either completely or partially failed (hard fault or soft fault) provide incorrect information for monitoring. Correct detection and isolation of the faulty SPNDs are of primary importance to the efficient operation and management of the nuclear reactor. In this study, the methodology of Principal Component Analysis (PCA) is utilized to construct the mathematical models among various detectors at different axial location within the same string. The data used to build the mathematical models are generated by advanced neutronics code SMART rather than measurements. The square prediction error based on the model and the Detector Validity Index (DVI) based on the reconstruction are employed, respectively, to detect the SPND fault and to isolate the faulty SPNDs. The fault detection and isolation scheme is validated with four types of simulated SPND faults, i.e. bias, drifting, precision degradation and complete failure. The simulation results show that the proposed PCA based method can be used in the nuclear reactor to ensure that faulty SPNDs can be detected quickly

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

    1998-01-01

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

  18. Reconfigurable Test Architecture for Online Concurrent Fault Detection, Diagnosis and Repair

    Rajeevan Chandel

    2012-03-01

    Full Text Available A complete and versatile online test solution based on reconfigurable test architecture is presented in the present paper. Reconfigurable test architecture works alongside the controllers for online concurrent fault detection. The output vectors of the controllers are concurrently monitored and any fault present is detected in a few cycles from the sensitization of the fault. The architecture is then reprogrammed to a similar set of diagnostic hardware to locate a sub block which is the cause for the fault. The same architecture is then reprogrammed to replace the faulty block thereby completing repair. The test architecture is designed based on configurable logic blocks. The design has several advantages viz. (i it works well for critical VLSI controllers where shutting down or suspending the operation of a controller for testing is not possible and where the fault needs to be detected at the earliest, during the run time of the system, (ii after a fault is detected, diagnosis can be performed online, (iii once a faulty block is located, repair is also done online. Since fault detection, diagnosis and repair are completed online with one test hardware, the effective hardware overhead is negligible and the system can resume its function within a brief period. The applicability of the architecture is demonstrated for the control blocks in OC8051.

  19. Detection and diagnosis of bearing and cutting tool faults using hidden Markov models

    Boutros, Tony; Liang, Ming

    2011-08-01

    Over the last few decades, the research for new fault detection and diagnosis techniques in machining processes and rotating machinery has attracted increasing interest worldwide. This development was mainly stimulated by the rapid advance in industrial technologies and the increase in complexity of machining and machinery systems. In this study, the discrete hidden Markov model (HMM) is applied to detect and diagnose mechanical faults. The technique is tested and validated successfully using two scenarios: tool wear/fracture and bearing faults. In the first case the model correctly detected the state of the tool (i.e., sharp, worn, or broken) whereas in the second application, the model classified the severity of the fault seeded in two different engine bearings. The success rate obtained in our tests for fault severity classification was above 95%. In addition to the fault severity, a location index was developed to determine the fault location. This index has been applied to determine the location (inner race, ball, or outer race) of a bearing fault with an average success rate of 96%. The training time required to develop the HMMs was less than 5 s in both the monitoring cases.

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

    Bergantino, Nicola; Caponetti, Fabio; Longhi, Sauro

    2009-01-01

    Efficient and reliable monitoring systems are mandatory to assure the required security standards in industrial complexes. This paper describes the recent developments of FaultBuster, a purely data-driven diagnostic system. It is designed so to be easily scalable to different monitor tasks...

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

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

    2014-01-01

    Multi-way principal component analysis (MPCA) has received considerable attention and been widely used in process monitoring. A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces. However, low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model. This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information. The MPCA model and the knowledge base are built based on the new subspace. Then, fault detection and isolation with the squared prediction error (SPE) statistic and the Hotelling (T2) statistic are also realized in process monitoring. When a fault occurs, fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables. For fault isolation of subspace based on the T2 statistic, the relationship between the statistic indicator and state variables is constructed, and the constraint conditions are presented to check the validity of fault isolation. Then, to improve the robustness of fault isolation to unexpected disturbances, the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation. Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system (ASCS) to prove the correctness and effectiveness of the algorithm. The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model, and sets the relationship between the state variables and fault detection indicators for fault isolation.

  2. Palaeoseismology of the L'Aquila faults (central Italy, 2009, Mw 6.3 earthquake): implications for active fault linkage

    Galli, Paolo A. C.; Giaccio, Biagio; Messina, Paolo; Peronace, Edoardo; Zuppi, Giovanni Maria

    2011-12-01

    Urgent urban-planning problems related to the 2009 April, Mw 6.3, L'Aquila earthquake prompted immediate excavation of palaeoseismological trenches across the active faults bordering the Aterno river valley; namely, the Mt. Marine, Mt. Pettino and Paganica faults. Cross-cutting correlations amongst existing and new trenches that were strengthened by radiocarbon ages and archaeological constraints show unambiguously that these three investigated structures have been active since the Last Glacial Maximum period, as seen by the metric offset that affected the whole slope/alluvial sedimentary succession up to the historical deposits. Moreover, in agreement with both 18th century accounts and previous palaeoseismological data, we can affirm now that these faults were responsible for the catastrophic 1703 February 2, earthquake (Mw 6.7). The data indicate that the Paganica-San Demetrio fault system has ruptured in the past both together with the conterminous Mt. Pettino-Mt. Marine fault system, along more than 30 km and causing an Mw 6.7 earthquake, and on its own, along ca. 19 km, as in the recent 2009 event and in the similar 1461 AD event. This behaviour of the L'Aquila faults has important implications in terms of seismic hazard assessment, while it also casts new light on the ongoing fault linkage processes amongst these L'Aquila faults.

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

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

    2008-01-01

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

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

    Fang Wu

    2014-01-01

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

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

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

    2012-01-01

    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...

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

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

    2010-01-01

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

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

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

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

    Zhao, Jinsong; Huang, Jianchao; Sun, Wei

    2008-11-01

    A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows that automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI. PMID:18255276

  9. 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...

  10. 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...

  11. A study on transient enhancement for fault diagnosis based on an active noise control system

    Tian, X.; Gu, Fengshou; Zhen, Dong; Tran, Tung; Ball, Andrew

    2012-01-01

    Active noise control (ANC) is a more effective technique used for acoustic noise cancelation in comparison with passive approaches which are difficult and expensive to implement, especially for cancelling the noise in the low frequency range. In the ANC system, an anti-noise signal is introduced to suppress the primary noise to produce a residual which is used for updating the adaptive filter coefficients. In this paper, a method of transient content enhancement for fault detection and diagno...

  12. Automatic learning of state machines for fault detection systems in discrete event based distributed systems

    Neuner, Oliver

    2011-01-01

    The electronic components in modern automobiles build up a distributed system with so called electronic control units connected via bus systems. As more safety- and security-relevant functions are implemented in such systems, the more important fault detection becomes. A promising approach to fault detection is to build a system model from state machines and compare its predictions with properties observed in a real system. In the automobile, potential are communication characteristics betwee...

  13. Consideration of Gyroscopic Effect in Fault Detection and Isolation for Unbalance Excited Rotor Systems

    Zhentao Wang; Arne Wahrburg; Stephan Rinderknecht

    2012-01-01

    Fault detection and isolation (FDI) in rotor systems often faces the problem that the system dynamics is dependent on the rotor rotary frequency because of the gyroscopic effect. In unbalance excited rotor systems, the continuously distributed unbalances are hard to be determined or estimated accurately. The unbalance forces as disturbances make fault detection more complicated. The aim of this paper is to develop linear time invariant (LTI) FDI methods (i.e., with constant parameters) for ro...

  14. Luenberger observer-based sensor fault detection: online application to DC motor

    ALKAYA, Alkan; EKER, İlyas

    2014-01-01

    Fault detection and diagnosis (FDD) are very important for engineering systems in industrial applications. One of the most popular approaches is model-based fault detection. Recently, many techniques have been proposed in the FDD area. However, there are still very few reported applications or real-time implementations of the schemes. This paper presents online sensor FDD based on the model-based approach using a Luenberger observer and experimental application on a permanent magnet DC ...

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

    Guillermo Heredia; Anibal Ollero

    2011-01-01

    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 ...

  16. Development of monitoring and automatic fault detection solutions for grid-connected photovoltaic systems

    Capogna, Vicenzo

    2012-01-01

    In this Final Thesis work, the development of a new monitoring and automatic fault detection system for grid-connected photovoltaic systems is presented and described in its details. This product has been developed in JavaScript and HTLM protocols and it allow real time an online performance monitoring and comparison together with fault detection and causes diagnosis. The presented solution is focus on the DC side of the PV system and it includes: a simple and effective simulat...

  17. 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

    2008-06-03

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

  18. Fault detection and diagnosis using statistical control charts and artificial neural networks

    In order to operate a successful plant or process, continuous improvement must be made in the areas of safety, quality and reliability. Central to this continuous improvement is the early or proactive detection and correct diagnosis of process faults. This research examines the feasibility of using Cumulative Summation (CUSUM) Control Charts and artificial neural networks together for fault detection and diagnosis (FDD). The proposed FDD strategy was tested on a model of the heat transport system of a CANDU nuclear reactor. The results of the investigation indicate that a FDD system using CUSUM Control Charts and a Radial Basis Function (RBF) neural network is not only feasible but also of promising potential. The control charts and neural network are linked together by using a characteristic fault signature pattern for each fault which is to be detected and diagnosed. When tested, the system was able to eliminate all false alarms at steady state, promptly detect 6 fault conditions and correctly diagnose 5 out of the 6 faults. The diagnosis for the sixth fault was inconclusive. (author). 9 refs., 6 tabs., 7 figs

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

    Collins, Emmanuel G.

    2000-01-01

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

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

    JIN Xuexiang; ZHANG Yi; LI Li; HU Jianming

    2008-01-01

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

  1. A system for the non-destructive detection of faults in safety fuses using radioisotopes

    Design of an equipment for on line detection of faults in the safety fuses for conventional explosives employing transmission of #betta#-radiation is reported. The faults are detected by an ion-chamber based on the variation of the intensity of the beta particles transmitted through the fuse during its passage across the collimated beam. Strontium-90 encapsulated in stainless steel or aluminum is used as the #betta#-source. An electrical signal corresponding the fault is obtained by subtraction of an external current, that is equivalent to the output of the ion-chamber in the presence of faultless fuse. (Author)

  2. Detection of stator winding faults in induction machines using flux and vibration analysis

    Lamim Filho, P. C. M.; Pederiva, R.; Brito, J. N.

    2014-01-01

    This work aims at presenting the detection and diagnosis of electrical faults in the stator winding of three-phase induction motors using magnetic flux and vibration analysis techniques. A relationship was established between the main electrical faults (inter-turn short circuits and unbalanced voltage supplies) and the signals of magnetic flux and vibration, in order to identify the characteristic frequencies of those faults. The experimental results showed the efficiency of the conjugation of these techniques for detection, diagnosis and monitoring tasks. The results were undoubtedly impressive and can be adapted and used in real predictive maintenance programs in industries.

  3. FAULT DETECTION AND DIAGNOSIS ON A PWM INVERTER BY DIFFERENT TECHNIQUES

    S. Chafei

    2008-06-01

    Full Text Available This paper investigates the use of different techniques for fault detection in voltage-fed asynchronous machine drive systems. With the proposed techniques it is possible to detect and identify the power switch in which the fault has occurred. A diagnosis system which uses only the input variables of the drive is presented. It is based on the analysis of the current-vector trajectory, of the instantaneous frequency in faulty mode, and the evaluation of machine state variables which are processed due to the machine control algorithm. With this algorithm a fast an reliable fault detection can be realized. Furthermore limited drive operation in case of a fault mode will be discussed. All obtained results are based on computer simulation. These knowledge based methods have been test in simulation.

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

    Martinez-Guerra, Rafael

    2014-01-01

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

  5. A Unified Framework for Fault Detection and Diagnosis Using Particle Filter

    Bo Zhao

    2014-10-01

    Full Text Available In this paper, a particle filter (PF based fault detection and diagnosis framework is proposed. A system with possible faults is modeled as a group of hidden Markov models representing the system in fault-free mode and different failure modes, and a first order Markov chain is modeling the system mode transitions. A modified particle filter algorithm is developed to estimate the system states and mode. By doing this, system faults are detected when estimating the system mode, and the size of the fault is diagnosed by estimating the system state. A new resampling method is also developed for running the modified PF efficiently. Two introductory examples and a case study are given in detail. The introduction examples demonstrate the manner to model a system with possible faults into hidden Markov model and Markov chain. The case study considers a numerical model with common measurement failure modes. It focuses on the verification of the proposed fault diagnosis and detection algorithm and shows the behavior of the particle filter.

  6. Detection of fault structures with airborne LiDAR point-cloud data

    Chen, Jie; Du, Lei

    2015-08-01

    The airborne LiDAR (Light Detection And Ranging) technology is a new type of aerial earth observation method which can be used to produce high-precision DEM (Digital Elevation Model) quickly and reflect ground surface information directly. Fault structure is one of the key forms of crustal movement, and its quantitative description is the key to the research of crustal movement. The airborne LiDAR point-cloud data is used to detect and extract fault structures automatically based on linear extension, elevation mutation and slope abnormal characteristics. Firstly, the LiDAR point-cloud data is processed to filter out buildings, vegetation and other non-surface information with the TIN (Triangulated Irregular Network) filtering method and Burman model calibration method. TIN and DEM are made from the processed data sequentially. Secondly, linear fault structures are extracted based on dual-threshold method. Finally, high-precision DOM (Digital Orthophoto Map) and other geological knowledge are used to check the accuracy of fault structure extraction. An experiment is carried out in Beiya Village of Yunnan Province, China. With LiDAR technology, results reveal that: the airborne LiDAR point-cloud data can be utilized to extract linear fault structures accurately and automatically, measure information such as height, width and slope of fault structures with high precision, and detect faults in areas with vegetation coverage effectively.

  7. Fault detection, isolation, and diagnosis of self-validating multifunctional sensors

    Yang, Jing-li; Chen, Yin-sheng; Zhang, Li-li; Sun, Zhen

    2016-06-01

    A novel fault detection, isolation, and diagnosis (FDID) strategy for self-validating multifunctional sensors is presented in this paper. The sparse non-negative matrix factorization-based method can effectively detect faults by using the squared prediction error (SPE) statistic, and the variables contribution plots based on SPE statistic can help to locate and isolate the faulty sensitive units. The complete ensemble empirical mode decomposition is employed to decompose the fault signals to a series of intrinsic mode functions (IMFs) and a residual. The sample entropy (SampEn)-weighted energy values of each IMFs and the residual are estimated to represent the characteristics of the fault signals. Multi-class support vector machine is introduced to identify the fault mode with the purpose of diagnosing status of the faulty sensitive units. The performance of the proposed strategy is compared with other fault detection strategies such as principal component analysis, independent component analysis, and fault diagnosis strategies such as empirical mode decomposition coupled with support vector machine. The proposed strategy is fully evaluated in a real self-validating multifunctional sensors experimental system, and the experimental results demonstrate that the proposed strategy provides an excellent solution to the FDID research topic of self-validating multifunctional sensors.

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

    Jørgensen, R.B.

    Almost all industrial systemns are automated to ensure optimal production both in relation to energy consumtion and safety to equipment and humans. All working parts are individually subject to faults. This can lead to unacceptable economic loss or injury to people. This thesis deals with a...

  9. Optimal Threshold Functions for Fault Detection and Isolation

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

    2003-01-01

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

  10. Hideen Markov Models and Neural Networks for Fault Detection in Dynamic Systems

    Smyth, Padhraic

    1994-01-01

    None given. (From conclusion): Neural networks plus Hidden Markov Models(HMM)can provide excellene detection and false alarm rate performance in fault detection applications. Modified models allow for novelty detection. Also covers some key contributions of neural network model, and application status.

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

    YangTianshe; LiHuaizu; SunYanbong

    2004-01-01

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

  12. Geophysical prospecting of a slow active fault in the Lower Rhine Embayment, NW Germany

    Streich, R.; Strecker, M.; Lück, E.; Scherbaum, F.; Schäbitz, F.; Spangenberg, U.

    2003-04-01

    The Lower Rhine embayment, Germany, is currently one of the most active sectors of the Cenozoic rift system of western and central Europe. Historical records denote at least 21 earthquakes with epicentral intensities >=7, and instrumental records show a concentration of seismicity at the major bounding Peel Boundary, Erft, Feldbiss and Rurrand faults. Many fault segments were active in the recent past and formed numerous morphologic scarps. However, fault scarps are poorly preserved since low displacement rates are opposed to interference of fluvioglacial with tectonic processes, a dense vegetation cover, high precipitation rates, and human landscape modification. This makes it difficult to determine the exact location, size and geometry of active fault segments in this region and hampers estimation of long-term displacement rates and fault activity. To overcome these difficulties, we applied a combination of morphologic, geophysical, and geological methods. We carried out detailed studies at the Hemmerich site located in the Erft fault system, SE Lower Rhine embayment (6.918oE, 50.758oN). The site is characterized by a topographic scarp, 4 m high and several km long. We placed special emphasis on testing the applicability of fast and simple geophysical prospecting techniques to fault assessment, and on evaluating the scarp as a potential site to excavate the suspected fault. The geophysical methods applied comprise resistivity and chargeability tomography, ground penetrating radar, and shallow seismic reflection, all carried out along profiles perpendicular to the topographic scarp. In addition, electromagnetic and magnetic maps were acquired. Beside geophysical prospecting, we conducted microtopographic levelling and coring. We detected a major break in a shallow radar reflector, and a steep seismic velocity contrast discernible both by seismic refraction tomography and dispersion analysis. These features are in good spatial correlation with each other and with

  13. Applications of pattern recognition techniques to online fault detection

    A common problem to operators of complex industrial systems is the early detection of incipient degradation of sensors and components in order to avoid unplanned outages, to orderly plan for anticipated maintenance activities and to assure continued safe operation. In such systems, there usually are a large number of sensors (upwards of several thousand is not uncommon) serving many functions, ranging from input to control systems, monitoring of safety parameters and component performance limits, system environmental conditions, etc. Although sensors deemed to measure important process conditions are generally alarmed, the alarm set points usually are just high-low limits and the operator's response to such alarms is based on written procedures and his or her experience and training. In many systems this approach has been successful, but in situations where the cost of a forced outage is high an improved method is needed. In such cases it is desirable, if not necessary, to detect disturbances in either sensors or the process prior to any actual failure that could either shut down the process or challenge any safety system that is present. Recent advances in various artificial intelligence techniques have provided the opportunity to perform such functions of early detection and diagnosis. In this paper, the experience gained through the application of several pattern-recognition techniques to the on-line monitoring and incipient disturbance detection of several coolant pumps and numerous sensors at the Experimental Breeder Reactor-II (EBR-II) which is located at the Idaho National Engineering Laboratory is presented

  14. 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.

  15. Detection Of Fiber Fault In FTTH Networking Using The Centralized Failure Detection System (CFDS

    Ng Boon Chuan

    2009-09-01

    Full Text Available Issues with fiber fault in fiber to the home (FTTH customer access network often become a challenge to thenetwork service providers. The most important issues troubled the service providers and customer premisesare regarding the service reliability and safety. Conventionally, optical time domain reflectometer (OTDR is used to detect the fiber fault and address the failure location in FTTH upwardly from customer sides towardcentral office (CO. However, OTDR can only display a measurement result of a testing line in a time and alsotime and cost misspend. By looking at the stated issues, a simple, attractive and user friendly graphical userinterface (GUI is developed for Centralized Failure Detection System (CFDS based on MATLAB programmingin this study. The developed program will be installed with optical line terminal (OLT at the CO to centralizedmonitoring each optical fiber line’s status and identifying the failure location that occurs in the drop regionof FTTH downwardly from CO towards customer sides. CFDS is interfaced with OTDR to accumulate everynetwork testing result to be displayed on a single computer screen for further data analyzing. The analysisresults will be sent to field engineers or service providers for promptly actions.

  16. Active faults and related Late Quaternary deformation along the Northwestern Himalayan Frontal Zone, India

    T. Nakata

    2003-06-01

    Full Text Available Numerous newly-identified traces of active faults in the Himalayan foothill zone along the HFF around Chandigarh, in Pinjore Dun, along the piedmont zone of the Lower Siwalik hill front and within the Lower Tertiary hill range reveal the pattern of thrust and strike-slip faulting, striking parallel to the principal structural trend (NNW-SSE of the orogenic belt. The active Chandigarh Fault, Pinjore Garden Fault and Barsar thrust have vertically dislocated, warped and backtilted fluvial and alluvial-fan surfaces made up of Late Pleistocene-Holocene sediments. West- and southwest-facing fault scarplets with heights ranging from 12 to 50 m along these faults suggest continued tectonic movement through Late Pleistocene to recent times. Gentle warping and backtilting of the terraces on the hanging wall sides of the faults indicate fault-bend folding. These active faults are the manifestation of north-dipping imbricated thrust faults branching out from the major fault systems like the Main Boundary Fault (MBF and Himalayan Frontal Fault (HFF, probably merging down northward into a décollement. The Taksal Fault, striking NNW-SSE, shows prominent right-lateral movement marked by lateral offset of streams and younger Quaternary terraces and occupies a narrow deep linear valley along the fault trace. Right stepping along this fault has resulted in formation of a small pull-apart basin. Fault scarplets facing ENE and WSW are the manifestation of dip-slip movement. This fault is an example of slip-partitioning between the strike-slip and thrust faults, suggesting ongoing oblique convergence of the Indian plate and northward migration of a tectonic sliver. Slip rate along the Taksal Fault has been calculated as 2.8 mm/yr. Preliminary trench investigation at the base of the Chandigarh Fault Scarp has revealed total displacement of 3.5 m along a low angle thrust fault with variable dip of 20° to 46° due northeast, possibly the result of one

  17. Active Fault Tolerant Control for Ultrasonic Piezoelectric Motor

    Boukhnifer, Moussa

    2012-07-01

    Ultrasonic piezoelectric motor technology is an important system component in integrated mechatronics devices working on extreme operating conditions. Due to these constraints, robustness and performance of the control interfaces should be taken into account in the motor design. In this paper, we apply a new architecture for a fault tolerant control using Youla parameterization for an ultrasonic piezoelectric motor. The distinguished feature of proposed controller architecture is that it shows structurally how the controller design for performance and robustness may be done separately which has the potential to overcome the conflict between performance and robustness in the traditional feedback framework. A fault tolerant control architecture includes two parts: one part for performance and the other part for robustness. The controller design works in such a way that the feedback control system will be solely controlled by the proportional plus double-integral PI2 performance controller for a nominal model without disturbances and H∞ robustification controller will only be activated in the presence of the uncertainties or an external disturbances. The simulation results demonstrate the effectiveness of the proposed fault tolerant control architecture.

  18. Detection of the present of fault structures in volcanic rock with magnetic methods

    Banten NPP site is located in Kramatwatu-Bojonegara district, Serang, it has a surface fault indication in volcanic rock it known that to Northwest Southeast trending. Indications of the satellite imagery analysis maps confirm the straightness (lineament) at Bojonegara-1 fault. A lineament as fault structures to be necessary to prove existence of magnetic method in order to determine the continuity of Bojonegara fault in the subsurface. The purpose of the study is to know the Bojonegara fault in the subsurface. Through on interpretation and analysis of the earth's magnetic field on the scale of an object to be caused a variety of sources it can be detected by intensity magnetic as a total magnetic moment of unity volume to study the condition of the deformed rocks. The study used are G856-AX Proton Magnetometer precession magnetometer (PPM) over a stretch of 300 m and 10 m intervals for the fault lineament. The measurement system uses two sensors and observations, corrected magnetic field strength is ideal as a reference for the total magnetic field anomalies. Preliminary results show that the fault lineament is indicated at the observation point with a depth to unknown so that it still need more detailed. Magnetic method is very good for an early review of fault structures with fast and simple. (author)

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

    Steffen Haus

    2013-01-01

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

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

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

    2014-01-01

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

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

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

    2001-01-01

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

  2. Continuous monitoring of an active fault in a plate suture zone: a creepmeter study of the Chihshang Fault, eastern Taiwan

    Lee, J.-C.; Angelier, J.; Chu, H.-T.; Hu, J.-C.; Jeng, F.-S.

    2001-04-01

    Data from continuously monitored creepmeters across the active Chihshang Fault in eastern Taiwan are presented. The Chihshang Fault is an active segment of the Longitudinal Valley Fault, the main suture between the converging Philippine and Eurasian plates in Taiwan. Since the 1951 earthquake (Mw=7.0), no earthquake larger than magnitude 6.0 occurred in the Chihshang area. At least during the last 20 years, the Chihshang Fault underwent a steady creep movement, resulting in numerous fractures at the surface. Five creepmeters were installed in 1998 at two sites, Tapo and Chinyuan, within the Chihshang active fault zone. One-year results (from August 1998 to July 1999) show a horizontal shortening of 19.4±0.3 mm and 17.3±0.7 mm, at Tapo and Chinyuan, respectively. These annual shortening rates are in a good agreement with other estimates of strain rate independently obtained from geodetic measurements and geological site investigation. The creepmeter measurements were made on a daily basis, providing accurate information on the previously unknown evolution of creep during the year. The records of fault creep at the Tapo site thus revealed close seasonal correlation with average rainfall: the period of high creep rate coincides with the wet season, whereas that of low creep rate coincides with the dry season. Also, in comparison with the Tapo site, the creep behaviour as a function of time is complex at the Chinyuan site. Possible factors of irregularity are under investigation (thermal effect acting on the concrete basement of the creepmeters, earth tide effect, water table variations in a nearby rice field, and rainfall). The comparison between GPS measurements across the Longitudinal Valley (31 mm/year of horizontal displacement) and the creepmeter measurement across the Chihshang Fault zone (17-19 mm/year of horizontal displacement) suggests that there exists other shortening deformation across the active fault zone in addition to those we have measured from the

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

    Khelouat, Samir

    2012-06-01

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

  4. Detection of Inter-turn Faults in Five-Phase Permanent Magnet Synchronous Motors

    SAAVEDRA, H.

    2014-11-01

    Full Text Available Five-phase permanent magnet synchronous motors (PMSMs have inherent fault-tolerant capabilities. This paper analyzes the detection of inter-turn short circuit faults in five-phase PMSMs in their early stage, i.e. with only one turn in short circuit by means of the analysis of the stator currents and the zero-sequence voltage component (ZSVC spectra. For this purpose, a parametric model of five-phase PMSMs which accounts for the effects of inter-turn short circuits is developed to determine the most suitable harmonic frequencies to be analyzed to detect such faults. The amplitudes of these fault harmonic are analyzed in detail by means of finite-elements method (FEM simulations, which corroborate the predictions of the parametric model. A low-speed five-phase PMSM for in-wheel applications is studied and modeled. This paper shows that the ZSVC-based method provides better sensitivity to diagnose inter-turn faults in the analyzed low-speed application. Results presented under a wide speed range and different load levels show that it is feasible to diagnose such faults in their early stage, thus allowing applying a post-fault strategy to minimize their effects while ensuring a safe operation.

  5. Hidden Markov models for fault detection in dynamic systems

    Smyth, Padhraic J. (Inventor)

    1995-01-01

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

  6. Sensor Fault Detection and Diagnosis for autonomous vehicles

    Realpe Miguel; Vintimilla Boris; Vlacic Ljubo

    2015-01-01

    In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed ar...

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

    2007-01-01

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

  8. Detection and location of electrical insulation faults on the LHC superconducting circuits during hardware commissioning

    Bozzini, D; Mess, K H; Russenschuck, Stephan

    2008-01-01

    As part of the electrical quality assurance program (ELQA), the insulation of all superconducting circuits of the LHC has to be tested with a d.c. voltage of up to 1.9 kV. Fault location within a ± 3 m range over the total length of 2700 m has been achieved in order to limit the number of interconnection openings for repair. In this paper, the methods, tooling, and procedures for the detection and location of electrical faults will be presented in view of the practical experience gained in the LHC tunnel. Three particular cases of localized faults during LHC hardware commissioning will be discussed.

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

    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.)

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

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

    1997-03-01

    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.)

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

    Hamid Fekri Azgomi; Javad Poshtan

    2013-01-01

    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 det...

  12. Simulation and fault-detection of a pressure control servosystem in a Boiling Water Reactor

    This master thesis describes a Simnon model of a boiling water reactor to be used in simulating faults and disturbances. These faults and disturbanses will be detected by noise analysis. Some methods in identification and noise analysis are also described and are applied on some malfunctions of a servo. A Pascal program for recursive parameter identification was also written and tested. This program is to be used in an expert system for noise analysis on the nuclear power plant Barsebaeck. (author)

  13. Concurrent Detection and Classification of Faults in Matrix Converter using Trans-Conductance

    Sarah Azimi; Mehdi Vejdaniamiri

    2014-01-01

    This paper presents a fault diagnostic algorithm for detecting and locating open-circuit and short-circiut faults in switching components of matrix converters (MCs) which can be effectively used to drive a permanent magnet synchronous motor for research in critical applications. The proposed method is based on monitoring the voltages and currents of the switches. These measurements are used to evaluate the forward trans-conductance of each transistor for different values of switch voltages. T...

  14. A Proposition for Geodetic Recording of Active Fault Zones

    Ladislav Placer

    2007-12-01

    Full Text Available Establishing recent displacements along faults is an important and delicate task. Larger faults are accompanied by broader fault zones that require a specificapproachtogeodeticmeasurements of fault block displacements. The vector of fault block displacements, or resultant, is a vector sum of differential displacements within the fault zone. For the purposes of recording the displacements we propose the stabilization of a geodetic network of points positioned in fault blocks outside the fault zone, whereby the displacements would be manifested in the deformation of the network. The resultant displacement vector can then be derived from the latter deformation, and from that, the dip and strike of the fault zone as well as the extent of the displacement.

  15. Soil radon survey for tracing active fault: a case study along Qena-Safaga road, Eastern Desert, Egypt

    High concentrations of radon are often used as a geophysical tool for uranium exploration, earthquake and volcanic activity predication, and fault zones confirmation. The aim of this study was to assure the suitability of this method in the study of fault zones. For this purpose, a portable AlphaGUARD PQ 2000 device was used to detect the fracture zones along Qena-Safaga road, Eastern Desert, Egypt. Radon soil gas anomalies were found to be linearly distributed along NW-SE and NE-SW trends. Such directions agree well with the directions of the active fault deduced from earlier studies. Radon concentration in soil along the repeated three profiles was anomalously high in all fault zones by a factor of 3-6 above background values. In the profiles studied, the peaks recorded on the fault trace were found to be higher than the background. The analysis of the water samples collected from a well in the studied area showed that the HCO3 contents exceeded 1000 ppm, providing an additional evidence that the area under study is likely to be included within a major seismic belt. This study confirms strongly that radon gas and hydrochemical studies are a good tool for fault zones detection in similar areas

  16. Soil radon survey for tracing active fault: a case study along Qena-Safaga road, Eastern Desert, Egypt

    Moussa, M.M.; El Arabi, A.M. E-mail: elarabi21@yahoo.com

    2003-06-01

    High concentrations of radon are often used as a geophysical tool for uranium exploration, earthquake and volcanic activity predication, and fault zones confirmation. The aim of this study was to assure the suitability of this method in the study of fault zones. For this purpose, a portable AlphaGUARD PQ 2000 device was used to detect the fracture zones along Qena-Safaga road, Eastern Desert, Egypt. Radon soil gas anomalies were found to be linearly distributed along NW-SE and NE-SW trends. Such directions agree well with the directions of the active fault deduced from earlier studies. Radon concentration in soil along the repeated three profiles was anomalously high in all fault zones by a factor of 3-6 above background values. In the profiles studied, the peaks recorded on the fault trace were found to be higher than the background. The analysis of the water samples collected from a well in the studied area showed that the HCO{sub 3} contents exceeded 1000 ppm, providing an additional evidence that the area under study is likely to be included within a major seismic belt. This study confirms strongly that radon gas and hydrochemical studies are a good tool for fault zones detection in similar areas.

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

    REYES-ARCHUNDIA, E.

    2015-08-01

    Full Text Available This paper proposes a fault detection and localization method for power transmission lines with a Static Synchronous Series Compensator (SSSC. The algorithm is based on applying a modal transformation to the current and voltage signals sampled at high frequencies. Then, the wavelet transform is used for calculating the current and voltage traveling waves, avoiding low frequency interference generated by the system and the SSSC. Finally, by using reflectometry principles, straightforward expressions for fault detection and localization in the transmission line are derived. The algorithm performance was tested considering several study cases, where some relevant parameters such as voltage compensation level, fault resistance and fault inception angle are varied. The results indicate that the algorithm can be successfully be used for fault detection and localization in transmission lines compensated with a SSSC. The estimated error in calculating the distance to the fault is smaller than 1% of the transmission line length. The test system is simulated in PSCAD platform and the algorithm is implemented in MATLAB software.

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

    Hua-Qing Wang

    2014-01-01

    Full Text Available Vibration signals of rolling element bearings faults are usually immersed in background noise, which makes it difficult to detect the faults. Wavelet-based methods being used commonly can reduce some types of noise, but there is still plenty of room for improvement due to the insufficient sparseness of vibration signals in wavelet domain. In this work, in order to eliminate noise and enhance the weak fault detection, a new kind of peak-based approach combined with multiscale decomposition and envelope demodulation is developed. First, to preserve effective middle-low frequency signals while making high frequency noise more significant, a peak-based piecewise recombination is utilized to convert middle frequency components into low frequency ones. The newly generated signal becomes so smoother that it will have a sparser representation in wavelet domain. Then a noise threshold is applied after wavelet multiscale decomposition, followed by inverse wavelet transform and backward peak-based piecewise transform. Finally, the amplitude of fault characteristic frequency is enhanced by means of envelope demodulation. The effectiveness of the proposed method is validated by rolling bearings faults experiments. Compared with traditional wavelet-based analysis, experimental results show that fault features can be enhanced significantly and detected easily by the proposed method.

  19. 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

    2016-08-01

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

  20. 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

    2016-08-26

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

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

    Songpon Klinchaeam

    2014-10-01

    Full Text Available This paper presents a condition monitoring technique of a spur gear fault detection using vibration signal analysis based on time domain. Vibration signals were acquired from gearboxes and used to simulate various faults on spur gear tooth. In this study, vibration signals were applied to monitor a normal and various fault conditions of a spur gear such as normal, scuffing defect, crack defect and broken tooth. The statistical parameters of vibration signal were used to compare and evaluate the value of fault condition. This technique can be applied to set alarm limit of the signal condition based on statistical parameter such as variance, kurtosis, rms and crest factor. These parameters can be used to set as a boundary decision of signal condition. From the results, the vibration signal analysis with single statistical parameter is unclear to predict fault of the spur gears. The using at least two statistical parameters can be clearly used to separate in every case of fault detection. The boundary decision of statistical parameter with the 99.7% certainty ( 3   from 300 referenced dataset and detected the testing condition with 99.7% ( 3   accuracy and had an error of less than 0.3 % using 50 testing dataset.

  2. Fault Detection in WSNs - An Energy Efficiency Perspective Towards Human-Centric WSNs

    Orfanidis, Charalampos; Zhang, Yue; Dragoni, Nicola

    2015-01-01

    Energy efficiency is a key factor to prolong the lifetime of wireless sensor networks (WSNs). This is particularly true in the design of human-centric wireless sensor networks (HCWSN) where sensors are more and more embedded and they have to work in resource-constraint settings. Resource limitation...... has a significant impact on the design of a WSN and the adopted fault detection method. This paper investigates a number of fault detection approaches and proposes a fault detection framework based on an energy efficiency perspective. The analysis and design guidelines given in this paper aims...... at representing a first step towards the design of energy-efficient detection approaches in resource-constraint WSN, like HCWSNs....

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

    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

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

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

    2016-02-01

    Fault diagnosis of rolling element bearings is important for improving mechanical system reliability and performance. Vibration signals contain a wealth of complex information useful for state monitoring and fault diagnosis. However, any fault-related impulses in the original signal are often severely tainted by various noises and the interfering vibrations caused by other machine elements. Narrow-band amplitude demodulation has been an effective technique to detect bearing faults by identifying bearing fault characteristic frequencies. To achieve this, the key step is to remove the corrupting noise and interference, and to enhance the weak signatures of the bearing fault. In this paper, a new method based on adaptive wavelet filtering and spectral subtraction is proposed for fault diagnosis in bearings. First, to eliminate the frequency associated with interfering vibrations, the vibration signal is bandpass filtered with a Morlet wavelet filter whose parameters (i.e. center frequency and bandwidth) are selected in separate steps. An alternative and efficient method of determining the center frequency is proposed that utilizes the statistical information contained in the production functions (PFs). The bandwidth parameter is optimized using a local ‘greedy’ scheme along with Shannon wavelet entropy criterion. Then, to further reduce the residual in-band noise in the filtered signal, a spectral subtraction procedure is elaborated after wavelet filtering. Instead of resorting to a reference signal as in the majority of papers in the literature, the new method estimates the power spectral density of the in-band noise from the associated PF. The effectiveness of the proposed method is validated using simulated data, test rig data, and vibration data recorded from the transmission system of a helicopter. The experimental results and comparisons with other methods indicate that the proposed method is an effective approach to detecting the fault-related impulses

  5. Control Surface Fault Diagnosis with Specified Detection Probability - Real Event Experiences

    Hansen, Søren; Blanke, Mogens

    2013-01-01

    desired levels of false alarms and detection probabilities. Self-tuning residual generators are employed for diagnosis and are combined with statistical change detection to form a setup for robust fault diagnosis. On-line estimation of test statistics is used to obtain a detection threshold and a desired...... false alarm probability. A data based method is used to determine the validity of the methods proposed. Verification is achieved using real data and shows that the presented diagnosis method is efficient and could have avoided incidents where faults led to loss of aircraft....

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

    Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

    2016-07-01

    Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes. PMID:27038887

  7. Offshore active faults of the Mikata fault zone in Fukui, Japan, revealed by high-resolution seismic profiles

    Inoue, T.; Sugiyama, Y.; Sakamoto, I.; Takino, Y.; Murakami, F.; Hosoya, T.; Usami, T.

    2014-12-01

    The Mikata fault zone are located in coastal and shallow sea area off Fukui Prefecture, West Japan. National Institute of Advanced Industrial Science and Technology (AIST) and Tokai University conducted, as part of MEXT 2013 nearshore active fault survey project, a high-resolution multi-channel seismic survey using Boomer and a 12-channel streamer cable, acoustic profiling survey using parametric sub-bottom profiler and shallow-sea offshore drilling, in order to clarify distribution and activity of the Mikata fault zone. The seismic reflection surveys identified four reflection surfaces as vertical displacement markers in the post-glacial deposits at a depth ranging from ca. 4.5m to ca. 17m below the sea bottom on the downthrown side. We estimated the age of each marker reflection surface by using the C14 age and others from 4m-long core obtained on the downthrown side of fault and the sea level change in the latest Pleistocene and early Holocene around Japan. The results of these surveys have revealed that the fault system was reactivated three times since the latest Pleistocene. The vertical slip rate and average recurrence interval of the fault system are estimated at ca. 0.8-1.0 m/ky and 2,000-3,800 years, respectively.

  8. Improved spectral kurtosis with adaptive redundant multiwavelet packet and its applications for rotating machinery fault detection

    Rotating machinery fault detection is significant to avoid serious accidents and huge economic losses effectively. However, due to the vibration signal with the character of non-stationarity and nonlinearity, the detection and extraction of the fault feature turn into a challenging task. Therefore, a novel method called improved spectral kurtosis (ISK) with adaptive redundant multiwavelet packet (ARMP) is proposed for this task. Spectral kurtosis (SK) has been proved to be a powerful tool to detect and characterize the non-stationary signal. To improve the SK in filter limitation and enhance the resolution of spectral analysis as well as match fault feature optimally, the ARMP is introduced into the SK. Moreover, since kurtosis does not reflect the actual trend of periodic impulses, the SK is improved by incorporating an evaluation index called envelope spectrum entropy as supplement. The proposed method is applied to the rolling element bearing and gear fault detection to validate its reliability and effectiveness. Compared with the conventional frequency spectrum, envelope spectrum, original SK and some single wavelet methods, the results indicate that it could improve the accuracy of frequency-band selection and enhance the ability of rotating machinery fault detection. (paper)

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

    Wang, Chao; Liu, Xiao; Chen, Zhe

    2014-01-01

    Incipient stator winding fault in permanent magnet synchronous wind generators (PMSWGs) is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic. This paper simulates the incipient stator winding faults at different degree of...

  10. The use of LANDSAT ETM and ERS data for the detection of faults for seismic microzonation

    Estimating the likelihood of seismic hazard and the degree of damage, including damage of secondary effects is essential for damage mitigation planning. The present study is an attempt to integrate various data sets as LANDSAT ETM - and satellite radar (ERS) - data and geological and geophysical data to obtain a better understanding of processes influencing the damage intensity of stronger earthquakes. Special attention is given to the mapping of structural features visible on satellite imageries from the area in order to investigate the tectonic setting and to detect surface traces of fracture and fault zones that might influence the contour and degree of seismic shock and earthquake induced secondary effects as soil liquefaction. Special attention is focussed on active, neotectonice features. Linear features visible on remote sensing - data from the test area, thus, were mapped and risk areas delineated using ArcView - Geographic Information System (GIS) - technology. As risk areas were mapped those regions with higher risk of seismic wave amplification due to water saturated surfaces or due to intersecting fault zones guiding seismic waves. The evaluations were compared. correlated and combined with available geologic and geophysic data. The results of this study allow an application for seismic microzonation purposes. (author)

  11. 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 o...

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

    Byung Eun Lee

    2014-09-01

    Full Text Available This paper proposes an algorithm for fault detection, faulted phase and winding identification of a three-winding power transformer based on the induced voltages in the electrical power system. The ratio of the induced voltages of the primary-secondary, primary-tertiary and secondary-tertiary windings is the same as the corresponding turns ratio during normal operating conditions, magnetic inrush, and over-excitation. It differs from the turns ratio during an internal fault. For a single phase and a three-phase power transformer with wye-connected windings, the induced voltages of each pair of windings are estimated. For a three-phase power transformer with delta-connected windings, the induced voltage differences are estimated to use the line currents, because the delta winding currents are practically unavailable. Six detectors are suggested for fault detection. An additional three detectors and a rule for faulted phase and winding identification are presented as well. The proposed algorithm can not only detect an internal fault, but also identify the faulted phase and winding of a three-winding power transformer. The various test results with Electromagnetic Transients Program (EMTP-generated data show that the proposed algorithm successfully discriminates internal faults from normal operating conditions including magnetic inrush and over-excitation. This paper concludes by implementing the algorithm into a prototype relay based on a digital signal processor.

  13. Open and closed-loop motor control system with incipient broken rotor bar fault detection using current signature

    Refaat, Shady S.; Abu-Rub, Haitham; Saad, M. S.; Iqbal, Atif

    2014-01-01

    Motor drive system is considered the most important asset in industrial applications. Detection of broken rotor bars has long been important but difficult job in detection area of incipient motor faults. The need for highly efficient motor control drive systems becomes more and more important. Motors are controlled in closed-loop or open-loop modes of operation. This paper develops a novel approach for fault-detection scheme of broken rotor bar faults for three-phase induction motor using sta...

  14. Fault Detection and Classification in Transmission lines based on a Combination of Wavelet Singular Values and Fuzzy Logic

    NAYERİPOUR, Majid; RAJAEİ, Amir Hosein; GHANBARİAN, Mohammad Mehdi; DEHGHANİ, Moslem

    2015-01-01

    Abstract. In this paper, a new method for fault detection and classification in transmission lines has been used. This method, called Fuzzy-Wavelet Singular Values, combines the advantages of wavelet transform and singular value decomposition, then uses fuzzy logic to detect and classify the fault. The proposed algorithm uses the singular values of wavelet transform of three phases and zero sequence current for fault detection and classification. The input of fuzzy logic is singular values wa...

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

    Haitao Wang

    2016-01-01

    An online robust fault detection method is presented in this paper for VAV air handling unit and its implementation. Residual-based EWMA control chart is used to monitor the control processes of air handling unit and detect faults of air handling unit. In order to provide a level of robustness with respect to modeling errors, control limits are determined by incorporating time series model uncertainty in EWMA control chart. The fault detection method proposed was tested and validated using re...

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

    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)

  17. 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)

    2011-07-01

    In this work a new monitoring and fault detection methodology was developed using GMDH (Group Method of Data Handling) algorithm and artificial neural networks (ANNs) which was applied in the IEA-R1 research reactor at IPEN. The monitoring and fault detection system was developed in two parts: the first was dedicated to preprocess information, using GMDH algorithm; and the second to the process information using ANNs. The preprocess information was divided in two parts. In the first part, the GMDH algorithm was used to generate a better database estimate, called matrix z, which was used to train the ANNs. In the second part the GMDH was used to study the best set of variables to be used to train the ANNs, resulting in a best monitoring variable estimative. The methodology was developed and tested using five different models: one theoretical model and for models using different sets of reactor variables. After an exhausting study dedicated to the sensors monitoring, the fault detection in sensors was developed by simulating faults in the sensors database using values of +5%, +10%, +15% and +20% in these sensors database. The good results obtained through the present methodology shows the viability of using GMDH algorithm in the study of the best input variables to the ANNs, thus making possible the use of these methods in the implementation of a new monitoring and fault detection methodology applied in sensors. (author)

  18. Power plant surveillance and fault detection: applications to a commercial PWR

    The theoretical basis and validation studies of a real-time, model-based process monitoring and fault detection system (MSET, multivariate state estimation technique) is presented. Through use of a non-linear state estimation technique coupled with a probabilistically-based statistical hypothesis test, it is possible to detect and identify sensor, component and process faults at extremely early times from changes in the stochastic characteristics of measured signals. Data from an experimental fast reactor and a commercial LWR are used to demonstrate functional capabilities of the monitoring system. In addition, operational data from the Crystal River-3 (CR-3) nuclear power plant are used to illustrate the high sensitivity, accuracy, and the rapid response time of MSET for annunciation of variety signal disturbances. The types of faults detected and identified included the gradual degradation of a venturi flowmeter, rapidly failing flow sensor and the loss-of-time-response of a pressure transmitter. (author)

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

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

  20. Study and Design of Diaphragm Pump Vibration Detection Fault Diagnosis System Based on FFT

    Jia Yin

    2013-02-01

    Full Text Available This study has proposed a fault diagnosis system based on vibration detection. The system mainly includes four modules: signal acquisition module, signal processing module, state identification module, fault diagnosis and alarm module. The system uses CMSS 2200 acceleration sensor to collect vibration signals, processing spectrum with FFT (Fast Fourier Transform which is used effectively in current industry and finally achieve fault diagnosis and prediction for diaphragm pump. Through collection and analysis of the history signal data, set threshold value in the fault diagnosis system. According to the characteristics of different types, set the corresponding effective threshold value. The simulation results show that, the spectrum after FFT transformation processing, can really and effectively reflect equipment operating condition of the diaphragm. This system is not only simple and stable, but also can predict pump failure effectively, so that it reduces equipment downtime, plan maintenance time and unplanned maintenance time.

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

    Zhou, Binzhong 13Hatherly, Peter

    2014-10-01

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

  2. COMPILATION OF ACTIVE FAULT DATA IN PORTUGAL FOR USE IN SEISMIC HAZARD ANALYSIS

    Nemser, E.S.; Cabral, J.; Terrinha, P.; Vilanova, S.; Besana-Ostman, G.M.; Bezzeghoud, M.; Borges, J. F.; Brum da Silveira, A.; Carvalho, J.; R.P. Dias; P. M. Figueiredo; Fonseca, J.; Lopes, F.C.; J. Madeira; L. Matias

    2010-01-01

    To estimate where future earthquakes are likely to occur, it is essential to combine information about past earthquakes with knowledge about the location and seismogenic properties of active faults. For this reason, robust probabilistic seismic hazard analysis (PSHA) integrates seismicity and active fault data. Existing seismic hazard assessments for Portugal rely exclusively on seismicity data and do not incorporate data on active faults. Project SHARE (Seismic Hazard Harmonization in Europe...

  3. A New Adaptive Kalman Estimator for Detection and Isolation of Multiple Faults Integrated in a Fault Tolerant Control

    H. Jamouli

    2010-01-01

    Full Text Available For sequential jumps detection, isolation, and estimation in discrete-time stochastic linear systems, Willsky and Jones (1976 have developed the Generalized Likelihood Ratio (GLR test. After each detection and isolation of one jump, the treatment of another possible jump is obtained by a direct state estimate and covariance incrementation of the Kalman filter originally designed on the jump-free system. This paper proposes to extend this approach from a state estimator designed on a reference model directly sensitive to system changes. We will show that the obtained passive GLR test can be easily integrated in a Fault Tolerant Control System (FTCS via a control law designed in order to asymptotically reject the effect of sequential jumps.

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

    Petricca, Patrizio; Babeyko, Andrey

    2016-04-01

    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

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

    Jun-tong Qi; Jian-da Han

    2007-01-01

    This paper describes a novel wavelet-based approach to the detection of abrupt fault of Rotorcraft Unmanned Aerial Vehicle (RUAV) sensor system. By use of wavelet transforms that accurately localize the characteristics of a signal both in the time and frequency domains, the occurring instants of abnormal status of a sensor in the output signal can be identified by the multi-scale representation of the signal. Once the instants are detected, the distribution differences of the signal energy on all decomposed wavelet scales of the signal before and after the instants are used to claim and classify the sensor faults.

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

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

    2008-01-01

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

  7. 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)

    2011-05-15

    A fault detection and isolation (FDI) system for monitoring rotor current sensors in a doubly-fed induction generator (DFIG) for wind turbine applications is presented. The FDI system is designed so that the effect of parameter variations (resistances and inductances) is minimized. The residual generation is based on the generalized observer scheme (GOS) including parameter estimation. A decision system made of a combination of vector CUSUM (Cumulative sum) algorithms is used to process the residual vector and to achieve detection and isolation of incipient (small magnitude) faults. The approach is validated using signals obtained from a simulated vector-controlled DFIG. (author)

  8. 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.

    2013-12-01

    Subsidence has been a common occurrence in several cities in central Mexico for the past three decades. This process causes substantial damage to the urban infrastructure and housing in several cities and it is a major factor to be considered when planning urban development, land-use zoning and hazard mitigation strategies. Since the early 1980's the city of Morelia in Central Mexico has experienced subsidence associated with groundwater extraction in excess of natural recharge from rainfall. Previous works have focused on the detection and temporal evolution of the subsidence spatial distribution. The most recent InSAR analysis confirms the permanence of previously detected rapidly subsiding areas such as the Rio Grande Meander area and also defines 2 subsidence patches previously undetected in the newly developed suburban sectors west of Morelia at the Fraccionamiento Del Bosque along, south of Hwy. 15 and another patch located north of Morelia along Gabino Castañeda del Rio Ave. Because subsidence-induced, shallow faulting develops at high horizontal strain localization, newly developed a subsidence areas are particularly prone to faulting and fissuring. Shallow faulting increases groundwater vulnerability because it disrupts discharge hydraulic infrastructure and creates a direct path for transport of surface pollutants into the underlying aquifer. Other sectors in Morelia that have been experiencing subsidence for longer time have already developed well defined faults such as La Colina, Central Camionera, Torremolinos and La Paloma faults. Local construction codes in the vicinity of these faults define a very narrow swath along which housing construction is not allowed. In order to better characterize these fault systems and provide better criteria for future municipal construction codes we have surveyed the La Colina and Torremolinos fault systems in the western sector of Morelia using seismic tomographic techniques. Our results indicate that La Colina Fault

  9. Estimation of active faulting in a slow deformation area: Culoz fault as a case study (Jura-Western Alps junction).

    de La Taille, Camille; Jouanne, Francois; Crouzet, Christian; Jomard, Hervé; Beck, Christian; de Rycker, Koen; van Daele, Maarten; Lebourg, Thomas

    2014-05-01

    The north-western Alps foreland is considered as still experiencing distal effects of Alpine collision, resulting in both horizontal and vertical relative displacements. Based on seismological and geodetic surveys, detailed patterns of active faulting (including subsurface décollements, blind ramps and deeper crustal thrusts have been proposed (Thouvenot et al., 1998), underlining the importance of NW-SE left-lateral strike-slip offsets as along the Vuache and Culoz faults (cf. the 1996 Epagny event: M=5.4; Thouvenot et al., 1998 and the 1822 Culoz event I=VII-VIII; Vogt, 1979). In parallel to this tectonic evolution, the last glaciation-deglaciation cycles contributed to develop large and over-deepened lacustrine basins, such as Lake Le Bourget (Perrier, 1980). The fine grain, post LGM (ie post 18 ky), sedimentary infill gives a good opportunity to evidence late quaternary tectonic deformations. This study focuses on the Culoz fault, extending from the Jura to the West, to the Chautagne swamp and through the Lake Le Bourget to the East. Historical earthquakes are known nearby this fault as ie the 1822 Culoz event. The precise location and geometry of the main fault is illustrated but its Eastern termination still needs to be determined. High resolution seismic sections and side-scan sonar images performed in the 90's (Chapron et al., 1996) showed that the Col du Chat and Culoz faults have locally deformed the quaternary sedimentary infill of the lake. These studies, mainly devoted to paleo-climate analysis were not able to determine neither the geometry of the fault, or to quantify the observed deformations. A new campaign devoted to highlight the fault geometry and associated deformation, has been performed in October 2013. Very tight profiles were performed during this high resolution seismic survey using seistec boomer and sparker sources. In several places the rupture reaches the most recent seismic reflectors underlying that these faults were active during

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

    Hamid Fekri Azgomi

    2013-04-01

    Full Text Available Induction motors are critical components in many industrial processes. Therefore, swift, precise and reliable monitoring and fault detection systems are required to prevent any further damages. The online monitoring of induction motors has been becoming increasingly important. The main difficulty in this task is the lack of an accurate analytical model to describe a faulty motor. A fuzzy logic approach may help to diagnose traction motor faults. This paper presents a simple method for the detection of stator winding faults (which make up 38% of induction motor failures based on monitoring the line/terminal current amplitudes. In this method, fuzzy logic is used to make decisions about the stator motor condition. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. The motor condition is described using linguistic variables. Fuzzy subsets and the corresponding membership functions describe stator current amplitudes. A knowledge base, comprising rule and data bases, is built to support the fuzzy inference. Simulation results are presented to verify the accuracy of motor’s fault detection and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis.

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

    Miao Lingjuan; Shi Jing

    2014-01-01

    In micro-electro-mechanical system based inertial navigation system (MEMS-INS)/global position system (GPS) integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust esti-mation (RE) and fault detection (FD). A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing pri-ori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range;with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of distur-bances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.

  12. Balancing Frequencies and Fault Detection in the In-Parameter-Order Algorithm

    高世伟; 吕江花; 杜冰磊; Charles J. Colbourn; 马世龙

    2015-01-01

    The In-Parameter-Order (IPO) algorithm is a widely used strategy for the construction of software test suites for combinatorial testing (CT) whose goal is to reveal faults triggered by interactions among parameters. Variants of IPO have been shown to produce test suites within reasonable amounts of time that are often not much larger than the smallest test suites known. When an entire test suite is executed, all faults that arise from t-way interactions for some fixed t are surely found. However, when tests are executed one at a time, it is desirable to detect a fault as early as possible so that it can be repaired. The basic IPO strategies of horizontal and vertical growth address test suite size, but not the early detection of faults. In this paper, the growth strategies in IPO are modified to attempt to evenly distribute the values of each parameter across the tests. Together with a reordering strategy that we add, this modification to IPO improves the rate of fault detection dramatically (improved by 31% on average). Moreover, our modifications always reduce generation time (2 times faster on average) and in some cases also reduce test suite size.

  13. A new method for early fault detection and diagnosis of broken rotor bars

    A new method has been developed for the detection and diagnosis of broken rotor bars faults in three-phase induction motors under no-load conditions. Early detection of faults is made by using a sliding window constructed by Hilbert transforms of one of the phases of the thee-phase currents and the size of a fault is diagnosed by motor current signature analysis (MCSA) of the stored Hilbert transforms of several periods of one-phase current. The information entropy of a symbol tree generated by each sliding window is used as a fault index. The method was tested using healthy and damaged 0.37 kW induction motors under no-load conditions with applied voltages ranging from 220 V to 380 V. One and two broken rotor bars were detected under no-load conditions when supply voltages were 260 V and above. The results indicate that the method yields a high degree of accuracy in fault identification.

  14. A Comprehensive Investigation of an Offshore Active Fault in the Western Sagami Bay, Central Japan

    吴时国; 坂本泉; 徐纪人; 黄孝健

    2002-01-01

    Offshore active faults, especially those in the deep sea, are very difficult to study because of the waterand sedimentary cover. To characterize the nature and geometry of offshore active faults, a combination of methods mustbe employed. Generally, seismic profiling is used to map these faults, but often only fault-related folds rather thanfracture planes are imaged. Multi-beam swath bathymetry provides information on the structure and growth history of afault because movements of an active fault are reflected in the bottom morphology. Submersible and deep-tow surveysallow direct observations of deformations on the seafloor (including fracture zones and microstructures). In the deep sea,linearly aligned cold seep communities provide indirect evidence for active faults and the spatial migration of theiractivities.The Western Sagami Bay fault (WSBF) in the western Sagami Bay off central Japan is an active fault that has beenstudied in detail using the above methods. The bottom morphology, fractured breccias directly observed andphotographed, seismic profiles, as well as distribution and migration of cold seep communities provide evidence for thenature and geometry of the fault. Focal mechanism solutions of selected earthquakes in the western Sagami Bay duringthe period from 1900 to 1995 show that the maximum compression trends NW-SE and the minimum stress axis strikesNE-SW, a stress pattern indicating a left-lateral strike-slip fault.

  15. Spatiotemporal Correlation Based Fault-Tolerant Event Detection in Wireless Sensor Networks

    Kezhong Liu; Yang Zhuang; Zhibo Wang; Jie Ma

    2015-01-01

    Reliable event detection is one of the most important objectives in wireless sensor networks (WSNs), especially in the presence of faulty nodes. Existing fault-tolerant event detection approaches usually take the probability of faulty nodes into account and fusion techniques to weaken the influence of faulty readings are usually developed. Through extensive experiments, we discover a phenomenon that event detection accuracy degrades quickly when the faulty sensors ratio reaches a critical val...

  16. Energy-efficient fault-tolerant dynamic event region detection in wireless sensor networks

    Enemark, Hans-Jacob; Zhang, Yue; Dragoni, Nicola; Orfanidis, Charalampos

    2015-01-01

    Fault-tolerant event detection is fundamental to wireless sensor network applications. Existing approaches usually adopt neighborhood collaboration for better detection accuracy,while need more energy consumption due to communication.Focusing on energy efficiency, this paper makes an improvement to a hybrid algorithm for dynamic event region detection, such asreal-time tracking of chemical leakage regions. Considering the characteristics of the moving away dynamic events, we propose areturn b...

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

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

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

    Thomas Bak

    2012-07-01

    Full Text Available In this paper a set-membership approach for fault detection of a benchmark wind turbine is proposed. The benchmark represents relevant fault scenarios in the control system, including sensor, actuator and system faults. In addition we also consider parameter uncertainties and uncertainties on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach is used generate a set that contains all states consistent with the past measurements and the given model of the wind turbine including uncertainties and noise. This set represents all possible states the system can be in if not faulty. If the current measurement is not consistent with this set, a fault is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness of the proposed method compared to other proposed methods applied to the same problem. An advantage of the proposed method is that there is no need for threshold design, and it does not produce positive false alarms. In the case where uncertainty on the torque lookup table is introduced, some faults are not detectable. Previous research has not addressed this uncertainty. The method proposed here requires equal or less detection time than previous results.

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

    Park, Kiwoo; Chen, Zhe

    2014-01-01

    . 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 also possesses better reliability under a certain open-circuit fault condition. The proposed fault diagnosis method identifies both location and type of a fault using one current sensor in the output. Depending on the type of the fault, the proposed fault-tolerant strategy tries to keep the...... capability 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....

  20. 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

    2016-07-01

    This paper considers incipient sensor fault detection issue for a class of nonlinear systems with "observer unmatched" uncertainties. A particular fault detection sliding mode observer is designed for the augmented system formed by the original system and incipient sensor faults. The designed parameters are obtained using LMI and line filter techniques to guarantee that the generated residuals are robust to uncertainties and that sliding motion is not destroyed by faults. Then, three levels of novel adaptive thresholds are proposed based on the reduced order sliding mode dynamics, which effectively improve incipient sensor faults detectability. Case study of on the traction system in China Railway High-speed is presented to demonstrate the effectiveness of the proposed incipient senor faults detection schemes. PMID:27156675

  1. To err is robotic, to tolerate immunological: fault detection in multirobot systems.

    Tarapore, Danesh; Lima, Pedro U; Carneiro, Jorge; Christensen, Anders Lyhne

    2015-01-01

    Fault detection and fault tolerance represent two of the most important and largely unsolved issues in the field of multirobot systems (MRS). Efficient, long-term operation requires an accurate, timely detection, and accommodation of abnormally behaving robots. Most existing approaches to fault-tolerance prescribe a characterization of normal robot behaviours, and train a model to recognize these behaviours. Behaviours unrecognized by the model are consequently labelled abnormal or faulty. MRS employing these models do not transition well to scenarios involving temporal variations in behaviour (e.g., online learning of new behaviours, or in response to environment perturbations). The vertebrate immune system is a complex distributed system capable of learning to tolerate the organism's tissues even when they change during puberty or metamorphosis, and to mount specific responses to invading pathogens, all without the need of a genetically hardwired characterization of normality. We present a generic abnormality detection approach based on a model of the adaptive immune system, and evaluate the approach in a swarm of robots. Our results reveal the robust detection of abnormal robots simulating common electro-mechanical and software faults, irrespective of temporal changes in swarm behaviour. Abnormality detection is shown to be scalable in terms of the number of robots in the swarm, and in terms of the size of the behaviour classification space. PMID:25642825

  2. Improving the performance of PV systems by faults detection using GISTEL approach

    Highlights: • A new approach for detecting the faults in PV systems was explored. • A simulation results of an estimation of a global solar radiation was reached. • An algorithm for detecting the faults is proposed. - Abstract: In this paper, we present a new approach for detecting the faults in the photovoltaic systems based on the satellite image approach for estimating solar radiation data and DC output power calculations for detecting the failures. At first stage, the estimation of the hourly global horizontal solar radiation data has been evaluated by using the GISTEL (Gisement solaire par télédetection: Solar Radiation by Teledectection) model improved by the fuzzy logic technique. Thus, the results were compared with the ground solar radiation measurements. On the other hand, the comparison between the simulated and measured output DC powers was reached to find the nature of the faults in the PV array. The results showed a good accuracy and the simple implementation of the proposed approach. The estimation of the hourly solar radiation presents an NRMSE <0.22 using GISTEL model improved by fuzzy logic comparing with the estimation without fuzzy logic with an NRMSE = 0.2885 for clear sky and NRMSE = 0.2852 comparing with NRMSE = 0.3121 for cloudy sky

  3. STEM - software test and evaluation methods: fault detection using static analysis techniques

    STEM is a software reliability project with the objective of evaluating a number of fault detection and fault estimation methods which can be applied to high integrity software. This Report gives some interim results of applying both manual and computer-based static analysis techniques, in particular SPADE, to an early CERL version of the PODS software containing known faults. The main results of this study are that: The scope for thorough verification is determined by the quality of the design documentation; documentation defects become especially apparent when verification is attempted. For well-defined software, the thoroughness of SPADE-assisted verification for detecting a large class of faults was successfully demonstrated. For imprecisely-defined software (not recommended for high-integrity systems) the use of tools such as SPADE is difficult and inappropriate. Analysis and verification tools are helpful, through their reliability and thoroughness. However, they are designed to assist, not replace, a human in validating software. Manual inspection can still reveal errors (such as errors in specification and errors of transcription of systems constants) which current tools cannot detect. There is a need for tools to automatically detect typographical errors in system constants, for example by reporting outliers to patterns. To obtain the maximum benefit from advanced tools, they should be applied during software development (when verification problems can be detected and corrected) rather than retrospectively. (author)

  4. FAULT DETECTION FOR MULTIPLE-VALUED LOGIC CIRCUITS WITH FANOUT-FREE

    Pan Zhongliang

    2004-01-01

    The single fault and multiple fault detections for multiple-valued logic circuits are studied in this paper. Firstly, it is shown that the cardinality of optimal single fault test set for fanout-free m-valued circuits with n primary inputs is not more than n + 1, for linear tree circuits is two, and for multiplication modulo circuits is two if n is an odd number or if n is an even number and m > 3, where the optimal test set of a circuit has minimal number of test vectors. Secondly,it is indicated that the cardinality of optimal multiple fault test set for linear tree circuits with n primary inputs is 1 + [n/(m - 1)], for multiplication modulo circuits is n+ 1, for fanout-free circuits that consist of 2-input linear tree circuits and 2-input multiplication modulo circuits is not greater than n+ 1, where [x] denotes the smallest integer greater than or equal to x. Finally,the single fault location approaches of linear tree circuits and multiplication modulo circuits are presented, and all faults in the two types of circuits can be located by using a test set with n + 1 vectors.

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

    Sofge, D A

    2007-01-01

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

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

    Yang, Zhenyu; Rasmussen, Karsten B.; Kieu, Anh T.; Izadi-Zamanabadi, Roozbeh

    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 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 and...

  7. A comparison of some generic strategies for fault detection in liquid metal fast breeder reactors

    Data from the 1994 and 1995 benchmark tests were used to compare the performance of seven different signal processing strategies proposed for the detection of boiling or a sodium/water reaction in LMFBR. The general signal processing strategy relies on the signals from the normal background noise and the fault being additive, which gives rise to changes in the signal model in the time, frequency or probability domain. Two of the specific signal processing strategies are derived from an autoregressive model of the process, whilst the rest are implemented in the frequency domain using either global spectral distance measures or more particular spectral measures used in conjunction with wavelet analysis. The emphasis throughout the work reported in this report has been to make no assumptions about the nature of the fault to be detected other than the principle of the additive nature of the signals from a fault and the background noise. (author). 9 refs, 9 figs

  8. Relative tectonic activity assessment along the East Anatolian strike-slip fault, Eastern Turkey

    Khalifa, Abdelrahman

    2016-04-01

    The East Anatolian transform fault is a morphologically distinct and seismically active left-lateral strike-slip fault that extends for ~ 500 km from Karlıova to the Maraş defining the boundary between the Anatolian Block and Syrian Foreland. Deformed landforms along the East Anatolian fault provide important insights into the nature of landscape development within an intra-continental strike-slip fault system. Geomorphic analysis of the East Anatolian fault using geomorphic indices including mountain front sinuosity, stream length-gradient index, drainage density, hypsometric integral, and the valley-width to valley height ratio helped differentiate the faulting into segments of differing degrees of the tectonic and geomorphic activity. Watershed maps for the East Anatolian fault showing the relative relief, incision, and maturity of basins along the fault zone help define segments of the higher seismic risk and help evaluate the regional seismic hazard. The results of the geomorphic indices show a high degree of activity, reveal each segment along the fault is active and represent a higher seismic hazard along the entire fault.

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

    Yu Liu

    2013-01-01

    Full Text Available Many applications based on Internet of Things (IoT technology have recently founded in industry monitoring area. Thousands of sensors with different types work together in an industry monitoring system. Sensors at different locations can generate streaming data, which can be analyzed in the data center. In this paper, we propose a framework for online sensor fault detection. We motivate our technique in the context of the problem of the data value fault detection and event detection. We use the Statistics Sliding Windows (SSW to contain the recent sensor data and regress each window by Gaussian distribution. The regression result can be used to detect the data value fault. Devices on a production line may work in different workloads and the associate sensors will have different status. We divide the sensors into several status groups according to different part of production flow chat. In this way, the status of a sensor is associated with others in the same group. We fit the values in the Status Transform Window (STW to get the slope and generate a group trend vector. By comparing the current trend vector with history ones, we can detect a rational or irrational event. In order to determine parameters for each status group we build a self-learning worker thread in our framework which can edit the corresponding parameter according to the user feedback. Group-based fault detection (GbFD algorithm is proposed in this paper. We test the framework with a simulation dataset extracted from real data of an oil field. Test result shows that GbFD detects 95% sensor fault successfully.

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

    Babu Chellappachetty

    2014-09-01

    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.

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

    Abolfazl Akbari

    2011-02-01

    Full Text Available Some WSN by a lot of immobile node and with the limited energy and without furthercharge of energy. Whereas extension of many sensor nodes and their operation. Hence it isnormal.unactive nodes miss their communication in network, hence split the network. For avoidance splitof network, we proposed a fault recovery corrupted node and Self Healing is necessary. In this Thesis, wedesign techniques to maintain the cluster structure in the event of failures caused by energy-drainednodes. Initially, node with the maximum residual energy in a cluster becomes cluster heed and node withthe second maximum residual energy becomes secondary cluster heed. Later on, selection of cluster heedand secondary cluster heed will be based on available residual energy. We use Matlab software assimulation platform quantities. like, energy consumption at cluster and number of clusters is computed inevaluation of proposed algorithm. Eventually we evaluated and compare this proposed method againstprevious method and we demonstrate our model is better optimization than other method such asVenkataraman, in energy consumption rate.

  12. Fault Detection and Localization Method for Modular Multilevel Converters

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

    2015-01-01

    The modular multilevel converter (MMC) is attractive for medium- or high-power applications because of the advantages of its high modularity, availability, and high power quality. However, reliability is one of the most important issues for MMCs those are made of large number of power electronic ...... prototype controlled by a real-time digital signal controller in the laboratory. The results confirm the effectiveness of the proposed method.......The modular multilevel converter (MMC) is attractive for medium- or high-power applications because of the advantages of its high modularity, availability, and high power quality. However, reliability is one of the most important issues for MMCs those are made of large number of power electronic...... 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...

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

    2011-01-01

    The Brushless Direct Current (BLDC) motor is widely used in aerospace area, CNC machines and servo systems that require the high control accuracy Once the faults occur in the motor, it will cause great damage to the whole system. Mechanical faults are common in electric machines, and account for up to 50%-60% of the faults. Approximately, 80% of the mechanical faults lead to the eccentricity. So it is necessary to monitor the health condition of the motor to ensure the faults can be detected earlier and measures will be taken to imorove the reliability.

  14. Active faults crossing trunk pipeline routes: some important steps to avoid the disaster

    Besstrashnov, Vladimir; Strom, Alexander

    2010-05-01

    Trunk pipelines that pass through tectonically active areas connecting oil and gas reservoirs with terminals and refineries cross active faults that can produce large earthquakes. Besides strong motion affecting vast areas, these earthquakes are often associated with surface faulting that provides additional hazard to pipelines. To avoid significant economic losses and environmental pollution, pipelines should be designed to sustain both effects (shaking and direct rupturing) without pipe damage and spill. Special studies aimed to provide necessary input data for the designers should be performed in the course of engineering survey. However, our experience on conducting and review of such studies for several oil and gas trunk pipelines in Russia show urgent need of more strict definition of basic conceptions and approaches used for identification and localization of these potentially hazardous tectonic features. Identification of active faults (fault zones) considered as causative faults - sources of strong motion caused by seismic waves that affect dozens kilometers of pipeline route can be done by use of both direct and indirect evidence of Late Pleistocene - Holocene activity of faults and fault zones. Since strong motion parameters can be considered as constant within the near-field zone, which width in case of large earthquake is up to dozens kilometers, accuracy of active fault location is not so critical and ±1-2 km precision provided by use of indirect evidence is acceptable. In contrast, if one have to identify and characterize zones of potential surface rupturing that require special design of the endangered pipeline section, only direct evidence of such activity can provide reliable input data for crossing design with relevant accuracy of fault location, amount and direction of displacement. Only traces of surface faults displacing Late Pleistocene - Holocene sediments and/or geomorphic features are considered as direct evidence of fault activity. Just

  15. Shannon wavelet spectrum analysis on truncated vibration signals for machine incipient fault detection

    Although a variety of methods have been proposed in the literature for machine fault detection, it still remains a challenge to extract prominent features from random and nonstationary vibratory signals, a typical representative of which are the resonance signatures generated by incipient defects on the rolling elements of ball bearings. Due to its random and nonstationary nature, the involved signal generally possesses a low signal-to-noise ratio, where the classical signal processing methods cannot be effectively applied and the extracted features are usually submerged into the severe background noise. In this paper, a novel random and nonstationary vibratory signature analysis (R and N-VSA) technique is presented to address this challenge. The original vibration signal is decomposed into fault-related and non-fault-related signal segments, and multi-level exponential moving average power filtering is suggested to guide this decomposition. Instead of analyzing the whole vibratory signal, the developed Shannon wavelet spectrum analysis is more efficiently applied on the truncated fault-related signal segments so as to enhance the features' characteristics. The effectiveness of the proposed technique is examined through a series of tests with two experimental setups, and the investigation results show that the developed R and N-VSA technique is an effective signal processing technique for incipient machine fault detection. (paper)

  16. An online tacholess order tracking technique based on generalized demodulation for rolling bearing fault detection

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

    2016-04-01

    Vibration analysis has been proved to be an effective and powerful tool for the condition monitoring and fault diagnosis of rolling bearings. During the past decades, the conventional envelope analysis has been one of the main approaches in vibration signal processing. However, the envelope analysis is based on stationary assumption, thus it is not applicable to the fault diagnosis of bearings under rotating speed variation conditions. This constraint limits the bearing diagnosis in industrial applications. In recent years, order tracking methods based on time-frequency representation have been proposed for bearing fault detection under speed variation operating conditions. However, the methods are only applicable for offline bearing fault detection. Aiming at the shortcomings of the current tacholess order tracking techniques, an online tacholess order tracking method is proposed in this paper. The proposed method is on the basis of extracting the instantaneous tachometer information from the collected vibration signal itself continuously, and resampling the original signal with equal angle increment. The envelope order spectrum is used for bearing fault identification. The effectiveness of the proposed method has been validated by both simulated and experimental bearing vibration signals.

  17. 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.

    2012-01-01

    Induction motors fed through variable speed drives (VSD) are widely used in different industrial processes. Nowadays, the industry demands the integration of smart sensors to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can be produce severe damages. The combined fault identification in induction motors is a demanding task, but it has been rarely considered in spite of being a common situation, because it is difficult to identify two or more faults simultaneously. This work presents a smart sensor for online detection of simple and multiple-combined faults in induction motors fed through a VSD in a wide frequency range covering low frequencies from 3 Hz and high frequencies up to 60 Hz based on a primary sensor being a commercially available current clamp or a hall-effect sensor. The proposed smart sensor implements a methodology based on the fast Fourier transform (FFT), RMS calculation and artificial neural networks (ANN), which are processed online using digital hardware signal processing based on field programmable gate array (FPGA).

  18. Characteristics of Late Quaternary Activity of the Luhuatai Buried Fault Revealed by Drilling

    Lei Qiyun; Chai Chizhang; Du Peng; Wang Yin; Meng Guangkui

    2012-01-01

    The Luhuatai fault is one of the important buried tectonics in the Yinchuan basin. Based on the results of shallow seismic exploration, we conducted composite drilling section exploration and dating of the samples from boreholes. Some useful data was obtained, such as the depth of the upper breaking point, the latest activity age, displacement in the late Quaternary, and slip rates, etc. This study shows that the activity is different between the north and south segment along the Luhuatai fault. The north segment is a Holocene fault, while the south segment is a late mid-Pleistocene fault. From north to south along the north segment of Luhuatai fault, the activity has been enhanced, and the faulting is stronger in late Pleistocene than Holocene.

  19. Remote sensing analysis for fault-zones detection in the Central Andean Plateau (Catamarca, Argentina)

    Traforti, Anna; Massironi, Matteo; Zampieri, Dario; Carli, Cristian

    2015-04-01

    Remote sensing techniques have been extensively used to detect the structural framework of investigated areas, which includes lineaments, fault zones and fracture patterns. The identification of these features is fundamental in exploration geology, as it allows the definition of suitable sites for the exploitation of different resources (e.g. ore mineral, hydrocarbon, geothermal energy and groundwater). Remote sensing techniques, typically adopted in fault identification, have been applied to assess the geological and structural framework of the Laguna Blanca area (26°35'S-66°49'W). This area represents a sector of the south-central Andes localized in the Argentina region of Catamarca, along the south-eastern margin of the Puna plateau. The study area is characterized by a Precambrian low-grade metamorphic basement intruded by Ordovician granitoids. These rocks are unconformably covered by a volcano-sedimentary sequence of Miocene age, followed by volcanic and volcaniclastic rocks of Upper Miocene to Plio-Pleistocene age. All these units are cut by two systems of major faults, locally characterized by 15-20 m wide damage zones. The detection of main tectonic lineaments in the study area was firstly carried out by classical procedures: image sharpening of Landsat 7 ETM+ images, directional filters applied to ASTER images, medium resolution Digital Elevation Models analysis (SRTM and ASTER GDEM) and hill shades interpretation. In addition, a new approach in fault zone identification, based on multispectral satellite images classification, has been tested in the Laguna Blanca area and in other sectors of south-central Andes. In this perspective, several prominent fault zones affecting basement and granitoid rocks have been sampled. The collected fault gouge samples have been analyzed with a Field-Pro spectrophotometer mounted on a goniometer. We acquired bidirectional reflectance spectra, from 0.35μm to 2.5μm with 1nm spectral sampling, of the sampled fault rocks

  20. Expert system for detecting and diagnosing car engine starter cranks fault using dynamic control system

    David Ibitayo LANLEGE

    2015-12-01

    Full Text Available Application of Dynamic Control Systems (DCS in detecting and diagnosing car engine Starter Cranks is continuously being implemented to serve different cases of real life problems such as Control of MEMS-based scanning-probe data-storage devices, track-follow control for tape storage, probe-based ultrahigh-density storage technology, a review of feed forward control approaches in nanopositioning for high-speed SPM and so on. Car engine Starter Cranks faults can be detected by sequence of diagnostic processes which brings about the deployment of an Expert System. An Expert System is one of the leading Artificial Intelligence techniques that have been adopted to handle such task. This paper presents the imperatives for an Expert System in developing Dynamic Control Systems for detecting and diagnosing car engine Starter Crank faults through input and output requirements of constructing successful Knowledge-Based Systems. Furthermore, diagnosis of car engine Starter Cranks faults requires high technical skills and experience. thus, DCS provides input and output equations in form of Matrix/Vector State Space Representation (MSSR which is useful in assisting mechanics for car engine Starter Cranks fault detection and diagnosis via DCS and mathematical Differential Equations (DE’s.

  1. Construction of customized redundant multiwavelet via increasing multiplicity for fault detection of rotating machinery

    Chen, Jinglong; Zuo, Ming J.; Zi, Yanyang; He, Zhengjia

    2014-01-01

    Fault detection from the vibration measurement data of rotating machinery is significant for avoiding serious accidents. However, non-stationary vibration signal with a large amount of noise makes this task challenging. Multiwavelet not only owns the advantage on multi-resolution analysis but also can offer multiple wavelet basis functions. So it has the possibility of detecting various fault features preferably. However, the fixed basis functions which are not related to the given signal may lower the accuracy of fault detection. Moreover, another major intrinsic deficiency of multiwavelet lies in its critically sampled filter-bank, which causes shift-variance and is harmful to extract the feature of periodical impulses. To overcome these deficiencies, a new method called customized redundant multiwavelet (CRM) is constructed via increasing multiplicity (IM). IM is a simple method to design a series of changeable multiwavelet which are available for the subsequent optimization process. By the rule of the envelope spectrum entropy minimum principle, optimal multiwavelet is searched for. Based on the customized multiwavelet filters, the filters of CRM can be calculated by inserting zeros. The proposed method is applied to analyze the simulation, gearbox and rolling element bearing vibration signals. Compared with some other conventional methods, the results demonstrate that the proposed method possesses robust performance in detecting fault features of rotating machinery.

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

    Wang Zhaolei

    2015-06-01

    Full Text Available A closed-loop fault detection problem is investigated for the full-envelope flight vehicle with measurement delays, where the flight dynamics are modeled as a switched system with delayed feedback signals. The mode-dependent observer-based fault detection filters and state estimation feedback controllers are derived by considering the delays’ impact on the control system and fault detection system simultaneously. Then, considering updating lags of the controllers/filters’ switching signals which are introduced by the delayed measurement of altitude and Mach number, an asynchronous H∞ analysis method is proposed and the system model is further augmented to be an asynchronously switched time-delay system. Also, the global stability and desired performance of the augmented system are guaranteed by combining the switched delay-dependent Lyapunov–Krasovskii functional method with the average dwell time method (ADT, and the delay-dependent existing conditions for the controllers and fault detection filters are obtained in the form of the linear matrix inequalities (LMIs. Finally, numerical example based on the hypersonic vehicles and highly maneuverable technology (HiMAT vehicle is given to demonstrate the merits of the proposed method.

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

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

    2009-01-01

    In this paper nonlinear fault detection for in-service monitoring and decision support systems for ships will be presented. The ship is described as a nonlinear system, and the stochastic wave elevation and the associated ship responses are conveniently modelled in frequency domain. The transform...

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

    Odgaard, Peter F.; Stoustrup, Jakob

    2015-12-31

    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. An alternative would be to use the existing measurements which are normally available for the wind turbine control system. The usage of these sensors instead would cut down the cost of the wind turbine by not using additional sensors. One of these available measurements is the generator speed, in which changes 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 detects the gear-box fault with an acceptable detection delay.

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

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

    2016-01-01

    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. PMID:27092509

  6. Fault Detection of Railway Vehicle Suspension Systems Using Multiple-Model Approach

    Hayashi, Yusuke; Tsunashima, Hitoshi; Marumo, Yoshitaka

    This paper demonstrates the possibility to detect suspension failures of railway vehicles using a multiple-model approach from on-board measurement data. The railway vehicle model used includes the lateral and yaw motions of the wheelsets and bogie, and the lateral motion of the vehicle body, with sensors measuring the lateral acceleration and yaw rate of the bogie, and lateral acceleration of the body. The detection algorithm is formulated based on the Interacting Multiple-Model (IMM) algorithm. The IMM method has been applied for detecting faults in vehicle suspension systems in a simulation study. The mode probabilities and states of vehicle suspension systems are estimated based on a Kalman Filter (KF). This algorithm is evaluated in simulation examples. Simulation results indicate that the algorithm effectively detects on-board faults of railway vehicle suspension systems.

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

    Jonguk Lee

    2016-04-01

    Full Text Available Railway point devices act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Point failure can significantly affect railway operations, with potentially disastrous consequences. Therefore, early detection of anomalies is critical for monitoring and managing the condition of rail infrastructure. We present a data mining solution that utilizes audio data to efficiently detect and diagnose faults in railway condition monitoring systems. The system enables extracting mel-frequency cepstrum coefficients (MFCCs from audio data with reduced feature dimensions using attribute subset selection, and employs support vector machines (SVMs for early detection and classification of anomalies. Experimental results show that the system enables cost-effective detection and diagnosis of faults using a cheap microphone, with accuracy exceeding 94.1% whether used alone or in combination with other known methods.

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

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

    2015-02-01

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

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

    T. Benslimane

    2006-01-01

    Full Text Available This paper present a study on different input data types of ANN used to detect faults such as over-voltage in AC systems (AC network , induction motor. The input data of ANN are AC voltage and current. In no fault condition, voltage and current are sinusoidal. The input data of the ANN may be the instantaneous values of voltage and current, their RMS values or their average values after been rectified. In this paper we presented different characteristics of each one of these data. A digital software C++ simulation program was developed and simulation results were presented.

  10. Single Phase to Ground Fault Detection and Location in Compensated Network

    Loos, Matthieu

    2013-01-01

    This work takes place in the context of distribution power system protection and tries to improve the detection and location of earth faults. The protection problem is vast and many ideas emerge every year to enhance the reliability of the grid. The author has focused his energy into the compensated and isolated network protection in the specific case of single phase earth fault. This PhD thesis is divided in two main parts that might be considered as independent. The first part studies the d...

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

    Lijuan Wang; Lifeng Wu; Yong Guan; Guohui Wang

    2015-01-01

    We propose a method for online sensor fault detection that is based on the evolving Strong Tracking Filter (STCKF). The cubature rule is used to estimate states to improve the accuracy of making estimates in a nonlinear case. A residual is the difference in value between an estimated value and the true value. A residual will be regarded as a signal that includes fault information. The threshold is set at a reasonable level, and will be compared with residuals to determine whether or not the s...

  12. Implementation of non-intrusive fault detection in embedded control systems:

    Colnarič, Matjaž; Šprogar, Matej; Verber, Domen

    2007-01-01

    Paper presents fault detection in embedded control systems by the so-called monitoring cells. The basic idea is to monitor input/output variables and internal states of systems, processes or sub-processes by using acquired and built-in knowledge about the normal behavior in order to detect abnormalities. Paper gives the detailed architecture and the operation of the monitoring cells. The concept is applicable even if only a limited knowledge about the control system is available. In such case...

  13. The Acquisition High-resolution the Prospecting Technique of Seismic Data for of Active Faults

    Zhao Chengbin; Liu Baojin; Ji Jifa

    2011-01-01

    The high-resolution shallow seismic technique can be used for more accurately prospecting the position and property of faults and for the preliminary study of fault activity. The author obtains many high quality stack time sections through the prospecting methods of different seismic sources, different group intervals and different observation systems on the Xiadian fault. These sections clearly display the stratum structure and the structure characteristics from several meters to several hundred meters of the Xiadian fault. The resolutions of the different seismic sources, different group intervals and different observing systems are obtained. The prospecting methods and work parameters applicable for goal stratum of different depths and different accuracy requirements are proposed through the analysis of the stack time sections. This lays a good foundation for raising the prospecting resolution of the fault position and the latest active time of the fault.

  14. 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

    2003-01-01

    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.

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

    Guillermo Heredia

    2011-01-01

    Full Text Available Reliability is a critical issue in navigation of unmanned aerial vehicles (UAVs since there is no human pilot that can react to any abnormal situation. Due to size and cost limitations, redundant sensor schemes and aeronautical-grade navigation sensors used in large aircrafts cannot be installed in small UAVs. Therefore, other approaches like analytical redundancy should be used to detect faults in navigation sensors and increase reliability. This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters based on analytical redundancy. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the Observer/Kalman Filter Identification (OKID method. The OKID method is able to identify the system and an observer with properties similar to a Kalman filter, directly from input-output experimental data. Results are similar to the Kalman filter, but, with the proposed method, there is no need to estimate neither system matrices nor sensor and process noise covariance matrices. The system has been tested with real helicopter flight data, and the results compared with other methods.

  16. 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

    2016-05-01

    System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

  17. Concurrent Detection and Classification of Faults in Matrix Converter using Trans-Conductance

    Sarah Azimi

    2014-07-01

    Full Text Available This paper presents a fault diagnostic algorithm for detecting and locating open-circuit and short-circiut faults in switching components of matrix converters (MCs which can be effectively used to drive a permanent magnet synchronous motor for research in critical applications. The proposed method is based on monitoring the voltages and currents of the switches. These measurements are used to evaluate the forward trans-conductance of each transistor for different values of switch voltages. These trans-conductance values are then compared to the nominal values. Under healthy conditions, the values obtained for the fault signal is less than the tolerable value. Under the open/short-circuit conditions, the fault signal exceeds the threshold, hence enables the matrix converter drive to detect and exactly identify the location of the faulty IGBT. The main advantages of this diagnostic method include fast detection and locating of the faulty IGBT, easiness of implementation and independency of the modulation strategy of the converter.

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

    Javier Rosero García

    2012-04-01

    Full Text Available Permanent magnet alternating current machines are being widely used in applications demanding high and rugged performance, such as industrial automation and the aerospace and automotive industries. This paper presents a study of a permanent magnet synchronous machine (PMSM running in eccentricity; these machines’ condition monitoring and fault detection would provide added value and they are also assuming growing importance. This paper investigates the effect of eccentricity faults on PMSM motors’ current spectrum with a view to developing an effective condition-monitoring scheme using two-dimensional (2-D finite element analysis (FEA. Stator current induced harmonics were investigated for fault conditions and advanced signal analysis involved continuous and discrete wavelet transforms. Simulation and experimental results are presented to substantiate that the proposed method worked over a wide speed range for motor operation and that it provided an effective tool for diagnosing PMSM operating condition.

  19. Active tectonics of the Ganzi-Yushu fault in the southeastern Tibetan Plateau

    Shi, Feng; He, Honglin; Densmore, Alexander L.; Li, An; Yang, Xiaoping; Xu, Xiwei

    2016-04-01

    The ongoing convergence between India and Eurasia apparently is accommodated not merely by crustal shortening in Tibet, instead also by motions along strike slip faults which are usually boundaries between tectonic blocks, especially in the Tibetan Plateau. Quantification of this strike slip faulting is fundamental for understanding the collision between India and Eurasia. Here, we use a variety of geomorphic observations to place constraints on the late Quaternary kinematics and slip rates of the Ganzi-Yushu fault, one of the significant strike-slip faults in eastern Tibet. The Ganzi-Yushu fault is an active, dominantly left-lateral strike-slip structure that can be traced continuously for up to 500 km along the northern boundary of the clockwise-rotating southeastern block of the Tibetan Plateau. We analyse geomorphic evidence for deformation, and calculate the late Quaternary slip rates at four sites along the eastern portion of the fault trace. The latest Quaternary apparent throw rates are variable along strike but are typically ~ 1 mm/a. Rates of strike-slip displacement are likely to be an order of magnitude higher, 8-11 mm/a. Trenching at two locations suggests that the active fault behaviour is dominated by strike-slip faulting and reveals several earthquake events with refined information of timing. The 2010 Mw 6.9 Yushu earthquake, which occurred on the northwestern segment of the Ganzi-Yushu fault zone, provides additional evidence for fault activity. These observations agree with GPS-derived estimates, and show that late Quaternary slip rates on the Ganzi-Yushu fault are comparable to those on other major active strike-slip faults in the eastern Tibetan Plateau.

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

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

    2001-01-01

    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....

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

    Emmanuel Mazars

    2008-01-01

    Full Text Available This paper considers matrix inequality procedures to address the robust fault detection and isolation (FDI problem for linear time-invariant systems subject to disturbances, faults, and polytopic or norm-bounded uncertainties. We propose a design procedure for an FDI filter that aims to minimize a weighted combination of the sensitivity of the residual signal to disturbances and modeling errors, and the deviation of the faults to residual dynamics from a fault to residual reference model, using the ℋ∞-norm as a measure. A key step in our procedure is the design of an optimal fault reference model. We show that the optimal design requires the solution of a quadratic matrix inequality (QMI optimization problem. Since the solution of the optimal problem is intractable, we propose a linearization technique to derive a numerically tractable suboptimal design procedure that requires the solution of a linear matrix inequality (LMI optimization. A jet engine example is employed to demonstrate the effectiveness of the proposed approach.

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

    Kim, Woohyun; Braun, J.

    2016-03-05

    Refrigerant mass flow rate is an important measurement for monitoring equipment performance and enabling fault detection and diagnostics. However, a traditional mass flow meter is expensive to purchase and install. A virtual refrigerant mass flow sensor (VRMF) uses a mathematical model to estimate flow rate using low-cost measurements and can potentially be implemented at low cost. This study evaluates three VRMFs for estimating refrigerant mass flow rate. The first model uses a compressor map that relates refrigerant flow rate to measurements of inlet and outlet pressure, and inlet temperature measurements. The second model uses an energy-balance method on the compressor that uses a compressor map for power consumption, which is relatively independent of compressor faults that influence mass flow rate. The third model is developed using an empirical correlation for an electronic expansion valve (EEV) based on an orifice equation. The three VRMFs are shown to work well in estimating refrigerant mass flow rate for various systems under fault-free conditions with less than 5% RMS error. Each of the three mass flow rate estimates can be utilized to diagnose and track the following faults: 1) loss of compressor performance, 2) fouled condenser or evaporator filter, 3) faulty expansion device, respectively. For example, a compressor refrigerant flow map model only provides an accurate estimation when the compressor operates normally. When a compressor is not delivering the expected flow due to a leaky suction or discharge valve or other internal fault, the energy-balance or EEV model can provide accurate flow estimates. In this paper, the flow differences provide an indication of loss of compressor performance and can be used for fault detection and diagnostics.

  3. Upper Pleistocene - Holocene activity of the Carrascoy Fault (Murcia, SE Spain): preliminary results from paleoseismological research.

    Martin-Banda, Raquel; Garcia-Mayordomo, Julian; Insua-Arevalo, Juan M.; Salazar, Angel; Rodriguez-Escudero, Emilio; Alvarez-Gomez, Jose A.; Martinez-Diaz, Jose J.; Herrero, Maria J.; Medialdea, Alicia

    2014-05-01

    The Carrascoy Fault is located in the Internal Zones of the Betic Cordillera (Southern Spain). In particular, the Carrascoy Fault is one of the major faults forming the Eastern Betic Shear Zone, the main structure accommodating the convergence between Nubian and Eurasian plates in the westernmost Mediterranean. So far, the Carrascoy Fault has been defined as a left-lateral strike-slip fault. It extends for at least 31 km in a NE-SW trend from the village of Zeneta (Murcia) at its northeastern tip, to the Cañaricos village, controlling the northern edge of the Carrascoy Range and its linkage to the Guadalentin Depression towards the southwest. This is an area of moderate seismic activity, but densely populated, the capital of the region, Murcia, being settled very close to the fault. Hence, the knowledge of the structure and kinematics of the Carrascoy Fault is essential for assessing reliably the seismic hazard of the region. We present a detailed-scale geological and geomorphological map along the fault zone created from a LIDAR DEM combined with fieldwork, and geological and geophysical information. Furthermore, a number of trenches have been dug across the fault at different locations providing insights in the fault most recent activity as well as paleoseismic data. Preliminary results suggest that the Cararscoy Fault has recently changed its kinematic showing a near pure reverse motion. According to this, the fault can be divided into two distinct segments, the eastern one: Zeneta - Fuensanta, and the western one: Fuensanta - Cañaricos, each one having its own characteristic style and geodynamics. Some new active strands of the fault locate at the foot of the very first relief towards the North of the older strand, forming the current southern border of the Guadalentin Depression. These new faults show an increasingly reverse component westwards, so that the Fuensanta - Cañaricos segment is constituted by thrusts, which are blind at its western end

  4. Higher-Order TIME FREQUENCY Analysis and its Application to Fault Detection in Rotating Machinery

    Lee, S. K.; White, P. R.

    1997-07-01

    Impulsive acoustic and vibration signals within rotating machinery are often induced by irregular impacting. The detection of these impulses can be useful for fault diagnosis purposes. Recently there has been an increasing trend towards the use of higher-order statistics for fault detection within mechanical systems based on the observation that impulsive signals tend to increase the kurtosis values. This paper considers the use of the third- and fourth-order Wigner moment spectra, called the Wigner bi- and tri-spectra respectively, for analysing such signals. Expressions for the auto- and cross-terms in these distributions are presented and discussed. It is shown that the Wigner trispectrum is a more suitable analysis tool and its performance is compared to its second-order counterpart for detecting impulsive signals. These methods are also applied to measured data sets from a car engine and an industrial gearbox.

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

    Tao Li

    2013-01-01

    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.

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

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

    2014-05-01

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

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

    Wang Haiyun; Xie Lili; Tao Xiaxin; Li Jie

    2006-01-01

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

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

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

    2007-01-01

    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. 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)

    1998-08-01

    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

  10. Minimum System Sensitivity Study of Linear Discrete Time Systems for Fault Detection

    Xiaobo Li

    2013-01-01

    Full Text Available Fault detection is a critical step in the fault diagnosis of modern complex systems. An important notion in fault detection is the smallest gain of system sensitivity, denoted as ℋ− index, which measures the worst fault sensitivity. This paper is concerned with characterizing ℋ− index for linear discrete time systems. First, a necessary and sufficient condition on the lower bound of ℋ− index in finite time horizon for linear discrete time-varying systems is developed. It is characterized in terms of the existence of solution to a backward difference Riccati equation with an inequality constraint. The result is further extended to systems with unknown initial condition based on a modified ℋ− index. In addition, for linear time-invariant systems in infinite time horizon, based on the definition of the ℋ− index in frequency domain, a condition in terms of algebraic Riccati equation is developed. In comparison with the well-known bounded real lemma, it is found that ℋ− index is not completely dual to ℋ∞ norm. Finally, several numerical examples are given to illustrate the main results.

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

    Wu Chong

    2015-03-01

    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.

  12. 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)

    2011-07-01

    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)

  13. Beyond the Motagua and Polochic faults: Active strike-slip faulting along the Western North America-Caribbean plate boundary zone

    Guzmán-Speziale, Marco

    2010-12-01

    I investigate the role of two strike-slip faults in the tectonics of the western North America-Caribbean plate margin. The Ixcan fault, located in Guatemala north of the Polochic fault, is seismically active, with earthquakes of magnitude up to 5.7 reported recently. Fault-plane solutions along this curvilinear but generally E-W trending fault indicate left-lateral, strike-slip displacement. Several historic earthquakes appear to have taken place along the Ixcan fault since 1728, the largest one being the 1816 event ( M = 7.5). The NW-SE trending Concordia fault in southeastern Mexico appears to be the site of the great ( M = 7.6) earthquake of 1902. Isoseismals for this event suggest shallow, left-lateral strike-slip faulting. I propose a seismotectonic model in which both faults are part of the deformation associated to the North America-Caribbean plate boundary zone. Transpressive structures are found in the fault steps between strike-slip fault systems.

  14. 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

    2016-04-01

    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.

  15. Finding concealed active faults: Extending the southern Whidbey Island fault across the Puget Lowland, Washington

    Sherrod, Brian L.; Blakely, Richard J.; Weaver, Craig S.; Kelsey, Harvey M.; Barnett, Elizabeth; Liberty, Lee; Meagher, Karen L.; Pape, Kristin

    2008-05-01

    The southern Whidbey Island fault zone (SWIF), as previously mapped using borehole data, potential field anomalies, and marine seismic reflection surveys, consists of three subparallel, northwest trending strands extending ˜100 km from near Vancouver Island to the northern Puget Lowland. East of Puget Sound, the SWIF makes landfall between the cities of Seattle and Everett but is concealed beneath a thick mantle of young glacial deposits and vegetation. A ˜20-km-wide, northwest trending swath of subparallel, low-amplitude aeromagnetic anomalies crosses this region of the Puget Lowland and is on strike with the SWIF. The most prominent aeromagnetic anomaly, the Cottage Lake lineament, extends at least 18 km and lies approximately on strike with the SWIF on Whidbey Island. Subtle scarps and topographic lineaments on Pleistocene surfaces, visible on high-resolution lidar topography at a number of locations along the SWIF, lie on or near these magnetic anomalies. In the field, scarps exhibit northeast-side-up and vertical relief of 1 to 5 m. Excavations across several lidar scarps lying on or near magnetic anomalies show evidence for multiple folding and faulting events since deglaciation, most likely above buried reverse/oblique faults. Excavations in areas away from magnetic anomalies do not show evidence of tectonic deformation. In total, paleoseismological evidence suggests that the SWIF produced at least four earthquakes since deglaciation about 16,400 years ago, the most recent less than 2700 years ago.

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

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

    2014-01-01

    An active fault tolerant control (AFTC) method is proposed for discrete-time piecewise affine (PWA) systems. Only actuator faults are considered. The AFTC framework contains a supervisory scheme, which selects a suitable controller in a set of controllers such that the stability and an acceptable...

  17. 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...

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

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

    2015-01-01

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

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

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

    2013-01-01

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

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

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

    2011-01-01

    circuit faults have been developed. For other types of machines the single and partial turn short circuit is very difficult to deal with and requires normally very comprehensive detection and calculation schemes. The developed detection algorithm combined with the E-core transverse flux machine is...... extent also thermal. Since the E-core transverse flux-machine belongs to the family of the SRMs it has unique properties of intervals without current in the windings. By careful investigation of the voltage and current in these intervals a very simple method to detect single and partial turn short...

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

    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.

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

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

    2014-12-01

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

  3. Rolling bearing fault detection using an adaptive lifting multiwavelet packet with a 1(1/2) dimension spectrum

    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(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(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. (paper)

  4. Seismic design considerations for active faulting at Yucca Mountain, NV

    This paper explores the seismic hazard concerns at Yucca Mountain, NV that implicitly results from near field vibratory ground motion, fault displacement within the proposed repository block and the complexity that these two issues add to the siting and licensing process. Three major zones or belts of contemporary regional seismicity intersect in the Yucca Mountain, NV area, the proposed site for the nation's first high-level radioactive waste repository. Within a 1,000 sq. km area of the Yucca Mountain site, there are 32 known faults with demonstrated or suggested Quaternary displacements. Holocene displacement is evident on three of the faults. The maximum magnitude earthquake for the site is estimated to be somewhere between M 6.5--7.0. Free field peak ground acceleration from a maximum magnitude earthquake is estimated to range from 0.4--1.0 g. The maximum magnitude earthquake and resultant acceleration from movement on surface faults within the proposed repository block or on buried faults beneath the site without clear surface expression are estimated to be in the same range or larger. Due to the paucity of historical strong motion data recorded for near field earthquakes, estimate of potential ground motion and fault displacement effects within the repository block are extremely speculative

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

    Zhang, Yue; Dragoni, Nicola; Wang, Jiangtao

    2015-01-01

    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...

  6. Fault Detection of Aircraft System with Random Forest Algorithm and Similarity Measure

    Sanghyuk Lee

    2014-01-01

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

  7. Consideration of Gyroscopic Effect in Fault Detection and Isolation for Unbalance Excited Rotor Systems

    Zhentao Wang

    2012-01-01

    Full Text Available Fault detection and isolation (FDI in rotor systems often faces the problem that the system dynamics is dependent on the rotor rotary frequency because of the gyroscopic effect. In unbalance excited rotor systems, the continuously distributed unbalances are hard to be determined or estimated accurately. The unbalance forces as disturbances make fault detection more complicated. The aim of this paper is to develop linear time invariant (LTI FDI methods (i.e., with constant parameters for rotor systems under consideration of gyroscopic effect and disturbances. Two approaches to describe the gyroscopic effect, that is, as unknown inputs and as model uncertainties, are investigated. Based on these two approaches, FDI methods are developed and the results are compared regarding the resulting FDI performances. Results are obtained by the application in a rotor test rig. Restrictions for the application of these methods are discussed.

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

    Pengfei Guo

    2014-01-01

    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.

  9. A Delay System Approach to Fault Detection Filter of Networked Control Systems

    MA Li-wei; TIAN Zuo-hua; SHI Song-jiao; WENG Zheng-xin

    2009-01-01

    In this paper, the fault detection filter (FDF) design problem for networked control systems (NCSs) with both network-induced delay and data dropout is studied. Based on a new NCSs model proposed recently, an observer-based filter is introduced to be the residual generator and formulated as an H∞-optimization problem for systems with two successive delay components. By applying Lyapunov-Krasovskii approach, a new sufficient condition on stability and H∞ performance is derived for systems with two successive delay components in the state. A solution of the optimization problem is then presented in terms of linear matrix inequality (LMI) formulation, dependently of time delay. In order to detect the fault, the residual evaluation problem is also considered. An illustrative design example is employed to demonstrate the validity of the proposed approach.

  10. Fault detection and diagnosis of the deaerator level control system in nuclear power plants

    Kim, Kyung Youn; Lee, Yoon Joon [Cheju National Univ., Cheju (Korea, Republic of)

    2004-02-01

    The deaerator of a power plant is one of feedwater heaters in the secondary system, and it is located above the feedwater pumps. The feedwater pumps take the water from the deaerator storage tank, and the Net Positive Suction Head(NPSH) should always be ensured. To secure the sufficient NPSH, the deaerator tank is equipped with the level control system of which level sensors are critical items. And it is necessary to ascertain the sensor state on-line. For this, a model-based Fault Detection and Diagnosis(FDD) is introduced in this study. The dynamic control model is formulated from the relation of input-output flow rates and liquid-level of the deaerator storage tank. Then an adaptive state estimator is designed for the fault detection and diagnosis of sensors. The performance and effectiveness of the proposed FDD scheme are evaluated by applying the operation data of Yonggwang Units 3 and 4.

  11. 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

    1994-12-31

    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.

  12. Active fault, fault growth and segment linkage along the Janauri anticline (frontal foreland fold), NW Himalaya, India

    Malik, Javed N.; Shah, Afroz A.; Sahoo, Ajit K.; Puhan, B.; Banerjee, Chiranjib; Shinde, Dattatraya P.; Juyal, Navin; Singhvi, Ashok K.; Rath, Shishir K.

    2010-03-01

    The 100 km long frontal foreland fold — the Janauri anticline in NW Himalayan foothills represents a single segment formed due to inter-linking of the southern (JS1) and the northern (JS2) Janauri segments. This anticline is a product of the fault related fold growth that facilitated lateral propagation by acquiring more length and linkage of smaller segments giving rise to a single large segment. The linked portion marked by flat-uplifted surface in the central portion represents the paleo-water gap of the Sutlej River. This area is comparatively more active in terms of tectonic activity, well justified by the occurrence of fault scarps along the forelimb and backlimb of the anticline. Occurrence of active fault scarps on either side of the anticline suggests that the slip accommodated in the frontal part is partitioned between the main frontal thrust i.e. the Himalayan Frontal Thrust (HFT) and associated back-thrust. The uplift in the piedmont zone along southern portion of Janauri anticline marked by dissected younger hill range suggests fore-landward propagation of tectonic activity along newly developed Frontal Piedmont Thrust (FPT), an imbricated emergent thrust branching out from the HFT system. We suggests that this happened because the southern segment JS1 does not linked-up with the northwestern end of Chandigarh anticline segment (CS). In the northwestern end of the Janauri anticline, due to no structural asperity the tectonic activity on HFT was taken-up by two (HF1 — in the frontal part and HF2 — towards the hinterland side) newly developed parallel active faults ( Hajipur Fault) branched from the main JS2 segment. The lateral propagation and movements along HF1 and HF2 resulted in uplift of the floodplain as well as responsible for the northward shift of the Beas River. GPR and trench investigations suggest that earthquakes during the recent past were accompanied with surface rupture. OSL (optical stimulated luminescence) dates from the trench

  13. Non-stationary spectral estimation for wind turbine induction generator faults detection

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

    2013-01-01

    Development of large scale offshore wind and marine current turbine farms implies to minimize and predict maintenance operations. In direct- or indirect-drive, fixed- or variable-speed turbine generators, advanced signal processing tools are required to detect and diagnose the generator faults from vibration, acoustic, or generator current signals. The induction generator is traditionally used for wind turbines power generation. Even if induction machines are highly reliable, they are subject...

  14. Fault Detection And Diagnosis For Air Conditioners And Heat Pumps Based On Virtual Sensors

    Kim, Woohyun

    2013-01-01

    The primary goal of this research is to develop and demonstrate an integrated, on-line performance monitoring and diagnostic system with low cost sensors for air conditioning and heat pump equipment. Automated fault detection and diagnostics (FDD) has the potential for improving energy efficiency along with reducing service costs and comfort complaints. To achieve this goal, virtual sensors with low cost measurements and simple models were developed to estimate quantities that would be expens...

  15. Evaluating Fault Detection and Diagnostics Protocols Applied to Air-Cooled Vapor Compression Air-Conditioners

    Yuill, David P.; Braun, James E.

    2012-01-01

    Fault detection and diagnostics (FDD) tools are being increasingly applied in air-conditioning systems. There are many different protocols used in these FDD tools, so an important question to ask is: how well do the protocols work? This paper describes the ongoing development of the first standardized method of evaluation for FDD protocols applied to air-cooled vapor compression air-conditioning systems. The general approach is to feed a library of data – including temperatures, pressures, an...

  16. Fault Detection and Isolation in Industrial Systems Based on Spectral Analysis Diagnosis

    Attia Daoudi; Mouloud Guemana; Ahmed Hafaifa

    2013-01-01

    The diagnoses in industrial systems represent an important economic objective in process industrial automation area. To guarantee the safety and the continuity in production exploitation and to record the useful events with the feedback experience for the curative maintenance. We propose in this work to examine and illustrate the application ability of the spectral analysis approach, in the area of fault detection and isolation industrial systems. In this work, we use a combined analysis dia...

  17. FAULT DETECTION AND DIAGNOSIS USING A HYBRID DYNAMIC SIMULATOR: APPLICATION TO INDUSTRIAL RISK PREVENTION

    Olivier-Maget, Nelly; HETREUX, Gilles

    2014-01-01

    The main tool for the development of hazardous chemical syntheses in the field of fine chemicals and pharmaceuticals remains the batch reactor. Nevertheless, even if it offers the required flexibility and versatility, this reactor presents technological limitations. In particular, poor transfer of the heat generated by exothermic chemical reactions is a serious problem with regard to safety. In this context, a simple failure is considered as prejudicial. So, fault detection and diagnosis are ...

  18. From model, signal to knowledge: a data-driven perspective of fault detection and diagnosis

    Dai, Xuewu; Gao, Zhiwei

    2013-01-01

    This review paper is to give a full picture of fault detection and diagnosis (FDD) in complex systems from the perspective of data processing. As a matter of fact, an FDD system is a data-processing system on the basis of information redundancy, in which the data and human's understanding of the data are two fundamental elements. Human's understanding may be an explicit input-output model representing the relationship among the system's variables. It may also be represented as knowledge impli...

  19. Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms

    Dae-Ho Kwak; Dong-Han Lee; Jong-Hyo Ahn; Bong-Hwan Koh

    2013-01-01

    This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibrat...

  20. Intelligent alarms detection for the analysis of system fault impact on business

    Pace, C.; Russo, I; Fernández, V.; Britos, Paola Verónica; Rossi, Bibiana D.; García Martínez, Ramón

    1998-01-01

    The tools for fault impact analysis are important for the deployment of critical mission systems. These tools can be also used as a development phase aid. We introduce several concepts related to "business alarms". Business alarms are an approximation to the company's business conceptual scheme driven by the business rules from systems conceptual schemes. In order to specify them we propose the utilization of Knowledge Engineering typical techniques. The object of alarm detection for impa...

  1. The ground fault detection system for the Tore Supra toroidal pump limiter

    The toroidal pump limiter (TPL) of Tore Supra is electrically insulated from the vacuum-vessel, to allow its polarization at a voltage of up to 1 kV. In order to monitor continuously the integrity of the TPL electrical insulation, an electronic diagnostic system called TPL ground fault detection system (GFDS) has been developed. The paper will report on the design and the operation experience of the GFD system and on the evolution of the TPL grounding

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

    Chintan Bhatt; Asha Koshti; Hemant Agrawal; Zakiya Malek; Bhushan Trivedi

    2011-01-01

    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 application...

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

    Steffen Haus; Heiko Mikat; Martin Nowara; Surya Teja Kandukuri; Uwe Klingauf; Matthias Buderath

    2013-01-01

    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 th...

  4. Software fault detection and recovery in critical real-time systems: An approach based on loose coupling

    Highlights: •We analyze fault tolerance in mission-critical real-time systems. •Decoupled architectural model can be used to implement fault tolerance. •Prototype implementation for remote handling control system and service manager. •Recovery from transient faults by restarting services. -- Abstract: Remote handling (RH) systems are used to inspect, make changes to, and maintain components in the ITER machine and as such are an example of mission-critical system. Failure in a critical system may cause damage, significant financial losses and loss of experiment runtime, making dependability one of their most important properties. However, even if the software for RH control systems has been developed using best practices, the system might still fail due to undetected faults (bugs), hardware failures, etc. Critical systems therefore need capability to tolerate faults and resume operation after their occurrence. However, design of effective fault detection and recovery mechanisms poses a challenge due to timeliness requirements, growth in scale, and complex interactions. In this paper we evaluate effectiveness of service-oriented architectural approach to fault tolerance in mission-critical real-time systems. We use a prototype implementation for service management with an experimental RH control system and industrial manipulator. The fault tolerance is based on using the high level of decoupling between services to recover from transient faults by service restarts. In case the recovery process is not successful, the system can still be used if the fault was not in a critical software module

  5. Real-time fault detection for a waste-water treatment plant

    Automatic fault detection is becoming increasingly important in wastewater treatment plant operation, given the stringent treatment standards and the need to protect the investment costs from the potential damage of an unchecked fault propagating through the plant. This paper describes the development of a real-time Fault Detection and Isolation (FDI) system based on an adaptive Principal Component Analysis (PCA) algorithm, used to compare the current plant operation with a good behaviour model based on a preliminary set of data. The algorithm was developed in the Lab View 8.20 (National Instruments, Austin, TX, USA) platform for real-time operation in the compact Field Point, a Programmable Automation Controller by National Instruments supervising the plant operation. The FDI was tested with a large set of operational plant data with 1 hour sampling time from August 2007 through May 2008. Two time horizons were used in the analysis: a short term monthly horizon proved very reliable in isolating sensor failures and short duration disturbances such as spikes, whereas the long term horizon provided accurate detection of long-term drifts. The system robustness is enhanced by the use of multiple statistics, not only control charts but also contribution plots, which proved instrumental in discriminating among the various causes of malfunctioning.

  6. VIBRATION ANALYSIS FOR DETECTION AND LOCALIZATION THE FAULTS OF ROTATING MACHINERY USING WAVELET TECHINIQUES

    MIHAIL PRICOP

    2016-06-01

    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.

  7. DETECTION OF FAULT LOCATION ON THE POWER LINES 6–35 kV WITH UNILATERAL FEED

    F. A. Romaniuk

    2014-01-01

    Full Text Available The paper describes new algorithm of detecting the fault location for the power lines 6–35 kV with unilateral feed. The results of operational control of the short-circuit current for the faulted phases are the only initial data needed for the fault location algorithm. Analysis of the impact of the type of short circuit, transition resistance at the damaged point, errors of current transformers, load of the line, power and resistance of supply system, calculation errors of short-circuit currents at the beginning and at the end of the line on the performance of this algorithm is also performed. Estimated parameters of the algorithm of detecting the fault location based on identified influencing factors were established by method of computational experiment. Analysis of the simulation results performed shows that the variation of the relative error in the fault location determination for different types of faults is about the same. Moreover levels of these relative errors from the effects of all influencing factors can be less than just from one of them. This is due to the mutual compensation of the various factors’ influence on values of relative errors. This fact must be taken into consideration when performing the corresponding estimates for the worst case scenario.This paper presents the dynamic characteristics of this algorithm for detecting the fault location that allows estimating the time of detecting the fault location in different modes. Their analysis shows that there is almost no difference in quantitative and qualitative dependencies for different loads and types of faults. As the evaluation of results performed it should be noted that by means of the control only one parameter in short current mode, i.e. the short-circuit current, it is possibly with acceptable accuracy to detect the fault location. 

  8. 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

    2016-04-01

    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

  9. Mixed l-/l1 fault detection observer design for positive switched systems with time-varying delay via delta operator approach

    Li, Shuo; Xiang, Zhengrong; Karimi, Hamid Reza

    2014-01-01

    This paper investigates the problem of fault detection observer design for positive switched systems with time-varying delay via delta operator approach. A new fault sensitivity measure, called l-index, is proposed. The l- fault detection observer design and multi-objective l -/l1 fault detection observer design problems are addressed. Based on the average dwell time approach and the piecewise copositive type Lyapunov-Krasovskii functional method in delta domain, sufficient conditions for the...

  10. Results From NICLAKES Survey of Active Faulting Beneath Lake Nicaragua, Central American Volcanic Arc

    Funk, J.; Mann, P.; McIntosh, K.; Wulf, S.; Dull, R.; Perez, P.; Strauch, W.

    2006-12-01

    In May of 2006 we used a chartered ferry boat to collect 520 km of seismic data, 886 km of 3.5 kHz subbottom profiler data, and 35 cores from Lake Nicaragua. The lake covers an area of 7700 km2 within the active Central American volcanic arc, forms the largest lake in Central America, ranks as the twentieth largest freshwater lake in the world, and has never been previously surveyed or cored in a systematic manner. Two large stratovolcanoes occupy the central part of the lake: Concepcion is presently active, Maderas was last active less than 2000 years ago. Four zones of active faulting and doming of the lake floor were mapped with seismic and 3.5 kHz subbottom profiling. Two of the zones consist of 3-5-km-wide, 20-30-km-long asymmetric rift structures that trend towards the inactive cone of Maderas Volcano in a radial manner. The northeastern rift forms a 20-27-m deep depression on the lake bottom that is controlled by a north-dipping normal fault. The southwestern rift forms a 25-35-m deep depression controlled by a northeast-dipping normal fault. Both depressions contain mound-like features inferred to be hydrothermal deposits. Two zones of active faulting are associated with the active Concepcion stratovolcano. A 600-m-wide and 6-km-long fault bounded horst block extends westward beneath the lake from a promontory on the west side of the volcano. Like the two radial rift features of Maderas, the horst points roughly towards the active caldera of Concepcion. A second north-south zone of active faulting, which also forms a high, extends off the north coast of Concepcion and corresponds to a localized zone of folding and faulting mapped by previous workers and inferred by them to have formed by gravitational spreading of the flank of the volcano. The close spatial relation of these faults to the two volcanic cones in the lake suggests that the mechanism for faulting is a result of either crustal movements related to magma intrusion or gravitational sliding and is

  11. Active fault tolerant control research for nuclear power plant based on BP neural network

    In view of the sensor fault of nuclear power plant, the sensor was trained by adopting improved back propagation (BP) neural network method, and the dynamic model bank in different states was set up. The system was detected by using BP neural network in real time. When the sensor goes wrong, it will be controlled by reconstruction. Taking pressurizer as the case, a simulation experiment was performed on the nuclear power plant simulator. The results show that the proposed method is valid for the fault tolerant control of sensor faults in nuclear power plant. (authors)

  12. Correlation between the spatial distribution of radon anomalies and fault activity in the northern margin of West Qinling Fault Zone, Central China

    The spatial variations of soil gas in the northern edge of West Qinling Fault were investigated based on the field measurement of radon concentration. Radon concentrations highlighted a decreasing gradient from the middle segment to NW and SE along the fault and the fault zone was divided into three segments. We observed that the measured radon data showed a moderate positive correlation with relative fault activity. The hazard segment area was marked according to the relationship between the spatial concentration anomaly values of soil-gas radon and the seismotectonic background. (author)

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

    Ying-Yi Hong

    2014-04-01

    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.

  14. Development of Fault Detection and Diagnosis Schemes for Industrial Refrigeration Systems

    Thybo, C.; Izadi-Zamanabadi, Roozbeh

    2004-01-01

    The success of a fault detection and diagnosis (FDD) scheme depends not alone on developing an advanced detection scheme. To enable successful deployment in industrial applications, an economically optimal development of FDD schemes are required. This paper reviews and discusses the gained...... experiences achieved by employing a combination of various techniques, methods, and algorithms, which are proposed by academia, on an industrial application. The main focus is on sharing the "lessons learned" from developing and employing Faulttolerant functionalities to a controlled process in order to meet...... the industrial needs while satisfying economically motivated constraints....

  15. On linear observers and application to fault detection in synchronous generators

    Jan Erik STELLET; Tobias ROGG

    2014-01-01

    This work introduces an observer structure and highlights its distinct advantages in fault detection and isolation. Its application to the issue of shorted turns detection in synchronous generators is demonstrated. For the theoretical foundation, the convergence and design of Luenberger-type observers for disturbed linear time-invariant (LTI) single-input single-output (SISO) systems are reviewed with a particular focus on input and output disturbances. As an additional result, a simple observer design for stationary output disturbances that avoids a system order extension, as in classical results, is proposed.

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

    Mohammad Sadeq Garshasbi

    2013-12-01

    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.

  17. 222Rn activity in soil gas across selected fault segments in the Cantabrian Mountains, NW Spain

    222Rn activity in soil gas was measured across fault segments of the seismic active Ventaniella Fault and the seismic inactive Sabero-Gordón Fault in the Cantabrian Mountains, NW Spain, in order to investigate the variability of the 222Rn concentration. The sampling took place in summer and autumn 2010. During the autumn measurement program, an additional 222Rn soil gas mapping was carried out in the Sabero-Gordón research area. Zones of elevated 222Rn activity in the soil gas were identified by background 222Rn values of the geological formations used for mapping and local background values from 222Rn values outside the elevated 222Rn activity zones. Unexpectedly, the Sabero-Gordón Fault showed higher 222Rn activity, up to 441 kBqm−3, compared to the 222Rn activity of the Ventaniella Fault which had a maximum of 106 kBqm−3. Comparison of the results shows that the values measured in summer are about 5 times higher than the autumn values. This difference is not reflected in petrophysical soil parameters or meteorological conditions documented during the field measurements. Based on the results of our work we conclude that the magnitude of 222Rn concentration in soil gas is not an indicator of local seismic activity of the investigated faults. For the studied segment of the aseismic Sabero-Gordón Fault we suggest active genesis of pathways for gas migration driven by aseismic fault slip causing the elevated 222Rn activity in soil gas.

  18. Characterization of active fault scarps from medium to high resolution DEM: case studies from Central and Southern Apennines (Italy)

    Brunori, C.; Cinti, F. R.; Ventura, G.

    2013-12-01

    We identify geo-morphometric features of active fault scarps in Italy through a semiautomatic processing using GIS. Medium to high resolution DEM was used to characterize the geometry, structural, and erosive elements of two seismogenic normal faults in Central and Southern Apennines. The Pettino fault in L'Aquila area was detected using a 1 m pixel DEM derived from airborne LiDAR survey (Friuli Venezia Giulia Civil Protection). For the Castrovillari fault in northern Calabria region was used a 4 m pixel DEM (Regional Cartography Office of Regione Calabria). Scarp segments are region of planar discontinuities identified by selected values of DEM-derived Terrain Ruggedness Index (TRI) and Vector Ruggedness Measure (VRM). These planar discontinuities corresponds to landscape features such as, river terraces, roads scarps, and other natural or human features. The discrimination between these features have been accomplished overlaying extracted features on aerial photograph, geological and geomorphologic maps and in situ survey. After that, we perform the quantitative and statistical analysis of these areas identified as "fault scarps". The identification of elements relative to the scarps (e.g. base, crest, slope) is then obtained to derive the estimate of parameters describing the fault: altitude, height of the scarp, length, slope and aspect, Terrain Ruggedness Index (TRI) and Vector Ruggedness Measure (VRM). The spatial distribution of the extracted values was obtained through their statistical analysis. We analyze scarp parameters variations along the whole scarp extent, such as strike value from aspect variations, slope and profile curvature differences as indicators of tectonic and/or erosion activity. The combined analysis of the DEM-derived parameters allows us to (a) define aspects of three-dimensional scarp geometry, (b) decipher its geomorphological significance, and (c) estimate the long-term slip rate.

  19. Fracture-zone conditions on a recently active fault: insights from mineralogical and geochemical analyses of the Hirabayashi NIED drill core on the Nojima fault, southwest Japan, which ruptured in the 1995 Kobe earthquake

    Matsuda, Tatsuo; Omura, Kentaro; Ikeda, Ryuji; Arai, Takashi; Kobayashi, Kenta; Shimada, Koji; Tanaka, Hidemi; Tomita, Tomoaki; Hirano, Satoshi

    2004-01-01

    An 1800-m-deep borehole into the Nojima fault zone was drilled at Nojima-Hirabayashi, Japan, after the 1995 Hyogo-ken Nanbu (Kobe) earthquake. Three possible fracture zones were detected at depths of about 1140, 1300, and 1800 m. To assess these fracture zones in this recently active fault, we analyzed the distributions of fault rocks, minerals, and chemical elements in these zones. The central fault plane in the shallowest fracture zone was identified by foliated blue-gray gouge at a depth of 1140 m. The degree of fracturing was evidently greater in the hanging wall than in the footwall. Minerals detected in this zone were quartz, orthoclase, plagioclase, and biotite, as in the parent rock (granodiorite), and also kaolinite, smectite, laumontite, stilbite, calcite, ankerite, and siderite, which are related to hydrothermal alteration. Biotite was absent in both the hanging wall and footwall across the central fault plane, but it was absent over a greater distance from the central fault plane in the hanging wall than in the footwall. Major element compositions across this zone suggested that hydrothermal alteration minerals such as kaolinite and smectite occurred across the central fault plane for a greater distance in the hanging wall than in the footwall. Similarly, H 2O+ and CO 2 had higher concentrations in the hanging wall than in the footwall. This asymmetrical distribution pattern is probably due to the greater degree of wall-rock fracturing and associated alteration in the hanging wall. We attributed the characteristics of this zone to fault activity and fluid-rock interactions. We analyzed the other fracture zones along this fault in the same way. In the fracture zone at about 1300 m depth, we detected the same kinds of hydrothermal alteration minerals as in the shallower zone, but they were in fewer samples. We detected relatively little H 2O+ and CO 2, and little evidence for movement of the major chemical elements, indicating little past fluid

  20. Study on active faults and weekly observation around them using cellurose nitrate film for the earthquake prediction research program

    The track etch method, which is one of the geochemical survey methods for the mapping and detection of active faults and evaluation of their activities, has been applied to many sites for the purpose of the earth-quake prediction research program. The method conventionally measures relative radon concentration in the soil gas by counting the track density (tracks per cm2.day) recorded on a piece of cellurose nitrate film (2 x 3 cm) which is sensitive to α particles. Weekly observation to monitor radon concentration changes in the soil gas using it has been carried on, on the several active faults since 1978, as a part of the earthquake prediction research program. (author)

  1. Fault Diagnosis and Accommodation of LTI systems by modified Youla parameterization

    Minupriya A

    2012-06-01

    Full Text Available In this paper an Active Fault Tolerant Control (FTC scheme is proposed for Linear Time Invariant (LTI systems, which achieves fault diagnosis followed by fault accommodation. The fault diagnosis scheme is carried out in two steps; Fault detection followed by Fault isolation. Fault detection filter use the sensor measurements to generate residuals, which have a unique static pattern in response to each fault. Distortion in these static patterns generates the probability of the presence of fault. The fault accommodation scheme is carried out using the Generalized Internal Model Control (GIMC architecture, also known as modified Youla parameterization. In addition, performance indices are also evaluated to indicate that the resulting fault tolerant scheme can detect, identify and accommodate actuator and sensor faults under additive faults. The DC motor example is considered for the demonstration of the proposed scheme.

  2. Bond Graph Modelling for Fault Detection and Isolation of an Ultrasonic Linear Motor

    Mabrouk KHEMLICHE

    2010-12-01

    Full Text Available In this paper Bond Graph modeling, simulation and monitoring of ultrasonic linear motors are presented. Only the vibration of piezoelectric ceramics and stator will be taken into account. Contact problems between stator and rotor are not treated here. So, standing and travelling waves will be briefly presented since the majority of the motors use another wave type to generate the stator vibration and thus obtain the elliptic trajectory of the points on the surface of the stator in the first time. Then, electric equivalent circuit will be presented with the aim for giving a general idea of another way of graphical modelling of the vibrator introduced and developed. The simulations of an ultrasonic linear motor are then performed and experimental results on a prototype built at the laboratory are presented. Finally, validation of the Bond Graph method for modelling is carried out, comparing both simulation and experiment results. This paper describes the application of the FDI approach to an electrical system. We demonstrate the FDI effectiveness with real data collected from our automotive test. We introduce the analysis of the problem involved in the faults localization in this process. We propose a method of fault detection applied to the diagnosis and to determine the gravity of a detected fault. We show the possibilities of application of the new approaches to the complex system control.

  3. Fault-tolerant permanent-magnet synchronous machine drives: fault detection and isolation, control reconfiguration and design considerations

    MEINGUET, Fabien

    2012-01-01

    The need for efficiency, reliability and continuous operation has lead over the years to the development of fault-tolerant electrical drives for various industrial purposes and for transport applications. Permanent-magnet synchronous machines have also been gaining interest due to their high torque-to-mass ratio and high efficiency, which make them a very good candidate to reduce the weight and volume of the equipment.In this work, a multidisciplinary approach for the design of fault-tolerant...

  4. Fault Analysis of Space Station DC Power Systems-Using Neural Network Adaptive Wavelets to Detect Faults

    Momoh, James A.; Wang, Yanchun; Dolce, James L.

    1997-01-01

    This paper describes the application of neural network adaptive wavelets for fault diagnosis of space station power system. The method combines wavelet transform with neural network by incorporating daughter wavelets into weights. Therefore, the wavelet transform and neural network training procedure become one stage, which avoids the complex computation of wavelet parameters and makes the procedure more straightforward. The simulation results show that the proposed method is very efficient for the identification of fault locations.

  5. Improvement of Method for Distance Detection of Damaged Section at One-Phase Ground Fault in Urban Distributive Networks

    M. D. Diachenko

    2014-07-01

    Full Text Available Methodology for distance detection of ground fault point in the networks with an insulated neutral for cable lines with distributed loads and parameters of emergency mode have been developed in the paper. The paper proposes an algorithm of automatic one-phase ground fault in the urban cable distributive networks with indication of damage point. The possibility of centralized damage detection is considered in the paper.

  6. Improvement of Method for Distance Detection of Damaged Section at One-Phase Ground Fault in Urban Distributive Networks

    M. D. Diachenko; Mironov, A. S.; V. V. Bourlaka; Podnebennaya, S. K.

    2014-01-01

    Methodology for distance detection of ground fault point in the networks with an insulated neutral for cable lines with distributed loads and parameters of emergency mode have been developed in the paper. The paper proposes an algorithm of automatic one-phase ground fault in the urban cable distributive networks with indication of damage point. The possibility of centralized damage detection is considered in the paper.

  7. An Aspect-Oriented Programming-based approach to software development for fault detection in measurement systems

    Arpaia, P; Inglese, Vitaliano; Bernardi, Mario Luca; Di Lucca, Giuseppe; Spiezia, Giovanni

    2010-01-01

    An Aspect-Oriented Programming-based approach to the development of software components for fault detection in automatic measurement systems is proposed. Faults are handled by means of specific software units, the ``aspects{''}, in order to better modularize issues transversal to several components. As a case study, this approach was applied to the design of the fault detection software inside a flexible framework for magnetic measurements, developed at the European Organization for Nuclear Research (CERN). Experimental results of software modularity and performance measurements for comparing aspect- and objectoriented solutions in rotating coils tests on superconducting magnets are reported. (C) 2009 Elsevier B.V. All rights reserved.

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

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

    2010-01-01

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

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

    Jinna Li

    2012-01-01

    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.

  10. Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications

    Wang, Yanxue; Xiang, Jiawei; Markert, Richard; Liang, Ming

    2016-01-01

    Condition-based maintenance via vibration signal processing plays an important role to reduce unscheduled machine downtime and avoid catastrophic accidents in industrial enterprises. Many machine faults, such as local defects in rotating machines, manifest themselves in the acquired vibration signals as a series of impulsive events. The spectral kurtosis (SK) technique extends the concept of kurtosis to that of a function of frequency that indicates how the impulsiveness of a signal. This work intends to review and summarize the recent research developments on the SK theories, for instance, short-time Fourier transform-based SK, kurtogram, adaptive SK and protrugram, as well as the corresponding applications in fault detection and diagnosis of the rotating machines. The potential prospects of prognostics using SK technique are also designated. Some examples have been presented to illustrate their performances. The expectation is that further research and applications of the SK technique will flourish in the future, especially in the fields of the prognostics.

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

    Imaouchen Yacine

    2015-01-01

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

  12. Model-Based Water Wall Fault Detection and Diagnosis of FBC Boiler Using Strong Tracking Filter

    Li Sun

    2014-01-01

    Full Text Available Fluidized bed combustion (FBC boilers have received increasing attention in recent decades. The erosion issue on the water wall is one of the most common and serious faults for FBC boilers. Unlike direct measurement of tube thickness used by ultrasonic methods, the wastage of water wall is reconsidered equally as the variation of the overall heat transfer coefficient in the furnace. In this paper, a model-based approach is presented to estimate internal states and heat transfer coefficient dually from the noisy measurable outputs. The estimated parameter is compared with the normal value. Then the modified Bayesian algorithm is adopted for fault detection and diagnosis (FDD. The simulation results demonstrate that the approach is feasible and effective.

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

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

    2009-01-01

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

  14. Design of the instrument fault detection for TRIGA Mark II Bandung

    The instrument fault detection of Bandung trigra mark II reactor has been designed. The validated reactor model was applied to design three instruments observers which each of them will estimate the reactor power, fuel element and coolant water temperatures. the observer inputs were the inputs and outputs of the system. By comparing the outputs of each observer, the faulty instrument can be determined. The result obtained from the reactor simulation show that there is no deviation in the steady state between observers and the model. All state variable of observer 1 are sensitive to power changes that these variables can be used to determine whether the fault occurs or not. On the contrary, only the 6th and 70th suite variables of observer 2 and 3 can be used to determine the instrument condition because these variables are sensitive to fuel element temperature changes for observer 2 and sensitive to coolant water temperature changes for observer 3. (author)

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

    Yu, Han

    2014-08-05

    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.

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

    Wenna Zhang

    2016-04-01

    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.

  17. 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

    2016-04-01

    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.

  18. Multi-attribute ant-tracking and neural network for fault detection: a case study of an Iranian oilfield

    Fault detection is one of the most important steps in seismic interpretation in both exploration and development phases. A variety of seismic attributes enhancing fault visualization and detection have been used by many interpreters. Geometric seismic attributes such as coherency and curvature have been successfully applied in delineating faults in sedimentary basins. Seismic attributes are often sensitive to noise and it is necessary to reduce noise and enhance the seismic quality before computing the attributes. In this study, after enhancing the quality of the seismic data, several different seismic attributes sensitive to discontinuities such as similarity and curvature were computed and applied to a 3D seismic dataset and their effective parameters were explained. Ant-tracking as an algorithm that captures continuous features was used to improve fault visualization. Ant-tracking was applied to different fault-sensitive attributes and their results were compared. Also artificial neural networks were used for combining multiple attributes into a single image to allow us to visually cluster different fault-sensitive attributes. The area of this study was an oilfield in the South West of Iran lying in the Zagros thrust belt. Results showed that the similarity and the most-positive curvature could detect faults and fractures more properly than the other attributes and applying the ant-tracking algorithm provided better interpretable information for studying faults and subtle faults. Results proved that applying ant-tracking to the most-positive curvature attribute was more acceptable than the dip attribute or even the similarity in this field. Also by an unsupervised neural network, different ant-tracking volumes were integrated into one volume and faults with more probability were clustered in one group. (paper)

  19. Zipper Faults

    Platt, J. P.; Passchier, C. W.

    2015-12-01

    Intersecting simultaneously active pairs of faults with different orientations and opposing slip sense ("conjugate faults") present geometrical and kinematic problems. Such faults rarely offset each other, even when they have displacements of many km. A simple solution to the problem is that the two faults merge, either zippering up or unzippering, depending on the relationship between the angle of intersection and the slip senses. A widely recognized example of this is the so-called blind front developed in some thrust belts, where a backthrust branches off a decollement surface at depth. The decollement progressively unzippers, so that its hanging wall becomes the hanging wall of the backthrust, and its footwall becomes the footwall of the active decollement. The opposite situation commonly arises in core complexes, where conjugate low-angle normal faults merge to form a single detachment; in this case the two faults zipper up. Analogous situations may arise for conjugate pairs of strike-slip faults. We present kinematic and geometrical analyses of the Garlock and San Andreas faults in California, the Najd fault system in Saudi Arabia, the North and East Anatolian faults, the Karakoram and Altyn Tagh faults in Tibet, and the Tonale and Guidicarie faults in the southern Alps, all of which appear to have undergone zippering over distances of several tens to hundreds of km. The zippering process may produce complex and significant patterns of strain and rotation in the surrounding rocks, particularly if the angle between the zippered faults is large. A zippering fault may be inactive during active movement on the intersecting faults, or it may have a slip rate that differs from either fault. Intersecting conjugate ductile shear zones behave in the same way on outcrop and micro-scales.

  20. A FAULT DETECTION SENSOR FOR CIRCUIT AGING USING DOUBLE-EDGE-TRIGGERED FLIP-FLOP

    Yan Luming; Liang Huaguo; Huang Zhengfeng; Liu Yanbin

    2013-01-01

    In nanoscale technology,transistor aging is one of the most critical problems that impact on the reliability of circuits.Aging sensor is a good online way to detect the circuit aging,which performs during the operating time with no influence of the normal operation of circuits.In this paper,a Double-edge-triggered Detection Sensor for circuit Aging (DSDA) is proposed,which employs data signal of logic circuits as its clock to control the sampling process.The simulation is done by Hspice using 45 nm technology.The results show that this technique is not sensitive to the process variations.The worst case of the detection precision is more than 80% under the different process variations.It can detect aging fault effectively with the 8% power cost and 30% performance cost.

  1. 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

    2008-01-01

    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.

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

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

    2016-05-01

    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.

  3. Active fault creep variations at Chihshang, Taiwan, revealed by creep meter monitoring, 1998-2001

    Lee, Jian-Cheng; Angelier, Jacques; Chu, Hao-Tsu; Hu, Jyr-Ching; Jeng, Fu-Shu; Rau, Ruey-Juin

    2003-11-01

    The daily creep meter data recorded at Chihshang in 1998-2001 are presented. The Chihshang creep meter experiment was set up across the Chihshang thrust fault, the most active segment of the Longitudinal Valley Fault, which is the present-day plate suture between the Eurasian and the Philippine Sea plates in eastern Taiwan. Near-continuous data recording at two sites revealed different surface fault motions yet similar annual shortening rates: 16.2 mm at the Tapo site (comprising two connected creep meters) and 15.0 mm at the Chinyuan site (three creep meters straddling parallel fault branches). Four of the five creep meters showed a seasonal variation, with the fault moving steadily during the rainy season from April to October, and remaining quiescent during the rest of the year. The only exception was recorded by the creep meter located on a mélange-composed hillslope, where local gravitational landsliding played an additional role other than tectonic faulting. Through comparison with daily precipitation data, we inferred that moderate rainfall suffices to trigger or facilitate slippage on the surface fault, during the transition period of the dry/wet season. During the observation period from 1998 to 2001, the subsurface seismicity exhibited clusters of microearthquakes on the Chihshang Fault at depths of 10-25 km. Recurrent earthquakes occurred regardless of whether the season was wet or dry, indicating that the stress relaxation associated with seismicity in the seismogenic zone did not transfer immediately up to the surface. The accumulated strain on the Chihshang Fault at shallow surface levels was released through creep during the wet season. In addition to these short-term seasonal variations, an apparent decrease in the annual slipping rate on the Chihshang Fault during the last few years deserves further investigation in order to mitigate against seismic hazard.

  4. 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

    2004-01-01

    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.

  5. 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

  6. 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

  7. An angle-based subspace anomaly detection approach to high-dimensional data: With an application to industrial fault detection

    The accuracy of traditional anomaly detection techniques implemented on full-dimensional spaces degrades significantly as dimensionality increases, thereby hampering many real-world applications. This work proposes an approach to selecting meaningful feature subspace and conducting anomaly detection in the corresponding subspace projection. The aim is to maintain the detection accuracy in high-dimensional circumstances. The suggested approach assesses the angle between all pairs of two lines for one specific anomaly candidate: the first line is connected by the relevant data point and the center of its adjacent points; the other line is one of the axis-parallel lines. Those dimensions which have a relatively small angle with the first line are then chosen to constitute the axis-parallel subspace for the candidate. Next, a normalized Mahalanobis distance is introduced to measure the local outlier-ness of an object in the subspace projection. To comprehensively compare the proposed algorithm with several existing anomaly detection techniques, we constructed artificial datasets with various high-dimensional settings and found the algorithm displayed superior accuracy. A further experiment on an industrial dataset demonstrated the applicability of the proposed algorithm in fault detection tasks and highlighted another of its merits, namely, to provide preliminary interpretation of abnormality through feature ordering in relevant subspaces. - Highlights: • An anomaly detection approach for high-dimensional reliability data is proposed. • The approach selects relevant subspaces by assessing vectorial angles. • The novel ABSAD approach displays superior accuracy over other alternatives. • Numerical illustration approves its efficacy in fault detection applications

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

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

    2010-10-01

    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.

  9. Bearing Fault Detection Using Multi-Scale Fractal Dimensions Based on Morphological Covers

    Pei-Lin Zhang

    2012-01-01

    Full Text Available Vibration signals acquired from bearing have been found to demonstrate complicated nonlinear characteristics in literature. Fractal geometry theory has provided effective tools such as fractal dimension for characterizing the vibration signals in bearing faults detection. However, most of the natural signals are not critical self-similar fractals; the assumption of a constant fractal dimension at all scales may not be true. Motivated by this fact, this work explores the application of the multi-scale fractal dimensions (MFDs based on morphological cover (MC technique for bearing fault diagnosis. Vibration signals from bearing with seven different states under four operations conditions are collected to validate the presented MFDs based on MC technique. Experimental results reveal that the vibration signals acquired from bearing are not critical self-similar fractals. The MFDs can provide more discriminative information about the signals than the single global fractal dimension. Furthermore, three classifiers are employed to evaluate and compare the classification performance of the MFDs with other feature extraction methods. Experimental results demonstrate the MFDs to be a desirable approach to improve the performance of bearing fault diagnosis.

  10. Triggered tremors beneath the seismogenic zone of an active fault zone, Kyushu, Japan

    Miyazaki, Masahiro; Matsumoto, Satoshi; Shimizu, Hiroshi

    2015-11-01

    Non-volcanic tremors were induced by the surface waves of the 2012 Sumatra earthquake around the Hinagu fault zone in Kyushu, Japan. We inferred from dense seismic observation data that the hypocenters of these tremors were located beneath the seismogenic zone of the Hinagu fault. Focal mechanisms of the tremors were estimated using S-wave polarization angles. The estimated focal mechanisms show similarities to those of shallow earthquakes in this region. In addition, one of the nodal planes of the focal mechanisms is almost parallel to the strike direction of the Hinagu fault. These observations suggest that the tremors were triggered at the deeper extension of the active fault zone under stress conditions similar to those in the shallower seismogenic region. A low-velocity anomaly beneath the hypocentral area of the tremors might be related to the tremor activity.

  11. Multiple tests for wind turbine fault detection and score fusion using two- level multidimensional scaling (MDS)

    Ye, Xiang; Gao, Weihua; Yan, Yanjun; Osadciw, Lisa A.

    2010-04-01

    Wind is an important renewable energy source. The energy and economic return from building wind farms justify the expensive investments in doing so. However, without an effective monitoring system, underperforming or faulty turbines will cause a huge loss in revenue. Early detection of such failures help prevent these undesired working conditions. We develop three tests on power curve, rotor speed curve, pitch angle curve of individual turbine. In each test, multiple states are defined to distinguish different working conditions, including complete shut-downs, under-performing states, abnormally frequent default states, as well as normal working states. These three tests are combined to reach a final conclusion, which is more effective than any single test. Through extensive data mining of historical data and verification from farm operators, some state combinations are discovered to be strong indicators of spindle failures, lightning strikes, anemometer faults, etc, for fault detection. In each individual test, and in the score fusion of these tests, we apply multidimensional scaling (MDS) to reduce the high dimensional feature space into a 3-dimensional visualization, from which it is easier to discover turbine working information. This approach gains a qualitative understanding of turbine performance status to detect faults, and also provides explanations on what has happened for detailed diagnostics. The state-of-the-art SCADA (Supervisory Control And Data Acquisition) system in industry can only answer the question whether there are abnormal working states, and our evaluation of multiple states in multiple tests is also promising for diagnostics. In the future, these tests can be readily incorporated in a Bayesian network for intelligent analysis and decision support.

  12. Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection

    Reljić Dejan

    2015-01-01

    Full Text Available In this paper, a suitable method for the on-line detection of the airgap mixed eccentricity fault in a three-phase cage induction motor has been proposed. The method is based on a Motor Current Signature Analysis (MCSA approach, a technique that is often used for an induction motor condition monitoring and fault diagnosis. It is based on the spectral analysis of the stator line current signal and the frequency identification of specific components, which are created as a result of motor faults. The most commonly used method for the current signal spectral analysis is based on the Fast Fourier transform (FFT. However, due to the complexity and memory demands, the FFT algorithm is not always suitable for real-time systems. Instead of the whole spectrum analysis, this paper suggests only the spectral analysis on the expected airgap fault frequencies employing the Goertzel’s algorithm to predict the magnitude of these frequency components. The method is simple and can be implemented in real-time airgap mixed eccentricity monitoring systems without much computational effort. A low-cost data acquisition system, supported by the LabView software, has been used for the hardware and software implementation of the proposed method. The method has been validated by the laboratory experiments on both the line-connected and the inverter-fed three-phase fourpole cage induction motor operated at the rated frequency and under constant load at a few different values. In addition, the results of the proposed method have been verified through the motor’s vibration signal analysis. [Projekat Ministarstva nauke Republike Srbije, br. III42004

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

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

    2016-01-01

    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

  14. 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

    2016-01-01

    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

  15. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

  16. Implementation of a Fractional Model-Based Fault Detection Algorithm into a PLC Controller

    Kopka, Ryszard

    2014-12-01

    This paper presents results related to the implementation of model-based fault detection and diagnosis procedures into a typical PLC controller. To construct the mathematical model and to implement the PID regulator, a non-integer order differential/integral calculation was used. Such an approach allows for more exact control of the process and more precise modelling. This is very crucial in model-based diagnostic methods. The theoretical results were verified on a real object in the form of a supercapacitor connected to a PLC controller by a dedicated electronic circuit controlled directly from the PLC outputs.

  17. Fault detection in non-linear systems based on type-2 fuzzy logic

    Safarinejadian, Behrooz; Ghane, Parisa; Monirvaghefi, Hossein

    2015-02-01

    This paper presents a new method for fault detection (FD) based on interval type-2 fuzzy sets. The main idea is based on a confident span using interval type-2 fuzzy systems. An estimate for upper and lower bounds of output has been taken using the designing of an optimal fuzzy system through clustering. Finally the method has been tested in two non-linear systems, a two-tank with a fluid flow and pH neutralisation process, and it is compared with a well-known method named ANFIS. Furthermore, the mathematical model and the results of simulations prove the effectiveness, usefulness and applications of our new method.

  18. Modeling and simulation of a reformate supplied PEM fuel cell stack, application to fault detection

    Najafi, Masoud; Dipenta, Damiano; Bencherif, Karim; Sorine, Michel

    2007-01-01

    A method to reduce the model of a nonlinear dynamic fuel cell stack, which is suitable for control and fault detection studies, is presented. In order to model the fuel cell stack, we have assumed that the fuel cells are arranged in a stack, electrically in series, with thermal and electrical contacts. Since in practical applications a stack may be composed of several (at least fifty) fuel cells, such model will be a large set of differential equations which may be difficult to simulate espec...

  19. Machine fault detection and failure prediction via measurement of the dynamic response in the frequency domain

    It is shown that some common machine structural failures can be identified on-line by monitoring in some chosen characteristic frequency response functions. The response signatures are shown to be insensitive to variations in machine loading and, by suitable location of vibration monitoring points, can be used to accurately locate and identify the cause of failure. The method is used to identify faults such as shaft misalignment and bearing failures on a high speed motor-pump assembly and to detect and predict fatigue failures in shafts subjected to torsional loads. (author)

  20. Sensor fault detection in nuclear power plants using multivariate state estimation technique and support vector machines

    Recent developments in artificial intelligence at Argonne National Laboratory (ANL) have culminated in the capability to perform nuclear power plant sensor validation and early fault detection in an integrated package called the Multivariate State Estimation Technique (MSET). Nuclear reactor signals are validated by comparing signal prototypes with the actual reactor signals. Residuals from these comparisons are used in a sensitive hypothesis testing method, the Sequential Probability Ratio Test (SPRT). The SPRT examines the stochastic components of the residuals and can detect if the statistical characteristics begin to change. The signal prototypes are estimated based on empirical data. The property of an estimation algorithm to make predictions on limited amount of data is designated as generalization ability. It is a very important issue in algorithm selection. Recently, we included a new machine learning algorithm called the Support Vector Machines (SVM) in the estimation module of MSET. In the SVM algorithm, the input data space (set of reactor signals) is transformed into a high-dimensional nonlinear space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In particular, we implemented and tested several kernels developed at Argonne National Laboratory. Our recent results indicated that the combination of MSET kernels with the SVM method has better noise reduction and generalization properties than the standard MSET algorithm. In this paper we compare fault detection properties of these algorithms. (author)