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Sample records for active fault detection

  1. Active fault detection in MIMO systems

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2014-01-01

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

  2. Controller modification applied for active fault detection

    DEFF Research Database (Denmark)

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

    2014-01-01

    This paper is focusing on active fault detection (AFD) for parametric faults in closed-loop systems. This auxiliary input applied for the fault detection will also disturb the external output and consequently reduce the performance of the controller. Therefore, only small auxiliary inputs are used...... 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. Model-based fault detection and isolation for intermittently active faults with application to motion-based thruster fault detection and isolation for spacecraft

    Science.gov (United States)

    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.

  4. Active Fault Detection and Isolation for Hybrid Systems

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  5. Active Fault Isolation in MIMO Systems

    DEFF Research Database (Denmark)

    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...

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

    Directory of Open Access Journals (Sweden)

    Ducard Guillaume J.J.

    2015-03-01

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

  7. Network Power Fault Detection

    OpenAIRE

    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

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1999-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

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

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2006-01-01

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

  11. Study of Active Faults in the Three Gorges Dam region by Detecting and Relocating Aftershocks

    Science.gov (United States)

    Huang, R.; Zhu, L.; Xu, Y.

    2014-12-01

    Seismicity in the Three Gorges Dam (TGD) region and its adjacent areas increased dramatically as the water- level of the TGD reservoir rises since its completion in 2003. Accordingly, many efforts have been put forward to quantify the seismicity and geological hazards in the region. However, the precise detective of earthquakes, especially for the minor ones, remains difficulty because of sparse distribution of permanent seismic stations. From December 2013 to June 2014, we deployed 30 three-component broadband seismic stations in the TGD region. During the deployment, we recorded two earthquakes of magnitudes lager than 5.0, one occurred on December 16th 2013 in Badong and another on March 30th 2014 in Zigui. We firstly used a sliding-window cross-correlation (SCC) detection technique to supplement the events catalog from the China Earthquake Networks Center. Over 500 new events with ML lager than 0.5 were detected. We then relocated 502 events out of the total 987 events using the double-difference (DD) relocation algorithm. We also determined moment tensors of some large earthquakes using gCAP. The results clearly show two active faults along Yangtze River with dips of 50 degrees and 90 degrees to a maximum depth of 10 km, respectively. And they also reveal that water might have permeated to a depth of 6 km corresponds to the interface of sediments and metamorphic basement beneath Zigui Basin. We thus preliminarily judge that the quakes are triggered by local stress adjustment resulting of fluctuation of Three Gorges reservoir's loading.

  12. Final Technical Report: PV Fault Detection Tool.

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-12-01

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

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

    Science.gov (United States)

    Hagag, Wael; Obermeyer, Hennes

    2016-01-01

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

  14. The property of fault zone and fault activity of Shionohira Fault, Fukushima, Japan

    Science.gov (United States)

    Seshimo, K.; Aoki, K.; Tanaka, Y.; Niwa, M.; Kametaka, M.; Sakai, T.; Tanaka, Y.

    2015-12-01

    The April 11, 2011 Fukushima-ken Hamadori Earthquake (hereafter the 4.11 earthquake) formed co-seismic surface ruptures trending in the NNW-SSE direction in Iwaki City, Fukushima Prefecture, which were newly named as the Shionohira Fault by Ishiyama et al. (2011). This earthquake was characterized by a westward dipping normal slip faulting, with a maximum displacement of about 2 m (e.g., Kurosawa et al., 2012). To the south of the area, the same trending lineaments were recognized to exist even though no surface ruptures occurred by the earthquake. In an attempt to elucidate the differences of active and non-active segments of the fault, this report discusses the results of observation of fault outcrops along the Shionohira Fault as well as the Coulomb stress calculations. Only a few outcrops have basement rocks of both the hanging-wall and foot-wall of the fault plane. Three of these outcrops (Kyodo-gawa, Shionohira and Betto) were selected for investigation. In addition, a fault outcrop (Nameishi-minami) located about 300 m south of the southern tip of the surface ruptures was investigated. The authors carried out observations of outcrops, polished slabs and thin sections, and performed X-ray diffraction (XRD) to fault materials. As a result, the fault zones originating from schists were investigated at Kyodo-gawa and Betto. A thick fault gouge was cut by a fault plane of the 4.11 earthquake in each outcrop. The fault materials originating from schists were fault bounded with (possibly Neogene) weakly deformed sandstone at Shionohira. A thin fault gouge was found along the fault plane of 4.11 earthquake. A small-scale fault zone with thin fault gouge was observed in Nameishi-minami. According to XRD analysis, smectite was detected in the gouges from Kyodo-gawa, Shionohira and Betto, while not in the gouge from Nameishi-minami.

  15. Fault Detection for Nonlinear Systems

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, H.H.

    1998-01-01

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

  16. Robust fault detection filter design

    Science.gov (United States)

    Douglas, Randal Kirk

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

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

    CERN Document Server

    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

  18. Exact, almost and delayed fault detection

    DEFF Research Database (Denmark)

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

    1999-01-01

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

  19. Fundamental problems in fault detection and identification

    DEFF Research Database (Denmark)

    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...

  20. A new fault detection method for computer networks

    International Nuclear Information System (INIS)

    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

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

    DEFF Research Database (Denmark)

    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...

  2. Integration of control and fault detection

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Stoustrup, J.

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

  3. Fault Detection for a Diesel Engine Actuator

    DEFF Research Database (Denmark)

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

    1995-01-01

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

  4. 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

    Science.gov (United States)

    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

  5. Faults in clays their detection and properties

    International Nuclear Information System (INIS)

    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

  6. Aluminium Process Fault Detection and Diagnosis

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Ogata, Y.

    2006-12-01

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

  8. Fault Detection and Isolation for Spacecraft

    DEFF Research Database (Denmark)

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2002-01-01

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

  9. Detecting Fan Faults in refrigerated Cabinets

    DEFF Research Database (Denmark)

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

    2002-01-01

    Fault detection in supermarket refrigeration systems is an important topic due to both economic and food safety reasons. If faults can be detected and diagnosed before the system drifts outside the specified operational envelope, service costs can be reduced and in extreme cases the costly...... 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...

  10. Fault Detection and Isolation using Eigenstructure Assignment

    DEFF Research Database (Denmark)

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

    1994-01-01

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

  11. Verification-based Software-fault Detection

    OpenAIRE

    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.

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

    Science.gov (United States)

    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

  13. DATA-MINING BASED FAULT DETECTION

    Institute of Scientific and Technical Information of China (English)

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

    2005-01-01

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

  14. Linear discriminant analysis for welding fault detection

    International Nuclear Information System (INIS)

    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.

  15. Fault Detection for Quantized Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Wei-Wei Che

    2013-01-01

    Full Text Available The fault detection problem in the finite frequency domain for networked control systems with signal quantization is considered. With the logarithmic quantizer consideration, a quantized fault detection observer is designed by employing a performance index which is used to increase the fault sensitivity in finite frequency domain. The quantized measurement signals are dealt with by utilizing the sector bound method, in which the quantization error is treated as sector-bounded uncertainty. By using the Kalman-Yakubovich-Popov (GKYP Lemma, an iterative LMI-based optimization algorithm is developed for designing the quantized fault detection observer. And a numerical example is given to illustrate the effectiveness of the proposed method.

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

    Directory of Open Access Journals (Sweden)

    Anamika Yadav

    2014-01-01

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

  17. Online Distributed Fault Detection of Sensor Measurements

    Institute of Scientific and Technical Information of China (English)

    GAO Jianliang; XU Yongjun; LI Xiaowei

    2007-01-01

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

  18. Fault Detection under Fuzzy Model Uncertainty

    Institute of Scientific and Technical Information of China (English)

    Marek Kowal; Józef Korbicz

    2007-01-01

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

  19. Fault Detection for Shipboard Monitoring and Decision Support Systems

    DEFF Research Database (Denmark)

    Lajic, Zoran; Nielsen, Ulrik Dam

    2009-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-01-01

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

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

    NARCIS (Netherlands)

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

    2011-01-01

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

  2. Active fault diagnosis by controller modification

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    2010-01-01

    Two active fault diagnosis methods for additive or parametric faults are proposed. Both methods are based on controller reconfiguration rather than on requiring an exogenous excitation signal, as it is otherwise common in active fault diagnosis. For the first method, it is assumed that the system...... considered is controlled by an observer-based controller. The method is then based on a number of alternate observers, each designed to be sensitive to one or more additive faults. Periodically, the observer part of the controller is changed into the sequence of fault sensitive observers. This is done...... in a way that guarantees the continuity of transition and global stability using a recent result on observer parameterization. An illustrative example inspired by a field study of a drag racing vehicle is given. For the second method, an active fault diagnosis method for parametric faults is proposed...

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

    Directory of Open Access Journals (Sweden)

    Jianyong Yao

    2014-01-01

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

  4. RepTFD: Replay Based Transient Fault Detection

    OpenAIRE

    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 ...

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

    International Nuclear Information System (INIS)

    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

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

    Institute of Scientific and Technical Information of China (English)

    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

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

    DEFF Research Database (Denmark)

    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...

  8. Techniques for Surveying Urban Active Faults by Seismic Methods

    Institute of Scientific and Technical Information of China (English)

    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.

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

    DEFF Research Database (Denmark)

    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...

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Directory of Open Access Journals (Sweden)

    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. 

  12. FUZZY FAULT DETECTION FOR PERMANENT MAGNET SYNCHRONOUS GENERATOR

    Directory of Open Access Journals (Sweden)

    N. Selvaganesan

    2011-07-01

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

  13. Fault Detection and Isolation in Centrifugal Pumps

    DEFF Research Database (Denmark)

    Kallesøe, Carsten

    Centrifugal pumps are used in a variety of different applications, such as water supply, wastewater, and different industrial applications. Some pump installations are crucial for the applications to work. Failures can lead to substantial economic losses and can influence the life of many people...... 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...... are tested on an industrial test setup, showing the usability of the algorithms on a real centrifugal pump....

  14. Frequency Based Fault Detection in Wind Turbines

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2014-01-01

    In order to obtain lower cost of energy for wind turbines fault detection and accommodation is important. Expensive condition monitoring systems are often used to monitor the condition of rotating and vibrating system parts. One example is the gearbox in a wind turbine. This system is operated...... gearbox. Only the generator speed measurement which is available in even simple wind turbine control systems is used as input. Consequently this proposed scheme does not need additional sensors and computers for monitoring the condition of the wind gearbox. The scheme is evaluated on a wide-spread wind...

  15. Optimal Robust Fault Detection for Linear Discrete Time Systems

    Directory of Open Access Journals (Sweden)

    Nike Liu

    2008-01-01

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

  16. Additional Fault Detection Test Case Prioritization

    Directory of Open Access Journals (Sweden)

    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.

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

    DEFF Research Database (Denmark)

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

    2005-01-01

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

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

    International Nuclear Information System (INIS)

    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.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    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...... normal and faulty conditions. Thus a fault detection system and a fault tolerant controller has been designed and combined. The fault tolerant control system has then been tested and compared to the reference system and shows improvement on all measures....

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

    Science.gov (United States)

    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.

  1. Illuminating Northern California’s Active Faults

    Science.gov (United States)

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

    2009-01-01

    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 EarthTM 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)

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

    Science.gov (United States)

    Zhong, Guang-Xin; Yang, Guang-Hong

    2015-09-01

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

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

    Science.gov (United States)

    Joshi, Suresh M.

    2012-01-01

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

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

    DEFF Research Database (Denmark)

    Lootsma, T.F.

    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......-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...... control software to handle the effects of the particular fault event. In the past mainly linear FDI methods were developed, but as most industrial plants show nonlinear behavior, nonlinear methods for fault diagnosis could probably perform better. This thesis considers the design of FDI for nonlinear...

  5. Model Based Incipient Fault Detection for Gear Drives

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

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

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

    CERN Document Server

    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 ...

  7. Model Based Fault Detection in a Centrifugal Pump Application

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  8. Kalman Filter Application to Symmetrical Fault Detection during Power Swing

    DEFF Research Database (Denmark)

    Khodaparast, Jalal; Silva, Filipe Miguel Faria da; Khederzadeh, M.;

    2016-01-01

    The main purpose of power swing blocking is to distinguish faults from power swings. However, faults occurred during a power swing should still be detected and cleared promptly. This paper proposes an index based on detecting abrupt jump of impedance trajectory by utilization of predicting capabi...

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

    CERN Document Server

    Li, Linlin

    2016-01-01

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

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

    Science.gov (United States)

    Li, Xiao-Jian; Yang, Guang-Hong

    2012-08-01

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

  11. Fault Detection of Wind Turbines with Uncertain Parameters

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  12. Fault detection and diagnosis of diesel engine valve trains

    Science.gov (United States)

    Flett, Justin; Bone, Gary M.

    2016-05-01

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

  13. Export Methods in Fault Detection and Localization Mechanisms

    Directory of Open Access Journals (Sweden)

    Aymen Belghith

    2012-07-01

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

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Indian Academy of Sciences (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.

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

    Science.gov (United States)

    Carlsson, Bengt; Zambrano, Jesús

    2016-01-01

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

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

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Shafiei, Seyed Ehsan

    2015-01-01

    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...

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...... 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....

  19. Distance Based Fault detection in wireless sensor network

    Directory of Open Access Journals (Sweden)

    Ayasha Siddiqua

    2013-05-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2006-01-01

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

  2. Lateral migration of fault activity in Weihe basin

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2011-02-01

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

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

    Data.gov (United States)

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

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

    CERN Document Server

    Dong, Hongli; Gao, Huijun

    2013-01-01

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

  7. Fault detection and isolation in processes involving induction machines

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-12-31

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

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

    OpenAIRE

    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...

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

    KAUST Repository

    Hanafy, Sherif M.

    2014-08-05

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

  10. Designing Expert System for Detecting Faults in Cloud Environment

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Stelling, P.

    1998-06-09

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

  12. Observer Based Detection of Sensor Faults in Wind Turbines

    DEFF Research Database (Denmark)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2016-05-01

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

  14. Convolutional Neural Network Based Fault Detection for Rotating Machinery

    Science.gov (United States)

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

    2016-09-01

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

  15. Bearings fault detection using inference tools

    OpenAIRE

    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.

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

    DEFF Research Database (Denmark)

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

    2006-01-01

    by the 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...

  17. Optimal Sensor Allocation for Fault Detection and Isolation

    Science.gov (United States)

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

    2004-01-01

    Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

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

    OpenAIRE

    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...

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

    International Nuclear Information System (INIS)

    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)

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermedi......In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors...... on the intermediate shafts inside the gearbox. An angular velocity error function is defined and compared in the faulty and fault-free conditions in frequency domain. Faults can be detected from the change in the energy level of the frequency spectrum of an error function. The method is demonstrated by detecting...... bearing faults in three locations: the high-speed shaft stage, the planetary stage and the intermediate-speed shaft stage. Simulations of the faulty and fault-free cases are performed on a gearbox model implemented in multibody dynamic simulation software. The global loads on the gearbox are obtained from...

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

    Science.gov (United States)

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

    2016-09-01

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

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    Cheung, Howard; Braun, James E.

    2015-12-31

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

  4. Applying Parametric Fault Detection to a Mechanical System

    DEFF Research Database (Denmark)

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

    2002-01-01

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

  5. Enhanced Fault Detection and Isolation in Modern Flight Actuators

    OpenAIRE

    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 (...

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

    Science.gov (United States)

    Button, Robert M.

    2004-01-01

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

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

    DEFF Research Database (Denmark)

    Li, Hui; Yang, Chao; Hu, Yaogang;

    2014-01-01

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

  8. Sensor Fault Detection and Diagnosis for autonomous vehicles

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2016-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Rubén Francisco Manrique Piramanrique

    2015-04-01

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

  11. Parameter estimation and reliable fault detection of electric motors

    Institute of Scientific and Technical Information of China (English)

    Dusan PROGOVAC; Le Yi WANG; George YIN

    2014-01-01

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

  12. Robust filtering and fault detection of switched delay systems

    CERN Document Server

    Wang, Dong; Wang, Wei

    2013-01-01

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

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

    Science.gov (United States)

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

    2015-07-01

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

  14. Image Fault Area Detection Algorithm Based on Visual Perception

    Directory of Open Access Journals (Sweden)

    Peng-Lu

    2011-02-01

    Full Text Available If the natural scenes decomposed by basic ICA which simulates visual perception then the arrangement in space of its basis functions are in disorder. This result is contradicted with physiological mechanisms of vision. So, a new compute model is proposed to simulate two important mechanisms of vision which are visual cortex receptive field topology construct and synchronous oscillation among neuron group. To solve the problem of train image fault detection, a novel algorithm was proposed based on above compute model. The experiment results show that, the algorithm can increase fault detection rate effectively compared with traditional methods which absence of above two important mechanisms of vision.

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

    Institute of Scientific and Technical Information of China (English)

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

    2005-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Lee SangHun

    2016-01-01

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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

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

    2015-11-01

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

  1. Vibration based fault detection techniques for mechanical structures

    International Nuclear Information System (INIS)

    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)

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    The angle faults of blades on wind turbines are usually included in the set angle fault and the pitch angle fault. They are occupied with a high proportion in all wind turbine faults. Compare with the traditional fault detection methods, using order tracking analysis method to detect angle faults...... 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....... By analyzing and reconstructing the fault signals, it is easy to detect the fault characteristic frequency and see the characteristic frequencies of angle faults depend on the shaft rotating frequency, which is known as the 1P frequency and 3P frequency distinctly....

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2016-03-01

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

  5. Active Fault Characterization in the Urban Area of Vienna

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2016-07-01

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

  7. 基于SR-UKF的移动机器人主动故障检测和容错控制%SR-UKF based active fault detection and tolerant control of mobile robots

    Institute of Scientific and Technical Information of China (English)

    周波; 戴先中

    2011-01-01

    提出了一种基于SR-UKF的主动状态建模方法用于移动机器人的在线故障检测和容错跟踪控制.通过对履带式机器人常见滑动故障的运动学分析,建立了带未知滑动故障参数的机器人运动学模型,并采用SR-UKF非线性滤波方法来联合估计机器人的位姿和滑动参数,在对机器人进行实时定位的同时实现了对快速变化(或突变)的滑动故障的在线跟踪和检测.在此基础上,将估计得到的自适应参数模型与基于Lyapunov分析的反馈控制律设计方法结合,获得了一致渐近稳定的轨迹跟踪控制结果,实现了针对在线故障自适应模型的容错控制重构.针对典型的阶跃式滑动故障参数变化的轨迹跟踪仿真实验表明了该方法的有效性.%A square-rooted unscented Kalman filter (SR-UKF) based active state model is proposed for online fault detection and tolerant tracking control of mobile robots. The common slipping fault of a tracked vehicle is considered and the corresponding kinematic model with unknown slipping parameters is created. The slipping parameters as well as the pose of the robot are estimated simultaneously by the joint estimation framework to realize the real-time localization of robots and online identification and detection of the fast changing (or even abrupt changing) slipping fault. The obtained adaptive fault model is then incorporated to the tolerant control configuration in which a Lyapunov based feedback law is designed to achieve uniformly asymptotic stable trajectory tracking control. Simulation experiments for trajectory tracking with typical step changing slipping faults show the efficiency of the proposed method.

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

    Directory of Open Access Journals (Sweden)

    Bekheïra Tabbache

    2012-01-01

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

  9. Battery Fault Detection with Saturating Transformers

    Science.gov (United States)

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

    2013-01-01

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

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

    DEFF Research Database (Denmark)

    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...

  11. Fault detection and diagnosis using neural network approaches

    Science.gov (United States)

    Kramer, Mark A.

    1992-01-01

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

  12. Fault Detection and Isolation (Fdi Via Neural Networks

    Directory of Open Access Journals (Sweden)

    Neeraj Prakash Srivastava,

    2014-01-01

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

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

    Science.gov (United States)

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

    2012-12-01

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

  14. Active faults of the Baikal depression

    Science.gov (United States)

    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.

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

    DEFF Research Database (Denmark)

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2001-01-01

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

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

    Science.gov (United States)

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

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    DEFF Research Database (Denmark)

    Orfanidis, Charalampos; Zhang, Yue; Dragoni, Nicola

    2015-01-01

    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...

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

    DEFF Research Database (Denmark)

    Jensen, Hans-Christian Becker; Wisniewski, Rafal

    2001-01-01

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

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

    Science.gov (United States)

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

    2015-03-01

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

  1. Information Based Fault Diagnosis

    DEFF Research Database (Denmark)

    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...

  2. An adaptive envelope spectrum technique for bearing fault detection

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

    Baer-Ruedhart, J. L.

    1984-01-01

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

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

    CERN Document Server

    Leloux, Jonathan; Luna, Alberto; Desportes, Adrien

    2014-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-08-20

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

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

    OpenAIRE

    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...

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

    DEFF Research Database (Denmark)

    Park, Kiwoo; Chen, Zhe

    2014-01-01

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

  8. Faults

    Data.gov (United States)

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    proposes a novel method of using order tracking analysis to analyze the signal of input aerodynamic torque which is received by hub. After the analyzed process, the fault characteristic frequency could be extracted by the analyzed signals and compared with the signals from normal operating conditions......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...... 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...

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

    KAUST Repository

    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.

  12. Insurance Applications of Active Fault Maps Showing Epistemic Uncertainty

    Science.gov (United States)

    Woo, G.

    2005-12-01

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

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

    DEFF Research Database (Denmark)

    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 implemented...

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

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

    OpenAIRE

    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...

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

    OpenAIRE

    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...

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Runxia Guo

    2016-01-01

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

  20. Active Fault Diagnosis in Sampled-data Systems

    DEFF Research Database (Denmark)

    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...... transformation) structure in the connection between the parametric faults and the matrix transfer function (also known as the fault signature matrix) applied for AFD is not directly preserved for sampled-data system. As a consequence of this, the AFD methods cannot directly be applied for sampled-data systems....... Two methods are considered in this paper to handle the fault signature matrix for sampled-data systems such that standard AFD methods can be applied. The first method is based on a discretization of the system such that the LFT structure is preserved resulting in the same LFT structure in the fault...

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

    International Nuclear Information System (INIS)

    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)

  2. Geodynamics of the Dead Sea Fault: Do active faulting and past earthquakes determine the seismic gaps?

    Science.gov (United States)

    Meghraoui, Mustapha

    2014-05-01

    The ~1000-km-long North-South trending Dead Sea transform fault (DSF) presents structural discontinuities and includes segments that experienced large earthquakes (Mw>7) in historical times. The Wadi Araba and Jordan Valley, the Lebanese restraining bend, the Missyaf and Ghab fault segments in Syria and the Ziyaret Fault segment in Turkey display geometrical complexities made of step overs, restraining and releasing bends that may constitute major obstacles to earthquake rupture propagation. Using active tectonics, GPS measurements and paleoseismology we investigate the kinematics and long-term/short term slip rates along the DSF. Tectonic geomorphology with paleoseismic trenching and archeoseismic investigations indicate repeated faulting events and left-lateral slip rate ranging from 4 mm/yr in the southern fault section to 6 mm/yr in the northern fault section. Except for the northernmost DSF section, these estimates of fault slip rate are consistent with GPS measurements that show 4 to 5 mm/yr deformation rate across the plate boundary. However, recent GPS results showing ~2.5 mm/yr velocity rate of the northern DSF appears to be quite different than the ~6 mm/yr paleoseismic slip rate. The kinematic modeling that combines GPS and seismotectonic results implies a complex geodynamic pattern where the DSF transforms the Cyprus arc subduction zone into transpressive tectonics on the East Anatolian fault. The timing of past earthquake ruptures shows the occurrence of seismic sequences and a southward migration of large earthquakes, with the existence of major seismic gaps along strike. In this paper, we discuss the role of the DSF in the regional geodynamics and its implication on the identification of seismic gaps.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Wonhee Lee

    2014-02-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  6. Comprehensive Multi-Level Exploration of Buried Active Faults: an Example of the Yinchuan Buried Active Fault

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The paper introduces the steps and methods of multi-approach, multi-level exploration of buried faults in thick Quaternary sediment regions by taking the test exploration of the Yinchuan active fault as example. Based on the comprehensive analyses of previous data, we choose the Xinqushao Village of Xingqing District of Yinchuan City as the test site for the comprehensive exploration. Firstly, we adopted shallow seismic investigation with group intervals of 10m, 5m and 1m to gradually trace layer by layer the master fault of the Yinchuan buried fault from a deep depth to a shallow depth where drilling could be used. Then, with composite geological profile drilling, we determined the precise location and dip angle of the fault. The drilling show the buried depth of the upper offset point is 8.3m. Finally, large-scale trenching revealed that the actual buried depth of the upper offset point of the fault is 1.5m from the ground surface and there are paleoearthquake events of 5 stages. Combined with the prellmiuary result of corresponding sample age, we conclude the Yinchuan buried fault is a mid to late Holocene active fault.

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

    OpenAIRE

    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. ...

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

    Institute of Scientific and Technical Information of China (English)

    Bibhrajit Halder; Nilanjan Sarkar

    2007-01-01

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

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

    CERN Document Server

    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...

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Castiglione Roberto

    2015-01-01

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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  14. On Real-Time Fault Detection in Wind Turbines: Sensor Selection Algorithm and Detection Time Reduction Analysis

    Directory of Open Access Journals (Sweden)

    Francesc Pozo

    2016-07-01

    Full Text Available In this paper, we address the problem of real-time fault detection in wind turbines. Starting from a data-driven fault detection method, the contribution of this paper is twofold. First, a sensor selection algorithm is proposed with the goal to reduce the computational effort of the fault detection method. Second, an analysis is performed to reduce the data acquisition time needed by the fault detection method, that is, with the goal of reducing the fault detection time. The proposed methods are tested in a benchmark wind turbine where different actuator and sensor failures are simulated. The results demonstrate the performance and effectiveness of the proposed algorithms that dramatically reduce the number of sensors and the fault detection time.

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Mohamed Lamine FADDA

    2016-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Faqi Diao

    2016-10-01

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

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

    Institute of Scientific and Technical Information of China (English)

    Deng Huiyu; Wang Xinli; Ma Peisun

    2005-01-01

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

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

    Science.gov (United States)

    Bai, Leishi; Tian, Zuohua; Shi, Songjiao

    2006-10-01

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

  1. A Carrier Signal Approach for Intermittent Fault Detection and Health Monitoring for Electronics Interconnections System

    Directory of Open Access Journals (Sweden)

    Syed Wakil Ahmad

    2015-12-01

    Full Text Available Intermittent faults are completely missed out by traditional monitoring and detection techniques due to non-stationary nature of signals. These are the incipient events of a precursor of permanent faults to come. Intermittent faults in electrical interconnection are short duration transients which could be detected by some specific techniques but these do not provide enough information to understand the root cause of it. Due to random and non-predictable nature, the intermittent faults are the most frustrating, elusive, and expensive faults to detect in interconnection system. The novel approach of the author injects a fixed frequency sinusoidal signal into electronics interconnection system that modulates intermittent fault if persist. Intermittent faults and other channel effects are computed from received signal by demodulation and spectrum analysis. This paper describes technology for intermittent fault detection, and classification of intermittent fault, and channel characterization. The paper also reports the functionally tests of computational system of the proposed methods. This algorithm has been tested using experimental setup. It generate an intermittent signal by external vibration stress on connector and intermittency is detected by acquiring and processing propagating signal. The results demonstrate to detect and classify intermittent interconnection and noise variations due to intermittency. Monitoring the channel in-situ with low amplitude, and narrow band signal over electronics interconnection between a transmitter and a receiver provides the most effective tool for continuously watching the wire system for the random, unpredictable intermittent faults, the precursor of failure.

  2. Interseismic Crustal Deformation in and around the Atotsugawa Fault System, Central Japan, Detected by InSAR and GNSS

    Science.gov (United States)

    Takada, Y.; Sagiya, T.; Nishimura, T.

    2015-12-01

    Interseismic crustal deformation of active faults provides crucial information to understand the stress accumulation process on the fault planes. Recently, the interseismic surface movements are detected with very high spatial resolution using combination of InSAR and GNSS survey. Most of the successful reports, however, addressed the fault creep in less vegetated area which enables C-band SAR interferometry. In this study, we report the interseismic crustal deformation in and around the Atotsugawa fault system, a strike-slip active fault in central Japan. This area is covered with dense vegetation in summer and with heavy snow in winter. We created a series of InSAR images acquired by ALOS/PALSAR and applied SBAS based time-series analysis (Berardino et al., 2002) to extract small deformation. Next, we corrected the long wave-length phase trend by GNSS network maintained by Japanese University Group (e.g, Ohzono et al., 2011) and GSI, Japan. The mean velocity field thus obtained shows a strain concentration zone along the Ushikubi fault, a major strand of the Atotsugawa fault system. The Ushikubi fault is seismically less active than the Atotsugawa fault, but it shows good correlation with a zone of large spatial gradient of Bouguer gravity anomaly. We further discuss on the deformation style at the junction between the Atotsugawa fault and the Hida mountain range (Tateyama volcano). Acknowledgement: The PALSAR level 1.0 data were provided by JAXA via the PALSAR Interferometry Consortium to Study our Evolving Land surface (PIXEL) based on a cooperative research contract between JAXA and the ERI, the University of Tokyo. The PALSAR product is owned by JAXA and METI.

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

    Science.gov (United States)

    Blakely, R.J.; Sherrod, B.L.; Weaver, C.S.; Wells, R.E.; Rohay, A.C.; Barnett, E.A.; Knepprath, N.E.

    2011-01-01

    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.

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

    Data.gov (United States)

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

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

    OpenAIRE

    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...

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

    Institute of Scientific and Technical Information of China (English)

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

    2007-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    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.

  8. An underwater ship fault detection method based on Sonar image processing

    Science.gov (United States)

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

    2016-02-01

    For the research of underwater ship fault detection method in conditions of sailing on the ocean especially in poor visibility muddy sea, a fault detection method under the assist of sonar image processing was proposed. Firstly, did sonar image denoising using the algorithm of pulse coupled neural network (PCNN); secondly, edge feature extraction for the image after denoising was carried out by morphological wavelet transform; Finally, interested regions Using relevant tracking method were taken, namely fault area mapping. The simulation results presented here proved the feasibility and effectiveness of the sonar image processing in underwater fault detection system.

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

    Science.gov (United States)

    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 (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.

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2005-01-01

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

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

    Directory of Open Access Journals (Sweden)

    METATLA, A.

    2011-02-01

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

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

    DEFF Research Database (Denmark)

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

    1998-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Hongli Dong

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    G.Satyanarayana,

    2015-08-01

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

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-05-15

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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2013-12-01

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

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

    DEFF Research Database (Denmark)

    Herp, Jürgen; S. Nadimi, Esmaeil

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Bingyong Yan

    2015-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2013-01-01

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

  3. Activity Tendency and Dynamic Characteristics of Shanxi Fault Zone

    Institute of Scientific and Technical Information of China (English)

    Yang Guohua; Wang Min; Han Yueping; Zhou Xiaoyan; Zhang Zhongfu; Wang Xiuwen; Guo Yuehong

    2003-01-01

    The tendency and dynamic characteristics of horizontal movement along the Shanxi fault zone have been analyzed using the data obtained from 6 repeated measurements (1996~2001) in the GPS monitoring network arranged along the Shanxi fault zone. The results indicate: (1) the tendentious activity of the present stage is characterized by a W-trending movement along the northern segment of the zone, an E-trending movement along the southern segment and counter clockwise differential activity on the whole, but the intensity of the tendentious activity is not high. The tendentious differential movement is only about 3 mm/a in the direction perpendicular to the fault zone from the south to the north, and its stretch in the SN direction is only 1 mm/a and mainly occurs along the north segment of the fault; (2) The azimuth of the principal compressive stress field reflected by the tendentious movement is 72°; (3) The property of annual activity is not the same, even contrary to one another or deviates from the tendentious activity. Therefore, the parameters of the strain field derived from them don't reflect the physical characteristics of the basic stress field. (4) The high-frequency movement (yearly) does not only exist but is also complicated by an intensity several times higher than that of the tendentious movement; (5) Obvious differential movements, including strike slip, can not be seen in either in secular activity or annual activity on both sides of any fault. The tendentious movement not only verifies the conjecture of "strong in the south and weak in north", which is the basic feature forcing the western boundary of the North China area, but it also extends to the hinterland of North China. The fact that there is no obvious differential activity on both sides of the fault might indicate that the differential activity among the intraplate blocks is completed by gradual variation in a certain space, rather than the abrupt change bordered by a fault or narrow

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Fault diagnosis based on controller modification

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    2015-01-01

    faults can be detected and isolated using active methods, where an auxiliary input is applied. Using active methods for the diagnosis of parametric faults in closed-loop systems, the amplitude of the applied auxiliary input need to be increased to be able to detect and isolate the faults in a reasonable...... with both fault detection and isolation will be discussed. Also passive fault diagnosis methods based on controller modification will be discussed...

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

    International Nuclear Information System (INIS)

    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

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

    OpenAIRE

    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...

  8. A Fault Detection Method of Rolling Bearing Based on Wavelet Packet-cepstrum

    Directory of Open Access Journals (Sweden)

    Tingting Leng

    2013-04-01

    Full Text Available In this study, we put forward a fault detection method of rolling bearing based on the wavelet packet-cepstrum. Firstly, the original signal is decomposed using the wavelet packet. Secondly, calculate the energy of the decomposed sub-band reconstruction signal and select the relatively band which is concentrated on the fault energy. Finally, calculate cepstrum of the reconstruction signal to detect fault. The actual normal and fault data of the rolling bearing's outer ring is analyzed in applying this method in the MATLAB simulation circumstance. The result shows that the outer ring's failure frequency measured by the experiment is consistent with the theoretical calculation result.

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

    Science.gov (United States)

    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

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

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2006-01-01

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

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

    KAUST Repository

    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.

  13. Active Fault Diagnosis in Sampled-data Systems

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    Moghadas, Amin A.; Shadaram, Mehdi

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Mehdi Shadaram

    2010-10-01

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

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

    Institute of Scientific and Technical Information of China (English)

    Yong JIANG; Hongguang WANG; Lijin FANG; Mingyang ZHAO

    2009-01-01

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

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

    DEFF Research Database (Denmark)

    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...

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

    Directory of Open Access Journals (Sweden)

    Silvia M. Zanoli

    2013-01-01

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

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

    DEFF Research Database (Denmark)

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

    2006-01-01

    . In this paper three different fault detection approaches are compared using a example of a coal mill, where a fault emerges. The compared methods are based on: an optimal unknown input observer, static and dynamic regression model-based detections. The conclusion on the comparison is that observer-based scheme...... detects the fault 13 samples earlier than the dynamic regression model-based method, and that the static regression based method is not usable due to generation of far too many false detections....

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

    OpenAIRE

    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...

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

    OpenAIRE

    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...

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

    Science.gov (United States)

    Grauer, Jared A.

    2016-01-01

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

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    S. hajiaghasi

    2014-07-01

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

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

    NARCIS (Netherlands)

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

    2016-01-01

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

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

    DEFF Research Database (Denmark)

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

    2008-01-01

    The paper focuses on the fault detection of a five-phase Permanent-Magnet (PM) machine. This machine has been de-signed for fault tolerant applications, and it is characterised by a mutual inductance equal to zero and a high self inductance, with the purpose to limit the short circuit current. Th...

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

    DEFF Research Database (Denmark)

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

    2009-01-01

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

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

    DEFF Research Database (Denmark)

    Schlechtingen, Meik; Santos, Ilmar

    2011-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    Han Zhennan; Xiong Shibo; Li Jinbao

    2003-01-01

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

  11. Rotor Faults Detection in Induction Motor by Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Neelam Mehala

    2009-12-01

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

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

    Institute of Scientific and Technical Information of China (English)

    PAN Zhongliang; CHEN Ling; ZHANG Guangzhao

    2006-01-01

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

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

    CERN Document Server

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

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

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

    International Nuclear Information System (INIS)

    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

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

    DEFF Research Database (Denmark)

    Bergantino, Nicola; Caponetti, Fabio; Longhi, Sauro

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Yi-Rui Lee

    2016-06-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Fang Wu

    2014-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    YANG Hongying; YE Hao; WANG Guizeng

    2008-01-01

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

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

    Science.gov (United States)

    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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    OpenAIRE

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

    Science.gov (United States)

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

    2013-04-01

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

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

    OpenAIRE

    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...

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

    OpenAIRE

    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...

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

    International Nuclear Information System (INIS)

    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

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

    Institute of Scientific and Technical Information of China (English)

    JIN Xuexiang; ZHANG Yi; LI Li; HU Jianming

    2008-01-01

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

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

    Science.gov (United States)

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

    2008-06-03

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

  18. Sparse representation based latent components analysis for machinery weak fault detection

    Science.gov (United States)

    Tang, Haifeng; Chen, Jin; Dong, Guangming

    2014-06-01

    Weak machinery fault detection is a difficult task because of two main reasons (1) At the early stage of fault development, signature of fault related component performs incompletely and is quite different from that at the apparent failure stage. In most instances, it seems almost identical with the normal operating state. (2) The fault feature is always submerged and distorted by relatively strong background noise and macro-structural vibrations even if the fault component already performs completely, especially when the structure of fault components and interference are close. To solve these problems, we should penetrate into the underlying structure of the signal. Sparse representation provides a class of algorithms for finding succinct representations of signal that capture higher-level features in the data. With the purpose of extracting incomplete or seriously overwhelmed fault components, a sparse representation based latent components decomposition method is proposed in this paper. As a special case of sparse representation, shift-invariant sparse coding algorithm provides an effective basis functions learning scheme for capturing the underlying structure of machinery fault signal by iteratively solving two convex optimization problems: an L1-regularized least squares problem and an L2-constrained least squares problem. Among these basis functions, fault feature can be probably contained and extracted if optimal latent component is filtered. The proposed scheme is applied to analyze vibration signals of both rolling bearings and gears. Experiment of accelerated lifetime test of bearings validates the proposed method's ability of detecting early fault. Besides, experiments of fault bearings and gears with heavy noise and interference show the approach can effectively distinguish subtle differences between defect and interference. All the experimental data are analyzed by wavelet shrinkage and basis pursuit de-noising (BPDN) method for comparison.

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

    Institute of Scientific and Technical Information of China (English)

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

    2001-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Wei Teng

    2016-01-01

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

  1. Enhanced Fault Detection of Rolling Element Bearing Based on Cepstrum Editing and Stochastic Resonance

    Science.gov (United States)

    Zhang, Xiaofei; Hu, Niaoqing; Hu, Lei; Fan, Bin; Cheng, Zhe

    2012-05-01

    By signal pre-whitening based on cepstrum editing,the envelope analysis can be done over the full bandwidth of the pre-whitened signal, and this enhances the bearing characteristic frequencies. The bearing faults detection could be enhanced without knowledge of the optimum frequency bands to demodulate, however, envelope analysis over full bandwidth brings more noise interference. Stochastic resonance (SR), which is now often used in weak signal detection, is an important nonlinear effect. By normalized scale transform, SR can be applied in weak signal detection of machinery system. In this paper, signal pre-whitening based on cepstrum editing and SR theory are combined to enhance the detection of bearing fault. The envelope spectrum kurtosis of bearing fault characteristic components is used as indicators of bearing faults. Detection results of planted bearing inner race faults on a test rig show the enhanced detecting effects of the proposed method. And the indicators of bearing inner race faults enhanced by SR are compared to the ones without enhancement to validate the proposed method.

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

    Directory of Open Access Journals (Sweden)

    Fei Song

    2014-01-01

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

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

    DEFF Research Database (Denmark)

    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...... 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...

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

    CERN Document Server

    Martinez-Guerra, Rafael

    2014-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2004-01-01

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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2015-01-01

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

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

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1996-01-01

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

  12. Optimal Threshold Functions for Fault Detection and Isolation

    DEFF Research Database (Denmark)

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

    2003-01-01

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

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

    DEFF Research Database (Denmark)

    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...

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

    Institute of Scientific and Technical Information of China (English)

    YangTianshe; LiHuaizu; SunYanbong

    2004-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jie Yang

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

  16. Enhanced detection of rolling element bearing fault based on stochastic resonance

    Science.gov (United States)

    Zhang, Xiaofei; Hu, Niaoqing; Cheng, Zhe; Hu, Lei

    2012-11-01

    Early bearing faults can generate a series of weak impacts. All the influence factors in measurement may degrade the vibration signal. Currently, bearing fault enhanced detection method based on stochastic resonance(SR) is implemented by expensive computation and demands high sampling rate, which requires high quality software and hardware for fault diagnosis. In order to extract bearing characteristic frequencies component, SR normalized scale transform procedures are presented and a circuit module is designed based on parameter-tuning bistable SR. In the simulation test, discrete and analog sinusoidal signals under heavy noise are enhanced by SR normalized scale transform and circuit module respectively. Two bearing fault enhanced detection strategies are proposed. One is realized by pure computation with normalized scale transform for sampled vibration signal, and the other is carried out by designed SR hardware with circuit module for analog vibration signal directly. The first strategy is flexible for discrete signal processing, and the second strategy demands much lower sampling frequency and less computational cost. The application results of the two strategies on bearing inner race fault detection of a test rig show that the local signal to noise ratio of the characteristic components obtained by the proposed methods are enhanced by about 50% compared with the band pass envelope analysis for the bearing with weaker fault. In addition, helicopter transmission bearing fault detection validates the effectiveness of the enhanced detection strategy with hardware. The combination of SR normalized scale transform and circuit module can meet the need of different application fields or conditions, thus providing a practical scheme for enhanced detection of bearing fault.

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

    Science.gov (United States)

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

    2015-11-01

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

  18. Active Fault Tolerant Control for Ultrasonic Piezoelectric Motor

    Science.gov (United States)

    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.

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

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2015-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-12-31

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

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

    Directory of Open Access Journals (Sweden)

    Steffen Haus

    2013-01-01

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

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

    Science.gov (United States)

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

    2001-01-01

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

  3. Fault Detection in the Blade and Pitch System of a Wind Turbine with H2 PI Observers

    Science.gov (United States)

    Sales-Setién, Ester; Peñarrocha, Ignacio; Dolz, Daniel; Sanchis, Roberto

    2015-11-01

    In this work, we present a fault detection strategy applicable to the blade and pitch system in offshore wind turbines. First, we model the system and possible faults and propose a PI observer to identify the faults. Then, the observer is designed accounting the sensors measurement noise, and addressing a trade off between the needs of false alarm rate, minimum detectable fault and detection time. By means of a well known benchmark, several simulations show the goodness of the approach and its flexibility to explicitly fix the fault detector performance.

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

    KAUST Repository

    Khelouat, Samir

    2012-06-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.)

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

    CERN Document Server

    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.

  8. Sensor Fault Detection and Diagnosis for autonomous vehicles

    OpenAIRE

    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...

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

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-03-15

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-11-15

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

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

    Institute of Scientific and Technical Information of China (English)

    MENG Tao; LIAO Ming-fu

    2003-01-01

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

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

    OpenAIRE

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

    International Nuclear Information System (INIS)

    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)

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    International Nuclear Information System (INIS)

    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

  17. Aftershocks illuninate the 2011 Mineral, Virginia, earthquake causative fault zone and nearby active faults

    Science.gov (United States)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    REYES-ARCHUNDIA, E.

    2015-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Songpon Klinchaeam

    2014-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Hongmei Liu

    2013-01-01

    Full Text Available This paper presents an approach to bearing fault diagnosis based on the Teager energy operator (TEO and Elman neural network. The TEO can estimate the total mechanical energy required to generate signals, thereby resulting in good time resolution and self-adaptability to transient signals. These attributes reflect the advantage of detecting signal impact characteristics. To detect the impact characteristics of the vibration signals of bearing faults, we used the TEO to extract the cyclical impact caused by bearing failure and applied the wavelet packet to reduce the noise of the Teager energy signal. This approach also enabled the extraction of bearing fault feature frequencies, which were identified using the fast Fourier transform of Teager energy. The feature frequencies of the inner and outer faults, as well as the ratio of resonance frequency band energy to total energy in the Teager spectrum, were extracted as feature vectors. In order to avoid a frequency leak error, the weighted Teager spectrum around the fault frequency was extracted as feature vector. These vectors were then used to train the Elman neural network and improve the robustness of the diagnostic algorithm. Experimental results indicate that the proposed approach effectively detects bearing faults under variable conditions.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-08-26

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Hua-Qing Wang

    2014-01-01

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

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

    Science.gov (United States)

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

    2016-02-01

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

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

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

    Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

    2016-07-01

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

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

    Science.gov (United States)

    Tousi, M. M.; Khorasani, K.

    2015-01-01

    In this paper, a hybrid fault detection and isolation (FDI) methodology is developed for a team of cooperating unmanned vehicles. The proposed approach takes advantage of the cooperative nature of the team to detect and isolate relatively low-severity actuator faults that are otherwise not detectable and isolable by the vehicles themselves individually. The approach is hybrid and consists of both low-level (agent/team level) and high-level [discrete-event systems (DES) level] FDI modules. The high-level FDI module is formulated in the DES supervisory control framework, whereas the low-level FDI module invokes classical FDI techniques. By properly integrating the two FDI modules, a larger class of faults can be detected and isolated as compared to the existing techniques in the literature that rely on each level separately. Simulation results for a team of five unmanned aerial vehicles are also presented to demonstrate the effectiveness and capabilities of our proposed methodology.

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

    Science.gov (United States)

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

    2015-10-09

    The Shannon sampling principle requires substantial amounts of data to ensure the accuracy of on-line monitoring of roller bearing fault signals. Challenges are often encountered as a result of the cumbersome data monitoring, thus a novel method focused on compressed vibration signals for detecting roller bearing faults is developed in this study. Considering that harmonics often represent the fault characteristic frequencies in vibration signals, a compressive sensing frame of characteristic harmonics is proposed to detect bearing faults. A compressed vibration signal is first acquired from a sensing matrix with information preserved through a well-designed sampling strategy. A reconstruction process of the under-sampled vibration signal is then pursued as attempts are conducted to detect the characteristic harmonics from sparse measurements through a compressive matching pursuit strategy. In the proposed method bearing fault features depend on the existence of characteristic harmonics, as typically detected directly from compressed data far before reconstruction completion. The process of sampling and detection may then be performed simultaneously without complete recovery of the under-sampled signals. The effectiveness of the proposed method is validated by simulations and experiments.

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

    Directory of Open Access Journals (Sweden)

    Byung Eun Lee

    2014-09-01

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

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

    DEFF Research Database (Denmark)

    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...

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    -switch detection method of the NPC converter is different from that of the NPC inverter due to the different current paths of the NPC converter. This paper proposes the open-switch fault detection method of the NPC converter connected the permanent-magnet synchronous generator (PMSG). Moreover, the open...

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    circuit faults have been developed. For other types of machines the single and partial turn short circuit is very difficult to deal with and requires normally very comprehensive detection and calculation schemes. The developed detection algorithm combined with the E-core transverse flux machine...

  13. Energy-Efficient Fault-Tolerant Dynamic Event Region Detection in Wireless Sensor Networks

    DEFF Research Database (Denmark)

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

    2015-01-01

    Fault-tolerant event detection is fundamental to wireless sensor network applications. Existing approaches usually adopt neighborhood collaboration for better detection accuracy, while need more energy consumption due to communication. Focusing on energy efficiency, this paper makes an improvement...... efficiency with the number of messages exchanged in the network decreased....

  14. Kalman Filter Application to Symmetrical Fault Detection during Power Swing

    DEFF Research Database (Denmark)

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

    2016-01-01

    capability of Kalman Filter. The proposed in- dex is calculated by assessing the dierence between predicted and actual samples of impedance. The predicted impedance samples are obtained using Kalman lter and Taylor expansion, which is used in this paper to track the phasor precisely. Second or- der of Taylor...... expansion is used to decrease corrugation eect of impedance estimation and increase the reliability of proposed method. The instantaneous estimation and pre- diction capability of Kalman lter are two reasons for proposing utilizing Kalman lter. Intensive studies have been performed and the merit...... of the method is demonstrated by test simulations. Keywords: Kalman Filter, Power Swing, Dynamic Phasor, Symmetrical Fault....

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

    OpenAIRE

    Haitao Wang

    2016-01-01

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

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

    International Nuclear Information System (INIS)

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

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

    In order to improve reliability of the excavator's hydraulic system, a fault detection approach based on dynamic principal component analysis(PCA) was proposed. Dynamic PCA is an extension of PCA, which can effectively extract the dynamic relations among process variables. With this approach, normal samples were used as training data to develop a dynamic PCA model in the first step. Secondly, the dynamic PCA model decomposed the testing data into projections to the principal component subspace(PCS) and residual subspace(RS). Thirdly, T2 statistic and Q statistic performed as indexes of fault detection in PCS and RS, respectively.Several simulated faults were introduced to validate the approach. The results show that the dynamic PCA model developed is able to detect overall faults by using T2 statistic and Q statistic. By simulation analysis, the proposed approach achieves an accuracy of 95% for 20 test sample sets, which shows that the fault detection approach can be effectively applied to the excavator's hydraulic system.

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

    Energy Technology Data Exchange (ETDEWEB)

    Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia, Guarulhos, SP (Brazil); Pereira, Iraci Martinez; Silva, Antonio Teixeira e, E-mail: martinez@ipen.b, E-mail: teixeira@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-09-15

    Two methods, one based on genetic algorithm (GA) and one based on neural networks (NN), are proposed for high impedance fault (HIF) detection in distribution systems. These methods are used to discriminate HIFs from isolator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no load line switching. Wavelet transform is used for the decomposition of signals and feature extraction in both methods. In one method, GA is used for feature vector reduction and Bayes for classification. In the other method, principal component analysis (PCA) is applied for feature vector reduction and NN for classification. HIF and ILC data was acquired by experimental tests and the data for other faults was obtained by simulating a real network using EMTP. Results show that either of the proposed procedures can be used to identify HIF from other events efficiently. (author) [Bayes classifier; High impedance fault; Genetic algorithm; Neural network; Principal component analysis; Wavelet transform].

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

    Science.gov (United States)

    Zhao, Qing; Xu, Zhihan

    2004-04-01

    In this paper, a real-time fault detection and isolation (FDI) scheme for dynamical systems is developed, by integrating the signal processing technique with neural network design. Wavelet analysis is applied to capture the fault-induced transients of the measured signals in real-time, and the decomposed signals are pre-processed to extract details about a fault. A Regional Self-Organizing feature Map (R-SOM) neural network is synthesized to classify the fault types. The R-SOM neural network adopts two regions adjustment in the learning algorithm, thus it has high precision in clustering and matching, especially when the noise, disturbance and other uncertainties exist in the systems. As a result, the proposed FDI scheme is robust and accurate. The design is implemented on a stirred tank system and satisfactory online testing results are obtained.

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

    Science.gov (United States)

    Zhou, Binzhong 13Hatherly, Peter

    2014-10-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

    Fang, Chih-Chiang; Yeh, Chun-Wu

    2016-09-01

    The quantitative evaluation of software reliability growth model is frequently accompanied by its confidence interval of fault detection. It provides helpful information to software developers and testers when undertaking software development and software quality control. However, the explanation of the variance estimation of software fault detection is not transparent in previous studies, and it influences the deduction of confidence interval about the mean value function that the current study addresses. Software engineers in such a case cannot evaluate the potential hazard based on the stochasticity of mean value function, and this might reduce the practicability of the estimation. Hence, stochastic differential equations are utilised for confidence interval estimation of the software fault-detection process. The proposed model is estimated and validated using real data-sets to show its flexibility.

  5. A Novel Approach to Fault Detection in Complex Electric Power Systems

    Directory of Open Access Journals (Sweden)

    ZHANG, Y.

    2014-08-01

    Full Text Available The new type of backup protection can utilize different kinds of information in a larger scale. The research of this paper is focused on the centralized decision and distributed implementation of wide area backup protection system in large-scale power grid. Topology analysis of power network is substantially network connectivity judgment. The operation conditions in case of a failure should be truthfully reflected in the actual structure of network topology, which requires the system failure must be detected promptly and accurately, and prepare for the subsequent adjustment of operation scheme. In the research of this paper, for different kinds of complex system failures, we have put forward a novel fault factor analysis scheme which can realize rapid, accurate and effective fault detection. Many simulations have verified that the fault factor analysis can successfully detect the failures in complex electric power system.

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

    Institute of Scientific and Technical Information of China (English)

    Qing Wang; Zhaolei Wang; Chaoyang Dong; Erzhuo Niu

    2015-01-01

    The observer-based robust fault detection filter design and optimization for networked control systems (NCSs) with uncer-tain time-varying delays are addressed. The NCSs with uncertain time-varying delays are modeled as parameter-uncertain systems by the matrix theory. Based on the model, an observer-based residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of the linear matrix inequality. Furthermore, a time domain opti-mization approach is proposed to improve the performance of the fault detection system. To prevent the false alarms, a new thresh-old function is established, and the solution of the optimization problem is given by using the singular value decomposition (SVD) of the matrix. A numerical example is provided to il ustrate the effectiveness of the proposed approach.

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

    OpenAIRE

    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...

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Chintan Bhatt

    2011-10-01

    Full Text Available This paper is a survey of the work, done for making an IDS fault tolerant.Architecture of IDS that usesmobile Agent provides higher scalability. Mobile Agent uses Platform for detecting Intrusions using filterAgent, co-relater agent, Interpreter agent and rule database. When server (IDS Monitor goes down,other hosts based on priority takes Ownership. This architecture uses decentralized collection andanalysis for identifying Intrusion. Rule sets are fed based on user-behaviour or applicationbehaviour.This paper suggests that intrusion detection system (IDS must be fault tolerant; otherwise, theintruder may first subvert the IDS then attack the target system at will.

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

    Energy Technology Data Exchange (ETDEWEB)

    Galvez-Carrillo, Manuel; Kinnaert, Michel [Dept. of Control Engineering and System Analysis, Universite Libre de Bruxelles (ULB), 50 Av. F.D. Roosevelt, CP 165/55, B-1050 Brussels (Belgium)

    2011-05-15

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

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

    Institute of Scientific and Technical Information of China (English)

    Jun-tong Qi; Jian-da Han

    2007-01-01

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

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

    DEFF Research Database (Denmark)

    Tabatabaeipour, Mojtaba; Bak, Thomas

    2014-01-01

    In this paper, a computationally efficient set-membership method for robust fault detection of linear systems is proposed. The method computes an interval outer-approximation of the output of the system that is consistent with the model, the bounds on noise and disturbance, and the past...... measurements. If the output of the system does not belong to this interval, a fault is detected. To compute the output interval, we propose using support functions. Only two support functions for each output must be computed which results in a computationally efficient algorithm. Moreover, the method...

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

    Science.gov (United States)

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

    2008-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Directory of Open Access Journals (Sweden)

    Hamid Fekri Azgomi

    2013-04-01

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

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

    Institute of Scientific and Technical Information of China (English)

    Miao Lingjuan; Shi Jing

    2014-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    International Nuclear Information System (INIS)

    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

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

    Directory of Open Access Journals (Sweden)

    Thomas Bak

    2012-07-01

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

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

    OpenAIRE

    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...

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

    OpenAIRE

    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...

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    Pan Zhongliang

    2004-01-01

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

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

    Science.gov (United States)

    Tejada, Arturo

    2009-01-01

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

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

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

    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

  11. Delineation of Urban Active Faults Using Multi-scale Gravity Analysis in Shenzhen, South China

    Science.gov (United States)

    Xu, C.; Liu, X.

    2015-12-01

    In fact, many cities in the world are established on the active faults. As the rapid urban development, thousands of large facilities, such as ultrahigh buildings, supersized bridges, railway, and so on, are built near or on the faults, which may change the balance of faults and induce urban earthquake. Therefore, it is significant to delineate effectively the faults for urban planning construction and social sustainable development. Due to dense buildings in urban area, the ordinary approaches to identify active faults, like geological survey, artificial seismic exploration and electromagnetic exploration, are not convenient to be carried out. Gravity, reflecting the mass distribution of the Earth's interior, provides a more efficient and convenient method to delineate urban faults. The present study is an attempt to propose a novel gravity method, multi-scale gravity analysis, for identifying urban active faults and determining their stability. Firstly, the gravity anomalies are decomposed by wavelet multi-scale analysis. Secondly, based on the decomposed gravity anomalies, the crust is layered and the multilayer horizontal tectonic stress is inverted. Lastly, the decomposed anomalies and the inverted horizontal tectonic stress are used to infer the distribution and stability of main active faults. For validating our method, a case study on active faults in Shenzhen City is processed. The results show that the distribution of decomposed gravity anomalies and multilayer horizontal tectonic stress are controlled significantly by the strike of the main faults and can be used to infer depths of the faults. The main faults in Shenzhen may range from 4km to 20km in the depth. Each layer of the crust is nearly equipressure since the horizontal tectonic stress has small amplitude. It indicates that the main faults in Shenzhen are relatively stable and have no serious impact on planning and construction of the city.

  12. A novel data channel fault detection mechanism in optical burst switching networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Fault detection in optical burst switching (OBS) networks will be a challenging task in the future. A novel mechanism based on probe burst (PB) and a new key concept is proposed to detect faults of OBS networks by sampling the health of data channels, which solve the difficulty of optical monitoring schemes while keeps the transparency of data network to Internet protocol (IP) packets. It takes full advantage of the characteristics of OBS, including architecture and signalling scheme, and introduces the excellent performances of single-hop-test used in electrical communication networks into OBS environment while avoids the shortcoming that any optical burst must undergo an optical-electric-optical (OEO) conversion.Well designed PB can provide exact criterion for judging whether protection/restoration should be excuted according to hard or soft fault identification.

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

    Directory of Open Access Journals (Sweden)

    Saeed Ahmadizadeh

    2013-01-01

    Full Text Available This paper deals with the problem of fault detection for linear uncertain time-delay systems. The proposed method for Luenberger observers is developed for unknown input observers (UIOs, and a novel procedure for the design of residual based on UIOs is presented. The design procedure is carried out based on the model matching approach which minimizes the difference between generated residuals by the optimal observer and those by the designed observer in the presence of uncertainties. The optimal observer is designed for the ideal system and works so that the fault effect is maximized while the exogenous disturbances and noise effects are minimized. This observer can give disturbance decoupling in the presence of noise and uncertainties for linear uncertain time-delay systems. The developed method is applied to a numerical example, and the simulation results show that the proposed approach is able to detect faults reliably in the presence of modeling errors, disturbances, and noise.

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

    Science.gov (United States)

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

    2016-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Hehong Zhang

    2015-01-01

    Full Text Available A fault detection method based on the optimized tracking differentiator is introduced. It is applied on the acceleration sensor of the suspension system of maglev train. It detects the fault of the acceleration sensor by comparing the acceleration integral signal with the speed signal obtained by the optimized tracking differentiator. This paper optimizes the control variable when the states locate within or beyond the two-step reachable region to improve the performance of the approximate linear discrete tracking differentiator. Fault-tolerant control has been conducted by feedback based on the speed signal acquired from the optimized tracking differentiator when the acceleration sensor fails. The simulation and experiment results show the practical usefulness of the presented method.

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

    CERN Document Server

    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...

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

    Directory of Open Access Journals (Sweden)

    Yu Liu

    2013-01-01

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

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Abolfazl Akbari

    2011-02-01

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

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  6. Evolution and dynamics of active faults in southeastern Egyptian Western Desert

    Science.gov (United States)

    Abdeen, Mamdouh

    2016-07-01

    Remote sensing data processing and analysis together with interpretation of earthquake data that are followed by extensive field studies on some of the prevailing NS and EW striking faults indicate that these faults have an intimate relationship and were formed synchronously as a conjugate Riedel shears. Parallel to the NS and the EW faults open fractures filled with blown sand dominate the area of study. The Quaternary terraces adjacent to these faults are offset by the faults. Kinematic indicators on the NS striking faults indicate major sinistral (left-lateral) strike slip and minor dip-slip (normal) movement. On the other hand, kinematic indicators on the EW striking faults indicate major dextral (right-lateral) strike slip and minor dip-slip (normal) movement. Paleo-stress analysis of the fault striae measured on the NS and EW faults indicate that these faults were formed under NNE-SSW oriented extension. Instrumental earthquake data analysis shows a comparable extension direction to that derived from field measurements of slickenlineation. These observations indicate that the NS- and EW-striking faults are contemporaneous and are related to the Red Sea rifting that is currently active.

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

    Directory of Open Access Journals (Sweden)

    Wang Zhaolei

    2015-06-01

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

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

    NARCIS (Netherlands)

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

    2013-01-01

    The vulnerability of multi-core processors is increasing due to tighter design margins and greater susceptibility to interference. Moreover, concurrent programming environments are the norm in the exploitation of multi-core systems. In this paper, we present an on-demand thread-level fault detection

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    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...

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

    Science.gov (United States)

    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.

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

    DEFF Research Database (Denmark)

    Borchersen, Anders Bech; Kinnaert, Michel

    2016-01-01

    In this work, an early fault detection system for the generator cooling of wind turbines is presented and tested. It relies on a hybrid model of the cooling system. The parameters of the generator model are estimated by an extended Kalman filter. The estimated parameters are then processed by an ...

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold-Kalman F...

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

    DEFF Research Database (Denmark)

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

    2009-01-01

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

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

    NARCIS (Netherlands)

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

    1996-01-01

    This paper describes the application of black-box models for fault detection and diagnosis (FDD) in heating, ventilat-ing, and air-conditioning (HVAC) systems. In this study, mul-tiple-input/single-output (MISO) ARX models and artificial neural network (ANN) models are used. The ARX models are exami

  15. Fault detection monitor circuit provides ''self-heal capability'' in electronic modules - A concept

    Science.gov (United States)

    Kennedy, J. J.

    1970-01-01

    Self-checking technique detects defective solid state modules used in electronic test and checkout instrumentation. A ten bit register provides failure monitor and indication for 1023 comparator circuits, and the automatic fault-isolation capability permits the electronic subsystems to be repaired by replacing the defective module.

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

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2014-01-01

    provided to the control system. In this paper a Karhunen-Loeve basis approach is designed for detecting changes in frequency response from rotating parts like a gearbox. The potential of this method is shown by applying it to an established Wind Turbine FDI and FTC Benchmark model. These faults...

  17. High-resolution imagery of active faulting offshore Al Hoceima, Northern Morocco

    Science.gov (United States)

    d'Acremont, E.; Gutscher, M.-A.; Rabaute, A.; Mercier de Lépinay, B.; Lafosse, M.; Poort, J.; Ammar, A.; Tahayt, A.; Le Roy, P.; Smit, J.; Do Couto, D.; Cancouët, R.; Prunier, C.; Ercilla, G.; Gorini, C.

    2014-09-01

    Two recent destructive earthquakes in 1994 and 2004 near Al Hoceima highlight that the northern Moroccan margin is one of the most seismically active regions of the Western Mediterranean area. Despite onshore geodetic, seismological and tectonic field studies, the onshore-offshore location and extent of the main active faults remain poorly constrained. Offshore Al Hoceima, high-resolution seismic reflection and swath-bathymetry have been recently acquired during the Marlboro-2 cruise. These data at shallow water depth, close to the coast, allow us to describe the location, continuity and geometry of three active faults bounding the offshore Nekor basin. The well-expressed normal-left-lateral onshore Trougout fault can be followed offshore during several kilometers with a N171°E ± 3° trend. Westward, the Bousekkour-Aghbal normal-left-lateral onshore fault is expressed offshore with a N020°E ± 4° trending fault. The N030°E ± 2° Bokkoya fault corresponds to the western boundary of the Plio-Quaternary offshore Nekor basin in the Al Hoceima bay and seems to define an en échelon tectonic pattern with the Bousekkour-Aghbal fault. We propose that these three faults are part of the complex transtensional system between the Nekor fault and the Al-Idrissi fault zone. Our characterization of the offshore expression of active faulting in the Al Hoceima region is consistent with the geometry and nature of the active fault planes deduced from onshore geomorphological and morphotectonic analyses, as well as seismological, geodetic and geodynamic data.

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

    Science.gov (United States)

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

    2015-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Jonguk Lee

    2016-04-01

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

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

    Science.gov (United States)

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

    2016-01-01

    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

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

    Science.gov (United States)

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

    2016-04-16

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

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

    Science.gov (United States)

    Meng, Xian-Ji; Yang, Guang-Hong

    2014-05-01

    This paper is concerned with the simultaneous fault detection and control problem for Itô-type stochastic time-delay systems. A full-order dynamic output feedback controller is designed to achieve the desired control and detection objectives. The main contributions of this paper are as follows: (1) for stochastic time-delay systems, the controller design with multiple objectives can be addressed by employing the multiple Lyapunov functions approach, (2) the dynamic output feedback controller synthesis conditions described by linear matrix inequalities (LMIs) are derived and (3) within the proposed fault detection and control framework, a better integrated control and detection performance can be obtained. Some numerical examples including the comparison results are presented to show the advantages of the proposed method.

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    OpenAIRE

    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...

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

    Directory of Open Access Journals (Sweden)

    T. Benslimane

    2006-01-01

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

  6. Operations management system advanced automation: Fault detection isolation and recovery prototyping

    Science.gov (United States)

    Hanson, Matt

    1990-01-01

    The purpose of this project is to address the global fault detection, isolation and recovery (FDIR) requirements for Operation's Management System (OMS) automation within the Space Station Freedom program. This shall be accomplished by developing a selected FDIR prototype for the Space Station Freedom distributed processing systems. The prototype shall be based on advanced automation methodologies in addition to traditional software methods to meet the requirements for automation. A secondary objective is to expand the scope of the prototyping to encompass multiple aspects of station-wide fault management (SWFM) as discussed in OMS requirements documentation.

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

    OpenAIRE

    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...

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

    Institute of Scientific and Technical Information of China (English)

    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.

  9. Active Fault Tolerant Control of Livestock Stable Ventilation System

    DEFF Research Database (Denmark)

    Gholami, Mehdi

    2011-01-01

    affine (PWA) components such as dead-zones, saturation, etc or contain piecewise nonlinear models which is the case for the climate control systems of the stables. Fault tolerant controller (FTC) is based on a switching scheme between a set of predefined passive fault tolerant controller (PFTC......). In the FTC part of the thesis, first a passive fault tolerant controller (PFTC) based on state feed-back is proposed for discretetime PWA systems. only actuator faults are considered. By dissipativity theory and H1 analysis, the problem is cast as a set of linear matrix inequalities (LMIs). In the next...... are not included, while due to the physical limitation, the input signal can not have any value. In continuing, a passive fault tolerant controller (PFTC) based on state feedback is proposed to track a reference signal while the control inputs are bounded....

  10. ABOUT THE WAVE MECHANISM OF ACTIVATION OF FAULTS IN SEISMIC ZONES OF THE LITHOSPHERE IN MONGOLIA

    Directory of Open Access Journals (Sweden)

    M. G. Mel’nikov

    2015-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Guillermo Heredia

    2011-01-01

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

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

    Science.gov (United States)

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

    2016-05-01

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

  13. A METHOD TO IMPROVE RELIABILITY OF GEARBOX FAULT DETECTION WITH ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    P.V. Srihari

    2010-12-01

    Full Text Available Fault diagnosis of gearboxes plays an important role in increasing the availability of machinery in condition monitoring. An effort has been made in this work to develop an artificial neural networks (ANN based fault detection system to increase reliability. Two prominent fault conditions in gears, worn-out and broken teeth, are simulated and five feature parameters are extracted based on vibration signals which are used as input features to the ANN based fault detection system developed in MATLAB, a three layered feed forward network using a back propagation algorithm. This ANN system has been trained with 30 sets of data and tested with 10 sets of data. The learning rate and number of hidden layer neurons are varied individually and the optimal training parameters are found based on the number of epochs. Among the five different learning rates used the 0.15 is deduced to be optimal one and at that learning rate the number of hidden layer neurons of 9 was the optimal one out of the three values considered. Then keeping the training parameters fixed, the number of hidden layers is varied by comparing the performance of the networks and results show the two and three hidden layers have the best detection accuracy.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Javier Rosero García

    2012-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Emmanuel Mazars

    2008-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Woohyun; Braun, J.

    2016-03-05

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

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

    DEFF Research Database (Denmark)

    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....

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

    Directory of Open Access Journals (Sweden)

    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.

  20. Frequency based Wind Turbine Gearbox Fault Detection applied to a 750 kW Wind Turbine

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Nejad, Amir R.

    2014-01-01

    turbines. One of the critical components in modern wind turbines is the gearbox. Failures in the gearbox are costly both due to the cost of the gearbox itself, but also due to lost power generation during repair of it. Wind turbine gearboxes are consequently monitored by condition monitoring systems...... operating in parallel with the control system, and also uses additional sensors measuring different accelerations and noises, etc. In this paper gearbox data from high fidelity gearbox model of a 750 kW wind turbine gearbox, simulated with and without faults are used to shown the potential of frequency...... based detection schemes applied on measurements normally available in a wind controller system. This paper shows that two given faults in the gearbox can be detected using a frequency based detection approach applied to sensor signals normally available in the wind turbine control system. This means...

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

    Institute of Scientific and Technical Information of China (English)

    Wang Haiyun; Xie Lili; Tao Xiaxin; Li Jie

    2006-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

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

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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)

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

    Science.gov (United States)

    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.

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

    Data.gov (United States)

    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...

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

    Science.gov (United States)

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

    2016-10-01

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

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    Hongru WANG; Changhong WANG; Shaoshuai MOU; Huijun GAO

    2007-01-01

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

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

    Science.gov (United States)

    Jiang, Hongkai; Xia, Yong; Wang, Xiaodong

    2013-12-01

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

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

    International Nuclear Information System (INIS)

    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.

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

    DEFF Research Database (Denmark)

    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...

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

    Directory of Open Access Journals (Sweden)

    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.

  20. A Delay System Approach to Fault Detection Filter of Networked Control Systems

    Institute of Scientific and Technical Information of China (English)

    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.

  1. Fault detection and diagnosis of the deaerator level control system in nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  3. An adaptive SK technique and its application for fault detection of rolling element bearings

    Science.gov (United States)

    Wang, Yanxue; Liang, Ming

    2011-07-01

    In this paper, we propose an adaptive spectral kurtosis (SK) technique for the fault detection of rolling element bearings. The primary contribution is adaptive determination of the bandwidth and center frequency. This is implemented with successive attempts to right-expand a given window along the frequency axis by merging it with its subsequent neighboring windows. Influence of the parameters such as the initial window function, bandwidth and window overlap on the merged windows as well as how to choose those parameters in practical applications are explored. Based on simulated experiments, it can be found that the proposed technique can further enhance the SK-based method as compared to the kurtogram approach. The effectiveness of the proposed method in fault detection of the rolling element bearings is validated using experimental signals.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  6. A 665 year record of Coulomb stress changes on active faults in the central Apennines, Italy.

    Science.gov (United States)

    Wedmore, L. N. J.; Faure Walker, J.; Roberts, G.; McCaffrey, K. J. W.; Sammonds, P. R.

    2014-12-01

    Active extension in the central Apennines is accommodated on numerous 20-30km long normal faults. Over multiple earthquake cycles fault slip is controlled by viscous flow in narrow shear zones, which are below the brittle seismogenic crust and are driven by upwelling mantle beneath the central Apennines. However, on short timescales, there is evidence for clustering along strike on the north eastern set of faults in the region, with the south western faults comparatively quiet during the period of reliable historical earthquake records (since 1349 AD). In contrast, 15±3ka strain rates show no evidence of skewness towards the north eastern faults. This suggests that on short timescales, elastic loading and fault interaction may be controlling the location of earthquakes and the seismic hazard, as opposed to the view that fault activity has permanently migrated from the south west flank of the central Apennines to the north east flank. We used Coulomb stress modelling to test whether the sequence of historical earthquakes can be explained by stress triggering and elastic loading. Palaeoseismic and historical records were used to reconstruct the co-seismic static Coulomb stress changes for 27 earthquakes in central Italy from 1349-2009. 15±3ka throws measured across faults in the area were used as an analogue for the slip distributions, with the slip direction constrained by field measurements of frictional wear striae on exposed bedrock fault scarps. Interseismic loading was modelled using a shear zone rheology below the seismogenic zone of each fault; slip rates measured at the surface were used to control the rate of loading. The sensitivity of the model was explored by iterating varying slip distributions, fault kinematics and earthquake locations. We show that for sequences of clustered earthquakes that occurred on timescales of days to weeks, co-seismic static Coulomb stress transfer can explain the pattern of faulting with stress changes of 0.001-0.1 MPa

  7. Software fault detection and recovery in critical real-time systems: An approach based on loose coupling

    International Nuclear Information System (INIS)

    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

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

    DEFF Research Database (Denmark)

    Katebi, S.D.; Blanke, M.; Katebi, M.R.

    This report describes a comparative study between two approaches to fault detection and isolation in dynamic systems. The first approach uses a parametric model of the system. The main components of such techniques are residual and signature generation for processing and analyzing. The second...... algorithms employed are adopted from the template matching in pattern recognition. Extensive simulation studies are performed to demonstrate satisfactory performance of the proposed techniques. The advantages and disadvantages of each approach are discussed and analyzed....

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

    Science.gov (United States)

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

    1993-01-01

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

  10. Fault Detection And Diagnosis For Air Conditioners And Heat Pumps Based On Virtual Sensors

    OpenAIRE

    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...

  11. Evaluating Fault Detection and Diagnostics Protocols Applied to Air-Cooled Vapor Compression Air-Conditioners

    OpenAIRE

    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...

  12. Gearbox Fault Detection through PSO Exact Wavelet Analysis and SVM Classifier

    OpenAIRE

    Zamanian, Amir Hosein; Ohadi, Abdolreza

    2016-01-01

    Time-frequency methods for vibration-based gearbox faults detection have been considered the most efficient method. Among these methods, continuous wavelet transform (CWT) as one of the best time-frequency method has been used for both stationary and transitory signals. Some deficiencies of CWT are problem of overlapping and distortion ofsignals. In this condition, a large amount of redundant information exists so that it may cause false alarm or misinterpretation of the operator. In this pap...

  13. Intelligent alarms detection for the analysis of system fault impact on business

    OpenAIRE

    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...

  14. 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

    Science.gov (United States)

    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

  15. VIBRATION ANALYSIS FOR DETECTION AND LOCALIZATION THE FAULTS OF ROTATING MACHINERY USING WAVELET TECHINIQUES

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Schreiner, John N.

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

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

    Institute of Scientific and Technical Information of China (English)

    Abhishek Pandey; Nicolas H. Younan

    2011-01-01

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

  18. Real-time fault detection for a waste-water treatment plant

    International Nuclear Information System (INIS)

    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.

  19. DETECTION OF FAULT LOCATION ON THE POWER LINES 6–35 kV WITH UNILATERAL FEED

    Directory of Open Access Journals (Sweden)

    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. 

  20. Results From NICLAKES Survey of Active Faulting Beneath Lake Nicaragua, Central American Volcanic Arc

    Science.gov (United States)

    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

  1. Fault Diagnosis and Accommodation of LTI systems by modified Youla parameterization

    Directory of Open Access Journals (Sweden)

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. On linear observers and application to fault detection in synchronous generators

    Institute of Scientific and Technical Information of China (English)

    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.

  5. Development of Fault Detection and Diagnosis Schemes for Industrial Refrigeration Systems

    DEFF Research Database (Denmark)

    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....

  6. Bond Graph Modelling for Fault Detection and Isolation of an Ultrasonic Linear Motor

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2011-05-01

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

  8. Zipper Faults

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

    Science.gov (United States)

    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

    Directory of Open Access Journals (Sweden)

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    KAUST Repository

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

    Directory of Open Access Journals (Sweden)

    Yun Li

    2013-01-01

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

  17. Model-Based Water Wall Fault Detection and Diagnosis of FBC Boiler Using Strong Tracking Filter

    Directory of Open Access Journals (Sweden)

    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.

  18. Design of the instrument fault detection for TRIGA Mark II Bandung

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    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.

  1. A FAULT DETECTION SENSOR FOR CIRCUIT AGING USING DOUBLE-EDGE-TRIGGERED FLIP-FLOP

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Directory of Open Access Journals (Sweden)

    M. Manimozhi

    2014-05-01

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

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

    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.

  5. Fault Activities and Paleoearthquake Events along the Piedmont Fault (Wujumengkou-Dongfengcun Segment) of Mt. Serteng, Inner Mongolia

    Institute of Scientific and Technical Information of China (English)

    Yang Xiaoping; Ran Yongkang; Hu Bo; Guo Wensheng

    2003-01-01

    Based on remote sensing data, field investigation and trench measurement along the piedmont fault (Wujumengkou-Dongfengcun) of Mt. Serteng, the vertical displacement rate has been found to be 0.88~1.83mm/a since the late period of late Pleistocene and 0.89mm/a since the middle period of Holocene. Using the progressive constraining method, five paleoearthquake events have been distinguished from two large trenches since Holocene. They occurred 9000±1300a B.P., 6500±500a B.P., 5770a B.P., 4200±300a B.P. and 3250±250a B.P., respectively. From the late period of late Pleistocene to the beginning of Holocene, some paleoearthquake events may have been missed due to a variety of reasons. All of the paleoearthquake events displayed clustering characteristics to a certain extent. The first duster was occurred around 8900a B.P., the second cluster occurred between 5700~6500a B.P. and the last cluster was occurred in 3250~4200 a B.P. The interval between the first cluster and the second cluster was about 2400a while that between the second cluster and the third cluster was only 1570a. No earthquake events have cut the ground surface along this active fault segment since 3250a B.P. The lapse time is more than the recurrence interval between two paleoearthquake clusters. Therefore, there is a potential risk for a recurring earthquake along this active fault segment.

  6. Analysis of Dynamics in Multiphysics Modelling of Active Faults

    Directory of Open Access Journals (Sweden)

    Sotiris Alevizos

    2016-09-01

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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

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

    Indian Academy of Sciences (India)

    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.

  10. Bearing Fault Detection Using Multi-Scale Fractal Dimensions Based on Morphological Covers

    Directory of Open Access Journals (Sweden)

    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.

  11. UAV's for active tectonics : case example from the Longitudinal Valley and the Chishan Faults (Southern Taiwan)

    Science.gov (United States)

    Deffontaines, Benoit; Chang, Kuo-Jen; Chan, Yu-Chang; Chen, Rou-Fei; Hsieh, Yu-Chung

    2015-04-01

    Taiwan is a case example to study active tectonics due to the active NW-SE collision of the Philippine and Eurasian Sea Plates as the whole convergence reaches 10cm/y. In order to decipher the structural active tectonics geometry, we used herein UAV's to get high resolution Digital Terrain Model (DTM) in local active tectonics key areas. Classical photo-interpretation where then developped in order to structurally interprete these data, confirmed by field studies. Two location had first been choosen in order to highlight the contribution of such high resolution DTM in SW Taiwan on the Longitudinal Valley Fault (SE Taiwan) on its southern branch from Pinting to Luyeh terraces (Pinanshan) where UAV's lead to better interprete the location of the outcropping active deformations. Combined with available GPS data and PALSAR interferometry (Deffontaines et Champenois et al., submitted) it is then possible to reconstruct the way of the present deformation in this local area. In the Pinting terraces, If the western branch of the fault correspond to an outcroping thrust fault, the eastern branch act as a a growing active anticline that may be characterized and quantified independantly. The interpretation of the UAV's high resolution DTM data on the Chishan Fault (SW Taiwan) reveals also the geometry of the outcropping active faults complex structural behaviour. If the Chishan Fault act as a thrusting in its northern tip (close to Chishan city), it acts as a right lateral strike-slip fault north of Chaoshan (Kaohsiung city) as described by Deffontaines et al. 2014. Therefore UAV's are a so useful tool to get very high resolution topographic data in Taiwan that are of great help to get the geometry of the active neotectonic structures in Taiwan.

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

    Science.gov (United States)

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

    2012-12-01

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

  13. Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection

    Directory of Open Access Journals (Sweden)

    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

  14. Multiple tests for wind turbine fault detection and score fusion using two- level multidimensional scaling (MDS)

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2016-08-19

    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.

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

    Science.gov (United States)

    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

  18. Evidence of multistage late Quaternary strong earthquakes on typical segments of Longmenshan Active Fault Zone in Sichuan, China

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Investigation of offset landforms and trench excavation are important means to acquire the evidence of multistage activities of active faults. Here we present the result of fault trough investigation in Beichuan County and the Pingtong Town of Pingwu County along the Longmenshan Central Fault Belt, as well as the result from trench excavation at the platform foreslope in Hanwang Town of Mianzhu County on the Longmenshan Front Range Fault Belt. These results show that at least three fault activity events, including the Wenchuan earthquake, occurred in the Beichuan fault trough, at least two, including the Wenchuan earthquake, at Pingtong fault trough, and 2-3 paleoearthquakes in the Hanwang trench. Among these three localities, the times of the last strong earthquake prior to Wenchuan earthquake at Beichuan fault trough and Hanwang trench are close, approximately 6000 years ago, i.e., greater than 5.8 ka and smaller than 6.63 ka ago. This provides the evidence of synchronous activity of the Central Fault Belt and the Front Range Fault Belt of the Longmenshan Active Fault Zone during the previous strong earthquake activities prior to Wenchuan earthquake.

  19. Evidence of multistage late Quaternary strong earthquakes on typical segments of Longrnenshan Active Fault Zone in Sichuan,China

    Institute of Scientific and Technical Information of China (English)

    JIANG WaLi; XIE XinSheng; ZHANG JinFa; SUN ChangBin; HUANG Wei; SHENG Qiang; FENG XiYing

    2009-01-01

    Investigation of offset landforms and trench excavation are important means to acquire the evidence of multistage activities of active faults.Here we present the result of fault trough investigation in Beichuan County and the Pingtong Town of Pingwu County along the Longmenshan Central Fault Belt,as well as the result from trench excavation at the platform foreslope in Hanwang Town of Mianzhu County on the Longmenshan Front Range Fault Belt.These results show that at least three fault activity events,including the Wenchuan earthquake,occurred in the Beichuan fault trough,at least two,including the Wenchuan earthquake,at Pingtong fault trough,and 2-3 paleoearthquakes in the Hanwang trench.Among these three localities,the times of the last strong earthquake prior to Wenchuan earthquake at Beichuan fault trough and Hanwang trench are close,approximately 6000 years ago,i.e.,greater than 5.8 ka and smaller than 6.63 ka ago.This provides the evidence of synchronous activity of the Central Fault Belt and the Front Range Fault Belt of the Longmenshan Active Fault Zone during the previous strong earthquake activities prior to Wenchuan earthquake.

  20. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    International Nuclear Information System (INIS)

    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

  1. Implementation of a Fractional Model-Based Fault Detection Algorithm into a PLC Controller

    Science.gov (United States)

    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.

  2. Modeling and simulation of a reformate supplied PEM fuel cell stack, application to fault detection

    OpenAIRE

    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...

  3. Fault detection in non-linear systems based on type-2 fuzzy logic

    Science.gov (United States)

    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.

  4. Support vector machine based fault detection approach for RFT-30 cyclotron

    Science.gov (United States)

    Kong, Young Bae; Lee, Eun Je; Hur, Min Goo; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-10-01

    An RFT-30 is a 30 MeV cyclotron used for radioisotope applications and radiopharmaceutical researches. The RFT-30 cyclotron is highly complex and includes many signals for control and monitoring of the system. It is quite difficult to detect and monitor the system failure in real time. Moreover, continuous monitoring of the system is hard and time-consuming work for human operators. In this paper, we propose a support vector machine (SVM) based fault detection approach for the RFT-30 cyclotron. The proposed approach performs SVM learning with training samples to construct the classification model. To compensate the system complexity due to the large-scale accelerator, we utilize the principal component analysis (PCA) for transformation of the original data. After training procedure, the proposed approach detects the system faults in real time. We analyzed the performance of the proposed approach utilizing the experimental data of the RFT-30 cyclotron. The performance results show that the proposed SVM approach can provide an efficient way to control the cyclotron system.

  5. A new statistical modeling and detection method for rolling element bearing faults based on alpha-stable distribution

    Science.gov (United States)

    Yu, Gang; Li, Changning; Zhang, Jianfeng

    2013-12-01

    Due to limited information given by traditional local statistics, a new statistical modeling method for rolling element bearing fault signals is proposed based on alpha-stable distribution. In order to fully take advantages of complete information provided by alpha-stable distribution, this paper focuses on testing the validity of the proposed statistical model. A number of hypothetical test methods were applied to practical bearing fault vibration signals with different fault types and degrees. Through testing on the consistency of three alpha-stable parameter estimation methods, and the probability density function fitting level between fault signals and their corresponding hypothetical alpha-stable distributions, it can be concluded that such a non-Gaussian model is sufficient to thoroughly describe the statistical characteristics of bearing fault signals with impulsive behaviors, and consequently the alpha-stable hypothesis is verified. In the meantime, a new bearing fault detection method based on kurtogram and α parameter of the alpha-stable model is proposed, experimental results have shown that the proposed method has better performance on detecting incipient bearing faults than that based on the traditional kurtogram.

  6. Detection and Localization of Tooth Breakage Fault on Wind Turbine Planetary Gear System considering Gear Manufacturing Errors

    Directory of Open Access Journals (Sweden)

    Y. Gui

    2014-01-01

    Full Text Available Sidebands of vibration spectrum are sensitive to the fault degree and have been proved to be useful for tooth fault detection and localization. However, the amplitude and frequency modulation due to manufacturing errors (which are inevitable in actual planetary gear system lead to much more complex sidebands. Thus, in the paper, a lumped parameter model for a typical planetary gear system with various types of errors is established. In the model, the influences of tooth faults on time-varying mesh stiffness and tooth impact force are derived analytically. Numerical methods are then utilized to obtain the response spectra of the system with tooth faults with and without errors. Three system components (including sun, planet, and ring gears with tooth faults are considered in the discussion, respectively. Through detailed comparisons of spectral sidebands, fault characteristic frequencies of the system are acquired. Dynamic experiments on a planetary gear-box test rig are carried out to verify the simulation results and these results are of great significances for the detection and localization of tooth faults in wind turbines.

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    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...

  8. A Robust Fault Detection and Isolation Scheme Based on Unknown Input Observers for Discrete Time-delay System with Disturbance

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

    This paper proposes a robust fault detection and isolation (FDI) scheme for discrete time-delay system with disturbance. The FDI scheme can not only detect but also isolate the faults. The lifting method is exploited to transform the discrete time-delay system into the non-time-delay form. A generalized structured residual set is designed based on the unknown input observer (UIO). For each residual generator, one of the system input signals together with the corresponding actuator fault and the disturbance signals are treated as an unknown input term. The residual signals can not only be robust against the disturbance, but also be of the capacity to isolate the actuator faults. The proposed method has been verified by a numerical example.

  9. Recurrence characteristics of late-quaternary strong earthquakes on the major active faults along the northern border of Ordos block

    Institute of Scientific and Technical Information of China (English)

    RAN; Yongkang; (冉勇康); CHEN; Lichun; (陈立春); YANG; Xiaoping; (杨晓平); HAN; Zhujun; (韩竹军)

    2003-01-01

    Through study on trenches, analysis of recurrence characteristics and recurrence interval cluster/gap of strong earthquakes along the major active faults on the northern border of Ordos block, we found 62 paleoearthquakes that occurred in the late Quaternary, including 33 earthquakes occurring in the Holocene. The recurrence characteristics of the paleoearthquakes are different at three levels, segments, faults, and fault zones. The strong seismic sequence on the independent segments is mostly characterized by long- and short-interval recurrences, while that on the faults and in fault zone is characterized clearly by random and cluster recurrences. Results of the moving window test indicate that the probabilities of "temporal cluster or gap", caused by random coincidence as opposed to intersegment contagion, are 64% and 70% for the Serteng piedmont fault and for the south-border fault of Wula Mountains, respectively, no clear interaction among the segments of each fault; while the probability is 26.8% for the whole fault zone, suggesting a clear interaction among the faults of this fault zone. These recurrence characteristics may imply an effect of the entire block motion on the recurrence of strong earthquakes. Moreover, the elapsed time for the Wujumeng Pass-Dongfeng Village segment of Serteng piedmont fault and the Tuzuo Banner-Wusutu and the Hohhot segments of Daqingshan piedmont fault has exceeded the average recurrence interval, hence these three segments may be the possible places for future strong earthquakes.

  10. Active faults and seismogenic models for the Urumqi city, Xinjiang Autonomous Region, China

    Science.gov (United States)

    Li, Yingzhen; Yu, Yang; Shen, Jun; Shao, Bo; Qi, Gao; Deng, Mei

    2016-06-01

    We have studied the characteristics of the active faults and seismicity in the vicinity of Urumqi city, the capital of Xinjiang Autonomous Region, China, and have proposed a seismogenic model for the assessment of earthquake hazard in this area. Our work is based on an integrated analysis of data from investigations of active faults at the surface, deep seismic reflection soundings, seismic profiles from petroleum exploration, observations of temporal seismic stations, and the precise location of small earthquakes. We have made a comparative study of typical seismogenic structures in the frontal area of the North Tianshan Mountains, where Urumqi city is situated, and have revealed the primary features of the thrust-fold-nappe structure there. We suggest that Urumqi city is comprised two zones of seismotectonics which are interpreted as thrust-nappe structures. The first is the thrust nappe of the North Tianshan Mountains in the west, consisting of the lower (root) thrust fault, middle detachment, and upper fold-uplift at the front. Faults active in the Pleistocene are present in the lower and upper parts of this structure, and the detachment in the middle spreads toward the north. In the future, M7 earthquakes may occur at the root thrust fault, while the seismic risk of frontal fold-uplift at the front will not exceed M6.5. The second structure is the western flank of the arc-like Bogda nappe in the east, which is also comprised a root thrust fault, middle detachment, and upper fold-uplift at the front, of which the nappe stretches toward the north; several active faults are also developed in it. The fault active in the Holocene is called the South Fukang fault. It is not in the urban area of Urumqi city. The other three faults are located in the urban area and were active in the late Pleistocene. In these cases, this section of the nappe structure near the city has an earthquake risk of M6.5-7. An earthquake M S6.6, 60 km east to Urumqi city occurred along the

  11. LiDAR-Assisted identification of an active fault near Truckee, California

    Science.gov (United States)

    Hunter, L.E.; Howle, J.F.; Rose, R.S.; Bawden, G.W.

    2011-01-01

    We use high-resolution (1.5-2.4 points/m2) bare-earth airborne Light Detection and Ranging (LiDAR) imagery to identify, map, constrain, and visualize fault-related geomorphology in densely vegetated terrain surrounding Martis Creek Dam near Truckee, California. Bare-earth LiDAR imagery reveals a previously unrecognized and apparently youthful right-lateral strike-slip fault that exhibits laterally continuous tectonic geomorphic features over a 35-km-long zone. If these interpretations are correct, the fault, herein named the Polaris fault, may represent a significant seismic hazard to the greater Truckee-Lake Tahoe and Reno-Carson City regions. Three-dimensional modeling of an offset late Quaternary terrace riser indicates a minimum tectonic slip rate of 0.4 ?? 0.1 mm/yr.Mapped fault patterns are fairly typical of regional patterns elsewhere in the northern Walker Lane and are in strong coherence with moderate magnitude historical seismicity of the immediate area, as well as the current regional stress regime. Based on a range of surface-rupture lengths and depths to the base of the seismogenic zone, we estimate a maximum earthquake magnitude (M) for the Polaris fault to be between 6.4 and 6.9.

  12. Voltage Quality Enhancement and Fault Current Limiting with Z-Source based Series Active Filter

    Directory of Open Access Journals (Sweden)

    F. Gharedaghi

    2011-11-01

    Full Text Available In this study, series active filter or dynamic voltage restorer application is proposed for reduction of downstream fault current in addition to voltage quality enhancement. Recently, the application of Z-source inverter is proposed in order to optimize DVR operation. This inverter makes DVR to operate appropriately when the energy storage device’s voltage level severely falls. Here, the Z-source inverter based DVR is proposed to compensate voltage disturbance at the PCC and to reduce the fault current in downstream of DVR. By calculating instantaneous current magnitude in synchronous frame, control system recognizes if the fault exists or not, and determines whether DVR should compensate voltage disturbance or try to reduce the fault current. The proposed system is simulated under voltage sag and swell and short circuit conditions. The simulation results show that the system operates correctly under voltage sag and short circuit conditions.

  13. Active faulting in northern Chile: ramp stacking and lateral decoupling along a subduction plate boundary?

    Science.gov (United States)

    Armijo, Rolando; Thiele, Ricardo

    1990-04-01

    Two large features parallel to the coastline of northern Chile have long been suspected to be the sites of young or active deformation: (1) The 700-km long Coastal Scarp, with average height (above sea level) of about 1000 m; (2) The Atacama Fault zone, that stretches linearly for about 1100 km at an average distance of 30-50 km from the coastline. New field observations combined with extensive analysis of aerial photographs demonstrate that both the Coastal Scarp and the Atacama Fault are zones of Quaternary and current fault activity. Little-degraded surface breaks observed in the field indicate that these fault zones have recently generated large earthquakes ( M = 7-8). Normal fault offsets observed in marine terraces in the Coastal Scarp (at Mejillones Peninsula) require tectonic extension roughly orthogonal to the compressional plate boundary. Strike-slip offsets of drainage observed along the Salar del Carmen and Cerro Moreno faults (Atacama Fault system) imply left-lateral displacements nearly parallel to the plate boundary. The left-lateral movement observed along the Atacama Fault zone may be a local consequence of E-W extension along the Coastal Scarp. But if also found everywhere along strike, left-lateral decoupling along the Atacama Fault zone would be in contradiction with the right lateral component of Nazca-South America motion predicted by models of present plate kinematics. Clockwise rotation with left-lateral slicing of the Andean orogen south of the Arica bend is one way to resolve this contradiction. The Coastal Scarp and the Atacama Fault zone are the most prominent features with clear traces of activity within the leading edge of continental South America. The great length and parallelism of these features with the subduction zone suggest that they may interact with the subduction interface at depth. We interpret the Coastal Scarp to be a west-dipping normal fault or flexure and propose that it is located over an east-dipping ramp stack at

  14. Compound faults detection of rolling element bearing based on the generalized demodulation algorithm under time-varying rotational speed

    Science.gov (United States)

    Zhao, Dezun; Li, Jianyong; Cheng, Weidong; Wen, Weigang

    2016-09-01

    Multi-fault detection of the rolling element bearing under time-varying rotational speed presents a challenging issue due to its complexity, disproportion and interaction. Computed order analysis (COA) is one of the most effective approaches to remove the influences of speed fluctuation, and detect all the features of multi-fault. However, many interference components in the envelope order spectrum may lead to false diagnosis results, in addition, the deficiencies of computational accuracy and efficiency also cannot be neglected. To address these issues, a novel method for compound faults detection of rolling element bearing based on the generalized demodulation (GD) algorithm is proposed in this paper. The main idea of the proposed method is to exploit the unique property of the generalized demodulation algorithm in transforming an interested instantaneous frequency trajectory of compound faults bearing signal into a line paralleling to the time axis, and then the FFT algorithm can be directly applied to the transformed signal. This novel method does not need angular resampling algorithm which is the key step of the computed order analysis, and is hence free from the deficiencies of computational error and efficiency. On the other hand, it only acts on the instantaneous fault characteristic frequency trends in envelope signal of multi-fault bearing which include rich fault information, and is hence free from irrelevant items interferences. Both simulated and experimental faulty bearing signal analysis validate that the proposed method is effective and reliable on the compound faults detection of rolling element bearing under variable rotational speed conditions. The comprehensive comparison with the computed order analysis further shows that the proposed method produces higher accurate results in less computation time.

  15. Fault Detection Based on Multi-Scale Local Binary Patterns Operator and Improved Teaching-Learning-Based Optimization Algorithm

    OpenAIRE

    Hongjian Zhang; Ping He; Xudong Yang

    2015-01-01

    Aiming to effectively recognize train center plate bolt loss faults, this paper presents an improved fault detection method. A multi-scale local binary pattern operator containing the local texture information of different radii is designed to extract more efficient discrimination information. An improved teaching-learning-based optimization algorithm is established to optimize the classification results in the decision level. Two new phases including the worst recombination phase and the cuc...

  16. Natural Radiation for Identification and Evaluation of Risk Zones for Affectation of Activated Faults in Aquifer Overexploited.

    Science.gov (United States)

    Ramos-Leal, J.; Lopez-Loera, H.; Carbajal-Perez, N.

    2007-05-01

    In basins as Mexico, Michoacán, Guanajuato, Queretaro, Aguascalientes and San Luis Potosi, the existence of faults and fractures have affected the urban infrastructure, lines of conduction of drinkable water, pipelines, etc., that when not being identified and considered, they don't reflect the real impact that these cause also to the aquifer system, modifying the permeability of the means and in occasions they work as preferential conduits that communicate hydraulically potentially to the aquifer with substances pollutants (metals, fertilizers, hydrocarbons, waste waters, etc.) located in the surface. In the Valley of San Luis Potosi, Villa of Reyes, Arista, Ahualulco and recently The Huizache-Matehuala is being strongly affected by faulting and supposedly due cracking to subsidence, however, the regional tectonic could also be the origin of this phenomenon. To know the origin of the faults and affectation to the vulnerability of the aquifer few works they have been carried out in the area. A preliminary analysis indicates that it is possible that a tectonic component is affecting the area and that the vulnerability of the aquifer in that area you this increasing. Before such a situation, it is necessary to carry out the isotopic study of the same one, for this way to know among other things, isotopic characterization, recharge places and addresses of flow of the groundwater; quality of waters and the behavior hydrochemistry with relationship to the faults. High radon values were measured in San Luis Potosi Valley, the natural source of radon could be the riolites and however, these are located to almost a once thousand meters deep for what the migration of the gas is not very probable. The anomalies radiometrics was not correlation with the faults in this case. In some areas like the Valley of Celaya, the origin of the structures and the tectonic activity in the area was confirmed, identifying the structural arrangement of the faulting, the space relationships

  17. Recently Active Traces of the Berryessa Fault, California: A Digital Database

    Science.gov (United States)

    Lienkaemper, James J.

    2012-01-01

    The purpose of this map is to show the location of and evidence for recent movement on active fault traces within the Berryessa section and parts of adjacent sections of the Green Valley Fault Zone, California. The location and recency of the mapped traces is primarily based on geomorphic expression of the fault as interpreted from large-scale 2010 aerial photography and from 2007 and 2011 0.5 and 1.0 meter bare-earth LiDAR imagery (that is, high-resolution topographic data). In a few places, evidence of fault creep and offset Holocene strata in trenches and natural exposures have confirmed the activity of some of these traces. This publication is formatted both as a digital database for use within a geographic information system (GIS) and for broader public access as map images that may be browsed on-line or download a summary map. The report text describes the types of scientific observations used to make the map, gives references pertaining to the fault and the evidence of faulting, and provides guidance for use of and limitations of the map.

  18. Comparative Study of Time-Frequency Decomposition Techniques for Fault Detection in Induction Motors Using Vibration Analysis during Startup Transient

    Directory of Open Access Journals (Sweden)

    Paulo Antonio Delgado-Arredondo

    2015-01-01

    Full Text Available Induction motors are critical components for most industries and the condition monitoring has become necessary to detect faults. There are several techniques for fault diagnosis of induction motors and analyzing the startup transient vibration signals is not as widely used as other techniques like motor current signature analysis. Vibration analysis gives a fault diagnosis focused on the location of spectral components associated with faults. Therefore, this paper presents a comparative study of different time-frequency analysis methodologies that can be used for detecting faults in induction motors analyzing vibration signals during the startup transient. The studied methodologies are the time-frequency distribution of Gabor (TFDG, the time-frequency Morlet scalogram (TFMS, multiple signal classification (MUSIC, and fast Fourier transform (FFT. The analyzed vibration signals are one broken rotor bar, two broken bars, unbalance, and bearing defects. The obtained results have shown the feasibility of detecting faults in induction motors using the time-frequency spectral analysis applied to vibration signals, and the proposed methodology is applicable when it does not have current signals and only has vibration signals. Also, the methodology has applications in motors that are not fed directly to the supply line, in such cases the analysis of current signals is not recommended due to poor current signal quality.

  19. Guaranteed Cost Active Fault-tolerant Control of Networked Control System with Packet Dropout and Transmission Delay

    Institute of Scientific and Technical Information of China (English)

    Xiao-Yuan Luo; Mei-Jie Shang; Cai-Lian Chen; Xin-Ping Guan

    2010-01-01

    The problem of guaranteed cost active fault-tolerant controller (AFTC) design for networked control systems (NCSs)with both packet dropout and transmission delay is studied in this paper.Considering the packet dropout and transmission delay,a piecewise constant controller is adopted.With a guaranteed cost function,optimal controllers whose number is equal to the number of actuators are designed,and the design process is formulated as a convex optimal problem that can be solved by existing software.The control strategy is proposed as follows:when actuator failures appear,the fault detection and isolation unit sends out the information to the controller choosing strategy,and then the optimal stabilizing controller with the smallest guaranteed cost value is chosen.Two illustrative examples are given to demonstrate the effectiveness of the proposed approach.By comparing with the existing methods,it can be seen that our method has a better performance.

  20. Detection of faults in rotating machinery using periodic time-frequency sparsity

    Science.gov (United States)

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

    2016-11-01

    This paper addresses the problem of extracting periodic oscillatory features in vibration signals for detecting faults in rotating machinery. To extract the feature, we propose an approach in the short-time Fourier transform (STFT) domain where the periodic oscillatory feature manifests itself as a relatively sparse grid. To estimate the sparse grid, we formulate an optimization problem using customized binary weights in the regularizer, where the weights are formulated to promote periodicity. In order to solve the proposed optimization problem, we develop an algorithm called augmented Lagrangian majorization-minimization algorithm, which combines the split augmented Lagrangian shrinkage algorithm (SALSA) with majorization-minimization (MM), and is guaranteed to converge for both convex and non-convex formulation. As examples, the proposed approach is applied to simulated data, and used as a tool for diagnosing faults in bearings and gearboxes for real data, and compared to some state-of-the-art methods. The results show that the proposed approach can effectively detect and extract the periodical oscillatory features.