Niemann, Hans Henrik; Poulsen, Niels Kjølstad
from auxiliary input to residual outputs. The analysis is based on a singular value decomposition of these transfer functions Based on this analysis, it is possible to design auxiliary input as well as design of the associated residual vector with respect to every single parametric fault in the system......The focus in this paper is on active fault detection (AFD) for MIMO systems with parametric faults. The problem of design of auxiliary inputs with respect to detection of parametric faults is investigated. An analysis of the design of auxiliary inputs is given based on analytic transfer functions...
Niemann, Hans Henrik; Stoustrup, Jakob; Poulsen, Niels Kjølstad
This paper is focusing on active fault detection (AFD) for parametric faults in closed-loop systems. This auxiliary input applied for the fault detection will also disturb the external output and consequently reduce the performance of the controller. Therefore, only small auxiliary inputs are used...... modify the feedback controller with a minor effect on the external output in the fault free case. Further, in the faulty case, the signature of the auxiliary input can be optimized. This is obtained by using a band-pass filter for the YJBK parameter that is only effective in a small frequency range where...... the frequency for the auxiliary input is selected. This gives that it is possible to apply an auxiliary input with a reduced amplitude. An example is included to show the results....
Yeganeh Fallah, Arash; Taghikhany, Touraj
Recent decades have witnessed much interest in the application of active and semi-active control strategies for seismic protection of civil infrastructures. However, the reliability of these systems is still in doubt as there remains the possibility of malfunctioning of their critical components (i.e. actuators and sensors) during an earthquake. This paper focuses on the application of the sliding mode method due to the inherent robustness of its fault detection observer and fault-tolerant control. The robust sliding mode observer estimates the state of the system and reconstructs the actuators’ faults which are used for calculating a fault distribution matrix. Then the fault-tolerant sliding mode controller reconfigures itself by the fault distribution matrix and accommodates the fault effect on the system. Numerical simulation of a three-story structure with magneto-rheological dampers demonstrates the effectiveness of the proposed fault-tolerant control system. It was shown that the fault-tolerant control system maintains the performance of the structure at an acceptable level in the post-fault case.
Wilson, Edward (Inventor)
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.
Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas;
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...
Niemann, Hans Henrik; Poulsen, Niels Kjølstad
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...
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
Stoustrup, Jakob; Niemann, Hans Henrik
The problem of fault detection and isolation of parametric faults is considered in this paper. A fault detection problem based on parametric faults are associated with internal parameter variations in the dynamical system. A fault detection and isolation method for parametric faults is formulated...
King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
The PV Fault Detection Tool project plans to demonstrate that the FDT can (a) detect catastrophic and degradation faults and (b) identify the type of fault. This will be accomplished by collecting fault signatures using different instruments and integrating this information to establish a logical controller for detecting, diagnosing and classifying each fault.
This master’s thesis concerns three different areas in the field of fault detection in photovoltaic systems.Previous studies have concerned homogeneous systems with a large set of parameters being observed,while this study is focused on a more restrictive case. The first problem is to discover immediate faults occurring in solar panels. A new online algorithm is developed based on similarity measures with in a single installation. It performs reliably and is able to detect all significant fau...
Niemann, Hans Henrik
An algebraic approach is given for a design of a static residual weighting factor in connection with fault detection. A complete parameterization is given of the weighting factor which will minimize a given performance index......An algebraic approach is given for a design of a static residual weighting factor in connection with fault detection. A complete parameterization is given of the weighting factor which will minimize a given performance index...
Hernandez-Alcantara, Diana; Morales-Menendez, Ruben; Amezquita-Brooks, Luis
Fault detection for automotive semi-active shock absorbers is a challenge due to the non-linear dynamics and the strong influence of the disturbances such as the road profile. First obstacle for this task, is the modeling of the fault, which has been shown to be of multiplicative nature. Many of the most widespread fault detection schemes consider additive faults. Two model-based fault algorithms for semiactive shock absorber are compared: an observer-based approach and a parameter identification approach. The performance of these schemes is validated and compared using a commercial vehicle model that was experimentally validated. Early results shows that a parameter identification approach is more accurate, whereas an observer-based approach is less sensible to parametric uncertainty.
The radon surface can be used to investigates not only for environment but also to be develop in an earth application. The investigation is carried out at the Rahtawu fault, that includes, to the Pati regency which is located 40 km South of ULA. The objective of study to measure the radon released from the fracture zone activities. RDA equipment is being used to measure the radon gas released. The result shown that the high value of radon is 311 cpm with the background of 18 cpm, whereas the low value falls at 0 cpm. The tattoo value are influenced by the soil condition, tattoo time, hardness, weather, soil/stone porosity and fault possession. (author)
Niemann, Hans Henrik; Stoustrup, J.; Shafai, B.
The fault detection and isolation (FDI) problem in connection with Proportional Integral (PI) Observers is considered in this paper. A compact formulation of the FDI design problem using PI observers is given. An analysis of the FDI design problem is derived with respectt to the time domain...... properties. A method for design of PI observers applied to FDI is given....
Alwi, Halim; Tan, Chee Pin
""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
Niemann, Hans Henrik; Saberi, Ali; Stoorvogel, Anton A.;
Considers the problem of fault detection and isolation while using zero or almost zero threshold. A number of different fault detection and isolation problems using exact or almost exact disturbance decoupling are formulated. Solvability conditions are given for the formulated design problems. The...... l-step delayed fault detection problem is also considered for discrete-time systems....
Zhang, Liang; B. Jack, Lindsay; Nandi, Asoke K.
Genetic programming (GP) is a stochastic process for automatically generating computer programs. GP has been applied to a variety of problems which are too wide to reasonably enumerate. As far as the authors are aware, it has rarely been used in condition monitoring (CM). In this paper, GP is used to detect faults in rotating machinery. Featuresets from two different machines are used to examine the performance of two-class normal/fault recognition. The results are compared with a few other methods for fault detection: Artificial neural networks (ANNs) have been used in this field for many years, while support vector machines (SVMs) also offer successful solutions. For ANNs and SVMs, genetic algorithms have been used to do feature selection, which is an inherent function of GP. In all cases, the GP demonstrates performance which equals or betters that of the previous best performing approaches on these data sets. The training times are also found to be considerably shorter than the other approaches, whilst the generated classification rules are easy to understand and independently validate.
Saberi, A.; Stoorvogel, A. A.; Sannuti, P.;
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...
Gao, Qing; Dong, Daoyi; Petersen, Ian R.
This paper aims to determine the fault tolerant quantum filter and fault detection equation for a class of open quantum systems coupled to a laser field that is subject to stochastic faults. In order to analyze this class of open quantum systems, we propose a quantum-classical Bayesian inference method based on the definition of a so-called quantum-classical conditional expectation. It is shown that the proposed Bayesian inference approach provides a convenient tool to simultaneously derive t...
Nazatul Aini Abd Majid; Taylor, Mark P; Chen, John J. J.; Brent R. Young
The challenges in developing a fault detection and diagnosis system for industrial applications are not inconsiderable, particularly complex materials processing operations such as aluminium smelting. However, the organizing into groups of the various fault detection and diagnostic systems of the aluminium smelting process can assist in the identification of the key elements of an effective monitoring system. This paper reviews aluminium process fault detection and diagnosis systems and propo...
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
Gelso, Esteban R.; Blanke, Mogens
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...
Blanke, M.; Bøgh, S.A.; Jørgensen, R.B.; Patton, R.J.
An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI).......An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI)....
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...
Prentice, Carol S.; Crosby, Christopher J.; Whitehill, Caroline S.; Arrowsmith, J. Ramón; Furlong, Kevin P.; Phillips, David A.
Newly acquired light detection and ranging (lidar) topographic data provide a powerful community resource for the study of landforms associated with the plate boundary faults of northern California (Figure 1). In the spring of 2007, GeoEarthScope, a component of the EarthScope Facility construction project funded by the U.S. National Science Foundation, acquired approximately 2000 square kilometers of airborne lidar topographic data along major active fault zones of northern California. These data are now freely available in point cloud (x, y, z coordinate data for every laser return), digital elevation model (DEM), and KMZ (zipped Keyhole Markup Language, for use in Google Earth™ and other similar software) formats through the GEON OpenTopography Portal (http://www.OpenTopography.org/data). Importantly, vegetation can be digitally removed from lidar data, producing high-resolution images (0.5- or 1.0-meter DEMs) of the ground surface beneath forested regions that reveal landforms typically obscured by vegetation canopy (Figure 2).
Seismic attribute detection of faults and fluid pathways within an active strike-slip shear zone: New insights from high-resolution 3D P-Cable™ seismic data along the Hosgri Fault, offshore California
Kluesner, Jared; Brothers, Daniel
Poststack data conditioning and neural-network seismic attribute workflows are used to detect and visualize faulting and fluid migration pathways within a 13.7 km2 13.7 km2 3D P-Cable™ seismic volume located along the Hosgri Fault Zone offshore central California. The high-resolution 3D volume used in this study was collected in 2012 as part of Pacific Gas and Electric’s Central California Seismic Imaging Project. Three-dimensional seismic reflection data were acquired using a triple-plate boomer source (1.75 kJ) and a short-offset, 14-streamer, P-Cable system. The high-resolution seismic data were processed into a prestack time-migrated 3D volume and publically released in 2014. Postprocessing, we employed dip-steering (dip and azimuth) and structural filtering to enhance laterally continuous events and remove random noise and acquisition artifacts. In addition, the structural filtering was used to enhance laterally continuous edges, such as faults. Following data conditioning, neural-network based meta-attribute workflows were used to detect and visualize faults and probable fluid-migration pathways within the 3D seismic volume. The workflow used in this study clearly illustrates the utility of advanced attribute analysis applied to high-resolution 3D P-Cable data. For example, results from the fault attribute workflow reveal a network of splayed and convergent fault strands within an approximately 1.3 km wide shear zone that is characterized by distinctive sections of transpressional and transtensional dominance. Neural-network chimney attribute calculations indicate that fluids are concentrated along discrete faults in the transtensional zones, but appear to be more broadly distributed amongst fault bounded anticlines and structurally controlled traps in the transpressional zones. These results provide high-resolution, 3D constraints on the relationships between strike-slip fault mechanics, substrate deformation, and fluid migration along an active
Baldi, G.; Carabelli, E.; Chiantore, V.; Colombo, P.F.; Gruszka, A.; Pensieri, R.; Superbo, S.; Gera, F.
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.
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
Lala, J. H.
The Fault-Tolerant Multiprocessor (FTMP) is a highly reliable computer designed to meet a goal of 10 to the -10th failures per hour and built with the objective of flying an active-control transport aircraft. Fault detection, identification, and recovery software is described, and experimental results obtained by injecting faults in the pin level in the FTMP are presented. Over 21,000 faults were injected in the CPU, memory, bus interface circuits, and error detection, masking, and error reporting circuits of one LRU of the multiprocessor. Detection, isolation, and reconfiguration times were recorded for each fault, and the results were found to agree well with earlier assumptions made in reliability modeling.
Nazatul Aini Abd Majid
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.
Lo, Chun; Bai, Yechao; Liu, Mingyan; Lynch, Jerome P.
When faulty sensors are rare in a network, diagnosing sensors individually is inefficient. This study introduces a novel use of concepts from group testing and Kalman filtering in detecting these rare faulty sensors with significantly fewer number of tests. By assigning sensors to groups and performing Kalman filter-based fault detection over these groups, we obtain binary detection outcomes, which can then be used to recover the fault state of all sensors. We first present this method using ...
Thybo, C.; Rasmussen, B.D.; Izadi-Zamanabadi, Roozbeh
Fault detection in supermarket refrigeration systems is an important topic due to both economic and food safety reasons. If faults can be detected and diagnosed before the system drifts outside the specified operational envelope, service costs can be reduced and in extreme cases the costly...... 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...
Jensen, Hans-Christian Becker; Wisniewski, Rafal
This article realizes nonlinear Fault Detection and Isolation for actuators, given there is no measurement of the states in the actuators. The Fault Detection and Isolation of the actuators is instead based on angular velocity measurement of the spacecraft and knowledge about the dynamics 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....
Jørgensen, R.B.; Patton, R.J.; Chen, J.
The purpose of this article is to investigate the robustness to model uncertainties of observer based fault detection and isolation. The approach is designed with a straight forward dynamic nad the observer.......The purpose of this article is to investigate the robustness to model uncertainties of observer based fault detection and isolation. The approach is designed with a straight forward dynamic nad the observer....
Gladisch, Christoph David
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.
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
Pueyo Anchuela, Óscar; Lafuente, Paloma; Arlegui, Luis; Liesa, Carlos L.; Simón, José L.
The Concud Fault is a ~14-km-long active fault that extends close to Teruel, a city with about 35,000 inhabitants in the Iberian Range (NE Spain). It shows evidence of recurrent activity during Late Pleistocene time, posing a significant seismic hazard in an area of moderate-to-low tectonic rates. A geophysical survey was carried out along the mapped trace of the southern branch of the Concud Fault to evaluate the geophysical signature from the fault and the location of paleoseismic trenches. The survey identified a lineation of inverse magnetic dipoles at residual and vertical magnetic gradient, a local increase in apparent conductivity, and interruptions of the underground sediment structure along GPR profiles. The origin of these anomalies is due to lateral contrast between both fault blocks and the geophysical signature of Quaternary materials located above and directly south of the fault. The spatial distribution of anomalies was successfully used to locate suitable trench sites and to map non-exposed segments of the fault. The geophysical anomalies are related to the sedimentological characteristics and permeability differences of the deposits and to deformation related to fault activity. The results illustrate the usefulness of geophysics to detect and map non-exposed faults in areas of moderate-to-low tectonic activity where faults are often covered by recent pediments that obscure geological evidence of the most recent earthquakes. The results also highlight the importance of applying multiple geophysical techniques in defining the location of buried faults.
Ma Hongguang; Han Chongzhao; Wang Guohua; Xu Jianfeng; Zhu Xiaofei
This paper presents a fault-detection method based on the phase space reconstruction and data mining approaches for the complex electronic system. The approach for the phase space reconstruction of chaotic time series is a combination algorithm of multiple autocorrelation and Γ-test, by which the quasi-optimal embedding dimension and time delay can be obtained.The data mining algorithm, which calculates the radius of gyration of unit-mass point around the centre of mass in the phase space, can distinguish the fault parameter from the chaotic time series output by the tested system. The experimental results depict that this fault detection method can correctly detect the fault phenomena of electronic system.
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.
Full Text Available In this paper, we present a new reset tree-based scheme to protect cryptographic hardware against optical fault injection attacks. As one of the most powerful invasive attacks on cryptographic hardware, optical fault attacks cause semiconductors to misbehave by injecting high-energy light into a decapped integrated circuit. The contaminated result from the affected chip is then used to reveal secret information, such as a key, from the cryptographic hardware. Since the advent of such attacks, various countermeasures have been proposed. Although most of these countermeasures are strong, there is still the possibility of attack. In this paper, we present a novel optical fault detection scheme that utilizes the buffers on a circuit’s reset signal tree as a fault detection sensor. To evaluate our proposal, we model radiation-induced currents into circuit components and perform a SPICE simulation. The proposed scheme is expected to be used as a supplemental security tool.
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.
Centrifugal pumps are used in a variety of different applications, such as water supply, wastewater, and different industrial applications. Some pump installations are crucial for the applications to work. Failures can lead to substantial economic losses and can influence the life of many people...... when they occur. Therefore, detection of faults, if possible in an early stage, and isolation of their causes are of great interest. Especially fault detection, which can be used for predictive maintenance, can decrease working expenses and increase the reliability of the application in which the pump...... is placed. The topic of this work is Fault Detection and Identification in centrifugal pumps. Different approaches are developed with special focus on robustness. Robustness with respect to disturbances, unknown parts of the system, and parameter variations are considered. All developed algorithms...
GAO Jianliang; XU Yongjun; LI Xiaowei
In wireless sensor networks (WSNs), a faulty sensor may produce incorrect data and transmit them to the other sensors. This would consume the limited energy and bandwidth of WSNs. Furthermore, the base station may make inappropriate decisions when it receives the incorrect data sent by the faulty sensors. To solve these problems, this paper develops an online distributed algorithm to detect such faults by exploring the weighted majority vote scheme. Considering the spatial correlations in WSNs, a faulty sensor can diagnose itself through utilizing the spatial and time information provided by its neighbor sensors. Simulation results show that even when as many as 30% of the sensors are faulty, over 95% of faults can be correctly detected with our algorithm. These results indicate that the proposed algorithm has excellent performance in detecting fault of sensor measurements in WSNs.
Jirsa, Ladislav; Pavelková, Lenka; Dedecius, Kamil
Prague: Institute of Information Theory and Automation, 2013 - (Guy, T.; Kárný, M.) ISBN 978-80-903834-8-7. [The 3rd International Workshop on Scalable Decision Making: Uncertainty, Imperfection, Deliberation held in conjunction with ECML/PKDD 2013. Prague (CZ), 23.09.2013-23.09.2013] R&D Projects: GA MŠk 7D12004; GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Fault detection * FDI * probabilistic logic * system health Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2013/AS/jirsa-preliminaries of probabilistic hierarchical fault detection.pdf
Lavrova, Olga [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flicker, Jack David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Johnson, Jay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
We have examined ground faults in PhotoVoltaic (PV) arrays and the efficacy of fuse, current detection (RCD), current sense monitoring/relays (CSM), isolation/insulation (Riso) monitoring, and Ground Fault Detection and Isolation (GFID) using simulations based on a Simulation Program with Integrated Circuit Emphasis SPICE ground fault circuit model, experimental ground faults installed on real arrays, and theoretical equations.
Van Eykeren, L.; Chu, Q.P.
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
Lajic, Zoran; Nielsen, Ulrik Dam
In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection will be p...
With the rise in automation the increase in fault detectionand isolation & reconfiguration is inevitable. Interest in fault detection and isolation (FDI) for nonlinear systems has grown significantly in recent years. The design of FDI is motivated by the need for knowledge about occurring faults in fault-tolerant control systems (FTC systems). The idea of FTC systems is to detect, isolate, and handle faults in such a way that the systems can still perform in a required manner. One prefers...
George, Jemin; Gregory, Irene M.
This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.
Kallesøe, Carsten; Cocquempot, Vincent; Izadi-Zamanabadi, Roozbeh
A model based approach for fault detection in a centrifugal pump, driven by an induction motor, is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, observer design and Analytical Redundancy Relation (ARR) design. Structural considerations...... the algorithm is capable of detecting four different faults in the mechanical and hydraulic parts of the pump....
Li, Lei; Chen, Tianshi; Chen, Yunji; Li, Ling; Wu, Ruiyang
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 ...
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
-tolerance can be applied to ordinary industrial processes that are not categorized as high risk applications, but where high availability is desirable. The quality of fault-tolerant control is totally dependent on the quality of the underlying algorithms. They detect possible faults, and later reconfigure......With the rise in automation the increase in fault detectionand isolation & reconfiguration is inevitable. Interest in fault detection and isolation (FDI) for nonlinear systems has grown significantly in recent years. The design of FDI is motivated by the need for knowledge about occurring faults in...... fault-tolerant control systems (FTC systems). The idea of FTC systems is to detect, isolate, and handle faults in such a way that the systems can still perform in a required manner. One prefers reduced performance after occurrence of a fault to the shut down of (sub-) systems. Hence, the idea of fault...
Zhu Jinfang; Han Zhujun; Huang Zonglin; Xu Xiwei; Zheng Rongzhang; Fang Shengmin; Bai Denghai; Wang Guangcai; Min Wei; Wen Xueze
It has been proven by a number of earthquake case studies that an active fault-induced earthquake beneath a city can be devastating. It is an urgent issue for seismic hazard reduction to explore the distribution of active faults beneath the urban area and identify the seismic source and the risks underneath. As a pilot project of active fault exploration in China, the project, entitled "Active fault exploration and seismic hazard assessment in Fuzhou City",started in early 2001 and passed the check before acceptance of China Earthquake Administration in August 2004. The project was aimed to solve a series of scientific issues such as fault location, dating, movement nature, deep settings, seismic risk and hazard,preparedness of earthquake prevention and disaster reduction, and etc. by means of exploration and assessment of active faults by stages, i.e., the preliminary survey and identification of active faults in target area, the exploration of deep seismotectonic settings, the risk evaluation of active seismogenic faults, the construction of geographic information system of active faults, and so on. A lot of exploration methods were employed in the project such as the detection of absorbed mercury, free mercury and radon in soil, the geological radar,multi-channel DC electrical method, tsansient electromagnetic method, shallow seismic refraction and reflection, effect contrast of explored sources, and various sounding experiments, to establish the buried Quaternary standard section of the Fuzhou basin. By summing up, the above explorations and experiments have achieved the following results and conclusions:(1) The results of the synthetic pilot project of active fault exploration in Fuzhou City demonstrate that, on the basis of sufficient collection, sorting out and analysis of geological,geophysical and borehole data, the best method for active fault exploration (location) and seismic risk assessnent (dating and characterizing) in urban area is the combination
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...
Xu Mingcai; Gao Jinghua; Liu Jianxun; Rong Lixin
Using the seismic method to detect active faults directly below cities is an irreplaceable prospecting technique. The seismic method can precisely determine the fault position. Seismic method itself can hardly determine the geological age of fault. However, by considering in connection with the borehole data and the standard geological cross-section of the surveyed area, the geological age of reflected wave group can be qualitatively (or semi-quantitatively)determined from the seismic depth profile. To determine the upper terminal point of active faults directly below city, it is necessary to use the high-resolution seismic reflection technique.To effectively determine the geometric feature of deep faults, especially to determine the relation between deep and shallow fracture structures, the seismic reflection method is better than the seismic refraction method.
Niemann, Hans Henrik; Saberi, Ali; Stoorvogel, Anton A.;
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...
LI Ji; ZHANG Hongyue
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.
Borchersen, Anders Bech; Larsen, Jesper Abildgaard; Stoustrup, Jakob
is to detect and handle different faults occurring in the individual turbines on farm level. The fault detection system is designed such that it takes advantage of the fact that within a wind farm several of the turbines will be operating under similar conditions. To enable this the turbines are...... occurring in the model. All the detections are not within the requirement of the challenge thus room for improvement. To take advantage of the fault detection system a fault tolerant controller for the wind farm has been designed. The fault tolerant controller is a dispatch controller which is estimating......In this paper a fault detection system and a fault tolerant controller for a wind farm model is designed and tested. The wind farm model is taken from the wind farm challenge which is a public available challenge where a wind farm consisting of nine turbines is proposed. The goal of the challenge...
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.
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.
Gao, Qing; Dong, Daoyi; Petersen, Ian R.; Rabitz, Herschel
The purpose of this paper is to solve the fault tolerant filtering and fault detection problem for a class of open quantum systems driven by a continuous-mode bosonic input field in single photon states when the systems are subject to stochastic faults. Optimal estimates of both the system observables and the fault process are simultaneously calculated and characterized by a set of coupled recursive quantum stochastic differential equations.
Nguyen, Viet Ha; Rutten, Christophe; Golinval, Jean-Claude
In the field of structural health monitoring or machine condition monitoring, the activation of nonlinear dynamic behavior complicates the procedure of damage or fault detection. Principal Component Analysis (PCA) is known as an efficient method for damage diagnosis. However, two drawbacks of PCA are the assumption of the linearity of the system and the need of many sensors. This article presents industrial applications of two possible extensions of PCA: Null subspace analysis (NSA) and Kerne...
Full Text Available Mechanical faults in production lines can result in partial or total breakdown of a production line, destruction of equipment and even catastrophes. Implementation of an adequate fault detection system represents an important step towards early detection of such faults, thus reducing the risk of unexpected failures. Traditionally, fault detection process is done by comparing the observed machine state with a set of historical data representing the fault--free state. However, such historical data are rarely available. In such cases, the fault detection process is performed by examining whether a particular pre--modeled fault signature can be matched within the signals acquired from the monitored machine. In this paper we propuse a solution to a problem of fault detection without any prior data, presented at PHM'09 Data Challenge. The solution is based on a two step algorithm. The first step, based on the spectral kurtosis method, is used to determine whether a particular experimental run is likely to contain a faulty element. In case of a positive decision, fault isolation procedure is applied as the second step. The fault isolation procedure was based on envelope analysis of filtered vibration signals. The filtering of the vibration signals was performed in the frequency band that maximizes the spectral kurtosis. The effectiveness of the proposed approach was evaluated for bearing fault detection, on the vibration data obtained from the PHM'09 Data Challenge.
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.
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.
Khukhuudei, M.; Khukhuudei, U.
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.
Radon emanation has been observed to be anomalously high along active faults in many parts of the world. We tested this relationship by conducting and repeating soil-air radon surveys with a portable radon meter across several faults in California. The results confirm the existence of fault-associated radon anomalies, which show characteristic features that may be related to fault structures but vary in time due to other environmental changes, such as rainfall. Across two creeping faults in San Juan Bautista and Hollister, the radon anomalies showed prominent double peaks straddling the fault-gouge zone during dry summers, but the peak-to-background ratios diminished after significant rain fall during winter. Across a locked segment of the San Andreas fault near Olema, the anomaly has a single peak located several meters southwest of the slip zone associated with the 1906 San Francisco earthquake. Across two fault segments that ruptured during the magnitude 7.5 Landers earthquake in 1992, anomalously high radon concentration was found in the fractures three weeks after the earthquake. We attribute the fault-related anomalies to a slow vertical gas flow in or near the fault zones. Radon generated locally in subsurface soil has a concentration profile that increases three orders of magnitude from the surface to a depth of several meters; thus an upward flow that brings up deeper and radon-richer soil air to the detection level can cause a significantly higher concentration reading. This explanation is consistent with concentrations of carbon dioxide and oxygen, measured in soil-air samples collected during one of the surveys. (Author)
Azambuja, José Rodrigo; Becker, Jürgen
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 ...
Full Text Available Arc fault is one of the most critical reasons for electrical fires. Due to the diversity, randomness and concealment of arc faults in low-voltage circuits, it is difficult for general methods to protect all loads from series arc faults. From the analysis of many series arc faults, a large number of high frequency signals generated in circuits are found. These signals are easily affected by Gaussian noise which is difficult to be eliminated as a result of frequency aliasing. Thus, a novel detection algorithm is developed to accurately detect series arc faults in this paper. Initially, an autoregressive model of the mixed high frequency signals is modelled. Then, autoregressive bispectrum analysis is introduced to analyze common series arc fault features. The phase information of arc fault signal is preserved using this method. The influence of Gaussian noise is restrained effectively. Afterwards, several features including characteristic frequency, fluctuation of phase angles, diffused distribution and incremental numbers of bispectrum peaks are extracted for recognizing arc faults. Finally, least squares support vector machine is used to accurately identify series arc faults from the load states based on these frequency features of bispectrum. The validity of the algorithm is experimentally verified obtaining arc fault detection rate above 97%.
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...
Full Text Available This paper presents a technique to detect the location of the different faults on a transmission lines for quick and reliable operation of protection schemes. The simulation is developed in MATLAB to generate the fundamental component of the transient voltage and current simultaneously both in time and frequency domain. One cycle of waveform, covering pre-fault and post-fault information is abstracted for analysis. The discrete wavelet transform (DWT is used for data preprocessing. It is applied for decomposition of fault transients, because of its ability to extract information from the transient signal, simultaneously both in time and frequency domain. MATLAB software is used to simulate different operating and fault conditions on high voltage transmission line, namely single phase to ground fault, line to line fault, double line to ground and three phase short circuit.
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.
Flett, Justin; Bone, Gary M.
This paper presents the development of a fault detection and diagnosis (FDD) system for use with a diesel internal combustion engine (ICE) valve train. A novel feature is generated for each of the valve closing and combustion impacts. Deformed valve spring faults and abnormal valve clearance faults were seeded on a diesel engine instrumented with one accelerometer. Five classification methods were implemented experimentally and compared. The FDD system using the Naïve-Bayes classification method produced the best overall performance, with a lowest detection accuracy (DA) of 99.95% and a lowest classification accuracy (CA) of 99.95% for the spring faults occurring on individual valves. The lowest DA and CA values for multiple faults occurring simultaneously were 99.95% and 92.45%, respectively. The DA and CA results demonstrate the accuracy of our FDD system for diesel ICE valve train fault scenarios not previously addressed in the literature.
Deng Qidong; Lu Zaoxun; Yang Zhu'en
According to the practice of urban active fault exploration and associated fault activity assessment conducted in recent years, this paper summarizes the problems encountered in geological, geomorphological, geochemical and geophysical surveys, and proposes the following means and suggestions to solve these problems. To determine the most recent faults or fault zones, emphasis should be placed on identifying the youngest active faults and offset geomorphology. To understand the history of faulting and to discover the latest offset event, it is suggested that geophysical prospecting, drilling and trenching be conducted on one profile.Because of significant uncertainties in late Quaternary dating, we advise systematic sampling and the use of multiple dating methods. Shallow seismic reflection has been proven to be the most useful method in urban active fault exploration. However, there is a pressing need to increase the quality of data acquisition and processing to obtain high resolution images so as to enhance our ability to identify active faults. The combination of seismic P-wave reflection and S-wave reflection methods is proved to be a powerful means to investigate the tectonic environments of the deep crust.
This paper presents a technique to detect the location of the different faults on a transmission lines for quick and reliable operation of protection schemes. The simulation is developed in MATLAB to generate the fundamental component of the transient voltage and current simultaneously both in time and frequency domain. One cycle of waveform, covering pre-fault and post-fault information is abstracted for analysis. The discrete wavelet transform (DWT) is used for data preprocessing. It is app...
The main contribution in the hereby presented paper is to investigate the fault detection capability of a motor current signature analysis by expanding its scope to include the gearbox, and not only the induction motor. Detecting bearing faults outside the induction motor through the stator current analysis represents an interesting alternative to traditional vibration analysis. Bearing faults cause changes in the stator current spectrum that can be used for fault diagnosis purposes. A time-domain simulation of the drivetrain model is developed. The drivetrain system consists of a loaded single stage gearbox driven by a line-fed induction motor. Three typical bearing faults in the gearbox are addressed, i.e. defects in the outer raceway, the inner raceway, and the rolling element. The interaction with the fault is modelled by means of kinematical and mechanical relations. The fault region is modelled in order to achieve gradual loss and gain of contact. A bearing fault generates an additional torque component that varies at the specific bearing defect frequency. The presented dynamic electromagnetic dq-model of an induction motor is adjusted for diagnostic purpose and considers such torque variations. The bearing fault is detected as a phase modulation of the stator current sine wave at the expected bearing defect frequency.
Michio Morino; Javed N Malik; Prashant Mishra; Chandrashekhar Bhuiyan; Fumio Kaneko
Several new active fault traces were identiﬁed along Katrol Hill Fault (KHF).A new fault (named as Bhuj Fault,BF)that extends into the Bhuj Plain was also identiﬁed.These fault traces were identiﬁed based on satellite photo interpretation and ﬁeld survey.Trenches were excavated to identify the paleoseismic events,pattern of faulting and the nature of deformation.New active fault traces were recognized about 1 km north of the topographic boundary between the Katrol Hill and the plain area.The fault exposure along the left bank of Khari River with 10 m wide shear zone in the Mesozoic rocks and showing displacement of the overlying Quaternary deposits is indicative of continued tectonic activity along the ancient fault.The E-W trending active fault traces along the KHF in the western part changes to NE-SW or ENE-WSW near Wandhay village. Trenching survey across a low scarp near Wandhay village reveals three major fault strands F1, F2,and F3.These fault strands displaced the older terrace deposits comprising Sand,Silt and Gravel units along with overlying younger deposits from units 1 to 5 made of gravel,sand and silt. Stratigraphic relationship indicates at least three large magnitude earthquakes along KHF during Late Holocene or recent historic past.
Thakur, V. C.
In the Sub-Himalayan zone, the frontal Siwalik range abuts against the alluvial plain with an abrupt physiographic break along the Himalayan Frontal Thrust (HFT), defining the present-day tectonic boundary between the Indian plate and the Himalayan orogenic prism. The frontal Siwalik range is characterized by large active anticline structures, which were developed as fault propagation and fault-bend folds in the hanging wall of the HFT. Fault scarps showing surface ruptures and offsets observed in excavated trenches indicate that the HFT is active. South of the HFT, the piedmont zone shows incipient growth of structures, drainage modification, and 2-3 geomorphic depositional surfaces. In the hinterland between the HFT and the MBT, reactivation and out-of-sequence faulting displace Late Quaternary-Holocene sediments. Geodetic measurements across the Himalaya indicate a ~100-km-wide zone, underlain by the Main Himalayan Thrust (MHT), between the HFT and the main microseismicity belt to north is locked. The bulk of shortening, 15-20 mm/year, is consumed aseismically at mid-crustal depth through ductile by creep. Assuming the wedge model, reactivation of the hinterland faults may represent deformation prior to wedge attaining critical taper. The earthquake surface ruptures, ≥240 km in length, interpreted on the Himalayan mountain front through paleoseismology imply reactivation of the HFT and may suggest foreland propagation of the thrust belt.
The complexity of modern systems is increasing rapidly and the dominating relationships among system variables have become highly non-linear. This results in difficulty in the identification of a system's operating states. In turn, this difficulty affects the sensitivity of fault detection and imposes a challenge on ensuring the safety of operation. In recent years, Self-Organizing Maps has gained popularity in system monitoring as a robust non-linear dimensionality reduction tool. Self-Organizing Map is able to capture non-linear variations of the system. Therefore, it is sensitive to the change of a system's states leading to early detection of fault. In this paper, a new approach based on Self-Organizing Map is proposed to detect and assess the risk of fault. In addition, probabilistic analysis is applied to characterize the risk of fault into different levels according to the hazard potential to enable a refined monitoring of the system. The proposed approach is applied on two experimental systems. The results from both systems have shown high sensitivity of the proposed approach in detecting and identifying the root cause of faults. The refined monitoring facilitates the determination of the risk of fault and early deployment of remedial actions and safety measures to minimize the potential impact of fault. - Highlights: • A new approach based on Self-Organizing Map is proposed to detect faults. • Integration of fault detection with risk assessment methodology. • Fault risk characterization into different levels to enable focused system monitoring
Nejada, Amir R.; Odgaard, Peter Fogh; Gao, Zhen;
In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the...... intermediate shafts inside the gearbox. An angular velocity error function is defined and compared in the faulty and fault-free conditions in frequency domain. Faults can be detected from the change in the energy level of the frequency spectrum of an error function. The method is demonstrated by detecting...
Hong, Shi; Fang-jian, Shan; Bo, Cong; Wei, Qiu
For extracting mutation information from gear fault signal and achieving a valid fault diagnosis, a gear fault diagnosis method based on morphological mean wavelet transform was designed. Morphological mean wavelet transform is a linear wavelet in the framework of morphological wavelet. Decomposing gear fault signal by this morphological mean wavelet transform could produce signal synthesis operators and detailed synthesis operators. For signal synthesis operators, it was just close to orginal signal, and for detailed synthesis operators, it contained fault impact signal or interference signal and could be catched. The simulation experiment result indicates that, compared with Fourier transform, the morphological mean wavelet transform method can do time-frequency analysis for original signal, effectively catch impact signal appears position; and compared with traditional linear wavelet transform, it has simple structure, easy realization, signal local extremum sensitivity and high denoising ability, so it is more adapted to gear fault real-time detection.
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.
In this study, we carried out two sets of active fault investigation by the request from Ministry of Education, Culture, Sports, Science and Technology in the sea area of the extension of Kikugawa fault and the Nishiyama fault. We want to clarify the five following matters about both active faults based on those results. (1)Fault continuity of the land and the sea. (2) The length of the active fault. (3) The division of the segment. (4) Activity characteristics. In this investigation, we carried out a digital single channel seismic reflection survey in the whole area of both active faults. In addition, a high-resolution multichannel seismic reflection survey was carried out to recognize the detailed structure of a shallow stratum. Furthermore, the sampling with the vibrocoring to get information of the sedimentation age was carried out. The reflection profile of both active faults was extremely clear. The characteristics of the lateral fault such as flower structure, the dispersion of the active fault were recognized. In addition, from analysis of the age of the stratum, it was recognized that the thickness of the sediment was extremely thin in Holocene epoch on the continental shelf in this sea area. It was confirmed that the Kikugawa fault extended to the offing than the existing results of research by a result of this investigation. In addition, the width of the active fault seems to become wide toward the offing while dispersing. At present, we think that we can divide Kikugawa fault into some segments based on the distribution form of the segment. About the Nishiyama fault, reflection profiles to show the existence of the active fault was acquired in the sea between Ooshima and Kyushu. From this result and topographical existing results of research in Ooshima, it is thought that Nishiyama fault and the Ooshima offing active fault are a series of structure. As for Ooshima offing active fault, the upheaval side changes, and a direction changes too. Therefore, we
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.
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.
Feng, Xi-Jie; Dai, Wang-Qiang
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.
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...
Tabatabaeipour, Seyed Mojtaba; Odgaard, Peter Fogh; Bak, Thomas
of the measurement with a closed set that is computed based on the past measurements and a model of the system. If the measurement is not consistent with this set, a fault is detected. The result demonstrates effectiveness of the method for fault detection of the benchmark wind turbine.......This paper investigates a state estimation set- membership approach for fault detection of a benchmark wind turbine. The main challenges in the benchmark are high noise on the wind speed measurement and the nonlinearities in the aerodynamic torque such that the overall model of the turbine is...... nonlinear. We use an effective wind speed estimator to estimate the effective wind speed and then using interval analysis and monotonicity of the aerodynamic torque with respect to the effective wind speed, we can apply the method to the nonlinear system. The fault detection algorithm checks the consistency...
Tesson, Jim; Pace, Bruno; Benedetti, Lucilla; Visini, Francesco; Delli Rocioli, Mattia; Didier, Bourles; Karim, keddadouche; Gorges, Aumaitre
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.
Meseguer Amela, Jordi
An interval observer has been illustrated to be a suitable approach to detect and isolate faults affecting complex dynamical industrial systems. Concerning fault detection, interval observation is an appropriate passive robust strategy to generate an adaptive threshold to be used in residual evaluation when model uncertainty is located in parameters (interval model). In such approach, the observer gain is a key parameter since it determines the time evolution of the residual sensitiv...
Zell, K.; Medvedev, A. [Control Engineering Group, Luleaa University of Technology, Luleaa (Sweden)
A model-based technique for fault detection and isolation in electro-mechanical systems comprising induction machines is introduced. Two coupled state observers, one for the induction machine and another for the mechanical load, are used to detect and recognize fault-specific behaviors (fault signatures) from the real-time measurements of the rotor angular velocity and terminal voltages and currents. Practical applicability of the method is verified in full-scale experiments with a conveyor belt drive at SSAB, Luleaa Works. (orig.) 3 refs.
Odgaard, Peter Fogh; Shafiei, Seyed Ehsan
detection and isolation and fault tolerant control has previously been proposed. Based on this model, and international competition on wind farm FDI was organized. The contributions were presented at the IFAC World Congress 2014. In this paper the top three contributions to this competition are shortly......In the process of lowering cost of energy of power generated by wind turbines, some focus has been drawn towards fault detection and isolation and as well as fault tolerant control of wind turbines with the purpose of increasing reliability and availability of the wind turbines. Most modern wind...
Cilliers, Anthonie Christoffel
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...
Bergantino, Nicola; Caponetti, Fabio; Longhi, Sauro
Efficient and reliable monitoring systems are mandatory to assure the required security standards in industrial complexes. This paper describes the recent developments of FaultBuster, a purely data-driven diagnostic system. It is designed so to be easily scalable to different monitor tasks. Multivariate statistical models based on principal components are used to detect abnormal situations. Tailored to alarms, a probabilistic inference engine process the fault evidences to output the most pro...
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.
Odgaard, Peter Fogh; Stoustrup, Jakob; Nielsen, R.;
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....
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.
Hanafy, Sherif M.
The seismic scanning tunneling macroscope (SSTM) is proposed for detecting the presence of near-surface impedance anomalies and faults. Results with synthetic data are consistent with theory in that scatterers closer to the surface provide brighter SSTM profiles than those that are deeper. The SSTM profiles show superresolution detection if the scatterers are in the near-field region of the recording line. The field data tests near Gulf of Aqaba, Haql, KSA clearly show the presence of the observable fault scarp, and identify the subsurface presence of the hidden faults indicated in the tomograms. Superresolution detection of the fault is achieved, even when the 35 Hz data are lowpass filtered to the 5-10 Hz band.
Chandra, N. Harish; Sekhar, A. S.
Faults such as misalignment, rotor cracks and rotor to stator rub can exist collectively in rotor bearing systems. It is an important task for rotor dynamic personnel to monitor and detect faults in rotating machinery. In this paper, the rotor startup vibrations are utilized to solve the fault identification problem using time frequency techniques. Numerical simulations are performed through finite element analysis of the rotor bearing system with individual and collective combinations of faults as mentioned above. Three signal processing tools namely Short Time Fourier Transform (STFT), Continuous Wavelet Transform (CWT) and Hilbert Huang Transform (HHT) are compared to evaluate their detection performance. The effect of addition of Signal to Noise ratio (SNR) on three time frequency techniques is presented. The comparative study is focused towards detecting the least possible level of the fault induced and the computational time consumed. The computation time consumed by HHT is very less when compared to CWT based diagnosis. However, for noisy data CWT is more preferred over HHT. To identify fault characteristics using wavelets a procedure to adjust resolution of the mother wavelet is presented in detail. Experiments are conducted to obtain the run-up data of a rotor bearing setup for diagnosis of shaft misalignment and rotor stator rubbing faults.
Janssens, Olivier; Slavkovikj, Viktor; Vervisch, Bram; Stockman, Kurt; Loccufier, Mia; Verstockt, Steven; Van de Walle, Rik; Van Hoecke, Sofie
Vibration analysis is a well-established technique for condition monitoring of rotating machines as the vibration patterns differ depending on the fault or machine condition. Currently, mainly manually-engineered features, such as the ball pass frequencies of the raceway, RMS, kurtosis an crest, are used for automatic fault detection. Unfortunately, engineering and interpreting such features requires a significant level of human expertise. To enable non-experts in vibration analysis to perform condition monitoring, the overhead of feature engineering for specific faults needs to be reduced as much as possible. Therefore, in this article we propose a feature learning model for condition monitoring based on convolutional neural networks. The goal of this approach is to autonomously learn useful features for bearing fault detection from the data itself. Several types of bearing faults such as outer-raceway faults and lubrication degradation are considered, but also healthy bearings and rotor imbalance are included. For each condition, several bearings are tested to ensure generalization of the fault-detection system. Furthermore, the feature-learning based approach is compared to a feature-engineering based approach using the same data to objectively quantify their performance. The results indicate that the feature-learning system, based on convolutional neural networks, significantly outperforms the classical feature-engineering based approach which uses manually engineered features and a random forest classifier. The former achieves an accuracy of 93.61 percent and the latter an accuracy of 87.25 percent.
Prieto, Miguel Delgado; Roura, Jordi Cusidó i; Martínez, Jose Luis Romeral
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.
Odgaard, Peter Fogh; Stoustrup, Jakob; Wickerhauser, Mladen Victor
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...
Nordmann Rainer; Aenis Martin
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...
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)
Ayasha Siddiqua; Shikha Swaroop; Prashant Krishan; Sandip Mandal
Wireless Sensor Network (WSNs) have become a new information collection and monitoring solution for a variety of application. In WSN, sensor nodes have strong hardware and software restrictionin terms of processing power, memory capability, power supply and communication throughput. Due to these restrictions, fault may occur in sensor. This paper presents a distance based fault detection (DBFD)method for wireless sensor network using the average of confidence level and sensed data of sensor n...
Lala, J. H.
The Advanced Information Processing System (AIPS) is designed to provide a fault tolerant and damage tolerant data processing architecture for a broad range of aerospace vehicles, including tactical and transport aircraft, and manned and autonomous spacecraft. A proof-of-concept (POC) system is now in the detailed design and fabrication phase. This paper gives an overview of a preliminary fault detection and error handling philosophy in AIPS.
Felício, P.; Stoustrup, Jakob; Niemann, H.; Lourtie, P.
A way of doing parametric fault detection is described. It is based on the representation of parameter changes as linear fractional transformations (lfts). We describe a model with parametric uncertainty. Then a stabilizing controller is chosen and its robustness properties are studied via mu. Th...... parameter changes (faults) are estimated based on estimates of the fictitious signals that enter the delta block in the lft. These signal estimators are designed by H-infinity techniques. The chosen example is an inverted pendulum....
An automated fault detection software system has been developed and was used during 1999 DIII-D plasma operations. The Fault Identification and Communication System (FICS) executes automatically after every plasma discharge to check dozens of subsystems for proper operation and communicates the test results to the tokamak operator. This system is now used routinely during DIII-D operations and has led to an increase in tokamak productivity
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 (...
Button, Robert M.
The NASA Glenn Research Center, partner universities, and defense contractors are working to develop intelligent power management and distribution (PMAD) technologies for future spacecraft and launch vehicles. The goals are to provide higher performance (efficiency, transient response, and stability), higher fault tolerance, and higher reliability through the application of digital control and communication technologies. It is also expected that these technologies will eventually reduce the design, development, manufacturing, and integration costs for large, electrical power systems for space vehicles. The main focus of this research has been to incorporate digital control, communications, and intelligent algorithms into power electronic devices such as direct-current to direct-current (dc-dc) converters and protective switchgear. These technologies, in turn, will enable revolutionary changes in the way electrical power systems are designed, developed, configured, and integrated in aerospace vehicles and satellites. Initial successes in integrating modern, digital controllers have proven that transient response performance can be improved using advanced nonlinear control algorithms. One technology being developed includes the detection of "soft faults," those not typically covered by current systems in use today. Soft faults include arcing faults, corona discharge faults, and undetected leakage currents. Using digital control and advanced signal analysis algorithms, we have shown that it is possible to reliably detect arcing faults in high-voltage dc power distribution systems (see the preceding photograph). Another research effort has shown that low-level leakage faults and cable degradation can be detected by analyzing power system parameters over time. This additional fault detection capability will result in higher reliability for long-lived power systems such as reusable launch vehicles and space exploration missions.
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
Cheung, Howard [Purdue Univ., West Lafayette, IN (United States); Braun, James E. [Purdue Univ., West Lafayette, IN (United States)
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.
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.
He, Wangpeng; Ding, Yin; Zi, Yanyang; Selesnick, Ivan W.
This paper addresses the detection of periodic transients in vibration signals so as to detect faults in rotating machines. For this purpose, we present a method to estimate periodic-group-sparse signals in noise. The method is based on the formulation of a convex optimization problem. A fast iterative algorithm is given for its solution. A simulated signal is formulated to verify the performance of the proposed approach for periodic feature extraction. The detection performance of comparative methods is compared with that of the proposed approach via RMSE values and receiver operating characteristic (ROC) curves. Finally, the proposed approach is applied to single fault diagnosis of a locomotive bearing and compound faults diagnosis of motor bearings. The processed results show that the proposed approach can effectively detect and extract the useful features of bearing outer race and inner race defect.
Highlights: ► Attempt was to use available resources at a nuclear plant in a value added fashion. ► Includes plant measurement data and plant training and engineering simulator capabilities. ► Correlating fault detection data for systems to develop of a deterministic fault identifications system. ► After implementing a host of data manipulation algorithms, the results provided more information on the fault than expected. - Abstract: Early fault identification systems enable detecting and diagnosing early onset faults or fault causes which allow maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. We have shown (Cilliers and Mulder, 2012) that detecting faults early during transient operation in NPPs is possible when coupled with a reliable reference to compare plant measurements with during transients. The problem introduced by the distributed application of control systems operating independently to keep the plant operating within the safe operating boundaries was solved by re-introducing the fault information it into the measurement data, thereby improving plant diagnostic performance. This paper introduces the use of improved fault detection information received from all distributed systems in the plant control system and correlating the information to not only detect the fault but also to diagnose it based on the location and magnitude of the fault cause
Mekki, Hemza; Benzineb, Omar; Boukhetala, Djamel; Tadjine, Mohamed; Benbouzid, Mohamed
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
Li, Pengfei; Hu, Weihao; Liu, Juncheng;
has many advantages, such as easy implementation and high system reliability. Because of using Power Spectral Density method (PSD) or Fast Fourier Transform (FFT) method cannot get clear fault characteristic frequencies, this kind of faults should be detected by an effective method. This paper......The angle faults of blades on wind turbines are usually included in the set angle fault and the pitch angle fault. They are occupied with a high proportion in all wind turbine faults. Compare with the traditional fault detection methods, using order tracking analysis method to detect angle faults...
Full Text Available Gear fault detection based on Empirical Mode Decomposition (EMD and Teager Kaiser Energy Operator (TKEO technique is presented. This novel method is named as Teager-Huang transform (THT. EMD can adaptively decompose the vibration signal into a series of zero mean Intrinsic Mode Functions (IMFs. TKEO can track the instantaneous amplitude and instantaneous frequency of the Intrinsic Mode Functions at any instant. The experimental results provide effective evidence that Teager-Huang transform has better resolution than that of Hilbert-Huang transform. The Teager-Huang transform can effectively diagnose the fault of the gear, thus providing a viable processing tool for gearbox defect detection and diagnosis.
A system is developed to show the viability of non-destructive detection of the faults of explosive safety fuses which are manufactured by Fabrica da Estrela do Ministerio do Exercito. The faults are detected by an ion-chamber based on the variation of the intensity of the beta particles that penetrate the fuse which passes through a collimator. The beta particles are emitted by Strontium-90 + Yttrium-90 encapsulated in either stainless steel or aluminum. The concept of 'bucking Voltage' is applied to differentiate electronically the signal generated by the ion-chamber. (author)
Smyth, Padhraic J.
Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).
Xiaogang Deng; Xuemin Tian
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.
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.
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)
Odgaard, Peter Fogh; Mataji, Babak
In order to achieve high performance and efficiency of coal-fired power plants, it is highly important to control the coal flow into the furnace in the power plant. This means suppression of disturbances and force the coal mill to deliver the required coal flow, as well as monitor the coal mill...... in order to detect faults in the coal mill when they emerge. This paper deals with the second objective. Based on a simple dynamic model of the energy balance a residual is formed for the coal mill. An optimal unknown input observer is designed to estimate this residual. The estimated residual is following...... tested on measured data of a fault in a coal mill, it can hereby be concluded that this residual is very useful for detecting faults in the coal mill....
Casau, Pedro; Rosa, Paulo Andre Nobre; Tabatabaeipour, Seyed Mojtaba;
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...
Ferrell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Brown, Barbara
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.
Pichler, Kurt; Lughofer, Edwin; Pichler, Markus; Buchegger, Thomas; Klement, Erich Peter; Huschenbett, Matthias
This paper presents a novel approach for detecting cracked or broken reciprocating compressor valves under varying load conditions. The main idea is that the time frequency representation of vibration measurement data will show typical patterns depending on the fault state. The problem is to detect these patterns reliably. For the detection task, we make a detour via the two dimensional autocorrelation. The autocorrelation emphasizes the patterns and reduces noise effects. This makes it easier to define appropriate features. After feature extraction, classification is done using logistic regression and support vector machines. The method's performance is validated by analyzing real world measurement data. The results will show a very high detection accuracy while keeping the false alarm rates at a very low level for different compressor loads, thus achieving a load-independent method. The proposed approach is, to our best knowledge, the first automated method for reciprocating compressor valve fault detection that can handle varying load conditions.
Narayan, Anand P.
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
Trippanera, D.; Acocella, V.; Ruch, J.; Abebe, B.
Recent studies highlight the importance of annual-scale dike-induced rifting episodes in developing normal faults and graben along the active axis of magmatic divergent plate boundaries (MDPB). However, the longer-term (102-105 years) role of diking on the cumulative surface deformation and evolution of MDPB is not yet well understood. To better understand the longer-term normal faults and graben along the axis of MDPB, we analyze fissure swarms in Iceland and Ethiopia. We first focus on the simplest case of immature fissure swarms, with single dike-fed eruptive fissures; these consist of a dike-fed eruptive fissures. We then consider the lateral termination of normal faults along these grabens to detect their upward or downward propagation. Most faults terminate as open fractures on flat surface, suggesting downward fault propagation; this is consistent with recent experiments showing dike-induced normal faults propagating downward from the surface. However, some normal faults also terminate as open fractures on monoclines, which resemble fault propagation folds; this suggests upward propagation of reactivated buried faults, promoted by diking. These results suggest that fault growth and graben development, as well as the longer-term evolution of the axis of MDPB, may be explained only through dike emplacement and that any amagmatic faulting is not necessary.
Singh, Gurmeet; Anil Kumar, T. Ch.; Naikan, V. N. A.
Induction motors are the most commonly used prime movers in industries. These are subjected to various environmental, thermal and load stresses that ultimately reduces the motor efficiency and later leads to failure. Inter turn fault is the second most commonly observed faults in the motors and is considered the most severe. It can lead to the failure of complete phase and can even cause accidents, if left undetected or untreated. This paper proposes an online and non invasive technique that uses infrared thermography, in order to detect the presence of inter turn fault in induction motor drive. Two methods have been proposed that detect the fault and estimate its severity. One method uses transient thermal monitoring during the start of motor and other applies pseudo coloring technique on infrared image of the motor, after it reaches a thermal steady state. The designed template for pseudo-coloring is in acquiescence with the InterNational Electrical Testing Association (NETA) thermographic standard. An index is proposed to assess the severity of the fault present in the motor.
Decker, Kurt; Grupe, Sabine; Hintersberger, Esther
The identification of active faults that lie beneath a city is of key importance for seismic hazard assessment. Fault mapping and characterization in built-up areas with strong anthropogenic overprint is, however, a challenging task. Our study of Quaternary faults in the city of Vienna starts from the re-assessment of a borehole database of the municipality containing several tens of thousands of shallow boreholes. Data provide tight constraints on the geometry of Quaternary deposits and highlight several locations with fault-delimited Middle to Late Pleistocene terrace sediments of the Danube River. Additional information is obtained from geological descriptions of historical outcrops which partly date back to about 1900. The latter were found to be particularly valuable by providing unprejudiced descriptions of Quaternary faults, sometimes with stunning detail. The along-strike continuations of some of the identified faults are further imaged by industrial 2D/3D seismic acquired outside the city limits. The interpretation and the assessment of faults identified within the city benefit from a very well constrained tectonic model of the active Vienna Basin fault system which derived from data obtained outside the city limits. This data suggests that the urban faults are part of a system of normal faults compensating fault-normal extension at a releasing bend of the sinistral Vienna Basin Transfer Fault. Slip rates estimated for the faults in the city are in the range of several hundredths of millimetres per year and match the slip rates of normal faults that were trenched outside the city. The lengths/areas of individual faults estimated from maps and seismic reach up to almost 700 km² suggesting that all of the identified faults are capable of producing earthquakes with magnitudes M>6, some with magnitudes up to M~6.7.
The ability to predict earthquakes is one of the greatest challenges for Earth Sciences. Radon has been suggested as one possible precursor, and its groundwater anomalies associated with earthquakes and water-rock interactions were proposed in several seismogenic areas worldwide as due to possible transport of radon through microfractures, or due to crustal gas fluxes along active faults. However, the use of radon as a possible earthquake's precursor is not clearly linked to crustal deformation. It is shown in this paper that uranium groundwater anomalies, which were observed in cataclastic rocks crossing the underground Gran Sasso National Laboratory, can be used as a possible strain meter in domains where continental lithosphere is subducted. Measurements evidence clear, sharp anomalies from July, 2008 to the end of March, 2009, related to a preparation phase of the seismic swarm, which occurred near L'Aquila, Italy, from October, 2008 to April, 2009. On April 6th, 2009 an earthquake (Mw = 6.3) occurred at 01:33 UT in the same area, with normal faulting on a NW-SE oriented structure about 15 km long, dipping toward SW. In the framework of the geophysical and geochemical models of the area, these measurements indicate that uranium may be used as a possible strain meter in extensional tectonic settings similar to those where the L'Aquila earthquake occurred. (author)
Davies, Francis J. (Inventor); Graika, Jason R. (Inventor)
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.
Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are...
Odgaard, Peter Fogh; Mataji, Babak
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...
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.
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.
Kuo, Li-Wei; Song, Sheng-Rong; Suppe, John; Yeh, En-Chao
Fault mirrors (FMs) are naturally polished and glossy fault slip surfaces that can record seismic deformation at shallow depths. They are important for investigating the processes controlling dynamic fault slip. We characterize FMs in borehole samples from the hanging wall damage zone of the active Hsiaotungshi reverse fault, Taiwan. Here we report the first documented occurrence of the combination of silica gel and melt patches coating FMs, with the silica gel resembling those observed on experimentally formed FMs that were cataclastically generated. In addition, the melt patches, which are unambiguous indicators of coseismic slip, suggest that the natural FMs were produced at seismic rates, presumably resulting from flash heating at asperities on the slip surfaces. Since flash heating is efficient at small slip, we propose that these natural FMs represent fossils of small earthquakes, formed in either coseismic faulting and folding or aftershock deformation in the active Taiwan fold-and-thrust belt.
Yamashita, F.; Kubo, A.; Yamada, R.; Omura, K.
Dense VLF-MT and TDEM surveys were carried out to image the electrical structure of a region interpreted as a creeping segment of the Atotsugawa Fault, central Japan. The Atotsugawa Fault is an active fault with a length of 60-70 km and a strike of approximately N60°E. The fault type is a right-lateral strike-slip. The most significant characteristic of this fault is a possible existence of creeping segment. In the central region, the stable slip with a rate of 1.5 mm/year was found by the observation of baseline change (Geographical Survey Institute, 1997). However, such slip has not been found at the southwestern region. Therefore, the central region is considered to be a creeping segment. In the creeping segment, many fault outcrops were found on the right bank of the Atotsu-gawa River that runs along the fault. Strikes of shear planes in outcrops were observed to be N30°-47°E, which is apparently different from that of the Atotsugawa fault. This observation suggested the existence of en echelon structure, which is the cluster of small shear zones oblique to main fault. Investigation of the nature of the en echelon structure will help us to understand the growth history of the Atotsugawa fault and the mechanisms of creeping phenomenon. Because a fracture zone usually includes much water, we can detect it as a low resistivity zone. In order to image the detailed structure of echelon, we carried out the electromagnetic surveys; VLF-MT and TDEM survey as a preliminary and main investigation, respectively. The results of VLF-MT survey has been reported by Yamashita et al. (2005), and therefore we don_ft refer to the results here. We acquired data at 10000 points with airborne TDEM survey, and over 4000 data were selectively used for modeling the subsurface structure. Apparent resistivity at each point was modeled assuming 1-D structure that consists of 30 and 70 m thick layers on a semi-infinite basement (three layers in total). Because over 4000 survey points
Padilla, Peter A.
The fault handling performance of the fault tolerant multiprocessor (FTMP) was investigated. Fault handling errors detected during fault injection experiments were characterized. In these fault injection experiments, the FTMP disabled a working unit instead of the faulted unit once every 500 faults, on the average. System design weaknesses allow active faults to exercise a part of the fault management software that handles byzantine or lying faults. It is pointed out that these weak areas in the FTMP's design increase the probability that, for any hardware fault, a good LRU (line replaceable unit) is mistakenly disabled by the fault management software. It is concluded that fault injection can help detect and analyze the behavior of a system in the ultra-reliable regime. Although fault injection testing cannot be exhaustive, it has been demonstrated that it provides a unique capability to unmask problems and to characterize the behavior of a fault-tolerant system.
A method is described by which a localized sensor abnormality can be detected using the Mahalanobis distance. The Mahalanobis distance is approximately the weighted distance from the hyperplane formed by the principal components to the particular observation. Qualitatively, the principal components correspond to the physical laws that govern the behavior of the systems and constraints placed on the system. If there are more sensors than principal components, there are redundant measurements. This redundancy can be used to detect abnormalities that are due either to sensor failure or a localized change in the system being measured. The method compares the distribution of the Mahalanobis distance during normal operation with the distribution during the current operation. A likelihood ratio test is then used to determine if a sensor has gone bad or if operations in the reactor are different from normal. The sensor whose value is not normal is identified by comparing Mahalanobis distances computed with one sensor masked. When the abnormal sensor is masked, the Mahalanobis distance for this subset of sensors will be within prespecified bounds. The method is demonstrated on 20 subassembly output thermocouples in the core of Experimental Breeder Reactor II
Jensen, Hans-Christian Becker; Wisniewski, Rafal
This article realizes nonlinear Fault Detection and Isolation for a momentum wheel. The Fault Detection and Isolation is based on a Failure Mode and Effect Analysis, which states which faults might occur and can be detected. The algorithms presented in this paper are based on a geometric approach...... toachieve nonlinear Fault Detection and Isolation. The proposed algorithms are tested in a simulation study and the pros and cons of the algorithm are discussed....
Jensen, Hans-Christian Becker; Wisniewski, Rafal
This article realizes nonlinear Fault Detection and Isolation for a momentum wheel. The Fault Detection and Isolation is based on a Failure Mode and Effect Analysis, which states which faults might occur and can be detected. The algorithms presented in this paper are based on a geometric approach...
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.
The development of fault detection algorithms is well-suited for remote deployment of small and medium reactors, such as the IRIS, and the development of new small modular reactors (SMR). However, an extensive number of tests are still to be performed for new engineering aspects and components that are not yet proven technology in the current PWRs, and present some technological challenges for its deployment since many of its features cannot be proven until a prototype plant is built. In this work, an IRIS plant simulation platform was developed using a Simulink® model. The dynamic simulation was utilized in obtaining inferential models that were used to detect faults artificially added to the secondary system simulations. The implementation of data-driven models and the results are discussed. (author)
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)
Guerrier, Stéphane; Waegli, Adrian; Skaloud, Jan; Victoria-Feser, Maria-Pia
This research presents methods for detecting and isolating faults in multiple MEMS-IMU configurations. First, geometric configurations with n sensor triads are investigated. It is proofed that the relative orientation between sensor triads is irrelevant to system optimality in the absence of failures. Then, the impact of sensor failure or decreased performance is investigated. Three FDI approaches (i.e. the parity space method, Mahalanobis distance method and its direct robustification) are r...
Leloux, Jonathan; Luna, Alberto; Desportes, Adrien
BIPV systems are small PV generation units spread out over the territory, and whose characteristics are very diverse. This makes difficult a cost-effective procedure for monitoring, fault detection, performance analyses, operation and maintenance. As a result, many problems affecting BIPV systems go undetected. In order to carry out effective automatic fault detection procedures, we need a performance indicator that is reliable and that can be applied on many PV systems at a very low cost. The existing approaches for analyzing the performance of PV systems are often based on the Performance Ratio (PR), whose accuracy depends on good solar irradiation data, which in turn can be very difficult to obtain or cost-prohibitive for the BIPV owner. We present an alternative fault detection procedure based on a performance indicator that can be constructed on the sole basis of the energy production data measured at the BIPV systems. This procedure does not require the input of operating conditions data, such as solar ...
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...
KÜÇÜKER, AHMET; BAYRAK, Mehmet
Stator interturn faults are one of the most common faults occurring in induction motors. Early detection of interturn short circuit is important to reduce repair costs. Axial leakage monitoring, zero-sequence components, negative sequence current, and motor current signature analysis have been used for fault detection in early states. In the paper, the instantaneous power signature analysis technique is used to detect these faults, and experimental results for healthy and faulty motors are sh...
Golafshan, Reza; Yuce Sanliturk, Kenan
Ball bearings remain one of the most crucial components in industrial machines and due to their critical role, it is of great importance to monitor their conditions under operation. However, due to the background noise in acquired signals, it is not always possible to identify probable faults. This incapability in identifying the faults makes the de-noising process one of the most essential steps in the field of Condition Monitoring (CM) and fault detection. In the present study, Singular Value Decomposition (SVD) and Hankel matrix based de-noising process is successfully applied to the ball bearing time domain vibration signals as well as to their spectrums for the elimination of the background noise and the improvement the reliability of the fault detection process. The test cases conducted using experimental as well as the simulated vibration signals demonstrate the effectiveness of the proposed de-noising approach for the ball bearing fault detection.
Polenta, Héctor P.; Bernard, John A.; Ray, Asok
The design and implementation of a redundancy management scheme for the on-line detection and isolation of faulty sensors is presented. Such a device is potentially useful in reactor-powered spacecraft for enhancing the processing capabilities of the main computer. The fault detection device can be used as an integral part of intelligent instrumentation systems. The device has been built using an 8-bit microcontroller and commercially available electronic hardware. The software is completely portable. The operation of this device has been successfully demonstrated for real-time validation of sensor data on Argentina's RA-1 Research Reactor.
The design and implementation of a redundancy management scheme for the on-line detection and isolation of faulty sensors is presented. Such a device is potentially useful in reactor-powered spacecraft for enhancing the processing capabilities of the main computer. The fault detection device can be used as an integral part of intelligent instrumentation systems. The device has been built using an 8-bit microcontroller and commercially available electronic hardware. The software is completely portable. The operation of this device has been successfully demonstrated for real-time validation of sensor data on Argentina's RA-1 Research Reactor
Full Text Available A study is presented to compare the performance of bearing fault detection using three types of artificial neural networks (ANNs, namely, multilayer perceptron (MLP, radial basis function (RBF network, and probabilistic neural network (PNN. The time domain vibration signals of a rotating machine with normal and defective bearings are processed for feature extraction. The extracted features from original and preprocessed signals are used as inputs to all three ANN classifiers: MLP, RBF, and PNN for two-class (normal or fault recognition. The characteristic parameters like number of nodes in the hidden layer of MLP and the width of RBF, in case of RBF and PNN along with the selection of input features, are optimized using genetic algorithms (GA. For each trial, the ANNs are trained with a subset of the experimental data for known machine conditions. The ANNs are tested using the remaining set of data. The procedure is illustrated using the experimental vibration data of a rotating machine with and without bearing faults. The results show the relative effectiveness of three classifiers in detection of the bearing condition.
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...
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.
Choi, Ui-Min; Jeong, Hae-Gwang; Lee, Kyo-Beum; Blaabjerg, Frede
This paper proposes a fault-detection method for an open-switch fault in the switches of grid-connected neutral-point-clamped inverter systems. The proposed method can not only detect the fault condition but also identify the location of the faulty switch. In the proposed method, which is designe...
Vukic, Z.; Ozbolt, H.; Blanke, M.
The paper gives an introduction and an overview of the field of fault detection and isolation for control systems. The summary of analytical (quantitative model-based) methodds and their implementation are presented. The focus is given to mthe analytical model-based fault-detection and fault...
Authemayou, Christine; Brocard, Gilles; TEYSSIER, Christian; Suski, Barbara; Cosenza, Beatriz; Moran-Ical, Sergio; Gonzalez-Veliz, Claussen Walther; Aguilar-Hengstenberg, Miguel Angel; Holliger, Klaus
The Polochic-Motagua fault system is part of the sinistral transform boundary between the North American and Caribbean plates in Guatemala and the associated seismic activity poses a threat to ∼70% of the country's population. The aim of this study is to constrain the Late Quaternary activity of the Polochic fault by determining the active structure geometry and quantifying recent displacement rates as well as paleo-seismic events. Slip rates have been estimated from offsets of Quaternary vol...
Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas
An active fault diagnosis approach for different kinds of faults is proposed. The input of the approach is designed off-line based on sensitivity analysis such that the maximum sensitivity for each individual system parameter is obtained. Using maximum sensitivity, results in a better precision 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...
Sen, B.; Wang, J.
This paper proposes a novel method of interturn fault detection based on measurement of pulsewidth modulation (PWM) ripple current. The method uses the ripple current generated by the switching inverter as a means to detect interturn fault. High-frequency (HF) impedance behavior of healthy and faulted windings is analyzed and modeled, and ripple current signature due to interturn faults is quantified. A simple analog circuit is designed to extract the PWM ripple current via a bandpass (BP) fi...
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...
Cilliers, Anthonie Christoffel; Mulder, Eben Johan
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...
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.
Suratsavadee Koonlaboon KORKUA
Full Text Available With the advances in power electronic technology, doubly-fed induction generators (DFIG have increasingly drawn the interest of the wind turbine industry. To ensure the reliable operation and power quality of wind power systems, the fault-tolerant control for DFIG is studied in this paper. The fault-tolerant controller is designed to maintain an acceptable level of performance during bearing fault conditions. Based on measured motor current data, an adaptive statistical time-frequency method is then used to detect the fault occurrence in the system; the controller then compensates for faulty conditions. The feature vectors, including frequency components located in the neighborhood of the characteristic fault frequencies, are first extracted and then used to estimate the next sampling stator side current, in order to better perform the current control. Early fault detection, isolation and successful reconfiguration would be very beneficial in a wind energy conversion system. The feasibility of this fault-tolerant controller has been proven by means of mathematical modeling and digital simulation based on Matlab/Simulink. The simulation results of the generator output show the effectiveness of the proposed fault-tolerant controller.
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)
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.
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
Zhao, Zheng; Wang, Can; Zhang, Yagang; Sun, Yi
In the researches of complex electrical engineering, efficient fault detection and localization schemes are essential to quickly detect and locate faults so that appropriate and timely corrective mitigating and maintenance actions can be taken. In this paper, under the current measurement precision of PMU, we will put forward a new type of fault detection and localization technology based on fault factor feature extraction. Lots of simulating experiments indicate that, although there are disturbances of white Gaussian stochastic noise, based on fault factor feature extraction principal, the fault detection and localization results are still accurate and reliable, which also identifies that the fault detection and localization technology has strong anti-interference ability and great redundancy.
De La Pena, A.; Wessels, S.A.; Gunnell, A.R.; Numa, K.J.; Williams-Stroud, S.; Eisner, Leo; Thornton, M.; Mueller, M.
New York: Curran Associates, 2011, s. 545-549. ISBN 978-1-61782-966-6. [European Association of Geoscientists and Engineers Conference and Exhibition 2011 /73./ - Incorporating SPE EUROPEC 2011. Vienna (AT), 23.05.2011-26.05.2011] Institutional research plan: CEZ:AV0Z30460519 Keywords : B value * fault activity * fault event Subject RIV: DC - Siesmology, Volcanology, Earth Structure
Dyi-Rong Duh; Ssu-Pei Li; Victor W. Cheng
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. ...
Amooee, Golriz; Bagheri-Dehnavi, Malihe
In the current competitive world, industrial companies seek to manufacture products of higher quality which can be achieved by increasing reliability, maintainability and thus the availability of products. On the other hand, improvement in products lifecycle is necessary for achieving high reliability. Typically, maintenance activities are aimed to reduce failures of industrial machinery and minimize the consequences of such failures. So the industrial companies try to improve their efficiency by using different fault detection techniques. One strategy is to process and analyze previous generated data to predict future failures. The purpose of this paper is to detect wasted parts using different data mining algorithms and compare the accuracy of these algorithms. A combination of thermal and physical characteristics has been used and the algorithms were implemented on Ahanpishegan's current data to estimate the availability of its produced parts. Keywords: Data Mining, Fault Detection, Availability, Predictio...
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.
V. S. Chandrika
Full Text Available This study presents a novel method of detection of inter turn shorts based on k means clustering technique. In addition to inter turn short detection, the other faults like open, short, phase to phase faults and DC volt-age faults are detected through wavelet transforms and k means clustering. Open and short faults are classified using artificial neural network. All other faults are classified using Support Vector Machines (SVM. Switched reluctance motors are very popular in these days, because of ease in manufacturing and operation. Though an electronic circuit can detect the faults like open and short, the classification cannot be done effectively with electronic circuitry. More over an intelligent method can easily identify the fault and classify and hence the root cause of the fault may be guessed and rectified using this method of classification. This is highly possible with the time localization property of the wavelet transforms. So instant of fault occurrence can be detected along with the type of fault. The information used to include this intelligence in the system are just current waveforms, flux waveforms and torque waveforms. Inter turn shorts are very critical for a long run operation of the motor. Moreover, the early detection minimizes the faulty operation time and ensures the plant stability and saves the life of motor too. Hence an integrated system to detect the major faults under a simulation model has been proposed in this study.
Barba, M.; Rains, C.; von Dassow, W.; Parker, J. W.; Glasscoe, M. T.
Knowing the location and behavior of active faults is essential for earthquake hazard assessment and disaster response. In Interferometric Synthetic Aperture Radar (InSAR) images, faults are revealed as linear discontinuities. Currently, interferograms are manually inspected to locate faults. During the summer of 2013, the NASA-JPL DEVELOP California Disasters team contributed to the development of a method to expedite fault detection in California using remote-sensing technology. The team utilized InSAR images created from polarimetric L-band data from NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) project. A computer-vision technique known as 'edge-detection' was used to automate the fault-identification process. We tested and refined an edge-detection algorithm under development through NASA's Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) project. To optimize the algorithm we used both UAVSAR interferograms and synthetic interferograms generated through Disloc, a web-based modeling program available through NASA's QuakeSim project. The edge-detection algorithm detected seismic, aseismic, and co-seismic slip along faults that were identified and compared with databases of known fault systems. Our optimization process was the first step toward integration of the edge-detection code into E-DECIDER to provide decision support for earthquake preparation and disaster management. E-DECIDER partners that will use the edge-detection code include the California Earthquake Clearinghouse and the US Department of Homeland Security through delivery of products using the Unified Incident Command and Decision Support (UICDS) service. Through these partnerships, researchers, earthquake disaster response teams, and policy-makers will be able to use this new methodology to examine the details of ground and fault motions for moderate to large earthquakes. Following an earthquake, the newly discovered faults can
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.
Nguyen-Duy, Khiem; Liu, Tian-Hua; Chen, Der-Fa
The matrix converter system is becoming a very promising candidate to replace the conventional two-stage ac/dc/ac converter, but system reliability remains an open issue. The most common reliability problem is that a bidirectional switch has an open-switch fault during operation. In this paper, a...... matrix converter driving a speed-controlled permanent-magnet synchronous motor is examined under a single open-switch fault. First, a new fault-detection method is proposed using only the motor currents. Second, a novel fault-tolerant switching strategy is presented. By treating the matrix converter as a...... two-stage rectifier/inverter, existing modulation techniques for the inverter stage can be reused, whereas the rectifier stage is modified by control to counteract the fault. However, the proposed techniques require no additional hardware devices or circuit modifications to the matrix converter...
As digital instrumentation and control (I and C) systems are gradually introduced into nuclear power plants (NPPs), concerns about the I and C systems’ reliability and safety are growing. Fault detection coverage is one of the most critical factors in the probabilistic safety assessment (PSA) of digital I and C systems. To correctly estimate the fault detection coverage, it is first necessary to identify important factors affecting it. From experimental results found in the literature and the authors’ experience in fault injection experiments on digital systems, four system-related factors and four fault-related factors are identified as important factors affecting the fault detection coverage. A fault injection experiment is performed to demonstrate the dependency of fault detection coverage on some of the identified important factors. The implications of the experimental results on the estimation of fault detection coverage for the PSA of digital I and C systems are also explained. The set of four system-related factors and four fault-related factors is expected to provide a framework for systematically comparing and analyzing various fault injection experiments and the resultant estimations on fault detection coverage of digital I and C systems in NPPs. (author)
The fault detection and diagnosis system, the FDD system, for the HVAC was initiated around the middle of 1970s in Japan but it still remains at the elementary stage. The HVAC is really one of the most complicated and large scaled system for the FDD system. Besides, the maintenance engineering was never focussed as the target of the academic study since after the war, but the FDD system for some kinds of the components and subsystems has been developed for the sake of the practical industrial needs. Recently, international cooperative study in the IEA Annex 25 on the energy conservation for the building and community targetted on the BOFD, the building optimization, fault detection and diagnosis. Not a few academic peaple from various engineering field got interested and, moreover, some national projects seem to start in the European countries. The author has reviewed the state of the art of the FDD and BO as well based on the references and the experience at the IEA study.
This paper presents a discussion of the ground-fault detecting systems on the DIII-D tokamak. The subsystems that must be monitored for an inadvertent ground include the toroidal and poloidal coil systems, the vacuum vessel, and the coil support structures. In general, one point of each coil is tied to coil/power supply ground through a current limiting resistor. For ground protection the current through this resistor is monitored using a dynamically feedback balanced Hall probe transducer from LEM Industries. When large inductive currents flow in closed loops near the the tokamak, the result is undesirable magnetic error fields in the plasma region and noise generation on signal cables. Therefore, attention must be paid to avoid closed loops in the design of the coil and vessel support structure. For DIII-D a concept of dual insulating breaks and a single-point ground for all structure elements was used to satisfy this requirement. The integrity of the support structure is monitored by a system which continuously attempts to couple a variable frequency waveform onto these single-point grounds. The presence of an additional ground completes the circuit resulting in current flow. A Rogowski coil is then used to track the unwanted ground path in order to eliminate it. Details of the ground fault detection circuitry, and a description of its operation will be presented
This paper presents a discussion of the ground-fault detection systems on the DIII-D tokamak. The subsystems that must be monitored for an inadvertent ground include the toroidal and poloidal coil systems, the vacuum vessel, and the coil support structures. In general, one point of each coil is tied to coil/power supply ground through a current limiting resistor. For ground protection the current through this resistor is monitored using a dynamically feedback balanced Hall probe transducer from LEM Industries. When large inductive currents flow in closed loops near the tokamak, the result is undesirable magnetic error fields in the plasma region and noise generation on signal cables. Therefore, attention must be paid to avoid closed loops in the design of the coil and vessel support structure. For DIII-D a concept of dual insulating breaks and a single-point ground for all structure elements was used to satisfy this requirement. The integrity of the support structure is monitored by a system which continuously attempts to couple a variable frequency waveform onto these single-point grounds. The presence of an additional ground completes the circuit resulting in current flow. A Rogowski coil is then used to track the unwanted ground path in order to eliminate it. Details of the ground fault detection circuitry, and a description of its operation will be presented. 2 refs., 7 figs
Yang, Zhenyu; Rasmussen, Karsten B.; Kieu, Anh T.;
Fault Detection and Isolation (FDI) using the Kalman Filter (KF) technique for a supermarket refrigeration system is explored. Four types of sensor fault scenarios, namely drift, offset, freeze and hard-over, are considered for two temperature sensors, and one type of parametric fault scenario...
Tadić Predrag R.
Full Text Available This paper presents a design of a decentralized fault detection and isolation (FDI filter by means of an overlapping decentralized estimation algorithm based on a consensus strategy. An efficient solution to the FDI problem can be obtained by an adequate system decomposition into overlapping subsystems and the construction of local FDI estimators aimed at achieving the desired performance. The general aspects and properties of a consensus based estimator are described in the first part of the paper. An applicability of such an estimator to an FDI problem in a large scale system is discussed next. Namely, a case study related to the detection of fire dissymmetry in a thermal power plant boiler is presented, including the process description and identification procedure, comparison between the results obtained by local and decentralized estimators and conclusions concerning their validity.
Das, N.; Roy, P.; Rahaman, H.
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.
of the hybrid model are estimated by a recursive estimation algorithm, the Extended Kalman Filter (EKF), using experimental data which was provided by an equipped laboratory. Two methods for active fault diagnosis are proposed. The AFD methods excite the system by injecting a so-called excitation...... degraded performance even in the faulty case. In this thesis, we have designed such controllers for climate control systems for livestock buildings in three steps: Deriving a model for the climate control system of a pig-stable. Designing a active fault diagnosis (AFD) algorithm for different kinds of...... fault. Designing a fault tolerant control scheme for the climate control system. In the first step, a conceptual multi-zone model for climate control of a live-stock building is derived. The model is a nonlinear hybrid model. Hybrid systems contain both discrete and continuous components. The parameters...
We propose in this paper robust reconstruction methods for tangential dislocations on planar faults. We assume that only surface observations are available, and that a traction free condition applies at that surface. This study is an extension to the full three dimensions of Ionescu and Volkov (2006 Inverse Problems 22 2103). We also explore in this present paper the possibility of detecting slow slip events (such as silent earthquakes, or earthquake nucleation phases) from GPS observations. Our study uses extensively an asymptotic estimate for the observed surface displacement. This estimate is first used to derive what we call the moments reconstruction method. Then it is also used for finding necessary conditions for a surface displacement field to have been caused by a slip on a fault. These conditions lead to the introduction of two parameters: the activation factor and the confidence index. They can be computed from the surface observations in a robust fashion. They indicate whether a measured displacement field is due to an active fault. We also infer a second, combined, reconstruction technique blending least square minimization and the moments method. We carefully assess how our reconstruction method is affected by the sensitivity of the observation apparatus and the stepsize for the grid of surface observation points. The maximum permissible stepsize for such a grid is computed for different values of fault depth and orientation. Finally we present numerical examples of reconstruction of faults. We demonstrate that our combined method is sharp, robust and computationally inexpensive. We also note that this method performs satisfactorily for shallow faults, despite the fact that our asymptotic formula deteriorates in that case
N. Talebi; M.A. Sadrnia; A. Darabi
Reliability of Wind Energy Conversion Systems (WECSs) is greatly important regarding to extract the maximum amount of available wind energy. In order to accurately study WECSs during occurrence of faults and to explore the impact of faults on each component of WECSs, a detailed model is required in which mechanical and electrical parts of WECSs are properly involved. In addition, a Fault Detection and Isolation System (FDIS) is required by which occurred faults can be diagnosed at the appropr...
Yang, Kai; Zhang, Rencheng; Yang, Jianhong; Liu, Canhua; Chen, Shouhong; Zhang, Fujiang
Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires. PMID:27070618
Authemayou, Christine; Brocard, Gilles; Teyssier, Christian; Suski, Barbara; Cosenza, Beatriz; MoráN-Ical, Sergio; GonzáLez-VéLiz, Claussen Walther; Aguilar-Hengstenberg, Miguel Angel; Holliger, Klaus
The Polochic-Motagua fault system is part of the sinistral transform boundary between the North American and Caribbean plates in Guatemala and the associated seismic activity poses a threat to ˜70% of the country's population. The aim of this study is to constrain the Late Quaternary activity of the Polochic fault by determining the active structure geometry and quantifying recent displacement rates as well as paleo-seismic events. Slip rates have been estimated from offsets of Quaternary volcanic markers and alluvial fan using in situ cosmogenic 36Cl exposure dating. Holocene left-lateral slip rate and Mid-Pleistocene vertical slip rate have been estimated to 4.8 ± 2.3 mm/y and 0.3 ± 0.06 mm/y, respectively, on the central part of the Polochic fault. The horizontal slip rate is within the range of longer-term geological slip rates and short-term GPS-based estimates. In addition, the non-negligible vertical motion participates in the uplift of the block north of the fault and seems to be a manifestation of the regional, far-field stress regime. We excavated the first trench for paleo-seismological study on the Polochic fault in which we distinguish four large paleo-seismic events since 17 ky during which the Polochic fault ruptured the ground surface.
Planetary gearboxes are commonly used in modern industry because of their large transmission ratio and strong load-bearing capacity. They generally work under heavy load and tough working environment and therefore their key components including sun gear, planet gears, ring gear, etc are subject to severe pitting and fatigue crack. Planetary gearboxes significantly differ from fixed-axis gearboxes and exhibit unique behavior, which invalidates the use of the diagnostic parameters developed and suitable for fixed-axis gearboxes. Therefore, there is a need to develop parameters specifically for detecting and diagnosing faults of planetary gearboxes. In this study, two diagnostic parameters are proposed based on the examination of the vibration characteristics of planetary gearboxes in both time and frequency domains. One is the root mean square of the filtered signal (FRMS) and the other is the normalized summation of positive amplitudes of the difference spectrum between the unknown signal and the healthy signal (NSDS). To test the proposed diagnostic parameters, we conducted experiments on a planetary gearbox test rig with sun gear faults including a cracked tooth and a pitted tooth. The vibration signals were measured under different motor speeds. The proposed parameters are compared with the existing parameters reported in the literature. The comparison results show the proposed diagnostic parameters perform better than others. (paper)
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...
Blakely, Richard J.; Sherrod, Brian L.; Weaver, Craig S.; Wells, Ray E.; Rohay, Alan C.; Barnett, Elizabeth A.; Knepprath, Nichole E.
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.
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...
Jensen, V; Gibson, G; R. Van Dissen; McCue, K.; Boreham, B.
The Lake Edgar Fault in Western Tasmania, Australia is marked by a prominent fault scarp and is a recently reactivated fault initially of Cambrian age. The scarp has a northerly trend and passes through the western abutment of the Edgar Dam, a saddle dam on Lake Pedder. The active fault segment displaces geologically young river and glacial deposits. It is 29 ± 4 km long, and dips to the west. Movement on the fault has ruptured the ground surface at least twice within the ...
Highlights: • Attempt was to use available resources at a nuclear plant in a value added fashion. • Includes plant measurement data and plant training and engineering simulator capabilities. • Correlating fault detection data for systems to develop of a deterministic fault identifications system. • After implementing a host of data manipulation algorithms, the results provided more information on the fault than expected. • TMI benchmark results in value added to the operator and system. - Abstract: Early fault identification systems enable detecting and diagnosing early onset faults or fault causes which allow maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. We have shown (Cilliers and Mulder, 2012) that detecting faults early during transient operation in NPPs is possible when coupled with a reliable reference to compare plant measurements with during transients. We have also shown (Cilliers, 2013) that by correlating the fault detection information as received from distributed systems it is possible to diagnose the faults in terms of location and magnitude. This paper makes use of the techniques and processes developed in the previous papers and apply it to a case study of the Three Mile Island accident. In this way we can determine how the improved information available could present the operator with a better idea to the state of the plant during situations where a combination of faults and transients prevents the operator and conventional systems to recognise the abnormal behaviour
The proper and timely fault detection and isolation of industrial plant is of premier importance to guarantee the safe and reliable operation of industrial plants. The paper presents application of a neural networks-based scheme for fault detection and isolation, for the pressurizer of a PWR nuclear power plant. The scheme is constituted by 2 components: residual generation and fault isolation. The first component generates residuals via the discrepancy between measurements coming from the plant and a nominal model. The neutral network estimator is trained with healthy data collected from a full-scale simulator. For the second component detection thresholds are used to encode the residuals as bipolar vectors which represent fault patterns. These patterns are stored in an associative memory based on a recurrent neutral network. The proposed fault diagnosis tool is evaluated on-line via a full-scale simulator detected and isolate the main faults appearing in the pressurizer of a PWR. (orig.)
Zhanshan WANG; Huaguang ZHANG
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.
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.
METATLA, A.; BENZAHIOUL, S.; BAHI, T.; Lefebvre, D.
This work concerns the monitoring and diagnosis of faults in induction motors. We develop an approach based on residual analysis of stator currents to detect and diagnose faults eccentricity static, dynamic and mixed in three phase induction motor. To simulate the behavior of motor failure, a model is proposed based on the approach of magnetically coupled coils. The simulation results show the importance of the approach applied for the detection and diagnosis of fault in three phase induct...
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.
De Pascale, Gregory P.; Chandler-Yates, Nicholas; Dela Pena, Federico; Wilson, Pam; May, Elijah; Twiss, Amber; Cheng, Che
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.
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.
Jung, Woo Sik [Sejong University, Seoul (Korea, Republic of)
A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This paper presents a new linear time algorithm to detect modules of large fault trees. The size of cut sets can be substantially reduced by replacing independent subtrees in a fault tree with super-components. Chatterjee and Birnbaum developed properties of modules, and demonstrated their use in the fault tree analysis. Locks expanded the concept of modules to non-coherent fault trees. Independent subtrees were manually identified while coding a fault tree for computer analysis. However, nowadays, the independent subtrees are automatically identified by the fault tree solver. A Dutuit and Rauzy (DR) algorithm to detect modules of a fault tree for coherent or non-coherent fault tree was proposed in 1996. It has been well known that this algorithm quickly detects modules since it is a linear time algorithm. The new algorithm minimizes computational memory and quickly detects modules. Furthermore, it can be easily implemented into industry fault tree solvers that are based on traditional Boolean algebra, binary decision diagrams (BDDs), or Zero-suppressed BDDs. The new algorithm employs only two scalar variables in Eqs. to that are volatile information. After finishing the traversal and module detection of each node, the volatile information is destroyed. Thus, the new algorithm does not employ any other additional computational memory and operations. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.
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
Herp, Jürgen; S. Nadimi, Esmaeil
Slowly developing faults in wind turbine can, when not detected and fixed on time, cause severe damage and downtime. We are proposing a fault detection method based on Artificial Neural Networks (ANN) and the recordings from Supervisory Control and Data Acquisition (SCADA) systems installed in wind...
Zhao Xin; Wang Shicheng; Zhang Jinsheng; Fan Zhiliang; Min Haibo
Real-time and accurate fault detection is essential to enhance the aircraft navigation system's reliability and safety.The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults.On account of this reason,we propose an online detection solution based on non-analytical model.In this article,the navigation system fault detection model is established based on belief rule base (BRB),where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output.To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update,a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization (EM) algorithm.Furthermore,the proposed method is verified by navigation experiment.Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model.The output of the detection model can track the fault state very well,and the faults can be diagnosed in real time and accurately.In addition,the detection ability,especially in the probability of false detection,is superior to offline optimization method,and thus the system reliability has great improvement.
Wang, Chao; Delgado Prieto, Miguel; Romeral, Luis;
Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold-Kalman F......Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold......-Kalman Filter is proposed to detect the partial demagnetization fault in PMSMs running at nonstationary conditions. Amplitude of envelope of the fault characteristic orders is used as fault indictor. Experimental results verify the superiority of the proposed method on partial demagnetization online fault...
Luiso, Paola; Paoletti, Valeria; Gaudiosi, Germana; Nappi, Rosa; Cella, Federico; Fedi, Maurizio
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
Padilla, Peter A.
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.
Zhang, Kunbo; Kao, Imin; Kambli, Sachin; Boehm, Christian
Fault is a undesirable factor in any mechanical/pneumatic system. It affects the efficiency of system operation and reduces economic benefit in industry. The early detection and diagnosis of faults in a mechanical system becomes important for preventing failure of equipment and loss of productivity and profits. In this paper, we present our ongoing research results on intelligent fault detections and diagnosis (FDD) on mechanical/ pneumatic systems. Using data from sensors and sensor network in an integrated industrial system, our proposed FDD methodology provides the analysis of necessary sensory information (for example, flow rates and pressure, as well as other digital sensor data) for the detection and diagnosis of system fault. In this experimental study, the leakage of pneumatic cylinder was the "fault." It was shown that the FDD analysis was able to make diagnosis of leakage both in location and size of the fault. In addition, the systematic fault and localized faults can be detected separately. The proposed wavelet method gives rise to the fingerprint analysis to recognize the patterns of the flow rate and pressure data - a very useful tool in intelligent fault detection and diagnosis.
Full Text Available Reliability of Wind Energy Conversion Systems (WECSs is greatly important regarding to extract the maximum amount of available wind energy. In order to accurately study WECSs during occurrence of faults and to explore the impact of faults on each component of WECSs, a detailed model is required in which mechanical and electrical parts of WECSs are properly involved. In addition, a Fault Detection and Isolation System (FDIS is required by which occurred faults can be diagnosed at the appropriate time in order to ensure safe system operation and avoid heavy economic losses. This can be performed by subsequent actions through fast and accurate detection and isolation of faults. In this paper, by utilizing a comprehensive dynamic model of the WECS, an FDIS is presented using dynamic recurrent neural networks. In industrial processes, dynamic neural networks are known as a good mathematical tool for fault detection. Simulation results show that the proposed FDIS detects faults of the generator's angular velocity sensor, pitch angle sensors and pitch actuators appropriately. The suggested FDIS is capable to detect and isolate the faults shortly while owing very low false alarms rate. The presented FDIS scheme can be used to identify faults in other parts of the WECS.
Xie Heping; Zhao Jianfeng; Yu Guangming
Mining-caused activation of fault is an important research subject in mining science. In the past, the influences of geometrical morphology of fault surface on the activation have not been revealed. In view of the fractal character of fault surface, the self-affine fractal curves and geological-mining models with these kinds of fractal fault surface are constructed in order to numerically simulate the mining-caused activation phenomenon of fractal fault surface, and the law of influence of fr...
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.
Wang, Bright L.
The electrical power system of a spacecraft plays a very critical role for space mission success. Such a modern power system may contain numerous hybrid DC/DC converters both inside the power system electronics (PSE) units and onboard most of the flight electronics modules. One of the faulty conditions for DC/DC converter that poses serious threats to mission safety is the random occurrence of oscillation related to inherent instability characteristics of the DC/DC converters and design deficiency of the power systems. To ensure the highest reliability of the power system, oscillations in any form shall be promptly detected during part level testing, system integration tests, flight health monitoring, and on-board fault diagnosis. The popular gain/phase margin analysis method is capable of predicting stability levels of DC/DC converters, but it is limited only to verification of designs and to part-level testing on some of the models. This method has to inject noise signals into the control loop circuitry as required, thus, interrupts the DC/DC converter's normal operation and increases risks of degrading and damaging the flight unit. A novel technique to detect oscillations at early stage for flight hybrid DC/DC converters was developed.
Park, Han; Zak, Michail
Proper orthogonal decomposition (POD) is the mathematical basis of a method of constructing low-order mathematical models for the "gray-box" fault-detection algorithm that is a component of a diagnostic system known as beacon-based exception analysis for multi-missions (BEAM). POD has been successfully applied in reducing computational complexity by generating simple models that can be used for control and simulation for complex systems such as fluid flows. In the present application to BEAM, POD brings the same benefits to automated diagnosis. BEAM is a method of real-time or offline, automated diagnosis of a complex dynamic system.The gray-box approach makes it possible to utilize incomplete or approximate knowledge of the dynamics of the system that one seeks to diagnose. In the gray-box approach, a deterministic model of the system is used to filter a time series of system sensor data to remove the deterministic components of the time series from further examination. What is left after the filtering operation is a time series of residual quantities that represent the unknown (or at least unmodeled) aspects of the behavior of the system. Stochastic modeling techniques are then applied to the residual time series. The procedure for detecting abnormal behavior of the system then becomes one of looking for statistical differences between the residual time series and the predictions of the stochastic model.
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
Wei Li; Dawu Gu; Xiaoling Xia; Ya Liu; Zhiqiang Liu
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...
Diaz Ledezma, F.
In this paper, we use an extended version of the cardiovascular system\\'s state space model presented by  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.
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
Cornet, Francois; Bourouis, Seid
In 2007, a high frequency monitoring system was deployed in the 1000 m deep AIG10 well that intersects the Aigion fault at a depth of 760 m. This active 15 km long fault is located on the south shore of the Corinth rift, some 40 km east from Patras, in western central Greece. The borehole intersects quaternary sediments down to 495 m, then cretaceous and tertiary heavily tectonized deposits from the Pindos nappe. Below the fault encountered at 760 m, the borehole remains within karstic limestone of the Gavrovo Tripolitza nappe. The monitoring system involved two geophones located some 15 m above the fault, and two hydrophones located respectively at depths equal to 500 m and 250 m. The frequency domain for the data acquisition system ranged from a few Hz to 2500 Hz. The seismic velocity structure close to the borehole was determined through both sonic logs and vertical seismic profiles. This monitoring system has been active during slightly over six months and has recorded signals from microseismic events that occurred in the rift, the location of which was determined thanks to the local 11 stations, three components, short period (2 Hz), monitoring system. In addition, the borehole monitoring system has recorded more than 1000 events not identified with the regional network. Events were precisely correlated with pressure variations associated with two human interventions. These extremely low magnitude events occurred at distances that reached at least up to 1500 m from the well. They were associated, some ten days later, with some local rift activity. A tentative model is proposed that associates local short slip instabilities in the upper part of the fault close to the well, with a longer duration pore pressure diffusion process. Results demonstrate that the Aigion fault is continuously creeping down to a depth at least equal to 5 km but probably deeper.
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.
Niemann, Hans Henrik; Poulsen, Niels Kjølstad
The focus in this paper is on active fault diagnosis (AFD) in closed-loop sampleddata systems. Applying the same AFD architecture as for continuous-time systems does not directly result in the same set of closed-loop matrix transfer functions. For continuous-time systems, the LFT (linear fractional...
Su, Hua; Kim, Yeong-Min; Chong, Kil To
Induction machine is probably the most commonly utilized electromechanical device in modern society. However, there are many undesirable problems arising in the machine operation of industrial plants. It is desirable for early detection and diagnosis of incipient faults for online condition monitoring, product quality assurance, and improved operational efficiency of induction motors. In this paper, a high-performance residual-based novel method is developed for induction machine fault detection, using Fourier-based signal processing for steady-state vibration signals. The proposed approach uses only motor vibration measurements without the nameplate information. The reference model in spectra is obtained statistically to represent the healthy condition. The effectiveness of the proposed approach in detecting a wide range of mechanical and electrical faults is demonstrated through staged motor faults, and it is shown that a robust and reliable induction machine fault detection system has been produced.
Silvia M. Zanoli
Full Text Available The paper illustrates the design and the implementation of a Fault Detection and Isolation (FDI system to a rotary machine like a multishaft centrifugal compressor. A model-free approach, that is, the Principal Component Analysis (PCA, has been employed to solve the fault detection issue. For the fault isolation purpose structured residuals have been adopted while an adaptive threshold has been designed in order to detect and to isolate the faults. To prove the goodness of the proposed FDI system, historical data of a nitrogen centrifugal compressor employed in a refinery plant are considered. Tests results show that detection and isolation of single as well as multiple faults are successfully achieved.
Fogh Odgaard, Peter; Lin, Bao; Jørgensen, Sten Bay
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...
Yong JIANG; Hongguang WANG; Lijin FANG; Mingyang ZHAO
A combined logic- and model-based approach to fault detection and identification (FDI) in a suction foot control system of a wall-climbing robot is presented in this paper. For the control system, some fault models are derived by kinematics analysis. Moreover, the logic relations of the system states are known in advance. First, a fault tree is used to analyze the system by evaluating the basic events (elementary causes), which can lead to a root event (a particular fault). Then, a multiple-model adaptive estimation algorithm is used to detect and identify the model-known faults. Finally, based on the system states of the robot and the results of the estimation, the model-unknown faults are also identified using logical reasoning. Experiments show that the proposed approach based on the combination of logical reasoning and model estimating is efficient in the FDI of the robot.
In this paper we discuss two advanced techniques, process fault detection and nonlinear time series analysis, and apply them to the analysis of vector-valued and single-valued time-series data. We investigate model-based process fault detection methods for analyzing simulated, multivariate, time-series data from a three-tank system. The model-predictions are compared with simulated measurements of the same variables to form residual vectors that are tested for the presence of faults (possible diversions in safeguards terminology). We evaluate two methods, testing all individual residuals with a univariate z-score and testing all variables simultaneously with the Mahalanobis distance, for their ability to detect loss of material from two different leak scenarios from the three-tank system: a leak without and with replacement of the lost volume. Nonlinear time-series analysis tools were compared with the linear methods popularized by Box and Jenkins. We compare prediction results using three nonlinear and two linear modeling methods on each of six simulated time series: two nonlinear and four linear. The nonlinear methods performed better at predicting the nonlinear time series and did as well as the linear methods at predicting the linear values
The paper discusses process fault detection and non-linear time series analysis, which are applied to the analysis for vector-valued and single-valued time series data. Model based process fault detection methods for analysing simulated, multivariate, time series data from a three-tank system are investigated. The model predictions are compared with simulated measurements of the same variables to form residual vectors that are tested for the presence of faults (possible diversions in safeguards terminology). Two methods are evaluated, testing all individual residuals with a univariate z score and testing all variables simultaneously with the Mahalanobis distance, for their ability to detect loss of material from two different leak scenarios from the three-tank system: a leak without replacement and a leak with replacement of the lost volume. Non-linear time series analysis tools have been compared with the linear methods popularized by Box and Jenkins. The paper compares prediction results using three non-linear and two linear modelling methods on each of six simulated time series: two non-linear and four linear time series. The non-linear methods performed better at predicting the non-linear time series and did as well as the linear methods at predicting the linear values. (author). 10 refs, 5 figs, 1 tab
Abd Alla, Ahmed N.
In the present study the Artificial Neural Network (ANN) technique for the detection of (bearing and stator inter turn faults) incipient faults in an induction motor bas been explored. Radial basis function approach has been used for ANN Training and test. Three phase instantaneous currents and angular velocity depending on rotor speed are utilized in proposed approach. An experimental setup is used to implement an online fault defector
Romero-Troncoso, Rene J.; Arturo Garcia-Perez; David Granados-Lieberman; Osornio-Rios, Roque A.; Garcia-Ramirez, Armando G.
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...
Rodrigues, Mickael; THEILLIOL, DIDIER; Adam Medina, Manuel; Sauter, Dominique
In this paper, a fault diagnosis method is developed for systems described by multi- models. The main contribution consists in the design of a new Fault Detection and Isolation scheme (FDI) through an adaptive filter for such systems. Based on the assumption that dynamic behavior of the process is described by a multi-model approach around different operating points, a set of residual is established in order to generate weighting functions robust to faults. These robust weighting functions ar...
Jia Yin; Jiande Wu; Xuyi Yuan; Xiaodong Wang; Yugang Fan
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...
Grauer, Jared A.
A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.
Borchersen, Anders Bech; Kinnaert, Michel
In this work, an early fault detection system for the generator cooling of wind turbines is presented and tested. It relies on a hybrid model of the cooling system. The parameters of the generator model are estimated by an extended Kalman filter. The estimated parameters are then processed by an...... appropriate statistical change detection algorithm in order to detect faults in the cooling system. To validate the method, it has been tested on 3 years of historical data from 43 turbines. During the testing period, 16 faults occurred; 15 of these were detected by the developed method, and one false alarm...... was issued. This is an improvement compared with the current system that gives 15 detections and more than 10 false alarms. In some cases, the method detects the fault a long time before the turbine reports an alarm. A further advantage of the method is that it is based on supervisory control and data...
Poulsen, Niels Kjølstad; Niemann, Hans Henrik
error output from the system. The classical cumulative sum (CUSUM) test will be modified with respect to the AFD approach applied. The CUSUM method will be altered such that it will be able to detect a change in the signature from the auxiliary input signal in an (error) output signal. It will be shown...... how it is possible to apply both the gain and the phase change of the output signal in CUSUM tests. The method is demonstrated using an example....
Yu Liu; Yang Yang; Xiaopeng Lv; Lifeng Wang
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 ...
Odgaard, Peter Fogh; Stoustrup, Jakob
in the gear-box resonance frequency can be detected. Two different time–frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen–Loeve basis. Both of them detect the gear-box fault with an acceptable detection delay of maximum 100s, which...... is neglectable compared with the fault developing time....
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.
Ahmed, M.; Gu, F.; Ball, A. D.
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.
Niemann, Hans Henrik; Poulsen, Niels Kjølstad
Fault detection and isolation, (FDI) of parametric faults in dynamic systems will be considered in this paper. An active fault diagnosis (AFD) approach is applied. The fault diagnosis will be investigated with respect to different information levels from the external inputs to the systems. These...... inputs are disturbance inputs, reference inputs and auxilary inputs. The diagnosis of the system is derived by an evaluation of the signature from the inputs in the residual outputs. The changes of the signatures form the external inputs are used for detection and isolation of the parametric faults....
Niemann, Hans Henrik; Poulsen, Niels Kjølstad
Fault detection and isolation, (FDI) of parametric faults in dynamic systems will be considered in this paper. An active fault diagnosis (AFD) approach is applied. The fault diagnosis will be investigated with respect to different information levels from the external inputs to the systems. These...... inputs are disturbance inputs, reference inputs and auxilary inputs. The diagnosis of the system is derived by an evaluation of the signature from the inputs in the residual outputs. The changes of the signatures form the external inputs are used for detection and isolation of the parametric faults....
Schlechtingen, Meik; Santos, Ilmar
This paper presents the research results of a comparison of three different model based approaches for wind turbine fault detection in online SCADA data, by applying developed models to five real measured faults and anomalies. The regression based model as the simplest approach to build a normal...
Wang, Yuxin; Tian, Yifu; Teixeira, André; Hulstijn, Joris; Tan, Yao-Hua
Currently international supply chains are facing risks concerning faults in compliance, such as altering shipping documentations, fictitious inventory, and inter-company manipulations. In this paper a method to detect and diagnose fault scenarios regarding customs compliance in supply chains is prop
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.
Demetriou, Michael A.
The purpose of this manuscript is to construct natural observers for vector second-order systems by utilising unknown input observer (UIO) methods. This observer is subsequently used for a robust fault detection scheme and also as an adaptive detection scheme for a certain class of actuator faults wherein the time instance and characteristics of an incipient actuator fault are detected. Stability of the adaptive scheme is provided by a parameter-dependent Lyapunov function for second-order systems. Numerical example on a mechanical system describing an automobile suspension system is used to illustrate the theoretical results.
Odgaard, Peter Fogh; Lin, Bao; Jørgensen, Sten Bay
In order to improve the reliability of power plants it is important to detect fault as fast as possible. Doing this it is interesting to find the most efficient method. Since modeling of large scale systems is time consuming it is interesting to compare a model-based method with data driven ones....... In this paper three different fault detection approaches are compared using a example of a coal mill, where a fault emerges. The compared methods are based on: an optimal unknown input observer, static and dynamic regression model-based detections. The conclusion on the comparison is that observer...
The overall objective of this thesis is to develop methods for fault detection and diagnosis for ground source heat pumps that can be used by servicemen to assist them to accurately detect and diagnose faults during the operation of the heat pump. The aim of this thesis is focused to develop two fault detection and diagnosis methods, sensitivity ratio and data-driven using principle component analysis. For the sensitivity ratio method model, two semi-empirical models for heat pump unit were b...
Novelty detection is the identification of deviations from a training set. It is suitable for monitoring the health of mechanical systems where it usually is impossible to know every potential fault. In this paper, two novelty detectors are presented. The first detector which integrates One-Class Support Vector Machine (OCSVM) with an incremental clustering algorithm is designed for health monitoring of the turbopump, while the second one which is trained on sensor fault samples is designed to recognize faults from sensors and faults actually from the turbopump. Analysis results showed that these two detectors are both sensitive and efficient for the health monitoring of the turbopump.
Ladislav Placer; Božo Koler
Establishing recent displacements along faults is an important and delicate task. Larger faults are accompanied by broader fault zones that require a specific approach to geodetic measurements of fault block displacements. The vector of fault block displacements, or resultant, is a vector sum of differential displacements within the fault zone. For the purposes of recording the displacements we propose the stabilization of a geodetic network of points positioned in fault blocks...
Blakely, R. J.; Sherrod, B. L.; Wells, R. E.; Weaver, C. S.
The Puget Lowland, Washington, lies within the Cascadia forearc and is underlain by at least six seismically active and regionally significant crustal faults that together accommodate several mm/yr of net north-south shortening. The surface expression of pre-15-ka slip on Puget Lowland faults has been largely scoured away or covered by glacial deposits, and younger fault geomorphology is often concealed by vegetation and urban development. High-resolution aeromagnetic and lidar surveys, followed by geologic site investigations, have identified and confirmed late Holocene deformation on each of these mostly concealed but potentially hazardous faults. Most geomorphic features identified in lidar data are closely associated with linear magnetic anomalies that reflect the underlying basement structure of the fault and help map its full extent. The southern Whidbey Island fault (SWIF) is a case in point. The northwest-striking SWIF was mapped previously using borehole data and potential-field anomalies on Whidbey Island and marine seismic-reflection surveys beneath surrounding waterways. Gravity inversions and aeromagnetic mapping suggest that the SWIF extends at least 50 km southeast, from Vancouver Island to the Washington mainland, and transitions along its length from northeast-side-down beneath Puget Sound to northeast-side-up on the mainland. Abrupt subsidence at a coastal marsh on south-central Whidbey Island suggests that the SWIF experienced a MW 6.5 to 7.0 earthquake about 3 ka. Southeast of Whidbey Island, a hypothesized southeastward projection of the SWIF makes landfall between the cities of Seattle and Everett. Linear, northwest-striking magnetic anomalies in this mainland region do coincide with this hypothesized projection, are low in amplitude, and are best illuminated in residual magnetic fields. The most prominent of the residual magnetic anomalies extends at least 16 km, lies approximately on strike with the SWIF on Whidbey Island, and passes within
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.