Robust observer-based fault diagnosis for nonlinear systems using Matlab

CERN Document Server

Zhang, Jian; Nguang, Sing Kiong

2016-01-01

This book introduces several observer-based methods, including: • the sliding-mode observer • the adaptive observer • the unknown-input observer and • the descriptor observer method for the problem of fault detection, isolation and estimation, allowing readers to compare and contrast the different approaches. The authors present basic material on Lyapunov stability theory, H¥ control theory, sliding-mode control theory and linear matrix inequality problems in a self-contained and step-by-step manner. Detailed and rigorous mathematical proofs are provided for all the results developed in the text so that readers can quickly gain a good understanding of the material. MATLAB® and Simulink® codes for all the examples, which can be downloaded from http://extras.springer.com, enable students to follow the methods and illustrative examples easily. The systems used in the examples make the book highly relevant to real-world problems in industrial control engineering and include a seventh-order aircraft mod...

Fault diagnosis of an intelligent hydraulic pump based on a nonlinear unknown input observer

Directory of Open Access Journals (Sweden)

Zhonghai MA

2018-02-01

Full Text Available Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system (IHPS based on a nonlinear unknown input observer (NUIO is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS. Keywords: Fault diagnosis, Hydraulic piston pump, Model-based, Nonlinear unknown input observer (NUIO, Residual error

Observer-Based Fault Estimation and Accomodation for Dynamic Systems

CERN Document Server

Zhang, Ke; Shi, Peng

2013-01-01

Due to the increasing security and reliability demand of actual industrial process control systems, the study on fault diagnosis and fault tolerant control of dynamic systems has received considerable attention. Fault accommodation (FA) is one of effective methods that can be used to enhance system stability and reliability, so it has been widely and in-depth investigated and become a hot topic in recent years. Fault detection is used to monitor whether a fault occurs, which is the first step in FA. On the basis of fault detection, fault estimation (FE) is utilized to determine online the magnitude of the fault, which is a very important step because the additional controller is designed using the fault estimate. Compared with fault detection, the design difficulties of FE would increase a lot, so research on FE and accommodation is very challenging. Although there have been advancements reported on FE and accommodation for dynamic systems, the common methods at the present stage have design difficulties, whi...

Observer-based distributed adaptive fault-tolerant containment control of multi-agent systems with general linear dynamics.

Science.gov (United States)

Ye, Dan; Chen, Mengmeng; Li, Kui

2017-11-01

In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Observer-based estimation of stator-winding faults in delta-connected induction motors

DEFF Research Database (Denmark)

Skovemose Kallesøe, Carsten; Izadi-Zamanabadi, Roozbeh; Vadstrup, Pierre

2007-01-01

This paper addresses the subject of interturn short circuit estimation in the stator of a delta-connected induction motor. In this paper, an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved...... in the short circuit, and an expression of the current in the short circuit. Moreover, the currents are made available even though a fault has occurred in the motor. To be able to develop this observer, a model that is particularly suitable for the chosen observer design, is also derived. The effeciency...... of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate interturn short-circuit faults....

Design of neuro fuzzy fault tolerant control using an adaptive observer

International Nuclear Information System (INIS)

Anita, R.; Umamaheswari, B.; Viswanathan, B.

2001-01-01

New methodologies and concepts are developed in the control theory to meet the ever-increasing demands in industrial applications. Fault detection and diagnosis of technical processes have become important in the course of progressive automation in the operation of groups of electric drives. When a group of electric drives is under operation, fault tolerant control becomes complicated. For multiple motors in operation, fault detection and diagnosis might prove to be difficult. Estimation of all states and parameters of all drives is necessary to analyze the actuator and sensor faults. To maintain system reliability, detection and isolation of failures should be performed quickly and accurately, and hardware should be properly integrated. Luenberger full order observer can be used for estimation of the entire states in the system for the detection of actuator and sensor failures. Due to the insensitivity of the Luenberger observer to the system parameter variations, state estimation becomes inaccurate under the varying parameter conditions of the drives. Consequently, the estimation performance deteriorates, resulting in ordinary state observers unsuitable for fault detection technique. Therefore an adaptive observe, which can estimate the system states and parameter and detect the faults simultaneously, is designed in our paper. For a Group of D C drives, there may be parameter variations for some of the drives, and for other drives, there may not be parameter variations depending on load torque, friction, etc. So, estimation of all states and parameters of all drives is carried out using an adaptive observer. If there is any deviation with the estimated values, it is understood that fault has occurred and the nature of the fault, whether sensor fault or actuator fault, is determined by neural fuzzy network, and fault tolerant control is reconfigured. Experimental results with neuro fuzzy system using adaptive observer-based fault tolerant control are good, so as

Aircraft Attitude Distributed Fault-tolerant Control Based on Dynamic Actuator

Directory of Open Access Journals (Sweden)

Zhou Hong-Cheng

2014-09-01

Full Text Available For attitude control system, based on decentralized fault-tolerant control framework, actuators damage and stuck fault detection and identification unit are designed for the flight control system. And observer-based auxiliary system unit is also designed. The auxiliary system implies control surface damage faults and disturbances information. Firstly, we give the attitude control system under actuator stuck, lose of effectiveness, and control surface damages faults. Secondly, a multi-observer is designed for actuator fault detection and identification using a decision-making mechanism to determine current actuator failure modes. Then, an adaptive sliding mode observer is designed for implicit control surface damages and interference information. The reconfigurable controller can achieve fault tolerant using the information of adaptive sliding mode observer. Finally, the simulation results show the effectiveness of the proposed method.

Fault tolerant control based on active fault diagnosis

DEFF Research Database (Denmark)

Niemann, Hans Henrik

2005-01-01

An active fault diagnosis (AFD) method will be considered in this paper in connection with a Fault Tolerant Control (FTC) architecture based on the YJBK parameterization of all stabilizing controllers. The architecture consists of a fault diagnosis (FD) part and a controller reconfiguration (CR......) part. The FTC architecture can be applied for additive faults, parametric faults, and for system structural changes. Only parametric faults will be considered in this paper. The main focus in this paper is on the use of the new approach of active fault diagnosis in connection with FTC. The active fault...... diagnosis approach is based on including an auxiliary input in the system. A fault signature matrix is introduced in connection with AFD, given as the transfer function from the auxiliary input to the residual output. This can be considered as a generalization of the passive fault diagnosis case, where...

Non-Andersonian conjugate strike-slip faults: Observations, theory, and tectonic implications

International Nuclear Information System (INIS)

Yin, A; Taylor, M H

2008-01-01

Formation of conjugate strike-slip faults is commonly explained by the Anderson fault theory, which predicts a X-shaped conjugate fault pattern with an intersection angle of ∼30 degrees between the maximum compressive stress and the faults. However, major conjugate faults in Cenozoic collisional orogens, such as the eastern Alps, western Mongolia, eastern Turkey, northern Iran, northeastern Afghanistan, and central Tibet, contradict the theory in that the conjugate faults exhibit a V-shaped geometry with intersection angles of 60-75 degrees, which is 30-45 degrees greater than that predicted by the Anderson fault theory. In Tibet and Mongolia, geologic observations can rule out bookshelf faulting, distributed deformation, and temporal changes in stress state as explanations for the abnormal fault patterns. Instead, the GPS-determined velocity field across the conjugate fault zones indicate that the fault formation may have been related to Hagen-Poiseuille flow in map view involving the upper crust and possibly the whole lithosphere based on upper mantle seismicity in southern Tibet and basaltic volcanism in Mongolia. Such flow is associated with two coeval and parallel shear zones having opposite shear sense; each shear zone produce a set of Riedel shears, respectively, and together the Riedel shears exhibit the observed non-Andersonian conjugate strike-slip fault pattern. We speculate that the Hagen-Poiseuille flow across the lithosphere that hosts the conjugate strike-slip zones was produced by basal shear traction related to asthenospheric flow, which moves parallel and away from the indented segment of the collisional fronts. The inferred asthenospheric flow pattern below the conjugate strike-slip fault zones is consistent with the magnitude and orientations of seismic anisotropy observed across the Tibetan and Mongolian conjugate fault zones, suggesting a strong coupling between lithospheric deformation and asthenospheric flow. The laterally moving

Non-Andersonian conjugate strike-slip faults: Observations, theory, and tectonic implications

Energy Technology Data Exchange (ETDEWEB)

Yin, A [Department of Earth and Space Sciences and Institute of Geophysics and Planetary Physics, University of California, Los Angeles, Los Angeles, CA 90025-1567 (United States); Taylor, M H [Department of Geology, University of Kansas, 1475 Jayhawk Blvd., Lawrence, KS 66044 (United States)], E-mail: yin@ess.ucla.edu

2008-07-01

Formation of conjugate strike-slip faults is commonly explained by the Anderson fault theory, which predicts a X-shaped conjugate fault pattern with an intersection angle of {approx}30 degrees between the maximum compressive stress and the faults. However, major conjugate faults in Cenozoic collisional orogens, such as the eastern Alps, western Mongolia, eastern Turkey, northern Iran, northeastern Afghanistan, and central Tibet, contradict the theory in that the conjugate faults exhibit a V-shaped geometry with intersection angles of 60-75 degrees, which is 30-45 degrees greater than that predicted by the Anderson fault theory. In Tibet and Mongolia, geologic observations can rule out bookshelf faulting, distributed deformation, and temporal changes in stress state as explanations for the abnormal fault patterns. Instead, the GPS-determined velocity field across the conjugate fault zones indicate that the fault formation may have been related to Hagen-Poiseuille flow in map view involving the upper crust and possibly the whole lithosphere based on upper mantle seismicity in southern Tibet and basaltic volcanism in Mongolia. Such flow is associated with two coeval and parallel shear zones having opposite shear sense; each shear zone produce a set of Riedel shears, respectively, and together the Riedel shears exhibit the observed non-Andersonian conjugate strike-slip fault pattern. We speculate that the Hagen-Poiseuille flow across the lithosphere that hosts the conjugate strike-slip zones was produced by basal shear traction related to asthenospheric flow, which moves parallel and away from the indented segment of the collisional fronts. The inferred asthenospheric flow pattern below the conjugate strike-slip fault zones is consistent with the magnitude and orientations of seismic anisotropy observed across the Tibetan and Mongolian conjugate fault zones, suggesting a strong coupling between lithospheric deformation and asthenospheric flow. The laterally moving

Observability analysis for model-based fault detection and sensor selection in induction motors

International Nuclear Information System (INIS)

Nakhaeinejad, Mohsen; Bryant, Michael D

2011-01-01

Sensors in different types and configurations provide information on the dynamics of a system. For a specific task, the question is whether measurements have enough information or whether the sensor configuration can be changed to improve the performance or to reduce costs. Observability analysis may answer the questions. This paper presents a general algorithm of nonlinear observability analysis with application to model-based diagnostics and sensor selection in three-phase induction motors. A bond graph model of the motor is developed and verified with experiments. A nonlinear observability matrix based on Lie derivatives is obtained from state equations. An observability index based on the singular value decomposition of the observability matrix is obtained. Singular values and singular vectors are used to identify the most and least observable configurations of sensors and parameters. A complex step derivative technique is used in the calculation of Jacobians to improve the computational performance of the observability analysis. The proposed algorithm of observability analysis can be applied to any nonlinear system to select the best configuration of sensors for applications of model-based diagnostics, observer-based controller, or to determine the level of sensor redundancy. Observability analysis on induction motors provides various sensor configurations with corresponding observability indices. Results show the redundancy levels for different sensors, and provide a sensor selection guideline for model-based diagnostics, and for observer-based controllers. The results can also be used for sensor fault detection and to improve the reliability of the system by increasing the redundancy level in measurements

Short-Circuit Fault Tolerant Control of a Wind Turbine Driven Induction Generator Based on Sliding Mode Observers

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Takwa Sellami

2017-10-01

Full Text Available The installed energy production capacity of wind turbines is growing intensely on a global scale, making the reliability of wind turbine subsystems of greater significance. However, many faults like Inter-Turn Short-Circuit (ITSC may affect the turbine generator and quickly lead to a decline in supplied power quality. In this framework, this paper proposes a Sliding Mode Observer (SMO-based Fault Tolerant Control (FTC scheme for Induction Generator (IG-based variable-speed grid-connected wind turbines. First, the dynamic models of the wind turbine subsystems were developed. The control schemes were elaborated based on the Maximum Power Point Tracking (MPPT method and Indirect Rotor Flux Oriented Control (IRFOC method. The grid control was also established by regulating the active and reactive powers. The performance of the wind turbine system and the stability of injected power to the grid were hence analyzed under both healthy and faulty conditions. The robust developed SMO-based Fault Detection and Isolation (FDI scheme was proved to be fast and efficient for ITSC detection and localization.Afterwards, SMO were involved in scheming the FTC technique. Accordingly, simulation results assert the efficacy of the proposed ITSC FTC method for variable-speed wind turbines with faulty IG in protecting the subsystems from damage and ensuring continuous connection of the wind turbine to the grid during ITSC faults, hence maintaining power quality.

Fault detection using (PI) observers

DEFF Research Database (Denmark)

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

1997-01-01

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...

Fault detection for discrete-time LPV systems using interval observers

Science.gov (United States)

Zhang, Zhi-Hui; Yang, Guang-Hong

2017-10-01

This paper is concerned with the fault detection (FD) problem for discrete-time linear parameter-varying systems subject to bounded disturbances. A parameter-dependent FD interval observer is designed based on parameter-dependent Lyapunov and slack matrices. The design method is presented by translating the parameter-dependent linear matrix inequalities (LMIs) into finite ones. In contrast to the existing results based on parameter-independent and diagonal Lyapunov matrices, the derived disturbance attenuation, fault sensitivity and nonnegative conditions lead to less conservative LMI characterisations. Furthermore, without the need to design the residual evaluation functions and thresholds, the residual intervals generated by the interval observers are used directly for FD decision. Finally, simulation results are presented for showing the effectiveness and superiority of the proposed method.

Mesoscopic Structural Observations of Cores from the Chelungpu Fault System, Taiwan Chelungpu-Fault Drilling Project Hole-A, Taiwan

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Hiroki Sone

2007-01-01

Full Text Available Structural characteristics of fault rocks distributed within major fault zones provide basic information in understanding the physical aspects of faulting. Mesoscopic structural observations of the drilledcores from Taiwan Chelungpu-fault Drilling Project Hole-A are reported in this article to describe and reveal the distribution of fault rocks within the Chelungpu Fault System.

Model Based Fault Detection in a Centrifugal Pump Application

DEFF Research Database (Denmark)

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

2006-01-01

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

Observer-Based and Regression Model-Based Detection of Emerging Faults in Coal Mills

DEFF Research Database (Denmark)

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

2006-01-01

In order to improve the reliability of power plants it is important to detect fault as fast as possible. Doing this it is interesting to find the most efficient method. Since modeling of large scale systems is time consuming it is interesting to compare a model-based method with data driven ones....

An Improved Wavelet‐Based Multivariable Fault Detection Scheme

KAUST Repository

Harrou, Fouzi

2017-07-06

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

Fault Features Extraction and Identification based Rolling Bearing Fault Diagnosis

International Nuclear Information System (INIS)

Qin, B; Sun, G D; Zhang L Y; Wang J G; HU, J

2017-01-01

For the fault classification model based on extreme learning machine (ELM), the diagnosis accuracy and stability of rolling bearing is greatly influenced by a critical parameter, which is the number of nodes in hidden layer of ELM. An adaptive adjustment strategy is proposed based on vibrational mode decomposition, permutation entropy, and nuclear kernel extreme learning machine to determine the tunable parameter. First, the vibration signals are measured and then decomposed into different fault feature models based on variation mode decomposition. Then, fault feature of each model is formed to a high dimensional feature vector set based on permutation entropy. Second, the ELM output function is expressed by the inner product of Gauss kernel function to adaptively determine the number of hidden layer nodes. Finally, the high dimension feature vector set is used as the input to establish the kernel ELM rolling bearing fault classification model, and the classification and identification of different fault states of rolling bearings are carried out. In comparison with the fault classification methods based on support vector machine and ELM, the experimental results show that the proposed method has higher classification accuracy and better generalization ability. (paper)

Performance based fault diagnosis

DEFF Research Database (Denmark)

Niemann, Hans Henrik

2002-01-01

Different aspects of fault detection and fault isolation in closed-loop systems are considered. It is shown that using the standard setup known from feedback control, it is possible to formulate fault diagnosis problems based on a performance index in this general standard setup. It is also shown...

Novel neural networks-based fault tolerant control scheme with fault alarm.

Science.gov (United States)

Shen, Qikun; Jiang, Bin; Shi, Peng; Lim, Cheng-Chew

2014-11-01

In this paper, the problem of adaptive active fault-tolerant control for a class of nonlinear systems with unknown actuator fault is investigated. The actuator fault is assumed to have no traditional affine appearance of the system state variables and control input. The useful property of the basis function of the radial basis function neural network (NN), which will be used in the design of the fault tolerant controller, is explored. Based on the analysis of the design of normal and passive fault tolerant controllers, by using the implicit function theorem, a novel NN-based active fault-tolerant control scheme with fault alarm is proposed. Comparing with results in the literature, the fault-tolerant control scheme can minimize the time delay between fault occurrence and accommodation that is called the time delay due to fault diagnosis, and reduce the adverse effect on system performance. In addition, the FTC scheme has the advantages of a passive fault-tolerant control scheme as well as the traditional active fault-tolerant control scheme's properties. Furthermore, the fault-tolerant control scheme requires no additional fault detection and isolation model which is necessary in the traditional active fault-tolerant control scheme. Finally, simulation results are presented to demonstrate the efficiency of the developed techniques.

Centrifugal compressor fault diagnosis based on qualitative simulation and thermal parameters

Science.gov (United States)

Lu, Yunsong; Wang, Fuli; Jia, Mingxing; Qi, Yuanchen

2016-12-01

This paper concerns fault diagnosis of centrifugal compressor based on thermal parameters. An improved qualitative simulation (QSIM) based fault diagnosis method is proposed to diagnose the faults of centrifugal compressor in a gas-steam combined-cycle power plant (CCPP). The qualitative models under normal and two faulty conditions have been built through the analysis of the principle of centrifugal compressor. To solve the problem of qualitative description of the observations of system variables, a qualitative trend extraction algorithm is applied to extract the trends of the observations. For qualitative states matching, a sliding window based matching strategy which consists of variables operating ranges constraints and qualitative constraints is proposed. The matching results are used to determine which QSIM model is more consistent with the running state of system. The correct diagnosis of two typical faults: seal leakage and valve stuck in the centrifugal compressor has validated the targeted performance of the proposed method, showing the advantages of fault roots containing in thermal parameters.

Data-driven fault mechanics: Inferring fault hydro-mechanical properties from in situ observations of injection-induced aseismic slip

Science.gov (United States)

Bhattacharya, P.; Viesca, R. C.

2017-12-01

In the absence of in situ field-scale observations of quantities such as fault slip, shear stress and pore pressure, observational constraints on models of fault slip have mostly been limited to laboratory and/or remote observations. Recent controlled fluid-injection experiments on well-instrumented faults fill this gap by simultaneously monitoring fault slip and pore pressure evolution in situ [Gugleilmi et al., 2015]. Such experiments can reveal interesting fault behavior, e.g., Gugleilmi et al. report fluid-activated aseismic slip followed only subsequently by the onset of micro-seismicity. We show that the Gugleilmi et al. dataset can be used to constrain the hydro-mechanical model parameters of a fluid-activated expanding shear rupture within a Bayesian framework. We assume that (1) pore-pressure diffuses radially outward (from the injection well) within a permeable pathway along the fault bounded by a narrow damage zone about the principal slip surface; (2) pore-pressure increase ativates slip on a pre-stressed planar fault due to reduction in frictional strength (expressed as a constant friction coefficient times the effective normal stress). Owing to efficient, parallel, numerical solutions to the axisymmetric fluid-diffusion and crack problems (under the imposed history of injection), we are able to jointly fit the observed history of pore-pressure and slip using an adaptive Monte Carlo technique. Our hydrological model provides an excellent fit to the pore-pressure data without requiring any statistically significant permeability enhancement due to the onset of slip. Further, for realistic elastic properties of the fault, the crack model fits both the onset of slip and its early time evolution reasonably well. However, our model requires unrealistic fault properties to fit the marked acceleration of slip observed later in the experiment (coinciding with the triggering of microseismicity). Therefore, besides producing meaningful and internally consistent

Observer Based Estimation of Stator Winding Faults in Delta-connected Induction Motors, a LMI Approach

DEFF Research Database (Denmark)

Kallesøe, Carsten; Vadstrup, Pierre; Rasmussen, Henrik

2006-01-01

This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

Science.gov (United States)

Zhao, Kaihui; Li, Peng; Zhang, Changfan; Li, Xiangfei; He, Jing; Lin, Yuliang

2017-12-06

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

Fault tolerant control of wind turbines using unknown input observers

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2012-01-01

This paper presents a scheme for accommodating faults in the rotor and generator speed sensors in a wind turbine. These measured values are important both for the wind turbine controller as well as the supervisory control of the wind turbine. The scheme is based on unknown input observers, which...

Robust Mpc for Actuator–Fault Tolerance Using Set–Based Passive Fault Detection and Active Fault Isolation

Directory of Open Access Journals (Sweden)

Xu Feng

2017-03-01

Full Text Available In this paper, a fault-tolerant control (FTC scheme is proposed for actuator faults, which is built upon tube-based model predictive control (MPC as well as set-based fault detection and isolation (FDI. In the class of MPC techniques, tubebased MPC can effectively deal with system constraints and uncertainties with relatively low computational complexity compared with other robust MPC techniques such as min-max MPC. Set-based FDI, generally considering the worst case of uncertainties, can robustly detect and isolate actuator faults. In the proposed FTC scheme, fault detection (FD is passive by using invariant sets, while fault isolation (FI is active by means of MPC and tubes. The active FI method proposed in this paper is implemented by making use of the constraint-handling ability of MPC to manipulate the bounds of inputs.

Case-Based Fault Diagnostic System

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Nowadays, case-based fault diagnostic (CBFD) systems have become important and widely applied problem solving technologies. They are based on the assumption that “similar faults have similar diagnosis”. On the other hand, CBFD systems still suffer from some limitations. Common ones of them are: (1) failure of CBFD to have the needed diagnosis for the new faults that have no similar cases in the case library. (2) Limited memorization when increasing the number of stored cases in the library. The proposed research introduces incorporating the neural network into the case based system to enable the system to diagnose all the faults. Neural networks have proved their success in the classification and diagnosis problems. The suggested system uses the neural network to diagnose the new faults (cases) that cannot be diagnosed by the traditional CBR diagnostic system. Besides, the proposed system can use the another neural network to control adding and deleting the cases in the library to manage the size of the cases in the case library. However, the suggested system has improved the performance of the case based fault diagnostic system when applied for the motor rolling bearing as a case of study

High-frequency maximum observable shaking map of Italy from fault sources

KAUST Repository

Zonno, Gaetano

2012-03-17

We present a strategy for obtaining fault-based maximum observable shaking (MOS) maps, which represent an innovative concept for assessing deterministic seismic ground motion at a regional scale. Our approach uses the fault sources supplied for Italy by the Database of Individual Seismogenic Sources, and particularly by its composite seismogenic sources (CSS), a spatially continuous simplified 3-D representation of a fault system. For each CSS, we consider the associated Typical Fault, i. e., the portion of the corresponding CSS that can generate the maximum credible earthquake. We then compute the high-frequency (1-50 Hz) ground shaking for a rupture model derived from its associated maximum credible earthquake. As the Typical Fault floats within its CSS to occupy all possible positions of the rupture, the high-frequency shaking is updated in the area surrounding the fault, and the maximum from that scenario is extracted and displayed on a map. The final high-frequency MOS map of Italy is then obtained by merging 8,859 individual scenario-simulations, from which the ground shaking parameters have been extracted. To explore the internal consistency of our calculations and validate the results of the procedure we compare our results (1) with predictions based on the Next Generation Attenuation ground-motion equations for an earthquake of M w 7.1, (2) with the predictions of the official Italian seismic hazard map, and (3) with macroseismic intensities included in the DBMI04 Italian database. We then examine the uncertainties and analyse the variability of ground motion for different fault geometries and slip distributions. © 2012 Springer Science+Business Media B.V.

High-frequency maximum observable shaking map of Italy from fault sources

KAUST Repository

Zonno, Gaetano; Basili, Roberto; Meroni, Fabrizio; Musacchio, Gemma; Mai, Paul Martin; Valensise, Gianluca

2012-01-01

We present a strategy for obtaining fault-based maximum observable shaking (MOS) maps, which represent an innovative concept for assessing deterministic seismic ground motion at a regional scale. Our approach uses the fault sources supplied for Italy by the Database of Individual Seismogenic Sources, and particularly by its composite seismogenic sources (CSS), a spatially continuous simplified 3-D representation of a fault system. For each CSS, we consider the associated Typical Fault, i. e., the portion of the corresponding CSS that can generate the maximum credible earthquake. We then compute the high-frequency (1-50 Hz) ground shaking for a rupture model derived from its associated maximum credible earthquake. As the Typical Fault floats within its CSS to occupy all possible positions of the rupture, the high-frequency shaking is updated in the area surrounding the fault, and the maximum from that scenario is extracted and displayed on a map. The final high-frequency MOS map of Italy is then obtained by merging 8,859 individual scenario-simulations, from which the ground shaking parameters have been extracted. To explore the internal consistency of our calculations and validate the results of the procedure we compare our results (1) with predictions based on the Next Generation Attenuation ground-motion equations for an earthquake of M w 7.1, (2) with the predictions of the official Italian seismic hazard map, and (3) with macroseismic intensities included in the DBMI04 Italian database. We then examine the uncertainties and analyse the variability of ground motion for different fault geometries and slip distributions. © 2012 Springer Science+Business Media B.V.

Subsidence and Fault Displacement Along the Long Point Fault Derived from Continuous GPS Observations (2012-2017)

Science.gov (United States)

Tsibanos, V.; Wang, G.

2017-12-01

The Long Point Fault located in Houston Texas is a complex system of normal faults which causes significant damage to urban infrastructure on both private and public property. This case study focuses on the 20-km long fault using high accuracy continuously operating global positioning satellite (GPS) stations to delineate fault movement over five years (2012 - 2017). The Long Point Fault is the longest active fault in the greater Houston area that damages roads, buried pipes, concrete structures and buildings and creates a financial burden for the city of Houston and the residents who live in close vicinity to the fault trace. In order to monitor fault displacement along the surface 11 permanent and continuously operating GPS stations were installed 6 on the hanging wall and 5 on the footwall. This study is an overview of the GPS observations from 2013 to 2017. GPS positions were processed with both relative (double differencing) and absolute Precise Point Positioning (PPP) techniques. The PPP solutions that are referred to IGS08 reference frame were transformed to the Stable Houston Reference Frame (SHRF16). Our results show no considerable horizontal displacements across the fault, but do show uneven vertical displacement attributed to regional subsidence in the range of (5 - 10 mm/yr). This subsidence can be associated to compaction of silty clays in the Chicot and Evangeline aquifers whose water depths are approximately 50m and 80m below the land surface (bls). These levels are below the regional pre-consolidation head that is about 30 to 40m bls. Recent research indicates subsidence will continue to occur until the aquifer levels reach the pre-consolidation head. With further GPS observations both the Long Point Fault and regional land subsidence can be monitored providing important geological data to the Houston community.

Fault diagnosis and fault-tolerant control based on adaptive control approach

CERN Document Server

Shen, Qikun; Shi, Peng

2017-01-01

This book provides recent theoretical developments in and practical applications of fault diagnosis and fault tolerant control for complex dynamical systems, including uncertain systems, linear and nonlinear systems. Combining adaptive control technique with other control methodologies, it investigates the problems of fault diagnosis and fault tolerant control for uncertain dynamic systems with or without time delay. As such, the book provides readers a solid understanding of fault diagnosis and fault tolerant control based on adaptive control technology. Given its depth and breadth, it is well suited for undergraduate and graduate courses on linear system theory, nonlinear system theory, fault diagnosis and fault tolerant control techniques. Further, it can be used as a reference source for academic research on fault diagnosis and fault tolerant control, and for postgraduates in the field of control theory and engineering. .

Strain Variation along Cimandiri Fault, West Java Based on Continuous and Campaign GPS Observation From 2006-2016

Science.gov (United States)

Safitri, A. A.; Meilano, I.; Gunawan, E.; Abidin, H. Z.; Efendi, J.; Kriswati, E.

2018-03-01

The Cimandiri fault which is running in the direction from Pelabuhan Ratu to Padalarang is the longest fault in West Java with several previous shallow earthquakes in the last 20 years. By using continues and campaign GPS observation from 2006-2016, we obtain the deformation pattern along the fault through the variation of strain tensor. We use the velocity vector of GPS station which is fixed in stable International Terrestrial Reference Frame 2008 to calculate horizontal strain tensor. Least Square Collocation is applied to produce widely dense distributed velocity vector and optimum scale factor for the Least Square Weighting matrix. We find that the strain tensor tend to change from dominantly contraction in the west to dominantly extension to the east of fault. Both the maximum shear strain and dilatation show positive value along the fault and increasing from the west to the east. The findings of strain tensor variation along Cimandiri Fault indicate the post seismic effect of the 2006 Java Earthquake.

UIO-based Fault Diagnosis for Hydraulic Automatic Gauge Control System of Magnesium Sheet Mill

Directory of Open Access Journals (Sweden)

Li-Ping FAN

2014-02-01

Full Text Available Hydraulic automatic gauge control system of magnesium sheet mill is a complex integrated control system, which including mechanical, hydraulic and electrical comprehensive information. The failure rate of AGC system always is high, and its fault reasons are always complex. Based on analyzing the fault of main components of the automatic gauge control system, unknown input observer is used to realize fault diagnosis and isolation. Simulation results show that the fault diagnosis method based on the unknown input observer for the hydraulic automatic gauge control system of magnesium sheet mill is effective.

Cooperative Fault Tolerant Tracking Control for Multiagent Systems: An Intermediate Estimator-Based Approach.

Science.gov (United States)

Zhu, Jun-Wei; Yang, Guang-Hong; Zhang, Wen-An; Yu, Li

2017-10-17

This paper studies the observer based fault tolerant tracking control problem for linear multiagent systems with multiple faults and mismatched disturbances. A novel distributed intermediate estimator based fault tolerant tracking protocol is presented. The leader's input is nonzero and unavailable to the followers. By applying a projection technique, the mismatched disturbances are separated into matched and unmatched components. For each node, a tracking error system is established, for which an intermediate estimator driven by the relative output measurements is constructed to estimate the sensor faults and a combined signal of the leader's input, process faults, and matched disturbance component. Based on the estimation, a fault tolerant tracking protocol is designed to eliminate the effects of the combined signal. Besides, the effect of unmatched disturbance component can be attenuated by directly adjusting some specified parameters. Finally, a simulation example of aircraft demonstrates the effectiveness of the designed tracking protocol.This paper studies the observer based fault tolerant tracking control problem for linear multiagent systems with multiple faults and mismatched disturbances. A novel distributed intermediate estimator based fault tolerant tracking protocol is presented. The leader's input is nonzero and unavailable to the followers. By applying a projection technique, the mismatched disturbances are separated into matched and unmatched components. For each node, a tracking error system is established, for which an intermediate estimator driven by the relative output measurements is constructed to estimate the sensor faults and a combined signal of the leader's input, process faults, and matched disturbance component. Based on the estimation, a fault tolerant tracking protocol is designed to eliminate the effects of the combined signal. Besides, the effect of unmatched disturbance component can be attenuated by directly adjusting some

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

Directory of Open Access Journals (Sweden)

Guillermo Heredia

2011-01-01

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

Empirical Relationships Among Magnitude and Surface Rupture Characteristics of Strike-Slip Faults: Effect of Fault (System) Geometry and Observation Location, Dervided From Numerical Modeling

Science.gov (United States)

Zielke, O.; Arrowsmith, J.

2007-12-01

In order to determine the magnitude of pre-historic earthquakes, surface rupture length, average and maximum surface displacement are utilized, assuming that an earthquake of a specific size will cause surface features of correlated size. The well known Wells and Coppersmith (1994) paper and other studies defined empirical relationships between these and other parameters, based on historic events with independently known magnitude and rupture characteristics. However, these relationships show relatively large standard deviations and they are based only on a small number of events. To improve these first-order empirical relationships, the observation location relative to the rupture extent within the regional tectonic framework should be accounted for. This however cannot be done based on natural seismicity because of the limited size of datasets on large earthquakes. We have developed the numerical model FIMozFric, based on derivations by Okada (1992) to create synthetic seismic records for a given fault or fault system under the influence of either slip- or stress boundary conditions. Our model features A) the introduction of an upper and lower aseismic zone, B) a simple Coulomb friction law, C) bulk parameters simulating fault heterogeneity, and D) a fault interaction algorithm handling the large number of fault patches (typically 5,000-10,000). The joint implementation of these features produces well behaved synthetic seismic catalogs and realistic relationships among magnitude and surface rupture characteristics which are well within the error of the results by Wells and Coppersmith (1994). Furthermore, we use the synthetic seismic records to show that the relationships between magntiude and rupture characteristics are a function of the observation location within the regional tectonic framework. The model presented here can to provide paleoseismologists with a tool to improve magnitude estimates from surface rupture characteristics, by incorporating the

Comparison of Cenozoic Faulting at the Savannah River Site to Fault Characteristics of the Atlantic Coast Fault Province: Implications for Fault Capability

International Nuclear Information System (INIS)

Cumbest, R.J.

2000-01-01

This study compares the faulting observed on the Savannah River Site and vicinity with the faults of the Atlantic Coastal Fault Province and concludes that both sets of faults exhibit the same general characteristics and are closely associated. Based on the strength of this association it is concluded that the faults observed on the Savannah River Site and vicinity are in fact part of the Atlantic Coastal Fault Province. Inclusion in this group means that the historical precedent established by decades of previous studies on the seismic hazard potential for the Atlantic Coastal Fault Province is relevant to faulting at the Savannah River Site. That is, since these faults are genetically related the conclusion of ''not capable'' reached in past evaluations applies.In addition, this study establishes a set of criteria by which individual faults may be evaluated in order to assess their inclusion in the Atlantic Coast Fault Province and the related association of the ''not capable'' conclusion

Real-Time Fault Detection Approach for Nonlinear Systems and its Asynchronous T-S Fuzzy Observer-Based Implementation.

Science.gov (United States)

Li, Linlin; Ding, Steven X; Qiu, Jianbin; Yang, Ying

2017-02-01

This paper is concerned with a real-time observer-based fault detection (FD) approach for a general type of nonlinear systems in the presence of external disturbances. To this end, in the first part of this paper, we deal with the definition and the design condition for an L ∞ / L 2 type of nonlinear observer-based FD systems. This analytical framework is fundamental for the development of real-time nonlinear FD systems with the aid of some well-established techniques. In the second part, we address the integrated design of the L ∞ / L 2 observer-based FD systems by applying Takagi-Sugeno (T-S) fuzzy dynamic modeling technique as the solution tool. This fuzzy observer-based FD approach is developed via piecewise Lyapunov functions, and can be applied to the case that the premise variables of the FD system is nonsynchronous with the premise variables of the fuzzy model of the plant. In the end, a case study on the laboratory setup of three-tank system is given to show the efficiency of the proposed results.

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

DEFF Research Database (Denmark)

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

2012-01-01

advanced fault detection and isolation schemes. In this paper, an observer-based fault detection and isolation method for the cooling system in a liquid-cooled frequency converter on a wind turbine which is built up in a scalar version in the laboratory is presented. A dynamic model of the scale cooling...... system is derived based on energy balance equation. A fault analysis is conducted to determine the severity and occurrence rate of possible component faults and their end effects in the cooling system. A method using unknown input observer is developed in order to detect and isolate the faults based...... on the developed dynamical model. The designed fault detection and isolation algorithm is applied on a set of measured experiment data in which different faults are artificially introduced to the scaled cooling system. The experimental results conclude that the different faults are successfully detected...

Robust Fault Estimation Design for Discrete-Time Nonlinear Systems via A Modified Fuzzy Fault Estimation Observer.

Science.gov (United States)

Xie, Xiang-Peng; Yue, Dong; Park, Ju H

2018-02-01

The paper provides relaxed designs of fault estimation observer for nonlinear dynamical plants in the Takagi-Sugeno form. Compared with previous theoretical achievements, a modified version of fuzzy fault estimation observer is implemented with the aid of the so-called maximum-priority-based switching law. Given each activated switching status, the appropriate group of designed matrices can be provided so as to explore certain key properties of the considered plants by means of introducing a set of matrix-valued variables. Owing to the reason that more abundant information of the considered plants can be updated in due course and effectively exploited for each time instant, the conservatism of the obtained result is less than previous theoretical achievements and thus the main defect of those existing methods can be overcome to some extent in practice. Finally, comparative simulation studies on the classical nonlinear truck-trailer model are given to certify the benefits of the theoretic achievement which is obtained in our study. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Detecting tangential dislocations on planar faults from traction free surface observations

International Nuclear Information System (INIS)

Ionescu, Ioan R; Volkov, Darko

2009-01-01

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

Data-based fault-tolerant control for affine nonlinear systems with actuator faults.

Science.gov (United States)

Xie, Chun-Hua; Yang, Guang-Hong

2016-09-01

This paper investigates the fault-tolerant control (FTC) problem for unknown nonlinear systems with actuator faults including stuck, outage, bias and loss of effectiveness. The upper bounds of stuck faults, bias faults and loss of effectiveness faults are unknown. A new data-based FTC scheme is proposed. It consists of the online estimations of the bounds and a state-dependent function. The estimations are adjusted online to compensate automatically the actuator faults. The state-dependent function solved by using real system data helps to stabilize the system. Furthermore, all signals in the resulting closed-loop system are uniformly bounded and the states converge asymptotically to zero. Compared with the existing results, the proposed approach is data-based. Finally, two simulation examples are provided to show the effectiveness of the proposed approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Active fault diagnosis by controller modification

DEFF Research Database (Denmark)

Stoustrup, Jakob; Niemann, Hans Henrik

2010-01-01

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

Rupture Dynamics and Seismic Radiation on Rough Faults for Simulation-Based PSHA

Science.gov (United States)

Mai, P. M.; Galis, M.; Thingbaijam, K. K. S.; Vyas, J. C.; Dunham, E. M.

2017-12-01

Simulation-based ground-motion predictions may augment PSHA studies in data-poor regions or provide additional shaking estimations, incl. seismic waveforms, for critical facilities. Validation and calibration of such simulation approaches, based on observations and GMPE's, is important for engineering applications, while seismologists push to include the precise physics of the earthquake rupture process and seismic wave propagation in 3D heterogeneous Earth. Geological faults comprise both large-scale segmentation and small-scale roughness that determine the dynamics of the earthquake rupture process and its radiated seismic wavefield. We investigate how different parameterizations of fractal fault roughness affect the rupture evolution and resulting near-fault ground motions. Rupture incoherence induced by fault roughness generates realistic ω-2 decay for high-frequency displacement amplitude spectra. Waveform characteristics and GMPE-based comparisons corroborate that these rough-fault rupture simulations generate realistic synthetic seismogram for subsequent engineering application. Since dynamic rupture simulations are computationally expensive, we develop kinematic approximations that emulate the observed dynamics. Simplifying the rough-fault geometry, we find that perturbations in local moment tensor orientation are important, while perturbations in local source location are not. Thus, a planar fault can be assumed if the local strike, dip, and rake are maintained. The dynamic rake angle variations are anti-correlated with local dip angles. Based on a dynamically consistent Yoffe source-time function, we show that the seismic wavefield of the approximated kinematic rupture well reproduces the seismic radiation of the full dynamic source process. Our findings provide an innovative pseudo-dynamic source characterization that captures fault roughness effects on rupture dynamics. Including the correlations between kinematic source parameters, we present a new

Ontology-Based Method for Fault Diagnosis of Loaders.

Science.gov (United States)

Xu, Feixiang; Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

2018-02-28

This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

Fault zone hydrogeology

Science.gov (United States)

Bense, V. F.; Gleeson, T.; Loveless, S. E.; Bour, O.; Scibek, J.

2013-12-01

Deformation along faults in the shallow crust (research effort of structural geologists and hydrogeologists. However, we find that these disciplines often use different methods with little interaction between them. In this review, we document the current multi-disciplinary understanding of fault zone hydrogeology. We discuss surface- and subsurface observations from diverse rock types from unlithified and lithified clastic sediments through to carbonate, crystalline, and volcanic rocks. For each rock type, we evaluate geological deformation mechanisms, hydrogeologic observations and conceptual models of fault zone hydrogeology. Outcrop observations indicate that fault zones commonly have a permeability structure suggesting they should act as complex conduit-barrier systems in which along-fault flow is encouraged and across-fault flow is impeded. Hydrogeological observations of fault zones reported in the literature show a broad qualitative agreement with outcrop-based conceptual models of fault zone hydrogeology. Nevertheless, the specific impact of a particular fault permeability structure on fault zone hydrogeology can only be assessed when the hydrogeological context of the fault zone is considered and not from outcrop observations alone. To gain a more integrated, comprehensive understanding of fault zone hydrogeology, we foresee numerous synergistic opportunities and challenges for the discipline of structural geology and hydrogeology to co-evolve and address remaining challenges by co-locating study areas, sharing approaches and fusing data, developing conceptual models from hydrogeologic data, numerical modeling, and training interdisciplinary scientists.

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

DEFF Research Database (Denmark)

Li, Hui; Yang, Chao; Hu, Yaogang

2014-01-01

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

Model based fault diagnosis in a centrifugal pump application using structural analysis

DEFF Research Database (Denmark)

Kallesøe, C. S.; Izadi-Zamanabadi, Roozbeh; Rasmussen, Henrik

2004-01-01

A model based approach for fault detection and isolation in a centrifugal pump is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, Analytical Redundant Relations (ARR) and observer designs. Structural considerations on the system are used...

Model Based Fault Diagnosis in a Centrifugal Pump Application using Structural Analysis

DEFF Research Database (Denmark)

Kallesøe, C. S.; Izadi-Zamanabadi, Roozbeh; Rasmussen, Henrik

2004-01-01

A model based approach for fault detection and isolation in a centrifugal pump is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, Analytical Redundant Relations (ARR) and observer designs. Structural considerations on the system are used...

BEAT: A Web-Based Boolean Expression Fault-Based Test Case Generation Tool

Science.gov (United States)

Chen, T. Y.; Grant, D. D.; Lau, M. F.; Ng, S. P.; Vasa, V. R.

2006-01-01

BEAT is a Web-based system that generates fault-based test cases from Boolean expressions. It is based on the integration of our several fault-based test case selection strategies. The generated test cases are considered to be fault-based, because they are aiming at the detection of particular faults. For example, when the Boolean expression is in…

Norm based design of fault detectors

DEFF Research Database (Denmark)

Rank, Mike Lind; Niemann, Hans Henrik

1999-01-01

The design of fault detectors for fault detection and isolation (FDI) in dynamic systems is considered in this paper from a norm based point of view. An analysis of norm based threshold selection is given based on different formulations of FDI problems. Both the nominal FDI problem as well...

Fault Diagnosis and Tolerant Control Using Observer Banks Applied to Continuous Stirred Tank Reactor

Directory of Open Access Journals (Sweden)

Martin F. Pico

2017-04-01

Full Text Available This paper focuses on studying the problem of fault tolerant control (FTC, including a detailed fault detection and diagnosis (FDD module using observer banks which consists of output and unknown input observers applied to a continuous stirred tank reactor (CSTR. The main objective of this paper is to use a FDD module here proposed to estimate the fault in order to apply this result in a FTC system (FTCS, to prevent a lost of of the control system performance. The benefits of the observer bank and fault adaptation here studied are illustrated by numerical simulations which assumes faults in manipulated and measuring elements of the CSTR.

Norm based Threshold Selection for Fault Detectors

DEFF Research Database (Denmark)

Rank, Mike Lind; Niemann, Henrik

1998-01-01

The design of fault detectors for fault detection and isolation (FDI) in dynamic systems is considered from a norm based point of view. An analysis of norm based threshold selection is given based on different formulations of FDI problems. Both the nominal FDI problem as well as the uncertain FDI...... problem are considered. Based on this analysis, a performance index based on norms of the involved transfer functions is given. The performance index allows us also to optimize the structure of the fault detection filter directly...

Dynamic Evolution Of Off-Fault Medium During An Earthquake: A Micromechanics Based Model

Science.gov (United States)

Thomas, M. Y.; Bhat, H. S.

2017-12-01

Geophysical observations show a dramatic drop of seismic wave speeds in the shallow off-fault medium following earthquake ruptures. Seismic ruptures generate, or reactivate, damage around faults that alter the constitutive response of the surrounding medium, which in turn modifies the earthquake itself, the seismic radiation, and the near-fault ground motion. We present a micromechanics based constitutive model that accounts for dynamic evolution of elastic moduli at high-strain rates. We consider 2D in-plane models, with a 1D right lateral fault featuring slip-weakening friction law. The two scenarios studied here assume uniform initial off-fault damage and an observationally motivated exponential decay of initial damage with fault normal distance. Both scenarios produce dynamic damage that is consistent with geological observations. A small difference in initial damage actively impacts the final damage pattern. The second numerical experiment, in particular, highlights the complex feedback that exists between the evolving medium and the seismic event. We show that there is a unique off-fault damage pattern associated with supershear transition of an earthquake rupture that could be potentially seen as a geological signature of this transition. These scenarios presented here underline the importance of incorporating the complex structure of fault zone systems in dynamic models of earthquakes.

Dynamic Evolution Of Off-Fault Medium During An Earthquake: A Micromechanics Based Model

Science.gov (United States)

Thomas, Marion Y.; Bhat, Harsha S.

2018-05-01

Geophysical observations show a dramatic drop of seismic wave speeds in the shallow off-fault medium following earthquake ruptures. Seismic ruptures generate, or reactivate, damage around faults that alter the constitutive response of the surrounding medium, which in turn modifies the earthquake itself, the seismic radiation, and the near-fault ground motion. We present a micromechanics based constitutive model that accounts for dynamic evolution of elastic moduli at high-strain rates. We consider 2D in-plane models, with a 1D right lateral fault featuring slip-weakening friction law. The two scenarios studied here assume uniform initial off-fault damage and an observationally motivated exponential decay of initial damage with fault normal distance. Both scenarios produce dynamic damage that is consistent with geological observations. A small difference in initial damage actively impacts the final damage pattern. The second numerical experiment, in particular, highlights the complex feedback that exists between the evolving medium and the seismic event. We show that there is a unique off-fault damage pattern associated with supershear transition of an earthquake rupture that could be potentially seen as a geological signature of this transition. These scenarios presented here underline the importance of incorporating the complex structure of fault zone systems in dynamic models of earthquakes.

Research on Fault Diagnosis Method Based on Rule Base Neural Network

Directory of Open Access Journals (Sweden)

Zheng Ni

2017-01-01

Full Text Available The relationship between fault phenomenon and fault cause is always nonlinear, which influences the accuracy of fault location. And neural network is effective in dealing with nonlinear problem. In order to improve the efficiency of uncertain fault diagnosis based on neural network, a neural network fault diagnosis method based on rule base is put forward. At first, the structure of BP neural network is built and the learning rule is given. Then, the rule base is built by fuzzy theory. An improved fuzzy neural construction model is designed, in which the calculated methods of node function and membership function are also given. Simulation results confirm the effectiveness of this method.

Study of fault diagnosis software design for complex system based on fault tree

International Nuclear Information System (INIS)

Yuan Run; Li Yazhou; Wang Jianye; Hu Liqin; Wang Jiaqun; Wu Yican

2012-01-01

Complex systems always have high-level reliability and safety requirements, and same does their diagnosis work. As a great deal of fault tree models have been acquired during the design and operation phases, a fault diagnosis method which combines fault tree analysis with knowledge-based technology has been proposed. The prototype of fault diagnosis software has been realized and applied to mobile LIDAR system. (authors)

Active Disturbance Rejection Approach for Robust Fault-Tolerant Control via Observer Assisted Sliding Mode Control

Directory of Open Access Journals (Sweden)

John Cortés-Romero

2013-01-01

Full Text Available This work proposes an active disturbance rejection approach for the establishment of a sliding mode control strategy in fault-tolerant operations. The core of the proposed active disturbance rejection assistance is a Generalized Proportional Integral (GPI observer which is in charge of the active estimation of lumped nonlinear endogenous and exogenous disturbance inputs related to the creation of local sliding regimes with limited control authority. Possibilities are explored for the GPI observer assisted sliding mode control in fault-tolerant schemes. Convincing improvements are presented with respect to classical sliding mode control strategies. As a collateral advantage, the observer-based control architecture offers the possibility of chattering reduction given that a significant part of the control signal is of the continuous type. The case study considers a classical DC motor control affected by actuator faults, parametric failures, and perturbations. Experimental results and comparisons with other established sliding mode controller design methodologies, which validate the proposed approach, are provided.

Fault prediction for nonlinear stochastic system with incipient faults based on particle filter and nonlinear regression.

Science.gov (United States)

Ding, Bo; Fang, Huajing

2017-05-01

This paper is concerned with the fault prediction for the nonlinear stochastic system with incipient faults. Based on the particle filter and the reasonable assumption about the incipient faults, the modified fault estimation algorithm is proposed, and the system state is estimated simultaneously. According to the modified fault estimation, an intuitive fault detection strategy is introduced. Once each of the incipient fault is detected, the parameters of which are identified by a nonlinear regression method. Then, based on the estimated parameters, the future fault signal can be predicted. Finally, the effectiveness of the proposed method is verified by the simulations of the Three-tank system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

Science.gov (United States)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

Sensor Fault Diagnosis Observer for an Electric Vehicle Modeled as a Takagi-Sugeno System

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S. Gómez-Peñate

2018-01-01

Full Text Available A sensor fault diagnosis of an electric vehicle (EV modeled as a Takagi-Sugeno (TS system is proposed. The proposed TS model considers the nonlinearity of the longitudinal velocity of the vehicle and parametric variation induced by the slope of the road; these considerations allow to obtain a mathematical model that represents the vehicle for a wide range of speeds and different terrain conditions. First, a virtual sensor represented by a TS state observer is developed. Sufficient conditions are given by a set of linear matrix inequalities (LMIs that guarantee asymptotic convergence of the TS observer. Second, the work is extended to perform fault detection and isolation based on a generalized observer scheme (GOS. Numerical simulations are presented to show the performance and applicability of the proposed method.

Isotropic events observed with a borehole array in the Chelungpu fault zone, Taiwan.

Science.gov (United States)

Ma, Kuo-Fong; Lin, Yen-Yu; Lee, Shiann-Jong; Mori, Jim; Brodsky, Emily E

2012-07-27

Shear failure is the dominant mode of earthquake-causing rock failure along faults. High fluid pressure can also potentially induce rock failure by opening cavities and cracks, but an active example of this process has not been directly observed in a fault zone. Using borehole array data collected along the low-stress Chelungpu fault zone, Taiwan, we observed several small seismic events (I-type events) in a fluid-rich permeable zone directly below the impermeable slip zone of the 1999 moment magnitude 7.6 Chi-Chi earthquake. Modeling of the events suggests an isotropic, nonshear source mechanism likely associated with natural hydraulic fractures. These seismic events may be associated with the formation of veins and other fluid features often observed in rocks surrounding fault zones and may be similar to artificially induced hydraulic fracturing.

Robust Fault Diagnosis Design for Linear Multiagent Systems with Incipient Faults

Directory of Open Access Journals (Sweden)

Jingping Xia

2015-01-01

Full Text Available The design of a robust fault estimation observer is studied for linear multiagent systems subject to incipient faults. By considering the fact that incipient faults are in low-frequency domain, the fault estimation of such faults is proposed for discrete-time multiagent systems based on finite-frequency technique. Moreover, using the decomposition design, an equivalent conclusion is given. Simulation results of a numerical example are presented to demonstrate the effectiveness of the proposed techniques.

Fuzzy Concurrent Object Oriented Expert System for Fault Diagnosis in 8085 Microprocessor Based System Board

OpenAIRE

Mr.D. V. Kodavade; Dr. Mrs.S.D.Apte

2014-01-01

With the acceptance of artificial intelligence paradigm, a number of successful artificial intelligence systems were created. Fault diagnosis in microprocessor based boards needs lot of empirical knowledge and expertise and is a true artificial intelligence problem. Research on fault diagnosis in microprocessor based system boards using new fuzzy-object oriented approach is presented in this paper. There are many uncertain situations observed during fault diagnosis. These uncertain situations...

Fault tolerant control with torque limitation based on fault mode for ten-phase permanent magnet synchronous motor

Directory of Open Access Journals (Sweden)

Guo Hong

2015-10-01

Full Text Available This paper proposes a novel fault tolerant control with torque limitation based on the fault mode for the ten-phase permanent magnet synchronous motor (PMSM under various open-circuit and short-circuit fault conditions, which includes the optimal torque control and the torque limitation control based on the fault mode. The optimal torque control is adopted to guarantee the ripple-free electromagnetic torque operation for the ten-phase motor system under the post-fault condition. Furthermore, we systematically analyze the load capacity of the ten-phase motor system under different fault modes. And a torque limitation control approach based on the fault mode is proposed, which was not available earlier. This approach is able to ensure the safety operation of the faulted motor system in long operating time without causing the overheat fault. The simulation result confirms that the proposed fault tolerant control for the ten-phase motor system is able to guarantee the ripple-free electromagnetic torque and the safety operation in long operating time under the normal and fault conditions.

Fault detection and fault tolerant control of a smart base isolation system with magneto-rheological damper

International Nuclear Information System (INIS)

Wang, Han; Song, Gangbing

2011-01-01

Fault detection and isolation (FDI) in real-time systems can provide early warnings for faulty sensors and actuator signals to prevent events that lead to catastrophic failures. The main objective of this paper is to develop FDI and fault tolerant control techniques for base isolation systems with magneto-rheological (MR) dampers. Thus, this paper presents a fixed-order FDI filter design procedure based on linear matrix inequalities (LMI). The necessary and sufficient conditions for the existence of a solution for detecting and isolating faults using the H ∞ formulation is provided in the proposed filter design. Furthermore, an FDI-filter-based fuzzy fault tolerant controller (FFTC) for a base isolation structure model was designed to preserve the pre-specified performance of the system in the presence of various unknown faults. Simulation and experimental results demonstrated that the designed filter can successfully detect and isolate faults from displacement sensors and accelerometers while maintaining excellent performance of the base isolation technology under faulty conditions

Grain scale observations of stick-slip dynamics in fluid saturated granular fault gouge

Science.gov (United States)

Johnson, P. A.; Dorostkar, O.; Guyer, R. A.; Marone, C.; Carmeliet, J.

2017-12-01

We are studying granular mechanics during slip. In the present work, we conduct coupled computational fluid dynamics (CFD) and discrete element method (DEM) simulations to study grain scale characteristics of slip instabilities in fluid saturated granular fault gouge. The granular sample is confined with constant normal load (10 MPa), and sheared with constant velocity (0.6 mm/s). This loading configuration is chosen to promote stick-slip dynamics, based on a phase-space study. Fluid is introduced in the beginning of stick phase and characteristics of slip events i.e. macroscopic friction coefficient, kinetic energy and layer thickness are monitored. At the grain scale, we monitor particle coordination number, fluid-particle interaction forces as well as particle and fluid kinetic energy. Our observations show that presence of fluids in a drained granular fault gouge stabilizes the layer in the stick phase and increases the recurrence time. In saturated model, we observe that average particle coordination number reaches higher values compared to dry granular gouge. Upon slip, we observe that a larger portion of the granular sample is mobilized in saturated gouge compared to dry system. We also observe that regions with high particle kinetic energy are correlated with zones of high fluid motion. Our observations highlight that spatiotemporal profile of fluid dynamic pressure affects the characteristics of slip instabilities, increasing macroscopic friction coefficient drop, kinetic energy release and granular layer compaction. We show that numerical simulations help characterize the micromechanics of fault mechanics.

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

DEFF Research Database (Denmark)

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

2012-01-01

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 account...

A Fault Diagnosis Methodology for Gear Pump Based on EEMD and Bayesian Network.

Science.gov (United States)

Liu, Zengkai; Liu, Yonghong; Shan, Hongkai; Cai, Baoping; Huang, Qing

2015-01-01

This paper proposes a fault diagnosis methodology for a gear pump based on the ensemble empirical mode decomposition (EEMD) method and the Bayesian network. Essentially, the presented scheme is a multi-source information fusion based methodology. Compared with the conventional fault diagnosis with only EEMD, the proposed method is able to take advantage of all useful information besides sensor signals. The presented diagnostic Bayesian network consists of a fault layer, a fault feature layer and a multi-source information layer. Vibration signals from sensor measurement are decomposed by the EEMD method and the energy of intrinsic mode functions (IMFs) are calculated as fault features. These features are added into the fault feature layer in the Bayesian network. The other sources of useful information are added to the information layer. The generalized three-layer Bayesian network can be developed by fully incorporating faults and fault symptoms as well as other useful information such as naked eye inspection and maintenance records. Therefore, diagnostic accuracy and capacity can be improved. The proposed methodology is applied to the fault diagnosis of a gear pump and the structure and parameters of the Bayesian network is established. Compared with artificial neural network and support vector machine classification algorithms, the proposed model has the best diagnostic performance when sensor data is used only. A case study has demonstrated that some information from human observation or system repair records is very helpful to the fault diagnosis. It is effective and efficient in diagnosing faults based on uncertain, incomplete information.

Fault Location Based on Synchronized Measurements: A Comprehensive Survey

Science.gov (United States)

Al-Mohammed, A. H.; Abido, M. A.

2014-01-01

This paper presents a comprehensive survey on transmission and distribution fault location algorithms that utilize synchronized measurements. Algorithms based on two-end synchronized measurements and fault location algorithms on three-terminal and multiterminal lines are reviewed. Series capacitors equipped with metal oxide varistors (MOVs), when set on a transmission line, create certain problems for line fault locators and, therefore, fault location on series-compensated lines is discussed. The paper reports the work carried out on adaptive fault location algorithms aiming at achieving better fault location accuracy. Work associated with fault location on power system networks, although limited, is also summarized. Additionally, the nonstandard high-frequency-related fault location techniques based on wavelet transform are discussed. Finally, the paper highlights the area for future research. PMID:24701191

Fault Location Based on Synchronized Measurements: A Comprehensive Survey

Directory of Open Access Journals (Sweden)

A. H. Al-Mohammed

2014-01-01

Full Text Available This paper presents a comprehensive survey on transmission and distribution fault location algorithms that utilize synchronized measurements. Algorithms based on two-end synchronized measurements and fault location algorithms on three-terminal and multiterminal lines are reviewed. Series capacitors equipped with metal oxide varistors (MOVs, when set on a transmission line, create certain problems for line fault locators and, therefore, fault location on series-compensated lines is discussed. The paper reports the work carried out on adaptive fault location algorithms aiming at achieving better fault location accuracy. Work associated with fault location on power system networks, although limited, is also summarized. Additionally, the nonstandard high-frequency-related fault location techniques based on wavelet transform are discussed. Finally, the paper highlights the area for future research.

A Framework-Based Approach for Fault-Tolerant Service Robots

Directory of Open Access Journals (Sweden)

Heejune Ahn

2012-11-01

Full Text Available Recently the component-based approach has become a major trend in intelligent service robot development due to its reusability and productivity. The framework in a component-based system should provide essential services for application components. However, to our knowledge the existing robot frameworks do not yet support fault tolerance service. Moreover, it is often believed that faults can be handled only at the application level. In this paper, by extending the robot framework with the fault tolerance function, we argue that the framework-based fault tolerance approach is feasible and even has many benefits, including that: 1 the system integrators can build fault tolerance applications from non-fault-aware components; 2 the constraints of the components and the operating environment can be considered at the time of integration, which – cannot be anticipated eaily at the time of component development; 3 consistency in system reliability can be obtained even in spite of diverse application component sources. In the proposed construction, we build XML rule files defining the rules for probing and determining the fault conditions of each component, contamination cases from a faulty component, and the possible recovery and safety methods. The rule files are established by a system integrator and the fault manager in the framework controls the fault tolerance process according to the rules. We demonstrate that the fault-tolerant framework can incorporate widely accepted fault tolerance techniques. The effectiveness and real-time performance of the framework-based approach and its techniques are examined by testing an autonomous mobile robot in typical fault scenarios.

An Improved Wavelet‐Based Multivariable Fault Detection Scheme

KAUST Repository

Harrou, Fouzi; Sun, Ying; Madakyaru, Muddu

2017-01-01

Data observed from environmental and engineering processes are usually noisy and correlated in time, which makes the fault detection more difficult as the presence of noise degrades fault detection quality. Multiscale representation of data using

Fault detection and fault-tolerant control for nonlinear systems

CERN Document Server

Li, Linlin

2016-01-01

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

Fault Detection for Automotive Shock Absorber

Science.gov (United States)

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

2015-11-01

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

Multi-link faults localization and restoration based on fuzzy fault set for dynamic optical networks.

Science.gov (United States)

Zhao, Yongli; Li, Xin; Li, Huadong; Wang, Xinbo; Zhang, Jie; Huang, Shanguo

2013-01-28

Based on a distributed method of bit-error-rate (BER) monitoring, a novel multi-link faults restoration algorithm is proposed for dynamic optical networks. The concept of fuzzy fault set (FFS) is first introduced for multi-link faults localization, which includes all possible optical equipment or fiber links with a membership describing the possibility of faults. Such a set is characterized by a membership function which assigns each object a grade of membership ranging from zero to one. OSPF protocol extension is designed for the BER information flooding in the network. The BER information can be correlated to link faults through FFS. Based on the BER information and FFS, multi-link faults localization mechanism and restoration algorithm are implemented and experimentally demonstrated on a GMPLS enabled optical network testbed with 40 wavelengths in each fiber link. Experimental results show that the novel localization mechanism has better performance compared with the extended limited perimeter vector matching (LVM) protocol and the restoration algorithm can improve the restoration success rate under multi-link faults scenario.

Feature-based handling of surface faults in compact disc players

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob; Andersen, Palle

2006-01-01

In this paper a novel method called feature-based control is presented. The method is designed to improve compact disc players’ handling of surface faults on the discs. The method is based on a fault-tolerant control scheme, which uses extracted features of the surface faults to remove those from...... the detector signals used for control during the occurrence of surface faults. The extracted features are coefficients of Karhunen–Loève approximations of the surface faults. The performance of the feature-based control scheme controlling compact disc players playing discs with surface faults has been...... validated experimentally. The proposed scheme reduces the control errors due to the surface faults, and in some cases where the standard fault handling scheme fails, our scheme keeps the CD-player playing....

Model-based fault diagnosis in PEM fuel cell systems

Energy Technology Data Exchange (ETDEWEB)

Escobet, T; de Lira, S; Puig, V; Quevedo, J [Automatic Control Department (ESAII), Universitat Politecnica de Catalunya (UPC), Rambla Sant Nebridi 10, 08222 Terrassa (Spain); Feroldi, D; Riera, J; Serra, M [Institut de Robotica i Informatica Industrial (IRI), Consejo Superior de Investigaciones Cientificas (CSIC), Universitat Politecnica de Catalunya (UPC) Parc Tecnologic de Barcelona, Edifici U, Carrer Llorens i Artigas, 4-6, Planta 2, 08028 Barcelona (Spain)

2009-07-01

In this work, a model-based fault diagnosis methodology for PEM fuel cell systems is presented. The methodology is based on computing residuals, indicators that are obtained comparing measured inputs and outputs with analytical relationships, which are obtained by system modelling. The innovation of this methodology is based on the characterization of the relative residual fault sensitivity. To illustrate the results, a non-linear fuel cell simulator proposed in the literature is used, with modifications, to include a set of fault scenarios proposed in this work. Finally, it is presented the diagnosis results corresponding to these fault scenarios. It is remarkable that with this methodology it is possible to diagnose and isolate all the faults in the proposed set in contrast with other well known methodologies which use the binary signature matrix of analytical residuals and faults. (author)

Information Based Fault Diagnosis

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2008-01-01

Fault detection and isolation, (FDI) of parametric faults in dynamic systems will be considered in this paper. An active fault diagnosis (AFD) approach is applied. The fault diagnosis will be investigated with respect to different information levels from the external inputs to the systems. These ...

Adaptive PCA based fault diagnosis scheme in imperial smelting process.

Science.gov (United States)

Hu, Zhikun; Chen, Zhiwen; Gui, Weihua; Jiang, Bin

2014-09-01

In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

Science.gov (United States)

Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

2016-01-01

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

Nonlinear Model-Based Fault Detection for a Hydraulic Actuator

NARCIS (Netherlands)

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

2011-01-01

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

Entropy-Based Voltage Fault Diagnosis of Battery Systems for Electric Vehicles

Directory of Open Access Journals (Sweden)

Peng Liu

2018-01-01

Full Text Available The battery is a key component and the major fault source in electric vehicles (EVs. Ensuring power battery safety is of great significance to make the diagnosis more effective and predict the occurrence of faults, for the power battery is one of the core technologies of EVs. This paper proposes a voltage fault diagnosis detection mechanism using entropy theory which is demonstrated in an EV with a multiple-cell battery system during an actual operation situation. The preliminary analysis, after collecting and preprocessing the typical data periods from Operation Service and Management Center for Electric Vehicle (OSMC-EV in Beijing, shows that overvoltage fault for Li-ion batteries cell can be observed from the voltage curves. To further locate abnormal cells and predict faults, an entropy weight method is established to calculate the objective weight, which reduces the subjectivity and improves the reliability. The result clearly identifies the abnormity of cell voltage. The proposed diagnostic model can be used for EV real-time diagnosis without laboratory testing methods. It is more effective than traditional methods based on contrastive analysis.

Bearing Fault Classification Based on Conditional Random Field

Directory of Open Access Journals (Sweden)

Guofeng Wang

2013-01-01

Full Text Available Condition monitoring of rolling element bearing is paramount for predicting the lifetime and performing effective maintenance of the mechanical equipment. To overcome the drawbacks of the hidden Markov model (HMM and improve the diagnosis accuracy, conditional random field (CRF model based classifier is proposed. In this model, the feature vectors sequences and the fault categories are linked by an undirected graphical model in which their relationship is represented by a global conditional probability distribution. In comparison with the HMM, the main advantage of the CRF model is that it can depict the temporal dynamic information between the observation sequences and state sequences without assuming the independence of the input feature vectors. Therefore, the interrelationship between the adjacent observation vectors can also be depicted and integrated into the model, which makes the classifier more robust and accurate than the HMM. To evaluate the effectiveness of the proposed method, four kinds of bearing vibration signals which correspond to normal, inner race pit, outer race pit and roller pit respectively are collected from the test rig. And the CRF and HMM models are built respectively to perform fault classification by taking the sub band energy features of wavelet packet decomposition (WPD as the observation sequences. Moreover, K-fold cross validation method is adopted to improve the evaluation accuracy of the classifier. The analysis and comparison under different fold times show that the accuracy rate of classification using the CRF model is higher than the HMM. This method brings some new lights on the accurate classification of the bearing faults.

Risk-based fault detection using Self-Organizing Map

International Nuclear Information System (INIS)

Yu, Hongyang; Khan, Faisal; Garaniya, Vikram

2015-01-01

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

Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis

Directory of Open Access Journals (Sweden)

Jinde Zheng

2014-01-01

Full Text Available A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE, Laplacian score (LS, and support vector machines (SVMs is proposed in this paper. Permutation entropy (PE was recently proposed and defined to measure the randomicity and detect dynamical changes of time series. However, for the complexity of mechanical systems, the randomicity and dynamic changes of the vibration signal will exist in different scales. Thus, the definition of MPE is introduced and employed to extract the nonlinear fault characteristics from the bearing vibration signal in different scales. Besides, the SVM is utilized to accomplish the fault feature classification to fulfill diagnostic procedure automatically. Meanwhile, in order to avoid a high dimension of features, the Laplacian score (LS is used to refine the feature vector by ranking the features according to their importance and correlations with the main fault information. Finally, the rolling bearing fault diagnosis method based on MPE, LS, and SVM is proposed and applied to the experimental data. The experimental data analysis results indicate that the proposed method could identify the fault categories effectively.

Observations on Faults and Associated Permeability Structures in Hydrogeologic Units at the Nevada Test Site

Energy Technology Data Exchange (ETDEWEB)

Prothro, Lance B.; Drellack, Sigmund L.; Haugstad, Dawn N.; Huckins-Gang, Heather E.; Townsend, Margaret J.

2009-03-30

Observational data on Nevada Test Site (NTS) faults were gathered from a variety of sources, including surface and tunnel exposures, core samples, geophysical logs, and down-hole cameras. These data show that NTS fault characteristics and fault zone permeability structures are similar to those of faults studied in other regions. Faults at the NTS form complex and heterogeneous fault zones with flow properties that vary in both space and time. Flow property variability within fault zones can be broken down into four major components that allow for the development of a simplified, first approximation model of NTS fault zones. This conceptual model can be used as a general guide during development and evaluation of groundwater flow and contaminate transport models at the NTS.

Geodetic Finite-Fault-based Earthquake Early Warning Performance for Great Earthquakes Worldwide

Science.gov (United States)

Ruhl, C. J.; Melgar, D.; Grapenthin, R.; Allen, R. M.

2017-12-01

GNSS-based earthquake early warning (EEW) algorithms estimate fault-finiteness and unsaturated moment magnitude for the largest, most damaging earthquakes. Because large events are infrequent, algorithms are not regularly exercised and insufficiently tested on few available datasets. The Geodetic Alarm System (G-larmS) is a GNSS-based finite-fault algorithm developed as part of the ShakeAlert EEW system in the western US. Performance evaluations using synthetic earthquakes offshore Cascadia showed that G-larmS satisfactorily recovers magnitude and fault length, providing useful alerts 30-40 s after origin time and timely warnings of ground motion for onshore urban areas. An end-to-end test of the ShakeAlert system demonstrated the need for GNSS data to accurately estimate ground motions in real-time. We replay real data from several subduction-zone earthquakes worldwide to demonstrate the value of GNSS-based EEW for the largest, most damaging events. We compare predicted ground acceleration (PGA) from first-alert-solutions with those recorded in major urban areas. In addition, where applicable, we compare observed tsunami heights to those predicted from the G-larmS solutions. We show that finite-fault inversion based on GNSS-data is essential to achieving the goals of EEW.

Analytical Model-based Fault Detection and Isolation in Control Systems

DEFF Research Database (Denmark)

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

1998-01-01

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

Model-Based Methods for Fault Diagnosis: Some Guide-Lines

DEFF Research Database (Denmark)

Patton, R.J.; Chen, J.; Nielsen, S.B.

1995-01-01

This paper provides a review of model-based fault diagnosis techniques. Starting from basic principles, the properties.......This paper provides a review of model-based fault diagnosis techniques. Starting from basic principles, the properties....

All Roads Lead to Fault Diagnosis : Model-Based Reasoning with LYDIA

NARCIS (Netherlands)

Feldman, A.B.; Pietersma, J.; Van Gemund, A.J.C.

2006-01-01

Model-Based Reasoning (MBR) over qualitative models of complex, real-world systems has proven succesful for automated fault diagnosis, control, and repair. Expressing a system under diagnosis in a formal model and infering a diagnosis given observations are both challenging problems. In this paper

Fault Detection and Isolation using Eigenstructure Assignment

DEFF Research Database (Denmark)

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

1994-01-01

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

Rule - based Fault Diagnosis Expert System for Wind Turbine

Directory of Open Access Journals (Sweden)

Deng Xiao-Wen

2017-01-01

Full Text Available Under the trend of increasing installed capacity of wind power, the intelligent fault diagnosis of wind turbine is of great significance to the safe and efficient operation of wind farms. Based on the knowledge of fault diagnosis of wind turbines, this paper builds expert system diagnostic knowledge base by using confidence production rules and expert system self-learning method. In Visual Studio 2013 platform, C # language is selected and ADO.NET technology is used to access the database. Development of Fault Diagnosis Expert System for Wind Turbine. The purpose of this paper is to realize on-line diagnosis of wind turbine fault through human-computer interaction, and to improve the diagnostic capability of the system through the continuous improvement of the knowledge base.

Reset Tree-Based Optical Fault Detection

Directory of Open Access Journals (Sweden)

Howon Kim

2013-05-01

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

A Design Method for Fault Reconfiguration and Fault-Tolerant Control of a Servo Motor

Directory of Open Access Journals (Sweden)

Jing He

2013-01-01

Full Text Available A design scheme that integrates fault reconfiguration and fault-tolerant position control is proposed for a nonlinear servo system with friction. Analysis of the non-linear friction torque and fault in the system is used to guide design of a sliding mode position controller. A sliding mode observer is designed to achieve fault reconfiguration based on the equivalence principle. Thus, active fault-tolerant position control of the system can be realized. A real-time simulation experiment is performed on a hardware-in-loop simulation platform. The results show that the system reconfigures well for both incipient and abrupt faults. Under the fault-tolerant control mechanism, the output signal for the system position can rapidly track given values without being influenced by faults.

Bond graph model-based fault diagnosis of hybrid systems

CERN Document Server

Borutzky, Wolfgang

2015-01-01

This book presents a bond graph model-based approach to fault diagnosis in mechatronic systems appropriately represented by a hybrid model. The book begins by giving a survey of the fundamentals of fault diagnosis and failure prognosis, then recalls state-of-art developments referring to latest publications, and goes on to discuss various bond graph representations of hybrid system models, equations formulation for switched systems, and simulation of their dynamic behavior. The structured text: • focuses on bond graph model-based fault detection and isolation in hybrid systems; • addresses isolation of multiple parametric faults in hybrid systems; • considers system mode identification; • provides a number of elaborated case studies that consider fault scenarios for switched power electronic systems commonly used in a variety of applications; and • indicates that bond graph modelling can also be used for failure prognosis. In order to facilitate the understanding of fault diagnosis and the presented...

Fault Diagnosis for Satellite Sensors and Actuators using Nonlinear Geometric Approach and Adaptive Observers

DEFF Research Database (Denmark)

Baldi, P.; Blanke, Mogens; Castaldi, P.

2018-01-01

This paper presents a novel scheme for diagnosis of faults affecting sensors that measure the satellite attitude, body angular velocity, flywheel spin rates, and defects in control torques from reaction wheel motors. The proposed methodology uses adaptive observers to provide fault estimates that...

Experiences of pathways, outcomes and choice after severe traumatic brain injury under no-fault versus fault-based motor accident insurance.

Science.gov (United States)

Harrington, Rosamund; Foster, Michele; Fleming, Jennifer

2015-01-01

To explore experiences of pathways, outcomes and choice after motor vehicle accident (MVA) acquired severe traumatic brain injury (sTBI) under fault-based vs no-fault motor accident insurance (MAI). In-depth qualitative interviews with 10 adults with sTBI and 17 family members examined experiences of pathways, outcomes and choice and how these were shaped by both compensable status and interactions with service providers and service funders under a no-fault and a fault-based MAI scheme. Participants were sampled to provide variation in compensable status, injury severity, time post-injury and metropolitan vs regional residency. Interviews were recorded, transcribed and thematically analysed to identify dominant themes under each scheme. Dominant themes emerging under the no-fault scheme included: (a) rehabilitation-focused pathways; (b) a sense of security; and (c) bounded choices. Dominant themes under the fault-based scheme included: (a) resource-rationed pathways; (b) pressured lives; and (c) unknown choices. Participants under the no-fault scheme experienced superior access to specialist rehabilitation services, greater surety of support and more choice over how rehabilitation and life-time care needs were met. This study provides valuable insights into individual experiences under fault-based vs no-fault MAI. Implications for an injury insurance scheme design to optimize pathways, outcomes and choice after sTBI are discussed.

Spatial clustering and repeating of seismic events observed along the 1976 Tangshan fault, north China

Science.gov (United States)

Li, Le; Chen, Qi-Fu; Cheng, Xin; Niu, Fenglin

2007-12-01

Spatial and temporal features of the seismicity occurring along the Tangshan fault in 2001-2006 were investigated with data recorded by the Beijing metropolitan digital Seismic Network. The relocated seismicity with the double difference method clearly exhibits a dextral bend in the middle of the fault. More than 85% of the earthquakes were found in the two clusters forming the northern segment where relatively small coseismic slips were observed during the 1976 M7.8 earthquake. The b values calculated from the seismicity occurring in the northern and southern segment are 1.03 +/- 0.02 and 0.85 +/- 0.03, respectively. The distinct seismicity and b values are probably the collective effect of the fault geometry and the regional stress field that has an ENE-WSW oriented compression. Using cross-correlation and fine relocation analyses, we also identified a total of 21 doublets and 25 multiplets that make up >50% of the total seismicity. Most of the sequences are aperiodic with recurrence intervals varying from a few minutes to hundreds of days. Based on a quasi-periodic sequence, we obtained a fault slip rate of <=2.6 mm/yr at ~15 km, which is consistent with surface GPS measurements.

Particle Filter Based Fault-tolerant ROV Navigation using Hydro-acoustic Position and Doppler Velocity Measurements

DEFF Research Database (Denmark)

Zhao, Bo; Blanke, Mogens; Skjetne, Roger

2012-01-01

This paper presents a fault tolerant navigation system for a remotely operated vehicle (ROV). The navigation system uses hydro-acoustic position reference (HPR) and Doppler velocity log (DVL) measurements to achieve an integrated navigation. The fault tolerant functionality is based on a modied...... particle lter. This particle lter is able to run in an asynchronous manner to accommodate the measurement drop out problem, and it overcomes the measurement outliers by switching observation models. Simulations with experimental data show that this fault tolerant navigation system can accurately estimate...

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

Directory of Open Access Journals (Sweden)

Yuanchun Li

2015-01-01

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

The Fault Detection, Localization, and Tolerant Operation of Modular Multilevel Converters with an Insulated Gate Bipolar Transistor (IGBT Open Circuit Fault

Directory of Open Access Journals (Sweden)

Wei Li

2018-04-01

Full Text Available Reliability is one of the critical issues for a modular multilevel converter (MMC since it consists of a large number of series-connected power electronics submodules (SMs. In this paper, a complete control strategy including fault detection, localization, and tolerant operation is proposed for the MMC under an insulated gate bipolar transistor (IGBT open circuit fault. According to the output characteristics of the SM with the open-circuit fault of IGBT, a fault detection method based on the circulating current and output current observation is used. In order to further precisely locate the position of the faulty SM, a fault localization method based on the SM capacitor voltage observation is developed. After the faulty SM is isolated, the continuous operation of the converter is ensured by adopting the fault-tolerant strategy based on the use of redundant modules. To verify the proposed fault detection, fault localization, and fault-tolerant operation strategies, a 900 kVA MMC system under the conditions of an IGBT open circuit is developed in the Matlab/Simulink platform. The capabilities of rapid detection, precise positioning, and fault-tolerant operation of the investigated detection and control algorithms are also demonstrated.

A fault-tolerant strategy based on SMC for current-controlled converters

Science.gov (United States)

Azer, Peter M.; Marei, Mostafa I.; Sattar, Ahmed A.

2018-05-01

The sliding mode control (SMC) is used to control variable structure systems such as power electronics converters. This paper presents a fault-tolerant strategy based on the SMC for current-controlled AC-DC converters. The proposed SMC is based on three sliding surfaces for the three legs of the AC-DC converter. Two sliding surfaces are assigned to control the phase currents since the input three-phase currents are balanced. Hence, the third sliding surface is considered as an extra degree of freedom which is utilised to control the neutral voltage. This action is utilised to enhance the performance of the converter during open-switch faults. The proposed fault-tolerant strategy is based on allocating the sliding surface of the faulty leg to control the neutral voltage. Consequently, the current waveform is improved. The behaviour of the current-controlled converter during different types of open-switch faults is analysed. Double switch faults include three cases: two upper switch fault; upper and lower switch fault at different legs; and two switches of the same leg. The dynamic performance of the proposed system is evaluated during healthy and open-switch fault operations. Simulation results exhibit the various merits of the proposed SMC-based fault-tolerant strategy.

ASCS online fault detection and isolation based on an improved MPCA

Science.gov (United States)

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

2014-09-01

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

Fault specific GIS based seismic hazard maps for the Attica region, Greece

Science.gov (United States)

Deligiannakis, G.; Papanikolaou, I. D.; Roberts, G.

2018-04-01

Traditional seismic hazard assessment methods are based on the historical seismic records for the calculation of an annual probability of exceedance for a particular ground motion level. A new fault-specific seismic hazard assessment method is presented, in order to address problems related to the incompleteness and the inhomogeneity of the historical records and to obtain higher spatial resolution of hazard. This method is applied to the region of Attica, which is the most densely populated area in Greece, as nearly half of the country's population lives in Athens and its surrounding suburbs, in the Greater Athens area. The methodology is based on a database of 24 active faults that could cause damage to Attica in case of seismic rupture. This database provides information about the faults slip rates, lengths and expected magnitudes. The final output of the method is four fault-specific seismic hazard maps, showing the recurrence of expected intensities for each locality. These maps offer a high spatial resolution, as they consider the surface geology. Despite the fact that almost half of the Attica region lies on the lowest seismic risk zone according to the official seismic hazard zonation of Greece, different localities have repeatedly experienced strong ground motions during the last 15 kyrs. Moreover, the maximum recurrence for each intensity occurs in different localities across Attica. Highest recurrence for intensity VII (151-156 times over 15 kyrs, or up to a 96 year return period) is observed in the central part of the Athens basin. The maximum intensity VIII recurrence (115 times over 15 kyrs, or up to a 130 year return period) is observed in the western part of Attica, while the maximum intensity IX (73-77/15 kyrs, or a 195 year return period) and X (25-29/15 kyrs, or a 517 year return period) recurrences are observed near the South Alkyonides fault system, which dominates the strong ground motions hazard in the western part of the Attica mainland.

Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty

International Nuclear Information System (INIS)

Purba, Julwan Hendry; Sony Tjahyani, D.T.; Ekariansyah, Andi Sofrany; Tjahjono, Hendro

2015-01-01

Highlights: • Fuzzy probability based fault tree analysis is to evaluate epistemic uncertainty in fuzzy fault tree analysis. • Fuzzy probabilities represent likelihood occurrences of all events in a fault tree. • A fuzzy multiplication rule quantifies epistemic uncertainty of minimal cut sets. • A fuzzy complement rule estimate epistemic uncertainty of the top event. • The proposed FPFTA has successfully evaluated the U.S. Combustion Engineering RPS. - Abstract: A number of fuzzy fault tree analysis approaches, which integrate fuzzy concepts into the quantitative phase of conventional fault tree analysis, have been proposed to study reliabilities of engineering systems. Those new approaches apply expert judgments to overcome the limitation of the conventional fault tree analysis when basic events do not have probability distributions. Since expert judgments might come with epistemic uncertainty, it is important to quantify the overall uncertainties of the fuzzy fault tree analysis. Monte Carlo simulation is commonly used to quantify the overall uncertainties of conventional fault tree analysis. However, since Monte Carlo simulation is based on probability distribution, this technique is not appropriate for fuzzy fault tree analysis, which is based on fuzzy probabilities. The objective of this study is to develop a fuzzy probability based fault tree analysis to overcome the limitation of fuzzy fault tree analysis. To demonstrate the applicability of the proposed approach, a case study is performed and its results are then compared to the results analyzed by a conventional fault tree analysis. The results confirm that the proposed fuzzy probability based fault tree analysis is feasible to propagate and quantify epistemic uncertainties in fault tree analysis

A knowledge-based approach to the evaluation of fault trees

International Nuclear Information System (INIS)

Hwang, Yann-Jong; Chow, Louis R.; Huang, Henry C.

1996-01-01

A list of critical components is useful for determining the potential problems of a complex system. However, to find this list through evaluating the fault trees is expensive and time consuming. This paper intends to propose an integrated software program which consists of a fault tree constructor, a knowledge base, and an efficient algorithm for evaluating minimal cut sets of a large fault tree. The proposed algorithm uses the approaches of top-down heuristic searching and the probability-based truncation. That makes the evaluation of fault trees obviously efficient and provides critical components for solving the potential problems in complex systems. Finally, some practical fault trees are included to illustrate the results

Fault detection and reliability, knowledge based and other approaches

International Nuclear Information System (INIS)

Singh, M.G.; Hindi, K.S.; Tzafestas, S.G.

1987-01-01

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)

Fault Severity Estimation of Rotating Machinery Based on Residual Signals

Directory of Open Access Journals (Sweden)

Fan Jiang

2012-01-01

Full Text Available Fault severity estimation is an important part of a condition-based maintenance system, which can monitor the performance of an operation machine and enhance its level of safety. In this paper, a novel method based on statistical property and residual signals is developed for estimating the fault severity of rotating machinery. The fast Fourier transformation (FFT is applied to extract the so-called multifrequency-band energy (MFBE from the vibration signals of rotating machinery with different fault severity levels in the first stage. Usually these features of the working conditions with different fault sensitivities are different. Therefore a sensitive features-selecting algorithm is defined to construct the feature matrix and calculate the statistic parameter (mean in the second stage. In the last stage, the residual signals computed by the zero space vector are used to estimate the fault severity. Simulation and experimental results reveal that the proposed method based on statistics and residual signals is effective and feasible for estimating the severity of a rotating machine fault.

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

Directory of Open Access Journals (Sweden)

B. S. Anami

2013-06-01

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

Gear-box fault detection using time-frequency based methods

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2015-01-01

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

Online fault detection of permanent magnet demagnetization for IPMSMs by nonsingular fast terminal-sliding-mode observer.

Science.gov (United States)

Zhao, Kai-Hui; Chen, Te-Fang; Zhang, Chang-Fan; He, Jing; Huang, Gang

2014-12-05

To prevent irreversible demagnetization of a permanent magnet (PM) for interior permanent magnet synchronous motors (IPMSMs) by flux-weakening control, a robust PM flux-linkage nonsingular fast terminal-sliding-mode observer (NFTSMO) is proposed to detect demagnetization faults. First, the IPMSM mathematical model of demagnetization is presented. Second, the construction of the NFTSMO to estimate PM demagnetization faults in IPMSM is described, and a proof of observer stability is given. The fault decision criteria and fault-processing method are also presented. Finally, the proposed scheme was simulated using MATLAB/Simulink and implemented on the RT-LAB platform. A number of robustness tests have been carried out. The scheme shows good performance in spite of speed fluctuations, torque ripples and the uncertainties of stator resistance.

State and actuator fault estimation observer design integrated in a riderless bicycle stabilization system.

Science.gov (United States)

Brizuela Mendoza, Jorge Aurelio; Astorga Zaragoza, Carlos Manuel; Zavala Río, Arturo; Pattalochi, Leo; Canales Abarca, Francisco

2016-03-01

This paper deals with an observer design for Linear Parameter Varying (LPV) systems with high-order time-varying parameter dependency. The proposed design, considered as the main contribution of this paper, corresponds to an observer for the estimation of the actuator fault and the system state, considering measurement noise at the system outputs. The observer gains are computed by considering the extension of linear systems theory to polynomial LPV systems, in such a way that the observer reaches the characteristics of LPV systems. As a result, the actuator fault estimation is ready to be used in a Fault Tolerant Control scheme, where the estimated state with reduced noise should be used to generate the control law. The effectiveness of the proposed methodology has been tested using a riderless bicycle model with dependency on the translational velocity v, where the control objective corresponds to the system stabilization towards the upright position despite the variation of v along the closed-loop system trajectories. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Active Fault Detection Based on a Statistical Test

DEFF Research Database (Denmark)

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

2016-01-01

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

Estimation of Stator winding faults in induction motors using an adaptive observer scheme

DEFF Research Database (Denmark)

Kallesøe, C. S.; Vadstrup, P.; Rasmussen, Henrik

2004-01-01

This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....

Estimation of Stator Winding Faults in Induction Motors using an Adaptive Observer Scheme

DEFF Research Database (Denmark)

Kallesøe, C. S.; Vadstrup, P.; Rasmussen, Henrik

2004-01-01

This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....

Safety assessment of automated vehicle functions by simulation-based fault injection

OpenAIRE

Juez, Garazi; Amparan, Estibaliz; Lattarulo, Ray; Rastelli, Joshue Perez; Ruiz, Alejandra; Espinoza, Huascar

2017-01-01

As automated driving vehicles become more sophisticated and pervasive, it is increasingly important to assure its safety even in the presence of faults. This paper presents a simulation-based fault injection approach (Sabotage) aimed at assessing the safety of automated vehicle functions. In particular, we focus on a case study to forecast fault effects during the model-based design of a lateral control function. The goal is to determine the acceptable fault detection interval for pe...

Algorithmic fault tree construction by component-based system modeling

International Nuclear Information System (INIS)

Majdara, Aref; Wakabayashi, Toshio

2008-01-01

Computer-aided fault tree generation can be easier, faster and less vulnerable to errors than the conventional manual fault tree construction. In this paper, a new approach for algorithmic fault tree generation is presented. The method mainly consists of a component-based system modeling procedure an a trace-back algorithm for fault tree synthesis. Components, as the building blocks of systems, are modeled using function tables and state transition tables. The proposed method can be used for a wide range of systems with various kinds of components, if an inclusive component database is developed. (author)

High-frequency imaging of elastic contrast and contact area with implications for naturally observed changes in fault properties

Science.gov (United States)

Nagata, Kohei; Kilgore, Brian D.; Beeler, Nicholas M.; Nakatani, Masao

2014-01-01

During localized slip of a laboratory fault we simultaneously measure the contact area and the dynamic fault normal elastic stiffness. One objective is to determine conditions where stiffness may be used to infer changes in area of contact during sliding on nontransparent fault surfaces. Slip speeds between 0.01 and 10 µm/s and normal stresses between 1 and 2.5 MPa were imposed during velocity step, normal stress step, and slide-hold-slide tests. Stiffness and contact area have a linear interdependence during rate stepping tests and during the hold portion of slide-hold-slide tests. So long as linearity holds, measured fault stiffness can be used on nontransparent materials to infer changes in contact area. However, there are conditions where relations between contact area and stiffness are nonlinear and nonunique. A second objective is to make comparisons between the laboratory- and field-measured changes in fault properties. Time-dependent changes in fault zone normal stiffness made in stress relaxation tests imply postseismic wave speed changes on the order of 0.3% to 0.8% per year in the two or more years following an earthquake; these are smaller than postseismic increases seen within natural damage zones. Based on scaling of the experimental observations, natural postseismic fault normal contraction could be accommodated within a few decimeter wide fault core. Changes in the stiffness of laboratory shear zones exceed 10% per decade and might be detectable in the field postseismically.

Model-Based Fault Diagnosis Techniques Design Schemes, Algorithms and Tools

CERN Document Server

Ding, Steven X

2013-01-01

Guaranteeing a high system performance over a wide operating range is an important issue surrounding the design of automatic control systems with successively increasing complexity. As a key technology in the search for a solution, advanced fault detection and identification (FDI) is receiving considerable attention. This book introduces basic model-based FDI schemes, advanced analysis and design algorithms, and mathematical and control-theoretic tools. This second edition of Model-Based Fault Diagnosis Techniques contains: ·         new material on fault isolation and identification, and fault detection in feedback control loops; ·         extended and revised treatment of systematic threshold determination for systems with both deterministic unknown inputs and stochastic noises; addition of the continuously-stirred tank heater as a representative process-industrial benchmark; and ·         enhanced discussion of residual evaluation in stochastic processes. Model-based Fault Diagno...

The mechanics of fault-bend folding and tear-fault systems in the Niger Delta

Science.gov (United States)

Benesh, Nathan Philip

This dissertation investigates the mechanics of fault-bend folding using the discrete element method (DEM) and explores the nature of tear-fault systems in the deep-water Niger Delta fold-and-thrust belt. In Chapter 1, we employ the DEM to investigate the development of growth structures in anticlinal fault-bend folds. This work was inspired by observations that growth strata in active folds show a pronounced upward decrease in bed dip, in contrast to traditional kinematic fault-bend fold models. Our analysis shows that the modeled folds grow largely by parallel folding as specified by the kinematic theory; however, the process of folding over a broad axial surface zone yields a component of fold growth by limb rotation that is consistent with the patterns observed in natural folds. This result has important implications for how growth structures can he used to constrain slip and paleo-earthquake ages on active blind-thrust faults. In Chapter 2, we expand our DEM study to investigate the development of a wider range of fault-bend folds. We examine the influence of mechanical stratigraphy and quantitatively compare our models with the relationships between fold and fault shape prescribed by the kinematic theory. While the synclinal fault-bend models closely match the kinematic theory, the modeled anticlinal fault-bend folds show robust behavior that is distinct from the kinematic theory. Specifically, we observe that modeled structures maintain a linear relationship between fold shape (gamma) and fault-horizon cutoff angle (theta), rather than expressing the non-linear relationship with two distinct modes of anticlinal folding that is prescribed by the kinematic theory. These observations lead to a revised quantitative relationship for fault-bend folds that can serve as a useful interpretation tool. Finally, in Chapter 3, we examine the 3D relationships of tear- and thrust-fault systems in the western, deep-water Niger Delta. Using 3D seismic reflection data and new

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

Directory of Open Access Journals (Sweden)

Faqi Diao

2016-10-01

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

Fuzzy delay model based fault simulator for crosstalk delay fault test ...

Indian Academy of Sciences (India)

In this paper, a fuzzy delay model based crosstalk delay fault simulator is proposed. As design .... To find the quality of non-robust tests, a fuzzy delay ..... Dubois D and Prade H 1989 Processing Fuzzy temporal knowledge. IEEE Transactions ...

Preliminary paleoseismic observations along the western Denali fault, Alaska

Science.gov (United States)

Koehler, R. D.; Schwartz, D. P.; Rood, D. H.; Reger, R.; Wolken, G. J.

2013-12-01

The Denali fault in south-central Alaska, from Mt. McKinley to the Denali-Totschunda fault branch point, accommodates ~9-12 mm/yr of the right-lateral component of oblique convergence between the Pacific/Yakutat and North American plates. The eastern 226 km of this fault reach was part of the source of the 2002 M7.9 Denali fault earthquake. West of the 2002 rupture there is evidence of two large earthquakes on the Denali fault during the past ~550-700 years but the paleoearthquake chronology prior to this time is largely unknown. To better constrain fault rupture parameters for the western Denali fault and contribute to improved seismic hazard assessment, we performed helicopter and ground reconnaissance along the southern flank of the Alaska Range between the Nenana Glacier and Pyramid Peak, a distance of ~35 km, and conducted a site-specific paleoseismic study. We present a Quaternary geologic strip map along the western Denali fault and our preliminary paleoseismic results, which include a differential-GPS survey of a displaced debris flow fan, cosmogenic 10Be surface exposure ages for boulders on this fan, and an interpretation of a trench across the main trace of the fault at the same site. Between the Nenana Glacier and Pyramid Peak, the Denali fault is characterized by prominent tectonic geomorphic features that include linear side-hill troughs, mole tracks, anastamosing composite scarps, and open left-stepping fissures. Measurements of offset rills and gullies indicate that slip during the most recent earthquake was between ~3 and 5 meters, similar to the average displacement in the 2002 earthquake. At our trench site, ~ 25 km east of the Parks Highway, a steep debris fan is displaced along a series of well-defined left-stepping linear fault traces. Multi-event displacements of debris-flow and snow-avalanche channels incised into the fan range from 8 to 43 m, the latter of which serves as a minimum cumulative fan offset estimate. The trench, excavated into

Track Circuit Fault Diagnosis Method based on Least Squares Support Vector

Science.gov (United States)

Cao, Yan; Sun, Fengru

2018-01-01

In order to improve the troubleshooting efficiency and accuracy of the track circuit, track circuit fault diagnosis method was researched. Firstly, the least squares support vector machine was applied to design the multi-fault classifier of the track circuit, and then the measured track data as training samples was used to verify the feasibility of the methods. Finally, the results based on BP neural network fault diagnosis methods and the methods used in this paper were compared. Results shows that the track fault classifier based on least squares support vector machine can effectively achieve the five track circuit fault diagnosis with less computing time.

Product quality management based on CNC machine fault prognostics and diagnosis

Science.gov (United States)

Kozlov, A. M.; Al-jonid, Kh M.; Kozlov, A. A.; Antar, Sh D.

2018-03-01

This paper presents a new fault classification model and an integrated approach to fault diagnosis which involves the combination of ideas of Neuro-fuzzy Networks (NF), Dynamic Bayesian Networks (DBN) and Particle Filtering (PF) algorithm on a single platform. In the new model, faults are categorized in two aspects, namely first and second degree faults. First degree faults are instantaneous in nature, and second degree faults are evolutional and appear as a developing phenomenon which starts from the initial stage, goes through the development stage and finally ends at the mature stage. These categories of faults have a lifetime which is inversely proportional to a machine tool's life according to the modified version of Taylor’s equation. For fault diagnosis, this framework consists of two phases: the first one is focusing on fault prognosis, which is done online, and the second one is concerned with fault diagnosis which depends on both off-line and on-line modules. In the first phase, a neuro-fuzzy predictor is used to take a decision on whether to embark Conditional Based Maintenance (CBM) or fault diagnosis based on the severity of a fault. The second phase only comes into action when an evolving fault goes beyond a critical threshold limit called a CBM limit for a command to be issued for fault diagnosis. During this phase, DBN and PF techniques are used as an intelligent fault diagnosis system to determine the severity, time and location of the fault. The feasibility of this approach was tested in a simulation environment using the CNC machine as a case study and the results were studied and analyzed.

Efficient fault-ride-through control strategy of DFIG-based wind turbines during the grid faults

International Nuclear Information System (INIS)

Mohammadi, J.; Afsharnia, S.; Vaez-Zadeh, S.

2014-01-01

Highlights: • A comparative review of DFIGs fault-ride-through improvement approaches is presented. • An efficient control strategy is proposed to improve the FRT capability of DFIG. • The rotor overcurrent, DC-link overvoltage and torque oscillations are decreased. • The RSC, DC-link capacitor and mechanical parts are kept safe during the grid faults. • The DFIG remains connected to the grid during the symmetrical and asymmetrical faults. - Abstract: As the penetration of wind power in electrical power system increases, it is necessary that wind turbines remain connected to the grid and contribute to the system stability during and after the grid faults. This paper proposes an efficient control strategy to improve the fault ride through (FRT) capability of doubly fed induction generator (DFIG) during the symmetrical and asymmetrical grid faults. The proposed scheme consists of active and passive FRT compensators. The active compensator is carried out by determining the rotor current references to reduce the rotor over voltages. The passive compensator is based on rotor current limiter (RCL) that considerably reduces the rotor inrush currents at the instants of occurring and clearing the grid faults with deep sags. By applying the proposed strategy, negative effects of the grid faults in the DFIG system including the rotor over currents, electromagnetic torque oscillations and DC-link over voltage are decreased. The system simulation results confirm the effectiveness of the proposed control strategy

Active Fault Detection and Isolation for Hybrid Systems

DEFF Research Database (Denmark)

Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas

2009-01-01

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

EKF-based fault detection for guided missiles flight control system

Science.gov (United States)

Feng, Gang; Yang, Zhiyong; Liu, Yongjin

2017-03-01

The guided missiles flight control system is essential for guidance accuracy and kill probability. It is complicated and fragile. Since actuator faults and sensor faults could seriously affect the security and reliability of the system, fault detection for missiles flight control system is of great significance. This paper deals with the problem of fault detection for the closed-loop nonlinear model of the guided missiles flight control system in the presence of disturbance. First, set up the fault model of flight control system, and then design the residual generation based on the extended Kalman filter (EKF) for the Eulerian-discrete fault model. After that, the Chi-square test was selected for the residual evaluation and the fault detention task for guided missiles closed-loop system was accomplished. Finally, simulation results are provided to illustrate the effectiveness of the approach proposed in the case of elevator fault separately.

Deformation around basin scale normal faults

International Nuclear Information System (INIS)

Spahic, D.

2010-01-01

Faults in the earth crust occur within large range of scales from microscale over mesoscopic to large basin scale faults. Frequently deformation associated with faulting is not only limited to the fault plane alone, but rather forms a combination with continuous near field deformation in the wall rock, a phenomenon that is generally called fault drag. The correct interpretation and recognition of fault drag is fundamental for the reconstruction of the fault history and determination of fault kinematics, as well as prediction in areas of limited exposure or beyond comprehensive seismic resolution. Based on fault analyses derived from 3D visualization of natural examples of fault drag, the importance of fault geometry for the deformation of marker horizons around faults is investigated. The complex 3D structural models presented here are based on a combination of geophysical datasets and geological fieldwork. On an outcrop scale example of fault drag in the hanging wall of a normal fault, located at St. Margarethen, Burgenland, Austria, data from Ground Penetrating Radar (GPR) measurements, detailed mapping and terrestrial laser scanning were used to construct a high-resolution structural model of the fault plane, the deformed marker horizons and associated secondary faults. In order to obtain geometrical information about the largely unexposed master fault surface, a standard listric balancing dip domain technique was employed. The results indicate that for this normal fault a listric shape can be excluded, as the constructed fault has a geologically meaningless shape cutting upsection into the sedimentary strata. This kinematic modeling result is additionally supported by the observation of deformed horizons in the footwall of the structure. Alternatively, a planar fault model with reverse drag of markers in the hanging wall and footwall is proposed. Deformation around basin scale normal faults. A second part of this thesis investigates a large scale normal fault

Wavelet Packet based Detection of Surface Faults on Compact Discs

DEFF Research Database (Denmark)

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

2006-01-01

based on these measurements. A precise detection of the surface fault is a prerequisite to a correct handling of the faults in order to protect the pick-up of the compact disc player from audible track losses. The actual fault handling which is addressed in other publications can be carried out......In this paper the detection of faults on the surface of a compact disc is addressed. Surface faults like scratches and fingerprints disturb the on-line measurement of the pick-up position relative to the track. This is critical since the pick-up is focused on and tracked at the information track...

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding.

Science.gov (United States)

Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

2015-07-06

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches.

Heterogeneity in the Fault Damage Zone: a Field Study on the Borrego Fault, B.C., Mexico

Science.gov (United States)

Ostermeijer, G.; Mitchell, T. M.; Dorsey, M. T.; Browning, J.; Rockwell, T. K.; Aben, F. M.; Fletcher, J. M.; Brantut, N.

2017-12-01

The nature and distribution of damage around faults, and its impacts on fault zone properties has been a hot topic of research over the past decade. Understanding the mechanisms that control the formation of off fault damage can shed light on the processes during the seismic cycle, and the nature of fault zone development. Recent published work has identified three broad zones of damage around most faults based on the type, intensity, and extent of fracturing; Tip, Wall, and Linking damage. Although these zones are able to adequately characterise the general distribution of damage, little has been done to identify the nature of damage heterogeneity within those zones, often simplifying the distribution to fit log-normal linear decay trends. Here, we attempt to characterise the distribution of fractures that make up the wall damage around seismogenic faults. To do so, we investigate an extensive two dimensional fracture network exposed on a river cut platform along the Borrego Fault, BC, Mexico, 5m wide, and extending 20m from the fault core into the damage zone. High resolution fracture mapping of the outcrop, covering scales ranging three orders of magnitude (cm to m), has allowed for detailed observations of the 2D damage distribution within the fault damage zone. Damage profiles were obtained along several 1D transects perpendicular to the fault and micro-damage was examined from thin-sections at various locations around the outcrop for comparison. Analysis of the resulting fracture network indicates heterogeneities in damage intensity at decimetre scales resulting from a patchy distribution of high and low intensity corridors and clusters. Such patchiness may contribute to inconsistencies in damage zone widths defined along 1D transects and the observed variability of fracture densities around decay trends. How this distribution develops with fault maturity and the scaling of heterogeneities above and below the observed range will likely play a key role in

Fault tolerant control for uncertain systems with parametric faults

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2006-01-01

A fault tolerant control (FTC) architecture based on active fault diagnosis (AFD) and the YJBK (Youla, Jarb, Bongiorno and Kucera)parameterization is applied in this paper. Based on the FTC architecture, fault tolerant control of uncertain systems with slowly varying parametric faults...... is investigated. Conditions are given for closed-loop stability in case of false alarms or missing fault detection/isolation....

Fault-tolerant measurement-based quantum computing with continuous-variable cluster states.

Science.gov (United States)

Menicucci, Nicolas C

2014-03-28

A long-standing open question about Gaussian continuous-variable cluster states is whether they enable fault-tolerant measurement-based quantum computation. The answer is yes. Initial squeezing in the cluster above a threshold value of 20.5 dB ensures that errors from finite squeezing acting on encoded qubits are below the fault-tolerance threshold of known qubit-based error-correcting codes. By concatenating with one of these codes and using ancilla-based error correction, fault-tolerant measurement-based quantum computation of theoretically indefinite length is possible with finitely squeezed cluster states.

A simulation training evaluation method for distribution network fault based on radar chart

Directory of Open Access Journals (Sweden)

Yuhang Xu

2018-01-01

Full Text Available In order to solve the problem of automatic evaluation of dispatcher fault simulation training in distribution network, a simulation training evaluation method based on radar chart for distribution network fault is proposed. The fault handling information matrix is established to record the dispatcher fault handling operation sequence and operation information. The four situations of the dispatcher fault isolation operation are analyzed. The fault handling anti-misoperation rule set is established to describe the rules prohibiting dispatcher operation. Based on the idea of artificial intelligence reasoning, the feasibility of dispatcher fault handling is described by the feasibility index. The relevant factors and evaluation methods are discussed from the three aspects of the fault handling result feasibility, the anti-misoperation correctness and the operation process conciseness. The detailed calculation formula is given. Combining the independence and correlation between the three evaluation angles, a comprehensive evaluation method of distribution network fault simulation training based on radar chart is proposed. The method can comprehensively reflect the fault handling process of dispatchers, and comprehensively evaluate the fault handling process from various angles, which has good practical value.

A Model-free Approach to Fault Detection of Continuous-time Systems Based on Time Domain Data

Institute of Scientific and Technical Information of China (English)

Ping Zhang; Steven X. Ding

2007-01-01

In this paper, a model-free approach is presented to design an observer-based fault detection system of linear continuoustime systems based on input and output data in the time domain. The core of the approach is to directly identify parameters of the observer-based residual generator based on a numerically reliable data equation obtained by filtering and sampling the input and output signals.

Fuzzy delay model based fault simulator for crosstalk delay fault test ...

Indian Academy of Sciences (India)

In this paper, a fuzzy delay model based crosstalk delay fault simulator is proposed. As design trends move towards nanometer technologies, more number of new parameters affects the delay of the component. Fuzzy delay models are ideal for modelling the uncertainty found in the design and manufacturing steps.

Spectrum-based Fault Localization in Embedded Software

NARCIS (Netherlands)

Abreu, R.

2009-01-01

Locating software components that are responsible for observed failures is a time-intensive and expensive phase in the software development cycle. Automatic fault localization techniques aid developers/testers in pinpointing the root cause of software failures, as such reducing the debugging effort.

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

Directory of Open Access Journals (Sweden)

Chen Lu

Full Text Available Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

Science.gov (United States)

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery.

Fault detection and isolation in systems with parametric faults

DEFF Research Database (Denmark)

Stoustrup, Jakob; Niemann, Hans Henrik

1999-01-01

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

Model based Fault Detection and Isolation for Driving Motors of a Ground Vehicle

Directory of Open Access Journals (Sweden)

Young-Joon Kim

2016-04-01

Full Text Available This paper proposes model based current sensor and position sensor fault detection and isolation algorithm for driving motor of In-wheel independent drive electric vehicle. From low level perspective, fault diagnosis conducted and analyzed to enhance robustness and stability. Composing state equation of interior permanent magnet synchronous motor (IPMSM, current sensor fault and position sensor fault diagnosed with parity equation. Validation and usefulness of algorithm confirmed based on IPMSM fault occurrence simulation data.

Fault diagnosis of nuclear-powered equipment based on HMM and SVM

International Nuclear Information System (INIS)

Yue Xia; Zhang Chunliang; Zhu Houyao; Quan Yanming

2012-01-01

For the complexity and the small fault samples of nuclear-powered equipment, a hybrid HMM/SVM method was introduced in fault diagnosis. The hybrid method has two steps: first, HMM is utilized for primary diagnosis, in which the range of possible failure is reduced and the state trends can be observed; then faults can be recognized taking the advantage of the generalization ability of SVM. Experiments on the main pump failure simulator show that the HMM/SVM system has a high recognition rate and can be used in the fault diagnosis of nuclear-powered equipment. (authors)

A New Acoustic Emission Sensor Based Gear Fault Detection Approach

Directory of Open Access Journals (Sweden)

Junda Zhu

2013-01-01

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

Postseismic relaxation along the San Andreas fault at Parkfield from continuous seismological observations.

Science.gov (United States)

Brenguier, F; Campillo, M; Hadziioannou, C; Shapiro, N M; Nadeau, R M; Larose, E

2008-09-12

Seismic velocity changes and nonvolcanic tremor activity in the Parkfield area in California reveal that large earthquakes induce long-term perturbations of crustal properties in the San Andreas fault zone. The 2003 San Simeon and 2004 Parkfield earthquakes both reduced seismic velocities that were measured from correlations of the ambient seismic noise and induced an increased nonvolcanic tremor activity along the San Andreas fault. After the Parkfield earthquake, velocity reduction and nonvolcanic tremor activity remained elevated for more than 3 years and decayed over time, similarly to afterslip derived from GPS (Global Positioning System) measurements. These observations suggest that the seismic velocity changes are related to co-seismic damage in the shallow layers and to deep co-seismic stress change and postseismic stress relaxation within the San Andreas fault zone.

Summary: beyond fault trees to fault graphs

International Nuclear Information System (INIS)

Alesso, H.P.; Prassinos, P.; Smith, C.F.

1984-09-01

Fault Graphs are the natural evolutionary step over a traditional fault-tree model. A Fault Graph is a failure-oriented directed graph with logic connectives that allows cycles. We intentionally construct the Fault Graph to trace the piping and instrumentation drawing (P and ID) of the system, but with logical AND and OR conditions added. Then we evaluate the Fault Graph with computer codes based on graph-theoretic methods. Fault Graph computer codes are based on graph concepts, such as path set (a set of nodes traveled on a path from one node to another) and reachability (the complete set of all possible paths between any two nodes). These codes are used to find the cut-sets (any minimal set of component failures that will fail the system) and to evaluate the system reliability

Fault tolerant system based on IDDQ testing

Science.gov (United States)

Guibane, Badi; Hamdi, Belgacem; Mtibaa, Abdellatif; Bensalem, Brahim

2018-06-01

Offline test is essential to ensure good manufacturing quality. However, for permanent or transient faults that occur during the use of the integrated circuit in an application, an online integrated test is needed as well. This procedure should ensure the detection and possibly the correction or the masking of these faults. This requirement of self-correction is sometimes necessary, especially in critical applications that require high security such as automotive, space or biomedical applications. We propose a fault-tolerant design for analogue and mixed-signal design complementary metal oxide (CMOS) circuits based on the quiescent current supply (IDDQ) testing. A defect can cause an increase in current consumption. IDDQ testing technique is based on the measurement of power supply current to distinguish between functional and failed circuits. The technique has been an effective testing method for detecting physical defects such as gate-oxide shorts, floating gates (open) and bridging defects in CMOS integrated circuits. An architecture called BICS (Built In Current Sensor) is used for monitoring the supply current (IDDQ) of the connected integrated circuit. If the measured current is not within the normal range, a defect is signalled and the system switches connection from the defective to a functional integrated circuit. The fault-tolerant technique is composed essentially by a double mirror built-in current sensor, allowing the detection of abnormal current consumption and blocks allowing the connection to redundant circuits, if a defect occurs. Spices simulations are performed to valid the proposed design.

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

Directory of Open Access Journals (Sweden)

Fei Song

2014-01-01

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

TWT transmitter fault prediction based on ANFIS

Science.gov (United States)

Li, Mengyan; Li, Junshan; Li, Shuangshuang; Wang, Wenqing; Li, Fen

2017-11-01

Fault prediction is an important component of health management, and plays an important role in the reliability guarantee of complex electronic equipments. Transmitter is a unit with high failure rate. The cathode performance of TWT is a common fault of transmitter. In this dissertation, a model based on a set of key parameters of TWT is proposed. By choosing proper parameters and applying adaptive neural network training model, this method, combined with analytic hierarchy process (AHP), has a certain reference value for the overall health judgment of TWT transmitters.

Crustal Deformation across the Jericho Valley Section of the Dead Sea Fault as Resolved by Detailed Field and Geodetic Observations

Science.gov (United States)

Hamiel, Yariv; Piatibratova, Oksana; Mizrahi, Yaakov; Nahmias, Yoav; Sagy, Amir

2018-04-01

Detailed field and geodetic observations of crustal deformation across the Jericho Fault section of the Dead Sea Fault are presented. New field observations reveal several slip episodes that rupture the surface, consist with strike slip and extensional deformation along a fault zone width of about 200 m. Using dense Global Positioning System measurements, we obtain the velocities of new stations across the fault. We find that this section is locked for strike-slip motion with a locking depth of 16.6 ± 7.8 km and a slip rate of 4.8 ± 0.7 mm/year. The Global Positioning System measurements also indicate asymmetrical extension at shallow depths of the Jericho Fault section, between 0.3 and 3 km. Finally, our results suggest the vast majority of the sinistral slip along the Dead Sea Fault in southern Jorden Valley is accommodated by the Jericho Fault section.

Fault diagnosis of power transformer based on fault-tree analysis (FTA)

Science.gov (United States)

Wang, Yongliang; Li, Xiaoqiang; Ma, Jianwei; Li, SuoYu

2017-05-01

Power transformers is an important equipment in power plants and substations, power distribution transmission link is made an important hub of power systems. Its performance directly affects the quality and health of the power system reliability and stability. This paper summarizes the five parts according to the fault type power transformers, then from the time dimension divided into three stages of power transformer fault, use DGA routine analysis and infrared diagnostics criterion set power transformer running state, finally, according to the needs of power transformer fault diagnosis, by the general to the section by stepwise refinement of dendritic tree constructed power transformer fault

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

Directory of Open Access Journals (Sweden)

Byung Eun Lee

2014-09-01

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

Active Fault-Tolerant Control for Wind Turbine with Simultaneous Actuator and Sensor Faults

Directory of Open Access Journals (Sweden)

Lei Wang

2017-01-01

Full Text Available The purpose of this paper is to show a novel fault-tolerant tracking control (FTC strategy with robust fault estimation and compensating for simultaneous actuator sensor faults. Based on the framework of fault-tolerant control, developing an FTC design method for wind turbines is a challenge and, thus, they can tolerate simultaneous pitch actuator and pitch sensor faults having bounded first time derivatives. The paper’s key contribution is proposing a descriptor sliding mode method, in which for establishing a novel augmented descriptor system, with which we can estimate the state of system and reconstruct fault by designing descriptor sliding mode observer, the paper introduces an auxiliary descriptor state vector composed by a system state vector, actuator fault vector, and sensor fault vector. By the optimized method of LMI, the conditions for stability that estimated error dynamics are set up to promote the determination of the parameters designed. With this estimation, and designing a fault-tolerant controller, the system’s stability can be maintained. The effectiveness of the design strategy is verified by implementing the controller in the National Renewable Energy Laboratory’s 5-MW nonlinear, high-fidelity wind turbine model (FAST and simulating it in MATLAB/Simulink.

MgB2-based superconductors for fault current limiters

Science.gov (United States)

Sokolovsky, V.; Prikhna, T.; Meerovich, V.; Eisterer, M.; Goldacker, W.; Kozyrev, A.; Weber, H. W.; Shapovalov, A.; Sverdun, V.; Moshchil, V.

2017-02-01

A promising solution of the fault current problem in power systems is the application of fast-operating nonlinear superconducting fault current limiters (SFCLs) with the capability of rapidly increasing their impedance, and thus limiting high fault currents. We report the results of experiments with models of inductive (transformer type) SFCLs based on the ring-shaped bulk MgB2 prepared under high quasihydrostatic pressure (2 GPa) and by hot pressing technique (30 MPa). It was shown that the SFCLs meet the main requirements to fault current limiters: they possess low impedance in the nominal regime of the protected circuit and can fast increase their impedance limiting both the transient and the steady-state fault currents. The study of quenching currents of MgB2 rings (SFCL activation current) and AC losses in the rings shows that the quenching current density and critical current density determined from AC losses can be 10-20 times less than the critical current determined from the magnetization experiments.

Analysis of large fault trees based on functional decomposition

International Nuclear Information System (INIS)

Contini, Sergio; Matuzas, Vaidas

2011-01-01

With the advent of the Binary Decision Diagrams (BDD) approach in fault tree analysis, a significant enhancement has been achieved with respect to previous approaches, both in terms of efficiency and accuracy of the overall outcome of the analysis. However, the exponential increase of the number of nodes with the complexity of the fault tree may prevent the construction of the BDD. In these cases, the only way to complete the analysis is to reduce the complexity of the BDD by applying the truncation technique, which nevertheless implies the problem of estimating the truncation error or upper and lower bounds of the top-event unavailability. This paper describes a new method to analyze large coherent fault trees which can be advantageously applied when the working memory is not sufficient to construct the BDD. It is based on the decomposition of the fault tree into simpler disjoint fault trees containing a lower number of variables. The analysis of each simple fault tree is performed by using all the computational resources. The results from the analysis of all simpler fault trees are re-combined to obtain the results for the original fault tree. Two decomposition methods are herewith described: the first aims at determining the minimal cut sets (MCS) and the upper and lower bounds of the top-event unavailability; the second can be applied to determine the exact value of the top-event unavailability. Potentialities, limitations and possible variations of these methods will be discussed with reference to the results of their application to some complex fault trees.

Analysis of large fault trees based on functional decomposition

Energy Technology Data Exchange (ETDEWEB)

Contini, Sergio, E-mail: sergio.contini@jrc.i [European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen, 21020 Ispra (Italy); Matuzas, Vaidas [European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen, 21020 Ispra (Italy)

2011-03-15

With the advent of the Binary Decision Diagrams (BDD) approach in fault tree analysis, a significant enhancement has been achieved with respect to previous approaches, both in terms of efficiency and accuracy of the overall outcome of the analysis. However, the exponential increase of the number of nodes with the complexity of the fault tree may prevent the construction of the BDD. In these cases, the only way to complete the analysis is to reduce the complexity of the BDD by applying the truncation technique, which nevertheless implies the problem of estimating the truncation error or upper and lower bounds of the top-event unavailability. This paper describes a new method to analyze large coherent fault trees which can be advantageously applied when the working memory is not sufficient to construct the BDD. It is based on the decomposition of the fault tree into simpler disjoint fault trees containing a lower number of variables. The analysis of each simple fault tree is performed by using all the computational resources. The results from the analysis of all simpler fault trees are re-combined to obtain the results for the original fault tree. Two decomposition methods are herewith described: the first aims at determining the minimal cut sets (MCS) and the upper and lower bounds of the top-event unavailability; the second can be applied to determine the exact value of the top-event unavailability. Potentialities, limitations and possible variations of these methods will be discussed with reference to the results of their application to some complex fault trees.

A seismic fault recognition method based on ant colony optimization

Science.gov (United States)

Chen, Lei; Xiao, Chuangbai; Li, Xueliang; Wang, Zhenli; Huo, Shoudong

2018-05-01

Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results.

Self-sealing Faults in the Opalinus Clay - Evidence from Field Observations, Hydraulic Testing and Pore water Chemistry

International Nuclear Information System (INIS)

Gautschi, Andreas

2001-01-01

As part of the Swiss programme for high-level radioactive-waste, the National Cooperative for the Disposal of Radioactive Waste (Nagra) is currently investigating the Jurassic (Aalenian) Opalinus Clay as a potential host formation (Nagra 1988, 1994). The Opalinus Clay consists of indurated dark grey micaceous Clay-stones (shales) that are subdivided into several litho-stratigraphic units. Some of them contain thin sandy lenses, limestone concretions or siderite nodules. The clay mineral content ranges from 40-80 weight per cent (9-29% illite, 3-10% chlorite, 6-20% kaolinite and 4-22% illite/smectite mixed layers in the ratio 70/30). Other minerals are quartz (15-30%), calcite (6-40%), siderite (2-3%), ankerite (0-3%), feldspars (1-7%), pyrite (1-3%) and organic carbon (<1%). The total water content ranges from 4-19% (Mazurek 1999, Nagra 2001). Faults are mainly represented by fault gouge and fault breccias, partly associated with minor veins of calcite. A key question in safety assessment is, whether these faults may represent preferential pathways for radionuclide transport. An extensive hydrogeological data base - part of which derives from strongly tectonized geological environments - suggests that advective transport through faults in the Opalinus Clay at depth > 200 m is insignificant. This conclusion is also supported by independent evidence from clay pore water hydrochemical and isotopic data. The lack of hydrochemical anomalies and the lack of extensive mineral veining suggest that there was also no significant paleo-flow through such faults. These observations can only be reconciled with a strong self-sealing capacity of the faults. Therefore it is concluded, that reactivated existing faults or newly induced fractures will not act as pathways for significant fluid flow at anytime due to self-healing processes. These conclusions are supported by results from laboratory hydro-frac and flow-through tests, and from field-tests in the Mont Terri underground

Coseismic and postseismic motion of a landslide: Observations, modeling, and analogy with tectonic faults

Science.gov (United States)

Lacroix, P.; Perfettini, H.; Taipe, E.; Guillier, B.

2014-10-01

We document the first time series of a landslide reactivation by an earthquake using continuous GPS measurements over the Maca landslide (Peru). Our survey shows a coseismic response of the landslide of about 2 cm, followed by a relaxation period of 5 weeks during which postseismic slip is 3 times greater than the coseismic displacement itself. Our results confirm the coseismic activation of landslides and provide the first observation of a postseismic displacement. These observations are consistent with a mechanical model where slip on the landslide basal interface is governed by rate and state friction, analogous to the mechanics of creeping tectonic faults, opening new perspectives to study the mechanics of landslides and active faults.

Delineation of fault systems on Langeland, Denmark based on AEM data and boreholes

DEFF Research Database (Denmark)

Andersen, Theis Raaschou; Westergaard, Joakim Hollenbo; Pytlich, Anders

in the fault systems can be observed in the AEM data as a low resistivity layer that clearly distinguish from the underlying and surrounding high resistivity fresh water saturated limestone (footwall block) and the overlying glacial clay till. Soil descriptions from a borehole confirm that the low resistivity...... with boreholes, three fault systems in the northern part of the island of Langeland, Denmark are mapped. Two of the fault systems were unknown prior to the mapping campaign. The two unknown fault systems are interpreted as a normal fault and graben structures, respectively. The presence of the hanging-wall block...

Fault diagnosis based on controller modification

DEFF Research Database (Denmark)

Niemann, Hans Henrik

2015-01-01

Detection and isolation of parametric faults in closed-loop systems will be considered in this paper. A major problem is that a feedback controller will in general reduce the effects from variations in the systems including parametric faults on the controlled output from the system. Parametric...... faults can be detected and isolated using active methods, where an auxiliary input is applied. Using active methods for the diagnosis of parametric faults in closed-loop systems, the amplitude of the applied auxiliary input need to be increased to be able to detect and isolate the faults in a reasonable......-parameterization (after Youla, Jabr, Bongiorno and Kucera) for the controller, it is possible to modify the feedback controller with a minor effect on the closed-loop performance in the fault-free case and at the same time optimize the detection and isolation in a faulty case. Controller modification in connection...

Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

Science.gov (United States)

Xiao, Lingfei; Du, Yanbin; Hu, Jixiang; Jiang, Bin

2018-03-01

In this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.

A Model of Intelligent Fault Diagnosis of Power Equipment Based on CBR

Directory of Open Access Journals (Sweden)

Gang Ma

2015-01-01

Full Text Available Nowadays the demand of power supply reliability has been strongly increased as the development within power industry grows rapidly. Nevertheless such large demand requires substantial power grid to sustain. Therefore power equipment’s running and testing data which contains vast information underpins online monitoring and fault diagnosis to finally achieve state maintenance. In this paper, an intelligent fault diagnosis model for power equipment based on case-based reasoning (IFDCBR will be proposed. The model intends to discover the potential rules of equipment fault by data mining. The intelligent model constructs a condition case base of equipment by analyzing the following four categories of data: online recording data, history data, basic test data, and environmental data. SVM regression analysis was also applied in mining the case base so as to further establish the equipment condition fingerprint. The running data of equipment can be diagnosed by such condition fingerprint to detect whether there is a fault or not. Finally, this paper verifies the intelligent model and three-ratio method based on a set of practical data. The resulting research demonstrates that this intelligent model is more effective and accurate in fault diagnosis.

Naive Bayes Bearing Fault Diagnosis Based on Enhanced Independence of Data.

Science.gov (United States)

Zhang, Nannan; Wu, Lifeng; Yang, Jing; Guan, Yong

2018-02-05

The bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Data-based bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not completely independent, which reduces the performance of NB algorithms. In order to solve this problem, we propose a NB bearing fault diagnosis method based on enhanced independence of data. The method deals with data vector from two aspects: the attribute feature and the sample dimension. After processing, the classification limitation of NB is reduced by the independence hypothesis. First, we extract the statistical characteristics of the original signal of the bearings effectively. Then, the Decision Tree algorithm is used to select the important features of the time domain signal, and the low correlation features is selected. Next, the Selective Support Vector Machine (SSVM) is used to prune the dimension data and remove redundant vectors. Finally, we use NB to diagnose the fault with the low correlation data. The experimental results show that the independent enhancement of data is effective for bearing fault diagnosis.

Naive Bayes Bearing Fault Diagnosis Based on Enhanced Independence of Data

Science.gov (United States)

Zhang, Nannan; Wu, Lifeng; Yang, Jing; Guan, Yong

2018-01-01

The bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Data-based bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not completely independent, which reduces the performance of NB algorithms. In order to solve this problem, we propose a NB bearing fault diagnosis method based on enhanced independence of data. The method deals with data vector from two aspects: the attribute feature and the sample dimension. After processing, the classification limitation of NB is reduced by the independence hypothesis. First, we extract the statistical characteristics of the original signal of the bearings effectively. Then, the Decision Tree algorithm is used to select the important features of the time domain signal, and the low correlation features is selected. Next, the Selective Support Vector Machine (SSVM) is used to prune the dimension data and remove redundant vectors. Finally, we use NB to diagnose the fault with the low correlation data. The experimental results show that the independent enhancement of data is effective for bearing fault diagnosis. PMID:29401730

Quaternary faulting in the Tatra Mountains, evidence from cave morphology and fault-slip analysis

OpenAIRE

Szczygieł Jacek

2015-01-01

Tectonically deformed cave passages in the Tatra Mts (Central Western Carpathians) indicate some fault activity during the Quaternary. Displacements occur in the youngest passages of the caves indicating (based on previous U-series dating of speleothems) an Eemian or younger age for those faults, and so one tectonic stage. On the basis of stress analysis and geomorphological observations, two different mechanisms are proposed as responsible for the development of these displacements. The firs...

Semi-supervised weighted kernel clustering based on gravitational search for fault diagnosis.

Science.gov (United States)

Li, Chaoshun; Zhou, Jianzhong

2014-09-01

Supervised learning method, like support vector machine (SVM), has been widely applied in diagnosing known faults, however this kind of method fails to work correctly when new or unknown fault occurs. Traditional unsupervised kernel clustering can be used for unknown fault diagnosis, but it could not make use of the historical classification information to improve diagnosis accuracy. In this paper, a semi-supervised kernel clustering model is designed to diagnose known and unknown faults. At first, a novel semi-supervised weighted kernel clustering algorithm based on gravitational search (SWKC-GS) is proposed for clustering of dataset composed of labeled and unlabeled fault samples. The clustering model of SWKC-GS is defined based on wrong classification rate of labeled samples and fuzzy clustering index on the whole dataset. Gravitational search algorithm (GSA) is used to solve the clustering model, while centers of clusters, feature weights and parameter of kernel function are selected as optimization variables. And then, new fault samples are identified and diagnosed by calculating the weighted kernel distance between them and the fault cluster centers. If the fault samples are unknown, they will be added in historical dataset and the SWKC-GS is used to partition the mixed dataset and update the clustering results for diagnosing new fault. In experiments, the proposed method has been applied in fault diagnosis for rotatory bearing, while SWKC-GS has been compared not only with traditional clustering methods, but also with SVM and neural network, for known fault diagnosis. In addition, the proposed method has also been applied in unknown fault diagnosis. The results have shown effectiveness of the proposed method in achieving expected diagnosis accuracy for both known and unknown faults of rotatory bearing. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Distributed bearing fault diagnosis based on vibration analysis

Science.gov (United States)

Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

2016-01-01

Distributed bearing faults appear under various circumstances, for example due to electroerosion or the progression of localized faults. Bearings with distributed faults tend to generate more complex vibration patterns than those with localized faults. Despite the frequent occurrence of such faults, their diagnosis has attracted limited attention. This paper examines a method for the diagnosis of distributed bearing faults employing vibration analysis. The vibrational patterns generated are modeled by incorporating the geometrical imperfections of the bearing components. Comparing envelope spectra of vibration signals shows that one can distinguish between localized and distributed faults. Furthermore, a diagnostic procedure for the detection of distributed faults is proposed. This is evaluated on several bearings with naturally born distributed faults, which are compared with fault-free bearings and bearings with localized faults. It is shown experimentally that features extracted from vibrations in fault-free, localized and distributed fault conditions form clearly separable clusters, thus enabling diagnosis.

Fault-Tolerant Control of ANPC Three-Level Inverter Based on Order-Reduction Optimal Control Strategy under Multi-Device Open-Circuit Fault.

Science.gov (United States)

Xu, Shi-Zhou; Wang, Chun-Jie; Lin, Fang-Li; Li, Shi-Xiang

2017-10-31

The multi-device open-circuit fault is a common fault of ANPC (Active Neutral-Point Clamped) three-level inverter and effect the operation stability of the whole system. To improve the operation stability, this paper summarized the main solutions currently firstly and analyzed all the possible states of multi-device open-circuit fault. Secondly, an order-reduction optimal control strategy was proposed under multi-device open-circuit fault to realize fault-tolerant control based on the topology and control requirement of ANPC three-level inverter and operation stability. This control strategy can solve the faults with different operation states, and can works in order-reduction state under specific open-circuit faults with specific combined devices, which sacrifices the control quality to obtain the stability priority control. Finally, the simulation and experiment proved the effectiveness of the proposed strategy.

Research on Fault Diagnosis for Pumping Station Based on T-S Fuzzy Fault Tree and Bayesian Network

Directory of Open Access Journals (Sweden)

Zhuqing Bi

2017-01-01

Full Text Available According to the characteristics of fault diagnosis for pumping station, such as the complex structure, multiple mappings, and numerous uncertainties, a new approach combining T-S fuzzy gate fault tree and Bayesian network (BN is proposed. On the one hand, traditional fault tree method needs the logical relationship between events and probability value of events and can only represent the events with two states. T-S fuzzy gate fault tree method can solve these disadvantages but still has weaknesses in complex reasoning and only one-way reasoning. On the other hand, the BN is suitable for fault diagnosis of pumping station because of its powerful ability to deal with uncertain information. However, it is difficult to determine the structure and conditional probability tables of the BN. Therefore, the proposed method integrates the advantages of the two methods. Finally, the feasibility of the method is verified through a fault diagnosis model of the rotor in the pumping unit, the accuracy of the method is verified by comparing with the methods based on traditional Bayesian network and BP neural network, respectively, when the historical data is sufficient, and the results are more superior to the above two when the historical data is insufficient.

Fault Identification Algorithm Based on Zone-Division Wide Area Protection System

Directory of Open Access Journals (Sweden)

Xiaojun Liu

2014-04-01

Full Text Available As the power grid becomes more magnified and complicated, wide-area protection system in the practical engineering application is more and more restricted by the communication level. Based on the concept of limitedness of wide-area protection system, the grid with complex structure is divided orderly in this paper, and fault identification and protection action are executed in each divided zone to reduce the pressure of the communication system. In protection zone, a new wide-area protection algorithm based on positive sequence fault components directional comparison principle is proposed. The special associated intelligent electronic devices (IEDs zones which contain buses and transmission lines are created according to the installation location of the IEDs. When a fault occurs, with the help of the fault information collecting and sharing from associated zones with the fault discrimination principle defined in this paper, the IEDs can identify the fault location and remove the fault according to the predetermined action strategy. The algorithm will not be impacted by the load changes and transition resistance and also has good adaptability in open phase running power system. It can be used as a main protection, and it also can be taken into account for the back-up protection function. The results of cases study show that, the division method of the wide-area protection system and the proposed algorithm are effective.

Neural network-based robust actuator fault diagnosis for a non-linear multi-tank system.

Science.gov (United States)

Mrugalski, Marcin; Luzar, Marcel; Pazera, Marcin; Witczak, Marcin; Aubrun, Christophe

2016-03-01

The paper is devoted to the problem of the robust actuator fault diagnosis of the dynamic non-linear systems. In the proposed method, it is assumed that the diagnosed system can be modelled by the recurrent neural network, which can be transformed into the linear parameter varying form. Such a system description allows developing the designing scheme of the robust unknown input observer within H∞ framework for a class of non-linear systems. The proposed approach is designed in such a way that a prescribed disturbance attenuation level is achieved with respect to the actuator fault estimation error, while guaranteeing the convergence of the observer. The application of the robust unknown input observer enables actuator fault estimation, which allows applying the developed approach to the fault tolerant control tasks. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Misbheaving Faults: The Expanding Role of Geodetic Imaging in Unraveling Unexpected Fault Slip Behavior

Science.gov (United States)

Barnhart, W. D.; Briggs, R.

2015-12-01

Geodetic imaging techniques enable researchers to "see" details of fault rupture that cannot be captured by complementary tools such as seismology and field studies, thus providing increasingly detailed information about surface strain, slip kinematics, and how an earthquake may be transcribed into the geological record. For example, the recent Haiti, Sierra El Mayor, and Nepal earthquakes illustrate the fundamental role of geodetic observations in recording blind ruptures where purely geological and seismological studies provided incomplete views of rupture kinematics. Traditional earthquake hazard analyses typically rely on sparse paleoseismic observations and incomplete mapping, simple assumptions of slip kinematics from Andersonian faulting, and earthquake analogs to characterize the probabilities of forthcoming ruptures and the severity of ground accelerations. Spatially dense geodetic observations in turn help to identify where these prevailing assumptions regarding fault behavior break down and highlight new and unexpected kinematic slip behavior. Here, we focus on three key contributions of space geodetic observations to the analysis of co-seismic deformation: identifying near-surface co-seismic slip where no easily recognized fault rupture exists; discerning non-Andersonian faulting styles; and quantifying distributed, off-fault deformation. The 2013 Balochistan strike slip earthquake in Pakistan illuminates how space geodesy precisely images non-Andersonian behavior and off-fault deformation. Through analysis of high-resolution optical imagery and DEMs, evidence emerges that a single fault map slip as both a strike slip and dip slip fault across multiple seismic cycles. These observations likewise enable us to quantify on-fault deformation, which account for ~72% of the displacements in this earthquake. Nonetheless, the spatial distribution of on- and off-fault deformation in this event is highly spatially variable- a complicating factor for comparisons

Multi-Level Wavelet Shannon Entropy-Based Method for Single-Sensor Fault Location

Directory of Open Access Journals (Sweden)

Qiaoning Yang

2015-10-01

Full Text Available In actual application, sensors are prone to failure because of harsh environments, battery drain, and sensor aging. Sensor fault location is an important step for follow-up sensor fault detection. In this paper, two new multi-level wavelet Shannon entropies (multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are defined. They take full advantage of sensor fault frequency distribution and energy distribution across multi-subband in wavelet domain. Based on the multi-level wavelet Shannon entropy, a method is proposed for single sensor fault location. The method firstly uses a criterion of maximum energy-to-Shannon entropy ratio to select the appropriate wavelet base for signal analysis. Then multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are used to locate the fault. The method is validated using practical chemical gas concentration data from a gas sensor array. Compared with wavelet time Shannon entropy and wavelet energy Shannon entropy, the experimental results demonstrate that the proposed method can achieve accurate location of a single sensor fault and has good anti-noise ability. The proposed method is feasible and effective for single-sensor fault location.

A novel KFCM based fault diagnosis method for unknown faults in satellite reaction wheels.

Science.gov (United States)

Hu, Di; Sarosh, Ali; Dong, Yun-Feng

2012-03-01

Reaction wheels are one of the most critical components of the satellite attitude control system, therefore correct diagnosis of their faults is quintessential for efficient operation of these spacecraft. The known faults in any of the subsystems are often diagnosed by supervised learning algorithms, however, this method fails to work correctly when a new or unknown fault occurs. In such cases an unsupervised learning algorithm becomes essential for obtaining the correct diagnosis. Kernel Fuzzy C-Means (KFCM) is one of the unsupervised algorithms, although it has its own limitations; however in this paper a novel method has been proposed for conditioning of KFCM method (C-KFCM) so that it can be effectively used for fault diagnosis of both known and unknown faults as in satellite reaction wheels. The C-KFCM approach involves determination of exact class centers from the data of known faults, in this way discrete number of fault classes are determined at the start. Similarity parameters are derived and determined for each of the fault data point. Thereafter depending on the similarity threshold each data point is issued with a class label. The high similarity points fall into one of the 'known-fault' classes while the low similarity points are labeled as 'unknown-faults'. Simulation results show that as compared to the supervised algorithm such as neural network, the C-KFCM method can effectively cluster historical fault data (as in reaction wheels) and diagnose the faults to an accuracy of more than 91%. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Fault healing promotes high-frequency earthquakes in laboratory experiments and on natural faults

Science.gov (United States)

McLaskey, Gregory C.; Thomas, Amanda M.; Glaser, Steven D.; Nadeau, Robert M.

2012-01-01

Faults strengthen or heal with time in stationary contact and this healing may be an essential ingredient for the generation of earthquakes. In the laboratory, healing is thought to be the result of thermally activated mechanisms that weld together micrometre-sized asperity contacts on the fault surface, but the relationship between laboratory measures of fault healing and the seismically observable properties of earthquakes is at present not well defined. Here we report on laboratory experiments and seismological observations that show how the spectral properties of earthquakes vary as a function of fault healing time. In the laboratory, we find that increased healing causes a disproportionately large amount of high-frequency seismic radiation to be produced during fault rupture. We observe a similar connection between earthquake spectra and recurrence time for repeating earthquake sequences on natural faults. Healing rates depend on pressure, temperature and mineralogy, so the connection between seismicity and healing may help to explain recent observations of large megathrust earthquakes which indicate that energetic, high-frequency seismic radiation originates from locations that are distinct from the geodetically inferred locations of large-amplitude fault slip

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

KAUST Repository

Madakyaru, Muddu

2017-01-31

Chemical and petrochemical processes require continuous monitoring to detect abnormal events and to sustain normal operations. Furthermore, process monitoring enhances productivity, efficiency, and safety in process industries. Here, we propose an innovative statistical approach that exploits the advantages of multiscale partial least squares (MSPLS) models and generalized likelihood ratio (GLR) tests for fault detection in processes. Specifically, we combine an MSPLS algorithm with wavelet analysis to create our modeling framework. Then, we use GLR hypothesis testing based on the uncorrelated residuals obtained from the MSPLS model to improve fault detection. We use simulated distillation column data to evaluate the MSPLS-based GLR chart. Results show that our MSPLS-based GLR method is more powerful than the PLS-based Q and GLR method and MSPLS-based Q method, especially in early detection of small faults with abrupt or incipient behavior.

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

KAUST Repository

Madakyaru, Muddu; Harrou, Fouzi; Sun, Ying

2017-01-01

Chemical and petrochemical processes require continuous monitoring to detect abnormal events and to sustain normal operations. Furthermore, process monitoring enhances productivity, efficiency, and safety in process industries. Here, we propose an innovative statistical approach that exploits the advantages of multiscale partial least squares (MSPLS) models and generalized likelihood ratio (GLR) tests for fault detection in processes. Specifically, we combine an MSPLS algorithm with wavelet analysis to create our modeling framework. Then, we use GLR hypothesis testing based on the uncorrelated residuals obtained from the MSPLS model to improve fault detection. We use simulated distillation column data to evaluate the MSPLS-based GLR chart. Results show that our MSPLS-based GLR method is more powerful than the PLS-based Q and GLR method and MSPLS-based Q method, especially in early detection of small faults with abrupt or incipient behavior.

Structural observations from the Canavese Fault west of Valle d'Ossola (Piemonte) and some time constraints

Science.gov (United States)

Pleuger, Jan; Mancktelow, Neil

2010-05-01

The Canavese Fault (CF) is the SW part of the most important fault system in the Alps, the Periadriatic Fault. The CF has a complex kinematic history involving an older stage of NW-side-up faulting and a younger stage of SE-side-up plus dextral faulting in the area of Valle d'Ossola (Schmid et al. 1987). There, shearing occurred under greenschist-facies conditions and the fault is a c. 1 km thick mylonite zone. Toward SW, faulting took place under progressively lower temperatures and the volume of rocks affected by S-side-up plus dextral shearing becomes larger at the expense of the N-side-up mylonites. S of Valle Sesia, brittle fault rocks dominate over mylonites. Still further SW, close to the Serra d'Ivrea, the CF splits into two branches, the Internal Canavese Fault (ICF) and the External Canavese Fault (ECF). S-side-up plus dextral faulting is localised along the ICF while the observed displacement senses at the ECF are mostly, though not always, N-side-up and sinistral. Age constraints for faulting along the CF are mostly derived from absolute ages of magmatic rocks exposed alongside or within the fault. In the section around Biella, NW-side-up faulting cannot have lasted longer than until 31±2 Ma (Scheuring et al. 1974) because this is the age of andesites overlying the basement of the Penninic Sesia Zone. However, some additional uplift of the Sesia Zone with respect to the South Alpine Ivrea Zone was accommodated by down-to-the-SE tilting of the Sesia zone around a roughly NNE-SSW-trending subhorizontal axis which is evidenced by palaeomagnetic data (Lanza 1977). As a result of that, the Early Oligocene Biella Pluton (c. 31 Ma, Romer et al. 1996) today occupies a similar altitude level as the andesites of the same age. Post-31-Ma uplift of the Ivrea Zone with respect to the andesites is evidenced by the Early Oligocene (29-33 Ma, Carraro & Ferrara 1968) Miagliano Pluton which is hosted by the Ivrea Zone rocks and exposed at the present topographic surface

Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis.

Science.gov (United States)

Deng, Xiaogang; Tian, Xuemin; Chen, Sheng; Harris, Chris J

2018-03-01

Many industrial processes contain both linear and nonlinear parts, and kernel principal component analysis (KPCA), widely used in nonlinear process monitoring, may not offer the most effective means for dealing with these nonlinear processes. This paper proposes a new hybrid linear-nonlinear statistical modeling approach for nonlinear process monitoring by closely integrating linear principal component analysis (PCA) and nonlinear KPCA using a serial model structure, which we refer to as serial PCA (SPCA). Specifically, PCA is first applied to extract PCs as linear features, and to decompose the data into the PC subspace and residual subspace (RS). Then, KPCA is performed in the RS to extract the nonlinear PCs as nonlinear features. Two monitoring statistics are constructed for fault detection, based on both the linear and nonlinear features extracted by the proposed SPCA. To effectively perform fault identification after a fault is detected, an SPCA similarity factor method is built for fault recognition, which fuses both the linear and nonlinear features. Unlike PCA and KPCA, the proposed method takes into account both linear and nonlinear PCs simultaneously, and therefore, it can better exploit the underlying process's structure to enhance fault diagnosis performance. Two case studies involving a simulated nonlinear process and the benchmark Tennessee Eastman process demonstrate that the proposed SPCA approach is more effective than the existing state-of-the-art approach based on KPCA alone, in terms of nonlinear process fault detection and identification.

Resonance-Based Sparse Signal Decomposition and its Application in Mechanical Fault Diagnosis: A Review.

Science.gov (United States)

Huang, Wentao; Sun, Hongjian; Wang, Weijie

2017-06-03

Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD's theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis.

Rotor current transient analysis of DFIG-based wind turbines during symmetrical voltage faults

International Nuclear Information System (INIS)

Ling, Yu; Cai, Xu; Wang, Ningbo

2013-01-01

Highlights: • We theoretically analyze the rotor fault current of DFIG based on space vector. • The presented analysis is simple, easy to understand. • The analysis highlights the accuracy of the expression of the rotor fault currents. • The expression can be widely used to analyze the different levels of voltage symmetrical fault. • Simulation results show the accuracy of the expression of the rotor currents. - Abstract: The impact of grid voltage fault on doubly fed induction generators (DFIGs), especially rotor currents, has received much attention. So, in this paper, the rotor currents of based-DFIG wind turbines are considered in a generalized way, which can be widely used to analyze the cases under different levels of voltage symmetrical faults. A direct method based on space vector is proposed to obtain an accurate expression of rotor currents as a function of time for symmetrical voltage faults in the power system. The presented theoretical analysis is simple and easy to understand and especially highlights the accuracy of the expression. Finally, the comparable simulations evaluate this analysis and show that the expression of the rotor currents is sufficient to calculate the maximum fault current, DC and AC components, and especially helps to understand the causes of the problem and as a result, contributes to adapt reasonable approaches to enhance the fault ride through (FRT) capability of DFIG wind turbines during a voltage fault

Fault isolability conditions for linear systems with additive faults

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, Jakob

2006-01-01

In this paper, we shall show that an unlimited number of additive single faults can be isolated under mild conditions if a general isolation scheme is applied. Multiple faults are also covered. The approach is algebraic and is based on a set representation of faults, where all faults within a set...

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-07-01

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

A comparison between rate-and-state friction and microphysical models, based on numerical simulations of fault slip

Science.gov (United States)

van den Ende, M. P. A.; Chen, J.; Ampuero, J.-P.; Niemeijer, A. R.

2018-05-01

Rate-and-state friction (RSF) is commonly used for the characterisation of laboratory friction experiments, such as velocity-step tests. However, the RSF framework provides little physical basis for the extrapolation of these results to the scales and conditions of natural fault systems, and so open questions remain regarding the applicability of the experimentally obtained RSF parameters for predicting seismic cycle transients. As an alternative to classical RSF, microphysics-based models offer means for interpreting laboratory and field observations, but are generally over-simplified with respect to heterogeneous natural systems. In order to bridge the temporal and spatial gap between the laboratory and nature, we have implemented existing microphysical model formulations into an earthquake cycle simulator. Through this numerical framework, we make a direct comparison between simulations exhibiting RSF-controlled fault rheology, and simulations in which the fault rheology is dictated by the microphysical model. Even though the input parameters for the RSF simulation are directly derived from the microphysical model, the microphysics-based simulations produce significantly smaller seismic event sizes than the RSF-based simulation, and suggest a more stable fault slip behaviour. Our results reveal fundamental limitations in using classical rate-and-state friction for the extrapolation of laboratory results. The microphysics-based approach offers a more complete framework in this respect, and may be used for a more detailed study of the seismic cycle in relation to material properties and fault zone pressure-temperature conditions.

Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis

Science.gov (United States)

Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.

2017-12-01

Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of

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

DEFF Research Database (Denmark)

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

2018-01-01

One of the major challenges in protection of the inverter-interfaced islanded microgrids is their limited fault current level. This degrades the performance of traditional overcurrent protection schemes. This paper proposes a fault detection strategy based on monitoring the transient response......-domain simulation case studies using the CIGRE benchmark low voltage microgrid network....

Quantifying structural uncertainty on fault networks using a marked point process within a Bayesian framework

Science.gov (United States)

Aydin, Orhun; Caers, Jef Karel

2017-08-01

Faults are one of the building-blocks for subsurface modeling studies. Incomplete observations of subsurface fault networks lead to uncertainty pertaining to location, geometry and existence of faults. In practice, gaps in incomplete fault network observations are filled based on tectonic knowledge and interpreter's intuition pertaining to fault relationships. Modeling fault network uncertainty with realistic models that represent tectonic knowledge is still a challenge. Although methods that address specific sources of fault network uncertainty and complexities of fault modeling exists, a unifying framework is still lacking. In this paper, we propose a rigorous approach to quantify fault network uncertainty. Fault pattern and intensity information are expressed by means of a marked point process, marked Strauss point process. Fault network information is constrained to fault surface observations (complete or partial) within a Bayesian framework. A structural prior model is defined to quantitatively express fault patterns, geometries and relationships within the Bayesian framework. Structural relationships between faults, in particular fault abutting relations, are represented with a level-set based approach. A Markov Chain Monte Carlo sampler is used to sample posterior fault network realizations that reflect tectonic knowledge and honor fault observations. We apply the methodology to a field study from Nankai Trough & Kumano Basin. The target for uncertainty quantification is a deep site with attenuated seismic data with only partially visible faults and many faults missing from the survey or interpretation. A structural prior model is built from shallow analog sites that are believed to have undergone similar tectonics compared to the site of study. Fault network uncertainty for the field is quantified with fault network realizations that are conditioned to structural rules, tectonic information and partially observed fault surfaces. We show the proposed

Evaluation of Wind Farm Controller based Fault Detection and Isolation

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Shafiei, Seyed Ehsan

2015-01-01

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

Interseismic Strain Accumulation of the Gazikoy-Saros segment (Ganos fault) of the North Anatolian Fault Zone

Science.gov (United States)

Havazli, E.; Wdowinski, S.; Amelung, F.

2017-12-01

The North Anatolian Fault Zone (NAFZ) is one of the most active continental transform faults in the world. A westward migrating earthquake sequence has started in 1939 in Erzincan and the last two events of this sequence occurred in 1999 in Izmit and Duzce manifesting the importance of NAFZ on the seismic hazard potential of the region. NAFZ exhibits slip rates ranging from 14-30 mm/yr along its 1500 km length with a right lateral strike slip characteristic. In the East of the Marmara Sea, the NAFZ splits into two branches. The Gazikoy-Saros segment (Ganos Fault) is the westernmost and onshore segment of the northern branch. The ENE-WSW oriented Ganos Fault is seismically active. It produced a Ms 7.2 earthquake in 1912, which was followed by several large aftershocks, including Ms 6.3 and Ms 6.9 events. Since 1912, the Ganos Fault did not produce any significant earthquakes (> M 5), in contrast to its adjacent segments, which produced 20 M>5 earthquakes, including a M 6.7 event, offshore in Gulf of Saros. Interseismic strain accumulation along the Ganos Fault was assessed from sparse GPS measurements along a single transect located perpendicular to the fault zone, suggesting strain accumulation rate of 20-25 mm/yr. Insofar, InSAR studies, based on C-band data, didn't produce conclusive results due to low coherence over the fault zone area, which is highly vegetated. In this study, we present a detailed interseismic velocity map of the Ganos Fault zone derived from L-band InSAR observations. We use 21 ALOS PALSAR scenes acquired over a 5-year period, from 2007 to 2011. We processed the ALOS data using the PySAR software, which is the University of Miami version of the Small Baseline (SB) method. The L-band observations enabled us to overcome the coherence issue in the study area. Our initial results indicate a maximum velocity of 15 mm/yr across the fault zone. The high spatial resolution of the InSAR-based interseismic velocity map will enable us to better to

Diagnosis of soft faults in analog integrated circuits based on fractional correlation

International Nuclear Information System (INIS)

Deng Yong; Shi Yibing; Zhang Wei

2012-01-01

Aiming at the problem of diagnosing soft faults in analog integrated circuits, an approach based on fractional correlation is proposed. First, the Volterra series of the circuit under test (CUT) decomposed by the fractional wavelet packet are used to calculate the fractional correlation functions. Then, the calculated fractional correlation functions are used to form the fault signatures of the CUT. By comparing the fault signatures, the different soft faulty conditions of the CUT are identified and the faults are located. Simulations of benchmark circuits illustrate the proposed method and validate its effectiveness in diagnosing soft faults in analog integrated circuits. (semiconductor integrated circuits)

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

Directory of Open Access Journals (Sweden)

D. U. Campos-Delgado

2008-01-01

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

Fault Diagnosis for Rolling Bearings under Variable Conditions Based on Visual Cognition.

Science.gov (United States)

Cheng, Yujie; Zhou, Bo; Lu, Chen; Yang, Chao

2017-05-25

Fault diagnosis for rolling bearings has attracted increasing attention in recent years. However, few studies have focused on fault diagnosis for rolling bearings under variable conditions. This paper introduces a fault diagnosis method for rolling bearings under variable conditions based on visual cognition. The proposed method includes the following steps. First, the vibration signal data are transformed into a recurrence plot (RP), which is a two-dimensional image. Then, inspired by the visual invariance characteristic of the human visual system (HVS), we utilize speed up robust feature to extract fault features from the two-dimensional RP and generate a 64-dimensional feature vector, which is invariant to image translation, rotation, scaling variation, etc. Third, based on the manifold perception characteristic of HVS, isometric mapping, a manifold learning method that can reflect the intrinsic manifold embedded in the high-dimensional space, is employed to obtain a low-dimensional feature vector. Finally, a classical classification method, support vector machine, is utilized to realize fault diagnosis. Verification data were collected from Case Western Reserve University Bearing Data Center, and the experimental result indicates that the proposed fault diagnosis method based on visual cognition is highly effective for rolling bearings under variable conditions, thus providing a promising approach from the cognitive computing field.

Integrated system fault diagnostics utilising digraph and fault tree-based approaches

International Nuclear Information System (INIS)

Bartlett, L.M.; Hurdle, E.E.; Kelly, E.M.

2009-01-01

With the growing intolerance to failures within systems, the issue of fault diagnosis has become ever prevalent. Information concerning these possible failures can help to minimise the disruption to the functionality of the system by allowing quick rectification. Traditional approaches to fault diagnosis within engineering systems have focused on sequential testing procedures and real-time mechanisms. Both methods have been predominantly limited to single fault causes. Latest approaches also consider the issue of multiple faults in reflection to the characteristics of modern day systems designed for high reliability. In addition, a diagnostic capability is required in real time and for changeable system functionality. This paper focuses on two approaches which have been developed to cater for the demands of diagnosis within current engineering systems, namely application of the fault tree analysis technique and the method of digraphs. Both use a comparative approach to consider differences between actual system behaviour and that expected. The procedural guidelines are discussed for each method, with an experimental aircraft fuel system used to test and demonstrate the features of the techniques. The effectiveness of the approaches is compared and their future potential highlighted

Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter.

Science.gov (United States)

Wang, Tianzhen; Qi, Jie; Xu, Hao; Wang, Yide; Liu, Lei; Gao, Diju

2016-01-01

Thanks to reduced switch stress, high quality of load wave, easy packaging and good extensibility, the cascaded H-bridge multilevel inverter is widely used in wind power system. To guarantee stable operation of system, a new fault diagnosis method, based on Fast Fourier Transform (FFT), Relative Principle Component Analysis (RPCA) and Support Vector Machine (SVM), is proposed for H-bridge multilevel inverter. To avoid the influence of load variation on fault diagnosis, the output voltages of the inverter is chosen as the fault characteristic signals. To shorten the time of diagnosis and improve the diagnostic accuracy, the main features of the fault characteristic signals are extracted by FFT. To further reduce the training time of SVM, the feature vector is reduced based on RPCA that can get a lower dimensional feature space. The fault classifier is constructed via SVM. An experimental prototype of the inverter is built to test the proposed method. Compared to other fault diagnosis methods, the experimental results demonstrate the high accuracy and efficiency of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

Golafshan, Reza; Yuce Sanliturk, Kenan

2016-03-01

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

Improved protection system for phase faults on marine vessels based on ratio between negative sequence and positive sequence of the fault current

DEFF Research Database (Denmark)

Ciontea, Catalin-Iosif; Hong, Qiteng; Booth, Campbell

2018-01-01

algorithm is implemented in a programmable digital relay embedded in a hardware-in-the-loop (HIL) test set-up that emulates a typical maritime feeder using a real-time digital simulator. The HIL set-up allows testing of the new protection method under a wide range of faults and network conditions......This study presents a new method to protect the radial feeders on marine vessels. The proposed protection method is effective against phase–phase (PP) faults and is based on evaluation of the ratio between the negative sequence and positive sequence of the fault currents. It is shown...... that the magnitude of the introduced ratio increases significantly during the PP fault, hence indicating the fault presence in an electric network. Here, the theoretical background of the new method of protection is firstly discussed, based on which the new protection algorithm is described afterwards. The proposed...

Study on Fault Diagnosis of Rolling Bearing Based on Time-Frequency Generalized Dimension

Directory of Open Access Journals (Sweden)

Yu Yuan

2015-01-01

Full Text Available The condition monitoring technology and fault diagnosis technology of mechanical equipment played an important role in the modern engineering. Rolling bearing is the most common component of mechanical equipment which sustains and transfers the load. Therefore, fault diagnosis of rolling bearings has great significance. Fractal theory provides an effective method to describe the complexity and irregularity of the vibration signals of rolling bearings. In this paper a novel multifractal fault diagnosis approach based on time-frequency domain signals was proposed. The method and numerical algorithm of Multi-fractal analysis in time-frequency domain were provided. According to grid type J and order parameter q in algorithm, the value range of J and the cut-off condition of q were optimized based on the effect on the dimension calculation. Simulation experiments demonstrated that the effective signal identification could be complete by multifractal method in time-frequency domain, which is related to the factors such as signal energy and distribution. And the further fault diagnosis experiments of bearings showed that the multifractal method in time-frequency domain can complete the fault diagnosis, such as the fault judgment and fault types. And the fault detection can be done in the early stage of fault. Therefore, the multifractal method in time-frequency domain used in fault diagnosis of bearing is a practicable method.

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

Science.gov (United States)

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

2013-12-01

include secondary faults at depths up to 4-8m below the surface and located up to 24m away from the main fault trace. The Torremolinos fault system includes secondary faults, which are present up to 8m deep and 12-18m away from the main fault trace. Even though the InSAR analysis provides an unsurpassed synoptic view, a higher temporal resolution observation of fault movement has been pursued using the MOIT continuously operating GPS station, which is located within 100 m from the La Colina main fault trace. GPS data is also particularly useful to decompose horizontal and vertical motion in the absence of both ascending and descending SAR data acquisitions. Observations since July 2009 show a total general displacement trend of -39mm/yr and a total horizontal differential motion of 41.8 mm/yr and -4.7mm/yr in its latitudinal and Longitudinal components respectively in respect to the motion observed at the MOGA GPS station located 5.0 km to the SSE within an area which is not affected by subsidence. In addition to the overall trend, high amplitude excursions at the MOIT station with individual residual amplitudes up to 20mm, 25mm, and 60mm in its latitudinal, longitudinal and vertical components respectively vertical are observed. The correlation of fault motion excursions in relationship to the rainfall records will be analyzed.

Cross-fault pressure depletion, Zechstein carbonate reservoir, Weser-Ems area, Northern German Gas Basin

Energy Technology Data Exchange (ETDEWEB)

Corona, F.V.; Brauckmann, F.; Beckmann, H.; Gobi, A.; Grassmann, S.; Neble, J.; Roettgen, K. [ExxonMobil Production Deutschland GmbH (EMPG), Hannover (Germany)

2013-08-01

A cross-fault pressure depletion study in Upper Permian Zechstein Ca2 carbonate reservoir was undertaken in the Weser-Ems area of the Northern German Gas Basin. The primary objectives are to develop a practical workflow to define cross-fault pressures scenarios for Zechstein Ca2 reservoir drillwells, to determine the key factors of cross-fault pressure behavior in this platform carbonate reservoir, and to translate the observed cross-fault pressure depletion to fault transmissibility for reservoir simulation models. Analysis of Zechstein Ca2 cross-fault pressures indicates that most Zechstein-cutting faults appear to act as fluid-flow baffles with some local occurrences of fault seal. Moreover, there appears to be distinct cross-fault baffling or pressure depletion trends that may be related to the extent of the separating fault or fault system, degree of reservoir flow-path tortuosity, and quality of reservoir juxtaposition. Based on the above observations, a three-part workflow was developed consisting of (1) careful interpretation and mapping of faults and fault networks, (2) analysis of reservoir juxtaposition and reservoir juxtaposition quality, and (3) application of the observed cross-fault pressure depletion trends. This approach is field-analog based, is practical, and is being used currently to provide reliable and supportable pressure prediction scenarios for subsequent Zechstein fault-bounded drill-well opportunities.

Synthetic seismicity for the San Andreas fault

Directory of Open Access Journals (Sweden)

S. N. Ward

1994-06-01

Full Text Available Because historical catalogs generally span only a few repetition intervals of major earthquakes, they do not provide much constraint on how regularly earthquakes recur. In order to obtain better recurrence statistics and long-term probability estimates for events M ? 6 on the San Andreas fault, we apply a seismicity model to this fault. The model is based on the concept of fault segmentation and the physics of static dislocations which allow for stress transfer between segments. Constraints are provided by geological and seismological observations of segment lengths, characteristic magnitudes and long-term slip rates. Segment parameters slightly modified from the Working Group on California Earthquake Probabilities allow us to reproduce observed seismicity over four orders of magnitude. The model yields quite irregular earthquake recurrence patterns. Only the largest events (M ? 7.5 are quasi-periodic; small events cluster. Both the average recurrence time and the aperiodicity are also a function of position along the fault. The model results are consistent with paleoseismic data for the San Andreas fault as well as a global set of historical and paleoseismic recurrence data. Thus irregular earthquake recurrence resulting from segment interaction is consistent with a large range of observations.

Sensor fault diagnosis of aero-engine based on divided flight status

Science.gov (United States)

Zhao, Zhen; Zhang, Jun; Sun, Yigang; Liu, Zhexu

2017-11-01

Fault diagnosis and safety analysis of an aero-engine have attracted more and more attention in modern society, whose safety directly affects the flight safety of an aircraft. In this paper, the problem concerning sensor fault diagnosis is investigated for an aero-engine during the whole flight process. Considering that the aero-engine is always working in different status through the whole flight process, a flight status division-based sensor fault diagnosis method is presented to improve fault diagnosis precision for the aero-engine. First, aero-engine status is partitioned according to normal sensor data during the whole flight process through the clustering algorithm. Based on that, a diagnosis model is built for each status using the principal component analysis algorithm. Finally, the sensors are monitored using the built diagnosis models by identifying the aero-engine status. The simulation result illustrates the effectiveness of the proposed method.

Sensor fault diagnosis of aero-engine based on divided flight status.

Science.gov (United States)

Zhao, Zhen; Zhang, Jun; Sun, Yigang; Liu, Zhexu

2017-11-01

Fault diagnosis and safety analysis of an aero-engine have attracted more and more attention in modern society, whose safety directly affects the flight safety of an aircraft. In this paper, the problem concerning sensor fault diagnosis is investigated for an aero-engine during the whole flight process. Considering that the aero-engine is always working in different status through the whole flight process, a flight status division-based sensor fault diagnosis method is presented to improve fault diagnosis precision for the aero-engine. First, aero-engine status is partitioned according to normal sensor data during the whole flight process through the clustering algorithm. Based on that, a diagnosis model is built for each status using the principal component analysis algorithm. Finally, the sensors are monitored using the built diagnosis models by identifying the aero-engine status. The simulation result illustrates the effectiveness of the proposed method.

Preliminary confirmation of a surface faulting based on geological and earthquake data in the Puspiptek Serpong area

International Nuclear Information System (INIS)

Hadi Suntoko; Supartoyo

2016-01-01

BAPETEN regulation No. 8/2013 present the requirement that the site of the nuclear industry should not be a fault capable in a radius of 5 km. It is known that the RDE site composed of sandstones, clay stone, conglomerates and pumice rework the age of Pliocene, there straightness river valley hypothesized as a fault. Potential faults are identified using morphological observation, remote sensing using DEM rock outcrops, and seismic interpretation results that aims to confirm capable faults in a radius of 5 km. Traces defence surface is focused on the observation of the appearance of the terrain (land form), in the form of straightness morphology or valleys, fault scarp (fault scarp), shift or offset (river or hill), depression formed along fault zones, saddle, pressure ridge, and the shape of the river as well as earthquake monitoring. The results showed that there was no fault capable also a surface faulting that prove the presence in the RDE site radius of 5 km. (author)

Fault diagnostics for turbo-shaft engine sensors based on a simplified on-board model.

Science.gov (United States)

Lu, Feng; Huang, Jinquan; Xing, Yaodong

2012-01-01

Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

Fault Diagnostics for Turbo-Shaft Engine Sensors Based on a Simplified On-Board Model

Directory of Open Access Journals (Sweden)

Yaodong Xing

2012-08-01

Full Text Available Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can’t be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

Sentinel-1 observation of the 2017 Sangsefid earthquake, northeastern Iran: Rupture of a blind reserve-slip fault near the Eastern Kopeh Dagh

Science.gov (United States)

Xu, Guangyu; Xu, Caijun; Wen, Yangmao

2018-04-01

New satellites are now revealing InSAR-based surface deformation within a week after natural hazard events. Quick hazard responses will be more publically accessible and provide information to responding agencies. Here we used Sentinel-1 interferometric synthetic aperture radar (InSAR) data to investigate coseismic deformation associated with the 2017 Sangsefid earthquake, which occurred in the southeast margin of the Kopeh Dagh fault system. The ascending and descending interferograms indicate thrust-dominated slip, with the maximum line-of-sight displacement of 10.5 and 13.7 cm, respectively. The detailed slip-distribution of the 2017 Sangsefid Mw6.1 earthquake inferred from geodetic data is presented here for the first time. Although the InSAR interferograms themselves do not uniquely constrain what the primary slip surface is, we infer that the source fault dips to southwest by analyzing the 2.5 D displacement field decomposed from the InSAR observations. The determined uniform slip fault model shows that the dip angle of the seimogenic fault is approximately 40°, with a strike of 120° except for a narrower fault width than that predicted by the empirical scaling law. We suggest that geometric complexities near the Kopeh Dagh fault system obstruct the rupture propagation, resulting in high slip occurred within a small area and much higher stress drop than global estimates. The InSAR-determined moment is 1.71 × 1018 Nm with a shear modulus of 3.32 × 1010 N/m2, equivalent to Mw 6.12, which is consistent with seismological results. The finite fault model (the west-dipping fault plane) reveals that the peak slip of 0.90 m occurred at a depth of 6.3 km, with substantial slip at a depth of 4-10 km and a near-uniform slip of 0.1 m at a depth of 0-2.5 km. We suggest that the Sangsefid earthquake occurred on an unknown blind reverse fault dipping southwest, which can also be recognised through observing the long-term surface effects due to the existence of the blind

Spatial analysis of hypocenter to fault relationships for determining fault process zone width in Japan

International Nuclear Information System (INIS)

Arnold, Bill Walter; Roberts, Barry L.; McKenna, Sean Andrew; Coburn, Timothy C.

2004-01-01

Preliminary investigation areas (PIA) for a potential repository of high-level radioactive waste must be evaluated by NUMO with regard to a number of qualifying factors. One of these factors is related to earthquakes and fault activity. This study develops a spatial statistical assessment method that can be applied to the active faults in Japan to perform such screening evaluations. This analysis uses the distribution of seismicity near faults to define the width of the associated process zone. This concept is based on previous observations of aftershock earthquakes clustered near active faults and on the assumption that such seismic activity is indicative of fracturing and associated impacts on bedrock integrity. Preliminary analyses of aggregate data for all of Japan confirmed that the frequency of earthquakes is higher near active faults. Data used in the analysis were obtained from NUMO and consist of three primary sources: (1) active fault attributes compiled in a spreadsheet, (2) earthquake hypocenter data, and (3) active fault locations. Examination of these data revealed several limitations with regard to the ability to associate fault attributes from the spreadsheet to locations of individual fault trace segments. In particular, there was no direct link between attributes of the active faults in the spreadsheet and the active fault locations in the GIS database. In addition, the hypocenter location resolution in the pre-1983 data was less accurate than for later data. These pre-1983 hypocenters were eliminated from further analysis

Spatial analysis of hypocenter to fault relationships for determining fault process zone width in Japan.

Energy Technology Data Exchange (ETDEWEB)

Arnold, Bill Walter; Roberts, Barry L.; McKenna, Sean Andrew; Coburn, Timothy C. (Abilene Christian University, Abilene, TX)

2004-09-01

Preliminary investigation areas (PIA) for a potential repository of high-level radioactive waste must be evaluated by NUMO with regard to a number of qualifying factors. One of these factors is related to earthquakes and fault activity. This study develops a spatial statistical assessment method that can be applied to the active faults in Japan to perform such screening evaluations. This analysis uses the distribution of seismicity near faults to define the width of the associated process zone. This concept is based on previous observations of aftershock earthquakes clustered near active faults and on the assumption that such seismic activity is indicative of fracturing and associated impacts on bedrock integrity. Preliminary analyses of aggregate data for all of Japan confirmed that the frequency of earthquakes is higher near active faults. Data used in the analysis were obtained from NUMO and consist of three primary sources: (1) active fault attributes compiled in a spreadsheet, (2) earthquake hypocenter data, and (3) active fault locations. Examination of these data revealed several limitations with regard to the ability to associate fault attributes from the spreadsheet to locations of individual fault trace segments. In particular, there was no direct link between attributes of the active faults in the spreadsheet and the active fault locations in the GIS database. In addition, the hypocenter location resolution in the pre-1983 data was less accurate than for later data. These pre-1983 hypocenters were eliminated from further analysis.

Plate rotations, fault slip rates, fault locking, and distributed deformation in northern Central America from 1999-2017 GPS observations

Science.gov (United States)

Ellis, A. P.; DeMets, C.; Briole, P.; Cosenza, B.; Flores, O.; Guzman-Speziale, M.; Hernandez, D.; Kostoglodov, V.; La Femina, P. C.; Lord, N. E.; Lasserre, C.; Lyon-Caen, H.; McCaffrey, R.; Molina, E.; Rodriguez, M.; Staller, A.; Rogers, R.

2017-12-01

We describe plate rotations, fault slip rates, and fault locking estimated from a new 100-station GPS velocity field at the western end of the Caribbean plate, where the Motagua-Polochic fault zone, Middle America trench, and Central America volcanic arc faults converge. In northern Central America, fifty-one upper-plate earthquakes caused approximately 40,000 fatalities since 1900. The proximity of main population centers to these destructive earthquakes and the resulting loss of human life provide strong motivation for studying the present-day tectonics of Central America. Plate rotations, fault slip rates, and deformation are quantified via a two-stage inversion of daily GPS position time series using TDEFNODE modeling software. In the first stage, transient deformation associated with three M>7 earthquakes in 2009 and 2012 is estimated and removed from the GPS position time series. In Stage 2, linear velocities determined from the corrected GPS time series are inverted to estimate deformation within the western Caribbean plate, slip rates along the Motagua-Polochic faults and faults in the Central America volcanic arc, and the gradient of extension in the Honduras-Guatemala wedge. Major outcomes of the second inversion include the following: (1) Confirmation that slip rates on the Motagua fault decrease from 17-18 mm/yr at its eastern end to 0-5 mm/yr at its western end, in accord with previous results. (2) A transition from moderate subduction zone locking offshore from southern Mexico and parts of southern Guatemala to weak or zero coupling offshore from El Salvador and parts of Nicaragua along the Middle America trench. (3) Evidence for significant east-west extension in southern Guatemala between the Motagua fault and volcanic arc. Our study also shows evidence for creep on the eastern Motagua fault that diminishes westward along the North America-Caribbean plate boundary.

Satellite Fault Diagnosis Using Support Vector Machines Based on a Hybrid Voting Mechanism

Science.gov (United States)

Yang, Shuqiang; Zhu, Xiaoqian; Jin, Songchang; Wang, Xiang

2014-01-01

The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM) to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved. PMID:25215324

Satellite Fault Diagnosis Using Support Vector Machines Based on a Hybrid Voting Mechanism

Directory of Open Access Journals (Sweden)

Hong Yin

2014-01-01

Full Text Available The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved.

Minimizing student’s faults in determining the design of experiment through inquiry-based learning

Science.gov (United States)

Nilakusmawati, D. P. E.; Susilawati, M.

2017-10-01

The purpose of this study were to describe the used of inquiry method in an effort to minimize student’s fault in designing an experiment and to determine the effectiveness of the implementation of the inquiry method in minimizing student’s faults in designing experiments on subjects experimental design. This type of research is action research participants, with a model of action research design. The data source were students of the fifth semester who took a subject of experimental design at Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University. Data was collected through tests, interviews, and observations. The hypothesis was tested by t-test. The result showed that the implementation of inquiry methods to minimize of students fault in designing experiments, analyzing experimental data, and interpret them in cycle 1 students can reduce fault by an average of 10.5%. While implementation in Cycle 2, students managed to reduce fault by an average of 8.78%. Based on t-test results can be concluded that the inquiry method effectively used to minimize of student’s fault in designing experiments, analyzing experimental data, and interpreting them. The nature of the teaching materials on subject of Experimental Design that demand the ability of students to think in a systematic, logical, and critical in analyzing the data and interpret the test cases makes the implementation of this inquiry become the proper method. In addition, utilization learning tool, in this case the teaching materials and the students worksheet is one of the factors that makes this inquiry method effectively minimizes of student’s fault when designing experiments.

A Novel Busbar Protection Based on the Average Product of Fault Components

Directory of Open Access Journals (Sweden)

Guibin Zou

2018-05-01

Full Text Available This paper proposes an original busbar protection method, based on the characteristics of the fault components. The method firstly extracts the fault components of the current and voltage after the occurrence of a fault, secondly it uses a novel phase-mode transformation array to obtain the aerial mode components, and lastly, it obtains the sign of the average product of the aerial mode voltage and current. For a fault on the busbar, the average products that are detected on all of the lines that are linked to the faulted busbar are all positive within a specific duration of the post-fault. However, for a fault at any one of these lines, the average product that has been detected on the faulted line is negative, while those on the non-faulted lines are positive. On the basis of the characteristic difference that is mentioned above, the identification criterion of the fault direction is established. Through comparing the fault directions on all of the lines, the busbar protection can quickly discriminate between an internal fault and an external fault. By utilizing the PSCAD/EMTDC software (4.6.0.0, Manitoba HVDC Research Centre, Winnipeg, MB, Canada, a typical 500 kV busbar model, with one and a half circuit breakers configuration, was constructed. The simulation results show that the proposed busbar protection has a good adjustability, high reliability, and rapid operation speed.

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

Science.gov (United States)

Abe, S.

2010-12-01

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

Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

KAUST Repository

Feng, Guangcai

2017-03-15

The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

KAUST Repository

Feng, Guangcai; Jonsson, Sigurjon; Klinger, Yann

2017-01-01

The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

Early Safety Assessment of Automotive Systems Using Sabotage Simulation-Based Fault Injection Framework

OpenAIRE

Juez, Garazi; Amparan, Estíbaliz; Lattarulo, Ray; Ruíz, Alejandra; Perez, Joshue; Espinoza, Huascar

2017-01-01

As road vehicles increase their autonomy and the driver reduces his role in the control loop, novel challenges on dependability assessment arise. Model-based design combined with a simulation-based fault injection technique and a virtual vehicle poses as a promising solution for an early safety assessment of automotive systems. To start with, the design, where no safety was considered, is stimulated with a set of fault injection simulations (fault forecasting). By doing so, safety strategies ...

Fault diagnosis for dynamic power system

International Nuclear Information System (INIS)

Thabet, A.; Abdelkrim, M.N.; Boutayeb, M.; Didier, G.; Chniba, S.

2011-01-01

The fault diagnosis problem for dynamic power systems is treated, the nonlinear dynamic model based on a differential algebraic equations is transformed with reduced index to a simple dynamic model. Two nonlinear observers are used for generating the fault signals for comparison purposes, one of them being an extended Kalman estimator and the other a new extended kalman filter with moving horizon with a study of convergence based on the choice of matrix of covariance of the noises of system and measurements. The paper illustrates a simulation study applied on IEEE 3 buses test system.

Fault diagnosis of direct-drive wind turbine based on support vector machine

International Nuclear Information System (INIS)

An, X L; Jiang, D X; Li, S H; Chen, J

2011-01-01

A fault diagnosis method of direct-drive wind turbine based on support vector machine (SVM) and feature selection is presented. The time-domain feature parameters of main shaft vibration signal in the horizontal and vertical directions are considered in the method. Firstly, in laboratory scale five experiments of direct-drive wind turbine with normal condition, wind wheel mass imbalance fault, wind wheel aerodynamic imbalance fault, yaw fault and blade airfoil change fault are carried out. The features of five experiments are analyzed. Secondly, the sensitive time-domain feature parameters in the horizontal and vertical directions of vibration signal in the five conditions are selected and used as feature samples. By training, the mapping relation between feature parameters and fault types are established in SVM model. Finally, the performance of the proposed method is verified through experimental data. The results show that the proposed method is effective in identifying the fault of wind turbine. It has good classification ability and robustness to diagnose the fault of direct-drive wind turbine.

Hydraulic Pump Fault Diagnosis Control Research Based on PARD-BP Algorithm

Directory of Open Access Journals (Sweden)

LV Dongmei

2014-12-01

Full Text Available Combining working principle and failure mechanism of RZU2000HM hydraulic press, with its present fault cases being collected, the working principle of the oil pressure and faults phenomenon of the hydraulic power unit –swash-plate axial piston pump were studied with some emphasis, whose faults will directly affect the dynamic performance of the oil pressure and flow. In order to make hydraulic power unit work reliably, PARD-BP (Pruning Algorithm based Random Degree neural network fault algorithm was introduced, with swash-plate axial piston pump’s vibration fault sample data regarded as input, and fault mode matrix regarded as target output, so that PARD-BP algorithm could be trained. In the end, the vibration results were verified by the vibration modal test, and it was shown that the biggest upward peaks of vacuum pump in X-direction, Y-direction and Z- direction have fallen by 30.49 %, 21.13 % and 18.73 % respectively, so that the reliability of the fact that PARD-BP algorithm could be used for the online fault detection and diagnosis of the hydraulic pump was verified.

Fault-tolerant cooperative output regulation for multi-vehicle systems with sensor faults

Science.gov (United States)

Qin, Liguo; He, Xiao; Zhou, D. H.

2017-10-01

This paper presents a unified framework of fault diagnosis and fault-tolerant cooperative output regulation (FTCOR) for a linear discrete-time multi-vehicle system with sensor faults. The FTCOR control law is designed through three steps. A cooperative output regulation (COR) controller is designed based on the internal mode principle when there are no sensor faults. A sufficient condition on the existence of the COR controller is given based on the discrete-time algebraic Riccati equation (DARE). Then, a decentralised fault diagnosis scheme is designed to cope with sensor faults occurring in followers. A residual generator is developed to detect sensor faults of each follower, and a bank of fault-matching estimators are proposed to isolate and estimate sensor faults of each follower. Unlike the current distributed fault diagnosis for multi-vehicle systems, the presented decentralised fault diagnosis scheme in each vehicle reduces the communication and computation load by only using the information of the vehicle. By combing the sensor fault estimation and the COR control law, an FTCOR controller is proposed. Finally, the simulation results demonstrate the effectiveness of the FTCOR controller.

New constraints on slip rates and locking depths of the San Andreas Fault System from Sentinel-1A InSAR and GAGE GPS observations

Science.gov (United States)

Ward, L. A.; Smith-Konter, B. R.; Higa, J. T.; Xu, X.; Tong, X.; Sandwell, D. T.

2017-12-01

After over a decade of operation, the EarthScope (GAGE) Facility has now accumulated a wealth of GPS and InSAR data, that when successfully integrated, make it possible to image the entire San Andreas Fault System (SAFS) with unprecedented spatial coverage and resolution. Resulting surface velocity and deformation time series products provide critical boundary conditions needed for improving our understanding of how faults are loaded across a broad range of temporal and spatial scales. Moreover, our understanding of how earthquake cycle deformation is influenced by fault zone strength and crust/mantle rheology is still developing. To further study these processes, we construct a new 4D earthquake cycle model of the SAFS representing the time-dependent 3D velocity field associated with interseismic strain accumulation, co-seismic slip, and postseismic viscoelastic relaxation. This high-resolution California statewide model, spanning the Cerro Prieto fault to the south to the Maacama fault to the north, is constructed on a 500 m spaced grid and comprises variable slip and locking depths along 42 major fault segments. Secular deep slip is prescribed from the base of the locked zone to the base of the elastic plate while episodic shallow slip is prescribed from the historical earthquake record and geologic recurrence intervals. Locking depths and slip rates for all 42 fault segments are constrained by the newest GAGE Facility geodetic observations; 3169 horizontal GPS velocity measurements, combined with over 53,000 line-of-sight (LOS) InSAR velocity observations from Sentinel-1A, are used in a weighted least-squares inversion. To assess slip rate and locking depth sensitivity of a heterogeneous rheology model, we also implement variations in crustal rigidity throughout the plate boundary, assuming a coarse representation of shear modulus variability ranging from 20-40 GPa throughout the (low rigidity) Salton Trough and Basin and Range and the (high rigidity) Central

Study on reliability analysis based on multilevel flow models and fault tree method

International Nuclear Information System (INIS)

Chen Qiang; Yang Ming

2014-01-01

Multilevel flow models (MFM) and fault tree method describe the system knowledge in different forms, so the two methods express an equivalent logic of the system reliability under the same boundary conditions and assumptions. Based on this and combined with the characteristics of MFM, a method mapping MFM to fault tree was put forward, thus providing a way to establish fault tree rapidly and realizing qualitative reliability analysis based on MFM. Taking the safety injection system of pressurized water reactor nuclear power plant as an example, its MFM was established and its reliability was analyzed qualitatively. The analysis result shows that the logic of mapping MFM to fault tree is correct. The MFM is easily understood, created and modified. Compared with the traditional fault tree analysis, the workload is greatly reduced and the modeling time is saved. (authors)

Toward Expanding Tremor Observations in the Northern San Andreas Fault System in the 1990s

Science.gov (United States)

Damiao, L. G.; Dreger, D. S.; Nadeau, R. M.; Taira, T.; Guilhem, A.; Luna, B.; Zhang, H.

2015-12-01

The connection between tremor activity and active fault processes continues to expand our understanding of deep fault zone properties and deformation, the tectonic process, and the relationship of tremor to the occurrence of larger earthquakes. Compared to tremors in subduction zones, known tremor signals in California are ~5 to ~10 smaller in amplitude and duration. These characteristics, in addition to scarce geographic coverage, lack of continuous data (e.g., before mid-2001 at Parkfield), and absence of instrumentation sensitive enough to monitor these events have stifled tremor detection. The continuous monitoring of these events over a relatively short time period in limited locations may lead to a parochial view of the tremor phenomena and its relationship to fault, tectonic, and earthquake processes. To help overcome this, we have embarked on a project to expand the geographic and temporal scope of tremor observation along the Northern SAF system using available continuous seismic recordings from a broad array of 100s of surface seismic stations from multiple seismic networks. Available data for most of these stations also extends back into the mid-1990s. Processing and analysis of tremor signal from this large and low signal-to-noise dataset requires a heavily automated, data-science type approach and specialized techniques for identifying and extracting reliable data. We report here on the automated, envelope based methodology we have developed. We finally compare our catalog results with pre-existing tremor catalogs in the Parkfield area.

Line-to-Line Fault Analysis and Location in a VSC-Based Low-Voltage DC Distribution Network

Directory of Open Access Journals (Sweden)

Shi-Min Xue

2018-03-01

Full Text Available A DC cable short-circuit fault is the most severe fault type that occurs in DC distribution networks, having a negative impact on transmission equipment and the stability of system operation. When a short-circuit fault occurs in a DC distribution network based on a voltage source converter (VSC, an in-depth analysis and characterization of the fault is of great significance to establish relay protection, devise fault current limiters and realize fault location. However, research on short-circuit faults in VSC-based low-voltage DC (LVDC systems, which are greatly different from high-voltage DC (HVDC systems, is currently stagnant. The existing research in this area is not conclusive, with further study required to explain findings in HVDC systems that do not fit with simulated results or lack thorough theoretical analyses. In this paper, faults are divided into transient- and steady-state faults, and detailed formulas are provided. A more thorough and practical theoretical analysis with fewer errors can be used to develop protection schemes and short-circuit fault locations based on transient- and steady-state analytic formulas. Compared to the classical methods, the fault analyses in this paper provide more accurate computed results of fault current. Thus, the fault location method can rapidly evaluate the distance between the fault and converter. The analyses of error increase and an improved handshaking method coordinating with the proposed location method are presented.

Fault architecture and growth in clay-limestone alternations: insights from field observations in the SE Basin, France

International Nuclear Information System (INIS)

Rocher, M.; Roche, V.; Homberg, C.

2012-01-01

Document available in extended abstract form only. The Callovo-Oxfordian (COX) clayey formation is currently studied by Andra in 'Meuse/Haute- Marne' (MHM), eastern Paris basin (France), for hosting a disposal of high level and intermediate, long-lived radioactive waste. As an independent organisation performing safety reviews for the Nuclear Safety Authority, IRSN conducts studies in support of the review of this disposal project. This nearly 130 m-thick clayey formation is surrounded by two 250 m-thick limestone formations. In such limestone/clay alternations, tectonic fracturing is often observed within limestones and propagates in some cases to clay layers. Such a propagation through the COX within or close to the disposal area could diminish its containment ability by creating preferential pathways of radioactive solute towards limestones. Nevertheless, minor to moderate fracturing is difficult to investigate in hectometre scale multilayer systems such as COX: seismic reflexion surveys only provide data on major faults, drilling data are too localised and clays have a 'bad-land' aspect at surface. The aim of this study is to provide a model of fracturing across clay-limestone alternations so as to strengthen the assessment of their possible development. We thus investigated fracturing within decametre-sized clay-limestone alternations, located in the South-Eastern Basin (France), to determine the evolution of fault architecture during its growth. After analysis of the possible scale effects using data from other analogous fields, an application to the COX in MHM is presented. We studied minor normal faults that reflect various stages of development, from simple fault planes restricted to limestones to complex fault zones propagated across several clay-limestone layers. The analysis of the fault characteristics, the construction of displacement profiles and the results obtained using numerical models enlighten fault growth processes, i.e. nucleation

3D Dynamic Rupture Simulations along Dipping Faults, with a focus on the Wasatch Fault Zone, Utah

Science.gov (United States)

Withers, K.; Moschetti, M. P.

2017-12-01

We study dynamic rupture and ground motion from dip-slip faults in regions that have high-seismic hazard, such as the Wasatch fault zone, Utah. Previous numerical simulations have modeled deterministic ground motion along segments of this fault in the heavily populated regions near Salt Lake City but were restricted to low frequencies ( 1 Hz). We seek to better understand the rupture process and assess broadband ground motions and variability from the Wasatch Fault Zone by extending deterministic ground motion prediction to higher frequencies (up to 5 Hz). We perform simulations along a dipping normal fault (40 x 20 km along strike and width, respectively) with characteristics derived from geologic observations to generate a suite of ruptures > Mw 6.5. This approach utilizes dynamic simulations (fully physics-based models, where the initial stress drop and friction law are imposed) using a summation by parts (SBP) method. The simulations include rough-fault topography following a self-similar fractal distribution (over length scales from 100 m to the size of the fault) in addition to off-fault plasticity. Energy losses from heat and other mechanisms, modeled as anelastic attenuation, are also included, as well as free-surface topography, which can significantly affect ground motion patterns. We compare the effect of material structure and both rate and state and slip-weakening friction laws have on rupture propagation. The simulations show reduced slip and moment release in the near surface with the inclusion of plasticity, better agreeing with observations of shallow slip deficit. Long-wavelength fault geometry imparts a non-uniform stress distribution along both dip and strike, influencing the preferred rupture direction and hypocenter location, potentially important for seismic hazard estimation.

Guideline for Bayesian Net based Software Fault Estimation Method for Reactor Protection System

International Nuclear Information System (INIS)

Eom, Heung Seop; Park, Gee Yong; Jang, Seung Cheol

2011-01-01

The purpose of this paper is to provide a preliminary guideline for the estimation of software faults in a safety-critical software, for example, reactor protection system's software. As the fault estimation method is based on Bayesian Net which intensively uses subjective probability and informal data, it is necessary to define formal procedure of the method to minimize the variability of the results. The guideline describes assumptions, limitations and uncertainties, and the product of the fault estimation method. The procedure for conducting a software fault-estimation method is then outlined, highlighting the major tasks involved. The contents of the guideline are based on our own experience and a review of research guidelines developed for a PSA

Diagnosis of Constant Faults in Read-Once Contact Networks over Finite Bases using Decision Trees

KAUST Repository

Busbait, Monther I.

2014-01-01

We study the depth of decision trees for diagnosis of constant faults in read-once contact networks over finite bases. This includes diagnosis of 0-1 faults, 0 faults and 1 faults. For any finite basis, we prove a linear upper bound on the minimum

Robust Sensor Faults Reconstruction for a Class of Uncertain Linear Systems Using a Sliding Mode Observer: An LMI Approach

International Nuclear Information System (INIS)

Iskander, Boulaabi; Faycal, Ben Hmida; Moncef, Gossa; Anis, Sellami

2009-01-01

This paper presents a design method of a Sliding Mode Observer (SMO) for robust sensor faults reconstruction of systems with matched uncertainty. This class of uncertainty requires a known upper bound. The basic idea is to use the H ∞ concept to design the observer, which minimizes the effect of the uncertainty on the reconstruction of the sensor faults. Specifically, we applied the equivalent output error injection concept from previous work in Fault Detection and Isolation (FDI) scheme. Then, these two problems of design and reconstruction can be expressed and numerically formulate via Linear Matrix Inequalities (LMIs) optimization. Finally, a numerical example is given to illustrate the validity and the applicability of the proposed approach.

Sensor fault detection and recovery in satellite attitude control

Science.gov (United States)

Nasrolahi, Seiied Saeed; Abdollahi, Farzaneh

2018-04-01

This paper proposes an integrated sensor fault detection and recovery for the satellite attitude control system. By introducing a nonlinear observer, the healthy sensor measurements are provided. Considering attitude dynamics and kinematic, a novel observer is developed to detect the fault in angular rate as well as attitude sensors individually or simultaneously. There is no limit on type and configuration of attitude sensors. By designing a state feedback based control signal and Lyapunov stability criterion, the uniformly ultimately boundedness of tracking errors in the presence of sensor faults is guaranteed. Finally, simulation results are presented to illustrate the performance of the integrated scheme.

Fault Diagnosis of Rolling Bearings Based on EWT and KDEC

Directory of Open Access Journals (Sweden)

Mingtao Ge

2017-12-01

Full Text Available This study proposes a novel fault diagnosis method that is based on empirical wavelet transform (EWT and kernel density estimation classifier (KDEC, which can well diagnose fault type of the rolling element bearings. With the proposed fault diagnosis method, the vibration signal of rolling element bearing was firstly decomposed into a series of F modes by EWT, and the root mean square, kurtosis, and skewness of the F modes were computed and combined into the feature vector. According to the characteristics of kernel density estimation, a classifier based on kernel density estimation and mutual information was proposed. Then, the feature vectors were input into the KDEC for training and testing. The experimental results indicated that the proposed method can effectively identify three different operative conditions of rolling element bearings, and the accuracy rates was higher than support vector machine (SVM classifier and back-propagation (BP neural network classifier.

Fault diagnostics of dynamic system operation using a fault tree based method

International Nuclear Information System (INIS)

Hurdle, E.E.; Bartlett, L.M.; Andrews, J.D.

2009-01-01

For conventional systems, their availability can be considerably improved by reducing the time taken to restore the system to the working state when faults occur. Fault identification can be a significant proportion of the time taken in the repair process. Having diagnosed the problem the restoration of the system back to its fully functioning condition can then take place. This paper expands the capability of previous approaches to fault detection and identification using fault trees for application to dynamically changing systems. The technique has two phases. The first phase is modelling and preparation carried out offline. This gathers information on the effects that sub-system failure will have on the system performance. Causes of the sub-system failures are developed in the form of fault trees. The second phase is application. Sensors are installed on the system to provide information about current system performance from which the potential causes can be deduced. A simple system example is used to demonstrate the features of the method. To illustrate the potential for the method to deal with additional system complexity and redundancy, a section from an aircraft fuel system is used. A discussion of the results is provided.

Method of fault diagnosis in nuclear power plant base on genetic algorithm and knowledge base

International Nuclear Information System (INIS)

Zhou Yangping; Zhao Bingquan

2000-01-01

Via using the knowledge base, combining Genetic Algorithm and classical probability and contraposing the characteristic of the fault diagnosis of NPP. The authors put forward a method of fault diagnosis. In the process of fault diagnosis, this method contact the state of NPP with the colony in GA and transform the colony to get the individual that adapts to the condition. On the 950MW full size simulator in Beijing NPP simulation training center, experimentation shows it has comparative adaptability to the imperfection of expert knowledge, illusive signal and other instance

Toward a physics-based rate and state friction law for earthquake nucleation processes in fault zones with granular gouge

Science.gov (United States)

Ferdowsi, B.; Rubin, A. M.

2017-12-01

Numerical simulations of earthquake nucleation rely on constitutive rate and state evolution laws to model earthquake initiation and propagation processes. The response of different state evolution laws to large velocity increases is an important feature of these constitutive relations that can significantly change the style of earthquake nucleation in numerical models. However, currently there is not a rigorous understanding of the physical origins of the response of bare rock or gouge-filled fault zones to large velocity increases. This in turn hinders our ability to design physics-based friction laws that can appropriately describe those responses. We here argue that most fault zones form a granular gouge after an initial shearing phase and that it is the behavior of the gouge layer that controls the fault friction. We perform numerical experiments of a confined sheared granular gouge under a range of confining stresses and driving velocities relevant to fault zones and apply 1-3 order of magnitude velocity steps to explore dynamical behavior of the system from grain- to macro-scales. We compare our numerical observations with experimental data from biaxial double-direct-shear fault gouge experiments under equivalent loading and driving conditions. Our intention is to first investigate the degree to which these numerical experiments, with Hertzian normal and Coulomb friction laws at the grain-grain contact scale and without any time-dependent plasticity, can reproduce experimental fault gouge behavior. We next compare the behavior observed in numerical experiments with predictions of the Dieterich (Aging) and Ruina (Slip) friction laws. Finally, the numerical observations at the grain and meso-scales will be used for designing a rate and state evolution law that takes into account recent advances in rheology of granular systems, including local and non-local effects, for a wide range of shear rates and slow and fast deformation regimes of the fault gouge.

Scattering transform and LSPTSVM based fault diagnosis of rotating machinery

Science.gov (United States)

Ma, Shangjun; Cheng, Bo; Shang, Zhaowei; Liu, Geng

2018-05-01

This paper proposes an algorithm for fault diagnosis of rotating machinery to overcome the shortcomings of classical techniques which are noise sensitive in feature extraction and time consuming for training. Based on the scattering transform and the least squares recursive projection twin support vector machine (LSPTSVM), the method has the advantages of high efficiency and insensitivity for noise signal. Using the energy of the scattering coefficients in each sub-band, the features of the vibration signals are obtained. Then, an LSPTSVM classifier is used for fault diagnosis. The new method is compared with other common methods including the proximal support vector machine, the standard support vector machine and multi-scale theory by using fault data for two systems, a motor bearing and a gear box. The results show that the new method proposed in this study is more effective for fault diagnosis of rotating machinery.

Adaptive Fault Tolerance for Many-Core Based Space-Borne Computing

Science.gov (United States)

James, Mark; Springer, Paul; Zima, Hans

2010-01-01

This paper describes an approach to providing software fault tolerance for future deep-space robotic NASA missions, which will require a high degree of autonomy supported by an enhanced on-board computational capability. Such systems have become possible as a result of the emerging many-core technology, which is expected to offer 1024-core chips by 2015. We discuss the challenges and opportunities of this new technology, focusing on introspection-based adaptive fault tolerance that takes into account the specific requirements of applications, guided by a fault model. Introspection supports runtime monitoring of the program execution with the goal of identifying, locating, and analyzing errors. Fault tolerance assertions for the introspection system can be provided by the user, domain-specific knowledge, or via the results of static or dynamic program analysis. This work is part of an on-going project at the Jet Propulsion Laboratory in Pasadena, California.

Learning and case-based reasoning for faults diagnosis-aiding in nuclear power plants

International Nuclear Information System (INIS)

Nicolini, C.

1998-01-01

The aim of this thesis is the design of a faults diagnosis-aiding system in a nuclear facility of the Cea. Actually the existing system allows the optimization of the production processes in regular operating conditions. Meanwhile during accidental events, the alarms, managed by threshold, are bringing no relevant information. To increase the reliability and the safety, the human operator needs a faults diagnosis-aiding system. The developed system, SECAPI, combines problem solving techniques and automatic learning techniques, that allow the diagnosis and the the simulation of various faults happening on nuclear facilities. Its reasoning principle uses case-based and rules-based techniques. SECAPI owns a learning module which reads out knowledge connected with faults. It can then simulate various faults, using the inductive logical computing. SECAPI has been applied on a radioactive tritium treatment operating channel, at the Cea with good results. (A.L.B.)

A Novel Mittag-Leffler Kernel Based Hybrid Fault Diagnosis Method for Wheeled Robot Driving System

Directory of Open Access Journals (Sweden)

Xianfeng Yuan

2015-01-01

presents a novel hybrid fault diagnosis framework based on Mittag-Leffler kernel (ML-kernel support vector machine (SVM and Dempster-Shafer (D-S fusion. Using sensor data sampled under different running conditions, the proposed approach initially establishes multiple principal component analysis (PCA models for fault feature extraction. The fault feature vectors are then applied to train the probabilistic SVM (PSVM classifiers that arrive at a preliminary fault diagnosis. To improve the accuracy of preliminary results, a novel ML-kernel based PSVM classifier is proposed in this paper, and the positive definiteness of the ML-kernel is proved as well. The basic probability assignments (BPAs are defined based on the preliminary fault diagnosis results and their confidence values. Eventually, the final fault diagnosis result is archived by the fusion of the BPAs. Experimental results show that the proposed framework not only is capable of detecting and identifying the faults in the robot driving system, but also has better performance in stability and diagnosis accuracy compared with the traditional methods.

Structure, Kinematics and Origin of Radial Faults: 3D Seismic Observations from the Santos Basin, offshore Brazil

Science.gov (United States)

Coleman, Alexander; Jackson, Christopher A.-L.

2017-04-01

Salt stock growth is typically accompanied by the development of geometrically and kinematically complex fault networks in the surrounding country rock. The most common networks comprise radial faults; these are characterised by low displacement (stock into flanking strata. Radial faults are commonly observed in an arched, unpierced roof developed above a rising salt stock; in these cases, the faults are typically well-imaged seismically and likely form due to outer-arc extension during overburden stretching. Radial faults are also found at deeper structural levels, in strata flanking the diapir stem; in these cases, they are typically less well-imaged, thus their structure, kinematics and origin are less well understood. Furthermore, understanding the growth of radial faults may provide insights into hydrocarbon reservoir compartmentalisation and the evolution of neighbouring salt stocks. Here, we use high-quality 3D seismic reflection data from the Santos Basin, offshore Brazil to determine the structure and kinematics, and infer the likely origin of exceptionally well-imaged radial faults overlying and flanking a mature salt stock. Furthermore, we compare the geometric (e.g. throw, geometry, spacing, distribution etc.) and kinematic (e.g. timing of formation and duration of activity) characteristics of radial faults at both structural levels, allowing us to infer their temporal relationship and likely origins. We show that radial faults regardless of their structural level typically have aspect ratios of c. 1.8 - 2, are laterally-restricted in the vicinity of the salt, and have lengths of indices of c. 1, with low throw gradients of 0.05 - 0.1 at the upper tip indicate that radial faults were likely blind. Throws range from 5 - 80 ms, with throw-maxima within 1 - 2 radii of the salt diapir. However, we note that the position of the throw maxima is not at the same level for all radial faults. We propose that radial faults nucleate and initially grow as blind

Gear Fault Detection Based on Teager-Huang Transform

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Hui Li

2010-01-01

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

Multiple-Fault Detection Methodology Based on Vibration and Current Analysis Applied to Bearings in Induction Motors and Gearboxes on the Kinematic Chain

Directory of Open Access Journals (Sweden)

Juan Jose Saucedo-Dorantes

2016-01-01

Full Text Available Gearboxes and induction motors are important components in industrial applications and their monitoring condition is critical in the industrial sector so as to reduce costs and maintenance downtimes. There are several techniques associated with the fault diagnosis in rotating machinery; however, vibration and stator currents analysis are commonly used due to their proven reliability. Indeed, vibration and current analysis provide fault condition information by means of the fault-related spectral component identification. This work presents a methodology based on vibration and current analysis for the diagnosis of wear in a gearbox and the detection of bearing defect in an induction motor both linked to the same kinematic chain; besides, the location of the fault-related components for analysis is supported by the corresponding theoretical models. The theoretical models are based on calculation of characteristic gearbox and bearings fault frequencies, in order to locate the spectral components of the faults. In this work, the influence of vibrations over the system is observed by performing motor current signal analysis to detect the presence of faults. The obtained results show the feasibility of detecting multiple faults in a kinematic chain, making the proposed methodology suitable to be used in the application of industrial machinery diagnosis.

A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis

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Muhammad Sohaib

2017-12-01

Full Text Available Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE-based deep neural networks (DNNs to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs and backpropagation neural networks (BPNNs.

A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis.

Science.gov (United States)

Sohaib, Muhammad; Kim, Cheol-Hong; Kim, Jong-Myon

2017-12-11

Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE)-based deep neural networks (DNNs) to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs) and backpropagation neural networks (BPNNs).

Protection algorithm for a wind turbine generator based on positive- and negative-sequence fault components

DEFF Research Database (Denmark)

Zheng, Tai-Ying; Cha, Seung-Tae; Crossley, Peter A.

2011-01-01

A protection relay for a wind turbine generator (WTG) based on positive- and negative-sequence fault components is proposed in the paper. The relay uses the magnitude of the positive-sequence component in the fault current to detect a fault on a parallel WTG, connected to the same power collection...... feeder, or a fault on an adjacent feeder; but for these faults, the relay remains stable and inoperative. A fault on the power collection feeder or a fault on the collection bus, both of which require an instantaneous tripping response, are distinguished from an inter-tie fault or a grid fault, which...... in the fault current is used to decide on either instantaneous or delayed operation. The operating performance of the relay is then verified using various fault scenarios modelled using EMTP-RV. The scenarios involve changes in the position and type of fault, and the faulted phases. Results confirm...

A Novel Bearing Fault Diagnosis Method Based on Gaussian Restricted Boltzmann Machine

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Xiao-hui He

2016-01-01

Full Text Available To realize the fault diagnosis of bearing effectively, this paper presents a novel bearing fault diagnosis method based on Gaussian restricted Boltzmann machine (Gaussian RBM. Vibration signals are firstly resampled to the same equivalent speed. Subsequently, the envelope spectrums of the resampled data are used directly as the feature vectors to represent the fault types of bearing. Finally, in order to deal with the high-dimensional feature vectors based on envelope spectrum, a classifier model based on Gaussian RBM is applied. Gaussian RBM has the ability to provide a closed-form representation of the distribution underlying the training data, and it is very convenient for modeling high-dimensional real-valued data. Experiments on 10 different data sets verify the performance of the proposed method. The superiority of Gaussian RBM classifier is also confirmed by comparing with other classifiers, such as extreme learning machine, support vector machine, and deep belief network. The robustness of the proposed method is also studied in this paper. It can be concluded that the proposed method can realize the bearing fault diagnosis accurately and effectively.

The Terminology of Fault Zones in the Brittle Regime: Making Field Observations More Useful to the End User

Science.gov (United States)

Shipton, Z.; Caine, J. S.; Lunn, R. J.

2013-12-01

Geologists are tiny creatures living on the 2-and-a-bit-D surface of a sphere who observe essentially 1D vanishingly small portions (boreholes, roadcuts, stream and beach sections) of complex, 4D tectonic-scale structures. Field observations of fault zones are essential to understand the processes of fault growth and to make predictions of fault zone mechanical and hydraulic properties at depth. Here, we argue that a failure of geologists to communicate their knowledge effectively to other scientists/engineers can lead to unrealistic assumptions being made about fault properties, and may result in poor economic performance and a lack of robustness in industrial safety cases. Fault zones are composed of many heterogeneously distributed deformation-related elements. Low permeability features include regions of intense grain-size reduction, pressure solution, cementation and shale smears. Other elements are likely to have enhanced permeability through fractures and breccias. Slip surfaces can have either enhanced or reduced permeability depending on whether they are open or closed, and the local stress state. The highly variable nature of 1) the architecture of faults and 2) the properties of deformation-related elements demonstrates that there are many factors controlling the evolution of fault zone internal structures (fault architecture). The aim of many field studies of faults is to provide data to constrain predictions at depth. For these data to be useful, pooling of data from multiple sites is usually necessary. This effort is frequently hampered by variability in the usage of fault terminologies. In addition, these terms are often used in ways as to make it easy for 'end-users' such as petroleum reservoir engineers, mining geologists, and seismologists to mis-interpret or over-simplify the implications of field studies. Field geologists are comfortable knowing that if you walk along strike or up dip of a fault zone you will find variations in fault rock type

Modeling Sensor Reliability in Fault Diagnosis Based on Evidence Theory

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Kaijuan Yuan

2016-01-01

Full Text Available Sensor data fusion plays an important role in fault diagnosis. Dempster–Shafer (D-R evidence theory is widely used in fault diagnosis, since it is efficient to combine evidence from different sensors. However, under the situation where the evidence highly conflicts, it may obtain a counterintuitive result. To address the issue, a new method is proposed in this paper. Not only the statistic sensor reliability, but also the dynamic sensor reliability are taken into consideration. The evidence distance function and the belief entropy are combined to obtain the dynamic reliability of each sensor report. A weighted averaging method is adopted to modify the conflict evidence by assigning different weights to evidence according to sensor reliability. The proposed method has better performance in conflict management and fault diagnosis due to the fact that the information volume of each sensor report is taken into consideration. An application in fault diagnosis based on sensor fusion is illustrated to show the efficiency of the proposed method. The results show that the proposed method improves the accuracy of fault diagnosis from 81.19% to 89.48% compared to the existing methods.

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

Science.gov (United States)

Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

2016-07-01

Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Bayes-Based Fault Discrimination in Wide Area Backup Protection

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WANG, Z.

2012-02-01

Full Text Available Multivariate statistical analysis is an effective tool to finish the fault location for electric power system. In Bayesian discriminant analysis as a subbranch, by the research of several populations, one can calculate the conditional probability that some samples belong to these populations, and compare the corresponding probability. The sample will be classified as population with maximum probability. In this paper, based on Bayesian discriminant analysis principle, a great number of simulation examples have confirmed that the results of Bayesian fault discriminant in wide area backup protection are accurate and reliable.

Fault Detection for Large-Scale Railway Maintenance Equipment Base on Wireless Sensor Networks

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Junfu Yu

2014-04-01

Full Text Available Focusing on the fault detection application for large-scale railway maintenance equipment with the specialties of low-cost, energy efficiency, collecting data of the function units. This paper proposed energy efficiency, convenient installation fault detection application using Sigsbee wireless sensor networks, which Sigsbee is the most widely used protocol based on IEEE 802.15.4. This paper proposed a systematic application from hardware design using STM32F103 chips as processer, to software system. Fault detection application is the basic part of the fault diagnose system, wireless sensor nodes of the fault detection application with different kinds of sensors for verities function units communication by Sigsbee to collecting and sending basic working status data to the home gateway, then data will be sent to the fault diagnose system.

Factors for simultaneous rupture assessment of active fault. Part 1. Fault geometry and slip-distribution based on tectonic geomorphological and paleoseismological investigations

International Nuclear Information System (INIS)

Sasaki, Toshinori; Ueta, Keiichi

2012-01-01

It is important to evaluate the magnitude of an earthquake caused by multiple active faults, taking into account the simultaneous effects. The simultaneity of adjacent active faults is often decided on the basis of geometric distances except for the cases in which paleoseismic records of these faults are well known. We have been studying the step area between the Nukumi fault and the Neodani fault, which appeared as consecutive ruptures in the 1891 Nobi earthquake, since 2009. The purpose of this study is to establish innovation in valuation technique of the simultaneity of adjacent active faults in addition to the techniques based on the paleoseismic record and the geometric distance. The present work is intended to clarify the distribution of tectonic geomorphology along the Nukumi fault and the Neodani fault by high-resolution interpretations of airborne LiDAR DEM and aerial photograph, and the field survey of outcrops and location survey. As a result of topographic survey, we found consecutive tectonic topography which is left lateral displacement of ridge and valley lines and reverse scarplets along these faults in dense vegetation area. We have found several new outcrops in this area where the surface ruptures of the 1891 Nobi earthquake have not been known. At the several outcrops, humic layer whose age is from 14th century to 19th century by 14C age dating was deformed by the active fault. We conclude that the surface rupture of Nukumi fault in the 1891 Nobi earthquake is continuous to 12km southeast of Nukumi village. In other words, these findings indicate that there is 10-12km parallel overlap zone between the surface rupture of the southeastern end of Nukumi fault and the northwestern end of Neodani fault. (author)

Intelligent Fault Diagnosis of HVCB with Feature Space Optimization-Based Random Forest.

Science.gov (United States)

Ma, Suliang; Chen, Mingxuan; Wu, Jianwen; Wang, Yuhao; Jia, Bowen; Jiang, Yuan

2018-04-16

Mechanical faults of high-voltage circuit breakers (HVCBs) always happen over long-term operation, so extracting the fault features and identifying the fault type have become a key issue for ensuring the security and reliability of power supply. Based on wavelet packet decomposition technology and random forest algorithm, an effective identification system was developed in this paper. First, compared with the incomplete description of Shannon entropy, the wavelet packet time-frequency energy rate (WTFER) was adopted as the input vector for the classifier model in the feature selection procedure. Then, a random forest classifier was used to diagnose the HVCB fault, assess the importance of the feature variable and optimize the feature space. Finally, the approach was verified based on actual HVCB vibration signals by considering six typical fault classes. The comparative experiment results show that the classification accuracy of the proposed method with the origin feature space reached 93.33% and reached up to 95.56% with optimized input feature vector of classifier. This indicates that feature optimization procedure is successful, and the proposed diagnosis algorithm has higher efficiency and robustness than traditional methods.

A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

Science.gov (United States)

Xue, Xiaoming; Zhou, Jianzhong

2017-01-01

To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A fault diagnosis and operation advising cooperative expert system based on multi-agent technology

Energy Technology Data Exchange (ETDEWEB)

Zhao, W.; Bai, X.; Ding, J.; Fang, Z.; Li, Z. [China Electric Power Research Inst., Haidian District, Beijing (China)

2006-07-01

Power systems are becoming more and more complex. In addition, the amount of real-time alarm messages from the supervisory control and data acquisition, energy management systems and wide area measurement systems about switchgear and protection are also increasing to a point far beyond the operator's capacity to digest the information. Research and development of a fault diagnosis system is necessary for the timely identification of fault or malfunctioning devices and for realizing the automation functions of dynamic supervisory control system. The prevailing fault diagnosis approaches in power systems include the expert system, artificial neural network, and fault diagnosis based on optimal theory. This paper discussed the advantages and disadvantages of each of these approaches for diagnosing faults. The paper also proposed a new fault diagnosis and operational processing approach based on a cooperative expert system combined with a multi-agent architecture. For solving complex and correlative faults, the cooperative expert system can overcome the deficiency of a single expert system. It can be used not only for diagnosing complex faults in real time but also in providing timely operational advice. The proposed system has been used successfully in a district power grid in China's Shangdong province for a year. 9 refs., 4 figs.

Fault diagnosis for tilting-pad journal bearing based on SVD and LMD

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Zhang Xiaotao

2016-01-01

Full Text Available Aiming at fault diagnosis for tilting-pad journal bearing with fluid support developed recently, a new method based on singular value decomposition (SVD and local mean decomposition (LMD is proposed. First, the phase space reconstruction of Hankel matrix and SVD method are used as pre-filter process unit to reduce the random noises in the original signal. Then the purified signal is decomposed by LMD into a series of production functions (PFs. Based on PFs, time frequency map and marginal spectrum can be obtained for fault diagnosis. Finally, this method is applied to numerical simulation and practical experiment data. The results show that the proposed method can effectively detect fault features of tilting-pad journal bearing.

Diagnosis of Constant Faults in Read-Once Contact Networks over Finite Bases using Decision Trees

KAUST Repository

Busbait, Monther I.

2014-05-01

We study the depth of decision trees for diagnosis of constant faults in read-once contact networks over finite bases. This includes diagnosis of 0-1 faults, 0 faults and 1 faults. For any finite basis, we prove a linear upper bound on the minimum depth of decision tree for diagnosis of constant faults depending on the number of edges in a contact network over that basis. Also, we obtain asymptotic bounds on the depth of decision trees for diagnosis of each type of constant faults depending on the number of edges in contact networks in the worst case per basis. We study the set of indecomposable contact networks with up to 10 edges and obtain sharp coefficients for the linear upper bound for diagnosis of constant faults in contact networks over bases of these indecomposable contact networks. We use a set of algorithms, including one that we create, to obtain the sharp coefficients.

Faulting of gas-hydrate-bearing marine sediments - contribution to permeability

Science.gov (United States)

Dillon, William P.; Holbrook, W.S.; Drury, Rebecca; Gettrust, Joseph; Hutchinson, Deborah; Booth, James; Taylor, Michael

1997-01-01

Extensive faulting is observed in sediments containing high concentrations of methane hydrate off the southeastern coast of the United States. Faults that break the sea floor show evidence of both extension and shortening; mud diapirs are also present. The zone of recent faulting apparently extends from the ocean floor down to the base of gas-hydrate stability. We infer that the faulting resulted from excess pore pressure in gas trapped beneath the gas hydrate-beating layer and/or weakening and mobilization of sediments in the region just below the gas-hydrate stability zone. In addition to the zone of surface faults, we identified two buried zones of faulting, that may have similar origins. Subsurface faulted zones appear to act as gas traps.

Constructing constitutive relationships for seismic and aseismic fault slip

Science.gov (United States)

Beeler, N.M.

2009-01-01

For the purpose of modeling natural fault slip, a useful result from an experimental fault mechanics study would be a physically-based constitutive relation that well characterizes all the relevant observations. This report describes an approach for constructing such equations. Where possible the construction intends to identify or, at least, attribute physical processes and contact scale physics to the observations such that the resulting relations can be extrapolated in conditions and scale between the laboratory and the Earth. The approach is developed as an alternative but is based on Ruina (1983) and is illustrated initially by constructing a couple of relations from that study. In addition, two example constitutive relationships are constructed; these describe laboratory observations not well-modeled by Ruina's equations: the unexpected shear-induced weakening of silica-rich rocks at high slip speed (Goldsby and Tullis, 2002) and fault strength in the brittle ductile transition zone (Shimamoto, 1986). The examples, provided as illustration, may also be useful for quantitative modeling.

An empirically based steady state friction law and implications for fault stability.

Science.gov (United States)

Spagnuolo, E; Nielsen, S; Violay, M; Di Toro, G

2016-04-16

Empirically based rate-and-state friction laws (RSFLs) have been proposed to model the dependence of friction forces with slip and time. The relevance of the RSFL for earthquake mechanics is that few constitutive parameters define critical conditions for fault stability (i.e., critical stiffness and frictional fault behavior). However, the RSFLs were determined from experiments conducted at subseismic slip rates ( V   0.1 m/s) remains questionable on the basis of the experimental evidence of (1) large dynamic weakening and (2) activation of particular fault lubrication processes at seismic slip rates. Here we propose a modified RSFL (MFL) based on the review of a large published and unpublished data set of rock friction experiments performed with different testing machines. The MFL, valid at steady state conditions from subseismic to seismic slip rates (0.1 µm/s fault frictional stability with implications for slip event styles and relevance for models of seismic rupture nucleation, propagation, and arrest.

Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I-V characteristics

International Nuclear Information System (INIS)

Chen, Zhicong; Wu, Lijun; Cheng, Shuying; Lin, Peijie; Wu, Yue; Lin, Wencheng

2017-01-01

Highlights: •An improved Simulink based modeling method is proposed for PV modules and arrays. •Key points of I-V curves and PV model parameters are used as the feature variables. •Kernel extreme learning machine (KELM) is explored for PV arrays fault diagnosis. •The parameters of KELM algorithm are optimized by the Nelder-Mead simplex method. •The optimized KELM fault diagnosis model achieves high accuracy and reliability. -- Abstract: Fault diagnosis of photovoltaic (PV) arrays is important for improving the reliability, efficiency and safety of PV power stations, because the PV arrays usually operate in harsh outdoor environment and tend to suffer various faults. Due to the nonlinear output characteristics and varying operating environment of PV arrays, many machine learning based fault diagnosis methods have been proposed. However, there still exist some issues: fault diagnosis performance is still limited due to insufficient monitored information; fault diagnosis models are not efficient to be trained and updated; labeled fault data samples are hard to obtain by field experiments. To address these issues, this paper makes contribution in the following three aspects: (1) based on the key points and model parameters extracted from monitored I-V characteristic curves and environment condition, an effective and efficient feature vector of seven dimensions is proposed as the input of the fault diagnosis model; (2) the emerging kernel based extreme learning machine (KELM), which features extremely fast learning speed and good generalization performance, is utilized to automatically establish the fault diagnosis model. Moreover, the Nelder-Mead Simplex (NMS) optimization method is employed to optimize the KELM parameters which affect the classification performance; (3) an improved accurate Simulink based PV modeling approach is proposed for a laboratory PV array to facilitate the fault simulation and data sample acquisition. Intensive fault experiments are

The Observation of Fault Finiteness and Rapid Velocity Variation in Pnl Waveforms for the Mw 6.5, San Simeon, California Earthquake

Science.gov (United States)

Konca, A. O.; Ji, C.; Helmberger, D. V.

2004-12-01

We observed the effect of the fault finiteness in the Pnl waveforms from regional distances (4° to 12° ) for the Mw6.5 San Simeon Earthquake on 22 December 2003. We aimed to include more of the high frequencies (2 seconds and longer periods) than the studies that use regional data for focal solutions (5 to 8 seconds and longer periods). We calculated 1-D synthetic seismograms for the Pn_l portion for both a point source, and a finite fault solution. The comparison of the point source and finite fault waveforms with data show that the first several seconds of the point source synthetics have considerably higher amplitude than the data, while finite fault does not have a similar problem. This can be explained by reversely polarized depth phases overlapping with the P waves from the later portion of the fault, and causing smaller amplitudes for the beginning portion of the seismogram. This is clearly a finite fault phenomenon; therefore, can not be explained by point source calculations. Moreover, the point source synthetics, which are calculated with a focal solution from a long period regional inversion, are overestimating the amplitude by three to four times relative to the data amplitude, while finite fault waveforms have the similar amplitudes to the data. Hence, a moment estimation based only on the point source solution of the regional data could have been wrong by half of magnitude. We have also calculated the shifts of synthetics relative to data to fit the seismograms. Our results reveal that the paths from Central California to the south are faster than to the paths to the east and north. The P wave arrival to the TUC station in Arizona is 4 seconds earlier than the predicted Southern California model, while most stations to the east are delayed around 1 second. The observed higher uppermost mantle velocities to the south are consistent with some recent tomographic models. Synthetics generated with these models significantly improves the fits and the

Frequency Based Fault Detection in Wind Turbines

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2014-01-01

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

Fault diagnosis

Science.gov (United States)

Abbott, Kathy

1990-01-01

The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to

Fault-Tolerant Approach for Modular Multilevel Converters under Submodule Faults

DEFF Research Database (Denmark)

Deng, Fujin; Tian, Yanjun; Zhu, Rongwu

2016-01-01

The modular multilevel converter (MMC) is attractive for medium- or high-power applications because of the advantages of its high modularity, availability, and high power quality. The fault-tolerant operation is one of the important issues for the MMC. This paper proposed a fault-tolerant approach...... for the MMC under submodule (SM) faults. The characteristic of the MMC with arms containing different number of healthy SMs under faults is analyzed. Based on the characteristic, the proposed approach can effectively keep the MMC operation as normal under SM faults. It can effectively improve the MMC...

Fault detection of Tennessee Eastman process based on topological features and SVM

Science.gov (United States)

Zhao, Huiyang; Hu, Yanzhu; Ai, Xinbo; Hu, Yu; Meng, Zhen

2018-03-01

Fault detection in industrial process is a popular research topic. Although the distributed control system(DCS) has been introduced to monitor the state of industrial process, it still cannot satisfy all the requirements for fault detection of all the industrial systems. In this paper, we proposed a novel method based on topological features and support vector machine(SVM), for fault detection of industrial process. The proposed method takes global information of measured variables into account by complex network model and predicts whether a system has generated some faults or not by SVM. The proposed method can be divided into four steps, i.e. network construction, network analysis, model training and model testing respectively. Finally, we apply the model to Tennessee Eastman process(TEP). The results show that this method works well and can be a useful supplement for fault detection of industrial process.

A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine

Science.gov (United States)

Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong

2015-08-01

Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.

Improved Tensor-Based Singular Spectrum Analysis Based on Single Channel Blind Source Separation Algorithm and Its Application to Fault Diagnosis

Directory of Open Access Journals (Sweden)

Dan Yang

2017-04-01

Full Text Available To solve the problem of multi-fault blind source separation (BSS in the case that the observed signals are under-determined, a novel approach for single channel blind source separation (SCBSS based on the improved tensor-based singular spectrum analysis (TSSA is proposed. As the most natural representation of high-dimensional data, tensor can preserve the intrinsic structure of the data to the maximum extent. Thus, TSSA method can be employed to extract the multi-fault features from the measured single-channel vibration signal. However, SCBSS based on TSSA still has some limitations, mainly including unsatisfactory convergence of TSSA in many cases and the number of source signals is hard to accurately estimate. Therefore, the improved TSSA algorithm based on canonical decomposition and parallel factors (CANDECOMP/PARAFAC weighted optimization, namely CP-WOPT, is proposed in this paper. CP-WOPT algorithm is applied to process the factor matrix using a first-order optimization approach instead of the original least square method in TSSA, so as to improve the convergence of this algorithm. In order to accurately estimate the number of the source signals in BSS, EMD-SVD-BIC (empirical mode decomposition—singular value decomposition—Bayesian information criterion method, instead of the SVD in the conventional TSSA, is introduced. To validate the proposed method, we applied it to the analysis of the numerical simulation signal and the multi-fault rolling bearing signals.

Detection of Early Faults in Rotating Machinery Based on Wavelet Analysis

Directory of Open Access Journals (Sweden)

Meng Hee Lim

2013-01-01

Full Text Available This paper explores the application of wavelet analysis for the detection of early changes in rotor dynamics caused by common machinery faults, namely, rotor unbalance and minor blade rubbing conditions. In this paper, the time synchronised wavelet analysis method was formulated and its effectiveness to detect machinery faults at the early stage was evaluated based on signal simulation and experimental study. The proposed method provides a more standardised approach to visualise the current state of rotor dynamics of a rotating machinery by taking into account the effects of time shift, wavelet edge distortion, and system noise suppression. The experimental results showed that this method is able to reveal subtle changes of the vibration signal characteristics in both the frequency content distribution and the amplitude distortion caused by minor rotor unbalance and blade rubbing conditions. Besides, this method also appeared to be an effective tool to diagnose and to discriminate the different types of machinery faults based on the unique pattern of the wavelet contours. This study shows that the proposed wavelet analysis method is promising to reveal machinery faults at early stage as compared to vibration spectrum analysis.

Decentralized Sliding Mode Observer Based Dual Closed-Loop Fault Tolerant Control for Reconfigurable Manipulator against Actuator Failure

Science.gov (United States)

Zhao, Bo; Li, Yuanchun

2015-01-01

This paper considers a decentralized fault tolerant control (DFTC) scheme for reconfigurable manipulators. With the appearance of norm-bounded failure, a dual closed-loop trajectory tracking control algorithm is proposed on the basis of the Lyapunov stability theory. Characterized by the modularization property, the actuator failure is estimated by the proposed decentralized sliding mode observer (DSMO). Moreover, the actuator failure can be treated in view of the local joint information, so its control performance degradation is independent of other normal joints. In addition, the presented DFTC scheme is significantly simplified in terms of the structure of the controller due to its dual closed-loop architecture, and its feasibility is highly reflected in the control of reconfigurable manipulators. Finally, the effectiveness of the proposed DFTC scheme is demonstrated using simulations. PMID:26181826

Decentralized Sliding Mode Observer Based Dual Closed-Loop Fault Tolerant Control for Reconfigurable Manipulator against Actuator Failure.

Directory of Open Access Journals (Sweden)

Bo Zhao

Full Text Available This paper considers a decentralized fault tolerant control (DFTC scheme for reconfigurable manipulators. With the appearance of norm-bounded failure, a dual closed-loop trajectory tracking control algorithm is proposed on the basis of the Lyapunov stability theory. Characterized by the modularization property, the actuator failure is estimated by the proposed decentralized sliding mode observer (DSMO. Moreover, the actuator failure can be treated in view of the local joint information, so its control performance degradation is independent of other normal joints. In addition, the presented DFTC scheme is significantly simplified in terms of the structure of the controller due to its dual closed-loop architecture, and its feasibility is highly reflected in the control of reconfigurable manipulators. Finally, the effectiveness of the proposed DFTC scheme is demonstrated using simulations.

Fault diagnosis in spur gears based on genetic algorithm and random forest

Science.gov (United States)

Cerrada, Mariela; Zurita, Grover; Cabrera, Diego; Sánchez, René-Vinicio; Artés, Mariano; Li, Chuan

2016-03-01

There are growing demands for condition-based monitoring of gearboxes, and therefore new methods to improve the reliability, effectiveness, accuracy of the gear fault detection ought to be evaluated. Feature selection is still an important aspect in machine learning-based diagnosis in order to reach good performance of the diagnostic models. On the other hand, random forest classifiers are suitable models in industrial environments where large data-samples are not usually available for training such diagnostic models. The main aim of this research is to build up a robust system for the multi-class fault diagnosis in spur gears, by selecting the best set of condition parameters on time, frequency and time-frequency domains, which are extracted from vibration signals. The diagnostic system is performed by using genetic algorithms and a classifier based on random forest, in a supervised environment. The original set of condition parameters is reduced around 66% regarding the initial size by using genetic algorithms, and still get an acceptable classification precision over 97%. The approach is tested on real vibration signals by considering several fault classes, one of them being an incipient fault, under different running conditions of load and velocity.

Design of a multi-model observer-based estimator for Fault Detection and Isolation (FDI strategy: application to a chemical reactor

Directory of Open Access Journals (Sweden)

Y. Chetouani

2008-12-01

Full Text Available This study presents a FDI strategy for nonlinear dynamic systems. It shows a methodology of tackling the fault detection and isolation issue by combining a technique based on the residuals signal and a technique using the multiple Kalman filters. The usefulness of this combination is the on-line implementation of the set of models, which represents the normal mode and all dynamics of faults, if the statistical decision threshold on the residuals exceeds a fixed value. In other cases, one Extended Kalman Filter (EKF is enough to estimate the process state. After describing the system architecture and the proposed FDI methodology, we present a realistic application in order to show the technique's potential. An algorithm is described and applied to a chemical process like a perfectly stirred chemical reactor functioning in a semi-batch mode. The chemical reaction used is an oxido reduction one, the oxidation of sodium thiosulfate by hydrogen peroxide.

Fault detection and isolation in processes involving induction machines

Energy Technology Data Exchange (ETDEWEB)

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

1998-12-31

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

Fault detection and isolation in processes involving induction machines

Energy Technology Data Exchange (ETDEWEB)

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

1997-12-31

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

Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

Science.gov (United States)

Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

2018-01-01

Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

UAVSAR observations of triggered slip on the Imperial, Superstition Hills, and East Elmore Ranch Faults associated with the 2010 M 7.2 El Mayor-Cucapah earthquake

Science.gov (United States)

Donnellan, Andrea; Parker, Jay; Hensley, Scott; Pierce, Marlon; Wang, Jun; Rundle, John

2014-03-01

4 April 2010 M 7.2 El Mayor-Cucapah earthquake that occurred in Baja California, Mexico and terminated near the U.S. Mexican border caused slip on the Imperial, Superstition Hills, and East Elmore Ranch Faults. The pattern of slip was observed using radar interferometry from NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument collected on 20-21 October 2009 and 12-13 April 2010. Right-lateral slip of 36 ± 9 and 14 ± 2 mm occurred on the Imperial and Superstition Hills Faults, respectively. Left-lateral slip of 9 ± 2 mm occurred on the East Elmore Ranch Fault. The widths of the zones of displacement increase northward suggesting successively more buried fault motion to the north. The observations show a decreasing pattern of slip northward on a series of faults in the Salton Trough stepping between the El Mayor-Cucapah rupture and San Andreas Fault. Most of the motion occurred at the time of the M 7.2 earthquake and the UAVSAR observations are consistent with field, creepmeter, GPS, and Envisat observations. An additional 28 ± 1 mm of slip at the southern end of the Imperial Fault over a <1 km wide zone was observed over a 1 day span a week after the earthquake suggesting that the fault continued to slip at depth following the mainshock. The total moment release on the three faults is 2.3 × 1023-1.2 × 1024 dyne cm equivalent to a moment magnitude release of 4.9-5.3, assuming shallow slip depths ranging from 1 to 5 km.

Three dimensional investigation of oceanic active faults. A demonstration survey

Energy Technology Data Exchange (ETDEWEB)

Nakao, Seizo; Kishimoto, Kiyoyuki; Kuramoto, Shinichi; Sato, Mikio [Geological Survey of Japan, Tsukuba, Ibaraki (Japan)

1998-02-01

In order to upgrade probability of activity and action potential evaluation of oceanic active faults which have some important effects on nuclear facilities, trench type oceanic active fault was investigated three dimensionally. Contents of the investigation were high precision sea bottom topographic survey and sea bottom back scattering wave image data observation by using a sea bottom topography acoustic imaginator. And, by high resolution earthquake wave survey, high precision survey of an active fault under sea bottom was conducted to detect oceanic active faults three-dimensionally. Furthermore, the generally issued data were summarized to promote to construct a data base for evaluating the active faults. (G.K.)

Three dimensional investigation of oceanic active faults. A demonstration survey

International Nuclear Information System (INIS)

Nakao, Seizo; Kishimoto, Kiyoyuki; Kuramoto, Shinichi; Sato, Mikio

1998-01-01

In order to upgrade probability of activity and action potential evaluation of oceanic active faults which have some important effects on nuclear facilities, trench type oceanic active fault was investigated three dimensionally. Contents of the investigation were high precision sea bottom topographic survey and sea bottom back scattering wave image data observation by using a sea bottom topography acoustic imaginator. And, by high resolution earthquake wave survey, high precision survey of an active fault under sea bottom was conducted to detect oceanic active faults three-dimensionally. Furthermore, the generally issued data were summarized to promote to construct a data base for evaluating the active faults. (G.K.)

A Model-Based Probabilistic Inversion Framework for Wire Fault Detection Using TDR

Science.gov (United States)

Schuet, Stefan R.; Timucin, Dogan A.; Wheeler, Kevin R.

2010-01-01

Time-domain reflectometry (TDR) is one of the standard methods for diagnosing faults in electrical wiring and interconnect systems, with a long-standing history focused mainly on hardware development of both high-fidelity systems for laboratory use and portable hand-held devices for field deployment. While these devices can easily assess distance to hard faults such as sustained opens or shorts, their ability to assess subtle but important degradation such as chafing remains an open question. This paper presents a unified framework for TDR-based chafing fault detection in lossy coaxial cables by combining an S-parameter based forward modeling approach with a probabilistic (Bayesian) inference algorithm. Results are presented for the estimation of nominal and faulty cable parameters from laboratory data.

A Weibull-based compositional approach for hierarchical dynamic fault trees

International Nuclear Information System (INIS)

Chiacchio, F.; Cacioppo, M.; D'Urso, D.; Manno, G.; Trapani, N.; Compagno, L.

2013-01-01

The solution of a dynamic fault tree (DFT) for the reliability assessment can be achieved using a wide variety of techniques. These techniques have a strong theoretical foundation as both the analytical and the simulation methods have been extensively developed. Nevertheless, they all present the same limits that appear with the increasing of the size of the fault trees (i.e., state space explosion, time-consuming simulations), compromising the resolution. We have tested the feasibility of a composition algorithm based on a Weibull distribution, addressed to the resolution of a general class of dynamic fault trees characterized by non-repairable basic events and generally distributed failure times. The proposed composition algorithm is used to generalize the traditional hierarchical technique that, as previous literature have extensively confirmed, is able to reduce the computational effort of a large DFT through the modularization of independent parts of the tree. The results of this study are achieved both through simulation and analytical techniques, thus confirming the capability to solve a quite general class of dynamic fault trees and overcome the limits of traditional techniques.

Elemental Geochemistry of Samples From Fault Segments of the San Andreas Fault Observatory at Depth (SAFOD) Drill Hole

Science.gov (United States)

Tourscher, S. N.; Schleicher, A. M.; van der Pluijm, B. A.; Warr, L. N.

2006-12-01

Elemental geochemistry of mudrock samples from phase 2 drilling of the San Andreas Fault Observatory at Depth (SAFOD) is presented from bore hole depths of 3066 m to 3169 m and from 3292 m to 3368 m, which contain a creeping section and main trace of the fault, respectively. In addition to preparation and analysis of whole rock sample, fault grains with neomineralized, polished surfaces were hand picked from well-washed whole rock samples, minimizing the potential contamination from drilling mud and steel shavings. The separated fractions were washed in deionized water, powdered using a mortar and pestle, and analyzed using an Inductively Coupled Plasma- Optical Emission Spectrometer for major and minor elements. Based on oxide data results, systematic differences in element concentrations are observed between the whole rock and fault rock. Two groupings of data points are distinguishable in the regions containing the main trace of the fault, a shallow part (3292- 3316 m) and a deeper section (3320-3368 m). Applying the isocon method, assuming Zr and Ti to be immobile elements in these samples, indicates a volume loss of more than 30 percent in the shallow part and about 23 percent in the deep part of the main trace. These changes are minimum estimates of fault-related volume loss, because the whole rock from drilling samples contains variable amount of fault rock as well. Minimum estimates for volume loss in the creeping section of the fault are more than 50 percent when using the isocon method, comparing whole rock to plucked fault rock. The majority of the volume loss in the fault rocks is due to the dissolution and loss of silica, potassium, aluminum, sodium and calcium, whereas (based on oxide data) the mineralized surfaces of fractures appear to be enriched in Fe and Mg. The large amount of element mobility within these fault traces suggests extensive circulation of hydrous fluids along fractures that was responsible for progressive dissolution and leaching

Online model-based fault detection for grid connected PV systems monitoring

KAUST Repository

Harrou, Fouzi; Sun, Ying; Saidi, Ahmed

2017-01-01

This paper presents an efficient fault detection approach to monitor the direct current (DC) side of photovoltaic (PV) systems. The key contribution of this work is combining both single diode model (SDM) flexibility and the cumulative sum (CUSUM) chart efficiency to detect incipient faults. In fact, unknown electrical parameters of SDM are firstly identified using an efficient heuristic algorithm, named Artificial Bee Colony algorithm. Then, based on the identified parameters, a simulation model is built and validated using a co-simulation between Matlab/Simulink and PSIM. Next, the peak power (Pmpp) residuals of the entire PV array are generated based on both real measured and simulated Pmpp values. Residuals are used as the input for the CUSUM scheme to detect potential faults. We validate the effectiveness of this approach using practical data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

Online model-based fault detection for grid connected PV systems monitoring

KAUST Repository

Harrou, Fouzi

2017-12-14

This paper presents an efficient fault detection approach to monitor the direct current (DC) side of photovoltaic (PV) systems. The key contribution of this work is combining both single diode model (SDM) flexibility and the cumulative sum (CUSUM) chart efficiency to detect incipient faults. In fact, unknown electrical parameters of SDM are firstly identified using an efficient heuristic algorithm, named Artificial Bee Colony algorithm. Then, based on the identified parameters, a simulation model is built and validated using a co-simulation between Matlab/Simulink and PSIM. Next, the peak power (Pmpp) residuals of the entire PV array are generated based on both real measured and simulated Pmpp values. Residuals are used as the input for the CUSUM scheme to detect potential faults. We validate the effectiveness of this approach using practical data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

A Novel Wide-Area Backup Protection Based on Fault Component Current Distribution and Improved Evidence Theory

Directory of Open Access Journals (Sweden)

Zhe Zhang

2014-01-01

Full Text Available In order to solve the problems of the existing wide-area backup protection (WABP algorithms, the paper proposes a novel WABP algorithm based on the distribution characteristics of fault component current and improved Dempster/Shafer (D-S evidence theory. When a fault occurs, slave substations transmit to master station the amplitudes of fault component currents of transmission lines which are the closest to fault element. Then master substation identifies suspicious faulty lines according to the distribution characteristics of fault component current. After that, the master substation will identify the actual faulty line with improved D-S evidence theory based on the action states of traditional protections and direction components of these suspicious faulty lines. The simulation examples based on IEEE 10-generator-39-bus system show that the proposed WABP algorithm has an excellent performance. The algorithm has low requirement of sampling synchronization, small wide-area communication flow, and high fault tolerance.

A Novel Wide-Area Backup Protection Based on Fault Component Current Distribution and Improved Evidence Theory

Science.gov (United States)

Zhang, Zhe; Kong, Xiangping; Yin, Xianggen; Yang, Zengli; Wang, Lijun

2014-01-01

In order to solve the problems of the existing wide-area backup protection (WABP) algorithms, the paper proposes a novel WABP algorithm based on the distribution characteristics of fault component current and improved Dempster/Shafer (D-S) evidence theory. When a fault occurs, slave substations transmit to master station the amplitudes of fault component currents of transmission lines which are the closest to fault element. Then master substation identifies suspicious faulty lines according to the distribution characteristics of fault component current. After that, the master substation will identify the actual faulty line with improved D-S evidence theory based on the action states of traditional protections and direction components of these suspicious faulty lines. The simulation examples based on IEEE 10-generator-39-bus system show that the proposed WABP algorithm has an excellent performance. The algorithm has low requirement of sampling synchronization, small wide-area communication flow, and high fault tolerance. PMID:25050399

Optimal design of RTCs in digital circuit fault self-repair based on global signal optimization

Institute of Scientific and Technical Information of China (English)

Zhang Junbin; Cai Jinyan; Meng Yafeng

2016-01-01

Since digital circuits have been widely and thoroughly applied in various fields, electronic systems are increasingly more complicated and require greater reliability. Faults may occur in elec-tronic systems in complicated environments. If immediate field repairs are not made on the faults, elec-tronic systems will not run normally, and this will lead to serious losses. The traditional method for improving system reliability based on redundant fault-tolerant technique has been unable to meet the requirements. Therefore, on the basis of (evolvable hardware)-based and (reparation balance technology)-based electronic circuit fault self-repair strategy proposed in our preliminary work, the optimal design of rectification circuits (RTCs) in electronic circuit fault self-repair based on global sig-nal optimization is deeply researched in this paper. First of all, the basic theory of RTC optimal design based on global signal optimization is proposed. Secondly, relevant considerations and suitable ranges are analyzed. Then, the basic flow of RTC optimal design is researched. Eventually, a typical circuit is selected for simulation verification, and detailed simulated analysis is made on five circumstances that occur during RTC evolution. The simulation results prove that compared with the conventional design method based RTC, the global signal optimization design method based RTC is lower in hardware cost, faster in circuit evolution, higher in convergent precision, and higher in circuit evolution success rate. Therefore, the global signal optimization based RTC optimal design method applied in the elec-tronic circuit fault self-repair technology is proven to be feasible, effective, and advantageous.

Wavelet-Based Feature Extraction in Fault Diagnosis for Biquad High-Pass Filter Circuit

OpenAIRE

Yuehai Wang; Yongzheng Yan; Qinyong Wang

2016-01-01

Fault diagnosis for analog circuit has become a prominent factor in improving the reliability of integrated circuit due to its irreplaceability in modern integrated circuits. In fact fault diagnosis based on intelligent algorithms has become a popular research topic as efficient feature extraction and selection are a critical and intricate task in analog fault diagnosis. Further, it is extremely important to propose some general guidelines for the optimal feature extraction and selection. In ...

An efficient diagnostic technique for distribution systems based on under fault voltages and currents

Energy Technology Data Exchange (ETDEWEB)

Campoccia, A.; Di Silvestre, M.L.; Incontrera, I.; Riva Sanseverino, E. [Dipartimento di Ingegneria Elettrica elettronica e delle Telecomunicazioni, Universita degli Studi di Palermo, viale delle Scienze, 90128 Palermo (Italy); Spoto, G. [Centro per la Ricerca Elettronica in Sicilia, Monreale, Via Regione Siciliana 49, 90046 Palermo (Italy)

2010-10-15

Service continuity is one of the major aspects in the definition of the quality of the electrical energy, for this reason the research in the field of faults diagnostic for distribution systems is spreading ever more. Moreover the increasing interest around modern distribution systems automation for management purposes gives faults diagnostics more tools to detect outages precisely and in short times. In this paper, the applicability of an efficient fault location and characterization methodology within a centralized monitoring system is discussed. The methodology, appropriate for any kind of fault, is based on the use of the analytical model of the network lines and uses the fundamental components rms values taken from the transient measures of line currents and voltages at the MV/LV substations. The fault location and identification algorithm, proposed by the authors and suitably restated, has been implemented on a microprocessor-based device that can be installed at each MV/LV substation. The speed and precision of the algorithm have been tested against the errors deriving from the fundamental extraction within the prescribed fault clearing times and against the inherent precision of the electronic device used for computation. The tests have been carried out using Matlab Simulink for simulating the faulted system. (author)

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

KAUST Repository

Harrou, Fouzi

2017-03-18

Fault detection has a vital role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. This paper proposes an innovative multivariate fault detection method that can be used for monitoring nonlinear processes. The proposed method merges advantages of nonlinear projection to latent structures (NLPLS) modeling and those of Hellinger distance (HD) metric to identify abnormal changes in highly correlated multivariate data. Specifically, the HD is used to quantify the dissimilarity between current NLPLS-based residual and reference probability distributions obtained using fault-free data. Furthermore, to enhance further the robustness of these methods to measurement noise, and reduce the false alarms due to modeling errors, wavelet-based multiscale filtering of residuals is used before the application of the HD-based monitoring scheme. The performances of the developed NLPLS-HD fault detection technique is illustrated using simulated plug flow reactor data. The results show that the proposed method provides favorable performance for detection of faults compared to the conventional NLPLS method.

Fault Diagnosis of Nonlinear Systems Using Structured Augmented State Models

Institute of Scientific and Technical Information of China (English)

Jochen Aβfalg; Frank Allg(o)wer

2007-01-01

This paper presents an internal model approach for modeling and diagnostic functionality design for nonlinear systems operating subject to single- and multiple-faults. We therefore provide the framework of structured augmented state models. Fault characteristics are considered to be generated by dynamical exosystems that are switched via equality constraints to overcome the augmented state observability limiting the number of diagnosable faults. Based on the proposed model, the fault diagnosis problem is specified as an optimal hybrid augmented state estimation problem. Sub-optimal solutions are motivated and exemplified for the fault diagnosis of the well-known three-tank benchmark. As the considered class of fault diagnosis problems is large, the suggested approach is not only of theoretical interest but also of high practical relevance.

NN-Es Fault Diagnosis Method in Nuclear Power Equipment Based on Concept Lattice

International Nuclear Information System (INIS)

Liu Yongkuo; Xie Chunli; Xia Hong

2010-01-01

In order to improve the fault diagnosis accuracy of nuclear power plant,neural network and expert systems were combined to give full play to their advantages. In this paper, the concept lattice was applied to get the object properties, extracting the core attributes, dispensable attributes and relative necessary attributes from a large number raw data of fault symptoms.Based on these attributes, neural networks with different levels of importance were designed to improve the learning speed and diagnosis accuracy, and the diagnosis results of the neural networks were verified by using rule-based reasoning expert system. To verify the accuracy of this method, some simulation experiments about the typical faults of nuclear power plant were conducted. And the simulation results show that it is feasible to diagnose nuclear power plant faults with the confederation diagnosis methods combined the neural networks based on the concept lattice theory and expert system, with the distinctive features such as the efficiency of neural network learning, less calculation and reliability of diagnosis results and so on. (authors)

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

International Nuclear Information System (INIS)

Far, R.R.; Davilu, H.; Lucas, C.

2008-01-01

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.)

A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine

Directory of Open Access Journals (Sweden)

Zhheng Ni

2016-01-01

Full Text Available At present, the fault signals of surface to air missile equipment are hard to collect and the accuracy of fault diagnosis is very low. To solve the above problems, based on the superiority of wavelet transformation on processing non-stationary signals and the advantage of SVM on pattern classification, this paper proposes a fault diagnosis model and takes the typical analog circuit diagnosis of one power distribution system as an example to verify the fault diagnosis model based on Wavelet Transformation and SVM. The simulation results show that the model is able to achieve fault diagnosis based on a small amount of training samples, which improves the accuracy of fault diagnosis.

Crustal Density Variation Along the San Andreas Fault Controls Its Secondary Faults Distribution and Dip Direction

Science.gov (United States)

Yang, H.; Moresi, L. N.

2017-12-01

The San Andreas fault forms a dominant component of the transform boundary between the Pacific and the North American plate. The density and strength of the complex accretionary margin is very heterogeneous. Based on the density structure of the lithosphere in the SW United States, we utilize the 3D finite element thermomechanical, viscoplastic model (Underworld2) to simulate deformation in the San Andreas Fault system. The purpose of the model is to examine the role of a big bend in the existing geometry. In particular, the big bend of the fault is an initial condition of in our model. We first test the strength of the fault by comparing the surface principle stresses from our numerical model with the in situ tectonic stress. The best fit model indicates the model with extremely weak fault (friction coefficient 200 kg/m3) than surrounding blocks. In contrast, the Mojave block is detected to find that it has lost its mafic lower crust by other geophysical surveys. Our model indicates strong strain localization at the jointer boundary between two blocks, which is an analogue for the Garlock fault. High density lower crust material of the Great Valley tends to under-thrust beneath the Transverse Range near the big bend. This motion is likely to rotate the fault plane from the initial vertical direction to dip to the southwest. For the straight section, north to the big bend, the fault is nearly vertical. The geometry of the fault plane is consistent with field observations.

Quaternary faulting in the Tatra Mountains, evidence from cave morphology and fault-slip analysis

Directory of Open Access Journals (Sweden)

Szczygieł Jacek

2015-06-01

Full Text Available Tectonically deformed cave passages in the Tatra Mts (Central Western Carpathians indicate some fault activity during the Quaternary. Displacements occur in the youngest passages of the caves indicating (based on previous U-series dating of speleothems an Eemian or younger age for those faults, and so one tectonic stage. On the basis of stress analysis and geomorphological observations, two different mechanisms are proposed as responsible for the development of these displacements. The first mechanism concerns faults that are located above the valley bottom and at a short distance from the surface, with fault planes oriented sub-parallel to the slopes. The radial, horizontal extension and vertical σ1 which is identical with gravity, indicate that these faults are the result of gravity sliding probably caused by relaxation after incision of valleys, and not directly from tectonic activity. The second mechanism is tilting of the Tatra Mts. The faults operated under WNW-ESE oriented extension with σ1 plunging steeply toward the west. Such a stress field led to normal dip-slip or oblique-slip displacements. The faults are located under the valley bottom and/or opposite or oblique to the slopes. The process involved the pre-existing weakest planes in the rock complex: (i in massive limestone mostly faults and fractures, (ii in thin-bedded limestone mostly inter-bedding planes. Thin-bedded limestones dipping steeply to the south are of particular interest. Tilting toward the N caused the hanging walls to move under the massif and not toward the valley, proving that the cause of these movements was tectonic activity and not gravity.

Fault tree synthesis for software design analysis of PLC based safety-critical systems

International Nuclear Information System (INIS)

Koo, S. R.; Cho, C. H.; Seong, P. H.

2006-01-01

As a software verification and validation should be performed for the development of PLC based safety-critical systems, a software safety analysis is also considered in line with entire software life cycle. In this paper, we propose a technique of software safety analysis in the design phase. Among various software hazard analysis techniques, fault tree analysis is most widely used for the safety analysis of nuclear power plant systems. Fault tree analysis also has the most intuitive notation and makes both qualitative and quantitative analyses possible. To analyze the design phase more effectively, we propose a technique of fault tree synthesis, along with a universal fault tree template for the architecture modules of nuclear software. Consequently, we can analyze the safety of software on the basis of fault tree synthesis. (authors)

Diagnosing a Strong-Fault Model by Conflict and Consistency

Directory of Open Access Journals (Sweden)

Wenfeng Zhang

2018-03-01

Full Text Available The diagnosis method for a weak-fault model with only normal behaviors of each component has evolved over decades. However, many systems now demand a strong-fault models, the fault modes of which have specific behaviors as well. It is difficult to diagnose a strong-fault model due to its non-monotonicity. Currently, diagnosis methods usually employ conflicts to isolate possible fault and the process can be expedited when some observed output is consistent with the model’s prediction where the consistency indicates probably normal components. This paper solves the problem of efficiently diagnosing a strong-fault model by proposing a novel Logic-based Truth Maintenance System (LTMS with two search approaches based on conflict and consistency. At the beginning, the original a strong-fault model is encoded by Boolean variables and converted into Conjunctive Normal Form (CNF. Then the proposed LTMS is employed to reason over CNF and find multiple minimal conflicts and maximal consistencies when there exists fault. The search approaches offer the best candidate efficiency based on the reasoning result until the diagnosis results are obtained. The completeness, coverage, correctness and complexity of the proposals are analyzed theoretically to show their strength and weakness. Finally, the proposed approaches are demonstrated by applying them to a real-world domain—the heat control unit of a spacecraft—where the proposed methods are significantly better than best first and conflict directly with A* search methods.

Diagnosing a Strong-Fault Model by Conflict and Consistency.

Science.gov (United States)

Zhang, Wenfeng; Zhao, Qi; Zhao, Hongbo; Zhou, Gan; Feng, Wenquan

2018-03-29

The diagnosis method for a weak-fault model with only normal behaviors of each component has evolved over decades. However, many systems now demand a strong-fault models, the fault modes of which have specific behaviors as well. It is difficult to diagnose a strong-fault model due to its non-monotonicity. Currently, diagnosis methods usually employ conflicts to isolate possible fault and the process can be expedited when some observed output is consistent with the model's prediction where the consistency indicates probably normal components. This paper solves the problem of efficiently diagnosing a strong-fault model by proposing a novel Logic-based Truth Maintenance System (LTMS) with two search approaches based on conflict and consistency. At the beginning, the original a strong-fault model is encoded by Boolean variables and converted into Conjunctive Normal Form (CNF). Then the proposed LTMS is employed to reason over CNF and find multiple minimal conflicts and maximal consistencies when there exists fault. The search approaches offer the best candidate efficiency based on the reasoning result until the diagnosis results are obtained. The completeness, coverage, correctness and complexity of the proposals are analyzed theoretically to show their strength and weakness. Finally, the proposed approaches are demonstrated by applying them to a real-world domain-the heat control unit of a spacecraft-where the proposed methods are significantly better than best first and conflict directly with A* search methods.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

Science.gov (United States)

Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

2017-10-03

This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

Identification method of non-reflective faults based on index distribution of optical fibers.

Science.gov (United States)

Lee, Wonkyoung; Myong, Seung Il; Lee, Jyung Chan; Lee, Sangsoo

2014-01-13

This paper investigates an identification method of non-reflective faults based on index distribution of optical fibers. The method identifies not only reflective faults but also non-reflective faults caused by tilted fiber-cut, lateral connector-misalignment, fiber-bend, and temperature variation. We analyze the reason why wavelength dependence of the fiber-bend is opposite to that of the lateral connector-misalignment, and the effect of loss due to temperature variation on OTDR waveforms through simulation and experimental results. This method can be realized by only upgrade of fault-analysis software without the hardware change, it is, therefore, competitive and cost-effective in passive optical networks.

Fault Detection for Industrial Processes

Directory of Open Access Journals (Sweden)

Yingwei Zhang

2012-01-01

Full Text Available A new fault-relevant KPCA algorithm is proposed. Then the fault detection approach is proposed based on the fault-relevant KPCA algorithm. The proposed method further decomposes both the KPCA principal space and residual space into two subspaces. Compared with traditional statistical techniques, the fault subspace is separated based on the fault-relevant influence. This method can find fault-relevant principal directions and principal components of systematic subspace and residual subspace for process monitoring. The proposed monitoring approach is applied to Tennessee Eastman process and penicillin fermentation process. The simulation results show the effectiveness of the proposed method.

Geotribology - Friction, wear, and lubrication of faults

Science.gov (United States)

Boneh, Yuval; Reches, Ze'ev

2018-05-01

We introduce here the concept of Geotribology as an approach to study friction, wear, and lubrication of geological systems. Methods of geotribology are applied here to characterize the friction and wear associated with slip along experimental faults composed of brittle rocks. The wear in these faults is dominated by brittle fracturing, plucking, scratching and fragmentation at asperities of all scales, including 'effective asperities' that develop and evolve during the slip. We derived a theoretical model for the rate of wear based on the observation that the dynamic strength of brittle materials is proportional to the product of load stress and loading period. In a slipping fault, the loading period of an asperity is inversely proportional to the slip velocity, and our derivations indicate that the wear-rate is proportional to the ratio of [shear-stress/slip-velocity]. By incorporating the rock hardness data into the model, we demonstrate that a single, universal function fits wear data of hundreds of experiments with granitic, carbonate and sandstone faults. In the next step, we demonstrate that the dynamic frictional strength of experimental faults is well explained in terms of the tribological parameter PV factor (= normal-stress · slip-velocity). This factor successfully delineates weakening and strengthening regimes of carbonate and granitic faults. Finally, our analysis revealed a puzzling observation that wear-rate and frictional strength have strikingly different dependencies on the loading conditions of normal-stress and slip-velocity; we discuss sources for this difference. We found that utilization of tribological tools in fault slip analyses leads to effective and insightful results.

A Lateral Tensile Fracturing Model for Listric Fault

Science.gov (United States)

Qiu, Z.

2007-12-01

The new discovery of a major seismic fault of the great 1976 Tangshan earthquake suggests a lateral tensile fracturing process at the seismic source. The fault is in listric shape but can not be explained with the prevailing model of listric fault. A double-couple of forces without moment is demonstrated to be applicable to simulate the source mechanism. Based on fracture mechanics, laboratory experiments as well as numerical simulations, the model is against the assumption of stick-slip on existing fault as the cause of the earthquake but not in conflict with seismological observations. Global statistics of CMT solutions of great earthquakes raises significant support to the idea that lateral tensile fracturing might account for not only the Tangshan earthquake but also others.

Kinematic Earthquake Ground‐Motion Simulations on Listric Normal Faults

KAUST Repository

Passone, Luca

2017-11-28

Complex finite-faulting source processes have important consequences for near-source ground motions, but empirical ground-motion prediction equations still lack near-source data and hence cannot fully capture near-fault shaking effects. Using a simulation-based approach, we study the effects of specific source parameterizations on near-field ground motions where empirical data are limited. Here, we investigate the effects of fault listricity through near-field kinematic ground-motion simulations. Listric faults are defined as curved faults in which dip decreases with depth, resulting in a concave upward profile. The listric profiles used in this article are built by applying a specific shape function and varying the initial dip and the degree of listricity. Furthermore, we consider variable rupture speed and slip distribution to generate ensembles of kinematic source models. These ensembles are then used in a generalized 3D finite-difference method to compute synthetic seismograms; the corresponding shaking levels are then compared in terms of peak ground velocities (PGVs) to quantify the effects of breaking fault planarity. Our results show two general features: (1) as listricity increases, the PGVs decrease on the footwall and increase on the hanging wall, and (2) constructive interference of seismic waves emanated from the listric fault causes PGVs over two times higher than those observed for the planar fault. Our results are relevant for seismic hazard assessment for near-fault areas for which observations are scarce, such as in the listric Campotosto fault (Italy) located in an active seismic area under a dam.

Kinematic Earthquake Ground‐Motion Simulations on Listric Normal Faults

KAUST Repository

Passone, Luca; Mai, Paul Martin

2017-01-01

Complex finite-faulting source processes have important consequences for near-source ground motions, but empirical ground-motion prediction equations still lack near-source data and hence cannot fully capture near-fault shaking effects. Using a simulation-based approach, we study the effects of specific source parameterizations on near-field ground motions where empirical data are limited. Here, we investigate the effects of fault listricity through near-field kinematic ground-motion simulations. Listric faults are defined as curved faults in which dip decreases with depth, resulting in a concave upward profile. The listric profiles used in this article are built by applying a specific shape function and varying the initial dip and the degree of listricity. Furthermore, we consider variable rupture speed and slip distribution to generate ensembles of kinematic source models. These ensembles are then used in a generalized 3D finite-difference method to compute synthetic seismograms; the corresponding shaking levels are then compared in terms of peak ground velocities (PGVs) to quantify the effects of breaking fault planarity. Our results show two general features: (1) as listricity increases, the PGVs decrease on the footwall and increase on the hanging wall, and (2) constructive interference of seismic waves emanated from the listric fault causes PGVs over two times higher than those observed for the planar fault. Our results are relevant for seismic hazard assessment for near-fault areas for which observations are scarce, such as in the listric Campotosto fault (Italy) located in an active seismic area under a dam.

Research on bearing fault diagnosis of large machinery based on mathematical morphology

Science.gov (United States)

Wang, Yu

2018-04-01

To study the automatic diagnosis of large machinery fault based on support vector machine, combining the four common faults of the large machinery, the support vector machine is used to classify and identify the fault. The extracted feature vectors are entered. The feature vector is trained and identified by multi - classification method. The optimal parameters of the support vector machine are searched by trial and error method and cross validation method. Then, the support vector machine is compared with BP neural network. The results show that the support vector machines are short in time and high in classification accuracy. It is more suitable for the research of fault diagnosis in large machinery. Therefore, it can be concluded that the training speed of support vector machines (SVM) is fast and the performance is good.

Multiple incipient sensor faults diagnosis with application to high-speed railway traction devices.

Science.gov (United States)

Wu, Yunkai; Jiang, Bin; Lu, Ningyun; Yang, Hao; Zhou, Yang

2017-03-01

This paper deals with the problem of incipient fault diagnosis for a class of Lipschitz nonlinear systems with sensor biases and explores further results of total measurable fault information residual (ToMFIR). Firstly, state and output transformations are introduced to transform the original system into two subsystems. The first subsystem is subject to system disturbances and free from sensor faults, while the second subsystem contains sensor faults but without any system disturbances. Sensor faults in the second subsystem are then formed as actuator faults by using a pseudo-actuator based approach. Since the effects of system disturbances on the residual are completely decoupled, multiple incipient sensor faults can be detected by constructing ToMFIR, and the fault detectability condition is then derived for discriminating the detectable incipient sensor faults. Further, a sliding-mode observers (SMOs) based fault isolation scheme is designed to guarantee accurate isolation of multiple sensor faults. Finally, simulation results conducted on a CRH2 high-speed railway traction device are given to demonstrate the effectiveness of the proposed approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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

DEFF Research Database (Denmark)

Herp, Jürgen; S. Nadimi, Esmaeil

2015-01-01

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

α-Cut method based importance measure for criticality analysis in fuzzy probability – Based fault tree analysis

International Nuclear Information System (INIS)

Purba, Julwan Hendry; Sony Tjahyani, D.T.; Widodo, Surip; Tjahjono, Hendro

2017-01-01

Highlights: •FPFTA deals with epistemic uncertainty using fuzzy probability. •Criticality analysis is important for reliability improvement. •An α-cut method based importance measure is proposed for criticality analysis in FPFTA. •The α-cut method based importance measure utilises α-cut multiplication, α-cut subtraction, and area defuzzification technique. •Benchmarking confirm that the proposed method is feasible for criticality analysis in FPFTA. -- Abstract: Fuzzy probability – based fault tree analysis (FPFTA) has been recently developed and proposed to deal with the limitations of conventional fault tree analysis. In FPFTA, reliabilities of basic events, intermediate events and top event are characterized by fuzzy probabilities. Furthermore, the quantification of the FPFTA is based on fuzzy multiplication rule and fuzzy complementation rule to propagate uncertainties from basic event to the top event. Since the objective of the fault tree analysis is to improve the reliability of the system being evaluated, it is necessary to find the weakest path in the system. For this purpose, criticality analysis can be implemented. Various importance measures, which are based on conventional probabilities, have been developed and proposed for criticality analysis in fault tree analysis. However, not one of those importance measures can be applied for criticality analysis in FPFTA, which is based on fuzzy probability. To be fully applied in nuclear power plant probabilistic safety assessment, FPFTA needs to have its corresponding importance measure. The objective of this study is to develop an α-cut method based importance measure to evaluate and rank the importance of basic events for criticality analysis in FPFTA. To demonstrate the applicability of the proposed measure, a case study is performed and its results are then benchmarked to the results generated by the four well known importance measures in conventional fault tree analysis. The results

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

KAUST Repository

Harrou, Fouzi

2017-09-18

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

Prodiag--a hybrid artificial intelligence based reactor diagnostic system for process faults

International Nuclear Information System (INIS)

Reifman, J.; Wei, T.Y.C.; Vitela, J.E.; Applequist, C. A.; Chasensky, T.M.

1996-01-01

Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL) are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA), project to perform feasibility studies on a novel approach to Artificial Intelligence (Al) based diagnostics for component faults in nuclear power plants. Investigations are being performed in the construction of a first-principles physics-based plant level process diagnostic expert system (ES) and the identification of component-level fault patterns through operating component characteristics using artificial neural networks (ANNs). The purpose of the proof-of-concept project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use thermal hydraulic (T-H) signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance.To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. A full-scope operator training simulator representing the Commonwealth Edison Braidwood nuclear power plant is being used both as the source of development data and as the means to evaluate the advantages of the proposed diagnostic system. This is an ongoing multi-year project and this paper presents the results to date of the CRADA phase

Research on Model-Based Fault Diagnosis for a Gas Turbine Based on Transient Performance

Directory of Open Access Journals (Sweden)

Detang Zeng

2018-01-01

Full Text Available It is essential to monitor and to diagnose faults in rotating machinery with a high thrust–weight ratio and complex structure for a variety of industrial applications, for which reliable signal measurements are required. However, the measured values consist of the true values of the parameters, the inertia of measurements, random errors and systematic errors. Such signals cannot reflect the true performance state and the health state of rotating machinery accurately. High-quality, steady-state measurements are necessary for most current diagnostic methods. Unfortunately, it is hard to obtain these kinds of measurements for most rotating machinery. Diagnosis based on transient performance is a useful tool that can potentially solve this problem. A model-based fault diagnosis method for gas turbines based on transient performance is proposed in this paper. The fault diagnosis consists of a dynamic simulation model, a diagnostic scheme, and an optimization algorithm. A high-accuracy, nonlinear, dynamic gas turbine model using a modular modeling method is presented that involves thermophysical properties, a component characteristic chart, and system inertial. The startup process is simulated using this model. The consistency between the simulation results and the field operation data shows the validity of the model and the advantages of transient accumulated deviation. In addition, a diagnostic scheme is designed to fulfill this process. Finally, cuckoo search is selected to solve the optimization problem in fault diagnosis. Comparative diagnostic results for a gas turbine before and after washing indicate the improved effectiveness and accuracy of the proposed method of using data from transient processes, compared with traditional methods using data from the steady state.

Architecture of buried reverse fault zone in the sedimentary basin: A case study from the Hong-Che Fault Zone of the Junggar Basin

Science.gov (United States)

Liu, Yin; Wu, Kongyou; Wang, Xi; Liu, Bo; Guo, Jianxun; Du, Yannan

2017-12-01

It is widely accepted that the faults can act as the conduits or the barrier for oil and gas migration. Years of studies suggested that the internal architecture of a fault zone is complicated and composed of distinct components with different physical features, which can highly influence the migration of oil and gas along the fault. The field observation is the most useful methods of observing the fault zone architecture, however, in the petroleum exploration, what should be concerned is the buried faults in the sedimentary basin. Meanwhile, most of the studies put more attention on the strike-slip or normal faults, but the architecture of the reverse faults attracts less attention. In order to solve these questions, the Hong-Che Fault Zone in the northwest margin of the Junggar Basin, Xinjiang Province, is chosen for an example. Combining with the seismic data, well logs and drill core data, we put forward a comprehensive method to recognize the internal architectures of buried faults. High-precision seismic data reflect that the fault zone shows up as a disturbed seismic reflection belt. Four types of well logs, which are sensitive to the fractures, and a comprehensive discriminated parameter, named fault zone index are used in identifying the fault zone architecture. Drill core provides a direct way to identify different components of the fault zone, the fault core is composed of breccia, gouge, and serpentinized or foliated fault rocks and the damage zone develops multiphase of fractures, which are usually cemented. Based on the recognition results, we found that there is an obvious positive relationship between the width of the fault zone and the displacement, and the power-law relationship also exists between the width of the fault core and damage zone. The width of the damage zone in the hanging wall is not apparently larger than that in the footwall in the reverse fault, showing different characteristics with the normal fault. This study provides a

Fault zone architecture, San Jacinto fault zone, southern California: evidence for focused fluid flow and heat transfer in the shallow crust

Science.gov (United States)

Morton, N.; Girty, G. H.; Rockwell, T. K.

2011-12-01

We report results of a new study of the San Jacinto fault zone architecture in Horse Canyon, SW of Anza, California, where stream incision has exposed a near-continuous outcrop of the fault zone at ~0.4 km depth. The fault zone at this location consists of a fault core, transition zone, damage zone, and lithologically similar wall rocks. We collected and analyzed samples for their bulk and grain density, geochemical data, clay mineralogy, and textural and modal mineralogy. Progressive deformation within the fault zone is characterized by mode I cracking, subsequent shearing of already fractured rock, and cataclastic flow. Grain comminution advances towards the strongly indurated cataclasite fault core. Damage progression towards the core is accompanied by a decrease in bulk and grain density, and an increase in porosity and dilational volumetric strain. Palygorskite and mixed-layer illite/smectite clay minerals are present in the damage and transition zones and are the result of hydrolysis reactions. The estimated percentage of illite in illite/smectite increases towards the fault core where the illite/smectite to illite conversion is complete, suggesting elevated temperatures that may have reached 150°C. Chemical alteration and elemental mass changes are observed throughout the fault zone and are most pronounced in the fault core. We conclude that the observed chemical and mineralogical changes can only be produced by the interaction of fractured wall rocks and chemically active fluids that are mobilized through the fault zone by thermo-pressurization during and after seismic events. Based on the high element mobility and absence of illite/smectite in the fault core, we expect that greatest water/rock ratios occur within the fault core. These results indicate that hot pore fluids circulate upwards through the fractured fault core and into the surrounding damage zone. Though difficult to constrain, the site studied during this investigation may represent the top

Seismic and aseismic fault slip in response to fluid injection observed during field experiments at meter scale

Science.gov (United States)

Cappa, F.; Guglielmi, Y.; De Barros, L.; Wynants-Morel, N.; Duboeuf, L.

2017-12-01

During fluid injection, the observations of an enlarging cloud of seismicity are generally explained by a direct response to the pore pressure diffusion in a permeable fractured rock. However, fluid injection can also induce large aseismic deformations which provide an alternative mechanism for triggering and driving seismicity. Despite the importance of these two mechanisms during fluid injection, there are few studies on the effects of fluid pressure on the partitioning between seismic and aseismic motions under controlled field experiments. Here, we describe in-situ meter-scale experiments measuring synchronously the fluid pressure, the fault motions and the seismicity directly in a fault zone stimulated by controlled fluid injection at 280 m depth in carbonate rocks. The experiments were conducted in a gallery of an underground laboratory in south of France (LSBB, http://lsbb.eu). Thanks to the proximal monitoring at high-frequency, our data show that the fluid overpressure mainly induces a dilatant aseismic slip (several tens of microns up to a millimeter) at the injection. A sparse seismicity (-4 laws, we simulated an experiment and investigated the relative contribution of the fluid pressure diffusion and stress transfer on the seismic and aseismic fault behavior. The model reproduces the hydromechanical data measured at injection, and show that the aseismic slip induced by fluid injection propagates outside the pressurized zone where accumulated shear stress develops, and potentially triggers seismicity. Our models also show that the permeability enhancement and friction evolution are essential to explain the fault slip behavior. Our experimental results are consistent with large-scale observations of fault motions at geothermal sites (Wei et al., 2015; Cornet, 2016), and suggest that controlled field experiments at meter-scale are important for better assessing the role of fluid pressure in natural and human-induced earthquakes.

Design of on-board Bluetooth wireless network system based on fault-tolerant technology

Science.gov (United States)

You, Zheng; Zhang, Xiangqi; Yu, Shijie; Tian, Hexiang

2007-11-01

In this paper, the Bluetooth wireless data transmission technology is applied in on-board computer system, to realize wireless data transmission between peripherals of the micro-satellite integrating electronic system, and in view of the high demand of reliability of a micro-satellite, a design of Bluetooth wireless network based on fault-tolerant technology is introduced. The reliability of two fault-tolerant systems is estimated firstly using Markov model, then the structural design of this fault-tolerant system is introduced; several protocols are established to make the system operate correctly, some related problems are listed and analyzed, with emphasis on Fault Auto-diagnosis System, Active-standby switch design and Data-Integrity process.

V and V based Fault Estimation Method for Safety-Critical Software using BNs

International Nuclear Information System (INIS)

Eom, Heung Seop; Park, Gee Yong; Jang, Seung Cheol; Kang, Hyun Gook

2011-01-01

Quantitative software reliability measurement approaches have severe limitations in demonstrating the proper level of reliability for safety-critical software. These limitations can be overcome by using some other means of assessment. One of the promising candidates is based on the quality of the software development. Particularly in the nuclear industry, regulatory bodies in most countries do not accept the concept of quantitative goals as a sole means of meeting their regulations for the reliability of digital computers in NPPs, and use deterministic criteria for both hardware and software. The point of deterministic criteria is to assess the whole development process and its related activities during the software development life cycle for the acceptance of safety-critical software, and software V and V plays an important role in this process. In this light, we studied a V and V based fault estimation method using Bayesian Nets (BNs) to assess the reliability of safety-critical software, especially reactor protection system software in a NPP. The BNs in the study were made for an estimation of software faults and were based on the V and V frame, which governs the development of safety-critical software in the nuclear field. A case study was carried out for a reactor protection system that was developed as a part of the Korea Nuclear Instrumentation and Control System. The insight from the case study is that some important factors affecting the fault number of the target software include the residual faults in the system specification, maximum number of faults introduced in the development phase, ratio between process/function characteristic, uncertainty sizing, and fault elimination rate by inspection activities

Fault diagnosis of rotating machinery using an improved HHT based on EEMD and sensitive IMFs

International Nuclear Information System (INIS)

Lei, Yaguo; Zuo, Ming J

2009-01-01

A Hilbert–Huang transform (HHT) is a time–frequency technique and has been widely applied to analyzing vibration signals in the field of fault diagnosis of rotating machinery. It analyzes the vibration signals using intrinsic mode functions (IMFs) extracted using empirical mode decomposition (EMD). However, EMD sometimes cannot reveal the signal characteristics accurately because of the problem of mode mixing. Ensemble empirical mode decomposition (EEMD) was developed recently to alleviate this problem. The IMFs generated by EEMD have different sensitivity to faults. Some IMFs are sensitive and closely related to the faults but others are irrelevant. To enhance the accuracy of the HHT in fault diagnosis of rotating machinery, an improved HHT based on EEMD and sensitive IMFs is proposed in this paper. Simulated signals demonstrate the effectiveness of the improved HHT in diagnosing the faults of rotating machinery. Finally, the improved HHT is applied to diagnosing an early rub-impact fault of a heavy oil catalytic cracking machine set, and the application results prove that the improved HHT is superior to the HHT based on all IMFs of EMD

Identification of the meta-instability stage via synergy of fault displacement: An experimental study based on the digital image correlation method

Science.gov (United States)

Zhuo, Yan-Qun; Ma, Jin; Guo, Yan-Shuang; Ji, Yun-Tao

In stick-slip experiments modeling the occurrence of earthquakes, the meta-instability stage (MIS) is the process that occurs between the peak differential stress and the onset of sudden stress drop. The MIS is the final stage before a fault becomes unstable. Thus, identification of the MIS can help to assess the proximity of the fault to the earthquake critical time. A series of stick-slip experiments on a simulated strike-slip fault were conducted using a biaxial servo-controlled press machine. Digital images of the sample surface were obtained via a high speed camera and processed using a digital image correlation method for analysis of the fault displacement field. Two parameters, A and S, are defined based on fault displacement. A, the normalized length of local pre-slip areas identified by the strike-slip component of fault displacement, is the ratio of the total length of the local pre-slip areas to the length of the fault within the observed areas and quantifies the growth of local unstable areas along the fault. S, the normalized entropy of fault displacement directions, is derived from Shannon entropy and quantifies the disorder of fault displacement directions along the fault. Based on the fault displacement field of three stick-slip events under different loading rates, the experimental results show the following: (1) Both A and S can be expressed as power functions of the normalized time during the non-linearity stage and the MIS. The peak curvatures of A and S represent the onsets of the distinct increase of A and the distinct reduction of S, respectively. (2) During each stick-slip event, the fault evolves into the MIS soon after the curvatures of both A and S reach their peak values, which indicates that the MIS is a synergetic process from independent to cooperative behavior among various parts of a fault and can be approximately identified via the peak curvatures of A and S. A possible application of these experimental results to field conditions

Enhanced DET-Based Fault Signature Analysis for Reliable Diagnosis of Single and Multiple-Combined Bearing Defects

Directory of Open Access Journals (Sweden)

In-Kyu Jeong

2015-01-01

Full Text Available To early identify cylindrical roller bearing failures, this paper proposes a comprehensive bearing fault diagnosis method, which consists of spectral kurtosis analysis for finding the most informative subband signal well representing abnormal symptoms about the bearing failures, fault signature calculation using this subband signal, enhanced distance evaluation technique- (EDET- based fault signature analysis that outputs the most discriminative fault features for accurate diagnosis, and identification of various single and multiple-combined cylindrical roller bearing defects using the simplified fuzzy adaptive resonance map (SFAM. The proposed comprehensive bearing fault diagnosis methodology is effective for accurate bearing fault diagnosis, yielding an average classification accuracy of 90.35%. In this paper, the proposed EDET specifically addresses shortcomings in the conventional distance evaluation technique (DET by accurately estimating the sensitivity of each fault signature for each class. To verify the efficacy of the EDET-based fault signature analysis for accurate diagnosis, a diagnostic performance comparison is carried between the proposed EDET and the conventional DET in terms of average classification accuracy. In fact, the proposed EDET achieves up to 106.85% performance improvement over the conventional DET in average classification accuracy.

Model-based fault diagnosis approach on external short circuit of lithium-ion battery used in electric vehicles

International Nuclear Information System (INIS)

Chen, Zeyu; Xiong, Rui; Tian, Jinpeng; Shang, Xiong; Lu, Jiahuan

2016-01-01

Highlights: • The characteristics of ESC fault of lithium-ion battery are investigated experimentally. • The proposed method to simulate the electrical behavior of ESC fault is viable. • Ten parameters in the presented fault model were optimized using a DPSO algorithm. • A two-layer model-based fault diagnosis approach for battery ESC is proposed. • The effective and robustness of the proposed algorithm has been evaluated. - Abstract: This study investigates the external short circuit (ESC) fault characteristics of lithium-ion battery experimentally. An experiment platform is established and the ESC tests are implemented on ten 18650-type lithium cells considering different state-of-charges (SOCs). Based on the experiment results, several efforts have been made. (1) The ESC process can be divided into two periods and the electrical and thermal behaviors within these two periods are analyzed. (2) A modified first-order RC model is employed to simulate the electrical behavior of the lithium cell in the ESC fault process. The model parameters are re-identified by a dynamic-neighborhood particle swarm optimization algorithm. (3) A two-layer model-based ESC fault diagnosis algorithm is proposed. The first layer conducts preliminary fault detection and the second layer gives a precise model-based diagnosis. Four new cells are short-circuited to evaluate the proposed algorithm. It shows that the ESC fault can be diagnosed within 5 s, the error between the model and measured data is less than 0.36 V. The effectiveness of the fault diagnosis algorithm is not sensitive to the precision of battery SOC. The proposed algorithm can still make the correct diagnosis even if there is 10% error in SOC estimation.

Improvement of testing and maintenance based on fault tree analysis

International Nuclear Information System (INIS)

Cepin, M.

2000-01-01

Testing and maintenance of safety equipment is an important issue, which significantly contributes to safe and efficient operation of a nuclear power plant. In this paper a method, which extends the classical fault tree with time, is presented. Its mathematical model is represented by a set of equations, which include time requirements defined in the house event matrix. House events matrix is a representation of house events switched on and off through the discrete points of time. It includes house events, which timely switch on and off parts of the fault tree in accordance with the status of the plant configuration. Time dependent top event probability is calculated by the fault tree evaluations. Arrangement of components outages is determined on base of minimization of mean system unavailability. The results show that application of the method may improve the time placement of testing and maintenance activities of safety equipment. (author)

Optimal Design of Rectification Circuit in Electronic Circuit Fault Self-repair Based on EHW and RBT

Institute of Scientific and Technical Information of China (English)

ZHANG Junbin; CAI Jinyan; MENG Yafeng

2018-01-01

Reliability of traditional electronic circuit is improved mainly by redundant fault-tolerant technol-ogy with large hardware resource consumption and limited fault self-repair capability. In complicated environment, electronic circuit faults appear easily. If on-site immedi-ate repair is not implemented, normal running of elec-tronic system will be directly affected. In order to solve these problems, Evolvable hardware (EHW) technology is widely used. The conventional EHW has some bottlenecks. The optimal design of Rectification circuit (RTC) is fur-ther researched on the basis of the previously proposed fault self-repair based on EHW and Reparation balance technology (RBT). Fault sets are selected by fault danger degree and fault coverage rate. The optimal designed RTC can completely repair faults in the fault set. Simulation re-sults prove that it has higher self-repair capability and less hardware resource.

Improved fault ride through capability of DFIG based wind turbines using synchronous reference frame control based dynamic voltage restorer.

Science.gov (United States)

Rini Ann Jerin, A; Kaliannan, Palanisamy; Subramaniam, Umashankar

2017-09-01

Fault ride through (FRT) capability in wind turbines to maintain the grid stability during faults has become mandatory with the increasing grid penetration of wind energy. Doubly fed induction generator based wind turbine (DFIG-WT) is the most popularly utilized type of generator but highly susceptible to the voltage disturbances in grid. Dynamic voltage restorer (DVR) based external FRT capability improvement is considered. Since DVR is capable of providing fast voltage sag mitigation during faults and can maintain the nominal operating conditions for DFIG-WT. The effectiveness of the DVR using Synchronous reference frame (SRF) control is investigated for FRT capability in DFIG-WT during both balanced and unbalanced fault conditions. The operation of DVR is confirmed using time-domain simulation in MATLAB/Simulink using 1.5MW DFIG-WT. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Optimum IMFs Selection Based Envelope Analysis of Bearing Fault Diagnosis in Plunger Pump

Directory of Open Access Journals (Sweden)

Wenliao Du

2016-01-01

Full Text Available As the plunger pump always works in a complicated environment and the hydraulic cycle has an intrinsic fluid-structure interaction character, the fault information is submerged in the noise and the disturbance impact signals. For the fault diagnosis of the bearings in plunger pump, an optimum intrinsic mode functions (IMFs selection based envelope analysis was proposed. Firstly, the Wigner-Ville distribution was calculated for the acquired vibration signals, and the resonance frequency brought on by fault was obtained. Secondly, the empirical mode decomposition (EMD was employed for the vibration signal, and the optimum IMFs and the filter bandwidth were selected according to the Wigner-Ville distribution. Finally, the envelope analysis was utilized for the selected IMFs filtered by the band pass filter, and the fault type was recognized by compared with the bearing character frequencies. For the two modes, inner race fault and compound fault in the inner race and roller of rolling element bearing in plunger pump, the experiments show that a promising result is achieved.

Fault feature analysis of cracked gear based on LOD and analytical-FE method

Science.gov (United States)

Wu, Jiateng; Yang, Yu; Yang, Xingkai; Cheng, Junsheng

2018-01-01

At present, there are two main ideas for gear fault diagnosis. One is the model-based gear dynamic analysis; the other is signal-based gear vibration diagnosis. In this paper, a method for fault feature analysis of gear crack is presented, which combines the advantages of dynamic modeling and signal processing. Firstly, a new time-frequency analysis method called local oscillatory-characteristic decomposition (LOD) is proposed, which has the attractive feature of extracting fault characteristic efficiently and accurately. Secondly, an analytical-finite element (analytical-FE) method which is called assist-stress intensity factor (assist-SIF) gear contact model, is put forward to calculate the time-varying mesh stiffness (TVMS) under different crack states. Based on the dynamic model of the gear system with 6 degrees of freedom, the dynamic simulation response was obtained for different tooth crack depths. For the dynamic model, the corresponding relation between the characteristic parameters and the degree of the tooth crack is established under a specific condition. On the basis of the methods mentioned above, a novel gear tooth root crack diagnosis method which combines the LOD with the analytical-FE is proposed. Furthermore, empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) are contrasted with the LOD by gear crack fault vibration signals. The analysis results indicate that the proposed method performs effectively and feasibility for the tooth crack stiffness calculation and the gear tooth crack fault diagnosis.

Fault diagnosis of rolling bearings based on multifractal detrended fluctuation analysis and Mahalanobis distance criterion

Science.gov (United States)

Lin, Jinshan; Chen, Qian

2013-07-01

Vibration data of faulty rolling bearings are usually nonstationary and nonlinear, and contain fairly weak fault features. As a result, feature extraction of rolling bearing fault data is always an intractable problem and has attracted considerable attention for a long time. This paper introduces multifractal detrended fluctuation analysis (MF-DFA) to analyze bearing vibration data and proposes a novel method for fault diagnosis of rolling bearings based on MF-DFA and Mahalanobis distance criterion (MDC). MF-DFA, an extension of monofractal DFA, is a powerful tool for uncovering the nonlinear dynamical characteristics buried in nonstationary time series and can capture minor changes of complex system conditions. To begin with, by MF-DFA, multifractality of bearing fault data was quantified with the generalized Hurst exponent, the scaling exponent and the multifractal spectrum. Consequently, controlled by essentially different dynamical mechanisms, the multifractality of four heterogeneous bearing fault data is significantly different; by contrast, controlled by slightly different dynamical mechanisms, the multifractality of homogeneous bearing fault data with different fault diameters is significantly or slightly different depending on different types of bearing faults. Therefore, the multifractal spectrum, as a set of parameters describing multifractality of time series, can be employed to characterize different types and severity of bearing faults. Subsequently, five characteristic parameters sensitive to changes of bearing fault conditions were extracted from the multifractal spectrum and utilized to construct fault features of bearing fault data. Moreover, Hilbert transform based envelope analysis, empirical mode decomposition (EMD) and wavelet transform (WT) were utilized to study the same bearing fault data. Also, the kurtosis and the peak levels of the EMD or the WT component corresponding to the bearing tones in the frequency domain were carefully checked

Ocean-bottom pressure changes above a fault area for tsunami excitation and propagation observed by a submarine dense network

Science.gov (United States)

Yomogida, K.; Saito, T.

2017-12-01

Conventional tsunami excitation and propagation have been formulated by incompressible fluid with velocity components. This approach is valid in most cases because we usually analyze tunamis as "long gravity waves" excited by submarine earthquakes. Newly developed ocean-bottom tsunami networks such as S-net and DONET have dramatically changed the above situation for the following two reasons: (1) tsunami propagations are now directly observed in a 2-D array manner without being suffered by complex "site effects" of sea shore, and (2) initial tsunami features can be directly detected just above a fault area. Removing the incompressibility assumption of sea water, we have formulated a new representation of tsunami excitation based on not velocity but displacement components. As a result, not only dynamics but static term (i.e., the component of zero frequency) can be naturally introduced, which is important for the pressure observed on the ocean floor, which ocean-bottom tsunami stations are going to record. The acceleration on the ocean floor should be combined with the conventional tsunami height (that is, the deformation of the sea level above a given station) in the measurement of ocean-bottom pressure although the acceleration exists only during fault motions in time. The M7.2 Off Fukushima earthquake on 22 November 2016 was the first event that excited large tsunamis within the territory of S-net stations. The propagation of tsunamis is found to be highly non-uniform, because of the strong velocity (i.e., sea depth) gradient perpendicular to the axis of Japan Trench. The earthquake was located in a shallow sea close to the coast, so that all the tsunami energy is reflected by the trench region of high velocity. Tsunami records (pressure gauges) within its fault area recorded clear slow motions of tsunamis (i.e., sea level changes) but also large high-frequency signals, as predicted by our theoretical result. That is, it may be difficult to extract tsunami

Stress sensitivity of fault seismicity: A comparison between limited-offset oblique and major strike-slip faults

Science.gov (United States)

Parsons, T.; Stein, R.S.; Simpson, R.W.; Reasenberg, P.A.

1999-01-01

We present a new three-dimensional inventory of the southern San Francisco Bay area faults and use it to calculate stress applied principally by the 1989 M = 7.1 Loma Prieta earthquake and to compare fault seismicity rates before and after 1989. The major high-angle right-lateral faults exhibit a different response to the stress change than do minor oblique (right-lateral/thrust) faults. Seismicity on oblique-slip faults in the southern Santa Clara Valley thrust belt increased where the faults were unclamped. The strong dependence of seismicity change on normal stress change implies a high coefficient of static friction. In contrast, we observe that faults with significant offset (>50-100 km) behave differently; microseismicity on the Hayward fault diminished where right-lateral shear stress was reduced and where it was unclamped by the Loma Prieta earthquake. We observe a similar response on the San Andreas fault zone in southern California after the Landers earthquake sequence. Additionally, the offshore San Gregorio fault shows a seismicity rate increase where right-lateral/oblique shear stress was increased by the Loma Prieta earthquake despite also being clamped by it. These responses are consistent with either a low coefficient of static friction or high pore fluid pressures within the fault zones. We can explain the different behavior of the two styles of faults if those with large cumulative offset become impermeable through gouge buildup; coseismically pressurized pore fluids could be trapped and negate imposed normal stress changes, whereas in more limited offset faults, fluids could rapidly escape. The difference in behavior between minor and major faults may explain why frictional failure criteria that apply intermediate coefficients of static friction can be effective in describing the broad distributions of aftershocks that follow large earthquakes, since many of these events occur both inside and outside major fault zones.

Fault Tolerant Feedback Control

DEFF Research Database (Denmark)

Stoustrup, Jakob; Niemann, H.

2001-01-01

An architecture for fault tolerant feedback controllers based on the Youla parameterization is suggested. It is shown that the Youla parameterization will give a residual vector directly in connection with the fault diagnosis part of the fault tolerant feedback controller. It turns out...... that there is a separation be-tween the feedback controller and the fault tolerant part. The closed loop feedback properties are handled by the nominal feedback controller and the fault tolerant part is handled by the design of the Youla parameter. The design of the fault tolerant part will not affect the design...... of the nominal feedback con-troller....

Fault kinematics and localised inversion within the Troms-Finnmark Fault Complex, SW Barents Sea

Science.gov (United States)

Zervas, I.; Omosanya, K. O.; Lippard, S. J.; Johansen, S. E.

2018-04-01

The areas bounding the Troms-Finnmark Fault Complex are affected by complex tectonic evolution. In this work, the history of fault growth, reactivation, and inversion of major faults in the Troms-Finnmark Fault Complex and the Ringvassøy Loppa Fault Complex is interpreted from three-dimensional seismic data, structural maps and fault displacement plots. Our results reveal eight normal faults bounding rotated fault blocks in the Troms-Finnmark Fault Complex. Both the throw-depth and displacement-distance plots show that the faults exhibit complex configurations of lateral and vertical segmentation with varied profiles. Some of the faults were reactivated by dip-linkages during the Late Jurassic and exhibit polycyclic fault growth, including radial, syn-sedimentary, and hybrid propagation. Localised positive inversion is the main mechanism of fault reactivation occurring at the Troms-Finnmark Fault Complex. The observed structural styles include folds associated with extensional faults, folded growth wedges and inverted depocentres. Localised inversion was intermittent with rifting during the Middle Jurassic-Early Cretaceous at the boundaries of the Troms-Finnmark Fault Complex to the Finnmark Platform. Additionally, tectonic inversion was more intense at the boundaries of the two fault complexes, affecting Middle Triassic to Early Cretaceous strata. Our study shows that localised folding is either a product of compressional forces or of lateral movements in the Troms-Finnmark Fault Complex. Regional stresses due to the uplift in the Loppa High and halokinesis in the Tromsø Basin are likely additional causes of inversion in the Troms-Finnmark Fault Complex.

An Active Fault-Tolerant Control Method Ofunmanned Underwater Vehicles with Continuous and Uncertain Faults

Directory of Open Access Journals (Sweden)

Daqi Zhu

2008-11-01

Full Text Available This paper introduces a novel thruster fault diagnosis and accommodation system for open-frame underwater vehicles with abrupt faults. The proposed system consists of two subsystems: a fault diagnosis subsystem and a fault accommodation sub-system. In the fault diagnosis subsystem a ICMAC(Improved Credit Assignment Cerebellar Model Articulation Controllers neural network is used to realize the on-line fault identification and the weighting matrix computation. The fault accommodation subsystem uses a control algorithm based on weighted pseudo-inverse to find the solution of the control allocation problem. To illustrate the proposed method effective, simulation example, under multi-uncertain abrupt faults, is given in the paper.

A Method of Rotating Machinery Fault Diagnosis Based on the Close Degree of Information Entropy

Institute of Scientific and Technical Information of China (English)

GENG Jun-bao; HUANG Shu-hong; JIN Jia-shan; CHEN Fei; LIU Wei

2006-01-01

This paper presents a method of rotating machinery fault diagnosis based on the close degree of information entropy. In the view of the information entropy, we introduce four information entropy features of the rotating machinery, which describe the vibration condition of the machinery. The four features are, respectively, denominated as singular spectrum entropy, power spectrum entropy, wavelet space state feature entropy and wavelet power spectrum entropy. The value scopes of the four information entropy features of the rotating machinery in some typical fault conditions are gained by experiments, which can be acted as the standard features of fault diagnosis. According to the principle of the shorter distance between the more similar models, the decision-making method based on the close degree of information entropy is put forward to deal with the recognition of fault patterns. We demonstrate the effectiveness of this approach in an instance involving the fault pattern recognition of some rotating machinery.

A new iterative approach for multi-objective fault detection observer design and its application to a hypersonic vehicle

Science.gov (United States)

Huang, Di; Duan, Zhisheng

2018-03-01

This paper addresses the multi-objective fault detection observer design problems for a hypersonic vehicle. Owing to the fact that parameters' variations, modelling errors and disturbances are inevitable in practical situations, system uncertainty is considered in this study. By fully utilising the orthogonal space information of output matrix, some new understandings are proposed for the construction of Lyapunov matrix. Sufficient conditions for the existence of observers to guarantee the fault sensitivity and disturbance robustness in infinite frequency domain are presented. In order to further relax the conservativeness, slack matrices are introduced to fully decouple the observer gain with the Lyapunov matrices in finite frequency range. Iterative linear matrix inequality algorithms are proposed to obtain the solutions. The simulation examples which contain a Monte Carlo campaign illustrate that the new methods can effectively reduce the design conservativeness compared with the existing methods.

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

KAUST Repository

Harrou, Fouzi

2016-10-20

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

Reliability analysis of the solar array based on Fault Tree Analysis

International Nuclear Information System (INIS)

Wu Jianing; Yan Shaoze

2011-01-01

The solar array is an important device used in the spacecraft, which influences the quality of in-orbit operation of the spacecraft and even the launches. This paper analyzes the reliability of the mechanical system and certifies the most vital subsystem of the solar array. The fault tree analysis (FTA) model is established according to the operating process of the mechanical system based on DFH-3 satellite; the logical expression of the top event is obtained by Boolean algebra and the reliability of the solar array is calculated. The conclusion shows that the hinges are the most vital links between the solar arrays. By analyzing the structure importance(SI) of the hinge's FTA model, some fatal causes, including faults of the seal, insufficient torque of the locking spring, temperature in space, and friction force, can be identified. Damage is the initial stage of the fault, so limiting damage is significant to prevent faults. Furthermore, recommendations for improving reliability associated with damage limitation are discussed, which can be used for the redesigning of the solar array and the reliability growth planning.

Reliability analysis of the solar array based on Fault Tree Analysis

Energy Technology Data Exchange (ETDEWEB)

Wu Jianing; Yan Shaoze, E-mail: yansz@mail.tsinghua.edu.cn [State Key Laboratory of Tribology, Department of Precision Instruments and Mechanology, Tsinghua University,Beijing 100084 (China)

2011-07-19

The solar array is an important device used in the spacecraft, which influences the quality of in-orbit operation of the spacecraft and even the launches. This paper analyzes the reliability of the mechanical system and certifies the most vital subsystem of the solar array. The fault tree analysis (FTA) model is established according to the operating process of the mechanical system based on DFH-3 satellite; the logical expression of the top event is obtained by Boolean algebra and the reliability of the solar array is calculated. The conclusion shows that the hinges are the most vital links between the solar arrays. By analyzing the structure importance(SI) of the hinge's FTA model, some fatal causes, including faults of the seal, insufficient torque of the locking spring, temperature in space, and friction force, can be identified. Damage is the initial stage of the fault, so limiting damage is significant to prevent faults. Furthermore, recommendations for improving reliability associated with damage limitation are discussed, which can be used for the redesigning of the solar array and the reliability growth planning.

A Roller Bearing Fault Diagnosis Method Based on LCD Energy Entropy and ACROA-SVM

Directory of Open Access Journals (Sweden)

HungLinh Ao

2014-01-01

Full Text Available This study investigates a novel method for roller bearing fault diagnosis based on local characteristic-scale decomposition (LCD energy entropy, together with a support vector machine designed using an Artificial Chemical Reaction Optimisation Algorithm, referred to as an ACROA-SVM. First, the original acceleration vibration signals are decomposed into intrinsic scale components (ISCs. Second, the concept of LCD energy entropy is introduced. Third, the energy features extracted from a number of ISCs that contain the most dominant fault information serve as input vectors for the support vector machine classifier. Finally, the ACROA-SVM classifier is proposed to recognize the faulty roller bearing pattern. The analysis of roller bearing signals with inner-race and outer-race faults shows that the diagnostic approach based on the ACROA-SVM and using LCD to extract the energy levels of the various frequency bands as features can identify roller bearing fault patterns accurately and effectively. The proposed method is superior to approaches based on Empirical Mode Decomposition method and requires less time.

Numerical modelling of the mechanical and fluid flow properties of fault zones - Implications for fault seal analysis

NARCIS (Netherlands)