Showing papers on "Fault detection and isolation published in 2010"

Issues of Fault Diagnosis for Dynamic Systems

Abstract: There is an increasing demand for dynamic systems to become safer, more reliable and more economical in operation. This requirement extends beyond the normally accepted safety-critical systems e.g., nuclear reactors, aircraft and many chemical processes, to systems such as autonomous vehicles and some process control systems where the system availability is vital. The field of fault diagnosis for dynamic systems (including fault detection and isolation) has become an important topic of research. Many applications of qualitative and quantitative modelling, statistical processing and neural networks are now being planned and developed in complex engineering systems. Issues of Fault Diagnosis for Dynamic Systems has been prepared by experts in fault detection and isolation (FDI) and fault diagnosis with wide ranging experience.Subjects featured include: - Real plant application studies; - Non-linear observer methods; - Robust approaches to FDI; - The use of parity equations; - Statistical process monitoring; - Qualitative modelling for diagnosis; - Parameter estimation approaches to FDI; - Fault diagnosis for descriptor systems; - FDI in inertial navigation; - Stuctured approaches to FDI; - Change detection methods; - Bio-medical studies. Researchers and industrial experts will appreciate the combination of practical issues and mathematical theory with many examples. Control engineers will profit from the application studies.

A Survey of Fault Detection, Isolation, and Reconfiguration Methods

Abstract: Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults.

Survey on Fault Operation on Multilevel Inverters

Abstract: This paper is related to faults that can appear in multilevel (ML) inverters, which have a high number of components. This is a subject of increasing importance in high-power inverters. First, methods to identify a fault are classified and briefly described for each topology. In addition, a number of strategies and hardware modifications that allow for operation in faulty conditions are also presented. As a result of the analyzed works, it can be concluded that ML inverters can significantly increase their availability and are able to operate even with some faulty components.

Cost-Effective Condition Monitoring for Wind Turbines

Abstract: Cost-effective wind turbine (WT) condition monitoring assumes more importance as turbine sizes increase and they are placed in more remote locations, for example, offshore. Conventional condition monitoring techniques, such as vibration, lubrication oil, and generator current signal analysis, require the deployment of a variety of sensors and computationally intensive analysis techniques. This paper describes a WT condition monitoring technique that uses the generator output power and rotational speed to derive a fault detection signal. The detection algorithm uses a continuous-wavelet-transform-based adaptive filter to track the energy in the prescribed time-varying fault-related frequency bands in the power signal. The central frequency of the filter is controlled by the generator speed, and the filter bandwidth is adapted to the speed fluctuation. Using this technique, fault features can be extracted, with low calculation times, from direct- or indirect-drive fixed- or variable-speed WTs. The proposed technique has been validated experimentally on a WT drive train test rig. A synchronous or induction generator was successively installed on the test rig, and both mechanical and electrical fault like perturbations were successfully detected when applied to the test rig.

Adaptive Fault-Tolerant Tracking Control of Near-Space Vehicle Using Takagi–Sugeno Fuzzy Models

Abstract: Based on the adaptive-control technique, this paper deals with the problem of fault-tolerant tracking control for near-space-vehicle (NSV) attitude dynamics. First, Takagi-Sugeno (T-S) fuzzy models are used to describe the NSV attitude dynamics; then, an actuator-fault model is developed. Next, an adaptive fault-tolerant tracking-control scheme is proposed based on the online estimation of actuator faults, in which a compensation control term is introduced in order to reduce the effect of actuator faults. Compared with some existing results of fault-tolerant control (FTC) in nonlinear systems, the technique presented in this paper is not dependent on fault detection and isolation (FDI) mechanism and is easy to implement in aerospace-engineering applications. Finally, simulation results are given to illustrate the effectiveness and potential of the proposed FTC scheme.

Sensor faults: Detection methods and prevalence in real-world datasets

Abstract: Various sensor network measurement studies have reported instances of transient faults in sensor readings. In this work, we seek to answer a simple question: How often are such faults observed in real deploymentsq We focus on three types of transient faults, caused by faulty sensor readings that appear abnormal. To understand the prevalence of such faults, we first explore and characterize four qualitatively different classes of fault detection methods. Rule-based methods leverage domain knowledge to develop heuristic rules for detecting and identifying faults. Estimation methods predict “normal” sensor behavior by leveraging sensor correlations, flagging anomalous sensor readings as faults. Time-series-analysis-based methods start with an a priori model for sensor readings. A sensor measurement is compared against its predicted value computed using time series forecasting to determine if it is faulty. Learning-based methods infer a model for the “normal” sensor readings using training data, and then statistically detect and identify classes of faults.We find that these four classes of methods sit at different points on the accuracy/robustness spectrum. Rule-based methods can be highly accurate, but their accuracy depends critically on the choice of parameters. Learning methods can be cumbersome to train, but can accurately detect and classify faults. Estimation methods are accurate, but cannot classify faults. Time-series-analysis-based methods are more effective for detecting short duration faults than long duration ones, and incur more false positives than the other methods. We apply these techniques to four real-world sensor datasets and find that the prevalence of faults as well as their type varies with datasets. All four methods are qualitatively consistent in identifying sensor faults, lending credence to our observations. Our work is a first step towards automated online fault detection and classification.

Diagnosis of Bearing Faults in Induction Machines by Vibration or Current Signals: A Critical Comparison

Abstract: Mechanical imbalances and bearing faults account for a large majority of the faults in a machine, particularly for small-medium size machines. Therefore, their diagnosis is an intensively investigated field of research. Recently, many research activities were focused on the diagnosis of bearing faults by current signals. This paper compares the bearing fault detection capability obtained with the vibration and current signals. The paper contribution is the use of a simple and effective signal processing technique for both current and vibration signals, and a theoretical analysis of the physical link between faults, modeled as a torque disturbance, and current components. The focus of the paper is on the theoretical development of the correlation between torque disturbances and the amplitude of the current components, together with a review of fault models used in the literature. Another contribution is the re-creation of realistic incipient faults and their experimental validation. Radial effects are visible only in case of large failures that result in air-gap variations. Experiments are reported that confirm the proposed approach.

Using Mutation to Automatically Suggest Fixes for Faulty Programs

Abstract: This paper proposes a strategy for automatically fixing faults in a program by combining the processes of mutation and fault localization. Statements that are ranked in order of their suspiciousness of containing faults can then be mutated in the same order to produce possible fixes for the faulty program. The proposed strategy is evaluated against the seven benchmark programs of the Siemens suite and the Ant program. Results indicate that the strategy is effective at automatically suggesting fixes for faults without any human intervention.

A Novel Back Up Wide Area Protection Technique for Power Transmission Grids Using Phasor Measurement Unit

Abstract: Current differential protection relays are widely applied to the protection of electrical plant due to their simplicity, sensitivity and stability for internal and external faults. The proposed idea has the feature of unit protection relays to protect large power transmission grids based on phasor measurement units. The principle of the protection scheme depends on comparing positive sequence voltage magnitudes at each bus during fault conditions inside a system protection center to detect the nearest bus to the fault. Then the absolute differences of positive sequence current angles are compared for all lines connecting to this bus to detect the faulted line. The new technique depends on synchronized phasor measuring technology with high speed communication system and time transfer GPS system. The simulation of the interconnecting system is applied on 500 kV Egyptian network using Matlab Simulink. The new technique can successfully distinguish between internal and external faults for interconnected lines. The new protection scheme works as unit protection system for long transmission lines. The time of fault detection is estimated by 5 msec for all fault conditions and the relay is evaluated as a back up relay based on the communication speed for data transferring.

Dynamic Output Feedback-Fault Tolerant Controller Design for Takagi–Sugeno Fuzzy Systems With Actuator Faults

Abstract: This paper addresses the problem of robust fault estimation and fault tolerant control (FTC) for Takagi-Sugeno (T-S) fuzzy systems. A fuzzy-augmented fault estimation observer (AFEO) design is proposed to achieve fault estimation of T-S models with actuator faults. Furthermore, based on the information of online fault estimation, an observer-based dynamic output feedback-fault tolerant controller (DOFFTC) is designed to compensate for the effect of faults by stabilizing the closed-loop system. Sufficient conditions for the existence of both AFEO and DOFFTC are given in terms of linear matrix inequalities. Simulation results of an inverted pendulum system are presented to illustrate the effectiveness of the proposed method.

A Traveling-Wave-Based Protection Technique Using Wavelet/PCA Analysis

Abstract: This paper proposes a powerful high-speed traveling-wave-based technique for the protection of power transmission lines. The proposed technique uses principal component analysis to identify the dominant pattern of the signals preprocessed by wavelet transform. The proposed protection algorithm presents a discriminating method based on the polarity, magnitude, and time interval between the detected traveling waves at the relay location. A supplemental algorithm consisting of a high-set overcurrent relay as well as an impedance-based relay is also proposed. This is done to overcome the well-known shortcomings of traveling-wave-based protection techniques for the detection of very close-in faults and single-phase-to-ground faults occurring at small voltage magnitudes. The proposed technique is evaluated for the protection of a two-terminal transmission line. Extensive simulation studies using PSCAD/EMTDC software indicate that the proposed approach is reliable for rapid and correct identification of various fault cases. It identifies most of the internal faults very rapidly in less than 2 ms. In addition, the proposed technique presents high noise immunity.

Fault Detection by Means of Hilbert–Huang Transform of the Stator Current in a PMSM With Demagnetization

Abstract: This paper presents a novel method to diagnose demagnetization in permanent-magnet synchronous motor (PMSM). Simulations have been performed by 2-D finite-element analysis in order to determine the current spectrum and the magnetic flux distribution due to this failure. The diagnostic just based on motor current signature analysis can be confused by eccentricity failure because the harmonic content is the same. Moreover, it can only be applied under stationary conditions. In order to overcome these drawbacks, a novel method is used based upon the Hilbert-Huang transform. It represents time-dependent series in a 2-D time-frequency domain by extracting instantaneous frequency components through an empirical-mode decomposition process. This tool is applied by running the motor under nonstationary conditions of velocity. The experimental results show the reliability and feasibility of the methodology in order to diagnose the demagnetization of a PMSM.

Fault tolerant flight control : a benchmark challenge

Abstract: Surviving the Improbable: Towards Resilient Aircraft Control.- Fault Tolerant Flight Control - A Survey.- Fault Detection and Diagnosis for Aeronautic and Aerospace Missions.- Real-Time Identification of Aircraft Physical Models for Fault Tolerant Flight Control.- Industrial Practices in Fault Tolerant Control.- RECOVER: The Benchmark Challenge.- RECOVER: A Benchmark for Integrated Fault Tolerant Flight Control Evaluation.- Assessment Criteria as Specifications for Reconfiguring Flight Control.- Design Methods and Benchmark Analysis.- Fault Tolerant Control Using Sliding Modes with On-Line Control Allocation.- An Adaptive Fault-Tolerant FCS for a Large Transport Aircraft.- Subspace Predictive Control Applied to Fault-Tolerant Control.- Fault-Tolerant Control through a Synthesis of Model-Predictive Control and Nonlinear Inversion.- A FTC Strategy for Safe Recovery against Trimmable Horizontal Stabilizer Failure with Guaranteed Nominal Performance.- Flight Control Reconfiguration Based on Online Physical Model Identification and Nonlinear Dynamic Inversion.- A Combined Fault Detection, Identification and Reconfiguration System Based around Optimal Control Allocation.- Detection and Isolation of Actuator/Surface Faults for a Large Transport Aircraft.- Real-Time Flight Simulator Assessment.- Real-Time Assessment and Piloted Evaluation of Fault Tolerant Flight Control Designs in the SIMONA Research Flight Simulator.- Piloted Evaluation Results of a Nonlinear Dynamic Inversion Based Controller Using Online Physical Model Identification.- Model Reference Sliding Mode FTC with SIMONA Simulator Evaluation: EL AL Flight 1862 Bijlmermeer Incident Scenario.- Conclusions.- Industrial Review.- Concluding Remarks.

Adaptive backstepping fault-tolerant control for flexible spacecraft with unknown bounded disturbances and actuator failures.

Abstract: In this paper, a robust adaptive fault-tolerant control approach to attitude tracking of flexible spacecraft is proposed for use in situations when there are reaction wheel/actuator failures, persistent bounded disturbances and unknown inertia parameter uncertainties. The controller is designed based on an adaptive backstepping sliding mode control scheme, and a sufficient condition under which this control law can render the system semi-globally input-to-state stable is also provided such that the closed-loop system is robust with respect to any disturbance within a quantifiable restriction on the amplitude, as well as the set of initial conditions, if the control gains are designed appropriately. Moreover, in the design, the control law does not need a fault detection and isolation mechanism even if the failure time instants, patterns and values on actuator failures are also unknown for the designers, as motivated from a practical spacecraft control application. In addition to detailed derivations of the new controller design and a rigorous sketch of all the associated stability and attitude error convergence proofs, illustrative simulation results of an application to flexible spacecraft show that high precise attitude control and vibration suppression are successfully achieved using various scenarios of controlling effective failures.

Reconstruction-based contribution for process monitoring with kernel principal component analysis

Abstract: This paper presents a new method for fault diagnosis based on kernel principal component analysis (KPCA). The proposed method uses reconstruction-based contributions (RBC) to diagnose simple and complex faults in nonlinear principal component models based on KPCA. Similar to linear PCA, a combined index, based on the weighted combination of the Hotelling's T2 and SPE indices, is proposed. Control limits for these fault detection indices are proposed using second order moment approximation. The proposed fault detection and diagnosis scheme is tested with a simulated CSTR process where simple and complex faults are introduced. The simulation results show that the proposed fault detection and diagnosis methods are effective for KPCA.

Passive Actuators' Fault-Tolerant Control for Affine Nonlinear Systems

Abstract: In this brief, the problem of passive fault-tolerant control (FTC) for nonlinear affine systems with actuator faults is considered. Two types of faults, additive and loss-of-effectiveness faults, are treated. In each case, a Lyapunov-based feedback controller is proposed, which ensures the local uniform asymptotic (exponential) stability of the faulty system, if the safe nominal system is locally uniformly asymptotically (exponentially) stable. The effectiveness of the FT controllers is shown on the autonomous helicopter numerical example.

Fault tolerant control of a quadrotor UAV using sliding mode control

Abstract: In this paper, the sliding mode approach is used to control of a quadrotor unmanned aerial vehicle (UAV) in the presence of external disturbance and actuator fault. Fault detection unit can detect the actuator fault using a state estimator. Then it reconfigures the structure of controller such that some control performance is achieved. The proposed control structure has the advantage of disturbance rejection in the fault-free condition. Moreover it can recover some of control performances when a fault occurs. Different simulations have been carried out to show the performance and effectiveness of the proposed method.

Continuous Glucose Monitoring: Real-Time Algorithms for Calibration, Filtering, and Alarms

Abstract: Algorithms for real-time use in continuous glucose monitors are reviewed, including calibration, filtering of noisy signals, glucose predictions for hypoglycemic and hyperglycemic alarms, compensation for capillary blood glucose to sensor time lags, and fault detection for sensor degradation and dropouts. A tutorial on Kalman filtering for real-time estimation, prediction, and lag compensation is presented and demonstrated via simulation examples. A limited number of fault detection methods for signal degradation and dropout have been published, making that an important area for future work.

Fault diagnosis of spur bevel gear box using artificial neural network (ANN), and proximal support vector machine (PSVM)

Abstract: Vibration signals extracted from rotating parts of machineries carries lot many information with in them about the condition of the operating machine. Further processing of these raw vibration signatures measured at a convenient location of the machine unravels the condition of the component or assembly under study. This paper deals with the effectiveness of wavelet-based features for fault diagnosis of a gear box using artificial neural network (ANN) and proximal support vector machines (PSVM). The statistical feature vectors from Morlet wavelet coefficients are classified using J48 algorithm and the predominant features were fed as input for training and testing ANN and PSVM and their relative efficiency in classifying the faults in the bevel gear box was compared.

Fault Detection and Classification in EHV Transmission Line Based on Wavelet Singular Entropy

Abstract: A novel technique for fault detection and classification in the extremely high-voltage transmission line using the fault transients is proposed in this paper. The novel technique, called wavelet singular entropy (WSE), incorporates the advantages of the wavelet transform, singular value decomposition, and Shannon entropy. WSE is capable of being immune to the noise in the fault transient and not being affected by the transient magnitude so it can be used to extract features automatically from fault transients and express the fault features intuitively and quantitatively even in the case of high-noise and low-magnitude fault transients. The WSE-based fault detection is performed in this paper, which proves the availability and superiority of WSE technique in fault detection. A novel algorithm based on WSE is put forward for fault classification and it is verified to be effective and reliable under various fault conditions, such as fault type, fault inception time, fault resistance, and fault location. Therefore, the proposed WSE-based fault detection and classification is feasible and has great potential in practical applications.

Feature Extraction for Short-Circuit Fault Detection in Permanent-Magnet Synchronous Motors Using Stator-Current Monitoring

Abstract: In this paper, a novel frequency pattern and competent criterion are introduced for short-circuit-fault recognition in permanent-magnet synchronous motors (PMSMs). The frequency pattern is extracted from the monitored stator current analytically and the amplitude of sideband components at these frequencies is introduced as a proper criterion to determine the number of short-circuited turns. Impacts of the load variation on the proposed criterion are investigated in the faulty PMSM. In order to demonstrate the aptitude of the proposed criterion for precise short-circuit fault detection, the relation between the nominated criterion and the number of short-circuited turns is specified by the mutual information index. Therefore, a white Gaussian noise is added to the simulated stator current and robustness of the criterion is analyzed with respect to the noise variance. The occurrence and the number of short-circuited turns are predicted using support-vector machine as a classifier. The classification results indicate that the introduced criterion can detect the short-circuit fault incisively. Simulation results are verified by the experimental results.

Fault diagnosis and fault tolerant control using set-membership approaches: Application to real case studies

Abstract: This paper reviews the use of set-membership methods in fault diagnosis (FD) and fault tolerant control (FTC). Setmembership methods use a deterministic unknown-but-bounded description of noise and parametric uncertainty (interval models). These methods aims at checking the consistency between observed and predicted behaviour by using simple sets to approximate the exact set of possible behaviour (in the parameter or the state space). When an inconsistency is detected between the measured and predicted behaviours obtained using a faultless system model, a fault can be indicated. Otherwise, nothing can be stated. The same principle can be used to identify interval models for fault detection and to develop methods for fault tolerance evaluation. Finally, some real applications will be used to illustrate the usefulness and performance of set-membership methods for FD and FTC.

Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis

Abstract: Fault detection and diagnosis in mechanical systems during their time-varying nonstationary operation is one of the most challenging issues. In the last two decades or so researches have noticed that machines work in nonstationary load/speed conditions during their normal operation. Diagnostic features for gearboxes were found to be load dependent. This was experimentally confirmed by a smearing effect in the spectrum. In order to better understand the involved phenomena and to ensure agreement between simulation and experimental results, two models of gearboxes (a fixed-axis two-stage gearbox and a planetary gearbox) operating under varying load conditions are proposed. The models are based on two mechanical systems used in the mining industry, i.e. the belt conveyor and the bucket wheel excavator. An original transmission error function expressing changes in technical condition and load variation is presented. Energy based parameters (the signal RMS value or the arithmetic sum of the amplitudes of spectral gearmesh components) are adopted as the diagnostic features. Simulation results show a strong correlation between load values, changes in condition and the diagnostic features. The findings are key to condition monitoring. Thanks to the use of the models one can better understand the phenomena identified through an analysis of vibration signals captured from real machines.

Positive invariant sets for fault tolerant multisensor control schemes

Abstract: This article deals with fault tolerant multisensor control schemes for systems with linear dynamics. Positive invariance is a common analysis and control design tool for systems affected by bounded constraints and disturbances. This article revisits the construction of e-approximations of minimal robust positive invariant sets for linear systems upon contractive set-iterations. The cases of switching between different sets of disturbances and the inclusion of a predefined region of the state space are treated in detail. All these results are used in multisensor control schemes which have to deal with specific problems originated by the switching between different estimators and by the presence of faults in some of the sensors. The construction of positive invariant sets for different operating regimes provides, in this context, effective fault detection information. Within the same framework, global stability of the switching strategies can be assured if the invariant sets topology allows the exclusive se...

Detection of Symmetrical Faults by Distance Relays During Power Swings

Abstract: For maintaining security of distance relays, power swing blocking is necessary to prevent unintended operation under power swings. To be dependable, distance relays must operate whenever a fault occurs. Therefore, detecting faults during power swings is an important issue since the relay should be able to differentiate the fault condition and not be blocked during that time. This paper presents a new method for detecting a symmetrical fault during a power swing, based on extracting components of the current waveform using the Prony method. The merit of the method is demonstrated by simulating different faults during power swing conditions using the Alternate Transients Program version of the Electromagnetic Transients Program.