Showing papers on "Fault indicator published in 2012"

Short-Circuit and Ground Fault Analyses and Location in VSC-Based DC Network Cables

Abstract: The application of high-power voltage-source converters (VSCs) to multiterminal dc networks is attracting research interest. The development of VSC-based dc networks is constrained by the lack of operational experience, the immaturity of appropriate protective devices, and the lack of appropriate fault analysis techniques. VSCs are vulnerable to dc-cable short-circuit and ground faults due to the high discharge current from the dc-link capacitance. However, faults occurring along the interconnecting dc cables are most likely to threaten system operation. In this paper, cable faults in VSC-based dc networks are analyzed in detail with the identification and definition of the most serious stages of the fault that need to be avoided. A fault location method is proposed because this is a prerequisite for an effective design of a fault protection scheme. It is demonstrated that it is relatively easy to evaluate the distance to a short-circuit fault using voltage reference comparison. For the more difficult challenge of locating ground faults, a method of estimating both the ground resistance and the distance to the fault is proposed by analyzing the initial stage of the fault transient. Analysis of the proposed method is provided and is based on simulation results, with a range of fault resistances, distances, and operational conditions considered.

Fault Analysis and Traveling-Wave Protection Scheme for Bipolar HVDC Lines

Abstract: Explicit fault analysis is the basis of protection for the bipolar HVDC Line. The characteristics of the initial values of traveling waves under various internal fault conditions are investigated on the basis of the symmetrical component analysis. The criteria of fault classification and faulty-pole selection are put forward based on the zero- and positive-sequence backward traveling waves, and an integrated traveling wave-based protection scheme is proposed. The simulations based on real-time digital simulation show that the proposed scheme can detect faults rapidly, determine the fault type effectively, and select the faulty pole correctly.

Decision tree-based fault detection and classification in solar photovoltaic arrays

Abstract: Because of the non-linear output characteristics of PV arrays, a variety of faults may be difficult to detect by conventional protection devices. To detect and classify these unnoticed faults, a fault detection and classification method has been proposed based on decision trees (DT). Readily available measurements in existing PV systems, such as PV array voltage, current, operating temperature and irradiance, are used as "attributes" in the training and test set. In experimental results, the trained DT models have shown high accuracy of fault detection and fault classification on the test set.

Relyzer: exploiting application-level fault equivalence to analyze application resiliency to transient faults

Abstract: Future microprocessors need low-cost solutions for reliable operation in the presence of failure-prone devices. A promising approach is to detect hardware faults by deploying low-cost monitors of software-level symptoms of such faults. Recently, researchers have shown these mechanisms work well, but there remains a non-negligible risk that several faults may escape the symptom detectors and result in silent data corruptions (SDCs). Most prior evaluations of symptom-based detectors perform fault injection campaigns on application benchmarks, where each run simulates the impact of a fault injected at a hardware site at a certain point in the application's execution (application fault site). Since the total number of application fault sites is very large (trillions for standard benchmark suites), it is not feasible to study all possible faults. Previous work therefore typically studies a randomly selected sample of faults. Such studies do not provide any feedback on the portions of the application where faults were not injected. Some of those instructions may be vulnerable to SDCs, and identifying them could allow protecting them through other means if needed.This paper presents Relyzer, an approach that systematically analyzes all application fault sites and carefully picks a small subset to perform selective fault injections for transient faults. Relyzer employs novel fault pruning techniques that prune faults that need detailed study by either predicting their outcomes or showing them equivalent to other faults. We find that Relyzer prunes about 99.78% of the total faults across twelve applications studied here, reducing the faults that require detailed simulation by 3 to 5 orders of magnitude for most of the applications. Fault injection simulations on the remaining faults can identify SDC causing faults in the entire application. Some of Relyzer's techniques rely on heuristics to determine fault equivalence. Our validation efforts show that Relyzer determines fault outcomes with 96% accuracy, averaged across all the applications studied here.

Detection of Demagnetization Faults in Surface-Mounted Permanent Magnet Synchronous Motors by Means of the Zero-Sequence Voltage Component

Abstract: This paper develops and analyzes an online methodology to detect demagnetization faults in surface-mounted permanent magnet synchronous motors. The proposed methodology, which takes into account the effect of the inverter that feeds the machine, is based on monitoring the zero-sequence voltage component of the stator phase voltages. The theoretical basis of the proposed method has been established. Attributes of the method presented here include simplicity, very low computational burden, and high sensibility. Since the proposed method requires access to the neutral point of the stator windings, it is especially useful when dealing with fault tolerant systems. A simple expression of the zero-sequence voltage component is deduced, which is proposed as a fault indicator parameter. Both simulation and experimental results presented in this paper show the potential of the proposed method to provide helpful and reliable data to carry out an online diagnosis of demagnetization failures in the rotor permanent magnets.

PMU-Based Fault Location Using Voltage Measurements in Large Transmission Networks

Abstract: This paper presents a general fault-location method for large transmission networks which uses phasor measurement unit (PMU) voltage measurements where the injected current at a fault point can be calculated by using the voltage change and its relevant transfer impedance on any bus. A two-stage fault-location optimization model is proposed, along with defining a matching degree index. The first stage is the fault region identification stage, which uses the matching degree index to determine the suspicious fault region in order to reduce the search area. The second stage is used to identify the exact fault line and fault distance. A method to determine optimal PMU placement is also proposed in this paper. Case studies verify that the proposed fault-location algorithm and optimal PMU placement scheme can locate faults in large transmission networks quickly and accurately without requiring fault-type classification or fault phase selection.

Support Vector Machines for classification and locating faults on transmission lines

Abstract: This paper presents a new approach to classify fault types and predict the fault location in the high-voltage power transmission lines, by using Support Vector Machines (SVM) and Wavelet Transform (WT) of the measured one-terminal voltage and current transient signals. Wavelet entropy criterion is applied to wavelet detail coefficients to reduce the size of feature vector before classification and prediction stages. The experiments performed for different kinds of faults occurred on the transmission line have proved very good accuracy of the proposed fault location algorithm. The fault classification error is below 1% for all tested fault conditions. The average error of fault location in a 380kV-360-km transmission line is below 0.26% and the maximum error did not exceed 0.95km.

A Novel Approach to Detect Symmetrical Faults Occurring During Power Swings by Using Frequency Components of Instantaneous Three-Phase Active Power

Abstract: Since distance relays are prone to interpret a power swing as a three-phase fault, they should be blocked during the power swing to prevent undesired trips. On the other hand, if any fault occurs during a power swing, they should be fast and reliably unblocked. Although unblocking the relay is straightforward in the case of asymmetrical faults by using the zero-sequence and/or negative-sequence component of current, detecting symmetrical faults during a power swing is still a challenge. This paper presents a novel method for detecting symmetrical faults occurring during a power swing. Based on the damping frequency component of 50 (or 60) Hz created on instantaneous three-phase active power profile after inception of a symmetrical fault, the proposed method will be able to detect the fault in less than one power cycle. This detection method can be readily implemented, and is immune to the power swing slip frequency, fault inception time, and fault location. To test the proposed method, several power swings and faults are numerically simulated in MATLAB/SIMULNK, and the simulation results show that the proposed method is sensitive as well as reliable.

Differential Power-Based Symmetrical Fault Detection During Power Swing

Abstract: Distance relays are blocked during power swing to ensure reliability of the power system. However, if a fault occurs during a power swing, it should be detected and the unblocking function should be invoked to clear the fault as soon as possible. Due to the symmetric nature of signals during the power swing, symmetrical faults are difficult to be detected. In this paper, a differential power-based fault detection technique is proposed for the detection of symmetrical faults during power swings. The differential power is calculated from the difference in predicted and actual samples of voltage and current. The predicted voltage and current samples are obtained using the autoregression technique. The proposed method is tested for different fault conditions and the results are compared with the available method. The proposed method is found to identify symmetrical faults accurately during slow and fast power swings for different power systems.

Detection of Airgap Eccentricity for Permanent Magnet Synchronous Motors Based on the d-Axis Inductance

Abstract: The majority of the work performed for detecting eccentricity faults for permanent magnet synchronous motors (PMSM) focus on motor current signature analysis (MCSA), as it provides continuous online monitoring with existing current sensors. However, MCSA cannot be applied under nonstationary conditions and cannot distinguish faults with load torque oscillations, which are limitations for many PMSM drive applications. In this paper, it is shown that the d-axis inductance L decreases with an increase in the severity of eccentricity due to the change in the degree of magnetic saturation, and it is proposed as a new fault indicator. The inverter can be used to perform a standstill test automatically whenever the motor is stopped to measure L for eccentricity testing independent of load variations or oscillations, which is not possible with MCSA. An finite element and experimental study on a 10-hp PMSM verifies that eccentricity can be detected independent of the load with high sensitivity and reliability.

Accurate Single-Phase Fault-Location Method for Transmission Lines Based on K-Nearest Neighbor Algorithm Using One-End Voltage

Abstract: In this paper, some useful features are extracted from voltage signals measured at one terminal of the transmission line, which are highly efficient for accurate fault locating. These features are the amplitude of harmonic components, which are extracted after fault inception through applying discrete Fourier transform on one cycle of three-phase voltage signals and then are normalized by a transformation. In this paper, the location of single-line-to-ground faults as the most probable type of fault in the transmission networks is considered. The SLG fault locator, which is designed based on the simple algorithm of k-nearest neighbor (k-NN) in regression mode, estimates the location of fault related to the new input pattern based on existing available patterns. The proposed approach only needs the measured data from one terminal; hence, data communication between both ends of the line and synchronization are not required. In addition, current signals are not used; therefore, the proposed approach is immune against current-transformer saturation and its related errors. Tests conducted on an untransposed transmission line indicate that the proposed fault locator has accurate performance despite simultaneous changes in fault location, fault inception angle, fault resistance, and magnitude and direction of load current.

Fault Detection Isolation and Estimation in a Vehicle Steering System

Abstract: Recently, a bond-graph-based fault detection and isolation (FDI) framework has been developed with a new concept of global analytical redundancy relations (GARRs) (Low, Wang, Arogeti, and Luo, 2009, 2010; Low, Wang, Arogeti, and Zhang, 2010). This new concept allows the fault diagnosis for hybrid systems which consist of both continuous dynamics and discrete modes. A failure of a safety critical system such as the steering system of an automated guided vehicle may cause severe damage. Such failure can be avoided by an early detection and estimation of faults. In this paper, the newly developed FDI method is studied in details using an electrohydraulic steering system of an electric vehicle. The steering system and faults are modeled as a hybrid dynamic system by the hybrid bond graph (HBG) modeling technique. GARRs are then derived systematically from the HBG model with a specific causality assignment. Fault detection, isolation, and estimation are applied, experimental setup is described, and results are discussed.

A knowledge-based system approach for sensor fault modeling, detection and mitigation

Abstract: Sensors are vital components for control and advanced health management techniques. However, sensors continue to be considered the weak link in many engineering applications since often they are less reliable than the system they are observing. This is in part due to the sensors' operating principles and their susceptibility to interference from the environment. Detecting and mitigating sensor failure modes are becoming increasingly important in more complex and safety-critical applications. This paper reports on different techniques for sensor fault detection, disambiguation, and mitigation. It presents an expert system that uses a combination of object-oriented modeling, rules, and semantic networks to deal with the most common sensor faults, such as bias, drift, scaling, and dropout, as well as system faults. The paper also describes a sensor correction module that is based on fault parameters extraction (for bias, drift, and scaling fault modes) as well as utilizing partial redundancy for dropout sensor fault modes). The knowledge-based system was derived from the results obtained in a previously deployed Neural Network (NN) application for fault detection and disambiguation. Results are illustrated on an electro-mechanical actuator application where the system faults are jam and spalling. In addition to the functions implemented in the previous work, system fault detection under sensor failure was also modeled. The paper includes a sensitivity analysis that compares the results previously obtained with the NN. It concludes with a discussion of similarities and differences between the two approaches and how the knowledge based system provides additional functionality compared to the NN implementation.

A New Method for Power Converter Fault Diagnosis in SRM Drives

Abstract: This paper presents a new fault diagnostic technique applied to switched reluctance motor drives, based on the analysis of the power converter supply current. A fault is detected when the measured amplitude of the dc bus current differs from its expected amplitude, assuming normal operating conditions. The information about phase currents amplitudes and the control commands of all power switches permit to easily estimate the amplitude of the power converter supply current, since an asymmetric bridge converter is used. Simulation and experimental results are presented. Open- and short-circuit fault occurrences in the converter power switches are considered and analyzed. The proposed technique can early detect these fault occurrences and can also identify the affected motor phase. In almost all situations, the faulty element is also identified. An early fault diagnosis, with an accurate fault identification, is of a paramount importance since it permits the early adoption of fault-tolerant procedures that minimize the fault impact on the machine operation.

A Novel Approach for Fault Location of Overhead Transmission Line With Noncontact Magnetic-Field Measurement

Abstract: Prompt and accurate location of faults in a large- scale transmission system can accelerate system restoration, reduce outage time, and improve system reliability. Traditional approaches are categorized into traveling-wave-based and impedance-based measurement techniques. The traveling-wave-based approach requires detection devices to connect to the high-voltage transmission line, making the solution complex and costly. And the impedance-measurement-based approach is highly dependent on the quality of the signal and affected by fault resistance, ground resistance and non-homogeneity in line configuration. Hence, these approaches may cause a location error that is unacceptable in certain operation cases. In this paper, a novel approach based on noncontact magnetic-field measurement is proposed. With the magnetic field measured along the transmission line by using highly sensitive, broadband, and a low-cost magnetoresistive magnetic sensor, the fault span can be located. The collected data can be further used for identifying the fault type and location within the fault span. The overall system was designed and numerical simulations were performed on typical tower configurations. The simulated results verify the validity of the proposed scheme.

Short-Circuit Fault Protection Strategy for High-Power Three-Phase Three-Wire Inverter

Abstract: This paper proposes a four-stage fault protection scheme against the short-circuit fault for the high-power three-phase three-wire combined inverter to achieve high reliability. The short-circuit fault on the load side is the focus of this paper, and the short-circuit fault of switching devices is not involved. Based on the synchronous rotating frame, the inverter is controlled as a voltage source in the normal state. When a short-circuit fault (line-to-line fault or balanced three-phase fault) occurs, the hardware-circuit-based hysteresis current control strategy can effectively limit the output currents and protect the switching devices from damage. In the meantime, the software controller detects the fault and switches to the current controlled mode. Under the current controlled state, the inverter behaves as a current source until the short-circuit fault is cleared by the circuit breaker. After clearing the fault, the output voltage recovers quickly from the current controlled state. Therefore, the selective protection is realized and the critical loads can be continuously supplied by the inverter. The operational principle, design consideration, and implementation are discussed in this paper. The simulation and experimental results are provided to verify the validity of theoretical analysis.

Effects of the fault inception angle in fault-induced transients

Abstract: The analysis of fault-induced transients in three-phase overhead transmission lines can provide extensive information about the fault type, detection, location, direction and sustained time in satisfactory agreement with real application in protective relays These transients depend on the system topology, load condition and the fault parameters, such as the fault type, resistance, inception angle and location This study addresses the fault inception angle effects in the energies of the fault-induced transients in both voltages and currents by means of the wavelet coefficient energy analysis at the first three wavelet scales, in which a generic energy equation regarding the fault-induced transients as a function of the fault inception angle in all kinds of faults was established

Fault Detection and Classification in Plasma Etch Equipment for Semiconductor Manufacturing $e$ -Diagnostics

Abstract: A method of fault detection and classification (FDC) for semiconductor manufacturing equipment e-diagnostics using equipment data is presented. Detecting faulty processes, identifying any anomaly at their onsets, and rapidly classifying the root cause of the fault are crucial for maximizing equipment utilization in current semiconductor manufacturing; however, tool data acquired from production equipment contains much information that is often challenging to analyze due to its sheer volume and complexity. In this paper, modular neural network (MNN) modeling is presented as a method for fault detection modeling in plasma etching. Based on the result from the MNN modeling, a tool data set is grouped according to its related subsystems, and FDC is performed using Dempster-Shafer (D-S) theory to address the uncertainty associated with fault diagnosis. Subsystem level fault detections, such as radio frequency (RF) power source module, RF power bias module, gas delivery module, and process chamber module, are presented by combining related parameters, and successful fault detection is achieved. The evidential reasoning of RF probe is also beneficial for the detection of chamber leak simulation, and the classification of fault is made by further investigating voltage signal of RF probe. Successful fault detection in subsystem level with zero missed alarms was demonstrated using D-S theory of evidential reasoning, and the classification for finding root cause of the fault is presented in the chamber leak fault simulation. We realized that successful FDC can be accomplished by combining various related information and by incorporating engineering expert knowledge.

Sensor fault estimation and compensation for time-delay switched systems

Abstract: In this article, the problems of sensor fault estimation and compensation approaches for time-delay switched systems are investigated based on a switched descriptor observer approach. First, a novel time-delay switched descriptor state observer is proposed to estimate both the state and sensor fault. The proposed observer technique is also extended to systems with nonlinearities. Then, based on the estimation of the sensor fault, an efficient fault-tolerant operation can be realised via sensor fault compensation. Finally, an example is given to show the efficiency of the developed techniques.

Superconducting fault current limiter to mitigate the effect of DC line fault in VSC-HVDC system

Abstract: Voltage source converter based HVDC systems involving overhead transmission lines are prone to severe over-voltages during line faults. At present, they find applications only in back to back and/or underground cable transmission, with low power ratings. A conventional HVDC system suppresses the dc fault very well with the controllers and smoothing reactors while the same is not true with voltage source converter based HVDC systems. This necessitates the operation of some kind of protective devices. A superconducting fault current limiter, in this regard, is a possible device which can mitigate the effects of dc line faults. In this work, it is aimed to evaluate the dynamic performance of VSC-HVDC system integrated with a superconducting fault current limiter. The resistive superconducting fault current limiter is modeled in MATLAB and is interfaced with low voltage VSC-HVDC system, in PSCAD/EMTDC environment. The results of analysis for various ac and dc fault conditions are presented.

Efficient Placement of Fault Indicators in an Actual Distribution System Using Evolutionary Computing

Abstract: This paper proposes an evolutionary computing strategy to solve the problem of fault indicator (FI) placement in primary distribution feeders. More specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions on the main feeder of a real-life distribution system. Thus, the problem is modeled as one of optimization, aimed at improving the distribution reliability indices, while, at the same time, finding the least expensive solution. Based on actual data, the results confirm the efficiency of the GA approach to the FI placement problem.

System and method for automated failure detection of hold-up power storage devices

Abstract: A fault detection circuit is utilized to automatically detect faults in hold-up power storage devices. The fault detection circuit includes a hold-up monitoring circuit 22 and a memory device 24. The hold-up monitoring circuit is connected to monitor output of the hold-up power storage device 18, wherein the hold-up monitoring circuit measures a duration of time that the hold-up power storage device provides sufficient power following a loss of normal power and detects faults based on the measured duration of time. The memory device is connected to store the duration of time measured by the hold-up power storage device following a loss of normal power

Small-delay-fault ATPG with waveform accuracy

Abstract: The detection of small-delay faults is traditionally performed by sensitizing transitions on a path of sufficient length from an input to an output of the circuit going through the fault site. While this approach allows efficient test generation algorithms, it may result in false positives and false negatives as well, i.e. undetected faults are classified as detected or detectable faults are classified as undetectable. We present an automatic test pattern generation algorithm which considers waveforms and their propagation on each relevant line of the circuit. The model incorporates individual delays for each gate and filtering of small glitches. The algorithm is based on an optimized encoding of the test generation problem by a Boolean satisfiability (SAT) instance and is implemented in the tool WaveSAT. Experimental results for ISCAS-85, ITC-99 and industrial circuits show that no known definition of path sensitization can eliminate false positives and false negatives at the same time, thus resulting in inadequate small-delay fault detection. WaveSAT generates a test if the fault is testable and is also capable of automatically generating a formal redundancy proof for undetectable small-delay faults; to the best of our knowledge this is the first such algorithm that is both scalable and complete.

Fault Detection and Classification on a Transmission Line using Wavelet Multi Resolution Analysis and Neural Network

Abstract: and distribution lines are vital links between generating units and consumers. They are exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high, which has to be immediately taken care of in order to minimize damage caused by it. In this paper discrete wavelet transform of voltage signals at the two ends of the transmission lines have been analyzed. Transient energies of detail information for two consecutive data windows at fault are used for analysis. Four layer feed forward back propagation neural networks are designed to classify and locate the fault at different single line to ground fault conditions.

New Fault-Based Side-Channel Attack Using Fault Sensitivity

Abstract: This paper proposes a new fault-based attack called fault sensitivity analysis (FSA) attack. In the FSA attack, fault injections are used to test out the sensitive information leakage called fault sensitivity. Fault sensitivity means the critical fault injection intensity that corresponds to the threshold between devices' normal and abnormal behaviors. We demonstrate that without using the values of the faulty outputs, attackers can obtain the information of the secret key based on the data-dependency of the collected fault sensitivity data. This paper explains the successful FSA attacks against three Advanced Encryption Standard (AES) hardware implementations, where two of them are resistant to the differential fault analysis. This paper also discusses the countermeasures against the proposed FSA attacks.