Showing papers on "Stuck-at fault published in 2016"

Observer-Based Fault Detection for Nonlinear Systems With Sensor Fault and Limited Communication Capacity

Abstract: In this technical note, a new fault detection design scheme is proposed for interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy systems with sensor fault based on a novel fuzzy observer. The parameter uncertainties can be captured by the membership functions of the IT2 fuzzy model. The premise variables of the plant are perfectly shared by the fuzzy observer. A stochastic process between the plant and the observer is considered in the system. A fault sensitive performance is established, and then sufficient conditions are obtained for determining the fuzzy observer gains. Finally, simulation results are provided to verify the effectiveness of the presented scheme.

Unknown Input Observer-Based Robust Fault Estimation for Systems Corrupted by Partially Decoupled Disturbances

Abstract: Robust fault estimation plays an important role in real-time monitoring, diagnosis, and fault-tolerance control. Accordingly, this paper aims to develop an effective fault estimation technique to simultaneously estimate the system states and the concerned faults, while minimizing the influences from process/sensor disturbances. Specifically, an augmented system is constructed by forming an augmented state vector composed of the system states and the concerned faults. Next, an unknown input observer (UIO) is designed for the augmented system by decoupling the partial disturbances and attenuating the disturbances that cannot be decoupled, leading to a simultaneous estimate of the system states and the concerned faults. In order to be close to the practical engineering situations, the process disturbances in this study are assumed not to be completely decoupled. In the first part of this paper, the existence condition of such an UIO is proposed to facilitate the fault estimation for linear systems subjected to process disturbances. In the second part, robust fault estimation techniques are addressed for Lipschitz nonlinear systems subjected to both process and sensor disturbances. The proposed technique is finally illustrated by the simulation studies of a three-shaft gas turbine engine and a single-link flexible joint robot.

Fault Diagnosis and Tolerant Control of Single IGBT Open-Circuit Failure in Modular Multilevel Converters

Abstract: The modular multilevel converter (MMC) is distinguished by its modularity that is the use of standardized submodules (SMs). To enhance reliability and avoid unscheduled maintenance, it is desired that an MMC can remain operational without having to shut down despite some of its SMs are failed. Particularly, in this paper, complete fault diagnosis and tolerant control solution, including the fault detection, fault tolerance, fault localization, and fault reconfiguration, have been proposed to ride through the insulated gate bipolar transistor open-circuit failures. The fault detection method detects the fault by means of state observers and the knowledge of fault behaviors of MMC, without using any additional sensors. Then, the MMC is controlled in a newly proposed tolerant mode until the specific faulty SM is located by the fault localization method; thus, no overcurrent problems will happen during this time interval. After that, the located faulty SM will be bypassed while the remaining SMs are reconfigured to provide continuous operation. Throughout the fault periods, it allows the MMC to operate smoothly without obvious waveform distortion and power interruption. Finally, experimental results using a single-phase scaled-down MMC prototype with six SMs per arm show the validity and feasibility of the proposed methods.

Open-Circuit Fault Diagnosis and Fault-Tolerant Control for a Grid-Connected NPC Inverter

Abstract: This paper presents an open-circuit fault detection method for a grid-connected neutral-point clamped (NPC) inverter system. Further, a fault-tolerant control method under an open-circuit fault in clamping diodes is proposed. Under the grid-connected condition, it is impossible to identify the location of a faulty switch by the conventional methods which usually use the distortion of outputs because the distortion of the outputs is the same in some fault cases. The proposed fault detection method identifies the location of the faulty switch and the faulty clamping diode of the NPC inverter without any additional hardware or complex calculations. In the case of the clamping diode faults, the NPC inverter can transfer full rated power with sinusoidal currents by the proposed fault-tolerant control. The feasibility of the proposed fault detection and the fault-tolerant control methods for the grid-connected NPC inverter are verified by simulation and experimental results.

Fault-Tolerant Operation of an Open-End Winding Five-Phase PMSM Drive With Short-Circuit Inverter Fault

Abstract: Multiphase machines are well known for their fault-tolerant capability. Star-connected multiphase machines have fault tolerance in an open circuit. For an inverter switch short-circuit fault, it is possible to keep a smooth torque of a permanent magnet synchronous machine if the currents of the faulty phases are determined and their values are acceptable. This paper investigates fault-tolerant operations of an open-end five-phase drive, i.e., a multiphase machine fed with a dual-inverter supply. Inverter switch short-circuit fault is considered and handled with a simple solution. Original theoretical developments are presented. Simulation and experimental results validate the proposed strategy.

Robustness Analysis and Experimental Validation of a Fault Detection and Isolation Method for the Modular Multilevel Converter

Abstract: This paper presents a fault detection and isolation (FDI) method for open-circuit faults of power semiconductor devices in a modular multilevel converter (MMC). The proposed FDI method is simple with only one sliding-mode observer (SMO) equation and requires no additional transducers. The method is based on an SMO for the circulating current in an MMC. An open-circuit fault of power semiconductor device is detected when the observed circulating current diverges from the measured one. A fault is located by employing an assumption-verification process. To improve the robustness of the proposed FDI method, a new technique based on the observer injection term is introduced to estimate the value of the uncertainties and disturbances; this estimated value can be used to compensate the uncertainties and disturbances. As a result, the proposed FDI scheme can detect and locate an open-circuit fault in a power semiconductor device while ignoring parameter uncertainties, measurement error, and other bounded disturbances. The FDI scheme has been implemented in a field-programmable gate array using fixed-point arithmetic and tested on a single-phase MMC prototype. Experimental results under different load conditions show that an open-circuit faulty power semiconductor device in an MMC can be detected and located in less than 50 ms.

A Novel Diagnostic Technique for Open-Circuited Faults of Inverters Based on Output Line-to-Line Voltage Model

Abstract: An output line-to-line voltage model-based fault diagnostic technique is presented in this paper. From the theoretical analysis of the output voltage under normal and faulty conditions, a preprocessing method is developed to extract fault features from diagnosis eigenvalue. A voltage envelope line is generated by the proposed voltage envelope function. By comparing the preprocessed diagnosis eigenvalue and the voltage envelope, single-switch open-circuit faults can be located precisely. Because the proposed method does not rely on the accurate amplitude of the output line-to-line voltage, the influence of the load changing is minimized and simple hardware is adopted, which has advantages of low cost, high reliability, and short diagnosis time. Moreover, as long as the inverter output voltages have the feature of periodic nonpositive and nonnegative, this method is valid no matter what control strategy is adopted by the inverter and no control signal is required for the diagnosis process. The prototype system is tested to validate the adaptability of the proposed method under different conditions, such as the diverse loads, various control strategies, and fault-occurrence time.

A Resilient Framework for Fault-Tolerant Operation of Modular Multilevel Converters

Abstract: This paper presents a resilient framework for fault-tolerant operation in modular multilevel converters (MMCs) to facilitate normal operation under internal and external fault conditions. This framework is realized by designing and implementing a supervisory algorithm and a postfault restoration scheme. The supervisory algorithm includes monitoring and decision-making units to detect and identify faults by analyzing the circulating current and submodule capacitor voltages in a very short time. The postfault restoration scheme is proposed to immediately replace the faulty submodule with the redundant healthy one. The restoration is achieved by virtue of a multilevel modular capacitor-clamped dc/dc converter (MMCCC), which is redundantly aggregated to each arm of the MMC. This design effectively guarantees smooth mode transition and handles the failure of multiple submodules in a short time interval. In addition, a modified modulation scheme is presented to ensure submodule capacitor voltage balancing of the MMC without implementing any additional hardware. Fast fault identification, a fully modular structure, and robust postfault restoration are the main features of the proposed framework. Digital time-domain simulation studies are conducted on a 21-level MMC to confirm the effectiveness and resilience of the proposed fault-tolerant framework during internal and external faults. Furthermore, the proposed framework is implemented in the FPGA-based RT-LAB real-time simulator platform to validate its resilience in a hardware-in-the-loop setup.

Controlling PC on ARM Using Fault Injection

Abstract: Fault injection attacks are a powerful technique to influence the intended behavior of embedded systems. They can be used to exploit or bypass robust security features found in secure embedded systems. Examples of such attacks include differential fault analysis (DFA) and bypassing authentication mechanisms. An embedded system's authenticated boot chain (i.e. secure boot) is an interesting target for fault injection. The initial boot stages are of limited size which means logically exploitable vulnerabilities are not guaranteed to be present. In this paper, we introduce an ARM specific fault injection attack strategy for exploiting embedded systems where externally controlled data is loaded in the program counter (PC) register of the processor. This allows an attacker to control the target's execution flow which eventually will lead to arbitrary code execution on the target. We first simulate the attack using a common fault model, after which we demonstrate the practicality of the attack using a development platform designed around an ARM based, fast and feature rich system on chip (SOC). We conclude with an overview of effective and non-effective countermeasures against this fault injection attack technique.

Robust state/fault estimation and fault tolerant control for T–S fuzzy systems with sensor and actuator faults

Abstract: This paper addresses the problems of state/fault estimation (FE) and fault tolerant control (FTC) for a class of Takagi–Sugeno (T–S) fuzzy systems subject to simultaneously external disturbances, sensor and actuator faults. A fuzzy-reduced-order robust state/fault estimation observer is proposed in this paper. The observer can not only estimate system state, sensor and actuator faults simultaneously, but also attenuate the influence of disturbances. Compared with the existing results, the observer has a wider application range and a lower dimension. Using the information of estimation, an observer-based fault tolerant controller is designed to compensate the fault effect and guarantee the stability of closed-loop system. In the paper, the observer and the controller are designed separately, which can avoid the coupling between them. As a result, the gain matrices of the observer and the controller can be calculated separately. At last, the simulations show the effectiveness of the proposed method.

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier

Abstract: Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis is one of the most significant issues in improving the reliability and reducing the outage cost for power systems. The limitation of training samples and types of machine faults in HVCBs causes the existing mechanical fault diagnostic methods to recognize new types of machine faults easily without training samples as either a normal condition or a wrong fault type. A new mechanical fault diagnosis method for HVCBs based on variational mode decomposition (VMD) and multi-layer classifier (MLC) is proposed to improve the accuracy of fault diagnosis. First, HVCB vibration signals during operation are measured using an acceleration sensor. Second, a VMD algorithm is used to decompose the vibration signals into several intrinsic mode functions (IMFs). The IMF matrix is divided into submatrices to compute the local singular values (LSV). The maximum singular values of each submatrix are selected as the feature vectors for fault diagnosis. Finally, a MLC composed of two one-class support vector machines (OCSVMs) and a support vector machine (SVM) is constructed to identify the fault type. Two layers of independent OCSVM are adopted to distinguish normal or fault conditions with known or unknown fault types, respectively. On this basis, SVM recognizes the specific fault type. Real diagnostic experiments are conducted with a real SF6 HVCB with normal and fault states. Three different faults (i.e., jam fault of the iron core, looseness of the base screw, and poor lubrication of the connecting lever) are simulated in a field experiment on a real HVCB to test the feasibility of the proposed method. Results show that the classification accuracy of the new method is superior to other traditional methods.

Open-Switch Fault Diagnosis and Fault Tolerant for Matrix Converter With Finite Control Set-Model Predictive Control

Abstract: To improve the reliability of the matrix converter (MC), a fault diagnosis method to identify a single open-switch fault is proposed in this paper. The introduced fault diagnosis method is based on finite control set-model predictive control (FCS-MPC), which employs a time-discrete model of the MC topology and a cost function to select the best switching state for the next sampling period. The proposed fault diagnosis method is realized by monitoring the load currents and judging the switching state to locate the faulty switch. Compared to the conventional modulation strategies such as carrier-based modulation method, indirect space vector modulation, and optimum Alesina–Venturini, the FCS-MPC has known and unchanged switching state in a sampling period. It is simpler to diagnose the exact location of the open switch in MC with FCS-MPC. To achieve better quality of the output current under single open-switch fault conditions without any redundant hardware, a fault tolerant strategy based on predictive control is also studied. The fault tolerant strategy is to select the most appropriate switching state associated with the remaining normal switches of the MC. Experiment results are presented to show the feasibility and effectiveness of the proposed fault diagnosis method and fault tolerant strategy.

Fast fault detection method for modular multilevel converter semiconductor power switches

Abstract: This study proposes a new fault detection method for modular multilevel converter (MMC) semiconductor power switches. While in common MMCs, the cells capacitor voltages are measured directly for control purposes, in this study voltage measurement point changes to the cell output terminal improving fault diagnosis ability. Based on this measurement reconfiguration, a novel fault detection algorithm is designed for MMCs semiconductor power switches. The open circuit and short circuit faults are detected based on unconformity between modules output voltage and switching signals. Simulation and experimental results confirm accurate and fast operation of the proposed method in faulty cell diagnosis. Implementation simplicity, no need to extra voltage measurements and multi faults detection ability are some other advantages of the proposed method.

Fuzzy logic based on-line fault detection and classification in transmission line

Abstract: This study presents fuzzy logic based online fault detection and classification of transmission line using Programmable Automation and Control technology based National Instrument Compact Reconfigurable i/o (CRIO) devices. The LabVIEW software combined with CRIO can perform real time data acquisition of transmission line. When fault occurs in the system current waveforms are distorted due to transients and their pattern changes according to the type of fault in the system. The three phase alternating current, zero sequence and positive sequence current data generated by LabVIEW through CRIO-9067 are processed directly for relaying. The result shows that proposed technique is capable of right tripping action and classification of type of fault at high speed therefore can be employed in practical application.

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

Abstract: 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.

A novel fault location method and algorithm for DC distribution protection

Abstract: DC fault current is contributed by various distributed energy resources in DC distribution systems. Most DC distribution systems have low line impedance. The fault current increases fast because of the low impedance. Some converters in DC distribution systems include Fault Current Limiting (FCL) function. The controlled fault currents at different locations are very close. Thus, it is important to design a reliable and fast fault detection and location method for DC distribution systems. This paper proposes a novel local measurement-based fault location algorithm for DC distribution systems. The proposed fault location algorithm can estimate the equivalent inductance from a protective device to a fault in less than one millisecond. The performance of the developed protection algorithm was validated in both numerical simulation and hardware testing.

An Analytic Model for Fault Diagnosis in Power Systems Utilizing Redundancy and Temporal Information of Alarm Messages

Abstract: In modern transmission systems, duplicated protections are widely employed to enhance reliability, and global positioning system (GPS) substation clocks are set up to deliver a higher degree of synchronization. Thus, redundant alarms tagged with synchronized timestamps would be received during a fault. Both redundancy and timestamps of alarms consist of rich and useful information. Given this background, an effort is made to develop a novel analytic model for power system fault diagnosis so as to well utilize redundancy and temporal information of alarms. An alarm preprocessing procedure is proposed to preserve such properties without impairing diagnosis accuracy and efficiency. A new fault hypothesis is established to systematically take account of malfunctions of protective devices, missing and distorted alarm messages, and timestamp errors in the proposed model. An objective function is developed for fault diagnosis, and could accommodate various protection schemes and bus configurations. Based on the presented fault diagnosis method, a software package is developed. Several fault scenarios occurred in an actual power system in China are served for demonstrating the correctness and efficiency of the developed software package.

Data-mining-based fault during power swing identification in power transmission system

Abstract: This study proposes a decision-tree-based scheme for detection and classification of fault during power swing in double circuit transmission lines. The power swing may result due to switching in/out of heavy loads, switching of lines, clearance of short-circuit faults, generator tripping or load shedding. The proposed decision tree approach makes the discrimination among no fault situation/power swing and fault during power swing. The fundamental components of currents and voltages and zero sequence currents measured at only one end of the double circuit line are used as input to decision tree. To ascertain validity of the proposed scheme, it is tested for variation in fault type, fault inception angle, fault location and fault resistance. The main advantage of this proposed scheme is that it detects fault during power swing within half cycle time and classify the type of fault and identify the faulty phase also.

Adaptive robust actuator fault compensation for linear systems using a novel fault estimation mechanism

Abstract: Summary This paper investigates the problem of adaptive fault-tolerant control for a class of linear systems with time-varying actuator faults. The outage and loss-of-effectiveness fault cases are covered. An active fault compensation control law was designed in two steps. Firstly, the time-varying fault parameters were estimated based on a novel adaptive observer. Compared with the traditional adaptive observer, the actuator fault estimations are faster and the high-frequency oscillations can be attenuated effectively. Such oscillations are usually caused by increasing the gains of adaptive laws to deal with abrupt changes in system dynamics. Then, based on online estimations of the fault parameters, an adaptive fault-tolerant controller was constructed to compensate for the loss of actuator effectiveness and to eliminate the effect of fault estimation error. The asymptotic stability and an adaptive performance of a closed-loop system can be guaranteed, even in the case of actuator faults and disturbances. Simulation results are given to verify the effectiveness and superiority of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.

A Novel Intermittent Fault Detection Algorithm and Health Monitoring for Electronic Interconnections

Abstract: There are various occurrences and root causes that result in no-fault-found (NFF) events but an intermittent fault (IF) is the most frustrating. This paper describes the challenging and most important area of an IF detection and health monitoring that focuses toward NFF situation in electronics interconnections. The experimental work focuses on mechanically-induced intermittent conditions in connectors. This paper illustrates a test regime, which can be used to repeatedly reproduce intermittence in electronic connectors, while subjected to vibration. A novel algorithm is used to detect an IF in interconnection. It sends a sine wave and decodes the received signal for intermittent information from the channel. This algorithm has been simulated to capture an IF signature using PSpice (electronic circuit simulation software). A simulated circuit is implemented for practical verification. However, measurements are presented using an oscilloscope. The results of this experiment provide an insight into the limitations of existing test equipment and requirements for future IF detection techniques. Aside from scheduled maintenance, this paper considers the possibility for in-service intermittent detection to be built into future systems, i.e., can IFs be captured without external test gear?