• Proceedings of the KIEE Conference
• /
• 1991.11a
• /
• pp.43-46
• /
• 1991

When a fault is occurred in Power System, relay system detect overcurrent or voltage drop and trip the circuit breaker. Then, an operator in the control room diagnoses the fault and start the recovery of the system after analyzing the alarm information of relays or circuit breakers. The alarm informations have different patterns for each fault of the electric equipments on lines in power systems. In this paper, Back propagation algorithm is applied to train for many kinds of the fault in the power system. The simulation results show the possibility of the neural network application for the fault diagnosis in the case of errorous operation as well as normal operation of relays or circuit breakers.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.25 no.8
• /
• pp.906-915
• /
• 1988

The reliability enhancement is the critical issue in many computer applications, particulary in process control system. In this paper we describe how to achieve the reliability improvement in control system which is based on multiprocessors. The proposed method is accomplished by using the techniques of fault detection which composed by internal and external fault detections, fault isolation for removing the fault propagation, safety action for driving safe input, and fault diagnosis. This approach is experimented and asopted in boiler backup control system constructed by VMEbus system, CPU boards, graphic system, and other interface boards with UNIX operating system.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.6
• /
• pp.63-70
• /
• 1994

In this paper, we propose a fault simulation method based on primary output in combinational circuit. In the deterministic test pattern generation, each test pattern is genterated incrementally. The test pattern is applied to the primary inputs of circuit under test to simulate faults. We detect the faults with respect to each primary output. The fault detection with resptect to each primary output is reflected by the corresponding bit in the detection words, and efficient fault detection for the reconvergent fan-out stem is achieved with dynamic fault propagation. As an experimental result of the fault simulation with our method for the several bench mark circuits, we illustrated the good performance showing that the number of gates to be activated is much reduced as compared with other method which is not based on primary output.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.2
• /
• pp.155-163
• /
• 2008

This paper presents a novel framework for analysis of power system wide-area blackout based on so called fault cascading scenarios. For a given power system operating state, "triggering" faults or a "seed faults" are chosen based on the probabilities estimated from the hazard rates. The fault probabilities reflect both the load and the weather conditions. Effects of hidden failures in protection systems are also reflected in establishing the fault propagation scenarios since they are one of the major causes for the wide-area blackouts. A tree type data structure called a PS-BEST(Power System Blackout Event Scenario Tree) is proposed for construction of the fault cascading scenarios, in which nodes represent various power system operating states and the arcs are the events causing transitions between the states. Arcs can be either probabilistic or deterministic. For a given initial fault, the total probability of leading to wide-area blackout is estimated by aggregating the individual probability of each fault sequence route leading to wide-area blackout. A case study is performed on the IEEE RTS-79(24 bus) system based on the fault data presented by the North American Electrical Reliability Council(NERC). Test results demonstrate the potentials and the effectiveness of the proposed technique for the future wide-area blackout analysis.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.14 no.5
• /
• pp.1-8
• /
• 2006

The Steer-By-Wire(SBW) system replaces complex mechanical linkages of the current steering system with electric motors, sensors, and electronic control units. However, the SBW system should guarantee its safety and reliability before commercialization, and therefore, a reliable and robust fault-tolerant technology has to be implemented. This paper proposes a fault-tolerant control algorithm for the SBW system. Based on careful analysis on propagation effects of sensor faults, a reliable fault-tolerant control strategy has been developed. The fault-tolerant controller consists of a fault detection part that monitors and detects faults in the steering wheel and road wheel sensors, and a reconfiguration part that switches to normal sensor signal based on fault detection information. It has been demonstrated by simulation that the proposed algorithm detects sensor faults accurately and enables reliable steering control under various dynamic fault situations.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.2
• /
• pp.9-20
• /
• 1998

In this paper, a new distance relaying scheme is proposed. Artificial neural networks are applied to the distance relaying system composed of pattern recognition based. The proposed distance relaying scheme has two blocks of pattern recognition stages to estimate the fundamental frequency and to classify the fault types. In the first block, a filtering method using neural networks called a neural networks mapping filter(NMF) is presented to efficiently extract the features. And in the sec'ond block, the estimator called neural networks fault pattern estimator(NFPE) is also presented to classify the fault types by the extracted effective features obtained from NMF. Each block of these applied schemes is trained by back-propagation algorithm of multilayer perceptron and show the fast and accurate pattern recognition by ability of multilayer neural networks. The test result of this approach are obtained the good performance from the fault transient wave signals of EMTP(e1ectromagnetic transients program) in the various fault conditions of power systems.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.17 no.5
• /
• pp.43-50
• /
• 2003

This presents a fault detecting method for a power transformer based upon a neural network. To maintain a normal relay operating conditions, external winding faults of a power transformer and magnetic inrush have been tested under consideration of the EMTP/ATP software and internal faults of power transformer have been tested by the EMTP/BCTRAN software. The neural network has been evaluated by the proposed fault. Input variables of the neural network for the proposed model can be obtained from fundamental currents, restraining and operating currents. This algorithm uses back-propagation and the ratio of a restraining current and an operating current as relay input parameters. The ratio may enhance the fault detection since the restraining currents increase rapidly at external faults. The proposed detecting method has been applied to the practical relay systems for transformer protection. As a result, the proposed detecting method based on the neural network has been shown to have better characteristics.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.6
• /
• pp.2219-2226
• /
• 2017

This paper deals with artificial neural network approach for automatic detection of severity level of stator winding fault in induction motor. The problem is faced through modelling and simulation of induction motor with inter coil shorting in stator winding. The sum of the absolute values of difference in the peak values of phase currents from each half cycle has been chosen as the main input to the classifier. Sample values from workspace of Simulink model, which are verified with experiment setup practically, have been imported to neural network architecture. Consideration of a single input extracted from time domain simplifies and advances the fault detection technique. The output of the feed forward back propagation neural network classifies the short circuit fault level of the stator winding.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.369_370
• /
• 2009

This paper describes the fault location method for HVDC submarine cables. Most conventional fault location methods can be applied in off-line. However, in this paper, on-line fault location algorithm is proposed using multi-scale correlating of wavelet coefficient and travelling wave. The propagation velocity is measured by field test on Jeju-Heanam submarine cable section. Finally, the fault location algorithm is tested by same system modeling using EMTP/ATP.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.805-812
• /
• 1989

An efficient diagnostic approach for real-time operation aiding expert system in chemical process plants is discussed. The approach is based on the hybrid of the simplified symptom tree(SST) and the fault consequence digraph(FCD), representation of propagation patterns of fault states. The SST generates fault hypothesis efficiently and the FCD resolve the real fault accurately. Frame based knowledge representation and object-oriented programming make diagnostic system general and efficient. Truth maintenance system enables robust pattern matching and provides enhanced explain facilities. A prototype expert system for supports operation of naphtha furnaces process, called OASYS, has been built and tested to demonstrate this methodology. Utilization of diversified process symbolic data, produced using dynamic normal standards, overcomes the problem of qualitative Boolean reasoning and enhance the applicability.