• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.220-227
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• 2010

This paper presents a novel fault location scheme on Korean AC electric railway systems. On AC railway system, because of long distance, 40[km] or above, between two railway substations, a fault location technique is very important. Since the fault current flows through the catenary system, it must be modeled exactly to analyze the fault current magnitude and fault location. In this paper, suggesting the novel scheme of fault location, a 9-conductor modeling technique including boost wires and impedance bonds is introduced based on the characteristics of Korean AC electric railway. After obtaining a 9-conductor modeling, the railway system is constructed for computer simulation by using PSCAD/EMTDC. By case studies, we can verify superiority of a new fault location scheme and propose a powerful model for fault analysis on electric railway systems.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.89-99
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• 2018

Downtime and malfunction of industrial rotor machines represents a crucial cost burden and productivity loss. Fault diagnosis of this equipment has recently been carried out to detect their fault(s) and cause(s) by using fault classification methods. However, these methods are of limited use in detecting rotor faults because of their hypersensitivity to unexpected and different equipment conditions individually. These limitations tend to affect the accuracy of fault classification since fault-related features calculated from vibration signal are moved to other regions or changed. To improve the limited diagnosis accuracy of existing methods, we propose a new approach for fault diagnosis of rotor machines based on the model generated by supervised learning. Our work is based on feature residual values from vibration signals as fault indices. Our diagnostic model is a robust and flexible process that, once learned from historical data only one time, allows it to apply to different target systems without optimization of algorithms. The performance of the proposed method was evaluated by comparing its results with conventional methods for fault diagnosis of rotor machines. The experimental results show that the proposed method can be used to achieve better fault diagnosis, even when applied to systems with different normal-state signals, scales, and structures, without tuning or the use of a complementary algorithm. The effectiveness of the method was assessed by simulation using various rotor machine models.

• ETRI Journal
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• v.36 no.3
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• pp.469-478
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• 2014

RSA signature algorithms using the Chinese remainder theorem (CRT-RSA) are approximately four-times faster than straightforward implementations of an RSA cryptosystem. However, the CRT-RSA is known to be vulnerable to fault attacks; even one execution of the algorithm is sufficient to reveal the secret keys. Over the past few years, several countermeasures against CRT-RSA fault attacks have tended to involve additional exponentiations or inversions, and in most cases, they are also vulnerable to new variants of fault attacks. In this paper, we review how Shamir's countermeasure can be broken by fault attacks and improve the countermeasure to prevent future fault attacks, with the added benefit of low additional costs. In our experiment, we use the side-channel analysis resistance framework system, a fault injection testing and verification system, which enables us to inject a fault into the right position, even to within $1{\mu}s$. We also explain how to find the exact timing of the target operation using an Atmega128 software board.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.341-350
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• 2005

In this study, fault diagnosis and monitoring of serial wound pre-engaged starter motors have been carried out. Starter motors are DC motors that enable internal combustion engine (ICE) to run. In case of breakdown of a starter motor, internal combustion engine can not be worked. Starter motors have vital importance on internal combustion engines. Kohonen network based fault diagnosis system is proposed for fault diagnosis and monitoring of starter motors. A graphical user interface (GUI) software has been developed by using Visual Basic 6.0 for fault diagnosis. Six faults, seen in starter motors, have been diagnosed successfully by using the developed fault diagnosis system. GUI software makes it possible to diagnose the faults in starter motors before they occur by keeping fault records of past occurrences.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.42-48
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• 2003

In general many engineers can diagnose the fault condition using the abnormal ones among data monitored from a diesel engine, but they don't need the system modelling or identification for the work. They check the abnormal data and the relationship and then catch the fault condition of the engine. This paper proposes the construction of a fault diagnosis engine through malfunction data gained from the data fault detection system of neural networks for diesel generator engine, and the rule inference method to induce the rule for fuzzy inference from the malfunction data of diesel engine like a site engineer with a fuzzy system. The proposed fault diagnosis system is constructed in the sense of the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HMH). The system is concerned with the rule reduction method of knowledge base for related data among the various interactive data.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.542-549
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• 2004

The conventional fault location algorithms based on the travelling waves have an inherent problem. In cases of the close-up faults occurring near the relaying point and of the faults having zero degree inception angle of voltage signals, the conventional algorithms can not estimate an accurate fault distance. It is because the shapes of travelling waves are near sinusoidal in those cases. A new method solving this problem is presented in this paper. An FIR(Finite Impulse response) filter which makes high frequency components prominent and makes the power frequency component and dc-offset attenuated is used. With this method, the cross-correlation peak is to be very clear when a close-up fault or a fault having near zero-degree inception angle occurs. The cross-correlation peaks can be clearly distinguished and accurate fault location is practically possible consequently. A series of simulation studies using EMTP(Electromagnetic Transients Program) show that the proposed algorithm can calculate an accurate fault distance having maximum 2% or less error.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.184-190
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• 2008

The fault location algorithm based on stationary wavelet transform was developed to locate the fault point more accurately. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. In previous paper, noise cancellation technique based on the correlation of wavelet coefficients at multi-scales was introduced, and the efficiency was also proved in full. In this paper, fault section discrimination and fault location algorithm using noise cancellation technique were tested by ATP simulation on real power cable systems. From these results, the fault can be located even in very difficult and complicated situations such as different inception angle and fault resistance.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.4
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• pp.202-206
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• 2006

In this paper, an auto detection method of stator winding fault of small induction motor is suggested. The Park's vector pattern which is obtained from 3-phase current signal by d-q transforming, is very good to detect winding fault. Comparing the Park's vector pattern of testing motor with its of healthy motor, the Park's vector pattern of fault motor is became an ellipse and the asymmetry is increased by the winding fault series. So for detecting the dis-symmetry, id-filtered function, Min-value, and Max-value are suggested for auto detecting. Using LabVIEW programing, 3-phase healthy motor and several kind of winding fault motors are tested and the test results are shown that the suggested method can gives us a possibility of an auto detecting winding fault.

• Journal of Power Electronics
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• v.6 no.1
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• pp.8-17
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• 2006

In this paper, we propose a fault-tolerant control system for the position control and vibration suppression of a flexible arm robot. The proposed control system has a strain gauge sensor signal observer based on a reaction force observer and detects a fault by monitoring an estimated error. In order to improve the estimation accuracy, the plant parameters included in the sensor signal observer are updated by using the strain gauge sensor signal in normal time through the adaptive law. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault mode controller so as to maintain the stability and the control performance. We confirmed the effectiveness of the proposed control system through several experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1869-1880
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• 2009

Distribution line fault has been reduced gradually by the efforts on improving the quality of electrical materials and distribution system maintenance. However faults caused by medium voltage customers have been increased gradually even though we have done many efforts. The problem is that we don't know which customer will cause the fault. This paper presents the concept to find these customers using data mining techniques, which is based on accumulated fault records of medium voltage customers in the past. It also suggests the prediction model construction of medium voltage customers causing distribution line fault and methods to enhance the reliability of distribution system. We expect that we can effectively reduce faults resulted from medium voltage customers, which is 30% of total faults.