• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1066-1067
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• 2015

This paper presents a diagnosis method for the detection and location of open-short switch faults in the three-phase power conditioning system. A method for switch fault diagnosis on the power conditioning system is proposed, based on the concordia transform. The switch fault types and locations on power conditioning system are diagnosed by a method in which analyze the d-q current vector locus and current pattern. The Simulation results confirm the proposed diagnostic method.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.21-23
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• 1994

A Fault Detection. Isolation scheme based on ANN(Artifical Neural Network) is proposed for the supervision of a DC shunt motor. The Proposed FDI scheme can promptly detect the occurence of fault and classify all the faults that may occur during the operation. Also. it covers the full operating range in spite that the mathematical model of the motor contain strong nonlinearities. The simulation results show that the FDIU has good diagnostic ability even in the noisy environment.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.8
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• pp.787-795
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• 2001

An experimentation on the on-line fault detection and diagnosis(FDD) system has been performed with HVAC system in he experimental building constructed inside the large scale environmental chamber. Personal computer with a home-made FDD program by pattern recognition method utilizing artificial neural network was connected on-line via Ether-net TCP/IP to the supervisory control server for HVAC system. The FDD program monitored the HVAC system by 1 minuted interval. The results showed that he FDD program detected the sudden or abrupt faults such s those in fans, sensors and heater, etc.

• Journal of the Korea Safety Management & Science
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• v.4 no.4
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• pp.97-108
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• 2002

This study deals with the application of knowledge-based engineering and a methodology for the assessment & measurement of reliability, availability, maintainability, and safety of industrial systems using fault-tree representation. A fuzzy methodology for fault-tree evaluation seems to be an alternative solution to overcome the drawbacks of the conventional approach. To improve the quality of results, the membership functions must be approximated based on heuristic considerations. Conventionally, it is not always easy to obtain a system reliability for components with different individual failure probability density functions(p.d.f.), We utilize fuzzy set theory to solve the adequacy of the conventional probability in accounting and processing of built-in uncertainties in the probabilistic data. The purpose of this study is to propose the framework of knowledge-based engineering through integrating the various sources of knowledge involved in a FTA.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.34-42
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• 2009

Gas turbine performance diagnostics is a method for detecting, isolating and quantifying faults in gas turbine gas path components. On-line precise fault diagnosis can promote greatly reliability and availability of gas turbine in real time operation. This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module are used for reducing computer calculating time and a signal generation module for simulating real time performance data. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. Evaluation of the proposed on-line diagnostic program is performed through application to the helicopter engine health monitoring.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1694-1697
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• 2002

KEPCO is planing to adopt a preventive diagnostic system to obtain the reliability of transformer and GIS in 765kV substation. KEPRI has developed the preventive diagnostic system for 765kV substation since 1997. We used various sensors and fault detecting devices such as a dissolved gas analyzer in oil, a ultrasonic detector and LA leakage current detector, etc., and carried out adaptation tests at the both a laboratory and a site. We developed a data acquisition system, a communication control unit and a server system as well. Furthermore, monitoring program and diagnostic expert system were also developed. This paper describes the preventive diagnostic system for 765kV Sin-Ga-Pyong and Sin-Tae-Baek substations which will be operated from 2004.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1087-1096
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• 2016

This paper reports an investigation conducted on two diagnostic methods based on the switching voltage pattern of IGBT open-circuit faults in voltage-source inverters (VSIs). One method was based on the bridge arm pole voltage, and the other was based on bridge arm line voltage. With an additional simple circuit, these two diagnostic methods detected and effectively identified single and multiple open-circuit faults of inverter IGBTs. A comparison of the times for the diagnosis and anti-interference features between these two methods is presented. The diagnostic time of both methods was less than 280ns in the best case. The diagnostic time for the method based on the bridge arm pole voltage was less than that of the method based on the bridge arm line voltage and was 1/2 of the fundamental period in the worst case. An experimental study was carried out to show the effectiveness of and the differences between these two methods.

• Journal of the Korean Institute of Gas
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• v.28 no.2
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• pp.38-46
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• 2024

The city gas pipeline network is characterized by being widely distributed and hierarchically connected in a complex manner over a wide area. In order to monitor the status of the widely distributed network pressures with high precision, Multi-block PCA(MBPCA) is recommended. However, while MBPCA has excellent performance in identifying faulty sensors as the number of sensors increases, the fault detection performance deteriorates, and also there is a problem that the model needs to be updated entirely even if minor changes occur. In this study, we developed fault detectability index and fault identificability index to determine the effectiveness of MBPCA application block by block. Based on these indices, we distinguished MBPCA and PCA blocks and developed a fault detection and diagnostic system for the city gas pipeline network of Haean Energy Co., Ltd., and were able to solve the problems that arise when there are many sensors.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.5
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• pp.29-37
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• 2002

This paper presents the diagnostic method for fault prevention in metal clad switchgear(MCS) through comparison of signals before and after detecting the partial discharge using electromagnetic detection technique. Electromagnetic waves detected by antennas of the inside and outside of MCS are analyzed and compared by frequency spectrum analysis method which can estimate an insulation abnormality and normality of MCS. As a result of the experiment by the proposed method, we can detect the insulation abnormality as partial discharge in MCS and these results can be applied to preventive diagnosis of MCS.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.87-91
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• 2019

The diagnosis of the failure for the existing electrical facilities was based on regular preventive maintenance, but this preventive maintenance was limited in preventing a lot of cost loss and sudden system failure. To overcome these shortcomings, fault prediction and diagnostic techniques are critical to increasing system reliability by monitoring electrical installations in real time and detecting abnormal conditions in the facility early. As the performance and quality deterioration problem occurs frequently due to the increase in the number of users of the motor pump, the purpose is to build an intelligent control system that can control the motor pump to maximize the performance and to improve the quality and reliability. To this end, a vibration sensor, temperature sensor, pressure sensor, and low water level sensor are used to detect vibrations, temperatures, pressures, and low water levels that can occur in the motor pump, and to build a system that can identify and diagnose information to users in real time.