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논문 기본 정보

자료유형
학술저널
저자정보
Ali Rohan (Kunsan National University) Sung Ho Kim (Kunsan National University)
저널정보
한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.19 No.2
발행연도
2019.6
수록면
78 - 87 (10page)
DOI
10.5391/IJFIS.2019.19.2.78

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초록· 키워드

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The RLC circuit is a basic building block of the more complicated electrical circuits and networks. RLC circuit mainly comprises of passive electronic components such as resistances, capacitors, and inductors. When used in an electrical circuit, these electronic components, lose their ability to perform properly due to continuous use and an aging factor. In some cases, these components confront with short circuit and get damaged due to high current. These damaged components get faulty. In the case of prolonging and continuous use, these faulty components, disturb the performance of the electrical circuit and in case of short circuit, totally stops the electrical circuit from performing some specific tasks. In this work, a fault diagnosis system for the detection of these faulty RLC electronic components is proposed. The proposed fault diagnosis system is based on a fault detection scheme comprising of image processing and artificial neural network. The proposed system is designed in MATLAB/Simulink. The system is tested under different fault scenarios and performance is evaluated. The simulation results have proved that the proposed system can diagnose the faulty electronic components effectively, within and outside an electrical circuit.

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Abstract
1. Introduction
2. Structure of Proposed Fault Diagnosis System
3. Simulation Studies
4. Conclusion
References

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