Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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A Study on a Fault Detection and Isolation Method of Nonlinear Systems using SVM and Neural Network

SVM과 신경회로망을 이용한 비선형시스템의 고장감지와 분류방법 연구

  • 이인수 (경북대학교 산업전자공학과) ;
  • 조정환 (미국 매사추세츠 로웰대학교 도시환경공학과) ;
  • 서해문 (전자부품연구원) ;
  • 남윤석 (동국대학교 경주캠퍼스 정보통신공학과)
  • Received : 2012.04.30
  • Accepted : 2012.05.22
  • Published : 2012.06.01
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Abstract

In this paper, we propose a fault diagnosis method using artificial neural network and SVM (Support Vector Machine) to detect and isolate faults in the nonlinear systems. The proposed algorithm consists of two main parts: fault detection through threshold testing using a artificial neural network and fault isolation by SVM fault classifier. In the proposed method a fault is detected when the errors between the actual system output and the artificial neural network nominal system output cross a predetermined threshold. Once a fault in the nonlinear system is detected the SVM fault classifier isolates the fault. The computer simulation results demonstrate the effectiveness of the proposed SVM and artificial neural network based fault diagnosis method.

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References

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