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

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Fault Diagnosis of Nonlinear Systems Based on Dynamic Threshold Using Neural Network

신경회로망을 이용한 동적 문턱값에 의한 비선형 시스템의 고장진단

  • 소병석 (삼성전자 중앙연구소) ;
  • 이인수 (상주대학교 전자전기공학과) ;
  • 전기준 (경북대학교 전자전기공학부)
  • Published : 2000.11.01
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Abstract

Fault diagnosis plays an important role in the performance and safe operation of many modern engineering plants. This paper investigates the problem of fault detection using neural networks in dynamic systems. A general framework for constructing a nonlinear fault detection scheme for nonlinear dynamic systems containing modeling uncertaintly is proposed. The main idea behind the proposed approach is to monitor the physical system with an off -line learning neural network and then to approximate the upper and lower thresholds of acceleration of the nominal system with the model-based threshold(ThMB) method, The performance of the proposed fault detection scheme is investigated through simulations of a pendulum with uncertainty.

Keywords

References

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