Multiple faults diagnosis of a linear system using ART2 neural networks

ART2 신경회로망을 이용한 선형 시스템의 다중고장진단

  • 이인수 (상주산업대학교 전자 전기공학과) ;
  • 신필재 (LG전자) ;
  • 전기준 (경북대학교 전자.전기공학부, 제어계측신기술연구센터)
  • Published : 1997.06.01


In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.


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