ART2 Neural Network Applications for Diagnosis of Sensor Fault in the Indoor Gas Monitoring System

  • Lee, In-Soo (School of Electronics and Electrical Engineering, Sangju National University) ;
  • Cho, Jung-Hwan (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
  • Shim, Chang-Hyun (Sense & Sensor Co., Ltd. Technopark of Kyungpook National University) ;
  • Lee, Duk-Dong (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
  • Jeon, Gi-Joon (School of Electrical Engineering and Computer Science, Kyungpook National University)
  • Published : 2004.08.25

Abstract

We propose an ART2 neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, fault classifier by ART2 NN (adaptive resonance theory 2 neural network) with uneven vigilance parameters is used for fault isolation. The performances of the proposed fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.

Keywords