Detecting single sensor's fault based on time series predictor using neural network

Chen Zhang*, Yueqiu Han, Ran Tao, Yongsheng Niu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Aim To study the detection of the single sensor's fault by using its output signal. Methods The principle of neural network based on time series predictor was presented. The on-line and off-line training algorithms of the predictor were summed up. Results The method has many advantages over other methods such as the ability to detect sensor fault by using the single sensor's output signal, the ability to detect multiple sensor faults, the ability to detect two sensor faults occurring simultaneously and the ability to detect many kinds of sensor faults. Conclusion The simulation results through an automotive engine model show that the method can detect the sensor fault successfully.

Original languageEnglish
Pages (from-to)220-223
Number of pages4
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume19
Issue number2
Publication statusPublished - 1999

Keywords

  • Fault detection
  • Neural network
  • Predictor
  • Sensor

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