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Detecting Single Sensor's Fault Based on Time Series Predictor Using Neural Network

Zhang Chen Han Yueqiu Tao Ran (Department of Electronics Engineering, Beijing Institute of Technology, Beijing100081)Niu Yongsheng (Department of Optical Engineering, Beijing Institute of Technology, Beijing100081)  
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.
【CateGory Index】: TP212.063
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