A method for sensor fault diagnosis based on wavelet transform and neural network

作者：Zhao Jinsong^*; Li Yuan; Qiu Tong

来源：Journal of Tsinghua University(Science and Technology), 2013, 53(2): 205-209+221.

• Chemical process
• Fault tolerant control
• Fault types
• Process dynamics
• Sensor fault
• Sensor fault diagnosis
• Signal changes
• Simulation signals

Sensor fault diagnosis plays an important role in chemical engineering. This paper proposes a method for sensor fault diagnosis based on wavelet transform and neural network, which can distinguish signal change caused by sensor fault from normal process dynamics. Furthermore, this method needs only the samples of the system under normal situation while training the neural network and overcomes the difficulties caused by the lack of sensor fault samples. This method can also calculate the normal simulation signal when there is a sensor fault. After a series of experiments, this method is proved to be applicable in fault diagnosis and can identify the fault types.

• 出版日期2013
• 单位清华大学