Research of a fan fault diagnosis system based on wavelet and neural network

An online fan fault diagnosis system is proposed based on wavelet and neural network, and the system is implemented on the LabVIEW platform. Relying on the noise signal from the fan, the recognition system utilizes power spectrum gravity center, sound level, wavelet frequency segment power of the signal as feature vectors, and the BP network as classifier for fault diagnosis. The experimental results show that it is effective to extract fault information by the combination of wavelet and neural network. The entire system has adaptability and fault-tolerant capability.