Identification of Vibrating Noise Signals of Electromotor Using Adaptive Wavelet Neural Network

Electromagnetic noise, unbalanced rotor noise and injuring bearing noise are three types of noise in faulting electromotor. An adaptive wavelet neural network is proposed to identify these noises. The process of wavelet-based feature extraction of signal is integrated into one part of neural network. During network’s training course the wavelet’s scale and shift parameters can be adaptively adjusted to fit input signal so that signal’s feature could be extracted in maximum limit. The network’s second part then uses these feature information to realize the identification of noise signal. The identification result of three types of noise of electromotor demonstrates that this neural network can give accurate identification result with high probability.