Gear Fault Diagnosis Based on Harmonic Wavelet Packet and BP Neural Network

The gear fault diagnosis system is proposed based on harmonic wavelet packet transform (WPT) and BP neural network techniques. The WPT is a well-known signal processing technique for fault detection and identification in mechanical system, In the preprocessing of vibration signals, WPT coefficients are used for evaluating their energy and treated as the features to distinguish the fault conditions. In the experimental work, the harmonic wavelets are used as mother wavelets to build and perform the proposed WPT technique. The experimental results showed that the proposed system achieved an average classification accuracy of over 95% for various gear working conditions.