Biphase randomization wavelet bicoherence for mechanical fault diagnosis

Wavelet bicoherence is one of the most useful tools for quadratic nonlinear behavior identification of stochastic system, which has been used in many fields. However, current wavelet bicoherence algorithm can neither eliminate the spurious peaks coming from components with long coherence time, nor distinguish the quadratic phase coupling and non quadratic phase coupling signals, which may constraint the application of wavelet bicoherence. In this article, biphase randomization wavelet bicoherence technique is proposed to solve this problem. In this method, an ensemble average biphase randomization algorithm is established, in which the biphase randomization is employed to damage the biphase dependence among bispectrum samples. The spurious bicoherence coming from long coherence time waves and non phase coupling waves is eliminated efficiently by using the proposed method. Based on that, two diagnosis features are established for mechanical fault diagnosis. Simulation and experiment results demonstrate that the performance of the proposed method is much better than that of current wavelet bicoherence method.