Application of cascaded bistable stochastic resonance and Hermite interpolation local mean decomposition method in gear fault diagnosis

Aiming at the difficulty of extracting the weak signal in gear fault diagnosis, a method for gear fault diagnosis based on cascaded bistable stochastic resonance(CBSR) denoising and local mean decomposition(LMD) was proposed. The technique of stochastic resonance can remove noise in signals effectively and make use of noise to strengthen the weak fault feature; LMD can decompose a complicated signal into several stationary PF (product function) components with reality meanings, so it is very suitable to analyze the multi-component amplitude-modulated and frequency-modulated signals. Here, the CBSR was employed in the pretreatment to remove noise in vibration signals, the denoised signal was decomposed with LMD, and then the fault frequency of gear was found by inspecting the amplitude spectra of PF components. The engineering application of the method in fault diagnosis of gear wear demonstrated that it can extract the weak feature of gear fault effectively and realize the early gear fault diagnosis.