On Fault Diagnosis of Gear Box Based on De-Trending Multifractal

For the non-stationary and nonlinear complex characteristics of gearbox vibration signals under fault condition, the identification of pitting failure, gear breakage and wear fault of gear box is recognized based on de-trended wave analysis and multifractal method. Multifractal spectrum has a clear physical significance, and it can characterize the kinetic mechanism of the signal, which makes it suitable to be the fault feature parameter of stationary signal, but not suitable for non-stationary signal. De-trended fluctuation analysis can filter out the trend component in the sequence effectively, and determine the long-range correlation characteristics in detecting signal and noise which can be used to deal with non-stationary data. In this paper, the two methods are combined to be the fault diagnosis method of gearbox. First, de-trended fluctuation analysis is used to process the gearbox signal, then the multifractal parameters are extracted that can be treated as the fault features to diagnose the gearbox fault. Finally, the experimental data of the gearbox are compared and analyzed. The experimental results show that the fault diagnosis method of MF - DFA improves the classification precision of the fault diagnosis.