Fault diagnosis for the gearbox of wind turbine combining ensemble intrinsic time-scale decomposition with Wigner bi-spectrum entropy

Abstract

The complex dynamic working conditions of wind turbine make it a challenge to identify work status and fault type of wind turbine gearbox. In this paper, a novel method is presented to decompose non-stationary vibration signal and identify wind turbine faults applying ensemble intrinsic time-scale decomposition (EITD) with Wigner bi-spectrum entropy (WBE). Ensemble intrinsic time-scale decomposition (EITD) is able to restrict the end effect and to prevent the signal distortion. Wigner bi-spectrum entropy (WBE) has perfect energy aggregation and can extract the signal feature effectively. The advantage of method is that it does extract the fault features and recognize the gearbox fault types when two or more fault features are close to each other. This proposed approach based on EITD and WBE is applied in the fault diagnosis of wind turbine gearbox.