Fault Feature Extraction of Gearbox Rolling Bearing based on VMD and Fast-kurtogram

Abstract

The rolling bearing fault signal of the gearbox is difficult to extract effectively due to noise interference. A fault feature extraction method of gearbox rolling bearing based on VMD and fast-kurtogram is proposed. Firstly， the vibration signal of bearing is decomposed into several Intrinsic Mode Function (IMF) components by VMD， and the component signal with the most prominent fault information is selected by the correlated kurtosis， and then the bandpass filtering is adaptively determined by the fast-kurtogram. Finally， the filtered signal is subjected to squared envelope spectrum analysis to extract fault information. The effectiveness and feasibility of the proposed method are demonstrated by public bearing fault data analysis and gearbox bearing fault experiments.

Keywords

• VMD