Incipient Faults Identification in Gearbox by Combining Kurtogram and Independent Component Analysis

Abstract

Envelope analysis is a popular incipient fault identification tool for rolling element bearings (REBs) and gears. However, in some harsh conditions where more than one fault of REBs and gears exists simultaneously in a gearbox. In general, only the characteristic frequencies of the stronger vibration can be exposed clearly, and the others may be missed by conventional envelope analysis. To address this issue, an incipient faults detection scheme combining the kurtogram and independent component analysis (ICA) for gearbox faults diagnosis is proposed in this paper. In the proposed scheme, multi-channel vibrations are acquired from the gearbox synchronously at first. Subsequently, the vibration envelopes from each channel are extracted by the novel fast kurtogram algorithm. Then, the independent component analysis algorithm is utilized to separate the envelopes. As a result, the independent envelope components corresponding to different sources are obtained. Finally, the characteristic frequencies of the incipient faults of rolling element bearings and/or gears in a gearbox can be clearly exposed in envelope spectral plots. An experiment on a gearbox test rig which has both a REB fault and a gear fault is conducted to compare the conventional envelope analysis scheme and the proposed scheme. Test results show that the proposed scheme is more effective to identify the incipient faults of REBs and gears simultaneously existing in a gearbox.