An informative frequency band identification framework for gearbox fault diagnosis under time-varying operating conditions

Abstract

The application of informative frequency band identification methods makes it possible to enhance weak damage components in the vibration signals acquired from rotating machines. Some rotating machines (e.g. wind turbines) operate inherently under time-varying operating conditions, however, very few frequency band identification methods have been developed with varying operating conditions in mind. Therefore, in this work, a systematic framework for obtaining consistent feature planes under time-varying operating conditions is proposed. This framework utilises the angle-frequency instantaneous power spectrum and the order-frequency cyclic modulation spectrum to construct feature planes. The kurtogram, the sparsogram, the infogram, the ICS2gram and the log-cycligram are obtained on numerical and experimental datasets acquired under time-varying operating conditions using this framework. In addition to this, we also implement the Informative Frequency Band Identification method using targeted cyclic orders, abbreviated to IFBIαgram, in this framework and compare the performance of this method against the other frequency band identification methods. Ultimately, we found that the feature used in the construction of the IFBIαgram is very well-suited for gear and bearing fault diagnosis under time-varying operating conditions.