Abstract

In recent years, order tracking methods based on time-frequency (TF) ridge detection have attracted considerable attention for bearing fault detection under varying speed conditions. Inevitably, these methods are subjected to the resolution of the time–frequency representation (TFR). Hence, to overcome the limitations of the current order tracking techniques, adaptive signal decomposition methods have drawn the growing interest, in which variational nonlinear chirp mode decomposition (VNCMD) is a recently introduced method for adaptive signal analysis. Unfortunately, the successful applicability of the VNCMD method considerably depends on the prior knowledge of initial parameters. To address this issue, a new decomposition strategy called the optimization tendency guiding VNCMD method is proposed for the instantaneous frequency (IF) estimation of bearings. In particular, the proposed method consists of two steps. First, a coarse TF spectrum is presented to roughly extract a dominant IF by the ridge extraction method. Second, the optimization tendency guiding VNCMD decomposition strategy is constructed to accurately extract the meaningful modes until meeting the stop criterion. The new method is especially suitable for bearing fault diagnosis under varying speed conditions, which is confirmed by an experimental case of bearing fault diagnosis.

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