A Tacholess Order Tracking Method Based on Spectral Amplitude Modulation for Variable Speed Bearing Fault Diagnosis

Abstract

Rolling bearings often work under nonstationary conditions, which will lead to spectrum smearing phenomenon and the failure of traditional diagnostic methods. Order tracking is a common technique to alleviate this problem by resampling the time-domain signal using the instantaneous rotation frequency. For tacholess applications, it is of great importance to obtain accurate rotation speeds. In this paper, a tacholess order tracking method based on spectral amplitude modulation (SAM) is proposed. Based on the fact that SAM can separate frequency components with different levels of energy, an appropriate weight is selected to highlight the instantaneous frequency, which is then extracted from the time-frequency representation by peak search algorithm. Moreover, entropy is employed to evaluate the valuable information in the time-frequency representation in order to select an optimal weight adaptively. A simulated signal and experimental signals of bearing outer and inner ring faults demonstrate that the proposed method can extract instantaneous rotation frequency and detect nonstationary bearing fault characteristics effectively.