Fault diagnosis in speed variation conditions via improved tacholess order tracking technique

Tacholess order tracking (TLOT) is a promising tool for mechanical fault diagnosis in speed variation conditions without a tachometer. However, TLOT is still a challenging task due to the inaccurately acquired instantaneous phase of shaft and noise corrupted resample signal in angle domain. Therefore, an improved TLOT technique is proposed in this paper to deal with those limitations for mechanical fault feature extraction. In this method, the modified numerical integration (MNI) algorithm is proposed to estimate the instantaneous phase by integrating instantaneous frequency (IF), which is estimated by a time-frequency representation (TFR) approach. During the MNI, Romberg integration is investigated and performed to improve the estimated accuracy of instantaneous phase. Subsequently, a flexible synchronous average (FSA) algorithm based on Chirp-Z transform in angle domain is further employed to reduce noise interference for the resampled signal. The effectiveness and efficiency of the improved TLOT technology is verified by both simulations and experiments. Analysis results show that the proposed method has an outstanding performance for the mechanical fault diagnosis in the condition of speed fluctuation.