Multiple Transient Extraction Algorithm and Its Application in Bearing Fault Diagnosis

Transient impulsive signal is usually related with the bearing or gear local defect. It is very difficult to extract those multi-transient features due to the non-stationary of the corresponding vibration signals of rotating machinery. Time-frequency analysis is a suitable tool for analyzing non-stationary signals. A multiple transient extracting transform has been proposed in this work, which can not only effectively detect the multiple transient information in the signal, but also achieve a more concentrated time-frequency representation. The results of numerical simulation show the effectiveness of this proposed method. The proposed multi-transient extracting transform can better locate the transient features and has a lower time-consuming and better noise robustness, compared with the traditional time-frequency analysis methods. Finally, multi-transient extraction algorithm is utilized to analyze practical bearing vibration signals. It has been well demonstrated that the proposed method is more effective than other advanced time-frequency methods in the field of transient feature extraction.

Automated summary

A multiple transient extracting transform has been proposed in this study to effectively detect transient information in signals and achieve a more concentrated time-frequency representation. The results from numerical simulation and practical vibration signal analysis demonstrate the effectiveness of this method in transient feature extraction compared to other advanced time-frequency methods.