A novel optimal demodulation frequency band extraction method of fault bearing based on power spectrum screening combination-gram. (15th July 2022) - Wang, Xinglong; Zheng, Jinde; Zhang, Jun
Highlights: The Power spectrum screening combination-gram (Psscgram) is proposed for rolling bearing fault diagnosis. A new idea of frequency band division is established to improve the accuracy of detecting the optimal demodulation frequency band. Negative entropy, as a robustness index, is used to capture the frequency band with rich fault information. The robustness of the proposed method is verified by simulation signals with different signal-to-noise ratios and interference components. The effectiveness of the Psscgram method is verified by three sets of data from different test benches. Abstract: As the prerequisite for obtaining the optimal demodulation frequency band (ODFB), the frequency band division model must be delicately constructed. The division models in existing methods of obtaining ODFB are vulnerable to the background noise and irrelevant components, which will cause an unsuitable demodulation frequency band. To improve the performance of frequency band division model, this paper proposes a fault diagnosis method called power spectrum screening combination-gram (Psscgram). Firstly, a frequency band screening combination model based on the auto-regressive (AR) power spectrum is established to obtain the frequency band group of vibration signal. Secondly, the negative entropy (NE) is used to quantify the fault characteristics of the frequency band group. The frequency band with the largest NE value is extracted from the frequency band group, whose characteristic frequency is calculated via envelope spectrum. Finally, the robustness and the anti-interference of the proposed method is verified by simulated signals with different signal-to-noise ratio. Moreover, the ODFB extraction ability of the proposed method is proved by the analyses of three sets of bearing experimental signals.