@article{Wang_Zhao_Liu_Cui_2022, title={CVRgram for Demodulation Band Determination in Bearing Fault Diagnosis under Strong Gear Interference}, volume={1}, url={https://ojs.istp-press.com/dmd/article/view/135}, DOI={10.37965.jdmd.2022.135}, abstractNote={<p><span dir="ltr" role="presentation">Fault-related resonance frequency band extraction-based demodulation methods are widely used for </span><span dir="ltr" role="presentation">bearing diagnostics. However, due to the high peaks of strong gear meshing interference, the classical band </span><span dir="ltr" role="presentation">selection methods have poor performance and cannot work well for bearing fault type detection. As such, the </span><span dir="ltr" role="presentation">CVRgram-based bearing fault diagnosis method is proposed in this paper. In the proposed method, inspired by the </span><span dir="ltr" role="presentation">conditional variance (CV) index and root mean square (RMS), a novel index, named the CV/ root mean square </span><span dir="ltr" role="presentation">(CVR), is</span> <span dir="ltr" role="presentation">fi</span><span dir="ltr" role="presentation">rst proposed. The CVR index has high robustness for the interference of non-Gaussian or Gaussian </span><span dir="ltr" role="presentation">noise and has the ability to determine the center frequency of the weak bearing fault-related resonance frequency </span><span dir="ltr" role="presentation">band under strong interference. Secondly, motived by the Kurtogram, the CVRgram algorithm is developed for </span><span dir="ltr" role="presentation">adaptively determining the optimal</span> <span dir="ltr" role="presentation">fi</span><span dir="ltr" role="presentation">ltering parameters. Finally, the CVRgram-based bearing fault diagnosis </span><span dir="ltr" role="presentation">method under strong gear meshing interference is proposed. The performance of the CVRgram-based method is </span><span dir="ltr" role="presentation">veri</span><span dir="ltr" role="presentation">fi</span><span dir="ltr" role="presentation">ed by both the simulation signal and the experiment signal. The comparison analysis with the Kurtogram, </span><span dir="ltr" role="presentation">Protrugram, and CVgram-based method shows that the proposed technique has a much better ability for bearing </span><span dir="ltr" role="presentation">fault detection under strong noise interference.</span></p> <p><span dir="ltr" role="presentation"><strong>Conflict of Interest Statement</strong><br />The authors declare no conflicts of interest.</span></p>}, number={4}, journal={Journal of Dynamics, Monitoring and Diagnostics}, author={Wang, Pengda and Zhao, Dezun and Liu, Dongdong and Cui, Lingli}, year={2022}, month={Dec.}, pages={237–250} }