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A multiresolution higher-order symmetric envelope-derivative operator and its application to bearing fault detection

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Abstract

Fault signals measured from a damaged rolling bearing usually exhibit amplitude modulation (AM)-frequency modulation (FM) properties. For this kind of signal, the demodulation technique is an effective and common method. In the demodulation techniques, a variety of energy operator (EO) tools have been available due to high computational efficiency and self-adaptability to transient signals. Hence, an alternative energy measure is proposed in this work. The new demodulation technique is achieved by combining a multiresolution higher-order symmetric difference sequence with the envelope-derivative operator (EDO). The multiresolution higher-order symmetric envelope-derivative operator (MHOS-EDO) can extract the weak bearing fault characteristics in a harsh environment without any pre-filtering. Especially in the presence of vibration interferences, its unique energy transformation can eliminate the influence of vibration interferences, so that the vibration interferences will no longer appear in the energy spectrum. Through simulation and practical experiments, the superiority of MHOS-EDO in dealing with noise and interfering components is demonstrated. Meanwhile, the comparison results reveal that the MHOS-EDO outperforms some previous EO and some other bearing fault identification methods.

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Acknowledgments

This work was supported by the Natural Science Foundation of Shaanxi Province (No. 2020JM-249).

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Correspondence to Kun Wu.

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Wu Kun received a M.D. in Mechanical Engineering from the Xidian University, Xi’an, P. R. China, in 2013. Now he works at the Department of Mechanical and Electrical Technology, Xijing University, Xi’an, P. R. China. His current research interests include rotating-machine fault diagnosis and signal analysis and processing, et al.

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Wu, K., Xu, Y., Yang, N. et al. A multiresolution higher-order symmetric envelope-derivative operator and its application to bearing fault detection. J Mech Sci Technol 37, 1165–1175 (2023). https://doi.org/10.1007/s12206-023-0203-5

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  • DOI: https://doi.org/10.1007/s12206-023-0203-5

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