Adaptive scale decomposition and weighted multikernel correntropy for wheelset axle box bearing diagnosis under impact interference



Chen, Jun, Hua, Chunrong, Dong, Dawei and Ouyang, Huajiang ORCID: 0000-0003-0312-0326
(2023) Adaptive scale decomposition and weighted multikernel correntropy for wheelset axle box bearing diagnosis under impact interference. MECHANISM AND MACHINE THEORY, 181. p. 105220.

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Abstract

In this paper, a novel diagnosis method based on adaptive scale decomposition and weighted multikernel correntropy (ASD-WMKC) is developed to diagnose the faults of wheelset axle box bearing under strong wheel-rail impact interference and background noise. The ASD method is utilized to extract the complete fault characteristic signal of axle box bearing, in which the CHIMDO method is applied to restrict the overshoot and undershoot problems, an optimal shape approximation extension method is developed to suppress the end effects, and an adaptive decomposition scale construction method is proposed to overcome the mode mixing and splitting problems of decomposition. The WMKC is applied to enhance the weak fault characteristic signal and suppress the impact interferences, in which the multikernel correntropy combined with a 2D Gaussian kernel is utilized to overcome the defects of weak adaptability and poor anti-interference ability of correntropy, respectively. Simulation and application studies show that the proposed ASD-WMKC method outperforms the comparative methods and can extract the fault characteristic signal of axle box bearing with the highest completeness and SNR under strong wheel-rail impact interference and background noise.

Item Type: Article
Uncontrolled Keywords: Wheelset axle box bearing, Fault diagnosis, Impact interference, Mode mixing, End effect, Multikernel correntropy
Divisions: Faculty of Science and Engineering > School of Engineering
Depositing User: Symplectic Admin
Date Deposited: 18 Jan 2023 09:24
Last Modified: 30 Dec 2023 02:30
DOI: 10.1016/j.mechmachtheory.2022.105220
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3167110