Rolling bearing fault diagnosis method based on IAO optimized VMD and DHKELM

ObjectiveAiming at the problems of low accuracy and insufficient efficiency of multi-type fault diagnosis caused by interference components such as harmonics and strong noise mixed in the fault vibration signals of rolling bearings, a rolling bearing fault diagnosis method based on improved Aquila o...

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Principais autores:	LIU Fei, ZHANG Chenyue, FENG Xinke, ZHAO Zhiwei
Formato:	Artigo
Idioma:	Chinês
Publicado em:	Editorial Office of Journal of Mechanical Transmission 2026-05-01
coleção:	Jixie chuandong
Assuntos:	Improved Aquila optimizer Variational mode decomposition Deep hybrid kernel extreme learning machine Rolling bearing Fault diagnosis
Acesso em linha:	http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2026.05.022
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