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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...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: LIU Fei, ZHANG Chenyue, FENG Xinke, ZHAO Zhiwei
Format: Artigo
Sprache:Chinês
Veröffentlicht: Editorial Office of Journal of Mechanical Transmission 2026-05-01
Schriftenreihe:Jixie chuandong
Schlagworte:
Improved Aquila optimizer
Variational mode decomposition
Deep hybrid kernel extreme learning machine
Rolling bearing
Fault diagnosis
Online-Zugang:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2026.05.022
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