Bearing fault diagnosis method based on fractional divergence entropy and improved pelican algorithm to optimize ELM

ObjectiveAiming at the problems of insufficient classification performance and strong parameter selection sensitivity of extreme learning machine (ELM) in rolling bearing fault diagnosis, an optimized ELM fault diagnosis method based on fractional divergence entropy and improved pelican optimization...

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Hlavní autoři:	MI Zhentao, YANG Yanshuai, ZHU Guoqing, SONG Yuxi, ZHANG Ruifeng, LIU Bing
Médium:	Artigo
Jazyk:	Chinês
Vydáno:	Editorial Office of Journal of Mechanical Transmission 2026-07-01
Edice:	Jixie chuandong
Témata:	Divergence entropy Fractional divergence entropy Pelican optimization algorithm Extreme learning machine Fault diagnosis
On-line přístup:	http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2026.07.019
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