Rolling Bearing Fault Diagnosis Based on Refined Composite Multi-Scale Approximate Entropy and Optimized Probabilistic Neural Network

A rolling bearing early fault diagnosis method is proposed in this paper, which is derived from a refined composite multi-scale approximate entropy (RCMAE) and improved coyote optimization algorithm based probabilistic neural network (ICOA-PNN) algorithm. Rolling bearing early fault diagnosis is a t...

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Hlavní autoři:	Jianpeng Ma, Zhenghui Li, Chengwei Li, Liwei Zhan, Guang-Zhu Zhang
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2021-02-01
Edice:	Entropy
Témata:	refined composite multi-scale approximate entropy coyote optimized algorithm probabilistic neural network rolling bearing fault diagnosis
On-line přístup:	https://www.mdpi.com/1099-4300/23/2/259
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