Localization of Rolling Element Faults Using Improved Binary Particle Swarm Optimization Algorithm for Feature Selection Task

Localization of Rolling Element Faults Using Improved Binary Particle Swarm Optimization Algorithm for Feature Selection Task

The accurate localization of the rolling element failure is very important to ensure the reliability of rotating machinery. This paper proposes an efficient and anti-noise fault diagnosis model for rolling elements. The proposed model is composed of feature extraction, feature selection and fault cl...

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Bibliographic Details
Main Authors:	Chun-Yao Lee, Guang-Lin Zhuo
Format:	Article
Language:	English
Published:	MDPI AG 2021-09-01
Series:	Mathematics
Subjects:	rolling element fault diagnosis model local mean decomposition wavelet packet decomposition binary particle swarm optimization
Online Access:	https://www.mdpi.com/2227-7390/9/18/2302

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