Intelligence Bearing Fault Diagnosis Model Using Multiple Feature Extraction and Binary Particle Swarm Optimization With Extended Memory

Intelligence Bearing Fault Diagnosis Model Using Multiple Feature Extraction and Binary Particle Swarm Optimization With Extended Memory

This article presents an effective bearing fault diagnosis model based on multiple extraction and selection techniques. In multiple feature extraction, the discrete wavelet transform, envelope analysis, and fast Fourier transform are considered. While the combined binary particle swarm optimization...

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Bibliographic Details
Main Authors: Chun-Yao Lee, Truong-An Le
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Fault diagnosis
feature extraction
feature selection
particle swarm optimization
Online Access:https://ieeexplore.ieee.org/document/9246594/

Internet

https://ieeexplore.ieee.org/document/9246594/

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