Time-Frequency Fusion Features-Based GSWOA-KELM Model for Gear Fault Diagnosis

Time-Frequency Fusion Features-Based GSWOA-KELM Model for Gear Fault Diagnosis

To improve the accuracy of gear fault diagnosis and overcome the low diagnostic accuracy of the model caused by manual parameter selection, a combined diagnostic model based on time-frequency fusion features is combined with the improved global search whale optimization algorithm (GSWOA) to optimize...

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Bibliographic Details
Main Authors: Qin Hu, Haiting Zhou, Chengcheng Wang, Chenxi Zhu, Jiaping Shen, Peng He
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Lubricants
Subjects:
gear fault diagnosis
kernel extreme learning machine
global search whale optimization algorithm
feature fusion
machine learning
Online Access:https://www.mdpi.com/2075-4442/12/1/10

Internet

https://www.mdpi.com/2075-4442/12/1/10

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