Research on Fault Diagnosis Method for Fan Rolling Bearing Based on Improved ResNet50

This paper presents a fault diagnosis technique for wind turbine rolling bearings, utilizing Continuous Wavelet Transform (CWT) and an Enhanced Deep Residual Network (ResNet). This method addresses the prevalent issues of low accuracy and slow speed in diagnosing faults in wind turbine rolling beari...

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Bibliographic Details

Published in:	2024 2nd International Conference on Signal Processing and Intelligent Computing (SPIC) pp. 779 - 783
Main Authors:	Guan, Qixue, Zhang, Yongxin, Yang, Wei, Li, Xiyu
Format:	Conference Proceeding
Language:	English
Published:	IEEE 20-09-2024
Subjects:	Accuracy continuous wavelet transform Continuous wavelet transforms Convolution Fault diagnosis Neural networks Residual Neural Network Residual neural networks Rolling bearings squeeze-and-excitation networks Vibrations Wavelet domain Wind turbines
Online Access:	Get full text
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