Fault diagnosis method for wind power gearbox based on wavelet transform and optimized Swin Transformer

被引：0

作者：

Zhou, Zhou ^{[1
]}

Chen, Jie ^{[1
,2
]}

Wu, Mingming ^{[2
]}

机构：

[1] College of Mechanical and Power Engineering, Nanjing Tech University, Nanjing

[2] Jiangsu Province Key Lab of Industrial Equipment Digital Manufacturing and Control Technology, Nanjing Tech University, Nanjing

来源：

Zhendong yu Chongji/Journal of Vibration and Shock | 2024年 / 43卷 / 15期

关键词：

data augmentation; Swin Transformer; wavelet transform; wind power gearbox;

D O I：

10.13465/j.cnki.jvs.2024.15.023

中图分类号：

学科分类号：

摘要：

Here, aiming at shortcomings of traditional fault diagnosis method applied in wind power gearbox operation fault diagnosis, a wind power gearbox fault diagnosis method based on wavelet transform and optimized Swin Transformer was proposed. This method could use wavelet transform to convert vibration signals of a wind turbine gearbox into a time-frequency map. Samples were expanded using SuperMix data augmentation algorithm. The transfer learning technique was used to train and optimize Swin Transformer model with pre-trained model parameters. The optimized and trained Swin Transformer model was applied in contrastive verification of actual wind field operation and maintenance data with a classification correct rate of 99. 61%. The verification results showed that this method can effectively realize fault diagnosis of wind power gearbox and improve the model’ s recognition correct rate. © 2024 Chinese Vibration Engineering Society. All rights reserved.

引用

页码：200 / 208

页数：8

共 19 条

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