Fault diagnosis of rolling bearing based on multi-scale and attention mechanism

被引：0

作者：

Ding, Xue ^{[1
,2
]}

Deng, Aidong ^{[1
,2
]}

Li, Jing ^{[1
,2
,3
]}

Deng, Minqiang ^{[1
,2
]}

Xu, Shuo ^{[1
,2
]}

Shi, Yaowei ^{[1
,2
]}

机构：

[1] School of Energy and Environment, Southeast University, Nanjing,210096, China

[2] National Engineering Research Center of Turbo-Generator Vibration, Southeast University, Nanjing,210096, China

[3] School of Information Engineering, Nanjing Audit University, Nanjing,211815, China

来源：

Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2022年 / 52卷 / 01期

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Failure analysis - Neural network models - Convolution - Computer aided diagnosis - Computerized tomography - Convolutional neural networks - Learning systems - Roller bearings - Extraction - Fault detection

引用

页码：172 / 178

共 28 条

[1] Multi-Scale Attention Based Deep Reinforcement Learning for Intelligent Fault Diagnosis of Planetary Gearbox
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[2] Rolling bearing fault diagnosis method based on Markov transition field and graph attention network
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[3] Automated segmentation of skin lesion based on multi-scale feature extraction and attention mechanism
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[4] Order analysis of gear fault signals based on multi-scale chirplet and sparse signal decomposition
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[5] Multi-Scale Transmission Line Component Detection Incorporating Efficient Attention
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Computer Engineering and Applications, 2024, 60 (01): : 327 - 336
[6] Rolling Bearing Fault Detection System and Experiment Based on Deep Learning
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[7] Multi-Scale Convolution Multi-Graph Attention Neural Networks for Traffic Flow Forecasting
Zhengzhou University, Henan, Zhengzhou, China
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[8] Feature extraction for rolling element bearing weak fault based on MCKD and VMD
Xia, Junzhong
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Yu, Mingqi
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[9] Generalized Composite Multiscale Diversity Entropy and Its Application for Fault Diagnosis of Rolling Bearing in Automotive Production Line
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Chen, Changzheng
IEEE Access, 2021, 9 : 84545 - 84558
[10] Fault recognition of rolling bearing based on improved 1D convolutional neural network
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Zhendong yu Chongji/Journal of Vibration and Shock, 2022, 41 (03): : 216 - 223

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