Intelligent fault diagnosis of train bearing based on ISTOA-VMD and SE-WDCNN
文献类型：期刊论文
| 作者 | He, Deqiang1,4; Zou, Xueyan1; Jin, Zhenzhen1; Yan, Jingren1; Ren, Chonghui2; Zhou, Jixu3 |
| 刊名 | JOURNAL OF VIBRATION AND CONTROL
 |
| 出版日期 | 2023-08-17 |
| 页码 | 12 |
| 关键词 | intelligent fault diagnosis train bearing improved sooty tern optimization algorithm variational mode decomposition deep convolutional neural network |
| ISSN号 | 1077-5463 |
| DOI | 10.1177/10775463231196351 |
| 通讯作者 | He, Deqiang(hdqianglqy@126.com) |
| 英文摘要 | Bearing plays a significant role in the transmission of traction forces and safe operation of train. Affected by the actual operating conditions of the train, it is of great significance to ensure the accurate diagnosis and classification of train bearing faults under strong noise background. An intelligent bearing fault diagnosis method based on the improved sooty tern optimization algorithm to optimize the variational mode decomposition (ISTOA-VMD) and the Squeeze-and-Excitation deep convolutional neural network with wide first-layer kernels (SE-WDCNN) is proposed. Firstly, an improved sooty tern optimization (ISTOA) is proposed by introducing the nonlinear convergence strategy and dynamic weight strategy, and the parameters of VMD are optimized by ISTOA. Furthermore, the VMD combined with sample entropy is used to reconstruct and denoise the signal. Finally, SE-WDCNN is proposed by fusing Squeeze-and-Excitation block, and the reconstructed signal is input into SE-WDCNN for automatic feature extraction and fault recognition. The experimental results show that the proposed method has significant effects on fault diagnosis tasks in different noise environments. |
| WOS关键词 | OPTIMIZATION |
| 资助项目 | National Natural Science Foundation of China[U22A2053] ; Major Project of Science and Technology of Guangxi Province of China[Guike AA20302010] ; Guangxi Manufacturing Systems and Advanced Manufacturing Technology Key Laboratory Director Fund[22-050-44-S015] ; Shandong Provincial Natural Science Foundation[ZR2020QF056] ; Innovation Project of Guangxi Graduate Education[YCSW2023086] |
| WOS研究方向 | Acoustics ; Engineering ; Mechanics |
| 语种 | 英语 |
| WOS记录号 | WOS:001062084800001 |
| 出版者 | SAGE PUBLICATIONS LTD |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/181841]  |
| 专题 | 中国科学院海洋研究所 |
| 通讯作者 | He, Deqiang |
| 作者单位 | 1.Guangxi Univ, Sch Mech Engn, Guangxi Key Lab Mfg Syst & Adv Mfg Technol, Nanning, Peoples R China 2.Nanning Rail Transit Co Ltd, Nanning, Peoples R China 3.Chinese Acad Sci, Inst Oceanol, Qingdao, Peoples R China 4.Guangxi Univ, Sch Mech Engn, 100 Daxue East Rd, Nanning 530004, Guangxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Deqiang,Zou, Xueyan,Jin, Zhenzhen,et al. Intelligent fault diagnosis of train bearing based on ISTOA-VMD and SE-WDCNN[J]. JOURNAL OF VIBRATION AND CONTROL,2023:12. |
| APA | He, Deqiang,Zou, Xueyan,Jin, Zhenzhen,Yan, Jingren,Ren, Chonghui,&Zhou, Jixu.(2023).Intelligent fault diagnosis of train bearing based on ISTOA-VMD and SE-WDCNN.JOURNAL OF VIBRATION AND CONTROL,12. |
| MLA | He, Deqiang,et al."Intelligent fault diagnosis of train bearing based on ISTOA-VMD and SE-WDCNN".JOURNAL OF VIBRATION AND CONTROL (2023):12. |
入库方式： OAI收割
来源：海洋研究所
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