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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 9
2787-2793

Remain useful life prediction method of rolling bearings based on S-MCLSTM and DANN

Dong Zhimin1,2
Dong Jiechao3
1. Dept. of Mathematics & Information Engineering, Puyang Vocational & Technical College, Puyang Henan 457000, China
2. Puyang Institute of Technology, Henan University, Puyang Henan 457000, China
3. Software Development Center, Industrial & Commercial Bank of China, Beijing 100080, China
DOI: 10.19734/j.issn.1001-3695.2023.12.0624

Abstract

Aiming at the problems of poor generalization ability and low accuracy of remain useful life prediction of rolling bearings under different working conditions and different faults, this paper proposed a remain useful life prediction method based on Siamese multi-convolutional long short-term memory(S-MClSTM) and domain adversarial neural network(DANN). Firstly, to reduce the influence of different working conditions on the degradation process, it input two samples with a certain time interval to the S-MCLSTM differentiation feature extractor to extract the differentiated features. At the same time, it designed and trained the work condition discriminator adversarially with the feature extractor, which could avoid to extract redundant features due to different working conditions. Then, to reduce the influence of different faults on the degradation process, it designed and trained a fault diagnoser adversarially with the differentiation feature extractor. Finally, considering the differences in the mapping between degradation process and features in different degradation stages, it proposed a stage discriminator and applied different remain useful life predictors in different stages. In the end, experiments on the XJTU-SY bearing dataset show that the method can accurately predict the remain useful life under various working conditions and faults, and has a wide range of application scenarios.

Foundation Support

河南省高等学校重点科研项目(18B520030)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.12.0624
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 9
Section: System Development & Application
Pages: 2787-2793
Serial Number: 1001-3695(2024)09-031-2787-07

Publish History

[2024-03-19] Accepted Paper
[2024-09-05] Printed Article

Cite This Article

董志民, 董洁超. 基于S-MCLSTM和DANN的滚动轴承剩余寿命预测方法 [J]. 计算机应用研究, 2024, 41 (9): 2787-2793. (Dong Zhimin, Dong Jiechao. Remain useful life prediction method of rolling bearings based on S-MCLSTM and DANN [J]. Application Research of Computers, 2024, 41 (9): 2787-2793. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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