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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 10
3098-3103

Remaining life prediction of rolling bearing based on CNN-WaveNet

Quan Hanga
Zhang Qiangb
Shao Siyub
Niu Tianlinb
Yang Xinyub
a. Graduate School, b. Air Defense & Antimissile School, Air Force Engineering University, Xi'an 710051, China
DOI: 10.19734/j.issn.1001-3695.2021.03.0078

Abstract

In order to ensure the normal operation of the equipment and to predict the remaining life of the bearing, this paper proposed a life prediction model based on the combination of two-dimensional convolutional neural network and an improved WaveNet. To overcome the gradient vanishing problem of the unoptimized recurrent networks in the process of prediction training, the WaveNet time-series networks structure was introduced into the model. Aiming at the situation that the original WaveNet structure was not suitable for rolling bearing vibration data, the improved WaveNet structure combined with two-dimensionalconvolutional neural networks was applied to the life prediction of rolling bearing. The model extracted the features of one-dimensional vibration sequence using two-dimensional convolutional networks, and then input the features to the WaveNet to predict the remaining life of the rolling bearing. Compared with the deep recurrent networks, the combined model has higher computational efficiency and more accurate results. Compared with the CNN-WaveNet-O model, the improved model has more accurate prediction results. Compared with the deep long short-term memory networks model, the root mean square error of the prediction results of this model is reduced by 11.04%, and the scoring function of the prediction results is reduced by 11.34%.

Foundation Support

陕西省自然科学基础研究计划资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.03.0078
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 10
Section: System Development & Application
Pages: 3098-3103
Serial Number: 1001-3695(2021)10-038-3098-06

Publish History

[2021-10-05] Printed Article

Cite This Article

全航, 张强, 邵思羽, 等. 基于CNN-WaveNet的滚动轴承剩余寿命预测 [J]. 计算机应用研究, 2021, 38 (10): 3098-3103. (Quan Hang, Zhang Qiang, Shao Siyu, et al. Remaining life prediction of rolling bearing based on CNN-WaveNet [J]. Application Research of Computers, 2021, 38 (10): 3098-3103. )

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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