Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 1
101-105

Research on bearing fault diagnosis based on discrete wavelet transform and random forest

Peng Cheng1,2
Wang Songsong1
He Jing1
Li Fengjuan1
1. School of Computer Science, Hunan University of Technology, Zhuzhou Hunan 412007, China
2. School of Automation, Central South University, Changsha 410083, China
DOI: 10.19734/j.issn.1001-3695.2019.09.0633

Abstract

Aiming at the difficulty of data feature selection under different working conditions and the low recognition rate of single classifier in rolling bearing fault diagnosis, this paper proposed a rolling bearing fault diagnosis algorithm based on discrete wavelet transform and random forest. Firstly the proposed method decomposed the vibration signal by discrete wavelet transform to get n-layer approximate coefficients. Then, it used the sigmoid entropy to construct n-dimensional eigenvectors innovatively. The sigmoid entropy could extract the features of non-stationary signals better and improve the diagnostic accuracy. Finally this paper used random forest to diagnose different fault signals of rolling bearing. It used the bearing data provided by the bearing data center website of Case Western Reserve University for experiments. Comparing with the results of traditional classifier(KNN and SVM) and single classification regression tree CART, this method has better diagnostic results.

Foundation Support

国家自然科学基金资助项目(61871432,61771492)
湖南省自然科学基金资助项目(2020JJ4275,2019JJ6008,2019JJ60054)
湖南省研究生创新计划资助项目(CX20190847)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.09.0633
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 1
Section: Algorithm Research & Explore
Pages: 101-105
Serial Number: 1001-3695(2021)01-020-0101-05

Publish History

[2021-01-05] Printed Article

Cite This Article

彭成, 王松松, 贺婧, 等. 基于离散小波变换和随机森林的轴承故障诊断研究 [J]. 计算机应用研究, 2021, 38 (1): 101-105. (Peng Cheng, Wang Songsong, He Jing, et al. Research on bearing fault diagnosis based on discrete wavelet transform and random forest [J]. Application Research of Computers, 2021, 38 (1): 101-105. )

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  • Application Research of Computers Monthly Journal
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    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.

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