System Development & Application
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 11
3366-3370,3375

Research on equipment life prediction based on machine learning combined algorithm under unknown small sample unbalanced data

Chen Yang
Liu Qinming
Liang Yaoxu
Business School, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2021.04.0119

Abstract

In order to solve the problems of lack of state labels, lack of data samples and unbalanced distribution in equipment life prediction, this paper proposed an improved K-means algorithm based on PSO and a data optimization scheme based on traditional SMOTE. In the process of optimizing K-means algorithm, it combined the characteristics of particle swarm optimization algorithm, and improved the optimization efficiency of particle swarm optimization algorithm by giving the particle generation range of particle swarm optimization algorithm, so as to quickly judge the working state of the equipment. Then, by comparing the mean distance of samples in the same cluster with the distance from the sample to the center, it established an improved SMOTE algorithm, and avoided the calculation error caused by the imbalance of samples by adding the number of minority samples. Finally, this paper used AdaBoost integrated optimization KNN algorithm to improve the classification effect, and by fitting the equipment life curve, it could better predict the equipment health level and future life. The example shows that the proposed model can effectively predict the health status of equipment under small sample unbalanced data.

Foundation Support

国家自然科学基金资助项目(71632008,71840003)
上海市自然科学基金资助项目(19ZR1435600)
国家教育部人文社会科学研究规划基金资助项目(20YJAZH068)
上海理工大学科技发展项目(2020KJFZ038)
2020年上海理工大学大学生创新创业训练计划资助项目(SH2020067)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.04.0119
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 11
Section: System Development & Application
Pages: 3366-3370,3375
Serial Number: 1001-3695(2021)11-028-3366-05

Publish History

[2021-11-05] Printed Article

Cite This Article

陈扬, 刘勤明, 梁耀旭. 陌生小样本不平衡数据下基于机器学习联合算法的设备寿命预测研究 [J]. 计算机应用研究, 2021, 38 (11): 3366-3370,3375. (Chen Yang, Liu Qinming, Liang Yaoxu. Research on equipment life prediction based on machine learning combined algorithm under unknown small sample unbalanced data [J]. Application Research of Computers, 2021, 38 (11): 3366-3370,3375. )

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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.

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.

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