System Development & Application
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 3
805-810

Equipment health diagnostics and prognostics method based on improved degenerated HMM

Liu Wenyi
Liu Qinming
Ye Chunming
Li Guanlin
Business School, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2020.02.0067

Abstract

In order to solve the problem of large deviation between hidden Markov model and actual equipment health diagnosis, this paper developed an improved degenerated hidden Markov model(DGHMM) with a core of the quasi power relation. Firstly, the model adopted the degradation factors, modeling the process of recession for the equipment's continuous decrease in performance. Compared with the conventional exponential accelerated degradation, the quasi power relation accelerated degradation could better describe the process that the performance of the equipment decreases gradually with the increase of service age. Then, the improved genetic algorithm could replace the conventional EM algorithm for parameters' estimation, which overcame the limitation that the EM algorithm was easy to fall into local optimization. At the same time, in terms of the limitation of life prediction problem as a result of the hidden Markov model must obeyed exponential distribution, an algorithm named greed & approximation based on approximation algorithm and Viterbi algorithm came out, and to seek maximum probability remaining observation, for the purpose of seeking maximum probability dynamically surplus state path, to predict the residual life of equipment. Finally, it validated and evaluated the proposed method with the data set of caterpillar hydraulic pumps. The results show that the method of equipment health diagnosis and life prediction based on the improved degraded hidden Markov model is more effective in describing equipment's degeneration and the accuracy of equipment state diagnosis, and is also feasible in the prediction of residual life.

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)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.02.0067
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 3
Section: System Development & Application
Pages: 805-810
Serial Number: 1001-3695(2021)03-032-0805-06

Publish History

[2021-03-05] Printed Article

Cite This Article

刘文溢, 刘勤明, 叶春明, 等. 基于改进退化隐马尔可夫模型的设备健康诊断与寿命预测研究 [J]. 计算机应用研究, 2021, 38 (3): 805-810. (Liu Wenyi, Liu Qinming, Ye Chunming, et al. Equipment health diagnostics and prognostics method based on improved degenerated HMM [J]. Application Research of Computers, 2021, 38 (3): 805-810. )

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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