机械产品多变量相依退化建模方法研究综述

doi:10.3901/JME.2023.20.470

机械工程学报 ›› 2023, Vol. 59 ›› Issue (20): 470-488.doi: 10.3901/JME.2023.20.470

• 交叉与前沿 • 上一篇

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机械产品多变量相依退化建模方法研究综述

孔雪峰, 潘骏, 钱萍, 魏义敏, 陈文华

浙江理工大学浙江省机电产品可靠性技术研究重点实验室杭州 310018

收稿日期:2023-06-26 修回日期:2023-08-25 出版日期:2023-10-20 发布日期:2023-12-08
通讯作者: 陈文华(通信作者),男,1963年出生,博士,教授,博士研究生导师。主要研究方向为可靠性分析、设计与试验。E-mail:chenwh@zstu.edu.cn
作者简介:孔雪峰,男,1993年出生,博士,研究员,硕士研究生导师。主要研究方向为系统可靠性分析、系统故障预测与健康管理。E-mail:kxf2022@zstu.edu.cn;潘骏,男,1974年出生,博士,教授,博士研究生导师。主要研究方向为加速退化试验、故障预测与健康管理。E-mail:panjun@zstu.edu.cn;钱萍,女,1983年出生,博士,副教授,硕士研究生导师。主要研究方向为机电产品可靠性试验设计、分析与评价。E-mail:qianping@zstu.edu.cn;魏义敏,男,1986年出生,博士,副教授,硕士研究生导师。主要研究方向为机械系统动力学、机电产品故障预测与健康管理。E-mail:yiminwei@126.com
基金资助:
国家自然科学基金(52075496)、浙江省高层次人才特殊支持计划(2021R52036)、浙江省“尖兵”“领雁”研发攻关计划(2023C01066)和浙江理工大学科研启动基金(11132832612201)资助项目。

Review of Multivariate Dependent Degeneration Modeling Methods for Mechanical Products

KONG Xuefeng, PAN Jun, QIAN Ping, WEI Yimin, CHEN Wenhua

Zhejiang Province's Key Laboratory of Reliability Technology for Mechanical and Electrical Product, Zhejiang Sci-Tech University, Hangzhou 310018

Received:2023-06-26 Revised:2023-08-25 Online:2023-10-20 Published:2023-12-08

摘要/Abstract

摘要： 退化建模是开展机械产品可靠性评估与剩余寿命预测、指导产品使用维护管理决策优化的关键技术。随着机械产品日趋结构复杂化与功能多样化方向发展，多变量退化数据由于能够更全面地反映产品健康状态，其建模方法在近几年受到研究者们的广泛关注，特别是针对多变量退化过程中普遍存在的随机相依性，构建诸多实用有效的多变量相依退化模型，提高了复杂机械产品寿命与可靠性的评估精度。然而，目前还没有形成针对该主题的系统性综述。为促进多变量相依退化建模方法的发展与应用，从研究现状、发展趋势及应用研究等方面，对现有的多变量相依退化建模方法进行回顾和总结。首先，介绍三类常用多变量相依退化建模方法的原理及其优缺点；接着，探讨考虑多源随机性、外部协变量以及时变随机相依性等因素影响下的多变量相依退化模型扩展研究；随后，讨论多变量相依退化模型在加速试验方案设计、剩余寿命预测和维修策略优化中的应用研究；最后，针对未来值得深入研究的方向进行归纳和总结。

关键词: 多变量退化数据, 随机相依性, 相依退化建模, 加速试验设计, 维修策略优化

Abstract: Degradation modeling has been recognized as a critical approach for mechanical products in conducting reliability assessments and remaining useful life(RUL) predictions, as well as guiding the optimization of operation and maintenance actions. With the increasing complexity in structure and diversification in the function of modern mechanical products, more interest and attention have been paid to the modeling of multivariate degradation data as it can comprehensively reflect the health status of products. Especially, focusing on the stochastic dependence that is widespread in multivariate degradation processes, many practical and effective multivariate dependent degradation(MVDD) models have been proposed, based on which the accuracy of reliability assessment and RUL prediction of products is greatly enhanced. However, there is no systematic review focusing specifically on this topic. Therefore, the research status, recent advances, and applications of existing MVDD modeling methods are reviewed to facilitate their developments and applications. First, three commonly used MVDD modeling methods are introduced in detail, including their principles, advantages, and disadvantages. Then, extended studies of MVDD models involving the effects of multi-source variability, external covariates, and time-varying stochastic dependences are investigated. In addition, applications of MVDD models for accelerated test design, RUL prediction, and maintenance strategy optimization are discussed. Finally, several possible directions for further research are summarized.

Key words: multivariable degradation data, stochastic dependence, dependent degradation modeling, accelerated test design maintenance strategy optimization

中图分类号:

TB114

孔雪峰, 潘骏, 钱萍, 魏义敏, 陈文华. 机械产品多变量相依退化建模方法研究综述[J]. 机械工程学报, 2023, 59(20): 470-488.

KONG Xuefeng, PAN Jun, QIAN Ping, WEI Yimin, CHEN Wenhua. Review of Multivariate Dependent Degeneration Modeling Methods for Mechanical Products[J]. Journal of Mechanical Engineering, 2023, 59(20): 470-488.

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机械产品多变量相依退化建模方法研究综述

Review of Multivariate Dependent Degeneration Modeling Methods for Mechanical Products

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