系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (1): 338-346.doi: 10.12305/j.issn.1001-506X.2022.01.42

• 可靠性 • 上一篇    下一篇

基于逆高斯退化过程的面向任务系统CBM优化模型

陈云翔1, 李京峰1,*, 项华春1, 李恒年2   

  1. 1. 空军工程大学装备管理与无人机工程学院, 陕西 西安 710051
    2. 西安卫星测控中心宇航动力学国家重点实验室, 陕西 西安 710043
  • 收稿日期:2020-09-22 出版日期:2022-01-01 发布日期:2022-01-19
  • 通讯作者: 李京峰
  • 作者简介:陈云翔(1962—), 男, 教授, 博士, 主要研究方向为装备系统工程、装备管理|李京峰(1993—), 男, 博士研究生, 主要研究方向为装备发展战略与管理决策、机器学习|项华春(1980—), 男, 副教授, 博士, 主要研究方向为装备可靠性与系统工程|李恒年(1967—), 男, 研究员, 博士, 主要研究方向为轨道动力学与控制
  • 基金资助:
    国家自然科学基金(12002394)

A CBM optimization model for mission-oriented system based on inverse Gaussian degradation process

Yunxiang CHEN1, Jingfeng LI1,*, Huachun XIANG1, Hengnian LI2   

  1. 1. Equipment Management and Unmanned Aerial Vehicle Engineering College, Air Force Engineering University, Xi'an 710051, China
    2. State Key Laboratory of Astronautic Dynamics, Xi'an Satellite Control Center, Xi'an 710043, China
  • Received:2020-09-22 Online:2022-01-01 Published:2022-01-19
  • Contact: Jingfeng LI

摘要:

针对现有单调退化系统视情维修(condition-based maintenance, CBM)优化模型中不完全维修影响考虑单一, 且未同时融入可用度约束的问题, 提出一种考虑不完全维修双重影响与可用度约束的单调退化系统CBM优化模型。首先, 基于具有随机漂移系数的逆高斯过程, 建立系统退化模型并得到相关概率分布; 其次, 描述任务背景下系统演化过程, 建立不完全维修后的剩余损伤模型, 提出随机漂移系数更新公式; 然后, 结合可用度约束给出系统维修或在3种时机更换的概率公式, 并建立CBM优化模型; 最后, 通过数值实验对模型进行对比和敏感性分析, 验证了该模型的可行性和应用价值。

关键词: 不完全维修, 可用度约束, 单调退化系统, 逆高斯过程, 视情维修优化

Abstract:

In the current condition-based maintenance (CBM) optimization models for monotonic degradation system, only the single influence of imperfect maintenance is considered, and the availability constraint is not incorporated at the same time. In order to solve these problems, a CBM optimization model for monotonic degradation system considering the dual influence of imperfect maintenance and availability constraint is proposed. Firstly, based on the inverse Gaussian process with random drift coefficient, the system degradation model is established and the relevant probability distributions are obtained. Secondly, the system evolution process in the context of the mission is described, the residual damage model after imperfect maintenance is established, and the update formula of random drift coefficient is proposed. Thirdly, combined with availability constraint, the probability formulas for system maintenance or replacement in three situations are given, and the CBM optimization model is constructed. Finally, the comparison and the sensitivity analysis of the model are conducted through a numerical example, the experiment results verify the feasibility and application value of the proposed model.

Key words: imperfect maintenance, availability constraint, monotonic degradation system, inverse Gaussian process, condition-based maintenance (CBM) optimization

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