上海交通大学学报 ›› 2022, Vol. 56 ›› Issue (9): 1276-1284.doi: 10.16183/j.cnki.jsjtu.2021.104

• 机械与动力工程 • 上一篇    

双目标优化的动车组系统多阶段机会维修决策

王红1(), 齐彦昆1, 何勇1, 杨国军2   

  1. 1.兰州交通大学 机电工程学院, 兰州 730070
    2.中车戚墅堰机车车辆工艺研究所有限公司,江苏 常州 213011
  • 收稿日期:2021-04-08 出版日期:2022-09-28 发布日期:2022-10-09
  • 作者简介:王 红(1968-),男,青海省海东市人,教授,博士生导师,现主要从事轨道车辆零部件疲劳可靠性及预防性维护策略研究.电话(Tel. ):0931-4956590; E-mail: wh@mail.lzjtu.cn.
  • 基金资助:
    国家自然科学基金项目(72061022);甘肃省自然科学基金项目(20JR5RA401)

Multi-Stage Opportunistic Maintenance Decision-Making for Electric Multiple Unit Systems with Bi-Objective Optimization

WANG Hong1(), QI Yankun1, HE Yong1, YANG Guojun2   

  1. 1. School of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
    2. China Railway Rolling Stock Corporation Qishuyan Institute Co., Ltd., Changzhou 213011, Jiangsu, China
  • Received:2021-04-08 Online:2022-09-28 Published:2022-10-09

摘要:

为保证在动车组可靠运行的前提下,尽可能提高其运用效率,在传统机会维修策略的基础上提出一种双目标优化的多阶段机会维修决策策略.该策略将维修机会窗口等距划分为多个阶段,对维修时机位于不同阶段的部件实施差异力度的维修.针对多部件维修任务分配问题,提出两名维修人员的任务分配算法,并将该算法引入到多属性决策中,使模型具有良好的多属性优化性能.算例分析验证了多阶段机会维修策略在优化可用度和平均成本率方面的有效性,同时探究权重因子对模型优化倾向的影响.

关键词: 维修策略, 机会维修, 多阶段窗口, 双目标优化, 动车组系统

Abstract:

In order to improve operation efficiency of the electric multiple unit when running reliably, a multi-stage opportunistic maintenance decision strategy with bi-objective optimization is proposed based on the traditional opportunistic maintenance strategy. The window of opportunistic maintenance is equidistantly divided into multiple stages, and components located at different stages are maintained by different efforts. Aimed to solve problem of assigning multiple maintenance tasks of components, an assignment algorithm with two repairpersons is proposed. To further improve the multi-attribute optimization performance of this model, the proposed algorithm is introduced into the multi-attribute decision-making. The numerical example analysis verifies the effectiveness of the multi-stage opportunistic maintenance strategy in optimizing availability and average cost rate. Furthermore, the influence of weight factors on optimization tendency is discussed as well.

Key words: maintenance strategy, opportunistic maintenance, multi-stage windows, bi-objective optimization, system of electric multiple unit

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