系统仿真学报 ›› 2018, Vol. 30 ›› Issue (6): 2216-2224.doi: 10.16182/j.issn1004731x.joss.201806027

• 仿真系统与技术 • 上一篇    下一篇

面向装备RUL预测的平行仿真框架

葛承垄1, 朱元昌1, 邸彦强1, 胡志伟1, 董志华2   

  1. 1.军械工程学院,河北 石家庄 050003;
    2.中国白城兵器试验中心,吉林 白城 137001
  • 收稿日期:2016-07-29 修回日期:2016-10-13 出版日期:2018-06-08 发布日期:2018-06-14
  • 作者简介:葛承垄(1990-),男,山东平阴,博士生,研究方向为装备平行仿真;朱元昌(1960-),男,黑龙江哈尔滨,博士,教授,博导,研究方向为系统仿真。
  • 基金资助:
    装备预研基金(9140A04020115JB34011)

Equipment RUL Prediction Oriented Parallel Simulation Framework

Ge Chenglong1, Zhu Yuanchang1, Di Yanqiang1, Hu Zhiwei1, Dong Zhihua2   

  1. 1.Ordnance Engineering College, Shijiazhuang 050003, China;
    2.Baicheng Ordnance Test Center, Baicheng 137001, China
  • Received:2016-07-29 Revised:2016-10-13 Online:2018-06-08 Published:2018-06-14

摘要: 由于装备状态具有复杂多变、不确定性强、信息量大的特点,造成根据装备状态研究具有自更新能力的剩余寿命预测模型成为当前的难点,仿真为解决剩余寿命预测问题提供了有效途径。基于平行系统理论,提出面向装备剩余寿命预测的平行仿真概念及技术框架,讨论了平行仿真的概念、特点、能力需求和功能组成,并重点介绍了面向装备剩余寿命预测平行仿真的主要建模技术,包括装备退化状态感知、装备退化状态空间模型构建、装备退化状态空间模型演化,为建立面向装备剩余寿命预测的平行仿真系统提供了借鉴。

关键词: 平行仿真, 模型演化, 剩余寿命, 状态感知, 状态空间模型, 数据同化, 参数估计

Abstract: As the equipment states are complicated with uncertainty, predicting remaining useful life with self-updating ability has become a hard task. Simulation provides an effective way to solve the problem. The concept and technology framework of equipment remaining useful life prediction oriented parallel simulation are proposed based on parallel system theory and the concept, characteristics, capacity demands and functional compositions of parallel simulation are introduced. The main modeling technologies of equipment remaining useful life prediction oriented parallel simulation are discussed, which include awareness of equipment degradation state, construction of equipment degradation state space model and evolution of equipment degradation state space model. It provides references for building equipment remaining useful life prediction oriented parallel simulation system.

Key words: parallel simulation, model evolution, remaining useful life, state awareness, state space model, data assimilation, parameter estimation

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