基于双重Rollout算法的多工作模式系统诊断策略优化
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  • 英文篇名:Diagnostic strategies optimization of multi-operating mode system based on double rollout algorithm
  • 作者:刘远宏
  • 英文作者:LIU Yuan-hong;College of Equipment Management and Supportability,Armed Police Force Engineering University;
  • 关键词:测试性设计 ; 工作模式 ; 故障隔离 ; 诊断策略 ; Rollout算法 ; 信息启发函数
  • 英文关键词:design of testability;;operating mode;;fault isolation;;diagnostic strategy;;rollout algorithm;;information heuristic function
  • 中文刊名:KZYC
  • 英文刊名:Control and Decision
  • 机构:武警工程大学装备管理与保障学院;
  • 出版日期:2018-04-18 15:02
  • 出版单位:控制与决策
  • 年:2019
  • 期:v.34
  • 基金:陕西省自然科学基金项目(2017JQ5016);; 飞行器海上测量与控制联合实验室开放基金项目(FOM2016OF11)
  • 语种:中文;
  • 页:KZYC201901028
  • 页数:6
  • CN:01
  • ISSN:21-1124/TP
  • 分类号:222-227
摘要
实际多工作模式系统测试与诊断过程中单一工作模式下测试不能检测和隔离全部故障,不同工作模式下测试检测和隔离故障的代价和效率也不同,为以最小的代价实现多工作模式系统的故障隔离与定位,提出基于双重Rollout算法的诊断策略优化方法.在构建指定工作模式下的完整诊断策略时,首先采用第1重Rollout算法,得到该工作模式下的局部诊断策略和故障模糊集;针对该工作模式下无法隔离的模糊集,采用第2重Rollout算法从剩余工作模式中选择切换至最优工作模式下进行隔离,得到新的局部诊断策略和新的模糊集;依次类推,直到故障模糊集为空或已满足系统隔离要求.实例分析结果表明,与现有算法相比,所提出方法得到的解更接近最优解,期望测试费用更低.
        The equipment system in practice has a variety of operating modes. In fault isolation and localization of multi-mode systems, faults cannot be detected and isolated in a single operating mode, and the cost and the efficiency for detecting and isolating faults are also different in different operating modes. In order to minimize the failure isolation cost of multi-operating mode systems, a diagnosis strategy optimization method for multi-operation modes based on the double rollout algorithm is proposed. Firstly, the first round of the rollout algorithm is adopted to construct the diagnosis strategy under the specific operating mode based on available tests, and the fuzzy set is obtained, based on which the second round of the rollout algorithm is used to select the optimal operating mode. The corresponding fuzzy set is obtained. Repeat these steps until the diagnostic strategy meets isolation requirements. The result of the example shows that the solution obtained by the proposed method is closer to the optimal solution than the existing algorithms, and the expected test cost is lower.
引文
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