Evidence and optimization theory based multi-source information fusion for reliability demonstration test plan design
编号:102 访问权限:仅限参会人 更新:2024-10-23 10:27:54 浏览:183次 口头报告

报告开始:2024年11月01日 17:20(Asia/Shanghai)

报告时间:20min

所在会场:[P3] Parallel Session 3 [P3-1] Parallel Session 3(November 1 PM)

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摘要
In the development stage and use stage, reliability demonstration test is important in determining products' reliability at a certain time. However, it is usually difficult to get the distribution of products with little testing data. In this paper, four methods for determining distribution parameters are proposed and compared. They are based on optimization with complex boundary and D-S evidence theory. These method can decrease the uncertainty of maximum entropy method by fusing several types of expert judgment and other prior information. By using bound search and visualization, the principle of decreasing the uncertainty is found to narrow the feasible region by changing the bound determined by prior information. And based on the result, an example is calculated by using different methods. The results indicates that by fusing prior information can effectively decrease risks of reliability demonstration test plan and optimization method will give lower risks for the same test plan than D-S evidence method.
 
关键词
D-S evidence theory,reliability demonstration,maximum entropy,boundary search,risk calculation
报告人
TanYunlei
Evidence and optimiz National University of Defense Technology;College of System Engineering

稿件作者
TanYunlei National University of Defense Technology;College of System Engineering
JiangPing College of Systems Engineering; National University of Defense Technology
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重要日期
  • 会议日期

    10月31日

    2024

    11月03日

    2024

  • 09月30日 2024

    初稿截稿日期

  • 11月12日 2024

    注册截止日期

主办单位
Anhui University
Xi’an Jiaotong University
Harbin Institute of Technology
IEEE Instrumentation & Measurement Society
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