系统工程与电子技术 ›› 2019, Vol. 41 ›› Issue (11): 2662-2668.doi: 10.3969/j.issn.1001-506X.2019.11.33

• 可靠性 • 上一篇    

基于模糊理论与D-S证据理论的FMEA方法

韦可佳1, 耿俊豹1, 徐孙庆2   

  1. 1. 海军工程大学动力工程学院, 湖北 武汉 430033;
    2. 解放军92493部队60分队, 辽宁 葫芦岛 125000
  • 出版日期:2019-10-30 发布日期:2019-11-05

FMEA method based on fuzzy theory and D-S evidence theory

WEI Kejia1, GENG Junbao1, XU Sunqing2   

  1. 1. College of Engineering, Naval University of Engineering, Wuhan 430033, China;
    2. Unit 92493 Detachment 60 of the PLA, Huludao 125000, China
  • Online:2019-10-30 Published:2019-11-05

摘要: 针对传统故障模式及影响分析(failure mode and effect analysis, FMEA)中主观性较强以及权重分配不够合理的问题,提出基于模糊理论与Dempster-Shafer (D-S)证据理论的FMEA方法。首先,参考软件FMEA方法,将故障被检测度引入到硬件FMEA方法中,并应用模糊理论建立模糊评定等级及对应模糊数。其次,提出基于D-S证据理论的专家赋权法合理分配权重。最后,基于风险优先数(risk priority number, RPN)得出各故障模式的风险排序。案例分析表明该方法可以根据评估偏差量来科学地分配权重,使得评估结果更合理、RPN值更准确、故障模式风险排序更客观。该方法能够满足实际需要,在工程实践中值得推广应用。

关键词: D-S证据理论, 模糊理论, 故障模式及影响分析, 权重分配

Abstract: To solve the problem of strong subjectivity and unreasonable weight distribution in traditional failure mode effect analysis (FMEA), this paper proposes an FMEA method based on fuzzy theory and D-S evidence theory. First of all, this paper refers to the software FMEA method, introduces the fault detection into hardware FMEA and uses the fuzzy theory to establish corresponding fuzzy evaluation grade and fuzzy number. Then, based on D-S evidence theory, an expert weighting method is proposed in order to allocate weight rationally. Finally, risk priority number (RPN) calculation is carried out to get the risk ranking of various failure modes. The case indicates that the method can distribute weights reasonably and accurately according to the evaluation deviation, make the evaluation result more reasonable, the RPN value more accurate, and the failure mode risk ranking more objective. This method can meet the practical demands, which is worth popularizing and applying in engineering practice.


Key words: D-S evidence, fuzzy theory, failure mode effect analysis, weight allocation