基于模糊FMEA分析的系统自动故障诊断方法

摘要

The traditional methods of system fault diagnosis are unable to automatically diagnose in the absence of historical statistics.In view of the above problem,a method of automatic fault diagnosis based on fussy FMEA analysis is proposed in this paper.By combining with fault modes,fault effect and diagnosis models of harm analysis,the method fulfills fault diagnosis based on different measured data.Fuzzy theory modeling is introduced while risk priorities number (RPN) is calculated.By means of gray correlation theory,fuzzy RPN (FRPN) of harm levels is concluded by solving fussy set,thus the expertise is merged into the evaluation model in the absence of statistics.Intelligent self-diagnosis system of fault in automatic measurement system is taken as an analysis case.By comparing the simulated results and actual results of RPN,the method is verified to be the feasible.%在缺乏历史数据统计的情况下,传统系统故障诊断方法无法进行自动诊断.对此提出了一套基于模糊FMEA分析的系统故障自动诊断的方法.该方法结合故障模式、影响及危害分析诊断模型,实现了基于不同观测数据的故障诊断,并在计算风险优先数(RPN)时引入模糊理论建模,通过灰色关联理论解模糊集得出故障危害程度的模糊风险优先数(FRPN),达到了在缺乏统计数据的情况下将专家经验融入评价模型的目的.以计量自动化系统故障(异常)智能化自诊断系统作为分析案例,通过对比仿真计算与实际运行一年的风险优先数验证了方法的可行性.