系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2013年
1期
187~193
,共null页
蔡志强 孙树栋 司书宾 王宁
蔡誌彊 孫樹棟 司書賓 王寧
채지강 손수동 사서빈 왕저
复杂装备 故障预测 贝叶斯网络 故障模式 影响及危害性分析 建模
複雜裝備 故障預測 貝葉斯網絡 故障模式 影響及危害性分析 建模
복잡장비 고장예측 패협사망락 고장모식 영향급위해성분석 건모
complex equipment; failure prediction; Bayesian network; failure mode; effects and criticalityanalysis; modeling
针对复杂装备故障预测问题,本文提出一种基于故障模式,影响及危害性分析(failuremode,effectsandcriticalityanalysis,FMECA)知识的故障预测贝叶斯网络模型(failurepredictionBayesiannetwork,FPBN)建模方法.首先,在分析现有FMECA知识所包含故障信息的基础上,提出了基于FMECA单元的FPBN网络结构转化方法和FPBN概率参数计算方法,建立起对应的FPBN单元模型.然后,对复杂装备各组成部分对应的FPBN单元模型进行连接,构建整体系统的FPBN集成模型.最后,根据某机载平视显示器(headupdisplay,HUD)FMECA知识,建立了HUD电子组件的FPBN模型实例.实例分析结果表明,基于FMECA知识建立的FPBN模型具有不确定性表达和定量分析方法的优势,能够准确、有效地进行复杂装备故障预测.
針對複雜裝備故障預測問題,本文提齣一種基于故障模式,影響及危害性分析(failuremode,effectsandcriticalityanalysis,FMECA)知識的故障預測貝葉斯網絡模型(failurepredictionBayesiannetwork,FPBN)建模方法.首先,在分析現有FMECA知識所包含故障信息的基礎上,提齣瞭基于FMECA單元的FPBN網絡結構轉化方法和FPBN概率參數計算方法,建立起對應的FPBN單元模型.然後,對複雜裝備各組成部分對應的FPBN單元模型進行連接,構建整體繫統的FPBN集成模型.最後,根據某機載平視顯示器(headupdisplay,HUD)FMECA知識,建立瞭HUD電子組件的FPBN模型實例.實例分析結果錶明,基于FMECA知識建立的FPBN模型具有不確定性錶達和定量分析方法的優勢,能夠準確、有效地進行複雜裝備故障預測.
침대복잡장비고장예측문제,본문제출일충기우고장모식,영향급위해성분석(failuremode,effectsandcriticalityanalysis,FMECA)지식적고장예측패협사망락모형(failurepredictionBayesiannetwork,FPBN)건모방법.수선,재분석현유FMECA지식소포함고장신식적기출상,제출료기우FMECA단원적FPBN망락결구전화방법화FPBN개솔삼수계산방법,건립기대응적FPBN단원모형.연후,대복잡장비각조성부분대응적FPBN단원모형진행련접,구건정체계통적FPBN집성모형.최후,근거모궤재평시현시기(headupdisplay,HUD)FMECA지식,건립료HUD전자조건적FPBN모형실례.실례분석결과표명,기우FMECA지식건립적FPBN모형구유불학정성표체화정량분석방법적우세,능구준학、유효지진행복잡장비고장예측.
To establish practical failure prediction model and facilitate its applications, this paper proposed a failure prediction Bayesian network (FPBN) modeling method based on the failure mode, effects and criticality analysis (FMECA). According to the useful failure relationships embedded in the FMECA unit, the FPBN network construction and the probability parameter computation algorithms were discussed to build the corresponding FPBN unit model. Then, the FPBN unit model of each part in the complex equipment was connected with each other to establish the integrated FPBN model of the whole system. At last, based on the FMECA knowledge of a head up display (HUD), the practical FPBN case of the electronic part was built for the actual failure prediction tasks. The case analysis results show that, the FMECA knowledge embedded FPBN model, which has the advantages of uncertainty representation and quantitative analysis, can perform effectively in the failure prediction of complex eauiDments.