本文選題：復(fù)雜系統(tǒng) + 故障診斷　； 參考：《計算機集成制造系統(tǒng)》2017年08期

【摘要】：針對復(fù)雜系統(tǒng)故障樹模型構(gòu)建困難且模型冗余節(jié)點多、計算復(fù)雜的問題,提出一種基于多源信息融合故障樹與模糊Petri網(wǎng)的故障診斷方法。該方法先將多源信息進行標(biāo)準(zhǔn)化處理,從處理后的信息中提取維修元數(shù)據(jù),同時利用數(shù)據(jù)挖掘方法得到故障關(guān)聯(lián)項集。通過維修元數(shù)據(jù)、故障關(guān)聯(lián)項集和系統(tǒng)結(jié)構(gòu)關(guān)系的映射、融合,更加全面、準(zhǔn)確地構(gòu)建復(fù)雜系統(tǒng)故障樹模型。采用模糊Petri網(wǎng)對多源信息融合故障樹模型進行簡化和改進,并利用基于模糊Petri網(wǎng)的動態(tài)故障推理方法和基于關(guān)聯(lián)矩陣的最小割集求解方法建立復(fù)雜系統(tǒng)故障診斷方法,提高了故障的診斷速度與推理效率。以汽車發(fā)動機故障診斷過程為例,證明了所提方法的合理性和有效性。
[Abstract]:A fault diagnosis method based on multi-source information fusion fault tree and fuzzy Petri net is proposed to solve the complex problem of complex system fault tree model with more redundant nodes and complicated computation. In this method, the multi-source information is standardized and the maintenance metadata is extracted from the processed information, and the fault association item set is obtained by using the data mining method. Through the mapping and fusion of maintenance metadata, fault association item set and system structure, a more comprehensive and accurate fault tree model of complex system is constructed. The fault tree model of multi-source information fusion is simplified and improved by using fuzzy Petri net, and the fault diagnosis method of complex system is established by using the dynamic fault reasoning method based on fuzzy Petri net and the minimum cut set solution method based on correlation matrix. The fault diagnosis speed and reasoning efficiency are improved. Taking the process of automobile engine fault diagnosis as an example, the rationality and effectiveness of the proposed method are proved.
【作者單位】： 西南交通大學(xué)制造業(yè)產(chǎn)業(yè)鏈協(xié)同與信息化支撐技術(shù)四川省重點實驗室;西南交通大學(xué)四川省現(xiàn)代服務(wù)科技工程技術(shù)研究中心;
【基金】：國家科技支撐計劃資助項目(2015BAF32B05) 四川省科技支撐計劃資助項目(2015GZ0076)~~
【分類號】：TP301.1;U472.9

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