基于RCMⅡ和CCF理论的隐蔽性故障的新评价模型  

A New Evaluation Model Based on RCM Ⅱ/CCF Theory for Hidden Faults

作　　者：倪爱伟[1] 谢里阳[1] 翁刚[2] 吴克勤[1] 

机构地区：[1]东北大学机械工程与自动化学院,辽宁沈阳110004 [2]中国石油天然气股份有限公司辽阳石化分公司,辽宁辽阳111003

出　　处：《东北大学学报（自然科学版）》2008年第1期105-108,共4页Journal of Northeastern University(Natural Science)

基　　金：国家高技术研究发展计划项目(2006AA04Z408);国家重大基础研究发展规划项目(2006CB605005)

摘　　要：以可靠性为中心的维修(RCM Ⅱ)中用以计算隐蔽性故障率的数学模型存在缺陷,特别对于具有安全性和环境性后果的隐蔽性故障可能引起致命的错误.基于共因失效(CCF)理论,充分分析国内外共因失效模型的优劣,修正原模型假设条件的缺陷,首次建立了新的评价隐蔽性故障的数学模型;并有效地应用神经网络技术求解,得到较精确的新模型的4个参数.通过与原模型和随机模型比较,新模型更准确地描述隐蔽性故障过程,可靠性预计的精度更高,较好地指导了生产设计和实际维修活动.It will possibly be a lethal mistake if using the defective mathematical model in terms of RCMⅡ （reliability-centered maintenance Ⅱ） to calculate the rate of hidden faults especially those hidden faults concerning safety and environmental adversity. So, based on the CCF（common cause failure） theory and analyzing lots of different failed CCF models in comparison with each other, a new evaluation model is developed first for hidden faults by way of modifying their defective assumption conditions, and the BP in neural network is used to solve efficiently the model in which 4 relatively accurate parameters are thus obtained. Compared with the original models and stochastic ones, the new model can express the process of hidden fault more exactly with higher accuracy of reliability evaluation and is therefore beneficial to actual design and maintenance in production.

关 键 词：隐蔽性故障 RCMⅡ CCF 神经网络 

分 类 号：TH17[机械工程—机械制造及自动化]