摘要
为解决因结构复杂、数据缺乏、人的认知水平不足等导致液压系统存在不确定性,以及液压系统存在多性能、多故障状态等多态性问题,提出了液压系统证据理论和贝叶斯网络相结合的可靠性分析方法。证据理论能够很好地处理不确定信息,利用证据理论的似然概率和信任概率描述根节点的失效可能性区间,解决根节点的故障概率存在不确定性及不易精确获取的问题;利用贝叶斯网络描述系统多态性,运用其推理算法给出了叶节点故障概率区间、根节点重要度区间以及根节点的灵敏度区间的计算方法。将该方法运用到工程机械液压驱动系统中,通过分析表明该方法能够有效地描述不确定性及多态性问题。
In order to solve the uncertainties of hydraulic systems caused by complex structure, incomplete data and imperfect cognition of failure and the multi-state problems of the multiple property and muhi-fault state in hydraulic systems, a reliability analysis method of hydraulic system combined with the evidence theory and Bayesian network is proposed. Evidence theory can well process uncertain information and describe the failure probability of the root node by using the likelihood probability and trust probability, which can solve the problem that the failure probabili- ty of the root node is not easy to obtain accurately. Then, by the description of the multi-state system and the infer- ence algorithm of Bayesian network, a method is given for calculating the failure probability interval of the leaf node, the importance indices of the root node and the sensitivity indices of the root node. Finally, the new method is applied to the construction machinery hydraulic drive system. The analysis shows that the method can effectively describe the problem of the uncertainty and multi-state.
作者
陈东宁
李怀水
姚成玉
李硕
饶乐庆
CHEN Dong-ning LI Huai-shui YAO Cheng-yu LI Shuo RAO Le-qing(Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan University Key Laboratory of Advanced Forging ＆ Stamping Technology and Science Yanshan University） , Ministry of Education of China, Qinhuangdao, Hebei 066004 Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University,Qinhuangdao, Hebei 066004)
出处
《液压与气动》
北大核心
2017年第4期8-14,共7页
Chinese Hydraulics & Pneumatics
基金
国家自然科学基金(51405426
51675460)
河北省自然科学基金(E2016203306)
关键词
液压驱动系统
可靠性分析
贝叶斯网络
证据理论
hydraulic drive system, reliability analysis, Bayesian network, evidence theory
