基于贝叶斯网络的元件重要度和灵敏度分析

对于机械系统来说,组成元件的可靠性决定了系统的可靠性,而处于系统结构不同位置的元件对于系统可靠性的影响又存在很大的差异.据此,提出了基于贝叶斯网络的复杂机械系统可靠性组成元件重要度和灵敏度分析的方法,运用该方法不但能计算出机械系统的可靠性指标,而且能方便地给出每个部件或几个部件对系统整体可靠性影响的大小,识别系统的薄弱环节.给出了结合故障树方法建立系统贝叶斯网络模型的方法,并用实例验证了用贝叶斯网络方法进行机械系统可靠性评估以及进行组成元件重要度和灵敏度分析的有效性和优越性.

Elements importance and sensitivity analysis based on Bayesian network

For mechanical system,the system reliability is determined by the reliability of elements which inference the system reliability differently according to the position in system.In this paper elements importance and sensitivity analysis based on Bayesian network for complex mechanical system are put forward Bayesian Networks permit not only computing the reliability indices of a mechanical system but also presenting the effect of each component or some components on the system reliability to distinguish the unsubstantial part of system.A method of constructing Bayesian networks with the ideology of fault tree is used to assess mechanical system reliability in the paper.The results of two examples prove the validity and superiority of the method in the application of the reliability assessment of mechanical system.