动态故障树分析方法以故障树的直观表达形式来对系统建模，以马尔科夫方法来求解模型，同时具有故障树方法与马尔科夫方法的优点，这使其得到广泛的运用。贝叶斯网络模型在不确定性的表达、量化和推理方面具有较强的处理能力。整流回馈系统作为大型矿用挖掘机电气控制系统的重要组成部分，其工作可靠性对整个挖掘机系统的正常工作及各个动作的顺利执行具有重要的影响。考虑到该系统内部采用了大量冗余结构，采用基于连续时间贝叶斯网络的建模及分析方法对其动态特性进行动态故障树建模与评估。另一方面，考虑到这种大型复杂系统样本数量少、难以进行失效参数的精确估计等，采用模糊数来表征其基本失效率参数。通过对整流回馈系统的可靠性建模及分析验证了本方法的可行性。

In dynamic fault tree analysis method, the model of complex system is constructed by fault tree, and the solution process is implemented by Markov process. It is provided with both the advantages of fault tree analysis and Markov process, which makes it extensively used in many engineering fields. Bayesian networks have the powerful capacity of dealing with representation, quantification and inference for uncertain information. Rectifier feedback system is an important part of electrical control systems of large mining excavator, whose working reliability has a significant impact on the reliability of the entire system. There exist a large number of redundant structures in the is system. The continuous time Bayesian network based modelling and analysis method is applied to model and evaluate these dynamic characteristics. Furthermore, the sample size of these complex systems is poor, which makes the precise estimation of failure parameters very difficult. The fuzzy numbers are utilized to characterize the failure rate of components. The proposed method is carried out on rectifier feedback system to demonstrate its effectiveness.