强电磁脉冲下柴油发动机系统薄弱环节识别

为识别强电磁脉冲环境下柴油发动机系统的薄弱环节，提出了一种加权故障树和分层贝叶斯网络相结合的柴油发动机系统薄弱环节识别方法。该方法综合考虑同层单元失效的相关性，加权故障树的局部应用解决了部分条件转移概率表不易获取问题。运用贝叶斯网络双向推理功能，首先，通过柴油发动机辐照试验和电磁仿真软件获得的各部件敏感度阈值及电磁应力数据，计算出强电磁脉冲下部件级到系统级的先验失效概率；然后，依据贝叶斯概率公式计算在发动机失效条件下各部件故障的后验概率，并排序以识别其薄弱环节，为电磁防护方案的设计提供参考和建议。以宽带高功率微波(WBHPM)辐照为例，说明了柴油发动机系统分层贝叶斯网络故障模型参数获取与概率计算过程。结果表明:执行器和凸轮轴位置传感器、曲轴位置传感器既为柴油发动机系统的重要部件，也为较薄弱环节，是需要重点防护的对象。 

Weak links identification of diesel engine system under strong electromagnetic pulse

To identify weaknesses in diesel engine systems under strong electromagnetic pulse, a method to study the identification of weak links in diesel engine system is proposed by combined weighted fault tree and hierarchical Bayesian network. This method takes into account the correlation of the failure of the same layer element, and the local application of the weighted fault tree solves the problem of obtaining partial conditional transfer probability tables. First, based on Bayesian network two-way reasoning function, the sensitivity threshold and electromagnetic stress data of each components were obtained by the diesel engine irradiation test and electromagnetic simulation software, the prior failure probability of component to the system level is calculated under strong electromagnetic pulse. Then, Bayesian probability formula is used to calculate the posterior probability of the components' failure under the condition of engine failure. The weak links of diesel engine system are identified according to the sequence of the components posterior probability, which may provide a reference for the design of electromagnetic protection scheme. Taking wide band high-power microwave (WBHPM) illumination as an example, the parameter acquisition and probability calculation process of the hierarchical Bayesian network fault model for diesel engines are illustrated. The results show that the actuator, camshaft and crankshaft sensors are not only important parts of diesel engine system, that but also is weak links, which need to be protected.