基于广义随机有色Petri网的测试性建模方法

针对现有测试性模型简化系统故障与测试之间的关系，忽略故障模式之间复杂性的问题，提出一种基于广义随机有色Petri网（CGSPN）的测试性建模方法。在Petri网的理论基础上对故障模式复杂性进行分析，并用不同颜色表示严酷度等级，完成CGSPN模型的构建。应用编码方案区分同一故障的多种故障模式，有效降低建模难度。采用可达性算法获取相关性矩阵。引入三角模糊数算法获取专家知识，将专家数据作为先验信息与后验测试数据相结合，解决数据量少和不可靠问题。以某型导弹为例建立CGSPN模型，对其进行测试性分析，得到96.8%的故障检测率和100%的故障隔离率，在满足系统测试性指标要求基础上丰富了模型的内容，为装备的测试性建模提出了一种新方法。

A Testability Modeling Method Based on Colored Generalized Stochastic Petri Nets

The relationship between system failures and tests is simplified and the complexity of failure modes is ignored in the existing testability model. A testability modeling method based on colored generalized stochastic Petri nets (CGSPN) is proposed. The complexity of the failure mode is analyzed based on the theory of Petri net, and the severity level is correlated with the color to complete the construction of CGSPN model. The coding scheme is used to distinguish the multiple failure modes of the same failure, thus effectively reducing the difficulty of modeling. A reachability algorithm is used to obtain the correlation matrix. The triangular fuzzy number algorithm is introduced to obtain expert knowledge, and the expert data, as a priori information, and a posteriori test data are used to solve the problem of low data volume and unreliability. Finally, taking a certain type of missile as an example, the CGSPN model was established, and 96.8% fault detection rate and 100% fault isolation rate were obtained. On the basis of meeting testability requirements, the content of the proposed model is enriched.