基于多影响因子和重要度的故障样本优选

针对测试性试验故障样本选择时影响因子考虑不全面、抽样方法工程应用性不强、影响因子权值主观性较强等问题，提出基于故障模式多影响因子和重要度的故障样本优选方法。在分析基于多影响因子抽样必要性的基础上确定了故障模式影响因子，并提出了基于PageRank的传播强度计算方法；提出了基于信息熵的相似度和基于相对比较关系的支持度计算方法，采用博弈决策方法确定了影响因子权值，实现了基于相对重要度的故障样本优选。将该方法应用于某装备控制系统的测试性验证试验，结果表明：故障样本优选方法能降低单次试验评估结果的随机性；样本选取时综合考虑多种影响因子和既客观又满足试验双方要求的影响因子权值，更符合测试性试验需求，选取的故障样本更合理。

Optimal Selection of Failure Samples Based on Multiple Impact Factors and Importance

A failure sample selection method based on multiple impact factors and importance of failure mode is proposed to solve the problem about the incomplete consideration of impact factors, the insufficient engineering application of sampling method and the strong subjectivity of impact factor weight in failure sample selection of testability test. On the basis of analyzing the necessity of sampling based on multiple influence factors, the impact factors are determined, and a calculation method of propagation intensity based on PageRank is proposed. A calculation method of similarity based on information entropy and support based on relative comparison is proposed, and then the impact factor weights are determined by using the game decision method, and finally the failure sample optimization based on relative importance is realized. The application of the proposed method in a control system shows that this method can be used to reduce the randomness of evaluation results of a single test. In the selection of samples, a variety of impact factors and their weights that are both objective and meet the requirements of test are taken into account comprehensively, which is more in line with the requirements of testability test and makes the selected failure samples more reasonable. Key