基于多源数据的测试性综合评估方法研究  

Integrated Evaluation of Testability Based on Multi-source Data

作　　者：杨宗浩 YANG Zonghao(PLA Rocket Force NCO College,Qingzhou 262500,China;No.96901 Unit of PLA,Beijing 100089,China)

机构地区：[1]火箭军士官学校,山东青州262500 [2]中国人民解放军96901部队,北京100089

出　　处：《电光与控制》2021年第2期29-32,64,共5页Electronics Optics & Control

基　　金：国家自然科学基金(61304103)。

摘　　要：针对当前小样本测试性评估方法中,丰富的先验信息无法得到充分利用,评估结论置信度低的问题,提出了一种新的基于Bayes理论的测试性综合评估模型。在求得5类先验Beta分布参数的基础上,采用K-L信息距离理论计算融合权重,进而得到混合先验分布。以此混合分布作为最终的验前分布,结合现场试验数据开展Bayes评估,并给出实例应用。In the current testability evaluation methods,rich priori information cannot be fully utilized under the condition of small samples,which will result in a low-confidence conclusion.To solve the problem,a new and integrated testability evaluation method based on Bayes theory is proposed.Firstly,five kinds of priori information are analyzed,and the parameters of corresponding priori Beta distribution are obtained.Then,the combined weight is calculated by adopting the theory of K-L information distance,so as to obtain the mixed priori distribution.Finally,the mixed distribution is taken as the final priori distribution,so as to conduct Bayes assessment by using field test data,and an example application is given.

关 键 词：测试性 综合评估 多源数据 K-L信息距离 Bayes理论 

分 类 号：V19[航空宇航科学与技术—人机与环境工程] TP8061[自动化与计算机技术—检测技术与自动化装置]