System level test selection based on combinatorial dependency matrix  

作　　者：YANG Peng XIE Haoyu QIU Jing 

机构地区：[1]Science and Technology on Integrated Logistics Support Laboratory,School of Intelligence Science,National University of Defense Technology,Changsha 410073,China [2]Unit 91697 of the PLA,Qingdao 266000,China

出　　处：《Journal of Systems Engineering and Electronics》2021年第4期984-994,共11页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(51605482);the Equipment Pre-research Project(41403020101).

摘　　要：Test selection is to select the test set with the least total cost or the least total number from the alternative test set on the premise of meeting the required testability indicators.The existing models and methods are not suitable for system level test selection.The first problem is the lack of detailed data of the units’fault set and the test set,which makes it impossible to establish a traditional dependency matrix for the system level.The second problem is that the system level fault detection rate and the fault isolation rate(referred to as"two rates")are not enough to describe the fault diagnostic ability of the system level tests.An innovative dependency matrix(called combinatorial dependency matrix)composed of three submatrices is presented.The first problem is solved by simplifying the submatrix between the units’fault and the test,and the second problem is solved by establishing the system level fault detection rate,the fault isolation rate and the integrated fault detection rate(referred to as"three rates")based on the new matrix.The mathematical model of the system level test selection problem is constructed,and the binary genetic algorithm is applied to solve the problem,which achieves the goal of system level test selection.

关 键 词：test selection dependency matrix fault detection rate testability prediction binary genetic algorithm 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]