Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (4): 984-994.doi: 10.23919/JSEE.2021.000084

• RELIABILITY • Previous Articles    

System level test selection based on combinatorial dependency matrix

Peng YANG1(), Haoyu XIE2,*(), Jing QIU1()   

  1. 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
  • Received:2020-04-16 Online:2021-08-18 Published:2021-09-30
  • Contact: Haoyu XIE;;
  • About author:|YANG Peng was born in 1978. He received his B.S. degree from Xi’an Communication College, Xi’an, Shaanxi, China, in 2001, M.S. and Ph.D. degrees from the National University of Defense Technology, Changsha, Hunan, China, in 2003 and 2008 respectively. His currently research interests are design for testability, sensor, and signal processing. E-mail:||XIE Haoyu was born in 1982. He received his B.S., M.S., and Ph.D. degrees from the National University of Defense Technology, Changsha, China, in 2005, 2008, and 2019 respectively. He is currently engaged in the research of machine condition monitoring and fault diagnosis and equipment testability engineering. E-mail:||QIU Jing was born in 1964. He received his B.S. degree in 1985 from Beihang University, Beijing, China, M.S. and Ph.D. degrees from the National University of Defense Technology, Changsha, China, in 1988 and 1998 respectively. His research interests include fault diagnosis, reliability, testability and maintenance. E-mail:
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (51605482) and the Equipment Pre-research Project (41403020101)


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.

Key words: test selection, dependency matrix, fault detection rate, testability prediction, binary genetic algorithm