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Heuristic particle swarm optimization approach for test point selection with imperfect test

Author

Listed:
  • Sen Deng

    (Air Force Engineering University)

  • Bo Jing

    (Air Force Engineering University)

  • Hongliang Zhou

    (Air Force Engineering University)

Abstract

The problem of near-optimal test point set selection with imperfect test is solved by using the heuristic particle swarm optimization (HPSO) algorithm. First, to describe the uncertainty of each test, the testability analysis model and such indexes as fault detection rate, fault isolation rate, and false alarm rate are redefined. A heuristic function is then established to evaluate the detection isolation capability and uncertainty of the test point, which can provide heuristic information to improve the searching efficiency of particle swarm optimization (PSO). The heuristic function and least test cost principle are used as bases to design a fitness function of PSO algorithm for test point selection. Finally, the HPSO algorithm is proposed to select the optimal test point set for two practical systems. Simulation and experiment results show that the method can determine the global optimal test point accurately and effectively while meeting the requirements of testability indexes with least cost.

Suggested Citation

  • Sen Deng & Bo Jing & Hongliang Zhou, 2017. "Heuristic particle swarm optimization approach for test point selection with imperfect test," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 37-50, January.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:1:d:10.1007_s10845-014-0960-1
    DOI: 10.1007/s10845-014-0960-1
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    Cited by:

    1. Tian, Heng & Duan, Fuhai & Fan, Liang & Sang, Yong, 2019. "Novel solution for sequential fault diagnosis based on a growing algorithm," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    2. Xiaofeng Lv & Deyun Zhou & Yongchuan Tang & Ling Ma, 2018. "An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO," Complexity, Hindawi, vol. 2018, pages 1-10, January.
    3. Wang, Jingyuan & Liu, Zhen & Wang, Jiahong & Long, Bing & Zhou, Xiuyun, 2022. "A general enhancement method for test strategy generation for the sequential fault diagnosis of complex systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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