Volume 45 Issue 5
May  2019
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QIU Wenhao, HUANG Kaoli, LIAN Guangyao, et al. Equivalent fault injection method based on FFS failure behavior model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(5): 952-960. doi: 10.13700/j.bh.1001-5965.2018.0486(in Chinese)
Citation: QIU Wenhao, HUANG Kaoli, LIAN Guangyao, et al. Equivalent fault injection method based on FFS failure behavior model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(5): 952-960. doi: 10.13700/j.bh.1001-5965.2018.0486(in Chinese)

Equivalent fault injection method based on FFS failure behavior model

doi: 10.13700/j.bh.1001-5965.2018.0486
Funds:

Equipment Pre-research Foundation of China 9140A27020215JB40001

National Defence Pre-research Foundation 51327030104

More Information
  • Corresponding author: HUANG Kaoli, E-mail: theroic@163.com
  • Received Date: 29 Aug 2018
  • Accepted Date: 30 Nov 2018
  • Publish Date: 20 May 2019
  • A equivalent fault injection method based on failure mode-function-state (FFS) failure behavior model is proposed to deal with the incapability of fault injection and permanent damage caused by fault injection in the fault injection based testability verification test. Firstly, the general FFS modeling idea is described, and the function is proposed as the basic element of modeling. Based on the multivariate modeling information of equipment, the failure behavior model is established. Then, the correlation matrixes and behavior state vector are defined, the method for characterizing uncertain information among failure modes, functions, and states is studied, and the calculation method for fault mode-state correlation matrix is proposed. Finally, the definition of equivalent failure mode and the equivalent fault injection process based on FFS failure behavior model are proposed. This method was applied to a launch control system. The results show that by this method the equivalent fault injection can be realized, and the rate of fault injection is increased by about 16.7%.

     

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