Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (3): 658-666.doi: 10.21629/JSEE.2018.03.23

• Reliability • Previous Articles    

Moment-independence global sensitivity analysis for the system with fuzzy failure state and its Kriging method

Guijie LI(), Chaoyang XIE(), Fayuan WEI*(), Fengjun WANG()   

  • Received:2017-01-10 Online:2018-06-28 Published:2018-07-02
  • Contact: Fayuan WEI E-mail:411liguij@caep.cn;xiezy@caep.cn;weify@caep.cn;wangfj@caep.cn
  • About author:LI Guijie was born in 1983. He is currently an engineer in Institute of System Engineering, China Academy of Engineering Physics. He received his B.S. degree, M.S. degree and Ph.D. degree in aircraft design from School of Aeronautics, Northwestern Polytechnical University, China, in 2006, 2010 and 2015, respectively. He has authored over 20 papers in international journals and conferences. His research interests include structural reliability, uncertain analysis and importance measure. E-mail: 411liguij@caep.cn|XIE Chaoyang was born in 1981. He is currently an engineer in Institute of System Engineering, China Academy of Engineering Physics. He received his B.S. degree in engineering physics from Department of Engineering Physics, Tsinghua University, China, in 2004. He is currently a Ph.D. candidate in School of Mechatronics Engineering, University of Electronic Science and Technology, China. His research interests include structural reliability and uncertain analysis. E-mail: xiezy@caep.cn|WEI Fayuan was born in 1974. He is currently a researcher in Institute of System Engineering, China Academy of Engineering Physics. He received his Ph.D. degree in mechanical design from School of Mechanical Science and Engineering, Huazhong University of Science and Technology, China, in 2003. His research interests include multidisciplinary integrated design, system engineering and reliability, prognostics and health management. E-mail: weify@caep.cn|WANG Fengjun was born in 1981. He is currently a senior engineer in Institute of System Engineering, China Academy of Engineering Physics. He received his M.S. degree in weapon system engineering from Graduate School, China Academy of Engineering Physics in 2006. His research interests include multidisciplinary integrated design and weapon system engineering. E-mail: wangfj@caep.cn
  • Supported by:
    the National Natural Science Foundation of China(11702281);the Science Challenge Project(TZ2018007);the Technology Foundation Project of State Administration of Science, Technology and Industry for National Defence, PRC(JSZL2017212A001);This work was supported by the National Natural Science Foundation of China (11702281), the Science Challenge Project (TZ2018007), and the Technology Foundation Project of State Administration of Science, Technology and Industry for National Defence, PRC (JSZL2017212A001)

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Abstract:

For the system with the fuzzy failure state, the effects of the input random variables and the fuzzy failure state on the fuzzy probability of failure for the structural system are studied, and the moment-independence global sensitivity analysis (GSA) model is proposed to quantitatively measure these effects. According to the fuzzy random theory, the fuzzy failure state is transformed into an equivalent new random variable for the system, and the complementary function of the membership function of the fuzzy failure state is defined as the cumulative distribution function (CDF) of the new random variable. After introducing the new random variable, the equivalent performance function of the original problem is built. The difference between the unconditional fuzzy probability of failure and conditional fuzzy probability of failure is defined as the moment-independent GSA index. In order to solve the proposed GSA index efficiently, the Kriging-based algorithm is developed to estimate the defined moment-independence GSA index. Two engineering examples are employed to verify the feasibility and rationality of the presented GSA model, and the advantages of the developed Kriging method are also illustrated.

Key words: fuzzy uncertainty, fuzzy failure state, fuzzy probability of failure, moment-independence global sensitivity analysis (GSA), Kriging model

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