Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (3): 658-666.doi: 10.21629/JSEE.2018.03.23
• • 上一篇
-
收稿日期:2017-01-10出版日期:2018-06-28发布日期:2018-07-02
Moment-independence global sensitivity analysis for the system with fuzzy failure state and its Kriging method
Guijie LI(
), Chaoyang XIE(), Fayuan WEI*(), Fengjun WANG()
- Institute of System Engineering, China Academy of Engineering Physics, Mianyang 621999, China
-
Received:2017-01-10Online:2018-06-28Published: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)
引用本文
. [J]. Journal of Systems Engineering and Electronics, 2018, 29(3): 658-666.
Guijie LI, Chaoyang XIE, Fayuan WEI, Fengjun WANG. Moment-independence global sensitivity analysis for the system with fuzzy failure state and its Kriging method[J]. Journal of Systems Engineering and Electronics, 2018, 29(3): 658-666.
"
"
"
"
| Random variable | Symbol | Mean | Standard deviation |
| q/(N/m) | X1 | 20 000 | 1 400 |
| l/m | X2 | 12 | 0.6 |
| AS/m2 | X3 | 9.82×10?4 | 9.82×10?5 |
| AC/m2 | X4 | 0.04 | 0.004 |
| ES/(N/m2) | X5 | 2×1011 | 1.2×1010 |
| EC//(N/m2) | X6 | 3×1010 | 1.8×109 |
"
"
| ηi | Method | |
| MCS | KM | |
| ηq/10?3 | 1.167 | 1.074 |
| ηl/10?3 | 1.659 | 1.413 |
| ηAs/10?3 | 1.256 | 1.212 |
| ηAc/10?4 | 5.546 | 6.015 |
| ηEs/10?4 | 6.935 | 7.475 |
| ηEc/10?4 | 3.670 | 3.600 |
| ηXn+1/10?4 | 5.345 | 5.114 |
"
"
"
| Symbol | Inputvariable | Mean | Standarddeviation | Distribution |
| X1 | A/mm | 100 | 1 | Normal |
| X2 | B/mm | 200 | 1 | Normal |
| X3 | C/mm | 80 | 1 | Normal |
| X4 | D/mm | 20 | 1 | Normal |
| X5 | L1/mm | 200 | 1 | Normal |
| X6 | L2/mm | 400 | 1 | Normal |
| X7 | L3/mm | 600 | 1 | Normal |
| X8 | L4/mm | 800 | 1 | Normal |
| X9 | L5/mm | 1 000 | 1 | Normal |
| X10 | L6/mm | 1 200 | 1 | Normal |
| X11 | L/mm | 1 400 | 2 | Normal |
| X12 | P1/kN | 15 | 1.5 | Gumbel |
| X13 | P2/kN | 15 | 1.5 | Gumbel |
| X14 | P3/kN | 15 | 1.5 | Gumbel |
| X15 | P4/kN | 15 | 1.5 | Gumbel |
| X16 | P5/kN | 15 | 1.5 | Gumbel |
| X17 | P6/kN | 15 | 1.5 | Gumbel |
| X18 | Ea/GPa | 70 | 7 | Normal |
| X19 | Ew/GPa | 8.75 | 0.875 | Normal |
| X20 | S/MPa | 60 | 6 | Gumbel |
"
"
| ηi | Method | |
| MCS | KM | |
| ηA/10?4 | 3.860 | 3.653 |
| ηB/10?4 | 4.143 | 4.041 |
| ηC/10?4 | 1.120 | 1.001 |
| ηD/10?4 | 5.221 | 5.553 |
| ηL1/10?5 | 2.196 | 1.898 |
| ηL2/10?5 | 1.786 | 1.860 |
| ηL3/10?5 | 3.225 | 3.177 |
| ηL4/10?5 | 1.380 | 1.486 |
| ηL5/10?5 | 2.845 | 2.716 |
| ηL6/10?5 | 1.950 | 2.123 |
| ηL/10?4 | 1.478 | 1.432 |
| ηP1/10?3 | 1.411 | 1.348 |
| ηP2/10?3 | 1.109 | 1.062 |
| ηP3/10?3 | 1.243 | 1.190 |
| ηP4/10?4 | 7.605 | 8.168 |
| ηP5/10?4 | 4.438 | 5.058 |
| ηP6/10?5 | 8.779 | 8.934 |
| ηEa/10?4 | 8.685 | 9.084 |
| ηEw/10?4 | 7.436 | 7.602 |
| ηS/10?3 | 2.143 | 2.237 |
| 1.929 | 2.043 | |
"
| 1 |
CASTILLO E, MINGUEZ R, CASTILLO C. Sensitivity analysis in optimization and reliability problems. Reliability Engineering and System Safety, 2008, 93 (12): 1788- 1800.
doi: 10.1016/j.ress.2008.03.010 |
| 2 |
DUI H Y, SI S B, CAI Z Q, et al. Importance measure of system reliability upgrade for multi-state consecutive k-outof-n systems. Journal of Systems Engineering and Electronics, 2012, 23 (6): 936- 942.
doi: 10.1109/JSEE.2012.00115 |
| 3 | LI G J, XIE C Y, WEI F Y. The moment-independence importance measure for fuzzy failure criterion and its Kriging solution. Proc. of Prognostics and System Health Management Conference, 2017: 1-6. |
| 4 | WEI P F, LU Z Z, SONG J W. Variable importance analysis: a comprehensive review. Reliability Engineering and System Safety, 2015, 142 (1): 399- 432. |
| 5 |
LI L Y, LU Z Z, FENG J, et al. Moment-independent importance measure of basic variable and its state dependent parameter solution. Structural Safety, 2012, 38, 40- 47.
doi: 10.1016/j.strusafe.2012.04.001 |
| 6 |
SALTELLI A, MARIVOET J. Non-parametric statistics in sensitivity analysis for model output: a comparison of selected techniques. Reliability Engineering and System Safety, 1990, 28 (2): 229- 253.
doi: 10.1016/0951-8320(90)90065-U |
| 7 |
DOKSUM K, SAMAROV A. Nonparametric estimation of global functionals and a measure of the explanatory power of covariates in regression. Annals of Statistics, 1995, 23 (5): 1443- 1473.
doi: 10.1214/aos/1176324307 |
| 8 |
IMAN R L, HORA S C. A robust measure of uncertainty importance for use in fault tree system analysis. Risk Analysis, 1990, 10 (3): 401- 406.
doi: 10.1111/j.1539-6924.1990.tb00523.x |
| 9 | SOBOL I M. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and Computers in Simulation, 2001, 55 (1-3): 271- 280. |
| 10 |
HELTON J C, DAVIS F J. Latin hypercube sampling and the propagation of uncertainty in analysis of complex systems. Reliability Engineering and System Safety, 2003, 81 (1): 23- 69.
doi: 10.1016/S0951-8320(03)00058-9 |
| 11 | CHUN M H, HAN S J, TAK N I. An uncertainty importance measure using a distance metric for the change in a cumulative distribution function. Reliability Engineering and System Safety, 2007, 70 (3): 313- 321. |
| 12 |
LIU H B, CHEN W, SUDJIANTO A. Relative entropy based method for probabilistic sensitivity analysis in engineering design. Journal of Mechanical Design -Transactions of the ASME, 2006, 128 (2): 326- 336.
doi: 10.1115/1.2159025 |
| 13 |
BORGONOVO E. A new uncertainty importance measure. Reliability Engineering and System Safety, 2007, 92 (6): 771- 784.
doi: 10.1016/j.ress.2006.04.015 |
| 14 |
BORGONOVO E, CASTAINGS W, TARANTOLA S. Moment independent importance measures: new results and analytical test cases. Risk Analysis, 2011, 31 (3): 404- 428.
doi: 10.1111/j.1539-6924.2010.01519.x |
| 15 | LU Z Z, YUE Z F, FENG Y S. Procedure for the computation of fuzzy random failure probability of wear. Mechanical Science and Technology, 1997, 16 (6): 1018- 1023. |
| 16 | ZADEH L A. Probability measures of fuzzy events. Journal of Mathematical Analysis & Applications, 1968, 23 (10): 421- 427. |
| 17 | ZADEH L A. The concept of a linguistic variable and its application to approximate reasoning. Information Sciences, 1975, 8 (3): 199- 249. |
| 18 |
CAI K Y, WEN C Y, ZHANG M L. Fuzzy variables as a basis for a theory of fuzzy reliability in the possibility context. Fuzzy Sets and Systems, 1991, 42 (2): 145- 172.
doi: 10.1016/0165-0114(91)90143-E |
| 19 |
JIANG Q, CHEN C H. A numerical algorithm of fuzzy reliability. Reliability Engineering and System Safety, 2003, 80 (3): 299- 307.
doi: 10.1016/S0951-8320(03)00055-3 |
| 20 |
HUANG H Z. Fuzzy reliability analysis of generalized strength of mechanical structure. Chinese Journal of Mechanical Engineering, 2001, 37 (6): 106- 108.
doi: 10.3901/JME.2001.06.106 |
| 21 | DONG Y G. A study on fuzzy reliability design approach of machine parts while the random stress is in the form of fuzzy strength. Journal of Machine Design, 1999, 16 (3): 11- 13. |
| 22 | LI L Y, LU Z Z, CHENG L, el at. Importance analysis on the failure probability of the fuzzy and random system and its state dependent parameter solution. Fuzzy Sets and Systems, 2014, 250 (2): 69- 89. |
| 23 | LI G J, LU Z Z, LI L Y, et al. Aleatory and epistemic uncertainties analysis based on non-probabilistic reliability and its Kriging solution. Applied Mathematical Modelling, 2016, 40 (9/10): 5703- 5716. |
| 24 |
BICHON B J, ELDRED M S, SWILER L P. Efficient global reliability analysis for nonlinear implicit performance functions. AIAA Journal, 2008, 46 (10): 2459- 2468.
doi: 10.2514/1.34321 |
| 25 |
BICHON B J, MCFARLAND J M, MAHADEVAN S. Efficient surrogate models for reliability analysis of systems with multiple failure modes. Reliability Engineering and System Safety, 2011, 96 (10): 1386- 1395.
doi: 10.1016/j.ress.2011.05.008 |
| 26 | ZHANG L G, LU Z Z, WANG P. Efficient structural reliability analysis method based on advanced Kriging model. Applied Mathematical Modelling, 2015, 39 (2): 781- 793. |
| 27 | ZHANG L G, LU Z Z, CHENG L. A new method for evaluating Borgonovo moment-independent importance measure with its application in an aircraft structure. Reliability Engineering and System Safety, 2014, 132 (8): 163- 175. |
| 28 |
DU X P, SUDJIANTO A. First order saddlepoint approximation for reliability analysis. AIAA Journal, 2004, 42 (6): 1199- 1207.
doi: 10.2514/1.3877 |
| 29 |
LI L Y, LU Z Z, HU J X. A new kind of regional importance measure of the input variable and its state dependent parameter solution. Reliability Engineering and System Safety, 2014, 128, 1- 16.
doi: 10.1016/j.ress.2014.03.008 |
| No related articles found! |
| 阅读次数 | ||||||
|
全文 |
|
|||||
|
摘要 |
|
|||||