RESEARCH PAPER
Reliability-based design optimization under fuzzy and interval variables based on entropy theory
1
School of Automobile and Transportation Xihua University No. 999, Jinzhou Road, Jinniu Zone, Chengdu 610039, China
2
Institute of Electronic Engineering China Academy of Engineering Physics No. 64, Mianshan Road, Youxian Zone, Mianyang 621900, China
Publication date: 2019-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2019;21(3):430-439
KEYWORDS
ABSTRACT
Reliability-based design optimization under fuzzy and interval variables is important in engineering practice. The interval Monte
Carlo simulation (IMCS), extremum method, and saddlepoint approximation (SPA) can be used for reliability optimization issues
contain only interval variables. Thus, how to deal with the fuzzy variables is critical for system reliability analysis and optimization
design. The α-level cut method can be applied to deal with fuzzy variables but it is complex and computationally expensive. Therefore, an equivalent conversion method based on entropy theory is proposed in this paper, which can convert the fuzzy variables to
the normal random variables to avoid the complex integral process. According to the equivalent conversion method, the entropybased sequential optimization and reliability assessment (E-SORA) is developed in combination with the worst case analysis
(WCA) for reliability-based design optimization under fuzzy and interval variables. A numerical example about the reliability
design of the crank-link mechanism under fuzzy and interval variables is solved by the E-SORA, double-loops method, and α-level
cut algorithm, respectively, is used to demonstrate the accuracy and efficiency, and the results show that the proposed method is
feasible for reliability-based design optimization under fuzzy and interval variables
REFERENCES (30)
1.
Awruch M D F, Gomes H M. A fuzzy α-cut optimization analysis for vibration control of laminated composite smart structures under uncertainties. Applied Mathematical Modelling 2018; 54: 551-566, https://doi.org/10.1016/j.apm.....
2.
Bagheri M, Miri M, Shabakhty N. Fuzzy reliability analysis using a new alpha level set optimization approach based on particle swarm optimization. Journal of Intelligent & Fuzzy Systems 2016; 30(1): 235-244, https://doi.org/10.3233/IFS-15....
3.
Bagheri M, Miri M, Shabakhty N. Fuzzy time dependent structural reliability analysis using alpha level set optimization method based on genetic algorithm. Journal of Intelligent & Fuzzy Systems 2017; 32(6): 4173-4182, https://doi.org/10.3233/JIFS-1....
4.
Chakraborty S, Sam P C. Probabilistic safety analysis of structures under hybrid uncertainty. International Journal for Numerical Methods in Engineering 2007; 70: 405-422, https://doi.org/10.1002/nme.18....
5.
Chakraborty S, Sam P C. Reliability Analysis of Structures Under Hybrid Uncertainty.Safety and Risk Modeling and Its Applications. London: Springer, 2011: 77-100.
6.
Chen N, Yu D, Xia B, Liu J, Ma Z. Interval and subinterval homogenization-based method for determining the effective elastic properties of periodic microstructure with interval parameters. International Journal of Solids and Structures 2017; 206: 174-182, https://doi.org/10.1016/j.ijso....
7.
Emam O E, Fathy E, Abdullah A A. Bi-Level Multi-Objective Large Scale Integer Quadratic Programming Problem with Symmetric Trapezoidal Fuzzy Numbers in the Objective Functions. Journal of Advances in Mathematics and Computer Science 2018; 27(2): 1-15, https://doi.org/10.9734/JAMCS/....
8.
Gao W, Wu D, Gao K, Chen X, Tin-Loi F. Structural reliability analysis with imprecise random and interval fields. Applied Mathematical Modelling 2018; 55: 49-67, https://doi.org/10.1016/j.apm.....
9.
Garg H. A novel approach for analyzing the reliability of series-parallel system using credibility theory and different types of intuitionistic fuzzy numbers. Journal of the Brazilian Society of Mechanical Sciences and Engineering 2016; 38(3): 1021-1035, https://doi.org/10.1007/ s40430-014-0284-2.
10.
He L, Zhang X. Fuzzy reliability analysis using cellular automata for network systems. Information Sciences 2016; 348: 322-336, https://doi.org/10.1016/j.ins.....
11.
He Q, Zhang R, Liu T, Zha Y, Liu J. Multi-state system reliability analysis methods based on Bayesian networks merging dynamic and fuzzy fault information. International Journal of Reliability and Safety 2019; 13(1-2): 44-60, https://doi.org/10.1504/IJRS.2....
12.
Huang H Z. Structural reliability analysis using fuzzy sets theory. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2012; 14(4):284-294.
13.
Lei Z, Chen Q. A new approach to fuzzy finite element analysis. Computer Methods in Applied Mechanics and Engineering 2002; 191(45):5113-5118, https://doi.org/10.1016/S0045-....
14.
Li Y F, Mi J, Liu Y, Yang Y J, Huang H Z. Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers. Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability 2015; 229(6): 530-541, https://doi.org/10.1177/174800....
15.
Liang J, Mourelatos Z P, Tu J. A single-loop method for reliability-based design optimization. Proceedings of ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Salt Lake City, Utah, USA, September 28-October 2, 2004: 419-430, https://doi.org/10.1115/DETC20....
16.
Mi J, Li Y F, Peng W, Huang H Z. Reliability analysis of complex multi-state system with common cause failure based on evidential networks. Reliability Engineering & System Safety 2018; 174: 71-81, https://doi.org/10.1016/j.ress....
17.
Mi J, Li Y F, Yang Y J, Peng W, Huang H Z. Reliability assessment of complex electromechanical systems under epistemic uncertainty. Reliability Engineering & System Safety 2016; 152: 1-15, https://doi.org/10.1016/j.ress....
18.
Muscolino G, Santoro R, Sofi A. Reliability analysis of structures with interval uncertainties under stationary stochastic excitations. Computer Methods in Applied Mechanics and Engineering 2016; 300: 47-69, https://doi.org/10.1016/j.cma.....
19.
Peng X, Wu T, Li J, Jiang S, Qiu C, Yi B. Hybrid reliability analysis with uncertain statistical variables, sparse variables and interval variables. Engineering Optimization 2018; 50(8): 1347-1363, https://doi.org/10.1080/030521....
20.
Shen H, Su L, Park J H. Reliable mixed H-infinity/passive control for T–S fuzzy delayed systems based on a semi-Markov jump model approach. Fuzzy Sets and Systems 2017; 314: 79-98, https://doi.org/10.1016/j.fss.....
21.
Tao Y R, Cao L, Huang Z H. A novel evidence-based fuzzy reliability analysis method for structures. Structural and Multidisciplinary Optimization 2017; 55(4): 1237-1249, https://doi.org/10.1007/s00158....
22.
Wu W, Huang H Z, Wang Z L, Li Y F, Pang Y. Reliability analysis of mechanical vibration component using fuzzy sets theory. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2012; 14 (2): 130-134.
23.
Wang L, Wang X, Wang R, Chen X. Reliability-based design optimization under mixture of random, interval and convex uncertainties. Archive of Applied Mechanics 2016; 86(7): 1341-1367, https://doi.org/10.1007/s00419....
24.
Wu D, Gao W. Hybrid uncertain static analysis with random and interval fields. Computer Methods in Applied Mechanics and Engineering 2017; 315: 222-246, https://doi.org/10.1016/j.cma.....
25.
Yang Y J, Peng W, Zhu S P, Huang H Z. A Bayesian approach for sealing failure analysis considering the non-competing relationship of multiple degradation processes. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2016; 18(1): 10-15, https://doi.org/10.17531/ein.2....
26.
Zadeh L A. Probability measures of fuzzy events. Journal of Mathematical Analysis and Applications 1968; 23(2): 421-427, https://doi.org/10.1016/0022-2....
27.
Zhang E, Chen Q. Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization. Reliability Engineering & System Safety 2016; 145: 83-92, https://doi.org/10.1016/j.ress....
28.
Zhang L, Zhang J, Zhai H, Zhou S. A new assessment method of mechanism reliability based on chance measure under fuzzy and random uncertainties. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018; 20 (2): 219-228, https://doi.org/10.17531/ein.2....
29.
Zhang X, Gao H, Huang H Z, Behera D. An Equivalent Method for Fuzzy Reliability Analysis. Proceedings of 2018 Annual Reliability and Maintainability Symposium, Reno, NV, USA, January 22-25, 2018: 1-4, https://doi.org/10.1109/RAM.20....
30.
Zhang X, Gao H, Li Y F, Huang H Z. A Novel Reliability Analysis Method for Turbine Discs with the Mixture of Fuzzy and Probability-Box Variables[J]. International Journal of Turbo & Jet-Engines 2018, https://doi.org/10.1515/tjj-20....
CITATIONS (2):
1.
Uncertainty propagation in structural reliability with implicit limit state functions under aleatory and epistemic uncertainties
Shuang Zhou, Jianguo Zhang, Lingfei You, Qingyuan Zhang
Eksploatacja i Niezawodność – Maintenance and Reliability
Shuang Zhou, Jianguo Zhang, Lingfei You, Qingyuan Zhang
Eksploatacja i Niezawodność – Maintenance and Reliability
2.
A Multisource Uncertainty Fusion Reliability Evaluation Method for the Control Rod Drive Mechanism of Nuclear Power Plants
Zhihu Gao, Bo Sun, Zeyu Wu, Yang Xi, Qiang Feng, Zili Wang, Yeli Zhou, Junlin Pan, Jiankun Xu, Chaofan Sun
International Journal of Energy Research
Zhihu Gao, Bo Sun, Zeyu Wu, Yang Xi, Qiang Feng, Zili Wang, Yeli Zhou, Junlin Pan, Jiankun Xu, Chaofan Sun
International Journal of Energy Research
Share
RELATED ARTICLE
| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
