具有强非线性状态方程的机械零部件可靠性灵敏度分析方法

张义民; 朱丽莎; 王新刚

doi:10.3879/j.issn.1000-0887.2010.10.013

具有强非线性状态方程的机械零部件可靠性灵敏度分析方法

doi: 10.3879/j.issn.1000-0887.2010.10.013

东北大学机械工程与自动化学院,沈阳 110819

基金项目: “高档数控机床与基础制造装备”科技重大专项课题(2010ZX04014-014);国家自然科学基金项目(50875039);长江学者和创新团队发展计划

详细信息

作者简介:
张义民(1958- ),男,河北衡水人,东北大学长江学者、特聘教授,博士生导师(联系人.E-mail:neu863ktz@yahoo.cn).

中图分类号: O213.2；TH123
计量
- 文章访问数: 1614
- HTML全文浏览量: 101
- PDF下载量: 961
- 被引次数: 0
出版历程
- 收稿日期: 1900-01-01
- 修回日期: 2010-07-23
- 刊出日期: 2010-10-15

Advanced Method to Estimate the Reliability-Based Sensitivity of Mechanical Components With Strongly Nonlinear Performance Function

School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, P. R. China

摘要

摘要: 基于可靠性灵敏度设计的随机摄动技术，结合可靠性分析的矩方法、矩阵微分理论和Kronecker代数的相关理论，讨论了实际中存在着高度非线性极限状态方程结构的可靠性灵敏度问题．在已知随机变量前4阶矩的前提下，对基于摄动法的可靠性灵敏度计算方法进行了修正，提出了具有高度非线性结构的可靠性灵敏度计算方法．并结合实例证明了采用此方法大大提高了可靠性灵敏度的计算精度，并为工程实际提供了更加可信的理论依据．
- 可靠度 /
- 灵敏度 /
- 非线性 /
- 摄动法 /
- 矩方法
Abstract: Based on the random perturbation technique of reliability sensitivity design, some realistic reliability-based sensitivity issues were discussed, with some of them having a structure of high nonlinear performance function.Combining the relating theories of moment method of reliability analysis, matrix differential and Kronecker algebra, the reliability-based sensitivity method based on perturbation method was modified, given that the first four moments of random variables.Meanwhile, a reliability-based sensitivity computing methodology also was put forward.Some examples were adopted to prove that using this methodology could highly improve the accuracy of reliabilitybased sensitivity computation and this methodology also offers some more dependable theoretic basis for engineering.
- reliability /
- sensitivity /
- non-linear /
- perturbation theory /
- moment method

HTML全文

参考文献(21)

[1]	Ben-Haim Y. Robust reliability of structures[J]. Advances in Applied Mechanics, 1997, 31:1-41.
[2]	Liaw L D, DeVries R I. Reliability-based optimization for robust design[J]. International Journal of Vehicle Design, 2001, 25(1/2): 64-77. doi: 10.1504/IJVD.2001.001908
[3]	Zhang Y M, He X D, Liu Q L, Wen B C. Reliability-based optimization and robust design of coil tube-spring with non-normal distribution parameters[J]. Proceedings of the Institution of Mechanical Engineers Part C-Journal of Mechanical Engineering Science, 2005, 219(6): 567-576.
[4]	de Lataillade A, Blanco S, Clergent Y, Dufresne J L, Hafi M El, Fournier R. Monte Carlo method and sensitivity estimations[J]. Journal of Quantitative Spectroscopy & Radiative Transfer, 2002, 75(5): 529-538.
[5]	Melchers R E, Ahammed M. A fast approximate method for parameter sensitivity estimation in Monte Carlo structural reliability[J]. Computers & Structures, 2004, 82(1): 55-61.
[6]	Shiraishi F, Tomita T, Iwata M, Berrada A A, Hirayama H. A reliable Taylor series-based computational method for the calculation of dynamic sensitivities in large-scale metabolic reaction systems: algorithm and software evaluation[J]. Mathematical Biosciences, 2009, 222(2): 73-85. doi: 10.1016/j.mbs.2009.09.001
[7]	Karamchandani A, Cornell C A. Sensitivity estimation within first and second order reliability methods[J]. Structural Safety, 1991, 11(2): 95-107.
[8]	Zhao Y G, Ono T. Moment methods for structural reliability[J]. Structural Safety, 2001, 23(1):47-55. doi: 10.1016/S0167-4730(00)00027-8
[9]	Wu Y T, Shah C R, Baruah A K D. Progressive advanced-mean-value method for CDF and reliability analysis[J]. International Journal of Materials and Product Technology, 2002, 17(5/6): 303-318. doi: 10.1504/IJMPT.2002.005459
[10]	Zhang Y M, He X D, Liu Q L, Wen B C, Zheng J X. Reliability sensitivity of automobile components with arbitrary distribution parameters[J]. Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering, 2005, 219(D2): 165-182.
[11]	Zhang Y M, Wen B C, Chen S H. PFEM formalism in Kronecker notation[J]. Mathematics and Mechanics of Solids, 1996, 1(4): 445-461. doi: 10.1177/108128659600100406
[12]	Zhang Y M, Wen B C, Liu Q L. Reliability sensitivity for rotor-stator systems with rubbing[J]. Journal of Sound and Vibration, 2003, 259(5): 1095-1107. doi: 10.1006/jsvi.2002.5117
[13]	Zhang Y M, Wen B C, Liu Q L. First passage of uncertain single degree-of-freedom nonlinear oscillators[J]. Computer Methods in Applied Mechanics and Engineering, 1998, 165(1/4): 223-231. doi: 10.1016/S0045-7825(98)00042-5
[14]	Zhang Y M, Liu Q L, Wen B C. Quasi-failure analysis on resonant demolition of random structural systems[J]. AIAA Journal, 2002, 40(3): 585-586. doi: 10.2514/2.1688
[15]	Wu Y T, Mohanty S. Variable screening and ranking using sampling-based sensitivity measures[J]. Reliability Engineering and System Safety, 2006, 91(6): 634-647. doi: 10.1016/j.ress.2005.05.004
[16]	Kreinovich V, Beck J, Ferregut C, Sanchez A, Keller G R, Averill M, Starks S A. Monte-Carlo-type techniques for processing interval uncertainty, and their potential engineering applications[J]. Reliable Computing, 2007, 13(1): 25-69.
[17]	Wu Y. Adaptive importance sampling (AIS)-based system reliability sensitivity analysis method[C] Proceedings of the IUTAM Symposium, June 7-10, 1993. New York: Springer-Verlag, 1993: 550.
[18]	Kim C, Wang S, Choi K K. Efficient response surface modeling by using moving least-squares method and sensitivity[J]. AIAA Journal, 2005, 43(11): 2404-2411. doi: 10.2514/1.12366
[19]	Youn B D, Choi K K. A new response surface methodology for reliability-based design optimization[J]. Computers & Structures, 2004, 82(2/3): 241-256.
[20]	Lee S H, Kwak B M. Response surface augmented moment method for efficient reliability analysis[J]. Structural Safety, 2006, 28(3): 261-272. doi: 10.1016/j.strusafe.2005.08.003
[21]	Brewer John W. Kronecker products and matrix calculus in system theory[J]. IEEE Transactions on Circuits and Systems, 1978, 25(9): 772-781. doi: 10.1109/TCS.1978.1084534