Hybrid dimension reduction for mechanism reliability analysis with random joint clearances

被引:88
作者
Wang, Jinge [2 ]
Zhang, Junfu [2 ]
Du, Xiaoping [1 ]
机构
[1] Missouri Univ Sci & Technol, Dept Mech & Aerosp Engn, Rolla, MO USA
[2] Xihua Univ, Sch Mech Engn & Automat, Chengdu, Peoples R China
关键词
Reliability; Mechanism analysis; Kinematics; Dimension reduction; CUBATURE FORMULAS; SEQUENTIAL OPTIMIZATION; MODEL REPRESENTATION; UNCERTAINTY ANALYSIS; DESIGN OPTIMIZATION; ERROR; LINKAGES; INTEGRATION; SIMPLICES; PLANAR;
D O I
10.1016/j.mechmachtheory.2011.05.008
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Randomness in mechanism dimensions and joints makes the mechanism motion deviate from its designed motion. The probability (reliability) that such deviation is within an error tolerance limit should be invariably large. This study shows that the accuracy of the reliability analysis for dependent joint clearances is insufficient by existing kinematic reliability methods, such as the First Order Second Moment (FOSM) Method and First Order Reliability Method (FORM). We therefore propose a Hybrid Dimension Reduction Method (HDRM) to better handle the dependent joint clearance variables. With the first order Taylor expansion for independent dimension variables and bivariate dimension reduction for dependent joint clearance variables, HDRM produces more accurate solutions than the FOSM and FORM while maintains higher efficiency than FORM and Monte Carlo simulation. A slider-crank mechanism is used as an example for the methodology demonstration and validation. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1396 / 1410
页数:15
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