文档介绍：Mechanism and Machine Theory 44 (2009) 1321–1337
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Mechanism and Machine Theory
journal homepage: ate/mechmt
Robust mechanism synthesis with random and interval variables
Xiaoping Du a,*, Pavan Kumar Venigella a, Deshun Liu b
a Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, 400 West 13th Street, Rolla, MO 65409-4494, USA
b Hunan University of Science and Technology, PR China
article info abstract
Article history: Robust mechanism synthesis minimizes the impact of uncertainties on the mechanism
Received 29 November 2007 performance. It has traditionally been performed by either a probabilistic approach or a
Received in revised form 10 October 2008 worst case approach. Both approaches treat uncertainty as either random variables or
Accepted 18 October 2008
interval variables. In reality, uncertainty can be a mixture of both. In this paper, methods
Available online 4 December 2008
are developed for robustness assessment and robust mechanism synthesis when random
and interval variables are involved. Monte Carlo simulation is used to perform robustness
assessment under an optimization framework for mechanism synthesis.
Keywords:
Ó 2008 Elsevier Ltd. All rights reserved.
Synthesis
Robustness
Optimization
1. Introduction
Kinematic synthesis is the process of systematic design of a mechanism to achieve a specific task [1]. The task can be mo-
tion generation, path generation, or function generation. Kinematic synthesis is classified into two groups, type synthesis and
dimensional synthesis. Type synthesis deals with finding the best suitable mechanism (cam mechanisms, linkages, gear
trains, etc.), number of links, degree of freedom and so on, to achieve the required performance. Dimensional synthesis deals
with determining the significant dimensions of the mechanism to achieve a specific task. In this paper, we concentrate on
dimensional synthesis of