4.7 Article

Unified motion reliability analysis and comparison study of planar parallel manipulators with interval joint clearance variables

期刊

MECHANISM AND MACHINE THEORY
卷 138, 期 -, 页码 58-75

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.mechmachtheory.2019.03.041

关键词

Uncertainties; Motion reliability; Condition number; Joint clearances; Planar parallel manipulator

资金

  1. National Natural Science Foundation of China [U1501247, 51820105007]

向作者/读者索取更多资源

Motion reliability is a significant performance index for manipulators with uncertainties. This paper presents a unified motion reliability analysis method for general planar parallel manipulators (PPMs) with interval clearance variables of revolute and prismatic joints. The uncertainties of manufacturing and inputs are also considered and assumed to follow normal distributions. Two typical types of PPMs, 3 (R) under bar RR PPM and 3 (R) under bar RR PPM, are analyzed as examples to demonstrate the effectiveness of the method. For the purpose of a relatively fair comparison, the two PPMs are designed to have the same sizes of base platforms and moving platforms by using a traditional kinematic optimization based on the global conditioning index (GCI). Then, the comparison studies of the two PPMs are made with respect to performance indices of GCI, LCI (local conditioning index) and motion reliability. Furthermore, the index comparison between LCI and motion reliability is also carried out in detail through the two PPMs. The numerical analysis results indicate that: (i) the presented method could achieve a higher confidence estimate compared with the traditional probability method; (ii) the 3 (R) under bar RR PPM exhibits better motion reliability performance than the 3 (R) under bar RR PPM at the same uncertainty levels; and (iii) the traditional optimization based on the GCI cannot guarantee the good motion reliability performance of the PPM. This study provides support for the design and control of PPMs in terms of accuracy and motion reliability. (C) 2019 Elsevier Ltd. All rights reserved.

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