期刊
APPLIED SOFT COMPUTING
卷 32, 期 -, 页码 369-382出版社
ELSEVIER
DOI: 10.1016/j.asoc.2015.03.044
关键词
Connection frame; Thermal-mechanical deformation; Natural frequency; RSM; Multi-objective optimization
资金
- Guangdong Innovative Research Team Program [2009010051]
- Guangdong Key Project [2011A080801004]
- National Natural Science Foundation of China [U1134004]
- Innovation Fund of Harbin Industrial University [HIT.NSRIF.2013099]
- Basic Research Plan of Shenzhen [JC201105160586A]
- Province University-industry Cooperation Project [2012B091100022]
- Dongguan City Project in Colleges and Universities [2012108102023]
Connection frame is an essential component to implement high acceleration and ultra-precision positioning motion in a macro-micro motion platform. The performance of the positioning system is mainly affected by two sources which include thermal-mechanical deformation and the natural frequency of connection frame. In the paper, multi-objective optimization and design for the connection frame is constructed and discussed comprehensively by the effects of thermal-mechanical deformation and the natural frequency of the system. The optimization objectives for the connection structure are the minimized displacement when thermal-mechanical deformation is occurred, the maximized natural frequency to avoid system resonance, and the light weight for the connection structure to fulfil high acceleration motion. Using response surface method (RSM) combined with finite element method (FEM), the objective function is formulated as a prediction model. Non-dominated Sorting Genetic Algorithm II (NSGAII) is used to solve the optimization model and attain the matched parameters. A cantilever beam example is tested to examine the validity of the methodology, and the results from prediction model agree well with that from theoretical model. By the above methodology, a high performance with optimal parameters for the connection structure is obtained, and its natural frequency and weight can meet our design expectation. (C) 2015 Elsevier B.V. All rights reserved.
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