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Position: Home > Articles > Error Optimization of Pitching Mechanism Motion in Wind Tunnel Test Based on Improved Ant Colony Algorithm Transactions of the Chinese Society for Agricultural Machinery 2016,47 (7) 375-381

基于改进蚁群算法的风洞试验俯仰机构运动误差优化

作  者:
郭宗环;谢志江;宋代平;齐凯
单  位:
重庆大学机械传动国家重点实验室
关键词:
俯仰机构;风洞试验;运动精度;初始误差;蚁群算法;误差优化
摘  要:
为提高风洞试验俯仰机构的运动精度,减少初始误差,提出了基于改进蚁群算法的俯仰机构运动误差优化分析方法。针对影响俯仰机构运动精度的3个误差源——弧形导轨半径R、连杆长度L、直线导轨安装位置yOa,建立俯仰机构运动误差分析数学模型;推导了可用于分析误差的改进蚁群算法模型,将俯仰机构3个误差源的求解转换为对目标函数优化问题的求解,采用改进算法进行误差优化。对比传统数值方法,改进后的蚁群算法对误差求解精度达到10~(-5)mm级,有效地避免了结构自身产生的初始误差源对计算结果的影响。
译  名:
Error Optimization of Pitching Mechanism Motion in Wind Tunnel Test Based on Improved Ant Colony Algorithm
作  者:
Guo Zonghuan;Xie Zhijiang;Song Daiping;Qi Kai;State Key Laboratory of Mechanical Transmission,Chongqing University;
关键词:
pitch mechanism;;wind tunnel test;;motion precision;;original errors;;ant colony algorithm;;error optimization
摘  要:
In order to enhance the motion precision and reduce the initial error of the pitching mechanism which is used in the wind tunnel experiment,a novel error optimizing method was proposed. This new error optimizing approach is based on an improved ant colony algorithm. Firstly,three independent error sources which have influences on the motion precision of pitching mechanism were found and the mathematical models of three error sources including the radius of arc guide rail R,the length of connecting rod L and the installation position of linear guide rail yOawere established,respectively. The effect of each error source with the method of controlling variables was analyzed. Secondly,according to mathematical models of each error source,the mathematical model of three combined errors in the pitching mechanism was established. Based on the derived ant colony algorithm which is used in the error analyzing,the error optimizing problem could be converted to an optimizing problem of multiplied objectives. Finally,compared with results which utilize traditional Newton-Raphson iterative method,the motion accuracy of improved ant colony algorithm was higher,and the accuracy can reach a level of 10~(-5)mm. The compared results could also prove that the improved algorithm has a better global optimizing ability and it could avoid undesired effects of initial error in the structures when adopting the improved algorithm. The correctness and effectiveness of this method were confirmed by simulation with Matlab. In conclusion,the proposed approach was certificated to be effective and applicable in the engineering field.
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