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题名:
基于Kriging模型和遗传算法的齿轮修形减振优化
其他题名: Vibration reduction optimization of gear modification based on Kriging model and genetic algorithm
作者: 杨丽; 佟操; 陈闯; 郭秋萍
作者部门: 空间自动化技术研究室
通讯作者: 杨丽
关键词: Kriging模型 ; 齿轮 ; 动力学 ; 减振 ; 修形优化 ; 遗传算法
刊名: 航空动力学报
ISSN号: 1000-8055
出版日期: 2017
卷号: 32, 期号:6, 页码:1412-1418
收录类别: EI ; CSCD
产权排序: 2
项目资助者: 辽宁省自然科学基金指导计划项目(201602650) ; 辽宁省教育厅科学研究项目(L2015469) ; 沈阳理工大学重点实验室开放基金(4771004kfs26)
摘要: 针对齿轮修形优化时计算啮合刚度计算量大、计算精度低、操作繁琐等问题,提出一种基于Kriging模型和遗传算法的齿轮减振修形优化算法.以典型直齿轮传动为例开展齿轮修形优化,通过拉丁抽样建立Kriging模型,解决齿轮修形优化的多响应和隐式函数的问题,通过Kriging预测的啮合刚度与有限元法的对比可知,时变啮合刚度函数各参数的误差最大值为7.79×10~(-5),1.20×10~(-3)及1.30×10~(-4),验证了Kriging多响应预测啮合刚度函数的精确性.将Kriging预测函数代入直齿轮啮合传动的动力学微分方程,采用遗传优化算法时将齿轮动态传动误差响应波动最小作为优化目标,得到最优的...
英文摘要: To solves the problems of large computation, low precision and complicated operation during optimization of gear modification, an algorithm for optimization of gear modification was proposed based on Kriging model and genetic algorithm. Taking spur gear drive as the research object, optimization of gear modification was carried out. Firstly, in order to solve the problems of multiple responses and implicit function during optimization of gear modification, Kriging model was established by using Latin sampling method. Compared with the gear engaged stiffness of Kriging prediction and finite element, it was shown that the maximum errors of predicted stiffness parameters were 7.79×10-5, 1.20×10-3 and 1.30×10-4 respectively, therefore, the precision of Kriging multiple prediction was validated. Secondly, Kriging prediction was applied to dynamical differential equation of spur gear, and then fluctuation of dynamic transmission error was regarded as the goal of genetic algorithm optimization, so optimal parameters of gear modification was obtained. Example showed that the proposed method was better than ISO(International Standardization Organization) modification and no modification, therefore, the efficiency and correctness of the gear modification by using genetic algorithm and Kriging model was validated. Compared with gear modification by using finite element directly, the cost time of the proposed method changed from 26.91d to 2.24h, so the computational efficiency of the proposed method was verified.
语种: 中文
EI收录号: 20173804185338
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/20774
Appears in Collections:空间自动化技术研究室_期刊论文

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Recommended Citation:
杨丽,佟操,陈闯,等. 基于Kriging模型和遗传算法的齿轮修形减振优化[J]. 航空动力学报,2017,32(6):1412-1418.
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