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基于Kriging模型和遗传算法的齿轮修形减振优化
Alternative TitleVibration reduction optimization of gear modification based on Kriging model and genetic algorithm
杨丽; 佟操; 陈闯; 郭秋萍
Department空间自动化技术研究室
Source Publication航空动力学报
ISSN1000-8055
2017
Volume32Issue:6Pages:1412-1418
Indexed ByEI ; CSCD
EI Accession number20173804185338
CSCD IDCSCD:6033460
Contribution Rank2
Funding Organization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)
KeywordKriging模型 齿轮 动力学 减振 修形优化 遗传算法
Abstract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...
Other AbstractTo 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.
Language中文
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20774
Collection空间自动化技术研究室
Corresponding Author杨丽
Affiliation1.沈阳理工大学装备工程学院
2.中国科学院沈阳自动化研究所
3.中国人民解放军驻474厂军代室
Recommended Citation
GB/T 7714
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.
APA 杨丽,佟操,陈闯,&郭秋萍.(2017).基于Kriging模型和遗传算法的齿轮修形减振优化.航空动力学报,32(6),1412-1418.
MLA 杨丽,et al."基于Kriging模型和遗传算法的齿轮修形减振优化".航空动力学报 32.6(2017):1412-1418.
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