基于稀疏网格模型与MOGA算法的起重机主梁结构优化  

Optimization of the main beam of bridge crane based on sparse grid model and MOGA algorithm

作　　者：梁其传 易朋兴[1] 邱悦 Liang Qichuan;Yi Pengxing;Qiu Yue(School of Mechanical Science & Engineering, Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]华中科技大学机械学院

出　　处：《现代制造工程》2019年第6期79-83,共5页Modern Manufacturing Engineering

基　　金：国家科技支撑计划项目(2015BAF06B00)

摘　　要：针对通用的双梁桥式起重机,提出了一种结合稀疏网格模型与MOGA算法的优化方法。运用稀疏网格模型对主梁结构参数进行拟合,模型能够自动网格细化,在减小计算量的同时保证模型建立的准确性,再通过MOGA算法对拟合的模型进行求解。相比于一般的响应面优化或者遗传算法优化,其求解的误差更小,迭代求解次数更少,效率更高。优化的结果为:质量减轻了9.6%,最大应力为78.85MPa,最大变形量为30.44mm,垂直振动频率为4.93Hz。A new method combing sparse grid model with MOGA algorithm was proposed to analyzing the universal bridge crane.The sparse grid model and automatic mesh refinement was used to fit the main beam structure parameter of crane,which can reduce the calculated amount and ensure the accuracy of model. The MOGA algorithm was used to solve the fitted model. Compared with general response surface optimization or genetic algorithm optimization,the error of solving was smaller,the number of iterative solutions was less,and the efficiency was higher. The optimized results are: mass loss of 9. 6 %,maximum stress of 78. 85 MPa,maximum deformation of 30. 44 mm,and vertical vibration frequency of 4. 93 Hz.

关 键 词：主梁 结构优化 稀疏网格模型 MOGA遗传算法 

分 类 号：TH215[机械工程—机械制造及自动化]