Focused on the complexity and highly nonlinearity of the structural dynamics characteristic in the rigid landing leg of gantry crane, the parametric finite element model and the back propagation (BP) neural network were used to establish the mapping relationship between the design variables of rigid landing leg and the maximum dynamic stress, the bending dynamic stiffness, the maximum dynamic displacement on the top of rigid landing leg. The hybrid genetic algorithm (HGA) was adopted based on the established neural network model in order to find the layout optimization of the clapboards, the lateral plates and their sizes in rigid landing leg. The fitness function was constructed based on fuzzy dynamic penalty function to guide the searching direction. Then the requirements of low-stress, high natural frequency and lightweight were meeted. Multi-objective dynamic optimization design systems were developed for the rigid landing leg of a certain crane. Application results indicate that the dynamic structural optimization of rigid landing leg can be effectively conducted, and the design quality and efficiency are evidently improved.
TONG Shui-guang, WANG Xiang-bing, ZHONG Wei, ZHANG Jian. Dynamic optimization design for rigid landing leg of crane
based on BP-HGA. J4, 2013, 47(1): 122-130.
[1] 荣见华,郑健龙,徐飞鸿.结构动力修改及优化设计[M].北京:人民交通出版社, 2002: 13-25.
[2] 廖伯瑜,周新民,尹志宏.现代机械动力学及其工程应用[M].北京:机械工业出版社,2003: 110-130.
[3] 陈官顺,刘艳斌,叶星. 龙门起重机结构动态优化设计[J]. 现代制造工程,2010(8): 149-152.
CHEN Guan-shun, LIU Yan-bin, YE Xing. Structural dynamic optimization design for gantry crane [J]. Modern Manufacturing Engineering, 2010(8): 149-152.
[4] 杨敏,黄俊杰,王浩,等. 载货车车架的灵敏度分析及结构优化[J]. 合肥工业大学学报:自然科学版,2011, 34(7): 993-996.
YANG Min, HUANG Jun-jie, WANG Hao, et al. Sensitivity analysis and structural optimization of truck frame [J]. Journal of Hefei University of Technology: Natural Science Edition, 2011,34(7): 993-996.
[5] 于兰峰,王金诺.基于遗传算法和神经网络的塔机结构动态优化设计[J].中国机械工程,2008, 19(1): 61-63.
YU Lan-feng, WANG Jin-nuo. Dynamic optimum design of tower crane based on neural networks and genetic algorithms [J]. China Mechanical Engineering, 2008, 19(1): 61-63.
[6] 郑艳平,朱厚军.具有横向裂纹轴的弯曲刚度研究[J].船舶工程,2006, 28(5): 10-13.
ZHENG Yan-ping, ZHU Hou-jun. Study on flexural stiffness of a shaft with transverse crack [J]. Ship Engineering, 2006, 28(5): 10-13.
[7] 陈浩,李军,唐宇,等. 基于动态罚函数遗传算法的电磁探测卫星多星规划方法[J].国防科技大学学报,2009, 31(2): 44-50.
CHEN Hao, LI Jun, TANG Yu, et al. An approach for electromagnetic detection satellites scheduling based on genetic algorithm with dynamic punish function [J]. Journal of National University of Defense Technology, 2009, 31(2): 44-50.
[8] ADELMAN H M, HAFTKA R T. Sensitivity analysis of discrete structural systems[J]. AIAA Journal, 1986, 24(5): 823-832.
[9] 王安麟,刘广军,姜涛.广义机械优化设计[M].武汉:华中科技大学,2008: 63-83.
[10] 于兰峰,王金诺.塔式起重机结构系统动态优化设计[J].西南交通大学学报,2007, 42(2): 206-210.
YU Lan-feng,WANG Jin-nuo. Dynamic optimum design of tower crane structures [J]. Journal of Southwest JiaoTong University, 2007, 42(2): 206-210.
[11]孙学伟,徐秉业. 起重机计算实例[M].北京: 中国铁道出版社,1985: 362-378.
[12]GEN M, CHENG R W. Genetic algorithms and engineering optimization [M]. New York: Wiley, 2000.
[13]李耀明,徐立章,丁为民.基于混合遗传算法的梳脱割台参数优化[J].农业机械学报,2003,34(4): 50-52.
LI Yaoming, XU Li-zhang, DING Wei-min. Parameter optimization of stripping header by a hybrid genetic algorithm [J].Transactions of the Chinese Society for Agricultural Machinery,2003,34 (4): 50-52.
[14]王东华,刘占生,窦唯.基于混合遗传算法的转子系统优化设计[J].振动与冲击,2009,28(5): 88-89.
WANG Dong-hua, LIU Zhan-sheng, DOU Wei. Rotor dynamics optimization based on a hybrid genetic algorithm [J]. Journal of Vibration and Shock, 2009, 28(5): 88-89.
[15]李锋,齐晓慧,李洪梁.基于权重因子的四种模糊控制规则比较[J].计算机仿真,2007, 24(12): 138-140.
LI Feng, QI Xiao-hui, LI Hong-liang.Comparison of fuzzy controller rules based on weight factor [J] . Computer Simulation, 2007, 24(12):138-140.