基于改进萤火虫算法的桥式起重机主梁优化方法研究

发布时间：2018-01-17 18:36

本文关键词：基于改进萤火虫算法的桥式起重机主梁优化方法研究　出处：《中北大学》2017年硕士论文　论文类型：学位论文

【摘要】：桥式起重机是制造业中必不可少的起重设备,可以提高运输效率,减轻劳动强度。本文针对桥式起重机传统优化设计方法减重效果差、运算效率低、无法求解复杂问题等缺点,尝试利用萤火虫优化算法(Glowworm Swarm Optimization,GSO)对桥式起重机的主梁截面尺寸进行优化,在满足生产要求的前提下,使其质量达到最轻。本文主要的研究内容有:(1)对国内外起重机和萤火虫算法的研究现状进行了分析,并对算法中存在的收敛速度慢、易陷入局部最优等缺点进行分析,提出了改进萤火虫优化算法(Improvement of Glowworm Swarm Optimization,IGSO),并将其应用于桥式起重机主梁尺寸优化当中。(2)研究了萤火虫算法优化过程中的关键步骤,并将觅食行为策略和自适应惯性权重引入到基本萤火虫算法中,最后将改进的算法与模拟退火算法重新融合构造,形成了本文的改进萤火虫算法,并用两个典型的函数对改进算法进行测试与改进前的优化数据进行对比,验证了本文算法性能和优化结果的合理性和可行性。(3)通过对模型的分析确定了优化流程,进一步研究了主梁结构和载荷分布的特点。最后,选取设计变量,建立目标函数,以及确定约束条件包括强度、刚度、稳定性、边界尺寸等等。在此基础上建立了相应的主梁截面尺寸优化设计的数学模型。(4)将某型号桥式起重机的箱形主梁作为研究对象,并对算法中的主要参数进行多次试验,确定最适合改进萤火虫算法的参数。用最优的一组控制参数来优化主梁截面面积。优化结果表明改进萤火虫算法优化结果比初始主梁的截面面积减少了20.86%,最后,用ANSYS Workbench对优化前后的模型进行对比,从强度、刚度方面验证了优化结果满足实际工程需求。
[Abstract]:Bridge crane is an indispensable lifting equipment in manufacturing industry, which can improve transportation efficiency and reduce labor intensity. We try to use the glowworm Swarm Optimization to solve the complex problem. GSO) optimizes the cross section size of the main girder of the bridge crane under the premise of satisfying the production requirements. The main research content of this paper is: 1) the research status of crane and firefly algorithm at home and abroad is analyzed, and the convergence speed of the algorithm is slow. It is easy to fall into local optimum and other shortcomings to be analyzed. The improvement of Glowworm Swarm optimization algorithm (IGSO) is proposed. The key steps in the optimization process of the firefly algorithm are studied, and the foraging behavior strategy and adaptive inertia weight are introduced into the basic firefly algorithm. Finally, the improved algorithm and simulated annealing algorithm are recombined to form the improved firefly algorithm, and two typical functions are used to test the improved algorithm and compare the optimized data before the improvement. Verify the rationality and feasibility of the algorithm performance and optimization results. (3) through the analysis of the model to determine the optimization process, and further study the characteristics of the main beam structure and load distribution. Finally. Select the design variables, establish the objective function, and determine the constraints including strength, stiffness, stability. On the basis of this, the mathematical model of the optimization design of the cross section size of the main girder is established. The box girder of a certain type of bridge crane is taken as the research object. The main parameters of the algorithm are tested many times. The optimum parameters of the improved firefly algorithm are determined. The optimum control parameters are used to optimize the cross-section area of the main beam. The optimization results show that the optimized result of the improved firefly algorithm is 20.8 less than that of the initial main beam. 6%. Finally, the model before and after optimization is compared with ANSYS Workbench, and the results of optimization are verified from the aspects of strength and stiffness to meet the actual engineering requirements.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP18;TH215

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