基于改进果蝇算法的桥式起重机主梁轻量化设计研究

发布时间：2018-02-21 10:37

本文关键词： 桥式起重机箱形主梁果蝇算法轻量化设计尺寸优化　出处：《中北大学》2017年硕士论文　论文类型：学位论文

【摘要】：桥式起重机作为现代机械中不可或缺的大型设备,被广泛应用在了冶金、建筑等领域。随着科学技术发展的日趋成熟和市场竞争的日益激烈,现有的桥式起重机已经不能满足企业生产的多元化需求,因此对桥式起重机进行优化设计已是行业趋势。传统的桥式起重机设计方法会造成起重机部分金属结构体积大、自重大等问题。因此,在保证实际工况的前提下,用智能优化算法对桥式起重机关键结构件进行轻量化研究,使得桥式起重机结构更加紧凑,对起重机行业的发展具有重要意义。主梁作为桥式起重机的关键组成部分,对其进行轻量化研究就显得尤为关键。本文在基本果蝇算法的基础上进行改进,得到了基于速度变量的自适应果蝇优化算法(An adaptive fruit fly optimization algorithm based on velocity variable,简称VFOA),并用改进后的果蝇算法对桥式起重机箱形主梁进行优化设计。主要内容有:(1)对国内外起重机和轻量化研究现状进行分析,确定了利用群智能优化算对桥式起重机主梁进行轻量化研究的思路。(2)针对果蝇优化算法收敛速度慢、已陷入局部最优、收敛早熟的问题进行改进,将自适应步长和基本果蝇算法进行结合,再引入粒子群算法中的速度变量的概念,得到一种改进后的果蝇算法(简称VFOA),最后使用该算法对主梁结构进行轻量化设计研究。(3)以某型号起重机的箱形主梁为工程实例,建立主梁优化数学模型,运行改进后的果蝇算法优化主梁截面尺寸并通过对比确定一组合理的参数,将优化结果和基本果蝇算法的优化结果进行对比分析。再根据此组参数在SolidWorks进行建模,并将其运用到Ansys软件中进行仿真分析。结果表明,优化后的主梁模型相对于原始模型减重效果明显,从而验证了优化结果的可行性。
[Abstract]:Bridge crane as an integral part of modern large-scale equipment machinery, is widely used in metallurgy, construction and other fields. With the development of science and technology matures and the increasingly fierce market competition, the existing bridge crane has been unable to meet the diversified production demand, so the optimization design has been the industry trend of bridge crane bridge crane. The traditional design method of the crane metal structure will cause some problems such as large volume, large weight. Therefore, under the premise of ensuring the actual condition of the optimization algorithm, the lightweight research on the key structure of bridge crane for bridge crane intelligent, makes the structure more compact, has an important significance for the development of the crane industry. As a key bridge crane girder part of the lightweight research on it is particularly important in this article. The basic algorithm based on Drosophila On the basis of improvement, then the adaptive optimization algorithm based on variable speed flies (An adaptive fruit fly optimization algorithm based on velocity variable, referred to as VFOA), and to optimize the design of crane's box girder with Drosophila improved algorithm. The main contents are as follows: (1) to the domestic and foreign research status of the crane and lightweight analysis identified the use of swarm intelligence optimization algorithm for the lightweight design of the crane girder method. (2) for Drosophila optimization algorithm slow convergence speed, has been falling into a local optimum, improved the problem of premature convergence, adaptive step and basic algorithm combined with Drosophila, and then the introduction of the concept of particle swarm algorithm in variable speed the obtained, an improved algorithm of Drosophila (VFOA), the use of the algorithm of the lightweight design of the main beam structure. (3) to a certain type of crane The box girder as an example, the establishment of the mathematical model, the improved algorithm of Drosophila operation optimization of main girder section and a reasonable set of parameters determined by contrast, results were compared to the optimization results and basic algorithm. Then flies according to the set of parameters for modeling in SolidWorks, and apply it to the Ansys software simulation analysis is carried out. The results show that the optimized girder model compared to the original model of obvious weight reduction, which verified the feasibility of the optimization results.

【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】：TH215

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