本文關(guān)鍵詞： 橋式起重機(jī) 箱形主梁 果蠅算法 輕量化設(shè)計(jì) 尺寸優(yōu)化　出處：《中北大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：橋式起重機(jī)作為現(xiàn)代機(jī)械中不可或缺的大型設(shè)備,被廣泛應(yīng)用在了冶金、建筑等領(lǐng)域。隨著科學(xué)技術(shù)發(fā)展的日趨成熟和市場(chǎng)競(jìng)爭(zhēng)的日益激烈,現(xiàn)有的橋式起重機(jī)已經(jīng)不能滿足企業(yè)生產(chǎn)的多元化需求,因此對(duì)橋式起重機(jī)進(jìn)行優(yōu)化設(shè)計(jì)已是行業(yè)趨勢(shì)。傳統(tǒng)的橋式起重機(jī)設(shè)計(jì)方法會(huì)造成起重機(jī)部分金屬結(jié)構(gòu)體積大、自重大等問(wèn)題。因此,在保證實(shí)際工況的前提下,用智能優(yōu)化算法對(duì)橋式起重機(jī)關(guān)鍵結(jié)構(gòu)件進(jìn)行輕量化研究,使得橋式起重機(jī)結(jié)構(gòu)更加緊湊,對(duì)起重機(jī)行業(yè)的發(fā)展具有重要意義。主梁作為橋式起重機(jī)的關(guān)鍵組成部分,對(duì)其進(jìn)行輕量化研究就顯得尤為關(guān)鍵。本文在基本果蠅算法的基礎(chǔ)上進(jìn)行改進(jìn),得到了基于速度變量的自適應(yīng)果蠅優(yōu)化算法(An adaptive fruit fly optimization algorithm based on velocity variable,簡(jiǎn)稱VFOA),并用改進(jìn)后的果蠅算法對(duì)橋式起重機(jī)箱形主梁進(jìn)行優(yōu)化設(shè)計(jì)。主要內(nèi)容有:(1)對(duì)國(guó)內(nèi)外起重機(jī)和輕量化研究現(xiàn)狀進(jìn)行分析,確定了利用群智能優(yōu)化算對(duì)橋式起重機(jī)主梁進(jìn)行輕量化研究的思路。(2)針對(duì)果蠅優(yōu)化算法收斂速度慢、已陷入局部最優(yōu)、收斂早熟的問(wèn)題進(jìn)行改進(jìn),將自適應(yīng)步長(zhǎng)和基本果蠅算法進(jìn)行結(jié)合,再引入粒子群算法中的速度變量的概念,得到一種改進(jìn)后的果蠅算法(簡(jiǎn)稱VFOA),最后使用該算法對(duì)主梁結(jié)構(gòu)進(jìn)行輕量化設(shè)計(jì)研究。(3)以某型號(hào)起重機(jī)的箱形主梁為工程實(shí)例,建立主梁優(yōu)化數(shù)學(xué)模型,運(yùn)行改進(jìn)后的果蠅算法優(yōu)化主梁截面尺寸并通過(guò)對(duì)比確定一組合理的參數(shù),將優(yōu)化結(jié)果和基本果蠅算法的優(yōu)化結(jié)果進(jìn)行對(duì)比分析。再根據(jù)此組參數(shù)在SolidWorks進(jìn)行建模,并將其運(yùn)用到Ansys軟件中進(jìn)行仿真分析。結(jié)果表明,優(yōu)化后的主梁模型相對(duì)于原始模型減重效果明顯,從而驗(yàn)證了優(yōu)化結(jié)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.

【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TH215

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