本文選題：橋式起重機 + 遺傳算法��； 參考：《中北大學》2014年碩士論文

【摘要】：橋式起重機是國家經(jīng)濟發(fā)展建設(shè)中不可或缺的、應(yīng)用廣泛的重要起重設(shè)備。橋架結(jié)構(gòu)中的主梁是橋式起重機的重要結(jié)構(gòu)部件，研究對其進行結(jié)構(gòu)優(yōu)化的方法，使其減輕重量，不但能夠在很大程度上節(jié)省資金，具有很強的實用價值，而且對于起重機械的發(fā)展也具有重要的意義。 遺傳算法是近年來發(fā)展迅速應(yīng)用廣泛的一種優(yōu)化算法，但在解決工程優(yōu)化問題時，常存在早熟收斂、容易陷入局部最優(yōu)解等問題。因此本文在研究了遺傳算法與人工免疫算法相關(guān)理論的基礎(chǔ)上，對兩種算法的優(yōu)點加以利用，將兩種算法結(jié)合，提出了一種對遺傳算法的改進算法——自適應(yīng)免疫遺傳算法。以遺傳算法為基本框架，將人工免疫算法的算子和選擇方法融合進去。利用自適應(yīng)概念，創(chuàng)新地設(shè)計了自適應(yīng)交叉概率和變異概率的公式，相比免疫遺傳算法的算子取值固定，自適應(yīng)概念的引入可以對尋優(yōu)過程進行智能調(diào)節(jié)，提高了尋優(yōu)速度以及增加了抗體種群的多樣性。該算法的提出，為基本遺傳算法的一些缺點，，提出了改進的方法。將該混合算法應(yīng)用于對橋式起重機的正軌箱形主梁的截面尺寸優(yōu)化。優(yōu)化結(jié)果表明，優(yōu)化后主梁截面面積較原模型減小了13.6%，具有較明顯的效果，達到了節(jié)省鋼材，減輕重量的目的。為了驗證優(yōu)化模型的合理性，本文將優(yōu)化后的模型導(dǎo)入ANSYS Workbench進行分析求解，得到的數(shù)據(jù)驗證了算法應(yīng)用于橋式起重機主梁的可行性。
[Abstract]:Bridge crane is an indispensable and widely used lifting equipment in the national economic development. The main beam of the bridge frame structure is an important structural part of the bridge crane. To study the method of structure optimization to reduce its weight can not only save money to a great extent, but also have a strong practical value. And for the development of lifting machinery is also of great significance. Genetic algorithm (GA) is one of the most widely used optimization algorithms in recent years. However, in solving engineering optimization problems, there are problems such as premature convergence, easy to fall into local optimal solution and so on. Therefore, on the basis of studying the theory of genetic algorithm and artificial immune algorithm, this paper makes use of the advantages of the two algorithms, and puts forward an improved genetic algorithm, adaptive immune genetic algorithm, by combining the two algorithms. Based on genetic algorithm (GA), the operator and selection method of artificial immune algorithm (AIA) are fused. By using adaptive concept, the formulas of adaptive crossover probability and mutation probability are designed innovatively. Compared with the fixed operator value of immune genetic algorithm, the introduction of adaptive concept can intelligently adjust the optimization process. The optimization speed is improved and the diversity of antibody population is increased. For some shortcomings of the basic genetic algorithm, an improved method is proposed. The hybrid algorithm is applied to optimize the cross section size of the box girder on the right track of the bridge crane. The optimization results show that the cross-section area of the optimized main beam is reduced by 13.6than that of the original model, which has obvious effect and achieves the purpose of saving steel and reducing the weight. In order to verify the rationality of the optimization model, the optimized model is imported into the ANSYS Workbench to analyze and solve, and the data obtained verify the feasibility of applying the algorithm to the bridge crane girder.
【學位授予單位】：中北大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TH215

【引證文獻】

相關(guān)期刊論文 前1條

1 張丹;俞齊鑫;;橋式起重機箱型主梁的改進遺傳算法優(yōu)化設(shè)計[J];機械與電子;2015年09期

本文編號：2017200