發(fā)布時(shí)間：2018-08-09 16:16

【摘要】：在鐵路起重機(jī)伸縮臂單目標(biāo)普通優(yōu)化的基礎(chǔ)上,以N1002G鐵路起重機(jī)伸縮臂為例,提出了多目標(biāo)模糊優(yōu)化的理論模型。其中以六邊形二節(jié)伸縮臂的截面幾何參數(shù)為設(shè)計(jì)變量,以強(qiáng)度、剛度、穩(wěn)定性和幾何約束等一系列具有模糊特性的限制條件為約束條件,以吊臂結(jié)構(gòu)的總重量最小和整體穩(wěn)定性最大這兩個(gè)相互制約的要求為目標(biāo)函數(shù)。 本文采用二級(jí)模糊綜合評(píng)判確定鐵路起重機(jī)吊臂結(jié)構(gòu)的最優(yōu)截集水平值,應(yīng)用最優(yōu)向量水平截集法將模糊多目標(biāo)優(yōu)化模型轉(zhuǎn)化為普通多目標(biāo)優(yōu)化模型。在ISIGHT多學(xué)科優(yōu)化軟件平臺(tái)上,應(yīng)用多目標(biāo)遺傳算法NSGA-Ⅱ求解該優(yōu)化模型,得到結(jié)構(gòu)總重與整體穩(wěn)定性這兩個(gè)目標(biāo)函數(shù)在可行解下的Pareto前沿,設(shè)計(jì)者可以根據(jù)需要在Pareto解集中選擇適宜的設(shè)計(jì)方案。 本文最后利用VC++編寫一個(gè)簡(jiǎn)單易用的程序界面,用戶通過輸入Pareto解集中的設(shè)計(jì)方案,可以實(shí)時(shí)生成APDL文件,然后調(diào)用ANSYS有限元分析程序?qū)��?yōu)化結(jié)果進(jìn)行分析、驗(yàn)證。 實(shí)例證明,文中提出的模型符合鐵路起重機(jī)伸縮臂設(shè)計(jì)的實(shí)際情況,有關(guān)算法及程序?qū)嵱每尚小１疚膽?yīng)用多目標(biāo)遺傳算法NSGA-Ⅱ,得到優(yōu)化模型的多目標(biāo)不同權(quán)重下的Pareto解,供設(shè)計(jì)人員自行選擇,提高了設(shè)計(jì)的靈活性。文中以六邊形二節(jié)伸縮臂為例,建立了一般性的理論模型,故對(duì)各種截面多節(jié)臂的伸縮臂多目標(biāo)優(yōu)化設(shè)計(jì),也具有普遍的適用價(jià)值。
[Abstract]:Based on the single objective general optimization of the telescopic boom of railway crane and taking N1002G railway crane telescopic boom as an example, a theoretical model of multi-objective fuzzy optimization is proposed. The geometric parameters of hexagonal two-section telescopic arm are taken as design variables, and a series of fuzzy constraints such as strength, stiffness, stability and geometric constraints are taken as constraints. The objective function is the minimum total weight and the maximum global stability of the cantilever structure. In this paper, the two-stage fuzzy comprehensive evaluation is used to determine the optimal level of the cut set of the crane boom structure. The fuzzy multi-objective optimization model is transformed into the ordinary multi-objective optimization model by using the optimal vector horizontal cut set method. On the platform of ISIGHT multidisciplinary optimization software, the multi-objective genetic algorithm NSGA- 鈪，

本文編號(hào)：2174642