發(fā)布時間：2018-11-21 08:04

【摘要】：沖壓成形是一項十分重要的零件制造方法,在汽車、飛機(jī)等工業(yè)領(lǐng)域得到了廣泛的應(yīng)用,是工業(yè)制造領(lǐng)域中的重要組成部分。對于一些形體表面極為復(fù)雜的零部件來說,在生產(chǎn)過程中需要通過調(diào)整壓邊力大小來嚴(yán)格控制板料不同成形階段或區(qū)域位置的流動,從而減少甚至消除因流動速度差別過大而造成的拉裂、起皺和回彈等成形缺陷。在一個新產(chǎn)品的開發(fā)過程中,需要通過反復(fù)地試模來獲得滿足生產(chǎn)要求的模具,其中經(jīng)常會因人為因素的緣故而造成整個模具的報廢,這無形中就增加了制模成本和周期。將數(shù)值模擬和近似模型優(yōu)化技術(shù)應(yīng)用到板料成形中,不僅可以極大縮短新產(chǎn)品的開發(fā)周期,而且能夠準(zhǔn)確獲得最優(yōu)工藝參數(shù)組合�；诖�,本文結(jié)合數(shù)值模擬和近似模型優(yōu)化技術(shù),對板料成形中壓邊力進(jìn)行了如下研究：首先,在充分考慮板料成形拉裂、起皺和回彈等多目標(biāo)情況下,采用灰色關(guān)聯(lián)分析的方法對影響板料成形的工藝參數(shù)進(jìn)行關(guān)聯(lián)分析,獲得了各個因子與板料成形質(zhì)量的關(guān)聯(lián)度,通過比較關(guān)聯(lián)度,驗證了壓邊力的控制對提高板料成形質(zhì)量的重要性。其次,基于人工免疫算法,在保證種群多樣性的同時,為了提高收斂速度,將適應(yīng)度概率與濃度抑制概率相結(jié)合,并加入精英交叉,改進(jìn)了人工免疫算法搜索性能。依據(jù)RBF神經(jīng)網(wǎng)絡(luò)的基本原理,將人工免疫算法用于RBF神經(jīng)網(wǎng)絡(luò)訓(xùn)練中,獲得了較優(yōu)的中心和寬度參數(shù),建立了一種基于人工免疫算法的RBF神經(jīng)網(wǎng)絡(luò)近似模型。最后,以NUMISHEET標(biāo)準(zhǔn)考題中的方盒和S梁作為研究對象,以變壓邊力作為設(shè)計變量,以板料成形后最大增厚、最大減薄為成形質(zhì)量指標(biāo),利用拉丁超立方進(jìn)行抽樣,使用仿真軟件Dynaform進(jìn)行成形仿真獲得訓(xùn)練樣本。以人工免疫算法為RBF神經(jīng)網(wǎng)絡(luò)的訓(xùn)練方法,分別建立隨行程、時間和位置變化的變壓邊力與成形質(zhì)量之間的近似模型,采用人工免疫算法對該模型進(jìn)行優(yōu)化,獲得最優(yōu)變壓邊力。通過與恒定壓邊成形進(jìn)行比較,表明板料成形中采用變壓邊力能夠有效提高成形件的成形質(zhì)量。
[Abstract]:Stamping forming is a very important part manufacturing method, which has been widely used in automobile, aircraft and other industrial fields. It is an important part in the industrial manufacturing field. For some parts with extremely complicated shape surface, the flow of sheet metal at different forming stages or regions should be strictly controlled by adjusting the size of the blank holder force during the production process. Thus reducing or even eliminating the forming defects such as crack wrinkle and springback caused by excessive flow velocity difference. In the process of developing a new product, it is necessary to repeatedly try the mold to obtain the mould that meets the production requirements, which often results in the die scrapping due to human factors, which increases the cost and cycle of the mould making intangibly. The application of numerical simulation and approximate model optimization techniques to sheet metal forming can not only greatly shorten the development period of new products, but also accurately obtain the optimal process parameters combination. Based on this, this paper combines numerical simulation and approximate model optimization technology to study the blank holder force in sheet metal forming as follows: firstly, considering the multi-objective of sheet metal forming such as crack, wrinkle and springback, etc. By using the method of grey correlation analysis, the correlation analysis of process parameters affecting sheet metal forming is carried out, and the correlation degree between each factor and forming quality of sheet metal is obtained, and the correlation degree is compared by comparing the correlation degree between each factor and the forming quality of sheet metal. The importance of the control of blank holder force to the improvement of sheet metal forming quality is verified. Secondly, based on the artificial immune algorithm, in order to improve the convergence speed and ensure the diversity of the population, the fitness probability is combined with the concentration suppression probability, and the elite crossover is added to improve the search performance of the artificial immune algorithm. According to the basic principle of RBF neural network, the artificial immune algorithm is applied to the training of RBF neural network. The optimal center and width parameters are obtained, and an approximate model of RBF neural network based on artificial immune algorithm is established. Finally, taking the square box and S beam in NUMISHEET standard test as the research object, taking the variable blank holder force as the design variable, taking the maximum thickening and thinning of the sheet metal after forming as the forming quality index, the Latin hypercube is used for sampling. Simulation software Dynaform is used to obtain training samples for shaping simulation. Using artificial immune algorithm as the training method of RBF neural network, the approximate models between variable blank holding force and forming quality with travel, time and position are established, and the model is optimized by artificial immune algorithm. The optimal variable blank holder force is obtained. By comparing with the constant blank holder forming, it is shown that the variable blank holder force can effectively improve the forming quality of the forming parts in sheet metal forming.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TG386

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本文編號：2346393