| 基于遗传算法的低压铸造铝合金车轮工艺优化 |
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| 引用本文： | 张响,童水光,刘岩,徐立.基于遗传算法的低压铸造铝合金车轮工艺优化[J].材料科学与工艺,2010,18(2):233-237. |
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| 作者姓名： | 张响 童水光 刘岩 徐立 |
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| 作者单位： | 浙江大学,化工机械研究所,杭州310027;郑州大学机械工程学院,郑州450001;浙江大学,化工机械研究所,杭州310027 |
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| 摘 要： | 为解决低压铸造铝合金车轮质量控制难度大的问题,采用遗传算法对工艺参数进行优化.基于铸造数值模拟结果,利用BP人工神经网络建立了铸造工艺参数与质量控制目标缩松缺陷和凝固时间的非线性关系,采用遗传算法实现了铸造工艺参数的优化.以某型低压铸造A356铝合金车轮为例,对浇注温度、上模温度、下模温度、侧模温度、模芯温度5个参数进行优化,得到的最佳工艺组合,可有效控制缩松缺陷和凝固时间.利用数值模拟结果、建立神经网络模型,采用遗传算法优化的方法,获得近似最优解,有助于优化低压铸造工艺.
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| 关 键 词： | 铸造模拟 人工神经网络 遗传算法 铝合金车轮 工艺优化 |
Process optimization of low-pressure die casting A356 aluminum alloy wheels based on GA |
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| ZHANG Xiang,TONG Shui-guang,LIU Yan and XU Li.Process optimization of low-pressure die casting A356 aluminum alloy wheels based on GA[J].Materials Science and Technology,2010,18(2):233-237. |
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| Authors: | ZHANG Xiang TONG Shui-guang LIU Yan and XU Li |
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| Affiliation: | Institute of Process Equipment and Control Engineering,Zhejiang University,Hangzhou 310027,China; College of Mechanical Engineering,Zhengzhou University,Zhengzhou 450001,China;Institute of Process Equipment and Control Engineering,Zhejiang University,Hangzhou 310027,China;Institute of Process Equipment and Control Engineering,Zhejiang University,Hangzhou 310027,China;Institute of Process Equipment and Control Engineering,Zhejiang University,Hangzhou 310027,China |
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| Abstract: | In order to find a solution to the casting quality control of low-pressure die casting aluminum alloy wheel,genetic algorithm is applied to the optimization of process parameters. Based on casting simulation results,the BP network is employed to build up the nonlinear mapping relationship between process parameters and control objectives,and then the optimization of parameters is realized by using genetic algorithm. A lowpressure die casting A356 aluminum alloy wheel is studied as an instance,and the parameters such as casting temperature,upper die temperature,bottom die temperature,mold core temperature and so on are optimized. Results show that this approach is effective to optimize the process parameters and control the porosity defect and solidification time,which can improve the casting process. |
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| Keywords: | casting simulation artificial neural network genetic algorithm A356 aluminum alloy wheel process optimization |
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