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作 者:崔庆安[1,2] 张亦驰 CUI Qingan;ZHANG Yichi(School of Management Engineering,Zhengzhou University,Zhengzhou Henan 450001,China;School of Economics&Management,Shanghai Maritime University,Shanghai 201306,China)
机构地区:[1]郑州大学管理工程学院,河南郑州450001 [2]上海海事大学经济管理学院,上海201306
出 处:《工业工程与管理》2023年第2期198-206,共9页Industrial Engineering and Management
基 金:国家自然科学基金资助项目(71571168);国家自然科学基金河南省联合基金重点项目(U1904211);科技部创新方法工作专项(2019IM020200)。
摘 要:针对同时降低翘曲量和缩短打印时间的熔融沉积成型(FDM)多响应参数优化问题,提出一种基于改进最小二乘支持向量回归机(LS-SVR)和逼近理想点决策法(TOPSIS)的优化方法。首先,将打印速度视作函数型参数并使用Bezier曲线对其建模,曲线定义点与喷嘴温度、热床温度和填充率共同作为设计变量,通过超拉丁方抽样进行实验设计。其次,采用基于Fréchet距离改进核函数的LS-SVR建立参数与各响应之间的作用关系模型,使得函数型参数以函数形式嵌入整体模型中。最后,通过带精英策略的非支配排序遗传算法寻优并利用TOPSIS确定最优参数组合。优化结果表明,所提方法与基于Euclidean距离的LS-SVR和基于标量型参数的LS-SVR方法相比优化效果更好,说明了方法的有效性。An optimization method based on an improved least squares support vector regression machine(LS-SVR)and the technique for order preference by similarity to an ideal solution(TOPSIS)was proposed for the parameter optimization of fused deposition molding(FDM)multiresponse that simultaneously reduced warpage and shortened printing time.Firstly,the print speed was considered as a functional parameter and modeled using a Bezier curve.The curve definition points together with nozzle temperature,hotbed temperature,and fill rate were the design variables.The experimental design was carried out by Latin hypercube sampling.Secondly,the LS-SVR based on the kernel function improved by the Frechet distance was used to model the action relationship between parameters and each response,so that the functional parameters were embedded in the overall model in a functional form.Finally,the non-dominated sorting genetic algorithm Ⅱ and TOPSIS were used to find and determine the optimal combination of parameters.The optimization results show that the proposed method is better than the LS-SVR method based on Euclidean distance and the LS-SVR based on scalar parameters,which illustrates the effectiveness of the method.
关 键 词:多响应参数优化 最小二乘支持向量回归 函数型参数
分 类 号:TP181[自动化与计算机技术—控制理论与控制工程]
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