LS-SVM网络在LDF成形过程中的应用  

Application of LS-SVM network in LDF forming process

作　　者：鲁中良[1] 李涤尘[1] 卢秉恒[1] 张安峰[1] 

机构地区：[1]西安交通大学机械制造系统工程国家重点实验室,西安710049

出　　处：《焊接学报》2010年第12期9-12,共4页Transactions of The China Welding Institution

基　　金：国家重点基础研究计划资助项目(2007CB707704);长江学者和创新团队发展计划资助项目(PCSIRT0646);国家自然科学基金资助项目(51005177);博士后基金资助项目(20090451379)

摘　　要：讨论了LDF激光功率、扫描速度与送粉速率对其单道成形精度的影响.结果表明,它们之间存在复杂非线性内在的本质关系.根据这种非线性特点,采用了最小二乘支持向量机(LS-SVM)网络对其成形精度进行预测;通过LDF单道成形试验采集了样本,建立了输入输出的非线性映射关系,并利用测试样本对训练的网络进行了检验,分析了该网络的训练性能与测试性能.结果表明,通过LS-SVM网络预测LDF成形精度,其函数逼近能力、泛化能力与实时性较好,实现了高精度薄壁零件的制造.The effect of laser power,scanning speed and powder feeding rate on the depositing height of single pass welding is firstly analyzed in laser direct fabrication（LDF）,and the result shows that there is the non-linear intrinsic relationship between them.Based on the non-linear characteristic,the least square support vector machine（LS-SVM） network is adopted to predict the building precision.Training and testing samples are collected by using single pass experiments,and non-linear mapping relationship between them is built.Then,the trained LS-SVM network is examined by testing samples,and their training and testing performances are investigated.The result shows that generalization ability,function-approximating ability and real-time of the LS-SVM network are better for the prediction of the building precision in LDF,and high definition thin-walled parts are successfully fabricated.

关 键 词：激光直接制造 工艺参数 成形精度 最小二乘支持向量机 

分 类 号：TG115.28[金属学及工艺—物理冶金]