选择性激光烧结成型件密度模型研究  

Density Prediction Model of Selective Laser Sintering Parts

作　　者：王荣吉[1] 王玲玲[1] 赵立华[1] 

机构地区：[1]湖南大学应用物理系

出　　处：《湖南大学学报（自然科学版）》2005年第2期95-98,共4页Journal of Hunan University:Natural Sciences

基　　金：湖南省自然科学基金资助项目(03JJY3068)

摘　　要：选择性激光烧结(SLS-selectivelasersintering)加工工艺参数的变化会引起成型件密度的变化,进而影响烧结强度.本文应用神经网络方法,建立了加工工艺参数与成型件密度之间的预测模型.应用该模型分析了加工工艺参数(层厚lt,扫描间距dh,激光功率W,扫描速度v,加工环境温度Te,层与层之间的加工时间间隔Ts和扫描方式F)对成型件密度的影响.试验研究结果表明:该模型能定量地反映加工工艺参数与成型件密度之间的关系.据此可通过合理地选取工艺参数得到所需的加工件.Selective laser sintering (SLS) processing parameters affect the density of the sintered parts, which affects the strength of the sintered parts. This paper presented a prediction model for the relationship between the processing parameters and the part density by using the neural network method. The effects of processing parameters, including the layer thickness, hatch spacing, laser power, scanning speed, temperature of work surroundings, interval time and scanning mode on part density were analyzed with the model. Experiment results showed that the neural network model might be used to analyze the relationship quantitatively. The model will allow users to produce parts with desired density by selecting appropriate parameter values prior to processing.

关 键 词：神经网络 选择性激光烧结(SIS) 工艺参数 预测模型 

分 类 号：TK12[动力工程及工程热物理—工程热物理]