【摘要】：采用SLA 3D打印機打印不同參數(shù)的同一模型,測量成型件模型尺寸參數(shù),并利用改進的LSSVM模型對不同參數(shù)的成型件尺寸誤差進行預(yù)測。首先分析主要影響SLA 3D打印模型質(zhì)量的原因,確定四個主要因素:疊層厚度,模型擺放角度和支撐密度,接觸點大小。設(shè)計試驗,采用SLA 3D打印機在此參數(shù)下打印,再對打印成型件進行測量確定成型件尺寸信息及尺寸誤差,基于已有數(shù)據(jù)建立改進的LS-SVM模型對不同打印參數(shù)下的成型件的尺寸誤差進行預(yù)測。結(jié)果表明模型預(yù)測正確率達到92.6471%,改進的LS-SVM相較于原尋優(yōu)方法及BP神經(jīng)網(wǎng)絡(luò)對SLA 3D打印尺寸誤差預(yù)測有良好的效果。
[Abstract]:SLA 3D printer is used to print the same model with different parameters to measure the dimension parameters of the model, and an improved LSSVM model is used to predict the dimension error of the model with different parameters. Designing experiment, using SLA 3D printer to print under this parameter, then measuring and determining the size information and size error of the printed parts. Based on the existing data, an improved LS-SVM model is established to predict the size error of the formed parts under different printing parameters. The results show that the prediction accuracy of the model reaches 92. 6471%. Compared with the original optimization method and BP neural network, the improved LS-SVM has a good effect on the prediction of dimensional error of SLA 3D printing.
【作者單位】： 上海交通大學(xué)機械與動力工程學(xué)院;
【基金】：上海市科委項目(15111102203;16111106102) 上海交通大學(xué)醫(yī)工(理)交叉基金資助(YG2014MS04;YG2015MS09)
【分類號】：TP18;TP334.8
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本文編號：2216718