[1]黄昕龙、花海燕、陈世辉.FDM表面粗糙度偏最小二乘回归建模研究[J].福建工程学院学报,2020,18(06):524-529.[doi:10.3969/j.issn.1672-4348.2020.06.003]
　HUANG Xinlong,HUA Haiyan,CHEN Shihui.Research on surface roughness modeling for FDM part based on 〖JZ〗partial least squares regression[J].Journal of FuJian University of Technology,2020,18(06):524-529.[doi:10.3969/j.issn.1672-4348.2020.06.003]
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FDM表面粗糙度偏最小二乘回归建模研究()
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《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第18卷
期数:
2020年06期
页码:
524-529
栏目:
出版日期:
2020-12-25

文章信息/Info

Title:
Research on surface roughness modeling for FDM part based on 〖JZ〗partial least squares regression
作者:
黄昕龙、花海燕、陈世辉
福建江夏学院
Author(s):
HUANG Xinlong1;  HUA Haiyan2;  CHEN Shihui
School of Engineering, Fujian Jiangxia University
关键词:
FDM; 粗糙度; 参数三次曲线; 丝宽模型; PLSR
Keywords:
fused deposition modeling (FDM);  surface roughness;  parametric cubic curve;  extruded filament section shape;  (PLSR) partial least squares regression
分类号:
TP391.7
DOI:
10.3969/j.issn.1672-4348.2020.06.003
文献标志码:
A
摘要:
产品的表面质量差严重制约了熔融沉积成型(fused deposition modeling，FDM)工艺的发展，通过粗糙度成型机理构建参数模型是提升FDM 成型件表面质量的重要途径。文章以某FDM 打印设备成型件的水平表面粗糙度为例，通过探讨参数三次曲线与多段直线拟合的丝宽模型，利用粗糙度的几何机理提出了基于3 个主要工艺参数的回归模型，采用样条变换的非线性偏最小二乘回归(partial least squares，PLSR)建立对所选参数的有效预测模型，并对建模中未覆盖的不同打印参数下的实验数据样本进行校验，分析工艺参数对水平表面粗糙度的影响。通过以上研究方法，提高了水平表面粗糙度预测效率，获取了相关的经验知识。
Abstract:
The low surface quality of products seriously affects the development of the fused deposition modeling (FDM) process. It is a very effective way to improve the surface roughness of FDM molded parts by constructing a parameter model through the roughness forming mechanism. The roughness of the horizontal surface in some FDM printing device was taken as an example. Based on the geometric mechanism of roughness, a regression model based on three main process parameters was proposed by researching the profile of extruded filament section shape fitted by the parameter cubic curve and the multi-segment straight line. An effective prediction model for selected parameters was established by the method of nonlinear partial least squares regression (PLSR) based on spline transformation afterwards. In order to verify the model, the experimental data which were not included in the samples of the regression model under different process parameters were tested. The influence of process parameters on the horizontal surface roughness was analyzed. Thus, the efficiency of predicting horizontal surface roughness was improved and relevant experience and knowledge was obtained.

参考文献/References:

[1] ALAFAGHANI A, QATTAWI A, ABLAT M. Design consideration for additive manufacturing: fused deposition modelling[J]. Open Journal of Applied Sciences, 2017, 7(6): 291-318.[2] RAYEGANI F, ONWUBOLU G. Fused deposition modelling (FDM) process parameter prediction and optimization using group method for data handling (GMDH) and differential evolution (DE)[J]. The International Journal of Advanced Manufacturing Technology, 2014, 73(1/2/3/4): 509-519.[3] 龚运息, 陈晨, 夏名祥, 等. FDM 3D打印模型表面阶梯效应的分析[J]. 制造技术与机床, 2016(4): 27-30.[4] 王玉, 陈子谦, 李后起, 等. 增材制造中耦合零件表面粗糙度及支撑面积的建造方向优化[J]. 同济大学学报(自然科学版), 2019, 47(8): 1180-1188.[5] RAJAN J, SUGAVANESWARAN M, PRASHANTHI B, et al. Influence of vapour smoothing process parameters on fused deposition modelling parts surface roughness at different build orientation[J]. Materials Today: Proceedings, 2020, 22: 2772-2778.[6] LALEGANI M, ARIFFIN M, ISMAIL M. Effects of CNC machining on surface roughness in fused deposition modelling (FDM) products[J]. Materials, 2020, 13(11): 2608.[7] PRAMANIK D, MANDAL A, KUAR A. An experimental investigation on improvement of surface roughness of ABS on fused deposition modelling process[J]. Materials Today: Proceedings, 2020, 26: 860-863.[8] 潘鑫龙, 陈元枝, 邓艳. FDM的出丝模型完善和补偿方法优化研究[J]. 精密制造与自动化, 2015(1): 31-34.[9] 刘植, 李晨, 谢进, 等. 一类双参数三次Bézier曲线的形状分析[J]. 图学学报, 2015, 36(3): 356-362.[10] 王惠文, 吴载斌, 孟洁. 偏最小二乘回归的线性与非线性方法[M]. 北京: 国防工业出版社, 2006: 191-215.

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更新日期/Last Update: 2020-12-25