针对选择性激光烧结成型件变形大、精度较低的问题,将神经网络方法应用于选择性激光烧结(SLS)加工工艺的研究.根据SLS加工工艺的特点,研究的工艺参数包括:层厚、扫描间距、激光功率、扫描速度、环境温度、层与层之间的加工时间间隔和扫描方式.建立了SLS加工工艺参数与加工变形、收缩率之间的神经网络预测模型.实验结果与神经网络模型计算结果十分吻合,说明该神经网络模型能定量地反映出工艺参数与加工材料变形、收缩率之间的关系.
参考文献
| [1] | 孙玉文,贾振元,王越超,刘伟军.基于自由曲面点云的快速原型制作技术研究[J].机械工程学报,2003(01):56-59,83. |
| [2] | Maekawa K.Three-dimensional powder fabrication by laser sintering[A].西安:陕西科学技术出版社,2002 |
| [3] | McMains S;Smith J;Wang Jian-lin.Layered manufacturing of thin-walled parts[A].Bartimore, Maryland: ASME,2000 |
| [4] | Hui S M;Choi K H;Hee S et al.Determination of fabrication orientation and packing in SLS process[J].Journal of Materials Processing Technology,2001,112:236-243. |
| [5] | Pham D T;Dimov S;Lacan F .Selective laser sintering:applications and technological capabilities[J].Pron Instn Mech Engrs B,1999,213B:435-450. |
| [6] | Leong K F;Phua K K S;Chua C K et al.Fabrication of porous polymeric matrix delivery devices using the selective laser sintering technique[J].Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine,2001,215H:191-202. |
| [7] | McMains S;Smith J;Sequin C.The Evolution of a layered manufacturing interchange format[A].Montreal, Quebec, Canada:ASME,2002 |
| [8] | Gabriel Bugeda;Miguel Cervera;Guillermo Lombera .Numerical prediction of temperature and density distributions in selective laser sintering processes[J].Rapid prototyping journal,1999(1):21-26. |
| [9] | 李湘生,韩明,史玉升,黄树槐.SLS成形件的收缩模型和翘曲模型[J].中国机械工程,2001(08):887-889. |
| [10] | 吴传保,刘承美,史玉升,黎步松.高分子材料选区激光烧结翘曲的研究[J].华中科技大学学报(自然科学版),2002(08):107-109. |
| [11] | 杜建红,白培康,程军.选择性激光烧结过程温度场数值模拟[J].华北工学院学报,2000(01):30-32. |
| [12] | Williams J D;Decard C R .Advances in modeling the effects of selected parameters on the SLS process[J].Rapid Prototyping Journal,1998,4(02):90-96. |
| [13] | Ian G;Shi D .Material properties and fabrication parameters in selective laser sintering process[J].Rapid Prototyping Journal,1997,3(04):129-135. |
| [14] | Junghui Chen;Yuezhi Yea .Neural Network-Based Predictive Control for Multivariable Processes[J].Chemical Engineering Communications,2002(7):865-894. |
| [15] | 吕冬,丁柯,何丹农,张永清,阮雪榆,彭大暑,江勇.基于神经网络的拉深力智能化预测系统[J].中国有色金属学报,2000(03):420. |
| [16] | 陈沅江,潘长良,曹平,王文星.基于人工神经网络的岩土流变本构模型辨识[J].中国有色金属学报,2002(05):1027-1034. |
| [17] | Pang T H;Guertin M D;Nguyen H D.Accuracy of stereolithography parts: mechanism and modes of distortion for a ' Letter-H ' diagnostic part[A].Dearborn:Univ Texas,1995 |
| [18] | Hornik K;Stinchcombe M;White H .Multiplayer feedforward networks are universal approximators[J].Neural Networks,1989,2:25-36. |
| [19] | Lee S H;Park W S;Cho H S et al.A neural network approach to modeling and analysis of stereolithography process[J].Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture,2001,215B:1719-1733. |
| [20] | 张连洪,朱克珊,吴华杰.分层实体制造快速成形工艺参数的人工神经网络预测[J].中国机械工程,1999(12):1347. |
上一张
下一张
上一张
下一张
计量
- 下载量()
- 访问量()
文章评分
- 您的评分：
-
10%
-
20%
-
30%
-
40%
-
50%