| 基于人工神经网络的等离子熔积层形貌试验研究 |
| |
| 引用本文： | 徐继彭,林柳兰,胡庆夕,方明伦.基于人工神经网络的等离子熔积层形貌试验研究[J].上海大学学报(英文版),2006,10(5):443-448. |
| |
| 作者姓名： | 徐继彭 林柳兰 胡庆夕 方明伦 |
| |
| 作者单位： | Rapid Manufacturing Engineering Center Shanghai University Shanghai 200444 P.R. China，Rapid Manufacturing Engineering Center Shanghai University Shanghai 200444 P.R. China，Rapid Manufacturing Engineering Center Shanghai University Shanghai 200444 P.R. China，Rapid Manufacturing Engineering Center Shanghai University Shanghai 200444 P.R. China |
| |
| 基金项目： | 国家自然科学基金;国家高技术研究发展计划(863计划) |
| |
| 摘 要： | 1IntroductionPlasma deposition manufacturing(PDM)is a newlydeveloped direct metal fabrication process based onplasma transferred arc surfacing1],as shown in Fig.1.Unlike most existing rapid prototyping techn-ologies,this technique is characterized by sup…
|
| 关 键 词： | 等离子沉积 人工神经网络 制造业 沉积层 后向传播 |
| 文章编号： | 1007-6417（2006）05-0443-06 |
| 收稿时间： | 2004-06-05 |
| 修稿时间： | 2005-03-21 |
Experiments and shape prediction of plasma deposit layer using artificial neural network |
| |
| Ji-peng Xu Ph. D.,Liu-lan Lin,Qing-xi Hu,Ming-lun Fang.Experiments and shape prediction of plasma deposit layer using artificial neural network[J].Journal of Shanghai University(English Edition),2006,10(5):443-448. |
| |
| Authors: | Ji-peng Xu Ph D Liu-lan Lin Qing-xi Hu Ming-lun Fang |
| |
| Abstract: | Plasma surfacing is an important enabling technology in high-performance coating applications. Recently, it is applied to rapid prototyping/tooling to reduce development time and manufacturing cost for the development of new products. However, this technology is in its infancy, it is essential to understand clearly how process variables relate to deposit microstructure and properties for plasma deposition manufacturing process control. In this paper, layer appearance of single surfacing under different parameters such as plasma current, voltage, powder feedrate and travel speed is studied. Back-propagation neural networks are used to associate the depositing process variables with the features of the deposit layer shape. These networks can be effectively implemented to estimate the layer shape. The results indicate that neural networks can yield fairly accurate results and can be used as a practical tool in plasma deposition manufacturing process. |
| |
| Keywords: | plasma deposition manufacturing (PDM) artificial neural network (ANN) deposit layer back-propagation |
| 本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录！ |
