上海大学学报（英文版）
上海大學學報（英文版）
상해대학학보（영문판）
JOURNAL OF SHANGHAI UNIVERSITY (ENGLISH EDITION)
2006年
5期
443-448
,共6页
徐继彭%林柳兰%胡庆夕%方明伦
徐繼彭%林柳蘭%鬍慶夕%方明倫
서계팽%림류란%호경석%방명륜
plasma deposition manufacturing (PDM)%artificial neural network (ANN)%deposit layer%back-propagation
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.
