Prediction of Fiber Diameter on Spunbonding Fabric Using Neural Network and Physical Model

摘要：

Two modeling methods (physical model, and artificial neural network model) are developed to predict the fiber diameter of spunbonding nonwovens. By analyzing the results of two models, the effects of process parameters on fiber diameter can be predicted. The results show the artificial neural network model can yield more accurate and stable predictions than the physical model, and it can yield reasonably good prediction results and provide insight into the relationship between process parameters and fiber diameter. At the same time, the experimental results and the corresponding analysis also show that the neural network is an efficient technique for the quality prediction.

关键词： artificial neural network model physical model spunbonding nonwoven fiber diameter process parameter

作者: Zhao Bo

作者单位: College of Textiles Zhong yuan University of Technology Henan, Zhengzhou, 450007, China

会议类型: 国际会议

会议名称: 2010 International Conference on Educational and Network Technology(2010教育与网络技术国际会议 ICENT 2010)

会议地点: 秦皇岛

会议语种:英文

页码: 389-392

在线出版日期: 2010-06-25（万方平台首次上网日期，不代表论文的发表时间）