Neural Networks Model of Polypropylene Surface Modification by Air Plasma

摘要：

In order to understand the relationship between discharge plasma parameters and material surface properties, neural networks model were constructed.The sample data are yielded from many experiments for polypropylene surface modification.The experiments were arranged according to uniform design method and conducted in home-made dielectric barrier discharge (DBD)system.Here,Voltage,air gap and discharge time were input parameters of the model.The output parameter was polypropylene surface water contact angle.Back- propagation algorithm was used to train neural networks model. Model evaluation was carried out by simulation and error analysis.The optimized model was applied to predict,and the results are in agreement with practical situation.The obtained neural networks model has excellent predictive capability.

关键词： Neural Networks Modeling Polypropylene Surface Modification

作者: Changquan Wang Xuewu Wang Xiangning He

作者单位: College of Mechanical and Electrical Engineering,Xuzhou Normal University,Xuzhou,Jiangsu Province,22 Research Institute of Automation,East China University of Science and Technology,Shanghai,200237 Chi College of Electrical Engineering,Zhejiang University,Hangzhou,Zhejiang Province,310027 China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）