Soft-Sensing Modeling Method of Vinyl Acetate Polymerization Rate Based on BP Neural Network

摘要：

Providing a soft-sensing modeling method of vinyl acetate (VAC) polymerization rate based on BP neural network. Solving the current problem that the VAC polymerization rate in the polyvinyl alcohol (PVA) producing process is hard to real-time measuring. Using the data samples collected from the scene to train the network. In the network learning process, using the Levenberg-Marquardt optimization algorithm. Finally, testing the network which has completed training. Test result shows that softsensing model of VAC polymerization rate based on BP neural network is accurate and effective.

关键词： Soft-sensing VAC polymerization rate BP network Modeling

作者: Huang Jiangping Tao Huihui Zhu Zhigao

作者单位: East China Jiaotong University, Nanchang, jiangxi, 330013, China

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 2664-2667

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）