Research on the Fouling Prediction of Heat exchanger Based on Support Vector Machine

摘要：

The development of prediction researching on heat exchanger fouling in recent years is reviewed The application of Support Vector Machine based on Statistical Learning Theory to predict heat exchanger fouling is reported in this paper. We construct a six inputs and one-output network according to the fouling monitor principle and parameters, the modeling of the SVM programmed with MATLAB, and trained with VSVR algorithm, all training data came from the Automatic Dynamic Simulator of Fouling and input the network after normalized processing and reclassification. Simulations show that the relative error of fouling prediction is less than 0.3 percent, and better than the RBF. SVM can be used to predict heat exchanger fouling, and has perfect prediction precision. The prediction model based on SVM offers anther method for the research of heat exchanger fouling.

作者: SUN Lingfang ZHANG Yingying ZHENG Xinpeng YANG Shanrang QIN Yukun

作者单位: School of Automation Engineering, Northeast Dianli University, Jilin City, China, 132012 Power Engin School of Automation Engineering, Northeast Dianli University, Jilin City, China, 132012 Power Engineering and Engineering Thermophysics Postdoctoral Workstation, Harbin Institute of Techno

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 240-244

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）