Soft Sensing and Optimization of Pesticide Waste Incinerator
Three soft sensor models (RBF, SVM, ICA-SVM) are proposed to infer the Chemical Oxygen Demand (COD) of quench water produced from pesticide waste incinerator respectively. An optimization model of COD is further proposed based on the above soft sensor models. Furthermore, chaos genetic algorithm is introduced to solve the optimization model. The procedure is demonstrated and discussed for practical industrial cases, where the mean relative error of the proposed ICA-SVM model is 0.16％ for COD prediction, and mean of COD can decrease from 1140 to 393, by 65.53％, with the proposed optimal soft sensing approach.
YAN Zhengbing LIU Xinggao
Institute of Industrial Control, Department of Control Science & Engineering, Zhejiang University, Hangzhou 310027, China
国际会议
2011 International Symposium on Advanced Control of Industrial Processes(2011工业过程先进控制技术国际研讨会)
杭州
英文
281-286
2011-05-01（万方平台首次上网日期，不代表论文的发表时间）