Soft measurement for component content based on adaptive model of Pr/Nd color features  

基于镨/钕颜色特征自适应模型的组分含量软测量（英文）

作　　者：陆荣秀 杨辉 

机构地区：[1]School of Mechanical & Electrical Engineering,Nanchang University [2]School of Electrical and Electronic Engineering,East China Jiaotong University [3]Key Laboratory of Advanced Control & Optimization of Jiangxi Province

出　　处：《Chinese Journal of Chemical Engineering》2015年第12期1981-1986,共6页中国化学工程学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China(51174091,61364013,61164013);Earlier Research Project of the State Key Development Program for Basic Research of China(2014CB360502)

摘　　要：For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.For measurement of component content in the extraction and separation process of praseodymium/neodymium（Pr/Nd）, a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine（LSSVM） model for Nd（Pr） content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.

关 键 词：Pr/Nd extraction Color feature Component content Adaptive iterative least squares support vector machine Real-time correction 

分 类 号：TF845[冶金工程—有色金属冶金]