单光照条件变化的镨/钕元素组分含量软测量

朱建勇; 张旭乾; 杨辉; 陆荣秀

doi:10.11949/j.issn.0438-1157.20180819

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单光照条件变化的镨/钕元素组分含量软测量

过程系统工程 | 更新时间：2026-07-24

- 单光照条件变化的镨/钕元素组分含量软测量
- Soft-sensing of Pr/Nd component content under different single illumination conditions
- 化工学报 2019年70卷第2期页码：780-788
- 作者机构：
  
  1.华东交通大学电气与自动化工程学院，江西南昌 330013
  2.江西省先进控制与优化重点实验室，江西南昌 330013
- 作者简介：
  
  朱建勇（1977—），男，博士，副教授，zhujyemail@163.com
  杨辉（1965—），男，博士，教授，yhshuo@263.net
- 基金信息：
  
  国家自然科学基金地区项目(61733005;61563015);江西省自然科学青年基金重点项目(20171ACB21039);江西省教育厅科技项目(GJJ150552;GJJ160524;GJJ170374)
- DOI：10.11949/j.issn.0438-1157.20180819
  中图分类号： TP 273
- 收稿：2018-07-18，
  
  修回：2018-11-20，
  
  网络首发：2020-06-16，
  
  纸质出版：2019-02-05
- 稿件说明：
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朱建勇, 张旭乾, 杨辉, 陆荣秀. 单光照条件变化的镨/钕元素组分含量软测量[J]. 化工学报, 2019, 70(2): 780-788

ZHU Jianyong, ZHANG Xuqian, YANG Hui, LU Rongxiu. Soft-sensing of Pr/Nd component content under different single illumination conditions[J]. CIESC Journal, 2019, 70(2): 780-788
朱建勇, 张旭乾, 杨辉, 陆荣秀. 单光照条件变化的镨/钕元素组分含量软测量[J]. 化工学报, 2019, 70(2): 780-788 DOI： 10.11949/j.issn.0438-1157.20180819.

ZHU Jianyong, ZHANG Xuqian, YANG Hui, LU Rongxiu. Soft-sensing of Pr/Nd component content under different single illumination conditions[J]. CIESC Journal, 2019, 70(2): 780-788 DOI： 10.11949/j.issn.0438-1157.20180819.

摘要

针对镨/钕稀土萃取工业生产现场光照条件变化导致具有颜色特征的镨/钕组分含量难以准确检测的问题，提出了一种基于单光照条件变化的组分含量软测量方法。首先，采用参数优化的Grey Edge算法，将不同光照条件下的稀土溶液图像校正到标准光照下；然后，以镨/钕溶液图像HSI颜色空间中的H、S、I分量一阶矩为模型的输入变量，利用加权最小二乘支持向量机（WLSSVM）建立组分含量软测量模型；最后采用工业数据对所提方法进行仿真实验，结果表明所提方法在不同光照条件下均能满足稀土萃取过程组分含量检测的准确度和快速性要求。

Abstract

It is known that due to the change of light condition on rare earth extraction industry

makes soft-sensing model for rare earth element content based on the color characteristics of the rare earth solution have larger error. First

the Grey Edge algorithm with parameter optimization is used to correct the image of rare earth solution under different illumination conditions to the standard illumination. Then

the first moment of H

S and I components in the HSI color space of the Pr/Nd solution image is used as a model. The weighted least squares support vector machine (WLSSVM) is used to model the component content. Finally

the simulation experiments of rare earth solution images under different illumination conditions are carried out. The simulation results show that the images of rare earth solutions under different illumination conditions can meet the high-accuracy and rapid requirements of element component content detection in rare earth extraction process.

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