Soft-sensing of Pr/Nd component content under different single illumination conditions

ZHU Jianyong; ZHANG Xuqian; YANG Hui; LU Rongxiu

doi:10.11949/j.issn.0438-1157.20180819

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Soft-sensing of Pr/Nd component content under different single illumination conditions

Process system engineering | 更新时间：2026-07-24

- Soft-sensing of Pr/Nd component content under different single illumination conditions
- CIESC Journal Vol. 70, Issue 2, Pages: 780-788(2019)
- 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：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20180819
  CLC： TP 273
- Received：18 July 2018，
  
  Revised：2018-11-20，
  
  Online First：16 June 2020，
  
  Published：05 February 2019
- 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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references

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