Affiliation:
1. College of Rare Earth, Jiangxi University of Science and Technology, 86 Hongqi Road, Ganzhou 341000, China
2. College of Chemistry and Chemical Engineering, Jiangxi University of Science and Technology, 86 Hongqi Road, Ganzhou 341000, China
3. School of Information Engineering, Jiangxi University of Science and Technology, 86 Hongqi Road, Ganzhou 341000, China
Abstract
The current hardware equipment used to detect the content of each element component in the rare earth extraction process has a complex structure and high maintenance cost. A modeling method for the soft measurement of rare earth multi-element component content is proposed to address this issue. This method uses the Multi-LightVGG multi-tasking learning model and the Multi Gradient Descent Algorithm based on Optimized Upper Bound (MGDA-OUB) to optimize the model for each prediction task and find the Pareto optimal solution. After conducting several experiments, the Multi-LightVGG model loaded with MGDA-OUB has lower MRE, RMSE for Pr, Nd prediction, and MAX(|error|) for Nd prediction than the Multi-LightVGG model without MGDA-OUB by 0.3778%, 0.5208%, 0.0015, 0.0015, and 0.1985%, respectively; and the MRE and RMSE of the Multi-LightVGG model for Pr and Nd prediction under the same optimization conditions are lower than those of Multi-ResNet18 by 0.3297%, 0.5423%, 0.0019, and 0.002, respectively, thus indicating that MGDA-OUB can effectively solve multiple task-specific Pareto solutions to avoid possible conflicts between specific tasks, while the Multi-LightVGG model, compared to the Multi-Resnet18 model, has a backbone network that can effectively capture the abstract representations in the images of the rare earth-extraction mixed solution, which in turn improves the prediction accuracy of the content of each elemental component.
Funder
National Natural Science Foundation
Distinguished Professor Program of Jinggang Scholars in institutions of higher learning
Education Department of Jiangxi Province
Subject
Geology,Geotechnical Engineering and Engineering Geology
Reference34 articles.
1. A review of competitive advantage theory applied to the global rare earth industry transition;Thibeault;Resour. Policy,2023
2. Extraction and separation of heavy rare earth elements: A review;Liu;Sep. Purif. Technol.,2021
3. Global rare earth resources and scenarios of future rare earth industry;Chen;J. Rare Earths,2011
4. Current status and prospect of the development of extraction, separation and purification technology of rare earth elements;Feng;China J. Rare Earths,2021
5. Research status and prospect of rare earth element separation and purification technology;Xu;Environ. Pollut. Prev.,2019