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Intelligent pre-selection based on spodumene UV fluorescence and improved MT-YOLOv11 algorithm to promote the development of smart green mining:From lab to industrial applications

Tianyou Yu Yimin Zhu Jie Liu Yuexin Han Yanjun Li

Green and Smart Mining Engineering2026，Vol.3Issue(2)：P.194-208,15.

Green and Smart Mining Engineering2026，Vol.3Issue(2)：P.194-208,15.DOI:10.1016/j.gsme.2025.12.004

Intelligent pre-selection based on spodumene UV fluorescence and improved MT-YOLOv11 algorithm to promote the development of smart green mining:From lab to industrial applications

Tianyou Yu ¹Yimin Zhu ¹Jie Liu ¹Yuexin Han ¹Yanjun Li¹

作者信息

1. School of Resources and Civil Engineering,Northeastern University,Shenyang 110819,China National-local Joint Engineering Research Center of High-efficient Exploitation Technology for Refractory Iron Ore Resources,Shenyang 110819,China
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摘要

关键词

Spodumene/MT-YOLOv11 deep-learning algorithm/Lithium resource/Ultraviolet fluorescence pre-selection/Concentrate grade/Tailings rejection/Intelligent green mining

分类

矿业与冶金

引用本文复制引用

Tianyou Yu,Yimin Zhu,Jie Liu,Yuexin Han,Yanjun Li..Intelligent pre-selection based on spodumene UV fluorescence and improved MT-YOLOv11 algorithm to promote the development of smart green mining:From lab to industrial applications[J].Green and Smart Mining Engineering,2026,3(2):P.194-208,15.

基金项目

supported by the National Natural Science Foundation of China(No.2021YFC2903201),which is part of the 14th Five-Year Plan for National Key R&D Program. （No.2021YFC2903201）

Green and Smart Mining Engineering

ISSN：2950-5550

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