世界有色金属Issue(4)：204-206,3.
基于深度学习的矿物堆浸在线监测技术
Mineral heap leaching online monitoring technology based on deep learning
尚文波1
作者信息
- 1. 内蒙古太平矿业有限公司,内蒙古 巴彦淖尔 015300
- 折叠
摘要
Abstract
This study proposes an online monitoring technology for mineral heap leaching based on deep learning,aiming to solve the problems of low efficiency and poor real-time performance of traditional monitoring methods.This technology includes three key steps:multi-source heterogeneous data acquisition and preprocessing,LSTM and CNN hybrid deep learning model design,and visual online monitoring and early warning.Through field comparative experiments at a large copper mine,the results show that this technology is significantly superior to traditional methods in terms of leaching rate prediction accuracy,metal recovery rate,anomaly detection rate,and production efficiency.The research results provide a new technological path for intelligent control of mineral heap leaching processes.关键词
深度学习/矿物堆浸/在线监测/智能预警Key words
deep learning/Mineral heap leaching/Online monitoring/Intelligent warning分类
矿业与冶金引用本文复制引用
尚文波..基于深度学习的矿物堆浸在线监测技术[J].世界有色金属,2025,(4):204-206,3.
