摘要
这是一篇矿业工程领域的论文。选矿厂节能降耗需求强烈,球磨机负荷检测是实现磨机控制、优化磨矿流程的关键技术。本文归纳了近年来磨机负荷的检测方法:压差法、磨音法、振动法、功率法、超声波法、基于多源信号融合的间接检测方法;总结并分析了磨机负荷的建模方法。未来一段时间内,多源信息融合的间接法将仍是检测磨机负荷的主要方法,改进神经网络为基础的建模方法、新型在线检测方法以及建立高效精准的负荷检测模型是磨机负荷检测的主要发展方向。
This is a paper in the field of mining engineering.With the increasing demands for energy conservation and consumption reduction in mineral processing plants,ball mill load measurement is the key technology to realize mill control and optimize the grinding process.This paper summarizes the measurement methods of mill load in the recent years:differential pressure method,grinding sound method,vibration method,power method,ultrasonic method,indirect detection method based on multi-source signal fusion.Moreover,it summarizes and analyzes the mill load modeling methods that have emerged inrecent years.In the future,the indirect methods of multi-source information fusion will still be the main methods to detect mill load,modeling methods based on improvement of neural network and new online detection methods,as well as the establishment of efficient and accurate load detection models will be the main development direction of mill load detection.
作者
王廷
赵建军
陶乐
田蕊
邹文杰
Wang Ting;Zhao Jianjun;Tao Le;Tian Rui;Zou Wenjie(School of Civil and Resource Engineering,University of Science and Technology Beijing,Beijing,China;State Key Laboratory of Process Automation in Mining&Metallurgy,Beijing,China)
出处
《矿产综合利用》
CAS
北大核心
2023年第3期107-111,118,共6页
Multipurpose Utilization of Mineral Resources
基金
矿冶过程自动控制技术国家重点实验室开放基金(BGRIMM-KZSKL-2019-02)
中央高校基本科研业务费(FRF-IP-20-03)。
关键词
磨机负荷
软测量
建模
神经网络
在线检测
矿业工程
Mill load
Soft measurement
Modeling
Neural network
Online detection
Mining engineering
