一种铁矿石合理含水量的评估系统  

An Evaluation System for Reasonable Water Content of Iron Ore

作　　者：岑仲迪[1] 杨东彪[2] 黄剑[1] 徐爱民[1] 

机构地区：[1]浙江万里学院,浙江宁波315100 [2]江西理工大学,江西赣州341000

出　　处：《大众科技》2021年第11期4-6,10,共4页Popular Science & Technology

基　　金：浙江省基础公益研究计划项目(LGF19A010001)。

摘　　要：文章研发了一种铁矿石合理含水量的评估系统,包含品种识别模块、粒径测定模块、数据存储模块、数据调用模块、神经网络模块和结果输出模块。神经网络模块是该系统的核心,其利用人工神经网络技术具有较好的非线性拟合能力,来构建铁矿石的饱和吸附水量与温度、湿度、粒径等影响因素之间相互关系的神经网络模型。该评估系统易于操作,只需扫描待评估铁矿石即可快速获得其在发运港自然条件下的铁矿石合理含水量的范围。In this paper,an evaluation system for reasonable water content of iron ore is developed,including variety identification module,particle size measurement module,data storage module,data transfer module,neural network module and result output module.The neural network module is the core of the system.It uses the artificial neural network technology with good nonlinear fitting ability to construct the neural network model of the relationship between the saturated adsorption water amount of iron ore and the influencing factors such as temperature,humidity and particle size.The evaluation system is easy to operate.It can quickly obtain the range of reasonable water content of iron ore under the natural conditions of the shipping port by scanning the iron ore to be evaluated.

关 键 词：铁矿石 含水量 评估系统 神经网络 

分 类 号：TF52[冶金工程—钢铁冶金]