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选矿工业大数据关键装备的研发与工程化实践——以浮选流体动力学特征阈值传感器系统为例

Investigate and Engineering Practice of Key Equipment for Big Data in Mineral Processing Industry——Taking the Flotation Fluid Dynamics Characteristic Threshold Sensor System as an Example
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摘要 为实现矿物加工领域高度网络化、大数据化、协同工作、分布式服务为特征的选矿工业4.0的到来,将一次检测仪表中心(中央)控制室系统和大数据专家智能系统连接,形成“一体化”的选矿信息化与智能化系统,实现矿物加工的安全、高效、绿色、可持续发展的必由之路。中铝科学技术研究院等研发了新一代浮选流体动力学特征阈值传感器系统,通过多维度测量浮选设备以及浮选回路的核心参数,对采集到的数据进行建模分析,形成优化方案,并生成自动化操作指令,推动选矿技术经济指标实现优化提升。在普朗铜矿的成功应用,提升了金属回收率1~5个百分点,提高了精矿品位0.5~3个百分点,浮选生产性成本降低5%~10%,选矿人工成本下降20%~40%,选矿厂年增效4440万元。该项技术和产品成功填补了国内矿业领域的空白,为实现行业工业4.0做出了贡献。 In order to realize the arrival of mineral processing industry 4.0 with high network,big da-ta,collaborative work and distributed service in the field of mineral processing,the one detection instru-ment center(central)control room system is connected with the big data expert intelligent system to form an“integration”beneficiation information and intelligent system,so as to realize the safe,efficient,green and sustainable development of mineral processing.China Aluminum Research Institute of Science and Technol-ogy Co.,Ltd.has developed a new generation of flotation fluid dynamics characteristic threshold sensor sys-tem.Through multi-dimensional measurement of the core parameters of flotation equipment and flotation cir-cuit,the collected data are modeled and analyzed to form an optimization scheme and generate automatic op-eration instructions,so as to promote the optimization and improvement of technical and economic indica-tors of mineral processing.It has been successfully applied in Pulang Copper Mine,the metal recovery rate was raised by 1~5 percentage points,the concentrate grade was raised by 0.5~3 percentage points,the production cost of flotation was reduced by 5%~10%,the labor cost of beneficiation was reduced by 20%~40%,and the annual efficiency of the ore dressing plant was raised by 44.4 million yuan.The technology and products successfully fill the gaps in the domestic mining field and contribute to the realization of industry 4.0.
作者 管孝强 谭志勇 李海斌 周仕庆 李腾飞 王超 张炜 GUAN Xiaoqiang;TAN Zhiyong;LI Haibin;ZHOU Shiqing;LI Tengfei;WANG Chao;ZHANG Wei(China Aluminum Research Institute of Science and Technology Co.,Ltd.;Beijing Branch of Kunming Metallurgy Research Institute Co.,Ltd.;China Aluminum Intelligent Tongchuang Technology(Yunnan)Co.,Ltd.;Yunnan Copper Co.,Ltd.)
出处 《现代矿业》 CAS 2023年第8期148-150,158,共4页 Modern Mining
关键词 AI选矿 工业4.0 检测仪表 中央控制室系统 大数据智能化仪器 AI mineral processing industry 4.0 detection instrument central control room system big data intelligent instrument
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