铅基固废协同熔炼过程在线智能优化控制
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作者:
作者单位:

1.中国恩菲工程技术有限公司, 北京 100038 ; 2.浙江大学 控制科学与工程学院, 浙江 杭州 310027

作者简介:

张哲铠(1989—),男,汉族,浙江嘉兴人,博士,工程师,研究方向为有色冶金工艺流程计算、智能控制系统。

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中图分类号:

TF812;TF355

基金项目:

国家重点研发计划“协同熔炼过程自适应在线智能优化控制系统”(2019YFC1907305)


Online intelligent optimization control for the lead-based solid waste synergistic smelting process
Author:
Affiliation:

1.China ENFI Engineering Corporation, Beijing 100038 , China ; 2.College of Control Science and Engineering, Zhejiang University, Hangzhou 310027 , China

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    摘要:

    铅基固废是生产端和消费端产生的常见固体废物,具有很强的污染性,其绿色处理技术是实现含铅废物污染防治的关键环节。双底吹炼铅工艺协同处理铅基固废是一种经济合理的铅基固废处理方式,相对于传统矿铅冶炼生产操作更为复杂,为确保生产状况处于稳定、经济的状态,对工艺控制系统有了更高要求。中国恩菲工程技术有限公司研发了一套铅基固废协同熔炼过程在线智能优化控制系统,整个系统由在线优化控制系统、智能预警与高效监控系统和系统数据库集成,主要实现以下功能:①针对铅基固废协同熔炼过程自动化水平不高的问题,基于冶炼过程机理与生产运行大数据,应用计算机建模和神经网络方法建立了冶炼过程关键参数预测模型,开发了一套铅基固废协同熔炼在线优化控制系统;②以车间实景模型为载体,建立了铅基固废协同熔炼智能预警与高效监控系统,实现了工业信号、场景及流程的数字化与可视化;③控制系统集成了现场相关软硬件,详细展示各模块间的数据交互与协同运行情况,形成了智能、高效、安全的协同熔炼车间。

    Abstract:

    Lead-based solid waste is a common waste produced at both production and consumption ends, and has a strong pollution effect. Its green treatment technology is a key link to achieve the prevention of lead containing waste pollution. The collaborative treatment of lead based solid waste by double-bottom blowing process is an economical and reasonable way to treat lead based solid waste. Comparing with the traditional ore lead smelting, its production operation is more complex for co-processing lead solid waste. In order to ensure its production status in a stable and economic state, there are higher requirements for its process control system. A set of online intelligent optimization control system for lead-based solid waste collaborative smelting process has been developed by China ENFI Engineering Corporation. The whole system is integrated of online optimization control system, intelligent early warning and efficient monitoring system and system database, which mainly realizes the following functions : ① In response to the low level of automation in treatment process, based on smelting process mechanism and big data of production operation, a prediction model of key parameters of smelting process is established by applying computer modeling and neural network method, and a set of online optimization control system for lead-based solid waste collaborative smelting is developed; ② Using the workshop reality model as the carrier, an intelligent early warning and efficient monitoring system for lead-based solid waste synergistic smelting is established to realize the digitalization and visualization of industrial signals, scenes and processes; ③ The control system integrates the relevant hardware and software on site, and displays the data interaction and collaborative operation between the modules in detail, forming an intelligent, efficient and safe synergistic smelting workshop.

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引用本文

张哲铠,楚金旺,郝亮钧,等. 铅基固废协同熔炼过程在线智能优化控制[J].中国有色冶金,2024,53(4):65-74.

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  • 收稿日期:2023-12-29
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  • 在线发布日期: 2025-12-21
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