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铜转炉吹炼炉口图像智能监测及辅助分析系统

张红哲 徐子昂 刘光远 郭廷谦 张冰洁

铜业工程Issue(2):1-7,7.
铜业工程Issue(2):1-7,7.DOI:10.3969/j.issn.1009-3842.2024.02.001

铜转炉吹炼炉口图像智能监测及辅助分析系统

Image Intelligent Monitoring and Auxiliary Analysis System of Copper Convert-er Blowing Furnace

张红哲 1徐子昂 2刘光远 2郭廷谦 1张冰洁1

作者信息

  • 1. 中国恩菲工程技术有限公司,北京 100038
  • 2. 西北工业大学航天学院,陕西 西安 710072
  • 折叠

摘要

Abstract

The traditional copper smelting process of converter depends very much on personal experience.By manually observing the flame of the furnace to judge the temperature in the furnace body and the end point of slag making and copper making,there are major safety and environmental protection problems.At the same time,the grade of copper in the corresponding stage is not guaranteed and the furnace body is easily damaged.With the improvement of environmental protection and intrinsic safety indicators,companies began to turn to closed window blowing.In order to meet the requirements of green and safety,based on the results of flame analysis and vari-ous factors involved in the blowing process,an intelligent monitoring system for the image of the converter mouth was designed to real-ize the intelligent monitoring of the converter mouth flame.On this basis,through the analysis of different stages of the furnace flame image,the color feature calculation method based on adaptive exposure threshold was designed,which could preprocess the image and extract the key features of the predictable end time,so as to solve the key problem that the sensor exposure parameters affect the image features.Finally,a prediction model of the end point time based on deep neural network was designed.The experimental results showed that the prediction errors of the end point in the first slag making stage,the second slag making stage and the copper making stage were 0.74,0.83 and 1.4 min,respectively,and the success rate was higher than 91.4%,which showed the effectiveness of the system de-signed in this paper.

关键词

转炉吹炼/炉口火焰图像/辅助炼铜/深度学习/终点预测

Key words

bessemer blowing/furnace flame image/auxiliary copper smelting/deep learning/endpoint prediction

分类

矿业与冶金

引用本文复制引用

张红哲,徐子昂,刘光远,郭廷谦,张冰洁..铜转炉吹炼炉口图像智能监测及辅助分析系统[J].铜业工程,2024,(2):1-7,7.

基金项目

北京市自然科学基金项目(8234060)资助 (8234060)

铜业工程

1009-3842

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