Image Intelligent Monitoring and Auxiliary Analysis System of Copper Convert-er Blowing Furnace
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.
国家科技期刊平台
NSTL
万方数据
