高炉煤气利用率预测模型

通过融合大数据技术与冶金机理，建立高炉煤气利用率智能预测及优化模型，操作人员可根据模型预测数据进行炉温调剂操作，保持炉温的稳定和铁水质量的稳定；当煤气利用率数据未达到设置目标时模型同步自动反馈合理的解决方案，操作人员可根据模型提出的优化建议进行优化调整，实现高炉煤气利用率的快速改善，从而降低燃料消耗成本。

By integrating big data technologies with metallurgical mechanisms, an intelligent prediction and optimization model for blast furnace gas utilization rate is developed. Operators can adjust the blast furnace temperature based on the model's predicted data to maintain stable furnace temperature and consistent hot metal quality. When the actual gas utilization rate fails to meet the preset targets, the model will synchronously and automatically provide reasonable solutions. Operators can then carry out targeted optimization adjustments according to the model's recommendations, achieving rapid improvement of the blast furnace gas utilization rate and thereby reducing fuel consumption costs.

搜集汇总

背景与挑战

背景概述

该数据集提供了一个高炉煤气利用率预测模型，它融合大数据技术与冶金机理，实现智能预测和优化功能。模型能够指导操作人员进行炉温调剂以保持稳定，并在煤气利用率未达标时自动反馈解决方案，帮助快速改善利用率并降低燃料消耗成本。