介绍了基于遗传算法的炉缸侵蚀结厚模型的研发概况和主要模型功能,并结合某4 000m3和5 000m3大型高炉长期在线运行数据,着重对模型计算和侵蚀结厚监测模拟效果进行了验证。当炉底中心温度不断升高时,炉底侵蚀加剧,剩余厚度减小;当温度不断降低时,炉缸中心区域渣铁流动性差,炉底易形成导热系数较低的粘结物。模型计算结果与实际的温度变化趋势及炉缸活跃性表现相一致。 This paper introduced the research and development of boiler hearth erosion knot thickness model based on genetic algorithm and the main model functions. Combined with long-term online operation data of 4 000m3 and 5 000m3 large blast furnaces, the simulation results of model calculation and erosion knot thickness monitoring were verified. When the center temperature of the hearth rises continuously, the bottom erosion intensifies and the remaining thickness decreases. When the temperature decreases, the flow of slag and iron in the hearth of the hearth is poor, and the bottom of the hearth tends to form a bond with a low thermal conductivity. The results of the model are consistent with the actual temperature trend and the performance of the hearth.