Heat state judgment for calcium carbide furnaces based on heat index calculation and furnace temperature prediction

In view of the importance of heat state judgment for calcium carbide smelting, the concept of furnace heat index was presented by analyzing the smelting features. A calculation model of furnace heat index was established based on the two-stage thermal equilibrium, and a prediction model of hot calcium carbide temperature was constructed by using a BP neural network. Both the models can effectively judge the furnace heat state. Simulation results show that there is a significant linear correlation between hot calcium carbide temperature and heat surplus, and it is feasible to consider furnace heat index as a heat state's sign. The hit rate to hot calcium carbide temperature predicted by the prediction model reaches 86.7%.