Bottom Blowing Furnace Copper Smelting Process Research And Application Of Intelligent Control Technology

Copper is the second largest non-ferrous metals because of its outstanding features which is widely used in every trade. "New process of oxygen bottom blowing for copper converting" has some characteristics about strong adaptability of raw material and low oxygen consumption. This process can be achieved without carbon copper matte melting and Carbon emissions. It is also in line with the development of low-carbon world economy overall direction.Production practice shows that in the bottom blowing furnace smelting process, the matte grade, the Fe/SiO2 and the matte temperature, called the three technician parameters that are the overall evaluation indexes. It has such characteristics like asmultivariate, nonlinearity, strong coupling, large inertia, time varying and uncertainty. Owing to the manual measurements of the three parameters lag behind production process more than one hour, it’s difficult for us to modify the model by feedback timely. To solve this problem, this paper takes a smelting factory in Shandong province as research object, makes studies to build the intelligent integrated model of the bottom blowing furnace smelting process in the three technician parameters.This paper establishes a mechanism model based on materiel balance and engine balance by analyzing the mode. Because of the mechanism’s complexity, the suppositions and the simplifications during modeling, the precision of the mechanism model couldn’t meet the demant of practical. Therefore, based on industrial running data, a neural network model for the forecast of the three parameters is established, whose inputs are the direct influencing factors of the three parameters and the outputs of the three parameters. The neural network model describes the relationship via training data samples quite well but with low generalization ability. Thus, taking advantage of the two models an intelligent integrated model is proposed.This model combines three process parameters of forecasting model with neural network forecasting combination model which puts forward an intelligent integrated prediction model. The integrated model is tested by industrial practical data, and the results show that the model is feasible and high precision.Finally, we need to make control strategy of bottom blowing furnace smelting process, combined with the factory’s practical situation. Monitor and control system of furnace bottom blowing is developed on the base of it. Practical application indicates that the control system is feasible, and with good effect.