| With the introduction of "integration technology of high efficiency and low cost clean steel production platform" and "intelligent manufacturing technology" of the steel making process, the process management and control in the dynamic operation of steelmaking plant is paid more and more attention. However, systematic researches on the basic parameters (mass flow, temperature and time) of the dynamic operation process in steelmaking plant are still in the early stage. Studies on the control precision of the basic parameters are in the blank stage. The basic parameters of the dynamic operation process in Shougang Qian’an Iron & Steel Co. Ltd No.2 Steelmaking Plant were analyzed. The control of mass flow, molten steel temperature and time, and energy saving potential under precise control was investigated.The major parameters and control status in the converter process, refining, continuous casting, ladle turnover and transport processes in Shougang Qian’an Iron & Steel Co. Ltd No.2 Steelmaking Plant were analyzed. The relationship among molten steel temperature drop, material consumption and time in RH refining,210t LF refining and transport processes was explored. Through the analysis of the present control status of mass flow, it was seen that less slag smelting was achieved in converter smelting process. The oxygen consumption and utilization was relatively stable, but loss of Fe per ton of steel was large. The strategy of dynamic adjustment of the addition amount of smelting auxiliary materials according to specific raw material conditions of each heat was proposed. Calculation result of the production data showed loss of Fe per ton of steel decreased 4kg/t steel.The management and control of molten steel temperature of each process node was investigated respectively, including molten steel temperature predetermination and prediction. Predetermined molten steel temperature was the controlling temperature of each process node obtained by dynamically adjusting the temperature schedule, taking into account the continuous casting heats, time factor of each process and the transport processes, and the ladle state. Molten steel temperature prediction was predicting the molten steel temperature of the next process node based on the previous one, therefore realizing molten steel temperature prediction for the whole process. Considering the characteristics of RH and 210t LF refining, optimized Case-Based Reasoning (CBR) method to predict molten steel temperature was proposed. The method could be applied to other sections and then the molten steel temperature prediction for the whole process could be realized. Division and optimization measure of case base was proposed to improve the prediction accuracy and operation efficiency with consideration of the mass accumulated production data in RH refining. Testing results showed that the prediction accuracy applying CBR based on divided case base was apparently higher than that based on single case base. The computation time of CBR based on optimized case base was only 44% of that before optimization. The operation efficiency was substantially improved. Bayes Belief Network (BBN) was applied to evaluate the reliability of the production data given the complex relevance among parameters in 210t LF refining. The result was used to revise case retrieval in CBR method. Testing results showed that the revised CBR method had higher prediction accuracy than both the normal CBR method and BP Neural Network (BPNN).The determination of reasonable continuous casting heats, optimization of production planning and the evaluation method of the scheduling level of ladle were explored with regards to time control in steelmaking plant. Under mismatch of process capability in BOF-RH-CC. a method comparing the production cost was proposed to determine the reasonable continuous casting heats on the basis of calculating the transport energy consumption. Under non-full operation. optimization method of production planning was proposed to achieve stabilization of ladle operation. Generic algorithm was applied to optimize production planning in Shougang Qian’an Iron & Steel Co. Ltd No.2 Steelmaking Plant in 2013. The results showed that the times of ladle dropping off production line decreased to once from five times, the number of ladle decreased from seven to five, and the consumption amount of heating coal gas was reduced by 20,400m3 and converter tapping temperature cumulatively decreased 20℃.The running state of turnover ladle and offline ladle was evaluated based on awaiting time analysis. Ladle utilization was proposed to evaluate the integral scheduling level of ladle. Practical ladle scheduling in Shougang Qian’an Iron & Steel Co. Ltd No.2 Steelmaking Plant was analyzed. Results showed that ladle utilization can effectively reflect the practical scheduling level of ladle.Based on the practical operation requirements, a method to obtain the energy saving potential in the present control precision of molten steel temperature and time was proposed by formulating and executing production planning. Present control level of the smelting process for SPHC-W steel in Shougang Qian’an Iron & Steel Co. Ltd No.2 Steelmaking Plant was analyzed. The standard deviation of the molten steel temperature and time in the production data at each stage was set as the control precision. Results showed that when the standard deviation of molten steel temperature in each process node was reduced by 1℃, potential temperature loss in executing production planning decreased 0.33℃.When the standard deviation of time in each process was reduced by 1 min. the potential temperature loss in formulating production planning decreased 1.76℃ and potential temperature loss in executing production planning decreased 1.62℃. Superposition exists when both reduce. |
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