| Abstract:Metallurgical industry emissions of sulfur dioxide is mainly generated from the sintering process, so the sintering flue gas desulfurization occupy an important position in energy saving and emission reduction in steel industry. In the circulating fluidized bed flue gas desulfurization of sintering process, the efficiency and cost of desulfurization are measures of desulfurization productivity effect.Based on the analysis of circulating fluidized bed flue gas desulfurization technology, this paper uses mechanism analysis and numerical correlation calculation and determines parameters and status parameters affecting the operation of the desulfurization efficiency. Then it establishes the Ca/S-desulfurization efficiency model and temperature-desulfurization efficiency model by using fuzzy linear regression method. Secondly, in order to optimize the desulfurization efficiency and reduce the desulfurization costs at the same time, it analyzes the factors affecting the desulfurization cost and constructs the relevant model. Finally, it optimizes the parameters of scope from the angle of production safety and calculates the optimization of operation parameters combined with the highest desulfurization efficiency and the minimum desulfurization cost in using multi-objective genetic algorithm and principle of great satisfication. The simulation proves that the method of modeling and optimizing are effective.In order to prove the practical value of the optimization algorithm, the semi physical cloud simulation system for process control of circulating fluidized bed is set up by making use of the hardware like typical programmable logic controller, distributed control system, server according as well as the hardware in actual situation. In addition, this paper takes the sintering smoke desulfurization control process as an example to decrease the risk of debugging describe the operation mode of the cloud simulation platform and verify its effectiveness. |
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