How to optimize the artificial intelligence of rolling mill


At present, the rolling procedure is the main technical content of steel plate and strip production and the basic guarantee of factory production capacity, so as to achieve the quality, accuracy and form quality of products and forms. With the rapid development of cold rolling technology, the cold rolling scheme based on empirical method can not meet the production demand. Nowadays, there are few studies on the optimization of artificial intelligence of rolling procedure in the field of single stand cold rolling mill.
Now, combined with the production situation of the steel plant, the unique hydraulic Ag number of the independent reversible cold rolling platform and the engineering practice of the electric propulsion system, the theoretical and experimental research of optimization, and the artificial intelligence of the cold rolling program of the single platform reversible cold rolling mill have important theoretical and Engineering importance and practical value. First, the document analyzes and compares a set of mathematical models suitable for the cold rolling system, Select the force whose target function distribution is proportional to the capacity load of the rolling mill equipment, optimize the program cold rolling genetic algorithm, and compare it with the rolling program of the original system.
Nowadays, the optimized moving schedule is more reasonable. In order to select the optimization algorithm more suitable for engineering practice, the new particle swarm optimization algorithm is used to optimize the balance program. When compared with the analysis results of genetic algorithm, the advantages of particle swarm optimization in convergence, calculation accuracy, search ability and speed are determined. Therefore, it is intended to be used in engineering practice and combined with the actual situation after many experiments, The particle swarm optimization algorithm is fully improved and a set of reasonable optimization parameters are selected to speed up the calculation time of the algorithm and meet the operation needs of cold strip mill on-line production.
The improved particle swarm optimization algorithm is applied to engineering practice to reduce equipment power consumption and improve production efficiency. According to different software platforms, the main computer system designed and developed, including computer and touch panel, has been completed under the computer communication system, and the rolling system and other functions have been calculated.


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