Research Of Control System Optimization In Heavy Factory Based On Neural Networks

With the rapid development of our country’s modernization and industrializationprocesses, all aspects of urban construction demand for steels both with large quantity andhigh quality. In order to improve the quality and efficiency of domestic steel productions,the replace the equipment to update is an effective way. However, it cost a large price. Inthis reason, we need to study how the use of modern control theory and technology forintelligent control of existing equipment to improve the existing production efficiency. Inthis way, both the research of artificial neural network theory put into use and theenhancement of existing domestic equipment’s productivity have very important practicalsignificance.In this paper, based on Bayesian network, a research for heavy rail bolt-holedouble-sided chamfering process is given to improve the chamfering processing efficiency,reduce the rejection rate of the heavy rail products and the production costs of heavy rail.The low measurement accuracy problem of the straightening machine in Wuhan Ironand Steel Group Corporation are also analyzed. Through analysis, monitoring and controlsystem are used to detect the transformation and straightening effect. Artificial neuralnetwork based on predictive control of a modern model is implemented in thehigh-precision control, shorten time to adjust the system to reduce the try straighteningtimes, improve efficiency and cost savings.The paper also gives an analysis of the water-cooling control system in high-speedwire production line. It shows the problem that the reliability and stability is low. Afteranalysis of the system structure, simplify of input and output variables, a water-coolingcontrol system network model based on LMBP algorithm are constructed in order toachieve optimal temperature control and improve the control accuracy.Simulation results and industrial site apply show that the artificial neural networkcontrol system has good performance. It can improve the control precision and stability.And thus gives feasible ideas and methods of the proficiency improvement of steelindustry.