Data Monitoring Of Glass Fiber Production System And Furnace Temperature Control

This thesis focuses on the difficulty to monitor the whole process data of domestic glass fiber manufacturers and the problem of temperature instability in the furnace production process under traditional PID control method.The glass fiber production process is complex and the amount of data is large.How to achieve the real-time monitoring of the production data of the entire production line is of great significance to improve the quality of glass fiber production.At the same time,furnace temperature control is an important link in glass fiber production.The current control method is still traditional PID control.The control effect is not good and manual onsite auxiliary control is required.The improvement of the temperature stability of the kiln has important practical significance for improving the quality of glass fiber products,reducing the number of field operators,and extending the service life of the kiln.First of all,this thesis makes a detailed explanation of the construction work of glass fiber Supervisory Control and Data Acquisition(SCADA)system.Based on the design requirements of the SCADA system and the network topology diagram,this thesis has completed the design of the system framework.Focusing on the human-machine interface part,a complete set of upper computer interfaces is designed through System Platform and Intouch software and successfully put into actual production.Secondly,in view of the characteristics of large lag and multiple disturbances of the furnace,based on the temperature data of No.5 glass fiber furnace under the mixed conditions of industrial sites,the fuzzy PID control and the adaptive MPC controller were designed to effectively overcome the effect on the control performance of the system by the time lag and uncertainty.The effectiveness of the control algorithm is illustrated by simulation results.Next,based on the PLC module and OPC communication technology,this thesis designs and builds a muffle furnace experimental platform.The result shows that the performance of adaptive MPC is better than fuzzy PID control.Finally,this thesis chooses the adaptive model predictive control method for practical application of the No.5 glass fiber furnace site.The connection between PC and the field equipment is established by OPC technology.The temperature setting value and feeding frequency are used as the input of the adaptive MPC controller,and the gas valve opening is used as the output to control the furnace gas valve.By comparing and updating the field data of the furnace in the mixed working environment for24 hours before and after updating the control method,the following results are obtained.Under the adaptive MPC,the temperature difference of the glass fiber production furnace is significantly reduced,and the resistance to interference is improved.The stability of temperature control is better than that in the traditional PID control method.Adaptive predictive control achieves the improvement of the temperature control of the furnace in the production line,it has practical production guiding significance.