Research On Industrial Field Scheduling Algorithm And Design Of Monitoring System

Industrial Control System(ICS)provides support for the automation of national infrastructure,which not only guarantees the normal operation of social economy,but also plays an important role in lean production and intelligent manufacturing.ICS’s research on security,data processing and intelligence,as well as connectivity,is widely followed.Among them,scheduling efficiency optimization of industrial tasks and monitoring and control system optimization of industrial data have always been hot topics in the field of industrial automation control.In order to improve the scheduling index of industrial field tasks and the automation control level of industrial production field,the design and optimization of industrial task scheduling algorithm and ICS are presented a major challenge.Based on the above background,the specific work of this paper is as follows:1)In order to optimize the automation control of industrial field,this paper developed a real-time data acquisition and analysis system for talc industrial production line based on Siemens S7-1200 programmable logic controller,taking the air flow grinding production line of talc ore deep processing as an example.In this paper,through the analysis of production line background requirements,the first design of industrial field network topology scheme.Secondly,the selection of the next machine and related communication configuration,to achieve the communication bridge.Finally,the real-time production process monitoring system is designed and developed.The system can transform massive run-time data into knowable and controllable industrial data and meet the necessary conditions of enterprise fault diagnosis and analysis.2)Aiming at the low scheduling efficiency of important industrial tasks in industrial fields,this paper combined the characteristics and attributes of industrial tasks on the basis of real-time scheduling algorithm.A Multi Queue based on Priority and Deadline(MQPD)scheduling algorithm is proposed.Firstly,this paper analyzes the characteristic attributes of multi-type industrial tasks,uses these characteristic attributes to model industrial tasks,and establishes the multi-objective optimization model of industrial task scheduling.Secondly,the algorithm uses multiple queues to store the ready industrial tasks,and a calculation method is designed to evaluate the urgency of the tasks,as a basis for dynamic sorting of the industrial tasks in the ready queue.In addition,in order to avoid unnecessary industrial scheduling time loss and improve the scheduling efficiency of industrial tasks,this paper designs the execution necessity and preemption necessity judgment of industrial tasks,and finally proposes the MQPD scheduling algorithm.In order to prove the effectiveness of this algorithm in solving the problem of industrial task scheduling,the simulation is divided into two groups.12 kinds of industrial scene characteristics are simulated and 12 groups of industrial task sets are simulated and scheduled.Through simulation,when the proportion weight of urgent important industrial tasks is large,MQPD algorithm can improve the ratio of important task completion,non-important task completion and total task completion by more than6.61%,3.74% and 4.10%,respectively,and reduce the average waiting time and average response time of important tasks.The validity of MQPD algorithm is proved.The real-time process monitoring and control system realizes the monitoring,control,data acquisition and storage requirements of talc air mill production line.In addition,MQPD real-time scheduling algorithm solves the efficiency problem of real-time scheduling algorithm for industrial field tasks,and can improve the scheduling efficiency of important industrial tasks while ensuring the completion rate of common industrial tasks.