Research And Application Of Parameter Characteristics Of Heavy Media Separation Process Based On Data Mining

Heavy medium separation process is an important part in the production process of coal preparation plant.At the same time,the precision of suspension density is directly related to the rate of cleaned coal.At present,the main operation method to adjust the density of suspension is to control diversion and water supply.The realization of intelligent coal preparation plant based on intelligent technology has become the main development goal of coal preparation industry.Based on the Internet of things,big data and cloud computing technology,such as the dense medium separation process of coal preparation plant design a set of intelligent control system,at the same time through data analysis and machine learning to achieve the optimization of shunt process control,remote mobile information platform is developed,and combined with cloud computing resources to complete the whole process of coal preparation plant production management control,finally realizes the dense medium separation process of intelligent control and data management.The traditional heavy medium separation control system mainly relies on the local network connection,PLC for logic control,and the industrial personal computer for the human unit interface.It does not pay much attention to intelligent remote control,process data storage,data processing analysis and platform resource control,but only realizes the basic action control.There are still many problems in the actual application process,which need the real-time participation of personnel.Combined with the industrial Internet of things framework,this paper designed a set of Web remote control system based on the Spring Boot MVC architecture,completed the data communication and interaction through Modbus/TCP technology,and designed a set of heavy media separation system database by integrating Mysql with Mybatis,realizing the intelligent control of heavy media separation,and carried out a field test,the test results can meet the normal production requirements.The fractional flow control of heavy medium separation process is a nonlinear process with large hysteresis.By analyzing the data of heavy medium separation process,the prediction model of fractional flow valve opening is established.Python language is used for machine learning training,and support vector machine algorithm is used for classification.Intelligent control of heavy media separation is a link in the construction of intelligent coal preparation plant.For the construction of intelligent coal preparation plant,a remote operation and maintenance solution based on hybrid cloud platform is proposed.Through the cloud platform,the production information,scheduling information and equipment information of the coal preparation plant are managed.In terms of security,data and operation and maintenance security of hybrid cloud system are protected seamlessly by various technologies of cloud security.The mobile terminal remote control platform based on APICloud is designed,which enables the whole coal preparation plant to obtain various information of the whole coal preparation plant and even the group conveniently and in real time.The system has been put into trial operation in the heavy medium workshop of the plant,and the whole system is in good operation condition.The classification and prediction of the diverging valve can also maintain about 95% accuracy.At the same time,a variety of process and equipment data have been effectively collected to provide effective resources for further data analysis.