| Under the background of promoting industrial development with information,China vigorously promotes the combination of Internet of things,big data,artificial intelligence and other advanced technologies with traditional industries.As one of the national pillar industries,it is particularly important to speed up the information and intelligent construction of iron and steel enterprises.In the iron and steel enterprises,the molten iron logistics process is between ironmaking and steelmaking,which plays an important role in connecting the preceding and the following.Now,the iron and steel enterprises are gradually carrying out intelligent and unmanned transformation of the molten iron logistics and transportation process.In addition,the complexity of the regional environment of molten iron transportation and the expansion of production scale,the enterprises put forward higher requirements for strengthening the monitoring capacity of the molten iron transportation process.But at present,there are many problems in the existing monitoring system of iron and steel enterprises,such as lack of function,isolated information,backward structure,etc.the existing monitoring system of iron and steel enterprises has not been able to meet the monitoring needs of the enterprise for the unmanned molten iron transportation process,so it is of great significance to use mature and advanced technology for the remote real-time monitoring of the unmanned molten iron transportation process.In this paper,based on the background of the process monitoring of unmanned hot metal transportation in iron and steel enterprises,the shortcomings of the current monitoring system are analyzed,and the remote monitoring system of unmanned hot metal transportation is designed and implemented.Aiming at the problem of insufficient remote monitoring ability of transport vehicles,this paper solves the problem from three aspects: environmental awareness of transport vehicles,state monitoring of transport vehicles and remote control of operation safety.In terms of vehicle environmental awareness,a comprehensive perception model of environmental data is established and the obstacles in front of the running locomotive are detected by using the Yolo algorithm based on deep learning;in terms of transport vehicles In the aspect of real-time monitoring of vehicle status,the monitoring model of running vehicle data is established,and the real-time transmission mode of monitoring data is designed to ensure the real-time transmission of data;in the aspect of operation safety remote control,the safety problems in the process of unmanned hot metal transportation are analyzed,and the remote control mode of UAV vehicle is designed to enhance the safety of the system operation process.Aiming at the problem of insufficient visualization ability of the system,Web GIS is used to visualize the running lines,vehicles and work stations,and Douglas-Peuker algorithm is used to dilute the points of the running lines,which reduces the rendering pressure of the browser.The system adopts B / S architecture design,which solves the cross platform problem of the system and the problem of different information sharing between stations.The main contents of this thesis are as follows:First of all,the system design requirements are put forward according to the current situation of unmanned hot metal transportation and the shortage of existing monitoring system.Then,the key problems of system construction are analyzed.The high available hardware platform with front and rear end separated deployment is designed and built.The system software architecture based on MVVM and SSM framework is designed.The rest style system data interface is designed,and the database selection and data model are completed at last,the remote monitoring system of unmanned hot metal transportation is developed and the function and performance of the system are tested,which realizes the remote monitoring of the whole process of unmanned hot metal transportation. |
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