The Design And Implementation Of Management And Control Platform For Campus Weak Electricity System

With the rapid development of Internet technology and the gradual promotion of smart campus construction,colleges and universities have entered the era of information and intelligent management.The types and quantity of the equipment in the weak current system are increasing day by day.The safe and stable operation of the weak current system is the basic guarantee for the development of teaching and scientific research,logistics management and the daily life of teachers and students in the campus.In the current information age,the management mode and method of weak current system need to be improved comprehensively.In the traditional weak current system,the network switch and other important equipment are usually directly connected to the common power socket.When an abnormal accident occurs,it will cause irreversible losses to all kinds of equipment in the weak current system.At the same time,in the management of the weak current system,the real-time control of the equipment in the weak current system cannot be implemented solely through the administrator's manual inspection and maintenance.Firstly,this thesis designs a reasonable layout scheme for the equipment in the weak current system.The whole equipment is connected to the Power Distribution Unit for power supply management.The power distribution unit can carry out real-time intelligent constant voltage and current protection for the equipment,improving the overall stability and safety of the weak current system.At the same time,a set of management and control platform integrating real-time information display,power statistics and analysis,equipment remote control,equipment anomaly warning and equipment power prediction is constructed by combining intelligent equipment,big data,deep learning,server and client development and other technologies,which can effectively improve the efficiency of weak current system management and maintenance.This thesis mainly studies from the following aspects:(1)This thesis introduces platform requirements and architecture analysis.First of all,the actual scale and equipment deployment of the weak current system in the campus are investigated on the spot.the research and development direction of the platform is determined,outlining the specific functional modules of the platform as well as putting forward thespecific requirements for the safety,stability,scalability,compatibility and user experience of the platform.According to the actual needs of the platform,the appropriate technology stack and development scheme are selected.Besides,the overall architecture,network architecture,software architecture and functional architecture of the platform are analyzed.(2)This thesis analyzes the detailed design of the platform.According to the requirements and architecture of the platform,the platform is divided into four independent modules: equipment communication module,big data processing module,power prediction module and application platform module.In the device communication module,realize the communication interaction between the server and the weak current system equipment.The big data processing module,which uses Logstash to collect the electric energy of the weak current system equipment,Kafka message queue to be responsible for the stable transmission of the data,Spark Streaming to analyze and process the data,monitor the real-time abnormality of the equipment,and HBase to store the real-time electric energy data of the equipment.In the electric energy prediction module,a kind of electric energy prediction model of weak current system based on LSTM neural network is designed,which can predict the electric energy trend of weak current system equipment relatively accurately.The application platform module adopts B/S architecture mode.it uses Vue and Spring technology stack to develop a web and small program dual platform with front-end and back-end separation.(3)This thesis introduces the specific implementation and testing process of the platform.Firstly,the prediction models of LSTM neural network,BP neural network and RNN neural network are trained respectively,and the experimental results are compared and analyzed according to the measurement indexes.At the same time,the detailed process of model deployment to the server is introduced.Next,it implements the five business functions:account management,power display,power early warning,equipment management and control,and log query in the application platform.After the completion of the overall function development of the platform,complete function,performance and compatibility of the platform,and the test results are analyzed.The campus weak current system management and control platform designed in this thesis has perfect functions and stable services.all the functional modules of the platformoperate normally,The application of the platform improves the stability and security of the weak current system,which reduces the cost of human management and improves the efficiency of management and control,promoting the information construction of the University.