The Design And Implementation Of Software For Intelligent Manhole Cover System Supervision Platform

With the rapid development of science and technology,the process of urban modernization is accelerating,various new technologies have been applied to people's lives,and the construction of cities has become intelligent and advanced.Therefore,the concept of smart city is proposed,and the smart city is a modern one.The deployment of urban intelligent facilities created by science and technology.Nowadays,the deployment of urban underground pipe network is becoming more and more complicated,and the number and types of urban manhole covers are also rising.Therefore,the safety accidents caused by the manhole cover problem are also rising.These problems have seriously affected people's lives and built wisdom.The intelligent manhole cover management system has become an important development theme in the construction of smart city infrastructure.Firstly,this thesis first analyzes the research background and significance of the intelligent manhole cover system.On the basis of this analysis,it compares the status quo and development trend of the management and maintenance of the manhole cover safety problem at home and abroad,and further puts forward the main research content of this thesis,namely the intelligent manhole cover system supervision platform software.Through the system architecture design and business requirement analysis,this thesis determines the software model of supervision platform based on B/S architecture,and chooses JavaEE enterprise-level application SSM framework technology to build the back-end software architecture of supervision platform.The intelligent manhole cover system supervision platform software can be divided into three layers in general,namely user interface layer,business processing layer and data service layer.Then,for the manhole explosion accident with the highest level of manhole cover failure,this thesis studies the prediction of the concentration of flammable gas inside the manhole cover.The research method uses BP neural network algorithm to construct the prediction model,and targets the shortcomings of BP neural network initial weight and threshold randomness.Genetic algorithms were introduced for optimization.Because the main combustible gas component that causes the manhole explosion is methane,this thesis takes the time series sample of methane gas concentration as the training and prediction data,and compares the prediction result with the combustible gas explosion limit theory to compare the alarm threshold set by the supervision platform by 10% LEL.Therefore,it is predicted in advance whether the manhole cover has the possibility of explosion hazard.Secondly,based on the platform requirements and solutions,on the basis of clarifying the function and data flow of each module,the design of the platform database table is completed.On this basis,the design and implementation method of the manhole cover explosion warning module is expounded.Then the implementation of the remaining main business function modules and communication server software of the supervision platform software is discussed in detail.Finally,in order to verify the software function of the intelligent manhole cover system supervision platform,the function and performance test of the supervision platform software were carried out,and the function and performance test results were elaborated.The test results show that the supervision platform software meets the project requirements and achieves the expected goals.