Research On Risk Detection System Of Urban Underground Pipeline Based On Java

At present,the process of urbanization is accelerating,and the scale of cities is constantly expanding.As a result,underground pipelines in cities are increasing and expanding,However,a large number of pipelines inevitably encounter a series of problems such as corrosion,leakage,and rupture during daily use.The reasons for the frequent occurrence of underground pipeline problems are multifaceted,which can be roughly summarized as internal and external reasons.The main internal reasons are the complex and diverse distribution of pipelines,substandard pipeline quality,and long-term overload use of pipelines;The main external reasons are that the pipeline management system is not sound enough,the daily maintenance and supervision mechanism of pipelines is lacking,and the existing pipeline monitoring technology and level are seriously insufficient.So in order to improve these issues,reduce water resource waste,and achieve intelligent urban underground pipeline management,this article combines satellite image data to design and implement an urban underground pipeline risk monitoring platform using Java language,which includes functions such as pipeline leakage verification and surface settlement monitoring.The urban underground pipeline risk monitoring platform is divided into two subsystems: the urban underground pipeline risk monitoring system and the mobile app.This article first analyzes the problems existing in urban underground pipelines at present,compares the technical level and current development status of risk monitoring for urban underground pipelines at home and abroad.After analysis,it is found that the current level of pipeline monitoring at home and abroad is basically limited to traditional monitoring instruments and methods,while the technology of using radar satellite data to monitor underground pipeline risks is only in the preliminary stage,However,the exploration of this new technology has achieved good results both domestically and internationally.In order to promote the application of radar leak detection technology and improve the existing pipeline monitoring level and technology,this article combines satellite image data to determine high-precision POI(suspected leak points),and uses traditional monitoring instruments for on-site verification to achieve a "heaven earth integration" leak detection model.Based on this,the paper introduces the main technologies and software architecture involved in the design and implementation of the system,and arranges the system requirements analysis,including functional requirements,non functional requirements and feasibility analysis.On this basis,the system design includes system architecture design,network topology design,structural design and database design.After the design was completed,the system’s functions were implemented.The core business of the system is to detect pipeline leakage points based on image data,while satellite image data only determines suspected leakage points.Therefore,the accuracy of on-site POI verification by inspection personnel directly affects the feasibility of the entire project.Next,I extracted six factors that affect the accuracy of inspection to evaluate the accuracy of inspection,using inspection results from January to March 2023 as sample data,After modeling and training using traditional BP neural networks,it was found that there was a significant difference in error between the output value and the true value.Therefore,considering the shortcomings of BP neural networks,the BP neural network was optimized using the previous improved GA algorithm.The optimized algorithm(OGA-BP)was used to rebuild the model.Through comparative analysis,the accuracy of OGA-BP model was greatly improved compared to the traditional BP neural network model,But the relative error is still around 15%.I improved the OGA-BP algorithm on the basis of previous studies and named it IGA-BP in this article.After establishing models and simulating these three algorithms.Through comparative analysis,the accuracy of the IGA-BP model is the highest among the three models,and the relative error between the predicted results and the actual values obtained by the improved IGA-BP algorithm is not more than 15%,achieving the expected goal.Moreover,the feasibility of the IGA-BP model in evaluating the accuracy of inspection has been verified.This algorithm is more convenient,fast,and reliable than traditional human evaluation techniques in evaluating the accuracy of inspection personnel.After the application of the inspection accuracy evaluation model in practice,inspection personnel are also more serious and focused on completing their own inspection tasks,which greatly increases the detection rate of leakage points and greatly improves the efficiency of satellite leak detection.After the system was implemented and launched,the following conclusions were drawn through testing: the functions of the two subsystems were basically implemented,meeting the design requirements.The entire system has the characteristics of good stability,high safety,and easy operation.It also plays a significant role in reducing the risk of urban underground pipelines and building a smart city.