Research On Intelligent Manhole Cover Monitoring System And Mobile Feature Extraction Model For Urban Integrated Pipeline Corridors

With the development of information technology,the Internet of Things technology plays an increasingly important role in the construction of urban underground comprehensive pipeline corridors.Faced with the loss of manhole cover and inaccurate monitoring of underground hazard information,the IOT smart manhole cover monitoring system came into being.The smart manhole cover monitoring system is based on the city underground comprehensive pipe gallery system and applies the Internet of Things technology provide a real-time monitoring of the huge number of manhole covers and complex underground information in the urban underground pipelines.The traditional well cover monitoring system and intelligent well cover movement feature extraction model have the defects of single monitoring function,poor flexibility,and inaccurate monitoring of well cover position information.Therefore,this thesis designed a new type of smart manhole cover monitoring system based on the Internet of Things technology and sensor technology on the basis of the city underground comprehensive pipe gallery Based on the principle of geomagnetic field detection,this thesis proposes a multi-sensor data fusion mechanism model and a machine learning model based on support vector machine of manhole movement.It has the advantages of low cost,convenient operation,accurate information acquisition,and accurate monitoring of well cover position information.1)Through the requirements analysis and system design,the basic functions of the intelligent well cover monitoring system are clearly defined.Based on the modular design concept,the system is divided into modules.The modules including the geomagnetic field data acquisition module are specifically designed and implemented.An intelligent manhole cover monitoring system is established on the basis of the underground comprehensive pipe gallery system in the city.2)The COMSOL software was used to simulate the change of the geomagnetic field caused by the movement of the manhole cover and calculate the strength characteristics of the geomagnetic field at different positions of the manhole cover.Based on the fuzzy reasoning method,a multi-sensor data fusion manhole movement mechanism model was proposed.Based on the support vector machine algorithm,a manhole movement feature machine learning model was proposed.3)The manhole movement feature extraction model test platform was built by using a programmable logic controller.The basic functional modules of the test platform was designed and implemented.and the basic functions of the test platform and the well cover movement feature extraction model were tested and the results were given.