Optimization Design And Motion Characteristics Analysis Of Wall-press City Gas Pipeline Robots

In the construction and production of underground roadways,once a flood occurs,it will immediately threaten the safety of a large number of people.The monitoring and early warning technology is used to predict the water level in the underground roadway,which can effectively obtain time for personnel to arrange emergency escape routes.In view of the existing methods,there is a lack of research on early warning of underground roadway floods.Through the analysis of underground roadway scenes and early warning methods,the thesis proposes a method for building a flood early warning model based on the Internet of Things technology.Based on the sensor network,combined with the spread of water flow,the real-time water level information in the underground underground is obtained.By comparing and analyzing the data fitting algorithm,a least square warning algorithm that uses the water level change rate to determine the mathematical model is used to fit the water level trend curve.By using the quick sorting method and the weighted data fusion method,the problem that the water level cannot be collected when the sensor is damaged and the water level that are collected by multi-sensor are solved.Use data visualization technology and Arc GIS technology to realize the visualization of water level information and underground roadway model.Based on the research of theoretical methods,the research and development of the flood warning system in the underground roadway mainly includes information data monitoring,flood warning method,data visualization and other functions.The thesis takes the mine water inrush disaster as an example,and uses multi-time water level information to test the system.The experimental results show that the method adopted in this thesis can effectively monitor the water level information in underground roadway in real time to construct a water level model and predict the water level change trend.Basically verified the availability and accuracy of the system,and provided a scientific basis for evacuation personnel.