The Research On Integration And Analysis Method Of Intelligent Leak Detection Date For Buried Pipeline

In recent years,with the rapid development of energy demand in countries around the world,the application of buried pipelines has become more and more extensive.Buried pipelines are deployed in a complex underground environment.Due to environmental loads,third-party activities,etc.,pipelines are easily damaged and leaks.Traditional monitoring and detection methods at the initial stage of leakage are difficult to identify leaks in a timely manner.Awareness and take remedial measures.Therefore,in this paper,advanced monitoring techniques are adopted to monitor buried pipelines in real time,and it is of great significance to realize leakage monitoring during buried pipeline operation from multiple dimensions.Existing pipeline leakage monitoring technologies and methods can only distinguish the occurrence of leakage accidents,and fail to evaluate the degree of leakage accidents.The evaluation of the degree of pipeline leakage can provide an effective basis for pipeline operation and maintenance personnel to make accident handling decisions.Therefore,in this paper,the leakage and diffusion of buried pipelines are analyzed through the pipeline leakage model test.Based on the distributed optical fiber monitoring data,the main influencing factors of the leakage and diffusion are explored for the impact of the soil environmental temperature time history changes during the leakage process.The test data shows that under different conditions of leakage and diffusion influencing factors,there is a significant difference in the temperature time history change trend and the peak temperature change rate of the leakage point,and the degree of influence on it under different values of the same diffusion influencing factor also exists.Therefore,based on the existence of this difference,the leakage simulation experiment data is used to establish the quantitative relationship of the buried pipeline leakage degree identification method through the multivariate linear fitting method,so as to carry out quantitative analysis and qualitative evaluation of the leakage degree.The leakage location information based on the distributed optical fiber sensor is based on the effective monitoring starting point of the optical fiber connection end as the reference point.The location information of each monitoring point represents the distance value between the monitoring point and the reference point.This positioning information is less intuitive and interactive.Therefore,this article proposes a method of visual expression of buried pipeline geographic information based on Baidu Map API.This method expresses the pipeline’s location and purpose in the real world by adding points,lines,planes and other overlays on top of the underlying logic of Baidu Map;The integration method of geographic information and monitoring data is established through the conversion relationship between the plane coordinate system of the Web Brower form and the latitude and longitude coordinates of the Baidu map view area.When the corresponding trigger action is executed on the Baidu map interface,the interaction between geographic information and monitoring data can be realized;The corresponding relationship between pipeline GIS geographic positioning and optical time domain reflection technology positioning information is established through calibration experiments.When pipeline leakage is identified based on distributed optical fiber monitoring data,the corresponding relationship between the two types of positioning information can be used to obtain the accident section Geographical location information,and in the form of a maroon pipeline in the Baidu map view interface for prompts.Based on the above method,the LabVIEW platform is used to write the buried pipeline leakage monitoring software.In order to verify the practicability and effectiveness of the system,the demonstration pipeline is used for system verification.The verification results show that the visualization effect of the entire section of the demonstration pipeline and the accident section in the Baidu map view interface is good,the integration and interaction between the monitoring data and the geographic information are high,and the error between the calculation result of the leakage degree and the setting value of the working condition is high.Smaller,the system is more practical.