A new method for extracting railway goaf boundary based on d-insar

Abstract

The invention discloses a new method for extracting railway goaf boundaries based on D‑InSAR, comprising the following steps: obtaining time series SAR images and precise track files in the research area; preprocessing the SAR image data to establish a connection diagram; Interference processing is performed on the interference pairs in the image to generate a differential interferogram, and the differential interferogram is geocoded; the U‑net neural network is used to identify the gobs of the geocoded differential interferograms to generate a goaf-non-goaf binary image ; Convert the raster to vector of the binary image of the goaf after identification; perform spatial fusion on the results of the goaf after multi-phase vectorization; statistically analyze the size of the goaf area, the direction of development, and the shortest distance from the boundary of the goaf to the railway . The invention automatically identifies underground mined-out areas that threaten railway safety, and systematically analyzes the distribution characteristics and development trends of the mined-out areas, and provides technical support for optimizing railway line selection and checking hidden danger points in railway mined-out areas.

Description

technical field [0001] The invention relates to a new method for extracting the boundary of a railway goaf, in particular to a new method for extracting a boundary of a railway goaf based on D-InSAR (Differential Interferometric Synthetic Aperture Radar). Background technique [0002] The goaf is a prominent ecological environment problem, which will lead to different degrees of ground subsidence around it, directly threatening the safety of houses, roads and infrastructure on the surface. When optimizing the railway direction plan, it is necessary to fully consider safety and later maintenance costs, and actively avoid these hidden mined-out areas. Therefore, fast and accurate identification of gobs is of great significance for optimizing the railway line selection scheme. At present, traditional techniques such as leveling and GPS are mainly used to monitor and identify gobs. Although real-time and high-precision point monitoring results can be obtained, the results can o...

AI Technical Summary

Problems solved by technology

However, goafs are often located in mining areas with complex geological environments, large subsidence levels, and fast-changing speeds. D-INSAR technology cannot directly obtain large-gradient terrain deformation information, and its application is limited.

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