Subway tunnel appearance detection method

Abstract

The invention discloses a subway tunnel appearance detection method, which comprises the steps of: acquiring high-definition images from all cross sections of subway structure at a certain speed alonga path of the subway through a subway rail image data acquisition platform; horizontally putting high-definition image acquired from each section, and vertically putting images acquired from certainnumber of stations at a certain speed to form image matrixes, vertically and horizontally stitching the image matrixes to form a complete and full section subway high definition image; correcting thestitched image by using a subway segment CAD vector diagram to obtain a roaming map with position coordinates; marking defects such as cracks and infiltration and the like on the roaming map, automatically calculating sizes and positions of defects, and automatically classifying and counting. According to the subway tunnel appearance detection method, all surface apparent defect information of thesubway tunnel surface can be obtained, information of submillimeter scale defect such as water seepage, cracks, erosion, leakage, peeling, dislocation and other defects on the surface can be observed, scientific and comprehensive data is provided for electronic management and maintenance of subway tunnels.

Description

technical field [0001] The invention relates to a method for detecting the appearance of a subway tunnel. Background technique [0002] The environment of the urban subway tunnel structure is sensitive and complex, and it is easily affected by the vibration of the subway train, as well as the joints of the lining structure and its own construction defects. Various diseases such as deformation will affect the performance and safety status of the structure. In order to fully and timely grasp the safety status of the tunnel structure, it is necessary to observe, detect and monitor it. At present, the detection of structural defects in subway tunnels basically adopts the method of manual inspection, which has problems such as heavy detection labor, high subjectivity, low detection efficiency, poor accuracy, and it is difficult to guarantee the integrity and accuracy of detection results, let alone record and Analyzing the time evolution law of the disease cannot meet the needs...

AI Technical Summary

Problems solved by technology

At present, the detection of structural defects in subway tunnels basically adopts manual inspection methods, which have problems such as heavy detection labor, high subjectivity, low detection efficiency, poor accuracy, and it is difficult to guarantee the integrity and accuracy of detection results, let alone record and Analyzing the time evolution law of the disease cannot meet the needs of the gradually expanding subway tunnel structure safety inspection

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