Integrated bridge detection method based on unmanned aerial vehicle

Abstract

The invention relates to an integrated bridge detection method based on an unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicle bridge detection. The method includesthe following steps: step I. acquiring detected bridge body and surrounding terrain environment data by an unmanned aerial vehicle A, and returning the data to a ground comprehensive information processing control system; step II. generating, by a 3D coordinate modeling system, a 3D coordinate model of the bridge body and the surrounding terrain environment; step III. establishing, by an unmannedaerial vehicle cruise path planning system, an autonomous cruise path of an unmanned aerial vehicle B, and sending the autonomous cruise path to the unmanned aerial vehicle B; step IV. executing, by the unmanned aerial vehicle B, autonomous cruise path to acquire and return the image of the bridge body; step V. detecting a bridge surface defect and identifying, by a marking system, the defect partof the bridge surface, calculating the defect degree of the defect part, and marking the defect part; step VI. automatically generating, by a bridge quality detection report generation system, a bridge quality detection report. The full automation of the bridge detection process is realized, the detection efficiency is greatly improved, and the detection quality is improved.

Description

technical field [0001] The invention relates to an integrated bridge detection method based on an unmanned aerial vehicle, belonging to the technical field of unmanned aerial vehicle bridge detection. Background technique [0002] In recent years, with the rapid development of my country's infrastructure construction, many infrastructure constructions have been put into use, which has also brought about a huge market space in infrastructure maintenance. In terms of bridges, according to statistics, the total number of bridges in active service in my country exceeds one million, and 40% of the bridges have been in service for more than 25 years, which belongs to the "aging" stage and requires a lot of effort in bridge inspection and maintenance. [0003] Traditional bridge detection is through manual detection or inspection vehicle detection. Manual inspection has problems such as high difficulty coefficient, large capital investment, detection blind spots, difficulty in gua...

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Problems solved by technology

[0005] This method can effectively reduce some of the deficiencies of manual inspection and inspection vehicle inspection, but there are still the following problems: First, UAV bridge inspection requires high levels of UAV pilots, and crashes are prone to occur in some complex terrain environments The incident caused the problem of increased detection cost and reduced detection effect; second, the quality of the existing UAV bridge detection image is uneven, and the overall performance and structural parameters of the bridge are lacking, resulting in misjudgment of the degree of bridge damage; third, in the In some complex environments, bridge detection is prone to detection blind spots, resulting in detection loopholes

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