Integrated bridge detection system based on unmanned aerial vehicles

Abstract

The invention relates to an integrated bridge detection system based on unmanned aerial vehicles and belongs to the technical field of unmanned aerial vehicle bridge detection. The system comprises abridge modeling unmanned aerial vehicle A, a bridge surface data collection unmanned aerial vehicle B and a ground integrated information processing control system. The ground integrated information processing control system comprises a 3D coordinate modeling system, an unmanned aerial vehicle cruising route planning system, a bridge deck defect detection and marking system, and a bridge quality detection report generation system. The unmanned aerial vehicle A is used for photographing a detected bridge and a surrounding terrain environment. The 3D coordinate modeling system is used for establishing 3D coordinate models of a bridge body and the surrounding terrain environment. The unmanned aerial vehicle cruising route planning system is used for planning a cruising route of the unmanned aerial vehicle B. The bridge deck defect detection and marking system is used for detecting defects of corresponding locations of a bridge deck, computing defect level indexes and marking the defect level indexes in the model. According to the system, full automation of a bridge detection process is realized, detection efficiency is greatly improved, and detection quality is improved.

Description

technical field [0001] The invention relates to an integrated bridge detection system 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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