Building appearance defect detection method and system based on unmanned aerial vehicle

The drone obtains building information to generate hierarchical scanning paths and three-dimensional obstacle avoidance flight trajectories, and combines multiple sensor information for space-time alignment processing and neural network analysis, solving the problems of low efficiency and insufficient accuracy of building appearance defect detection in the existing technology, and achieving efficient and accurate building appearance defect detection and intelligent prediction.

CN120369736AInactive Publication Date: 2025-07-25ZHEJIANG NONFERROUS GEOPHYSICAL TECH APPL RES INST CO LTD
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Patent Information

Application Number
CN202510416883.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-03
Publication Date
2025-07-25
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The existing building appearance defect detection methods are inefficient, making it difficult to achieve efficient and accurate detection of all areas of high-rise buildings or complex structures, and have limited ability to identify concealed defects, which affects the accuracy of building safety assessment.

Method used

The drone-based building appearance defect detection method is used to generate a hierarchical scanning path and a three-dimensional obstacle avoidance flight trajectory by obtaining building information, combining visible light images, infrared heatmaps and lidar point cloud information for spatiotemporal alignment processing, and using attention mechanism neural network to extract multi-scale features and generate detection reports.

Benefits of technology

It realizes efficient and accurate building appearance defect detection, improves the automation and safety of inspection, ensures comprehensiveness, and intelligently predicts defect development trends, and provides scientific maintenance decision support.

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Abstract

The invention relates to the technical field of building appearance defect detection, in particular to a building appearance defect detection method and system based on an unmanned aerial vehicle, and the method comprises the steps: obtaining the building information of a target building, and generating a hierarchical scanning path and a three-dimensional obstacle avoidance flight path, a visible light image, an infrared thermodynamic diagram and laser radar point cloud information are collected for space-time alignment processing, and an attention mechanism neural network is used for extracting multi-scale features to generate a detection report containing defect three-dimensional coordinates, damage levels and safety risk assessment. The method achieves the purpose of efficiently and accurately detecting the building appearance defects, can adapt to complex building structures and environmental conditions, supports defect trend prediction and maintenance decision, and remarkably improves the building safety management efficiency.
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