基于无人机多模态感知的缆索桥梁智能巡检方法、系统及存储介质

By using UAV multimodal perception technology, a coarse 3D model of the bridge was constructed and the flight path was optimized. Combined with multi-dimensional similarity evaluation and consistency verification mechanisms, the problem of data fusion and identification accuracy in bridge defect diagnosis was solved, and efficient and safe defect detection and maintenance support were achieved.

CN121187313BActive Publication Date: 2026-07-17JIANGSU RUNYANG BRIDGE DEV CO LTD +2
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
JIANGSU RUNYANG BRIDGE DEV CO LTD
Filing Date
2025-08-20
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies lack efficient consistency verification and fusion mechanisms in multi-source data collaborative applications, resulting in registration errors and differences in the extraction and expression of disease features in bridge disease diagnosis, making it difficult to achieve accurate identification and evaluation, and increasing interference with operation and maintenance decisions.

Method used

By using UAV multimodal perception methods, combined with lidar and oblique photogrammetry to acquire 3D point cloud and surface texture information of bridges, a 3D coarse model is constructed, flight path planning is optimized, safe flight boundaries are set, and multi-dimensional similarity evaluation indicators and consistency verification mechanisms are designed to achieve high-quality fusion and accurate verification of defect data.

Benefits of technology

It has achieved spatial benchmark unification of multi-source data, improved the accuracy and safety of bridge defect detection, generated comprehensive and reliable inspection reports, provided reliable support for bridge health monitoring and operation and maintenance decisions, and improved operation and maintenance efficiency and structural performance.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明公开了一种基于无人机多模态感知的缆索桥梁智能巡检方法和系统，方法包括：通过激光雷达获取桥梁三维点云，并开展倾斜摄影测量获取表面纹理和色彩信息；经控制点和特征匹配融合点云与影像，构建桥梁整体三维粗模型。识别关键构件，依其几何特征和检测需求生成无人机最优航线，结合环境因素动态优化航线并设置安全边界，针对细长构件完成特殊路径设置。按航线获取影像，结合定位数据完成几何校正及与三维模型的纹理映射；构建病害智能识别模型；获取病害特征向量，通过聚类合并重复病害，通过相似度评价和多源数据一致性检验实现病害数据处理，生成巡检报告。为桥梁维护提供了全面、精准的依据。
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Citation Information

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