摘要
基于视觉的桥索振动测量具有非接触、高精度、实时多点监测等优点。无人机作为移动平台可克服固定相机视场与分辨率限制,但仍存在自身运动干扰和目标跟踪难题。针对基于无人机视频的桥索振动识别方法,充分利用视频中静止背景信息和桥索动态特征,提出了融合线段检测及优化、特征点稳定跟踪、振动信息补偿的无靶标识别方法。首先,通过帧间稳定化抑制抖动并划分背景与桥索区域;随后,将两区域的线性轮廓作为目标同步跟踪并优化抗干扰;进而,利用背景运动轨迹估算并消除无人机全局运动,分离真实振动位移,再经后处理滤除噪声;最终,计算振动特性与索力。通过实桥无人机巡检视频验证表明,基频识别误差小于5%,有效提取了多阶频率,验证了精度与稳定性。本方法为无人机桥梁智能监测提供了新方案。
Vision-based cable vibration measurement is featured with the advantages such as noncontact operation,high precision,and real-time multi-point monitoring.Unmanned Aerial Vehicles(UAVs)as mobile platforms can overcome the limitations of fixed cameras regarding field of view and resolution.However,challenges remain,including interference from the UAV's own motion and difficulties in target tracking.Focusing on cable vibration identification methods using UAV videos,the static background information and dynamic features of the cables within the video are taken full advantaged,a target-free identification method that integrates line segment detection and optimization,robust feature point tracking,and vibration information compensation is proposed.Firstly,inter-frame stabilization is employed to suppress jitter and segment the background and cable regions.Subsequently,the linear contours of these two places are synchronously tracked and optimized for robustness against interference.Then,the background motion trajectory is utilized to estimate and eliminate the UAV's global motion,thereby isolating the true vibration displacement.Detrending processing is then conducted to filter out noise and calculate the vibration characteristics.Validation on real-bridge UAV inspection videos demonstrates that the fundamental frequency identification error is less than 5%,and effective extraction of multiple order frequencies is realized,verifying the accuracy and stability of the method.This provides a solution for UAV-based intelligent bridge monitoring.
作者
吴尚岗
闫昱杭
李书韬
WU Shang-gang;YAN Yu-hang;LI Shu-tao(Jiangsu Province Yangzijiang Expressway Management Co.Ltd.,Wuxi 214000,China;School of Civil Engineering,Harbin Institute of Technology,Harbin 150090,China;CCCC Highway Consultants Co.Ltd.,Beijing 100010,China)
出处
《公路》
北大核心
2025年第12期116-123,共8页
Highway
基金
国家自然科学基金面上项目,项目编号52578358
中交公路规划设计院有限公司技术服务项目,基于无人机的缆索体系桥梁智能巡检技术研究。
关键词
结构健康监测
桥索振动识别
无人机视频
计算机视觉
线段检测及合并优化算法
特征点稳定跟踪算法
桥索振动补偿算法
structural health monitoring(SHM)
cable vibration identification
UAV video
computer vision
line segment detection and merging optimization
robust feature point tracking
cable vibration compensation
