Noncontact cable force estimation with unmanned aerial vehicle and computer vision

Tian Yongding; Zhang Cheng; Jiang Shang; Zhang Jian; Duan Wenhui

摘要

Cables and hangers are critical components of long-span bridges, tension forces of them are needed to be accurately measured for ensuring the safety of bridges. Traditionally, cable tension forces are measured by attached accelerometers or elastomagnetic (EM) sensors, however, applying these sensors into engineering practice are time-consuming, labor-intensive, and highly dangerous. To address these problems, an unmanned aerial vehicle (UAV)-based noncontact cable force estimation method with computer vision technologies was proposed in this article. Basic concept of the proposed method is to use the UAV-installed camera for capturing vibration images of cables from a certain distance and cable dynamic properties are extracted by analyzing captured images. It includes two aspects: (a) a line segments detector (LSD) was employed for detecting cable edges from captured video and a line matching algorithm was further proposed for extracting dynamic displacements; (b) the frequency difference of adjacent higher modal frequencies identified from relative displacements of the cable was employed for cable force calculation to avoid the difficulty of extracting fundamental frequency from UAV-captured video. It should be noted that relative displacement herein refers to the difference between displacements of two points on the same cable. Advantages of the proposed method lie in that the proposed LSD and matching algorithm are more robust than traditional correlation-based algorithm for calculating dynamic displacements of bridge cables and it does not need to adjust predefined parameters (i.e., subset size in correlation-based algorithms). In addition, the combination of relative displacement and frequency difference-based cable force estimation has the capability of enhancing the Fourier spectrum magnitude of bridge cables and reducing the effect of UAV motion on extraction of cable vibration frequencies. The effectiveness and robustness of the proposed method was verified by using an experimental inclined cable and field-testing data of a long-span suspension bridge. Results show that calculated cable forces with UAV technology have a good agreement with reference values measured by attached accelerometers and fixed camera, demonstrating correctness and robustness of the proposed method for cable force estimation.

机译：电缆和吊架是长跨度桥的关键部件，需要精确测量它们的张力以确保桥接的安全性。传统上，通过连接的加速度计或弹性磁（EM）传感器测量电缆张力力，然而，将这些传感器应用于工程实践中是耗时，劳动密集型和高度危险的。为了解决这些问题，本文提出了一种无人驾驶飞行器（UAV）基于计算机视觉技术的非接触式电缆力估计方法。所提出的方法的基本概念是使用UAV安装的摄像机来捕获来自一定距离的电缆的振动图像，通过分析捕获的图像来提取电缆动态属性。它包括两个方面：（a）采用线段检测器（LSD）用于检测来自捕获的视频的电缆边缘，进一步提出了线匹配算法来提取动态位移; （b）采用电缆的相对位移识别的相邻较高模频频率的频率差用于电缆力计算，以避免从捕获的视频中提取基本频率的难度。应该注意的是，这里的相对位移是指同一电缆上的两个点的位移之间的差异。所提出的方法的优点在于，所提出的LSD和匹配算法比用于计算桥电缆的动态位移的传统相关性算法更鲁棒，并且它不需要调整预定义参数（即，基于相关的相关算法中的子集大小）。另外，相对位移和频率差的电缆力估计的组合具有增强桥接电缆的傅立叶频谱幅度的能力，并降低了UAV运动对电缆振动频率提取的影响。通过使用长跨度悬架桥的实验倾斜电缆和现场测试数据来验证所提出的方法的有效性和鲁棒性。结果表明，通过附加的加速度计和固定摄像机测量的参考值，具有UAV技术的计算电缆力量具有良好的一致性，证明了电缆力估计的所提出的方法的正确性和鲁棒性。

Noncontact cable force estimation with unmanned aerial vehicle and computer vision

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