Experimental verification and rapid estimation of uncalibrated cable force via video-based and vibration-based measurements

霍夫变换 加速度计 计算机科学 图像处理 流离失所(心理学) 振动 计算机视觉 快速傅里叶变换 过程(计算) 人工智能 声学 图像(数学) 算法 物理 操作系统 心理学 心理治疗师
作者
Yanhao Li,Ufuoma Joseph Udi,Mustafasanie M. Yussof,Xing Tan
出处
期刊:Review of Scientific Instruments [American Institute of Physics]
卷期号:95 (3)
标识
DOI:10.1063/5.0186377
摘要

The stayed-cable is an important component of cable-stayed bridges, with cable force being a focal point during construction and bridge operation. The advancement of camera and image processing technology has facilitated the integration of computer vision technology in structural inspection and monitoring. This paper focuses on enhancing cable force measurement methods and addressing the limitations of traditional testing techniques by conducting experimental research on cable force estimation using video recording. The proposed approach involves capturing video footage of the target on the cable with a smartphone. Subsequently, a combination of techniques such as the background subtraction method, image morphology processing, and Hough transform image processing technology are employed to detect the precise center coordinates and ultimately obtain the accurate displacement-time curve of the cable's vibration. In addition, the graphic Circularity Coefficient (CC) has been introduced to assess its effectiveness in post-motion-blur image processing for circular targets. The fundamental frequency of the cable is determined by the fast Fourier transformation, and the relationship between the cable force and the fundamental frequency is used to estimate the cable force. The experimental results are compared with data from accelerometers and force gauges, demonstrating that the frequency measurement error is below 1.2% and the cable force test error is less than 3%. In the process of acquiring the cable's fundamental frequency, the test directly employs the pixel as the displacement unit, eliminating the need for image calibration. The innovative use of the CC in processing motion-blurred targets ensured accurate recognition of target coordinates. The experimental findings highlight the method's simplicity, speed, and accuracy.

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