利用智能手机拍摄的视频和模板匹配算法快速估算电缆结构的受力情况

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Xiao-Wei Ye, Wei-Ming Que, Yang Ding, Tao Jin
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引用次数: 0

摘要

缆索是大跨度桥梁结构的重要组成部分,其运行会受到缆索力变化的严重影响。目前,缆索受力测试主要采用物理方法,即在缆索结构上安装传感器,监测其受力变化。显然,这种策略需要大量时间来实现缆力计算,因此无法实时监测缆索结构的受力情况。与此同时,由于智能手机在价格和使用寿命等方面比加速度计更具成本效益,因此在结构健康监测(SHM)领域受到广泛关注。此外,许多人都拥有智能手机,这也为更广泛的应用提供了可能。因此,本文提出了一种基于智能手机拍摄的视频和模板匹配算法的大跨度桥梁拉索力快速估算框架。首先,构建了经验模态分解(EMD)方法与小波分解(WD)方法,即 EMDWD 模型,通过消除智能手机振动和环境噪声对测量动态位移的影响,提取桥梁缆索的振动信号,从而有效提高了数据处理的准确性。此外,还建立了基于模板匹配算法的桥梁斜拉索振动识别模型,并得到了斜拉索的变形曲线。最后,利用傅立叶变换法(FFT)计算桥梁悬索的频率,并根据智能手机捕捉的视频估算索力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Fast Force Estimation of Cable Structures Using Smartphone-Captured Video and Template Matching Algorithm

Fast Force Estimation of Cable Structures Using Smartphone-Captured Video and Template Matching Algorithm

Cables are important components of long-span bridge structures, whose operation is significantly affected by cable force changes. Nowadays, cable force testing is performed by physical methods; that is, sensors are installed on the cable structure to monitor its force changes. Obviously, this strategy requires an extensive amount of time to achieve cable force calculation, which makes it impossible to monitor the force of the cable structure in real time. Meanwhile, smartphones have attracted extensive attention in the field of structural health monitoring (SHM) because of their higher cost-effectiveness than accelerometers, which include price and lifespan. Besides, many people own a smartphone, which leads to the possibility of a wider range of applications. Therefore, this paper presents a framework for the rapid estimation of the cable force of long-span bridges based on smartphones-captured video and a template matching algorithm. First, the empirical mode decomposition (EMD) method with wavelet decomposition (WD) method, that is, the EMDWD model, is constructed to extract the vibration signal of the bridge cable by eliminating the effects of smartphone vibration and environmental noise on the measured dynamic displacement, thus effectively improving the accuracy of data processing. In addition, the vibration identification model of bridge cable based on a template matching algorithm is established, and the deformation curve of cable is obtained. Finally, the frequency of bridge suspender is calculated by the Fourier transform method (FFT), and the cable force is estimated based on the smartphone-captured video.

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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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