基于单目视觉的典型桥梁结构关键动力参数测量方法

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Guowei Chen;Chenguang Cai;Ming Yang;Deguang Wang;Chengbin Liang;Jiansheng Yang
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引用次数: 0

摘要

桥梁结构关键动力参数的测量是桥梁健康监测的基础,一直受到重视。然而,常用的基于加速度计或线性可变位移传感器(LVDT)的测量方法不可避免地出现了测量不便、实时性差、成本高、精度低等问题。本文提出了一种基于单目视觉的典型桥梁结构健康监测关键动态参数测量新方法,该方法可以提高商用摄像机的性能。该方法将可靠的摄像机标定与简单的环形标记相结合,并结合改进的亚像素Zernike矩边缘提取与线性斜坡灰度模型相结合,实现了关键动态参数的精确测量。在不同工况下,与现有基于加速度计的方法(AM)进行了自建桥梁模型加速度、频率和跨中挠度测量的室内对比实验。基于加速度计的方法与提出的方法测得的跨中加速度幅值、频率和挠度的最大相对偏差分别为0.52%、1.35%和2.51%。此外,还在实际桥梁上进行了对比实验,结果表明该方法可以获得较好的测量性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monocular Vision-Based Key Dynamic Parameters Measurement Method Used for Typical Bridge Structures Health Monitoring
The key dynamic parameters measurement of bridge structures is essential to their health monitoring and has been highly valued. However, the commonly used accelerometer- or linear variable displacement transducer (LVDT)-based measurement methods have inevitably appeared in issues such as: measurement inconvenience, poor real-time performance, high cost, and low accuracy. In this study, a new monocular vision (MV)-based key dynamic parameters measurement method used for typical bridge structures health monitoring is proposed, which is capable of improving the performance with a commercial camera. This method combines the reliable camera calibration with a simple ring mark and improved sub-pixel Zernike moment edge extraction with linear ramp gray-scale model to accurately measure the key dynamic parameters. The laboratorial comparison experiments with the current accelerometer-based method (AM) at different working conditions to measure the acceleration, frequency, and deflection at the mid-span of a self-built bridge model were performed. The maximum relative deviations of the acceleration amplitude, frequency and deflection measured in the mid-span between the accelerometer-based and proposed methods were 0.52%, 1.35%, and 2.51%, respectively. Additionally, the comparison experiments on a practical bridge were also accomplished, and the results demonstrated that the proposed method can obtain a considerable measurement performance.
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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