Elsevier

NDT & E International

Volume 39, Issue 5, July 2006, Pages 425-431
NDT & E International

A vision-based system for remote sensing of bridge displacement

https://doi.org/10.1016/j.ndteint.2005.12.003Get rights and content

Abstract

This study proposed the vision-based system which remotely measures dynamic displacement of bridges in real-time using digital image processing techniques. This system has a number of innovative features including a high resolution in dynamic measurement, remote sensing, cost-effectiveness, real-time measurement and visualization, ease of installation and operation and no electro-magnetic interference. The digital video camera combined with a telescopic device takes a motion picture of the target installed on a measurement location. Meanwhile, the displacement of the target is calculated using an image processing technique, which requires a target recognition algorithm, projection of the captured image, and calculation of the actual displacement using target geometry and number of pixels moved. For the purpose of verification, a laboratory test using shaking table test and field application on a bridge with open-box girders were carried out. The test results gave sufficient dynamic resolution in frequency as well as the amplitude.

Introduction

Bridge health monitoring has become an important thrust in the current structural engineering research [1], [2]. The research has been motivated, among other things, by the need to provide the owners of the structures with the measured structural response in order to verify if the structural behavior is adequate under the postulated external disturbances and further to identify any anomaly including specific type of physical damage, aging effect, environment-induced deterioration, and possible others. In this respect, the list of existing inventory of emerging and traditional sensors covers an impressive range of applications. Unfortunately, however, the list is rather short for displacement sensors in spite of their critical importance as one of the most useful descriptors of structural behavior under loading and other ambient conditions. Often, this stems from the fact that existing displacement sensors are difficult to be installed firmly in a cost-effective manner at the bridge site, since most bridges span over active highways, rivers, sea channels, or mountainous terrains.

Traditional structural displacement sensors, such as linear variable differential transformers (LVDTs) and dial gauges, measure the displacement at a measurement point of the bridge, usually in any direction and meeting resolution requirement for structural testing. This device requires, however, a stationary platform near the measurement point as a reference. The two ends of the sensors are to be fastened to this reference point and the measurement point, respectively; the distance between these points is not easily adjustable because of the nature of the mechanism of the sensor. Sometimes, a wire-connection device is used to get around this difficulty at a loss of accuracy. This is the problem that limits the application of LVDTs for bridge displacement measurement.

There are some other non-contact type displacement measurement systems that are of recent origin. Among them, more prominently high-tech examples include Global Positioning System (GPS) [3], [4], [5], [6], [7] and Laser Doppler vibrometers [8]. Most of the published studies of GPS showed that it has an accuracy of about ±1 cm in the horizontal direction and ±2 cm in the vertical direction. High-accuracy and high sampling rate GPS-based tracking comparable with the proposed vision-based devices is much more costly. The Laser Doppler vibrometers perform very well but they are also much more expensive to use than the proposed vision-based sensors and the Laser intensity may become dangerously strong for the distance we envision for remote sensing (more than 75 m to even more than 100 m).

It is suggested sometimes that the displacement time history be developed by numerical double-integration of a corresponding acceleration time history with some appropriate baseline corrections [9]. This is in principle a correct approach. While it is convenient, low cost, and tempting, this approach rarely provides reliable results especially in field experiments in general and according to our experience. Also, the calculation of displacement from strain data [10] is very sensitive to noise, and should be measured at many points along a mechanistically meaningful lines such as principal stresses and strains on the surface of the bridge in order to accurately estimate even a deflection profile of a bridge. A microwave interferometer with imaging capability was utilized to measure the displacement of a real-scale building [11]. The images were obtained by a synthetic-aperture interferometric radar, and the phase information of the synthesized microwave images was exploited for detecting displacements of the illuminated structure. However, these devices are very expensive and difficult to be implemented.

Vision-based methods have offered effective alternatives to displacement measurement of bridges [12], [13]. However, there remain still challenges to be resolved in the existing systems such as a specially manufactured optical device [12], off-line processing for sophisticated signal processing [13], etc. Indeed, there is less cost-effective displacement sensor system to remotely measure the displacement of bridges, which is reliable, accurate, easy to use, and having real-time capability. For this reason, in this study, we propose the vision-based system which measure dynamic displacement of bridges using a real-time digital image processing technique. This technique is highly cost-effective and easy to implement, but still maintains the advantage of measuring dynamic displacement with a high level resolution.

Section snippets

Overview

Fig. 1 shows the schematics and flowchart of the vision-based system for real-time displacement measurement of bridges. At first, the measurement point is marked with a target panel of known geometry. A commercial digital video camera with a telescopic lens is installed on a fixed point away from the bridge (e.g. on the coast) or on a pier (abutment), which can be regarded as a fixed point. Then, the video camera takes a motion picture of the target placed at the measurement point. Meanwhile,

Verification through a shaking table test

For the verification of the present method, a laboratory test was made using a shaking table test and the measured displacement by image processing techniques was compared with the data from a contact-type sensor, a linear variable differential transformer (LVDT). Fig. 4 shows the test setups and the photos taken by a digital video camcorder with a telescopic lens. The displacement of a target under the excitation with the exciting frequencies of 2 and 4 Hz was measured at two locations, 16 m

Field application to a steel-box girder bridge

Another field test was performed on the Yeondae Bridge with four continuous spans and two open-box steel girders. Vehicle running tests were performed using two dump trucks with the load of 30 and 40 ton and the running speed of 3, 20 and 40 km/h. The dynamic displacement was measured at the center of the first span by a laser vibrometer with the sampling rate of 1 kHz (LB-1000, KEYENCE, Co.), and the proposed vision-based system. The camera was installed on the ground about 20 m apart from the

Concluding remarks

In this study, a vision-based dynamic displacement measurement system using digital image processing techniques is developed. The applicability and effectiveness of the present method were verified through a laboratory test using a shaking table test and a field application on a bridge with steel box girders. In the laboratory test, the measured displacement was compared with the data from a contact-type sensor, a linear variable differential transformer, and showed close results to a

Acknowledgements

This study was done under National Science Foundation Grant nos CMS 0509018 and CMS 0112665. Their supports are immensely appreciated.

References (13)

There are more references available in the full text version of this article.

Cited by (0)

View full text