Abstract
Bridges are exposed to various kinds of external loads, including vehicle and hurricanes, during their life cycle. These loads cause structural damage, which may lead to bridge collapse. To ensure bridge safety, it is essential to periodically inspect the physical and functional conditions of bridges. The displacement responses of a bridge have significance in determining the structural behaviors and assessing their safety. In recent years, many researchers have been studying bridge displacement measurements using image processing technologies. Image-processing-based displacement measurements using a computer analysis system can quickly assess bridge conditions and, thus, can be used to enhance the reliability of bridges with high accuracy. This paper presents a method based on multiple-image processing bridge displacement measurements that includes enhanced robustness to image rotation. This study applies template matching and a homography matrix to measure the displacement that works well regardless of the angle between the smartphone camera and the target.
Highlights
In modern society, bridges serve as the backbone of a nation’s economy as they connect separated regions and provide effective means of transportation to accommodate the needs of populations experiencing explosive growth
The main objective of this study is to extend the measurable range and to enhance the accuracy of displacement measurement, so that computer vision-based systems can be adopted for the civil engineering structures
We introduced a computer vision-based technique for the measurement of rotation-invariant displacement with the successful utilization of a smartphone camera
Summary
Bridges serve as the backbone of a nation’s economy as they connect separated regions and provide effective means of transportation to accommodate the needs of populations experiencing explosive growth. A bridge’s displacement responses provide valuable information for structural analysis to assess bridge safety [1,2] and performance. The monitoring of displacement characteristics is a critical issue for the safety and maintenance of bridges. Displacement response measurements in bridges are normally done using high precision sensors, such as linear-variable differential transformers (LVDTs) [3], accelerometers [4], global positioning systems (GPSs). Such conventional methods have limitations [5,6,7]. The GPS-based method has low precision of vertical displacement measurements [9]
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