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In concrete structures, surface cracks are important indicators of structural durability and serviceability. Generally, concrete cracks are visually monitored by inspectors who record crack information such as the existence, location, and width. Manual visual inspection is often considered ineffective in terms of cost, safety, assessment accuracy, and reliability. Digital image processing has been introduced to more accurately obtain crack information from images. A critical challenge is to auto

Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to

To assess the current conditions of bridges in practice, a manual visual inspection is commonly used for maintenance purposes. Because manual visual inspection is time consuming, expensive, and laborious, computer vision with deep learning techniques has recently been introduced as a promising tool for automatic damage detection and classification. However, damage localization is difficult in that close-up images do not contain the global structural context, while knowing the damage locations an

The displacement responses of a civil engineering structure can provide important information regarding structural behaviors that help in assessing safety and serviceability. A displacement measurement using conventional devices, such as the linear variable differential transformer (LVDT), is challenging owing to issues related to inconvenient sensor installation that often requires additional temporary structures. A promising alternative is offered by computer vision, which typically provides a

Displacement measurements are useful information for various engineering applications such as structural health monitoring (SHM), earthquake engineering and system identification. Most existing displacement measurement methods are costly, labor-intensive, and have difficulties particularly when applying to full-scale civil structures because the methods require stationary reference points. Indirect estimation methods converting acceleration to displacement can be a good alternative as accelerati

As cables are primary load carrying members in cable-stayed bridges, monitoring the tension forces of the cables provides valuable information regarding structural soundness. Incorporating wireless smart sensors with vibration-based tension estimation methods provides an efficient means of autonomous long-term monitoring of cable tensions. This study develops a wireless cable tension monitoring system using MEMSIC's Imote2 smart sensors. The monitoring system features autonomous operati

Understanding the dynamic behavior of civil engineering structures is important to adequately resolve problems related to structural vibration. The dynamic properties of a structure are commonly obtained by conducting a modal survey that can be used for model updating, design verification, and improvement of serviceability. However, particularly for large-scale civil structures, modal surveys using traditional wired sensor systems can be quite challenging to carry out due to difficulties in cabl

Long-term displacement measurements provide important information about the structural safety of civil engineering structures and the associated maintenance necessary. Most approaches developed for measuring displacement, such as direct measurements using the linear variable differential transformer and computer vision-based sensing, relate to campaign-type sensor deployment. However, these methods have critical limitations when used to accurately measure long-term displacement, because it is di

Peak picking is used to determine locations of salient peaks in a graphical representation of a physical quantity. It is often used to extract possible natural frequencies from the frequency domain representation of structural responses. One of the challenges in peak picking is to establish a method to automatically distinguish peaks from data containing noise peaks. As selecting peaks intrinsically depends on human perception, algorithms for automated peak picking have exhibited only partial su

As demand for long-span bridges is increasing worldwide, effective maintenance has become a critical issue to maintain their structural integrity and prolong their lifetime. Given that a stay-cable is the principal load-carrying component in cable-stayed bridges, monitoring tension forces in stay-cables provides critical data regarding the structural condition of bridges. Indeed, various methodologies have been proposed to measure cable tension forces, including the magneto-elastic effect-based

Vibration-based damage detection methods have been widely studied for structural health monitoring of civil infrastructure. Acceleration measurements are frequently employed to extract the dynamic characteristics of the structure and locate damage because they can be obtained conveniently and possess relatively little noise. However, considering the fact that damage is a local phenomenon, the sole use of acceleration measurements that are intrinsically global structural responses limits damage d