• Korean Journal of Remote Sensing
• /
• v.35 no.5_2
• /
• pp.831-840
• /
• 2019

Recently, the span length of long-span bridges is getting longer. As a result, it has been suggested that a new concept called 'super long-span bridge'. In case of super long span bridges, the structure is being complicated and the importance of structural stability is being emphasized. However, until recently, the most commonly used sensors (dual axis clinometer, anemometer, strain gauge, etc.) have got limit about the bridge monitoring. Consequently, we researched the application of a Global Navigation Satellite System (GNSS) to improve the limit of the existing sensors. In this study, the dual axis clinometer, the anemometer and the strain gauge together with the GNSS were used to analyze the behavior of a super-long suspension bridge. Also, we propose the detailed method of bridge monitoring using the GNSS. This study consisted of three steps. First step calculated the absolute coordinates of the towers and the longitudinal axis direction of the study bridge using the GNSS. In second step, through the analysis of the long-term behavior in shortly after construction, we calculated the permanent displacement and evaluated the stability of main towers. Third step analyzed the behavior of bridge by the wind direction and was numerically indicated. Consequently, the bridge measurement using the GNSS appeared that the acquired data is able to easy processing according to the analysis purpose. If we will use together the existing measurement sensors with the GNSS on the maintenance of the super long-span bridge, we figure each error of measurement data and improve the monitoring system through calibration. As a result, we acquire the accurate displacement of bridge and figure the behavior of bridge. Consequently, we identified that it is able to construct the effective monitoring system.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.22 no.3
• /
• pp.239-245
• /
• 2002

Many civil and infrastructures continue to be used despite aging and the associated potential for damage accumulation. Therefore, the ability to monitor the health of these systems is becoming increasingly important. The purpose of this paper is to propose a real-time health monitoring system of cable-stayed bridge, based-on non-destructive measurement. And also this paper focuses on the safety assessment for bridge from health monitoring system to accomplish this safety assesment. Using the proposed health monitoring system, it helps bridge maintenance and reduces the economic cost of a life-cycle costs. Also it give important data to develop the design and analysis method for cable-stayed bridges.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.10a
• /
• pp.1105-1106
• /
• 2019

고도성장 당시 건축되었던 사회기반시설들은 노후화로 인한 안전사고의 위험성이 부각되고 있다. 사회기반시설 중 교량의 경우 건축방식, 기후에 따른 안전점검 간 제약사항이 생긴다. 본 논문에서는 드론을 통해 점검이 필요한 교량을 촬영한다. 교량의 촬영 데이터를 정합 이미지로 생성하여 교량 내 유지보수를 위한 교량 모니터링 시스템을 제안한다.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.4
• /
• pp.505-516
• /
• 2018

In order to establish an efficient bridge maintenance strategy, the future performance of a bridge must be estimated by considering the current performance, which allows more rational way of decision-making in the prediction model with higher accuracy. However, personnel-based existing maintenance may result in enormous maintenance costs since it is difficult for a bridge administrator to estimate the bridge performance exactly at a targeting management level, thereby disrupting a rational decision making for bridge maintenance. Therefore, in this work, we developed a representative performance prediction model for each bridge element considering uncertainty using domestic bridge inspection data, and proposed a bayesian updating method that can apply the developed model to actual maintenance bridge with higher accuracy. Also, the feasibility analysis based on calculation of maintenance cost for monitoring maintenance scenario case is performed to propose advantages of the Bayesian-updating-driven preventive maintenance in terms of the cost efficiency in contrast to the conventional periodic maintenance.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.2
• /
• pp.183-191
• /
• 2018

In this study a traffic volume dependent displacement estimation model for Gwangan Bridge was developed using bridge monitoring big data. Traffic volume data for four different vehicle types and the vertical displacement data in the central position of the Gwangan Bridge were used to develop and validate the estimation model. Two statistical estimation models were developed using multiple regression analysis (MRA) and principal component analysis (PCA). Estimation performance of those two models were compared with actual values. The results show that both the MRA and the PCA based models are successfully estimating the vertical displacement of Gwangan Bridge. Based on the results, it is concluded that the developed model can effectively be used to predict the traffic volume dependent displacement behavior of Gwangan Bridge.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.28 no.3
• /
• pp.66-73
• /
• 2024

Stay-cable is one of the most important load carrying members in cable-stayed bridges. Monitoring structural integrity of stay-cables is crucial for evaluating the structural condition of the cable-stayed bridge. For stay-cables, tension and damping ratio are estimated based on modal properties as a measure of structural integrity. Since the monitoring system continuously measures the vibration for the long-term period, data acquisition systems should be stable and power-efficiency as the hardware system. In addition, massive signals from the data acquisition systems are continuously generated, so that automated analysis system should be indispensable. In order to fulfill these purpose simultaneously, this study presents an autonomous cable monitoring system based on domain-knowledge using IoT for continuous cable monitoring systems of cable-stayed bridges. An IoT system was developed to provide effective and power-efficient data acquisition and on-board processing capability for Edge-computing. Automated peak-picking algorithm using domain knowledge was embedded to the IoT system in order to analyze massive data from continuous monitoring automatically and reliably. To evaluate its operational performance in real fields, the developed autonomous monitoring system has been installed on a cable-stayed bridge in Korea. The operational performance are confirmed and validated by comparing with the existing system in terms of data transmission rates, accuracy and efficiency of tension estimation.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2005.05a
• /
• pp.1409-1412
• /
• 2005

무선 센서 네트워크는 교량 안전진단(Structural Health Monitoring, SHM)을 위한 효율성, 신뢰성 등의 특징들을 제공한다. 그러나 현재 교량 안전진단은 아날로그 센서를 이용하여 데이터를 수집하고, 유선망을 사용하여 관리프로그램으로 전송하고 있다. 본 논문에서는 무선망에서 동작하는 센서 네트워크를 이용하여 교량 및 노면을 모니터링하기 위한 안전진단 시스템을 구현하였다.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.15 no.2
• /
• pp.170-178
• /
• 2011

In this paper, a research was performed to develop a wireless measurement system for bridge monitoring using MEMS sensor and bluetooth wireless communication module. First, in order to prove the suitability of MEMS sensor for the bridge measurement, its ranges of measuring acceleration and of frequency response were experimented. Also, the quality of wireless communication was tested by an experiment on long-distance communication for the knowledge of maximum communication distance, and also by an experiment on the data transmit-receive capability both inside and outside of a steel box bridge. Later, placing the wireless acceleration sensor system that had been developed in our lab on a bridge in public service, we acquired vibration data from the bridge under traffic load and analyzed its dynamic characteristics in realtime. For the analysis of the data, NExT & ERA algorithm were employed. The result of analysis was compared to the FE analysis of the same bridge, and the comparison made it possible to evaluate the performance of wireless acceleration sensor system. As a result, it was proven that the wireless acceleration sensor system developed with the use of MEMS sensor and bluetooth wireless communication module could be effectively applied to the measurement of structure whose vibration feature was low frequency like a bridge.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.2
• /
• pp.233-238
• /
• 2020

Most deep learning (DL) approaches for bridge damage localization based on a structural health monitoring system commonly use supervised learning-based DL models. The supervised learning-based DL model requires the response data obtained from sensors on the bridge and also the label which indicates the damaged state of the bridge. However, it is impractical to accurately obtain the label data in fields, thus, the supervised learning-based DL model has a limitation in that it is not easily applicable in practice. On the other hand, an unsupervised learning-based DL model has the merit of being able to train without label data. Considering this advantage, this study aims to propose and theoretically validate a damage localization approach for bridges using a variational autoencoder, a representative unsupervised learning-based DL network: as a result, this study indicated the feasibility of VAE for damage localization.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.27 no.3
• /
• pp.385-392
• /
• 2009

This study aims to methodology a system which is able to monitor and configuration management of long span bridge in real time using multi GPS. Through setting up many GPS at the important points of long span bridge and measuring displacement in real time, over all 3D configuration of bridge could be analyzed. Behavior analyzing system developed in this study is able to digitize and visualize the overall and points displacement of bridge and deal with events actively. Also it is able to calculate statistical data related to analyze behavior through the constricting database of measuring data.