• Smart Structures and Systems
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• v.21 no.2
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• pp.171-185
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• 2018

Maintenance of deteriorated bridge structures has always been one of the challenging issues in developing countries as it is directly related to daily life of people including trade and economy. An effective maintenance strategy is highly dependent on timely inspections on the bridge health condition. This study is intended to investigate an approach for detecting bridge damage for the long-term health monitoring by use of copula theory. Long-term measured data for the seven-span plate-Gerber bridge is investigated. Autoregressive time series models constructed for the observed accelerations taken from the bridge are utilized for the computation of damage indicator for the bridge. The copula model is used to analyze the statistical changes associated with the modal parameters. The changes in the modal parameters with the time are identified by the copula statistical properties. Applicability of the proposed method is also discussed based on a comparison study among other approaches.

• Corrosion Science and Technology
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• v.3 no.2
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• pp.39-46
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• 2004

Development and application of structural health monitoring system in Korea have become active since the early 1990's. In earlier applications, health monitoring systems were installed in several existing bridges in order to collect initial field data by full scale load capacity test for design verification and subsequently monitor long-term performance and durability of the bridge as part of an inspection and maintenance program. Recently, modem and integrated monitoring systems have been introduced in most of the newly constructed long-span bridges since the design stage. This paper outlines the progresses and applications of monitoring systems in Korea for both existing and newly constructed bridges and describes their aims and characteristics.

• Smart Structures and Systems
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• v.15 no.3
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• pp.523-541
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• 2015

Structural health monitoring of steel truss bridge based on changes in modal properties was investigated in this study. Vibration measurements with five sensors were conducted at an existing Warren truss bridge with partial fractures in diagonal members before and after an emergency repair work. Modal properties identified by the Eigensystem Realization Algorithm showed evidences of increases in modal damping due to the damage in diagonal member. In order to understand the dynamic behavior of the bridge and possible mechanism of those increases in modal damping, theoretical modal analysis was conducted with three dimensional frame models. It was found that vibrations of the main truss could be coupled internally with local vibrations of diagonal members and the degree of coupling could change with structural changes in diagonal members. Additional vibration measurements with fifteen sensors were then conducted so as to understand the consistency of those theoretical findings with the actual dynamic behavior. Modal properties experimentally identified showed that the damping change caused by the damage in diagonal member described above could have occurred in a diagonal-coupled mode. The results in this study imply that damages in diagonal members could be detected from changes in modal damping of diagonal-coupled modes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.4
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• pp.469-475
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• 2019

A long-term bridge monitoring system has been introduced and is under operation for long-term safety management of the structure. However, it is difficult to assess the condition of the quantitative structural system as it only measures responses and does not measure input loads. To overcome these shortcomings, FBG (Fiber Bragg Grating)-based input load measurement sensors were developed in this paper for measuring highway bridge input loads and their validity was verified through laboratory tests.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.544-547
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• 2008

In 1990, Korea building contractors were indifferent maintenance management cause focus on completion of construction before construction collapsed. Currently, structures monitoring systems are restrictive on large structures. Structures monitoring systems are limited many old and small structures in the whole nation. Recently, we make efforts application Ubiquitous technology as like sensor, sensor network system, and wireless communication system in construction. This paper applies bridge management system using Ubiquitous skill which is real-time monitoring report offering system.

• Smart Structures and Systems
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• v.11 no.5
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• pp.511-531
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• 2013

Recent advances in low-cost remote monitoring systems have made it possible and practical to perform structural health monitoring (SHM) on a large scale. However, it is difficult for a single remote monitoring system to cover a wide range of SHM applications due to the amount of specialization required. For the remote monitoring system to be flexible, sustainable, and robust, this article introduces a new cost-effective, advanced remote monitoring and inspection system named DuraMote that can serve as a next generation supervisory control and data acquisition (SCADA) system for civil infrastructure systems. To evaluate the performance of DuraMote, we conduct experiments at two representative counterpart sites: a bridge and water pipelines. The objectives of this article are to improve upon the existing SCADA by integrating the remote monitoring system (i.e., DuraMote), to describe a prototype SCADA for civil engineering structures, and to validate its effectiveness with long-term field deployment results.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.147-156
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• 2023

Because the behavior of cable bridges is dominated by dynamic response and is relatively complex, short- and long-term field monitoring are often required to evaluate the bridge condition. If a permanent SHMS (Structural Health Monitoring System) is not installed, a portable monitoring system is needed for the checking of bridge condition. In this case, it can be difficult to operate the portable monitoring system due to limited conditions such as power and communication according to the location and type of the bridge. In this study, the portable-based smart structural response monitoring system is developed that can be effectively used for short- and long-term monitoring of cable bridges in Korea and Southeast Asia. The developed system is a multi-channel portable data acquisition and analyzer that can be operated for a long time in the field using its own power supply system, and is included with the automated analysis algorithm for the dynamic characteristics of cable bridges using real-time data. In order to evaluate the field applicability of the developed system, field demonstration was conducted on cable bridges in Korea and Vietnam. Through the demonstration, the reliability and efficiency of field operation of the developed system were confirmed, and additionally, the possibility of application to overseas markets was confirmed in cable bridge monitoring field.

• Smart Structures and Systems
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• v.24 no.2
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• pp.243-256
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• 2019

Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

• Structural Monitoring and Maintenance
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• v.2 no.2
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• pp.145-164
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• 2015

Bridge scour is the predominant cause of overwater bridge failures in North America and around the world. Several sensing systems have been developed over the years to detect the extent of scour so that preventative actions can be performed in a timely manner. These sensing systems have drawbacks, such as signal inaccuracy and discontinuity, installation difficulty, and high cost. Therefore, attempts to develop more efficient monitoring schemes continue. In this study, the viability of using optical dissolved oxygen (DO) probes for monitoring scour depths was explored. DO levels are very low in streambed sediments, as compared to the standard level of oxygen in flowing water. Therefore, scour depths can be determined by installing sensors to monitor DO levels at various depths along the buried length of a bridge pier or abutment. The measured DO is negligible when a sensor is buried but would increase significantly once scour occurs and exposes the sensor to flowing water. A set of experiments was conducted in which four dissolved oxygen probes were embedded at different soil depths in the vicinity of a mock bridge pier inside a laboratory flume simulating scour conditions. The results confirmed that DO levels jumped drastically when sensors became exposed during scour hole evolution, thereby providing discrete measurements of the maximum scour depth. Moreover, the DO probes could detect any subsequent refilling of the scour hole through the deposition of sediments. The effect of soil permeability on the sensing response time was also investigated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.135-142
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• 2004

Two-step identification approach for effective bridge health monitoring is proposed to alleviate the issues associated with many unknown parameters faced in the real structures and to improve the accuracy in the estimate results. It is suitable for on-line monitoring scheme, since the damage assessment is not always needed to be carried out whereas the alarming for damages is to be continuously monitored. In the first step for screening potential damaged members, damage indicator method based on modal strain energy, probabilistic neural networks and the conventional neural networks using grouping technique are used and then the conventional neural network technique is utilized for damage assessment on the screened members in the second step. The proposed methods are verified through a field test on the northern-most span of old Hannam Grand Bridge.