• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.61-73
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• 2009

In this paper, hybrid health monitoring techniques using acceleration-impedance features are newly proposed to detect two damage-type in steel plate-girder bridges, which are girder's stiffness-loss and support perturbation. The hybrid techniques mainly consists of three sequential phases: 1) to alarm the occurrence of damage in global manner, 2) to classify the alarmed damage into subsystems of the structure, and 3) to estimate the classified damage in detail using methods suitable for the subsystems. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the alarmed damage is classified into subsystems by recognizing patterns of impedance features. In the final phase, the location and the extent of damage are estimated by using modal strain energy-based damage index method and root mean square deviation (RMSD) method. The feasibility of the proposed hybrid technique is evaluated on a laboratory-scaled steel plate-girder bridge model for which hybrid acceleration-impedance signatures were measured for several damage scenarios. Also, the effect of temperature on the accuracy of the impedance-based damage monitoring results are experimentally examined from combined scenarios of support damage cases and temperature changes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.135-146
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• 2008

In this paper, a hybrid damage monitoring scheme for prestressed concrete (PSC) girder bridges by using sequential acceleration and impedance signatures is newly proposed. Damage types of interest include prestress-loss in tendon and flexural stiffness-loss in a concrete girder. The hybrid scheme mainly consists of three sequential phases: damage alarming, damage classification, and damage estimation. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the type of damage is classified into either prestress-loss or flexural stiffness-loss by recognizing patterns of impedance features. In the third phase, the location and the extent of damage are estimated by using two different ways: a mode shape-based damage detection to detect flexural stiffness-loss and a natural frequency-based prestress prediction to identify prestress-loss. The feasibility of the proposed scheme is evaluated on a laboratory-scaled PSC girder model for which hybrid vibration-impedance signatures were measured for several damage scenarios of prestress-loss and flexural stiffness-loss.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.2
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• pp.33-40
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• 2020

Various studies have been conducted on the structural health monitoring using optical fiber. Optical fibers can be used to measure multiple and distributed strain. Among the optical fiber sensors, FBG sensor has advantages of dynamic response measurement and high precision, but the number of measurement points is limited. Distributed fiber sensors, represented by distributed Brillouin sensors, usually have more than 1000 measurement points, but the low sampling rate makes dynamic measurements impossible. In this study, a hybrid nerve sensor system using only the advantages of the FBG sensor and the distributed Brillouin sensor has been proposed. Laboratory experiments were performed to verify the proposed system, and the accuracy and reproducibility were verified by comparing with commercial sensors. Applying the proposed system, dynamic response ambient measurements are used to evaluate the global state of the structure. When an abnormal condition is detected, the local condition of the structure is evaluated by static response measurement using the distributed measurement system. The proposed system can be used for efficient structural health monitoring.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.546-548
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• 2010

This paper proposes a new baseline-free TR-based SHM method in which the time-reversal (TR) property of the guided Lamb waves is utilized. The new TR-based SHM method has two distinct features when compared with the other existing SHM techniques: (1) The measurement- based backward TR process is replaced by the computation-based process (2) In place of the comparison method most commonly used for SHM, the TOF information of the damage signal extracted from the reconstructed signal is utilized for the damage diagnosis. For the damage diagnosis, the imaging method is adopted to efficiently detect damage by representing the damage as an image. The proposed TR-based SHM technique is then validated through the damage diagnosis experiment for an aluminum plate with a damage at different locations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.543-550
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• 2018

The rapid growth of IoT technology induced by the fourth industrial revolution has resulted in research into various types of wireless sensors, and applications based on this technology are prevalent in many areas. However, among the various sites where this technology is used, railway bridges and tunnels with lengths of tens of kilometers have problems with data acquisition, due to the signal noise induced by the long distance measurement and EMI induced by the high voltage power feeding system, when conventional electric sensors are used. To overcome these problems, many studies on fiber optic sensors have been conducted as a substitute for the conventional electric sensors. However, restrictions on the types of fiber optic sensors have limited their application in railways. For this reason, a hybrid measurement system with IoT based wireless data communication, in which both electric and fiber optic sensors can be applied simultaneously, has been developed. In this study, in order to evaluate the applicability of the hybrid measurement system developed in the previous study, a real-time test for 4 types of measurement environments, which reflect possible railway sites, is performed. As a result, it was confirmed that the signals from both the electric and fiber optic sensors, which were acquired at a remote area in real-time, showed good agreement with each other and that this measurement system has the potential to handle sensors with a sampling rate of 2.5 kHz. In the future, it is expected that the IoT-based hybrid measurement system will contribute to the improvement of structural safety by enabling real-time structural health monitoring when applied to various measurement sites.