• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.4
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• pp.313-319
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• 2017

Fiber optics sensors that have been mainly applied to aerospace areas are now finding applicability in other areas, such as transportation, including railways. Among the sensors, the fiber Bragg grating (FBG) sensors have led to a steep increase due to their properties of absolute measurement and multiplexing capability. Generally, the FBG sensors adhere to structures and sensing modules using adhesives such as an epoxy. However, the measurement errors that occurred when the FBG sensors were used in a long-term application, where they were exposed to environmental thermal load, required calibration. For this reason, the thermal curing of adhesives needs to be investigated to enhance the reliability of the FBG sensor system. This can be done at room temperature through cyclic thermal load tests using four types of specimens. From the test results, it is confirmed that residual compressive strain occurs to the FBG sensors due to an initial cyclic thermal load. In conclusion, signals of the FBG sensors need to be stabilized for applying them to a long-term SHM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.64-71
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• 2017

A damage estimation method is presented for jacket-type support structure of offshore wind turbine using a change of modal properties due to damage and committee of neural networks for effective structural health monitoring. For more practical monitoring, it is necessary to monitor the critical and prospective damaged members with a limited number of measurement locations. That is, many data channels and sensors are needed to identify all the members appropriately because the jacket-type support structure has many members. This is inappropriate considering economical and practical health monitoring. Therefore, intensive damage estimation for the critical members using a limited number of the measurement locations is carried out in this study. An analytical model for a jacket-type support structure which can be applied for a 5 MW offshore wind turbine is established, and a training pattern is generated using the numerical simulations. Twenty damage cases are estimated using the proposed method. The identified damage locations and severities agree reasonably well with the exact values and the accuracy of the estimation can be improved by applying the committee of neural networks. A verification experiment is carried out, and the damage arising in 3 damage cases is reasonably identified.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.6
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• pp.541-547
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• 2017

Climate change has become the main cause of the exacerbation in natural disasters. Social Overhead Capital(SOC) structure needs to be checked for displacement and crack periodically to prevent damage and the collapse caused by natural disaster and ensure the safety. For efficient structure maintenance, the optical image technology is applied to the Structure Health Monitoring(SHM). However, optical image is sensitive to environmental factors. So it is necessary to verify its validity. In this paper, the accuracy of estimating the vertical displacement was verified with respect to environmental condition such as natural light, measurement distance, and the number of image sheets. The result of experiments showed that the effect of natural light on accuracy of estimating vertical displacement was the greatest of all. The measurement angle which was affected by the change in measurement distance was also important to check the vertical displacement. These findings will be taken into account by applying appropriate environmental condition to minimize errors when the bridge was measured by camera. It will also enable the application of optical images to the SHM.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6A
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• pp.389-398
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• 2012

In this study, structural strain responses of the jacket-type Uldolmok tidal current power plant structure under severe tidal environments were measured and analyzed using long-term measurement system during construction and also operation. It was observed that there were significant changes in strain responses at the steps of jacket lifting, block loading, pile ejection and insertion. Strains due to dead loads and tidal loads were analyzed before and after removal of a jacket leg, and it was also found that the strains due to dead load were much significantly changed after jacket leg removal. From the measurement data during operation, it was found that strain responses were fluctuated with M2 and M4 tidal periods and also relatively short period of about 10 min due to the peculiar tidal characteristics in the Uldolmok strait. Finally, the neural network-based non-parametric estimation models were investigated to build up the signal-based structural damage monitoring system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.1-8
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• 2015

Wind power systems have gained much attention due to the relatively high reliability, good infrastructures and cost competitiveness to the fossil fuels. Advances have been made to increase the power efficiency of wind turbines while less attention has been focused on structural integrity assessment of structural sub-systems such as towers and foundations. Among many parameters for integrity assessment, the most perceptive parameter may be the induced horizontal displacement at the hub height although it is very difficult to measure particularly in large-scale and high-rise wind turbine structures. This study proposes an indirect displacement estimation scheme based on the combined use of inclinometers and accelerometers for more convenient and cost-effective measurements. To this end, (1) the formulation for data fusion of inclination and acceleration responses was presented and (2) the proposed method was numerically validated on an NREL 5 MW wind turbine model. The numerical analysis was carried out to investigate the performance of the propose method according to the number of sensors, the resolution and the available sampling rate of the inclinometers to be used.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.81-88
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• 2021

Structural health monitoring (SHM) systems have attracted considerable interest owing to the frequent earthquakes over the last decade. Smart concrete is a technology that can analyze the state of structures based on their electro-mechanical behavior. On the other hand, most research on the self-sensing response of smart concrete generally investigated the electro-mechanical behavior of smart concrete under a static loading rate, even though the loading rate under an earthquake would be much faster than the static rate. Thus, this study evaluated the electro-mechanical behavior of smart ultra-high-performance concrete (S-UHPC) at three different loading rates (1, 4, and 8 mm/min) using a Universal Testing Machine (UTM). The stress-sensitive coefficient (SC) at the maximum compressive strength of S-UHPC was -0.140 %/MPa based on a loading rate of 1 mm/min but decreased by 42.8% and 72.7% as the loading rate was increased to 4 and 8 mm/min, respectively. Although the sensing capability of S-UHPC decreased with increased load speed due to the reduced deformation of conductive materials and increased microcrack, it was available for SHM systems for earthquake detection in structures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.1-9
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• 2016

Railroad bridges account for 25% of the entire high-speed rail network. Railway bridges are subject to gradual structural degradation or fatigue accumulation due to consistent and repeating excitation by fast moving trains. Wireless sensing technology has opened up a new avenue for bridge health monitoring owing to its low-cost, high fidelity, and multiple sensing capability. On the other hand, measuring the transient response during train passage is quite challenging that the current wireless sensor system cannot be applied due to the intrinsic time delay of the sensor network. Therefore, this paper presents a framework for monitoring such transient responses with wireless sensing systems using 1) real-time excessive vibration monitoring through ultra-low-power MEMS accelerometers, and 2) post-event time synchronization scheme. The ultra-low power accelerometer continuously monitors the vibration and trigger network when excessive vibrations are detected. The entire network of wireless smart sensors starts sensing through triggering and the post-event time synchronization is conducted to compensate for the time error on the measured responses. The results of this study highlight the potential of detecting the impact load and triggering the entire network, as well as the effectiveness of the post-event time synchronized scheme for compensating for the time error. A numerical and experimental study was carried out to validate the proposed sensing hardware and time synchronization method.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.4
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• pp.20-29
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• 2022

The operational modal analysis (OMA) technique, which extracts the modal parameters of a structural system using ambient vibrations, has been actively developed as a field of structural health monitoring of cable-supported bridges. In this paper, the short and long-term modal parameters of a cable-stayed bridge were evaluated using the acceleration data obtained from the two ambient vibration tests (AVTs) and three years of continuous measurements. A total of 27 vertical modes and 1 lateral mode in the range 0.1 ~ 2.5 Hz were extracted from the high-resolution AVTs which were conducted in the 6th and 19th years after its completion. Existing OMA methods such as Peak-Picking (PP), Eigensystem Realization Algorithm with Data Correlation (ERADC), Frequency Domain Decomposition (FDD) and Time Domain Decomposition (TDD) were applied for modal parameters extraction, and it was confirmed that there was no significant difference between the applied methods. From the correlation analysis between long-term natural frequencies and environmental factors, it was confirmed that temperature change is the dominant factor influencing natural frequency fluctuations. It was revealed that the decreased natural frequencies of the bridge were not due to changes in structural performance and integrity, but to the environmental effects caused by the temperature difference between the two AVTs. In addition, when the TDD technique is applied, the accuracy of extracted mode shapes is improved by adding a proposed algorithm that normalizes the sequence so that the autocorrelations at zero lag equal 1.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.308-315
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• 2009

Because the attenuation of AE signal in composite materials is relatively higher than that of metallic materials, it is required to develop a damage assessment technique less affected by the attenuation property of composite materials in order to use AE sensing as a damage detection method. In the signal processing procedure, it is profitable to use the leading wave that arrives first because the leading wave is less influenced by the boundary conditions. Using wavelet transform, we investigated the frequency characteristics of impact induced AE signals focused on the leading wave in advance and chose the key factors to discriminate the damaged condition quantitatively. In this research, we established a damage assessment technique using the sharing percentage of the wavelet detail components of AE signal, and conducted a low-velocity impact test on composite laminates to confirm the feasibility of the proposed signal processing method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.799-804
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• 2013

The sensor/actuator active sensor diagnostics procedure, where the sensors/actuators are confirmed to be functioning properly during operation, is a critical component to successfully complete the structural health monitoring (SHM) process with large numbers of active sensors typically installed in a structure. The basis of this process is to track the changes in the capacitive value of piezoelectric materials, which shows up in measured admittance. Due to the temperature dependent nature of piezoelectric materials, we investigated the effects of temperature variations on sensor diagnostic process. The effect of temperature variations found to be remarkable, modifying the measured capacitive values significantly. In addition we analyzed the effect of bonding agents between a PZT patch and a host structure. This paper summarizes considerations needed to develop such sensor diagnostic processes, experimental procedures and results, and additional issues that can be used as guidelines for future investigations.