• Journal of the Korea institute for structural maintenance and inspection
• /
• v.8 no.1
• /
• pp.165-174
• /
• 2004

This research develops a technique which uses energy dissipation ratio in order to monitor the structural health on real time basis. For real-time monitoring, we employ the NExT and the ERA which enable us to obtain real-time data. Energy dissipation ratio is calculated from those data only with the damping and natural frequency of the structure, and from the calculated values we develop an algorithm (Energy dissipation method) which decides the damage degree of structure. The Energy dissipation method developed in this research is proved to be valid by comparison with other methods like the eigenparameter method and the MAC. Especially this method enables us to save measuring time and data which are the most important in real-time monitoring, and its use of the ambient vibration also makes it easy to monitor the whole structure and its damage points.

• International Journal of Aeronautical and Space Sciences
• /
• v.13 no.3
• /
• pp.323-331
• /
• 2012

A simple and robust methodology is presented to determine the location and amount of crack in beam like structures based on the incremental particle swarm optimization technique. A comparison is made for assessing the performance of standard particle swarm optimization and the incremental particle swarm optimization technique for detecting crack in structural members. The objective function is formulated using the measured natural frequency of the intact structure and the frequency obtained from the finite element simulation. The outcomes of the simulated results demonstrate that the developed method is capable of detecting and estimating the extent of damages with satisfactory precision.

• Structural Engineering and Mechanics
• /
• v.43 no.3
• /
• pp.371-394
• /
• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Structural Monitoring and Maintenance
• /
• v.3 no.4
• /
• pp.395-406
• /
• 2016

Modal parameter identification has received much attention recently for their usefulness in earthquake engineering, damage detection and structural health monitoring. The identification method based on Matrix Pencil technique is adopted in this paper to identify structural modal parameters, such as natural frequencies, damping ratios and modal shapes using impulse vibration responses. This method can also be applied to dynamic responses induced by stationary and white-noise inputs since the auto- and cross-correlation function of the two outputs has the same form as the impulse response dynamic functions. Matrix Pencil method is very robust to noise contained in the measurement data. It has a lower variance of estimates of the parameters of interest than the Polynomial Method, and is also computationally more efficient. The numerical simulation results show that this technique can identify modal parameters accurately even if the noise level is high.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.1035-1040
• /
• 2024

South Korea has seen an increased demand for road maintenance, since they experienced a rapid industrialization in 1960-70s. Between 2019 and the end of 2022, the total national expenditure on road maintenance steadily rose from KRW 3.4 trillion to KRW 4.5 trillion. Roads, responsible for about 80% of the nation's transportation, significantly affect ride quality, safety and maintenance costs. Among the different perspectives, this study focuses on the prevalence of potholes. Over 24,000 pothole instances are reported on highways in the past five years, which raises concerns due to various direct and indirect effects on road maintenance and safety issues. Various methods, including vision-based, vibration-based, and 3D reconstruction-based techniques, have been proposed for pothole detection and inspection. Vision-based methods effectively count and measure pothole shapes but which are sensitive to lighting conditions. Vibration-based methods offer cost-effectiveness, although it may not provide precise pothole shape information. 3D reconstruction-based methods deliver accurate shape measurements, while it comes with higher costs. To establish an effective road maintenance system, prioritization criteria for potholes is required to be established and applied. These criteria may vary across countries or regions. For example, in the United States, potholes are classified based on depth into Low (<25mm deep), Moderate (25 to 50mm deep), and High (>50mm deep). In conclusion, this research addresses this research challenge of road damage and potholes in South Korea by exploring various pothole classification standards and utilizing advanced technology to develop an efficient road maintenance system. The outcome would benefit improved road infrastructure management and enhanced safety.

• Journal of Sensor Science and Technology
• /
• v.32 no.3
• /
• pp.199-206
• /
• 2023

This study presents a novel monitoring technique for underwater high-voltage direct current (HVDC) cables based on the Distributed Acoustic Sensor (DAS). The proposed technique utilizes vibration and acoustic signals generated on HVDC cables to monitor their condition and detect events such as earthquakes, shipments, tidal currents, and construction activities. To implement the monitoring system, a DAS based on phase-sensitive optical time-domain reflectometry (Φ-OTDR) system was designed, fabricated, and validated for performance. For the HVDC cable monitoring experiments, a testbed was constructed on land, mimicking the cable burial method and protective equipment used underwater. Defined various scenarios that could cause cable damage and conducted experiments accordingly. The developed DAS system achieved a maximum measurement distance of 50 km, a distance measurement interval of 2 m, and a measurement repetition rate of 1 kHz. Extensive experiments conducted on HVDC cables and protective facilities demonstrated the practical potential of the DAS system for monitoring underwater and underground areas.

• Structural Engineering and Mechanics
• /
• v.75 no.4
• /
• pp.519-527
• /
• 2020

Dynamic analysis of a vehicle-track coupling system is important to structural design, damage detection and condition assessment of the structural system. Deterministic analysis of the vehicle-track coupling system has been extensively studied in the past, however, the structural parameters of the coupling system have uncertainties in engineering practices. It is essential to treat the parameters of the vehicle-track coupling system with consideration of uncertainties. In this paper, a method for predicting the bounds of the vehicle-track coupling system responses with uncertain parameters is presented. The uncertain system parameters are modeled as fuzzy variables instead of conventional random variables with known probability distributions. Then, the dynamic response functions of the coupling system are transformed into a component function based on the high dimensional representation approximation. The Lagrange interpolation method is used to approximate the component function. Finally, the bounds of the system's dynamic responses can be predicted by using Monte Carlo method for the interpolation polynomials of the Lagrange interpolation function. A numerical example is introduced to illustrate the ability of the proposed method to predict the bounds of the system's dynamic responses, and the results are compared with the direct Monte Carlo method. The results show that the proposed method is effective and efficient to predict the bounds of the system's dynamic responses with fuzzy variables.

• Structural Monitoring and Maintenance
• /
• v.3 no.1
• /
• pp.91-114
• /
• 2016

In this paper, recent research trends and activities on structural health monitoring (SHM) of civil infrastructure in Korea are reviewed. Recently, there has been increasing need for adopting smart sensing technologies to SHM, so this review focuses on smart sensing, monitoring, and assessment for civil infrastructure. Firstly, the research activities on smart sensor technology is reviewed including optical fiber sensors, piezoelectric sensors, wireless smart sensors, and vision-based sensing system. Then, a brief overview is given to the recent advances in smart monitoring and assessment techniques such as vibration-based global monitoring techniques, local monitoring with piezoelectric materials, decentralized monitoring techniques for wireless sensors, wireless power supply and energy harvest. Finally, recent joint SHM activities on several test beds in Korea are discussed to share the up-to-date information and to promote the smart sensors and monitoring technologies for applications to civil infrastructure. It includes a Korea-US joint research on test bridges of the Korea Expressway Corporation (KEC), a Korea-US-Japan joint research on Jindo cable-stayed bridge, and a comparative study for cable tension measurement techniques on Hwamyung cable-stayed bridge, and a campaign test for displacement measurement techniques on Sorok suspension bridge.

• Smart Structures and Systems
• /
• v.3 no.3
• /
• pp.341-356
• /
• 2007

A good understanding of normal modal variability of civil structures due to varying environmental conditions such as temperature and wind is important for reliable performance of vibration-based damage detection methods. This paper addresses the quantification of wind-induced modal variability of a cable-stayed bridge making use of one-year monitoring data. In order to discriminate the wind-induced modal variability from the temperature-induced modal variability, the one-year monitoring data are divided into two sets: the first set includes the data obtained under weak wind conditions (hourly-average wind speed less than 2 m/s) during all four seasons, and the second set includes the data obtained under both weak and strong (typhoon) wind conditions during the summer only. The measured modal frequencies and temperatures of the bridge obtained from the first set of data are used to formulate temperature-frequency correlation models by means of artificial neural network technique. Before the second set of data is utilized to quantify the wind-induced modal variability, the effect of temperature on the measured modal frequencies is first eliminated by normalizing these modal frequencies to a reference temperature with the use of the temperature-frequency correlation models. Then the wind-induced modal variability is quantitatively evaluated by correlating the normalized modal frequencies for each mode with the wind speed measurement data. It is revealed that in contrast to the dependence of modal frequencies on temperature, there is no explicit correlation between the modal frequencies and wind intensity. For most of the measured modes, the modal frequencies exhibit a slightly increasing trend with the increase of wind speed in statistical sense. The relative variation of the modal frequencies arising from wind effect (with the maximum hourly-average wind speed up to 17.6 m/s) is estimated to range from 1.61% to 7.87% for the measured 8 modes of the bridge, being notably less than the modal variability caused by temperature effect.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.2
• /
• pp.21-30
• /
• 2014

The use of induction motors has been recently increasing in a variety of industrial sites, and they play a significant role. This has motivated that many researchers have studied on developing fault detection and classification systems of induction motors in order to reduce economical damage caused by their faults. To early identify induction motor faults, this paper effectively estimates spectral envelopes of each induction motor fault by utilizing a linear prediction coding (LPC) analysis technique and an expectation maximization (EM) algorithm. Moreover, this paper classifies induction motor faults into their corresponding categories by calculating Mahalanobis distance using the estimated spectral envelopes and finding the minimum distance. Experimental results show that the proposed approach yields higher classification accuracies than the state-of-the-art conventional approach for both noiseless and noisy environments for identifying the induction motor faults.