• 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.

• Smart Structures and Systems
• /
• v.22 no.4
• /
• pp.481-493
• /
• 2018

Ultrasonic guided waves have attracted increasing attention for non-destructive testing (NDT) and structural health monitoring (SHM) of bridge cables. They offer advantages like single measurement, wide coverage of acoustical field, and long-range propagation capability. To design defect detection systems, it is essential to understand how guided waves propagate in cables and how to select the optimal excitation frequency and mode. However, certain cable characteristics such as multiple wires, anchorage, and polyethylene (PE) sheath increase the complexity in analyzing the guided wave propagation. In this study, guided wave modes for multi-wire bridge cables are identified by using a semi-analytical finite element (SAFE) technique to obtain relevant dispersion curves. Numerical results indicated that the number of guided wave modes increases, the length of the flat region with a low frequency of L(0,1) mode becomes shorter, and the cutoff frequency for high order longitudinal wave modes becomes lower, as the number of steel wires in a cable increases. These findings were used in design of transducers for defect detection and selection of the optimal wave mode and frequency for subsequent experiments. A magnetostrictive transducer system was used to excite and detect the guided waves. The applicability of the proposed approach for detecting and locating wire breakages was demonstrated for a cable with 37 wires. The present ultrasonic guided wave method has been found to be very responsive to the number of brokenwires and is thus capable of detecting defects with varying sizes.

• Earthquakes and Structures
• /
• v.17 no.5
• /
• pp.511-519
• /
• 2019

The concrete gravity dam is one of the most important parts of the nation's infrastructure. Besides the benefits, the dam also has some potentially catastrophic disasters related to the life of citizens directly. During the lifetime of service, some degradations in a dam may occur as consequences of operating conditions, environmental aspects and deterioration in materials from natural causes, especially from dynamic loads. Cumulative Absolute Velocity (CAV) plays a key role to assess the operational condition of a structure under seismic hazard. In previous researches, CAV is normally used in Nuclear Power Plant (NPP) fields, but there are no particular criteria or studies that have been made on dam structure. This paper presents a method to calculate the limitation of CAV for the Bohyeonsan Dam in Korea, where the critical Peak Ground Acceleration (PGA) is estimated from twelve sets of selected earthquakes based on High Confidence of Low Probability of Failure (HCLPF). HCLPF point denotes 5% damage probability with 95% confidence level in the fragility curve, and the corresponding PGA expresses the crucial acceleration of this dam. For determining the status of the dam, a 2D finite element model is simulated by ABAQUS. At first, the dam's parameters are optimized by the Minitab tool using the method of Central Composite Design (CCD) for increasing model reliability. Then the Response Surface Methodology (RSM) is used for updating the model and the optimization is implemented from the selected model parameters. Finally, the recorded response of the concrete gravity dam is compared against the results obtained from solving the numerical model for identifying the physical condition of the structure.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.36 no.3
• /
• pp.349-359
• /
• 2016

In order to analytically evaluate buffeting responses, the analysis of wind characteristics such as turbulence intensity, turbulence length, gust, roughness coefficient, etc must be a priority. Static aerodynamic force coefficients, flutter coefficients, structural damping ratios, aerodynamic damping ratios and natural frequencies affect the analytical responses. The bridge interested in this paper has being been used for 32 years. As the time passes, current terrain conditions around the bridge are different markedly from the conditions it was built 32 years ago. Also, wind environments were considerably varied by the climate change. For this reason, it is necessary to evaluate the turbulence intensity, length, spectrum and roughness coefficient of the bridge site from full-scale measurements using the structural health monitoring system. The evaluation results indicate that wind characteristics of bridge site is analogous to that of open terrain although the bridge is located on the coastal area. To calculate buffeting responses, the analysis variables such as damping ratios, static aerodynamic force coefficients and natural frequency were evaluated from measured data. The analysis was performed with regard to 4 cases. The evaluated variables from measured data are applied to the first and second analysis cases. And the other analysis cases were performed based on Design Guidelines for Steel Cable Supported Bridges. The calculated responses of each analysis cases are compared with the buffeting response measured at less than 25m/s wind speed. It is verified that the responses by the numerical analysis applying the estimated variables based on full-scale measurements are well agreed with the measured actual buffeting responses under wind speed 25m/s. Also, the extreme wind speed corresponding to a recurrence interval 200 years is derived from Gumbel distribution. The derived wind speed for return period of 200 years is 45m/s. Therefore the buffeting responses at wind speed 45m/s is determined by the analysis applying the estimated variables.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.1A
• /
• pp.1-10
• /
• 2012

Along with the development of coasts, islands and mountains, the demand of long-span bridges increases which, in turn, brings forth the construction of cable-supported bridges like suspension and cable-stayed bridges. There are various types of statically indeterminate structures widely applied that supported the main girder with stay cables, main cables, hanger cables with aesthetic structural appearance. As to the cable-supported bridges, the health monitoring of a bridge can be identified by measuring tension force on cable repeatedly. The tension force on cable is measured either by direct measurement of stress of cable using load cell or hydraulic jack, or by vibration method estimating tension force using cable shape and measured dynamic characteristics. In this study, a method to estimate dynamic characteristics of hanger cables by using a digital image processing is suggested. Digital images are acquired by a portable digital camcorder, which is the sensor to remotely measure dynamic responses considering convenient and economical aspects for use. A digital image correlation(DIC) technique is applied for digital image processing, and an image transform function(ITF) to correct the geometric distortion induced from the deformed images is used to estimate subpixel. And, the correction of motion of vision-based measurement system using a fixed object in an image without installing additional sensor can be enhanced the resolution of dynamic responses and modal frequencies of hanger cables.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.4
• /
• pp.779-789
• /
• 2015

Because cable-supported bridges have long spans and large members, their movements and geometrical changes by temperatures tend to be bigger than those of small or medium-sized bridges. Therefore, it is important for maintenance engineers to monitor and assess the effect of temperature on the cable-supported bridges. To evaluate how much the superstructure expands or contracts when subjected to changes in temperature is the first step for the maintenance. Thermal movements of a cable-stayed bridge in service are evaluated by using long-term temperatures and displacements data. Displacements data are obtained from extensometers and newly installed GNSS (Global Navigation Satellite System) receivers on the bridge. Based on the statistical data such as air temperatures, each sensor's temperatures, average temperatures and effective temperatures, correlation analysis between temperatures and displacements has been performed. Average temperatures or effective temperatures are most suitable for the evaluation of thermal movements. From linear regression analysis between effective temperatures and displacements, the variation rate's of displacement to temperature have been calculated. From additional regression analysis between expansion length's and variation rate's of displacement to temperature, the thermal expansion coefficient and neutral point have been estimated. Comparing these parameters with theoretical and analytical results, a practical procedure for evaluating the real thermal behaviors of the cable-supported bridges is proposed.

• Smart Structures and Systems
• /
• v.10 no.2
• /
• pp.131-154
• /
• 2012

In this paper, it is aimed to determine the seismic behaviour of highway bridges by nondestructive testing using ambient vibration measurements. Eynel Highway Bridge which has arch type structural system with a total length of 216 m and located in the Ayvaclk county of Samsun, Turkey is selected as an application. The bridge connects the villages which are separated with Suat U$\breve{g}$urlu Dam Lake. A three dimensional finite element model is first established for a highway bridge using project drawings and an analytical modal analysis is then performed to generate natural frequencies and mode shapes in the three orthogonal directions. The ambient vibration measurements are carried out on the bridge deck under natural excitation such as traffic, human walking and wind loads using Operational Modal Analysis. Sensitive seismic accelerometers are used to collect signals obtained from the experimental tests. To obtain experimental dynamic characteristics, two output-only system identification techniques are employed namely, Enhanced Frequency Domain Decomposition technique in the frequency domain and Stochastic Subspace Identification technique in time domain. Analytical and experimental dynamic characteristic are compared with each other and finite element model of the bridge is updated by changing of boundary conditions to reduce the differences between the results. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of highway bridges. After finite element model updating, maximum differences between the natural frequencies are reduced averagely from 23% to 3%. The updated finite element model reflects the dynamic characteristics of the bridge better, and it can be used to predict the dynamic response under complex external forces. It is also helpful for further damage identification and health condition monitoring. Analytical model of the bridge before and after model updating is analyzed using 1992 Erzincan earthquake record to determine the seismic behaviour. It can be seen from the analysis results that displacements increase by the height of bridge columns and along to middle point of the deck and main arches. Bending moments have an increasing trend along to first and last 50 m and have a decreasing trend long to the middle of the main arches.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.24 no.6
• /
• pp.451-464
• /
• 2022

The high-level nuclear waste repository is a deep geological disposal system exposed to complex environmental conditions such as high temperature, radiation, and ground-water due to handling spent nuclear fuel. Continuous exposure can lead to cracking and deterioration of the structure over time. On the other hand, the high-level nuclear waste repository requires an ultra-long life expectancy. Thus long-term structural health monitoring is essential. Various sensors such as an accelerometer, earth pressure gauge, and displacement meter can be used to monitor the health of a structure, and a piezoelectric sensor is generally used. Therefore, it is necessary to develop a highly durable sensor based on the durability assessment of the piezoelectric sensor. This study designed an accelerated life test for durability assessment and life prediction of the piezoelectric sensor. Based on the literature review, the number of accelerated stress levels for a single stress factor, and the number of samples for each level were selected. The failure mode and mechanism of the piezoelectric sensor that can occur in the environmental conditions of the high-level waste repository were analyzed. In addition, two methods were proposed to investigate the maximum harsh condition for the temperature stress factor. The reliable operating limit of the piezoelectric sensor was derived, and a reasonable accelerated stress level was set for the accelerated life test. The suggested methods contain economical and practical ideas and can be widely used in designing accelerated life tests of piezoelectric sensors.

• Journal of Korean Society of Steel Construction
• /
• v.17 no.1 s.74
• /
• pp.1-11
• /
• 2005

A bi-level damage detection algorithm that utilizes the dynamic responses of the structure as input and neural network (NN) as pattern classifier is presented. Signal anomaly index (SAI) is proposed to express the amount of changes in the shape of frequency response functions (FRF) or strain frequency response function (SFRF). SAI is calculated using the acceleration and dynamic strain responses acquired from intact and damaged states of the structure. In a bi-level damage identification algorithm, the presence of damage is first identified from the magnitude of the SAI value, then the location of the damage is identified using the pattern recognition capability of NN. The proposed algorithm is applied to an experimental model bridge to demonstrate the feasibility of the algorithm. Numerically simulated signals are used for training the NN, and experimentally-acquired signals are used to test the NN. The results of this example application suggest that the SAI-based pattern recognition approach may be applied to the structural health monitoring system for a real bridge.