• KIEAE Journal
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• v.7 no.4
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• pp.141-146
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• 2007

It is necessary to guarantee the safety, serviceability and durability of reinforced concrete structures over their service life. However, concrete structures represent a decrease in their durability due to the effects of external environments according to the passage of time, and such degradation in durability can cause structural degradation in materials. In concrete structures, some degradations in durability increase the corrosion of embedded rebars and also decrease the structural performance of materials. Thus, the structural condition assessment of RC materials damaged by corrosion of rebars becomes an important factor that judges needs to apply restoration. In order to detect the damage of reinforced concrete structures, a visual inspection, a nondestructive evaluation method(NDE) and a specific loading test have been employed. However, obscurities for visual inspection and inaccessible members raise difficulty in evaluating structure condition. For these reasons, detection of location and quantification of the damage in structures via structural response have been one of the very important topics in system identification research. The main objective of this project is to develope a methodologies for the damage identification via static responses of the members damaged by durability. Six reinforced concrete beams with variables of corrosion position and corrosion width were fabricated and the damage detections of corroded RC beams were performed by the optimization and the conjugate beam methods using static deflection. In results it is proved that the conjugate beam method could predict the damage of RC members practically.

• Smart Structures and Systems
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• v.2 no.3
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• pp.253-274
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• 2006

The structural monitoring of multi-wire strands is of importance to prestressed concrete structures and cable-stayed or suspension bridges. This paper addresses the monitoring of strands by ultrasonic guided waves with emphasis on the signal processing and automatic defect classification. The detection of notch-like defects in the strands is based on the reflections of guided waves that are excited and detected by magnetostrictive ultrasonic transducers. The Discrete Wavelet Transform was used to extract damage-sensitive features from the detected signals and to construct a multi-dimensional Damage Index vector. The Damage Index vector was then fed to an Artificial Neural Network to provide the automatic classification of (a) the size of the notch and (b) the location of the notch from the receiving sensor. Following an optimization study of the network, it was determined that five damage-sensitive features provided the best defect classification performance with an overall success rate of 90.8%. It was thus demonstrated that the wavelet-based multidimensional analysis can provide excellent classification performance for notch-type defects in strands.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1291-1296
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• 2000

A basis for the direct use of data from nondestructive evaluation methods in bridge management systems is presented. Bridge management systems use integer-valued condition ratings to recognize conditions of bridge elements, to model progression of deterioration, and to determine repair needs. Data from nondestructive evaluation methods can inform management systems on the extent of damage, on the initiation of deterioration processes, and on the exposure of bridge elements to aggressive agents. In addition, data obtained through nondestructive evaluation methods allow the formation of models of specific deterioration process. The use of these data in bridge management systems requires redefinition of condition ratings together with the creation of procedures for automated interpretation of data. By these action, nondestructive evaluation methods are directly used to assign condition ratings, and condition ratings are made into terse form of NDE data that are compatible with present day bridge management systems. This paper reports work in progress to strategic use of nondestructive evaluation methods in bridge management system.

• Computers and Concrete
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• v.32 no.5
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• pp.475-486
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• 2023

Nondestructive evaluation (NDE) is an important task of civil engineering structure monitoring and inspection, but minor damage such as small cracks in local structure is difficult to observe. If cracks continued expansion may cause partial or even overall damage to the structure. Therefore, monitoring and detecting the structure in the early stage of crack propagation is important. The crack detection technology based on machine vision has been widely studied, but there are still some problems such as bad recognition effect for small cracks. In this paper, we proposed a deep learning method based on sweep signals to evaluate concrete surface crack with a width less than 1 mm. Two convolutional neural networks (CNNs) are used to analyze the one-dimensional (1D) frequency sweep signal and the two-dimensional (2D) time-frequency image, respectively, and the probability value of average damage (ADPV) is proposed to evaluate the minor damage of structural. Finally, we use the standard deviation of energy ratio change (ERVSD) and infrared thermography (IRT) to compare with ADPV to verify the effectiveness of the method proposed in this paper. The experiment results show that the method proposed in this paper can effectively predict whether the concrete surface is damaged and the severity of damage.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.2
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• pp.40-48
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• 2012

Steel corrosion in concrete is a main cause of deterioration and early failure of concrete structures. A novel integration of electromagnetic heat induction and infrared (IR) thermography is proposed for nondestructive detection of steel corrosion in concrete, by taking advantage of the difference in thermal characteristics of corroded and non-corroded steel. This paper focuses on experimental investigation of the concept. An inductive heater is developed to remotely heat the embedded steel from concrete surface, which is integrated with an IR camera. Concrete samples with different cover depths are prepared. Each sample is embedded with a single rebar in the middle, resulting an identical cover depth from the front and the back surfaces, which enable heat induction from one surface and IR imaging from the other simultaneously. The impressed current (IC) method is adopted to induce accelerated corrosion on the rebar. IR video images are recorded during the entire heating and cooling periods. The test results demonstrate a clear difference in thermal characteristics between corroded and non-corroded samples. The corroded sample shows higher rates of heating and cooling than those of the non-corroded sample. This study demonstrates a potential for nondestructive detection of rebar corrosion in concrete.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.111-119
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• 2016

Rebound hammer test, SonReb method and concrete core test are most useful testing methods for estimate the concrete compressive strength of deteriorated concrete structures. But the accuracy of the NDE results on the existing structures could be reduced by the effects of the uncertainty of nondestructive test methods, material effects by aging and carbonation, and mechanical damage by drilling of core. In this study, empirical procedure for verifying the in-situ compressive strength of concrete is suggested through the probabilistic analysis on the 268 data of rebound and ultra-pulse velocity and core strengths obtained from 106 bridges. To enhance the accuracy of predicted concrete strength, the coefficients of core strength, and surface hardness caused by ageing or carbonation was adopted. From the results, the proposed equation by KISTEC and the estimation procedures proposed by authors is reliable than previously suggested equation and correction coefficient.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.1
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• pp.34-40
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• 2012

In this study, effects of bonding agent, e.g. epoxy, on the behavior of fundamental guided wave modes propagated in FRP plate bonded on a concrete, are investigated. Global matrix model of multilayered FRP-epoxy-concrete system was constructed to obtain the velocity and attenuation dispersion curves of the fundamental A0 and S0 modes. Two variables, thickness and elastic modulus of epoxy layer, were considered in the dispersion analysis. It was found that both the thickness and the elastic modulus of epoxy layer greatly affect the phase velocity and attenuation of S0 mode while those are negligible for A0 mode. Based on the results, it was concluded that S0 mode is more effective than A0 mode for bonding condition assessment for FRP plate bonded concrete.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.2 s.17
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• pp.1-8
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• 2005

Microwave tomographic imaging technology using a bi-focusing operator has been developed in order to detect the internal voids/objects inside concrete structures. The imaging system consists of several cylindrical or planar array antennas for transmitting and receiving signals, and a numerical focusing operator is applied to the external signals both in transmitting and in receiving fields. In this study, the authors developed 3-dimensional (3D) electromagnetic (EM) imaging technology to detect such damage and to identify exact location of steel rebars or dowel. The authors have developed sub-surface two-dimensional (2D) imaging technique using tomographic antenna array in previous works. In this study, extending the earlier analytical and experimental works on 2D image reconstruction, a 3D microwave imaging system using tomographic antenna way was developed, and multi-frequency technique was applied to improve quality of the reconstructed image and to reduce background noises. Numerical simulation demonstrated that a sub-surface image can be successfully reconstructed by using the proposed tomographic imaging technology. For the experimental verification, a prototype antenna array was fabricated and tested on a concrete specimen.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.4
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• pp.118-125
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• 2014

As the earth's current global warming has caused elevation of sea water temperature, size of storms is foreseen to increase and consequently large damages on port facilities are to be expected. In addition, due to the improved processing efficiency of port cargo volume and increasing necessity for construction of eco-friendly port, demands for various forms of port facilities are anticipated. In this study, two kinds of nondestructive evaluation (NDE) techniques (rebound hardness and ultrasonic pulse velocity methods) are investigated for the effective maintenance of smart green harbor system. A new methodology to estimate the underwater concrete strengths is proposed and its feasibility is verified throughout a series of experimental works.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.367-372
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• 2018

Defects in aging infrastructures such as pre-stressed concrete bridges and cable bridges can cause a collapse of the entire structure. Defects, however, are often located inside of the structures that they are not visible from the outside. For example, in PSC bridges, because reinforcement steels are encased by exterior covers, corrosion and void on the reinforcement steel cannot be detected with a visual inspection. Therefore, in this paper, a new non-destructive evaluation(NDE) method that can detect defects inside of structures is presented. The new method utilizes sending of electrical signals, a method often utilized in electrical engineering to detect any discontinuities on power cables. In order to confirm the applicability and accuracy of the method, some experiments were conducted in the laboratory. And to overcome the hardship of conducting experiments on real structures due to their enormous size, simualtions were conudcted using a commercial program, COMSOL. The results of the experiments were analyzed and compared to confirm the accuracy of the simualtions.