• Computers and Concrete
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• v.23 no.6
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• pp.445-457
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• 2019

Cracks are an important distress of concrete bridges, and may reduce the life and safety of bridges. However, the traditional manual crack detection means highly depend on the experience of inspectors. Furthermore, it is time-consuming, expensive, and often unsafe when inaccessible position of bridge is to be assessed, such as viaduct pier. To solve this question, the real-time automatic crack detecting system with unmanned aerial vehicle (UAV) become a choice. This paper designs a new automatic detection system based on real-time comprehensive image processing for bridge crack. It has small size, light weight, low power consumption and can be carried on a small UAV for real-time data acquisition and processing. The real-time comprehensive image processing algorithm used in this detection system combines the advantage of connected domain area, shape extremum, morphology and support vector data description (SVDD). The performance and validity of the proposed algorithm and system are verified. Compared with other detection method, the proposed system can effectively detect cracks with high detection accuracy and high speed. The designed system in this paper is suitable for practical engineering applications.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.96-104
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• 2003

To assess tunnel safety, cracks in tunnel lining are measured by inspectors who observe cracks with their eyes. A manual inspection is, however, slow and subjective. This paper, therefore, proposes vision-based inspection system for measuring cracks in the tunnel lining that inspects cracks fast and objective. The system is consisted of an on-vehicle system and a lab system. An on-vehicle system acquires image data with line CCD camera. A lab system extracts crack then inform their thickness, length and orientation by using image processing. To improve accuracy of crack recognition the geometric properties of a crack was applied to image processing. The proposed system were verified with experiments in both laboratory and field environment.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.64-77
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• 2012

In this study, the crack detecting system with digital image processing techniques based on the mathematical morphology method was developed to detect cracks in concrete structures. In the developed system, the image combining technique of reconstructing multiple images as an entire single image considering efficient management of analysis results was applied as an additional module. The developed system was verified through a field test with the cracked concrete culvert and the crack width of 0.2 mm was able to be detected in the 40m span. In the image analysis, the difference between calculated crack width and actual crack width were less than 0.08mm. For image combination in the stitching test of pattern images, the stitched image was identical with the original picture of entire subject in the visual perception level.

• Journal of the Korean Institute of Gas
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• v.4 no.1 s.9
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• pp.49-54
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• 2000

The DCPD(Direct Current Potential Drop) method has been adopted for the crack measurement of a structure. The objective of this paper is to develop a multi-channel DCPD system not only for detecting crack depth, but also for determining the accurate shape of the surface crack. For this purpose, an exclusive software was also developed. In order to verify the developed DCPD system it was initially tested on a CT specimen, and subsequently was applied to a wide plate specimen. The developed multi-channel DCPD system was proven to provide an efficient and accurate measurement of a surface crack during the crack growth.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.6
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• pp.950-956
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• 2013

This paper describes a sensitivity-coefficient-based iterative method for detecting cracks in a structure. The sensitivity coefficients of a cracked structure are obtained by changing its eigenvectors. The proposed method is applied to a cracked cantilever. The crack is modeled as a rotational stiffness. The predicted cracks are in good agreement with those from a structural reanalysis of the cracked structure.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1399-1406
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• 2011

As a result of the examination analyzed loop type of Detecting the Broken Rail Monitoring System as a part of prevention of train derailment, installed in the Seoul Metro No. 2 subway line 98.51m section which is Samsung to Seolleung, we found that it is possible to detect crack location(Thermit welding: 48.18m) within the margin of error of ${\pm}1m$ accurately As analysis of the first day, third day, fifty day, and seventh day periodically, we found that Fresnel reflection happened where the crack location 48.18m. However other 3 branches show loss by bending of optical cable(spread reflection from the outside impact).

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1928-1937
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• 2003

Effect of elastic modulus mismatch on the contact crack initiation is investigated to find major parameters in designing desirable surface-coated system. Silicon nitride coated soft materials with various elastic modulus mismatch, E$\_$c//E$\_$s/＝1.06∼356 are prepared for the analysis. Hertzian contact test is conducted for producing contact cracks and the acoustic emission detecting technique for measuring the critical load of crack initiation. The implication is that coating thickness and material strength are controllable parameters to prevent the initiation of contact cracks resulted from the elastic modulus mismatch in the hard ceramic coating layer on the soft materials.

• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.33-52
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• 2017

A cantilever beam with a breathing crack is studied to improve the breathing crack identification sensitivity by the parametric optimization of sample entropy and wavelet transformation. Crack breathing is a special bi-linear phenomenon experienced by fatigue cracks which are under dynamic loadings. Entropy is a measure, which can quantify the complexity or irregularity in system dynamics, and hence employed to quantify the bi-linearity/irregularity of the vibration response, which is induced by the breathing phenomenon of a fatigue crack. To improve the sensitivity of entropy measurement for crack identification, wavelet transformation is merged with entropy. The crack identification is studied under different sinusoidal excitation frequencies of the cantilever beam. It is found that, for the excitation frequencies close to the first modal frequency of the beam structure, the method is capable of detecting only 22% of the crack depth percentage ratio with respect to the thickness of the beam. Using parametric optimization of sample entropy and wavelet transformation, this crack identification sensitivity is improved up to 8%. The experimental studies are carried out, and experimental results successfully validate the numerical parametric optimization process.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.4
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• pp.593-599
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• 2022

In this study, a crack monitoring system capable of detecting cracks based on image processing techniques was developed to effectively check cracks, which are the main damage of concrete structures, and a program capable of imaging and analyzing cracks was developed using machine vision. This system provides objective and quantitative data by replacing the appearance inspection that checks cracks with the naked eye. The verification of the development system was applied to the construction site of a self-healing concrete water tank to monitor the crack and the amount of change in the crack width according to age. In the case of crack width detected by image analysis, the difference from the measured value using a digital microscope was up to 0.036 mm, and the crack healing effect of self-healing concrete could be confirmed through the reduction of crack width.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.11
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• pp.163-170
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• 2019

Most of the current crack investigation work consists of visual inspection using simple measuring equipment such as crack scale. These methods involve the subjection of the inspector, which may lead to differences in the inspection results prepared by the inspector, and may lead to a large number of measurement errors. So, this study proposes an image-based crack detection method to enhance objectivity and efficiency of concrete crack investigation. In this study, YOLOv2 was used to determine the presence of cracks in the image information to ensure the speed and accuracy of detection for real-time analysis. In addition, we extracted shapes of cracks and calculated quantitatively, such as width and length using various image processing techniques. The results of this study will be used as a basis for the development of image-based facility defect diagnosis automation system.