• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2486-2491
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• 2013

There are invisible defects by naked eyes in ceramic material images such as internal stomata, cracks and foreign substances. In this paper we propose a method to detect and extract such defects from ceramic pipe weld zone by applying ART2 learning. In pre-processing, we apply Ends-in Search Stretching to enhance the intensity and then perform fuzzy binarization with triangle type membership function followed by enhanced ART2 that interacts with random input patterns to extract such invisible defects. The experiment verifies that this proposed method is sufficiently effective.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.1
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• pp.10-14
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• 2009

Heat generation mechanism of ultrasound infrared thermography is still not well understood, yet and there are two reliable assumptions of heat generation, friction and thermo-mechanical effect. This paper investigates the principal cause of heat generation at fatigue crack with experimental and numerical approach. Our results show most of heat generation is contributed by friction between crack interface and thermo-mechanical effect is a negligible quantity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.125-137
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• 2009

Acoustic emission-based techniques are being used for the nondestructive inspection of mechanical systems used in service. For reliable fault monitoring related to the crack growth, it is important to identify the dynamical characteristics as well as transient crack-related signals. Widely used methods which are based on physical phenomena of the three damage stages for detecting the crack growth have a problem that crack-related acoustic emission activities overlap in time, therefore it is insufficient to estimate the exact crack growth time. The proposed pattern recognition method uses the dynamical characteristics of acoustic emission as inputs for minimizing false alarms and miss alarms and performs the temporal clustering to estimate the crack growth time accurately. Experimental results show that the proposed method is effective for practical use because of its robustness to changes of acoustic emission caused by changes of pressure levels.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.2
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• pp.180-185
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• 2004

Conventional ultrasonic examination to detect micro and small surface cracks is based on the pulse-echo technique using a normal immersion focused transducer with high frequency, or an angle-beam transducer generating surface waves. It is difficult to make an automatic ultrasonic system that can detect micro and small surface cracks and position in a large structure like steel and ceramic rolls, because of the huge data of inspection and the ambiguous position data of the transducer. In this study, a high-precision scanning acoustic microscope with a 10MHz large-aperture transducer has been used to assess the existence, position and depth of a surface crack from the real-time A, B, C scans obtained by exploiting the ultrasonic diffraction. The ultrasonic method with large aperture transducer has improved the accuracy of the crack depth assessment and also the scanning speed by ten times, compared with the conventional ultrasonic methods.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.5
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• pp.501-509
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• 2001

For the enhancement of ECT reliability on the primary water stress corrosion cracks of nuclear steam generator tubes, of which the occurrence is on the increase, it is important to comprehend the signal characteristics on crack morphology and to select an appropriate probe type. In this paper, the sizing accuracy and the detectability for the inner wall axial cracks of tubes were quantitatively evaluated using the following specimens: the electric discharge machined notches and the corrosion cracks which were developed on the operating steam generator tubes. The difference of eddy current signal characteristics between pancake and axial coil were also Investigated. The results obtained from this study provide a useful information for more precise evaluation on the inner wall axial tracks oi stram generator tubes.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.30-38
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• 2023

As the number of old buildings subject to safety inspection increases, the burden on designated institutions and management entities that are responsible for safety management is increasing. Accordingly, when selecting buildings subject to safety inspection, appropriate safety inspection standards and appropriate technology are essential. The current safety inspection standards for old buildings give low scores when it is difficult to confirm damage such as cracks in structural members due to finishing materials. This causes the evaluation results to be underestimated regardless of the actual safety status of the structure, resulting in an increase in the number of aging buildings subject to safety inspection. Accordingly, this study proposed a thermal imaging technique, a non-destructive and non-contact inspection, to detect cracks inside finishing materials. A concrete specimen was produced to observe cracks inside the finishing material using a thermal imaging camera, and thermal image data was measured by exciting a heat source on the concrete surface and cracked area. As a result of the measurement, it was confirmed that it was possible to observe cracks inside the finishing material with a width of 0.3mm, 0.5mm, and 0.7mm, but it was difficult to determine the cracks due to uneven temperature distribution due to surface peeling and peeling of the wallpaper. Accordingly, as a result of performing data analysis by deriving the amplitude and phase difference of the thermal image data, clear crack measurement was possible for 0.5mm and 0.7mm cracks. Based on this study, we hope to increase the efficiency of field application and analysis through the development of technology using big data-based deep learning in the diagnosis of internal crack damage in finishing materials.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.135-140
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• 2021

In this paper, we propose an on-line mechanism that simultaneously detects cracks and profiling pavement blocks to detect the displacement of ground surface adjacent to the excavation in the urban area. The proposed method utilizes a 2D laser to profile the information about pavement blocks including the depth and distance among them. In particular, it is designed to enable the detection of cracks and portholes at runtime. For the experiment, real data was collected through Gocator, and trainng was carried out using Faster R-CNN. The performance evaluation shows that our detection precision and recall are more than 90% and the pavement blocks are profiled at the same time. Our proposed mechanism can be used for monitoring management to quantitatively detect the level of excavation risk before a large-scale ground collapse occurs.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.505-510
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• 2024

Since rolling contact fatigue cracks can always occur on the rail surface, which is the contact surface between wheels and rails, railway rails require thorough inspection and diagnosis to thoroughly inspect the condition of the cracks and prevent breakage. Recent detailed guidelines on the performance evaluation of track facilities present the requirements for methods and procedures for track performance evaluation. However, diagnosing and grading rail surface damage mainly relies on external inspection (visual inspection), which inevitably relies on qualitative evaluation based on the subjective judgment of the inspector. Therefore, in this study, we conducted a deep learning model study for rail surface defect detection using Fast R-CNN. After building a dataset of rail surface defect images, the model was tested. The performance evaluation results of the deep learning model showed that mAP was 94.9%. Because Fast R-CNN has a high crack detection effect, it is believed that using this model can efficiently identify rail surface defects.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05c
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• pp.168-173
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• 2001

배전용 애자는 전기적, 열적, 기계적 스트레스 등 내 외부 서지에 의한 균열이 서서히 발생되며 장시간 사용시 절연파괴에 의한 지락사고로 진전되는 경우가 많다. 이러한 사고로 인하여 순간정전이나 장시간 정전에 의한 피해를 최소화하기 위해 열화된 애자를 조기에 검출함으로써 전력공급의 신뢰성 향상을 기하고자 한다. 이를 위해 열화된 애자에서 나타나는 물리적 현상에 의해 변화되는 주파수 스펙트럼 분포 해석을 통해 방전 전자파가 갖는 주기성 파형(120Hz)을 검출하여 열화된 애자를 탐지 추적하는 장치를 개발하고자 한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1137-1142
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• 2013

FBG sensors are mainly used to measure strain and temperature of structures. In this paper, an interrogator of FBG sensors is developed and implemented to measure the crack of structures using FPGA and DSP. Developed interrogator consists of an optical source, an optical circulator, an optical grating and a CCD sensor and controller. The spectrum of the reflected light from the FBG sensor is analyzed and peak wavelength is detected. Next, strain of structure can be measured using shift of peak wavelength. Centroid algorithm and Gaussian fitting which are mainly applied to detect peak wavelength of the interrogator are compared in this paper. As a result of experiment, Gaussian fitting is suitable for a developed interrogator.