• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.97-98
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• 2023

Recently, the use of digital technology in architectural technology is gradually increasing with the development of various industrial technologies. There are artificial intelligence and drones in the field of architecture, and among them, deep learning technology has been introduced to conduct research in areas such as precise inspection of buildings, and it is expressed in a highly reliable way. When a building is deteriorated, various defects such as cracks in the surface and subsidence of the structure may occur. Since these cracks can represent serious structural damage in the future, the detection of cracks was conducted using artificial intelligence that can detect and identify surface defects by detecting cracks and aging of buildings.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.231-232
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• 2023

It is important to utilize an efficient quality management platform because the management of deadlines at construction sites requires rapid and accurate processing of numerous defect data in a short time. In this study, 30 domestic patents for defect management and image analysis were analyzed to examine the development status of quality management platforms using mobile devices. As a result of the analysis, research on automatically detecting defects using artificial intelligence has been actively underway in recent years, and advanced IT technologies have been converging in various ways into linked services.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.27 no.2
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• pp.49-61
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• 1997

The purpose of this study was to compare E-speed film, CDR, and modified CDR images by means of observing some artificial defects of alveolar bone wall in the sound human dried mandibles. High diagnostic accuracy was shown in 1 wall and 4 wall defects by all 5 observers (2 Radiologists, 2 Periodontists, 1 General practitioner), but the diagnosis in 2 wall and 3 wall defects was inaccurate. Modified CDR images had the more diagnostic accuracy than E-speed film and CDR images, but there was no statistical difference among them. Finally, radiologist used modified CDR images more than others and used equalization effect more than the change in contrast and/or brightness.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.548-553
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• 2011

The lock-in thermography was employed to evaluate the defects in railway bogies. Prior to the actual application on railway bogies, in order to assess the detectability of known flaws, the calibration reference panel was prepared with various dimensions of artificial flaws. The panel was composed of polymer matrix composites, which were the same material with actual bogies. Through lock-in thermography evaluation, the optimal frequency of heat source was determined for the best flaw detection. Based on the defects information, the actual defect assessments on railway bogie were conducted with different types of railway bogies, which were used for the current operation. In summary, it was found that the novel infrared thermography technique could be an effective way for the inspection and the detection of surface defects on bogies since the infrared thermography method provided rapid and non-contact investigation of railway bogies.

• Journal of Welding and Joining
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• v.33 no.4
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• pp.63-67
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• 2015

Non-destructive techniques are used widely in the metal industry in order to control the quality of materials. Eddy current testing(ECT) is one of the most extensively used non-destructive techniques for inspecting electrically conductive materials at very high speeds that does not require any contact between the test piece and the sensor. The New ECT sensor which can detect inner defects was developed regardless the condition of surface. This sensor is verified to do experiment which measure the loss of induced electromotive force. The loss of induced electromotive force was measured in 5.4% and this low frequency ECT device can detect internal defects at depth 20 mm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.254-258
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• 2003

Electronic Speckle Pattern for quantitative evaluation of a impact defect inside of composite material plate are described. The impact on composite material makes inside delamination which is difficult to detect visual inspection and ultrasonic testing due to non-homeogenous structure. This paper proposes the quantitative evaluation technique of defects under real impact. Artificial defects are designed inside of composite plate for development of inspection technique and real defects under impact are inspected and compared with results of visual inspection.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.6
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• pp.398-406
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• 2015

This paper explored the results of experimental investigation on carbon fiber reinforced polymer (CFRP) composite sample with thermal wave technique. The thermal wave technique combines the advantages of both conventional thermal wave measurement and thermography using a commercial Infrared camera. The sample comprises the artificial inclusions of foreign material to simulate defects of different shape and size at different depths. Lock-in thermography is employed for the detection of defects. The temperature field of the front surface of sample was observed and analysed at several excitation frequencies ranging from 0.562 Hz down to 0.032 Hz. Four-point methodology was applied to extract the amplitude and phase of thermal wave's harmonic component. The phase images are analyzed to find qualitative and quantitative information about the defects.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.2
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• pp.87-92
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• 2006

This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.1097-1102
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• 2005

Non-Destructive Testing (NDT) is test method which finds the mechanical or natural or artificial defects of the interior or exterior of those without destructing materials and welded products. NDT is a means to assess the perfection of a component or system perfection. NOT images defects using scattered light, sound, electric current, magnetic fields and X-ray. Each NDT method has merits and demerits in the detecting ability of defects according to evaluated subjects. Defects can affect the serviceability of the material or structure, so NDT is important in guaranteeing safe operation as well as in quality control. In this review, we considered the methods of NDT applied to current railway vehicle manufacturing.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.3
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• pp.11-18
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• 2004

In this paper, the classification of artificial defects in semiconductor packages is studied by using pattern recognition technology. For this purpose, the pattern recognition algorithm includes the user made MATLAB code. And preprocess is made of the image process and self-organizing map, which is the input of the back-propagation neural network and the dimensionality reduction method, The image process steps are data acquisition, equalization, binary and edge detection. Image process and self-organizing map are compared to the preprocess method. Also the pattern recognition technology is applied to classify two kinds of defects in semiconductor packages: cracks and delaminations.