• Journal of Korean Association for Spatial Structures
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• v.10 no.4
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• pp.85-92
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• 2010

Use of concrete has undoubtedly become widespread in construction and civil engineering. Sensors are used to add functional characteristics to concrete. Self-diagnosis concrete is also being developed. The thermal protector used in the study is a sensor using the linear expansion and cubical expansion of metal. The LED(Light Emitting Diode) is a phototransistor type, and to secure high-sensitivity light, the prices of these sensors are low. Rising temperatures of concrete elements can be predicted from LED of the external virtual beam due to operation of thermal protector sensors of concrete beam caused by fire load on the concrete specimen. In this study, the development of fire-diagnosis concrete using composite sensors are the fundamental study for damage detection using simply measurements.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.36-44
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• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.

• Korean Journal of Environmental Biology
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• v.19 no.1
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• pp.19-24
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• 2001

Agricultural pesticides may cause certain biological risks since they are widely used to eradicate pests. Agricultural disasters may arise even from the possibility of their synergistic interaction with other harmful enviromnetal factors. The effect of pesticide on radiation-induced DNA damage in human blood lymphocytes was evaluated by the single cell gel electrophoresis (SCGE) assay. The lymphocytes, with or without pretreatment of the pesticide, were exposed to 0-2.0 Gy of $^60 CO$ gamma ray. Significantly increased tail moment, which was a marker of DNA strand breaks in SCGE assay, showed an excellent dose-response relationship. The present study confirms that the pesticide has the cytotoxic effect on lymphocytes and that it shows the synergistic interaction with radiation on DNA damage as well. The results may have a role of providing biological information necessary for the prevention of environmental disaster.

• Composites Research
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• v.24 no.6
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• pp.49-55
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• 2011

The use of advanced composite materials in main structures of military and civil aircraft has been increased rapidly because of their considerable metals in high specific strength and stiffness. However, the mechanical properties of composite materials may severely degrade in the presence of damage. Especially, the high-velocity impact such as a hailstorm, and a small piece of tire or stone during high taxing, can cause considerable damage to the structures and sub-system in spite of a very small mass. However, it is not easy to detect the damage in composite plates using a single sensor or any conventional methods. In this paper, the PVDF sensors and AE sensors were used for monitoring high-velocity impact damage initiation and propagation in composite laminates. The WT(wavelet transform) is used to decompose the sensor signals. In the PVDF sensor and AE sensor signal analysis, amounts of high-frequency signals are increased when the impact energy is increased. PVDF sensor and AE sensor signal appeared similar results. This study shows how various sensing techniques can be used to characterize high-velocity impact damage of advanced composite laminates.

• Computational Structural Engineering
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• v.10 no.4
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• pp.303-313
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• 1997

Though many techniques for the damage assessment of structures have been studied recently, most of them can be only applied to simple structures. Therefore, practical damage assessment techniques that evaluate the damage location and the damage state for large structures need to be developed. In this study, a damage assessment technique using a neural network is developed, in which the bilevel damage assessment procedure is proposed to evaluate the damage of a large structure from the limited monitoring data. The procedure is as follows ; first, for the rational selection of damage critical members, the members that affect the probability of failure or unusual structural behavior are selected by sensitivity analysis. Secondly, the monitoring points and the number of sensors that are sensitive to the damage severity of the selected members are also selected through the sensitivity analysis with a proposed sensitivity measurement format. The validity and applicability of the developed technique are demonstrated by various examples, and it has been shown that the practical information on the damage state of the selected critical members can be assessed even though the limited monitoring data have been used.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.1023-1026
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• 2013

The electronic equipment which was exposed to high level pulsed radiation is damaged as Upset, Latchup, and Burnout. Those damages has come from the instantaneous photocurrent from electron-hole pairs generated in itself. Such damages appeared as losses of power in military weapon system or of blackout in aerospace equipment and eventually caused in gross loss of national. In this paper, we have implemented a RDC(Radiation detection and control module) as part of the radiation protection technology of the electronic equipment or devices from the pulsed gamma radiation. The RDC which is composed of pulsed gamma-ray detection sensor, signal processors, and pulse generator is designed to protect the important electronic circuits from the pulse radiation. To verify the functionality of the RDC, LM118s which had damaged by the pulse radiation were tested. The test results showed that the test sample applied with a RDC was worked well in spite of the irradiation of the same pulse radiation. Through the experiments we could confirm that the radiation protection technology implemented with RDC had the functionality of radiation protection to the electronic devices.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.4
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• pp.351-359
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• 2011

In a structure, damage can occur at several scales from micro-cracking to corrosion or loose bolts. This makes the identification of damage difficult with one mode of sensing. Hence, a multi-mode actuated sensing system is proposed based on a self-sensing circuit using a piezoelectric sensor. In the self sensing-based multi-mode actuated sensing, one mode provides a wide frequency-band structural response from the self-sensed impedance measurement and the other mode provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. In this study, an experimental study on the pipeline system is carried out to verify the effectiveness and the robustness of the proposed structural health monitoring approach. Different types of structural damage are artificially inflicted on the pipeline system. To classify the multiple types of structural damage, a supervised learning-based statistical pattern recognition is implemented by composing a two-dimensional space using the damage indices extracted from the impedance and guided wave features. For more systematic damage classification, several control parameters to determine an optimal decision boundary for the supervised learning-based pattern recognition are optimized. Finally, further research issues will be discussed for real-world implementation of the proposed approach.

• Journal of the Korean Society for Nondestructive Testing
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• v.18 no.2
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• pp.92-102
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• 1998

Prediction of failure behavior in filament-wound composite motor cases is one of the important issues for their reliable application. Acoustic emission during hydroproof testing of the cases is used to solve this problem. Based on the acoustic emission behavior, failure sites can be located successfully. The identification of failure modes is also possible using the distribution of acoustic emission amplitude. Due to the limitation in the number of samples, it is not possible to predict the final burst pressure of motor cases and the effect of impact damage on the final burst pressure.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.239-244
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• 2006

Borehole radar reflection surveys were carried out in the horizontal borehole to detect EDZ while constructing the tunnel for the research facility of the nuclear waste disposal in Korea. The horizontal borehole has been bored at a length of 35 m from shelter to be parallel with the tunnel which would be planed. While the tunnel has been constructing with the explosive excavation, the borehole radar reflection surveys carried out 5 times with the interval of 2 or 4 days for monitoring EDZ. The most typical change of the reflection event resulted from the face of the wall of tunnel which had been produced newly by the excavation of the tunnel daily, EDZ has been detected with constructing images of difference between two measurement stages, and also the change of EDZ through the time has been done, which is due to the generation of crack and weakening of the rock strength of the face of the tunnel's wall near previous portion of the face of a blind end of tunnel according to explosive excavation.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.3
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• pp.202-210
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• 2016

A thermal barrier coating (TBC) has been widely applied to machine components working under high temperature as a thermal insulator owing to its critical financial and safety benefits to the industry. However, the nondestructive evaluation of TBC damage is not easy since sensing of the microscopic change that occurs on the TBC is required during an evaluation. We designed an eddy current probe for evaluating damage on a TBC based on the finite element method (FEM) and validated its performance through an experiment. An FEM analysis predicted the sensitivity of the probe, showing that impedance change increases as the TBC thermally degrades. In addition, the effect of the magnetic shield concentrating magnetic flux density was also observed. Finally, experimental validation showed good agreement with the simulation result.