• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.78-81
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• 2021

Through the smart factory construction project, sensors can be installed in manufacturing production facilities and various process data can be collected in real time. Through this, research on real-time facility anomaly detection is being actively conducted to reduce production interruption due to facility abnormality in the manufacturing process. In this paper, to detect abnormalities in production facilities, the manufacturing data was applied to deep learning models Autoencoder(AE), VAE(Variational Autoencoder), and AAE(Adversarial Autoencoder) to derive the results. Manufacturing data was used as input data through a simple moving average technique and preprocessing process, and performance analysis was conducted according to the window size of the simple movement average technique and the feature vector size of the AE model.

• Composites Research
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• v.12 no.4
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• pp.62-70
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• 1999

It was well recognized that damages associated mainly with the aging of civil infrastructrues were one of very serious problems for assurance of safety and reliability. In recent, carbon fiber sheet(CFS) has been widely used for reinforcement and rehabitation of damaged concrete beam. However, the fundamental mechanism of load transfer and its load-resistant for carbon fiber sheet reinforced concrete are not fully understood. In this study, three point bend test has been carried out to understand the damage progress and micro-failure mechanism of CFS reinforced concretes. For these purposes, four kinds of specimens are used, that is, concrete, respectively. Acoustic Emission(AE) technique was used to evaluate the characteristics of damage progress and failure mechanism of specimens. In addititon, two-dimensional AE source location was also performed to monitor crack initiation and propagation processes for four types of these specimens.

• 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.

• Journal of the Korea Concrete Institute
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• v.21 no.4
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• pp.457-464
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• 2009

Fiber is an important ingredient in fiber-reinforced cement composite (FRCC) which can control fracture of cement composite by bridging action. In compliance with the action of the fiber and the aggregate size, it also showed a different failure mechanism. For practical application, it is needed to investigate the fracture behavior of the FRCC and to understand the micro-mechanism of cement matrix with reinforcing fiber. In order to evaluate a characteristics of fracture process in the FRCC, acoustic emission (AE) technique was used for the analysis and evaluation of FRCC damage by acoustic emission under flexural and cyclic compressive loadings. The AE signals were monitored by AMSY4 AE instrument during the entire loading period. The specimens are reinforced with 0, 1.0, 1.5 and 2.0% (by volume) Polyvinyl alcohol (PVA) fiber. The test results showed that the damage progress of the FRCC was characteristic for the fiber replacement ratio. As a result of analyzing the felicity ratio (FR) values, it is shown that this values can be used for evaluating the degree of FRCC damage. On the whole the felicity ratio values of FRCC are shown between 0.4 and 1.1. And, the AE kaiser effect was shown in the all FRCC specimen. In addition, the damage behavior and the microscopic fracture process of the FRCC are evaluated using the AE parameters, such as calm ratio, b-value and felicity ratio. The purpose of this reserch was to advance the state of knowledge regarding the applicability of acoustic emission as an evaluation method for FRCC.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.271-279
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• 2006

Acoustic Emission (AE) technology is an effective nondestructive testing for continuous monitoring of defect formation and failures in structural materials. This paper presents a source location model using Acoustic Emission (AE) sensors in a Pre-Stressed Concrete (PSC) beam and the evaluation of the model was performed through lab experiments. 54 AE events were made on the surface of the 5m-PSC beam using a Schmidt Hammer and arrival times were measured with 7AE sensors. The source location f3r each event was estimated using least squares. The results were compared with actual positions and the RMSE (Root Mean Square Errors) was about 2cm.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.1
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• pp.48-57
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• 2007

The fatigue crack growth behavior of a cracked and patch-repaired Ah2024-T3 panel has been monitored by acoustic emission(AE). The overall crack growth rate was reduced The crack propagation into the adjacent hole was also retarded by introducing the patch repair. AE signals due to crack growth after the patch repair and those due to debonding of the plate-patch interface were discriminated by usiag the principal component analysis. The former showed high center frequency and low amplitude, whereas the latter showed long rise tine, low frequency and high amplitude. This type of AE signal recognition method could be effective for the prediction of fatigue crack growth behavior in the patch-repaired structures with the aid of AE source location.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.165-173
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• 2011

The acoustic emission(AE) technique is a well established method to carry out structural health monitoring(SHM) of large structures. However, the real-time monitoring of the crack growth in the roller coaster support structures is not easy since the vehicle operation produces very large noise as well as crack growth. In this investigation, we present the waveform parameter filtering method to classify acoustic sources in real-time. This method filtrates only the AE hits by the target acoustic source as passing hits in a specific parameter band. According to various acoustic sources, the waveform parameters were measured and analyzed to verify the present filtering method. Also, the AE system employing the waveform parameter filter was manufactured and applied to the roller coaster support structure in an actual amusement park.

• Composites Research
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• v.31 no.4
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• pp.145-150
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• 2018

Various structural health monitoring (SHM) systems have been suggested for aerospace industry in order to increase its life-cycle and economic efficiency. In the case of aircraft structure madden with metal, a major concern was hot spots, such as notches, bolts holes, and where corrosion or stress concentration occurs due to moisture or salinity. However, with the increasing use of composites in the aerospace industry, further advanced SHM systems have been being required to be applied to composite structures, which have much complex damage mechanism. In this paper, a method of acoustic emission localization for composite structures using Q-switched laser and multiple Amplifier-integrated PZTs have been proposed. The presented technique aims at localization of the AE with an error in distance of less than 10 mm. Acoustic emission simulation and the localization attempt were conducted in the composite structure to validate the suggested method. Localization results, which are coordinates of detected regions, grid plots and color intensity map have been presented together to show reliability of the method.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.56-67
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• 2015

In this study, a source locating technique applicable to transversely isotropic media was developed. Wave velocity anisotropy was considered based on the partition approximation method, which simply enabled AE source locating. Sets of P wave arrival time were decided by the two-step AIC algorithm and they were later used to locate the AE sources when having the least error compared with the partitioned elements. In order to validate the technique, pencil lead break test on artificial transversely isotropic mortar specimen was carried out. Defining the absolute error as the distance between the pencil lead break point and the located point, 1.60 mm ~ 14.46 mm of range and 8.57 mm of average were estimated therefore it was regarded as thought to be 'acceptable' considering the size of the specimen and the AE sensors. Comparing each absolute error under different threshold levels, results showed small discrepancies therefore this technique was hardly affected by background noise. Absolute error could be decomposed into each coordinate axis error and through it, effect of AE sensor position could be understood so if optimum sensor position was able to be decided, one could get more precise outcome.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.30-36
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• 2004

As fiber reinforced composite materials are widely used in aircraft, space structures and robot arms, the study on the non-destructive testing methods of the composite materials has become an important research area for improving their reliability and safety. In this paper, the AE signal analyzer with the resonance circuit to extract the specified frequency of the acoustic emission signal were designed and fabricated. The noise levels of the fabricated AE signal analyzer by the disturbance such as impact or mechanical vibration had a very small value comparable to those of the conventional AE signal analyzer. Also, the fabricated AE signal analyzer was proved to have about the same crack detection capabilities with the conventional AE signal analyzer under the static and dynamic tensile tests of the composite materials.