• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.9-14
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• 2014

Recently many efforts and researches have been done to cope with industrial facilities that require a low energy machines due to the gradual depletion of the natural resources. The fiber-reinforced composite materials in general have good properties and have the proper mechanical properties according to the change of the ply sequences and fiber distribution types. However, in the fiber-reinforced composite material, there are several problems, including fiber breaking, peeling, layer lamination, fiber cracking that can not be seen from the metallic material. Particularly, the fracture and delamination are likely to be affected by the thickness of the stacking laminates when the bi-material laminated structure is subjected to a load of the mixed mode. In this study, we investigated the effect of the thickness ratio of the difference in the CFRP/GFRP bi-material laminate composites by measuring the cracking behavior and the AE characteristics in a mixed mode loading, which may be generated in the actual structure. The results show that the thickness of the CFRP becomes more thick, the mode I energy release rate becomes a larger, and also the influence of mode I is greater than that of mode II. In addition, AE amplitude which shows the level of the damage in the structure was obtained the more damage in the CFRP with the thin thickness.

• Journal of the Korean Society for Nondestructive Testing
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• v.18 no.4
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• pp.278-291
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• 1998

Fracture process of continuous fiber reinforced composites is very complex because various fracture mechanisms such as matrix cracking, debonding, delamination and fiber breaking occur simultaneously during crack growth. If fibers cause crack bridging during crack growth, the stable crack growth and unstable crack growth appear repeatedly. Therefore, it is very difficult to exactly determine tile starting point of crack growth and the fracture toughness at the critical crack length in composites. In this research, fracture toughness test for CFRP was accomplished by using acoustic emission(AE) and recording of tile fracture process in real time by video-microscope. The starting point of crack growth, pop-in point and the point of unstable crack growth can be exactly determined. Each fracture mechanism can be classified by analyzing the fracture process through AE and video-microscope. The more reliable method ior the fracture toughness measurement of composite materials was proposed by using the combination of R-curve method, AE and video microscope.

• Proceedings of the KIEE Conference
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• 1997.07e
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• pp.1761-1763
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• 1997

Because of internal voids in insulators give rise to partial discharge (PD), which cause local breakdown and even entire insulation breakdown. Treeing due to PD is one of the main causes of breakdown of the insulating materials and reduction of the insulation life. Therefore the necessity for establishing a method to diagnose the aging of insulation materials and to predict the breakdown of insulation has become important. From this viewpoint, our studies diagnose insulation degradation using the method of computer sensing system, which has the advantages of PD and acoustic emission (AE) sensing system. To use advantages of these two methods can be used effectively to search for treeing location and PD in some materials. In analysis method of degradation, We analyzed the PD pulse and AE pulses by regression analysis, compared to these obtained the correlation coefficient and determination coefficient by T-distribution and saw that PD and AE pulses show a similar pattern on the whole. This is in agreement with the results of the research by Yoshimura and Fujita.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1570-1575
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• 1991

The feasibility of using an adaptive resonance network (ART2) with unsupervised learning capability for too] wear detection in turning operations is investigated. Specifically, acoustic emission (AE) and cutting force signals were measured during machining, the multichannel AR coefficients of the two signals were calculated and then presented to the network to make a decision on tool wear. If the presented features are significantly different from previously learned patterns associated with a fresh tool, the network will recognize the difference and form a new category m worn tool. The experimental results show that tool wear can be effectively detected with or without minimum prior training using the self-organization property of the ART2 network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.70-75
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• 1993

Chatter vibration is an unwanted phenomenon in metal cutting and it always affects surface finish, tool life machine life and the productivity of machining process. The In-process monitoring & control of chatter vibration is necessarily required to automation system. In this study, we constructed the multi-sensing system using Tool Dynamometer,Accelerometer and AE(Acoustic Emission) sensor for the credible detection of chatter vibration. And a new approach using a neural network to process the features of multi-sensor for the recognition of chatter vibration in turning operation is proposed. With the back propagation training process, the neural network memorize and classify the feature difference of multi-sensor signals.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.223-226
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• 2003

This paper presents a realization of sensor signal processing(noise filtering) and Fieldbus based communication for condition monitoring of check valve. we first acquired the AE(Acoustic Emission) sensor data at the KAERI check valve test loop, and their frequencies were analyzed to find the informative band. To reject background noises, bandpass filters have been designed. Also, to send the processed data to a remote site, wired communication facility has been realized via DeviceNet.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.151-154
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• 2002

The objective of this study is to find the change of signal characteristics of matrix cracks due to the different specimen shapes. As the concept of the smart structure, monitoring of acoustic emission (AE) can be applied to inspect the fracture of the structures in operating condition using built-in sensors. To understand the characteristics of matrix crack signals, we performed tensile tests by changing the thickness and width of the specimens. This paper describes the implementation of time-frequency analysis such as wavelet transform (WT) fur the quantitative evaluation of fracture signals. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.293-298
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• 2003

This study deals with the source location method of defect which can be occurred in structure. The existing methods was very difficult to be applied to predict it because of using very complex numerical formula. The triangulation method which was proposed in his study can predict the source location predicted easily with small amount of data. Wave arrival time data can be directly converted into source-sensor distance is known. For this purpose, the propagation velocity was measured by Rayleigh wave, and the propagation behavior was analyzed. For the consideration of jointed part in structure, the source location method was applied to the welded workpiece. The signal propagation velocity was measured in welding part for the purpose of application to the part and the revised algorithm of source location was proposed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.987-990
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• 2000

In modern manufacturing industry such as aerospace, vehicle and die/mold industry, the high hardness malarial which is remarkable in aspects of durability is effectively used. The high-speed and precision machining technology has been applied in these fields. In this study, efficient sensors in high-speed machining by observing similar tendency through comparing cutting force with AE signal, gap sensor signal and accelerometer signal are selected, and machinability of high-speed machining is experimentally evaluated. We performed a basic research for sensing system construction to monitor a machine tool and machining condition.

• Tribology and Lubricants
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• v.17 no.3
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• pp.244-250
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• 2001

A rotating axis diagnostic system supported with journal bearing has been established that has been widely used in the industry. In order to measure the most sensitive signals that would be generated in the abnormal operation, sensors which measure AE(acoustic emission), gap and acceleration have been attached at the various location on the experimental apparatus. Data were obtained in the steady state operational condition of the system which was verified through the empirical measurement. Notable discrepancies were observed in RMS acceleration signal which could be utilized to predict the undesirable operational condition of the system.