• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.5
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• pp.500-507
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• 2011

Acoustic emission(AE) signals during the polymerization shrinkage of composite resin subjected to the LED light exposure were detected through a wave guide method and a direct sensor attachment method. For PMMA, human tooth, stainless steel substrate, data of AE hits and amplitudes were compared. For the test using the wave guide, AE amplitudes decreased because of the attenuant wave. However, AE hits and 1st peak frequency distribution were not different according to the sensor attachments. Through the experiments, wave guide could be used for a nondestructive evaluation of the marginal disintegrative fracture of dental restoration.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.5
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• pp.514-520
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• 2009

In configuring an automated polishing system, a monitoring scheme to estimate the surface roughness is necessary. In this study, a precision polishing process, magnetic abrasive finishing (MAF), along with an in-process monitoring setup was investigated. A magnetic tooling is connected to a CNC machining to polish the surface of stavax(S136) die steel workpieces. During finishing experiments, both AE signals and force signals were sampled and analysed. The finishing results show that MAF has nano scale finishing capability (upto 8nm in surface roughness) and the sensor signals have strong correlations with the parameters such as gap between the tool and workpiece, feed rate and abrasive size. In addition, the signals were utilized as the input parameters of artificial neural networks to predict generated surface roughness. Among the three networks constructed -AE rms input, force input, AE+force input- the ANN with sensor fusion (AE+force) produced most stable results. From above, it has been shown that the proposed sensor fusion scheme is appropriate for the monitoring and prediction of the nano scale precision finishing process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5A
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• pp.917-925
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• 2006

Experimental tests were performed to estimate velocities of the acoustic signals through prestressed concrete beam and source locations using acoustic emission (AE) techniques. Seven AE sensors are mounted on the surface of 5m length test beam with equal spacing and using Schmidt Hammer AE events are made at 18 locations. The velocities of AE signals are estimated using the time differences of arrival times and the distances between the source locations and the AE sensor locations. In addition, using the Least Square Method, the AE source locations are re-evaluated reversely using both of the arrival times and the velocities of AE signals. Test results show the average velocity of the AE signals is about 4,000 m/sec and the velocity decreased with the increase of the distance from source locations to AE sensors due to the effect of attenuation. Based on the estimation of the source locations, it is observed that the errors of source locations are decreased when the velocities of each AE sensor are used rather than the average velocity.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.13 no.6
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• pp.502-508
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• 2000

In order to detect the partial discharge with the metallic particle in GIS the AE(Acoustic Emission) sensor was designed and simulated by ANSYS 5.5 and manufactured as the coupled vibration mode. The measured resonant frequency and the maximum sensitivity frequency of three coupled AE sensors were as follows ; 147.88 kHz in 8.1mm $\Phi$$\times$8.1mm 128.82 kHz and 58.8 kHz in 9.5 mm$\Phi$$\times$9.5mm, 85.22 kHz and 32.6 kHz in 14.3 mm$\Phi$$\times$14.3 mm, resonant frequency of the AE sensor. The AE sensor of 9.5 mm$\Phi$$\times$9.5mm responded higher than the other coupled vibration mode AE sensor at the partial discharge detection in GIS.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.560-565
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• 2001

Recently, machining process monitoring technique based on AE(acoustic emission) signal is used widely and becomes very important technique in machining process for improving the efficiency and the confidence of the systems. In this study, we fabricated a cheap acoustic emission sensor and monitoring system and estimated the properties of them through comparing with commercial AE sensor systems. In addition, we evaluated the performance of the fabricated sensor in polishing process. Futhermore, we are scheduled to develop the multi-point polishing process monitoring system through fabrication of the more AE sensors and complement of the monitoring system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.315-318
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• 1997

In terms of productivity, the speed of machining process has been increasing in most of engineering part. But the tapping process does not reach at enough level compared with other machining processes because of its complicate cutting mechanism. In the high speed tapping process, the one of important elements is tool monitoring system to prevent tool breakage. This paper describes tool monitoring system by acoustic emission(AE) in the tapping process. We used 2 types of AE sensors in this test. The one is commercial sensor which is used in other machining monitoring system like polishing and the other is a self-fabricated sensor for this test. In this test we purpose to find out the frequency of AE signal in tapping process and verify the possibility of applying AE sensor in in-process tapping monitoring system. Also grasp of characteristic of tapping process by AE signal is handled.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1682-1687
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• 2003

Die polishing technology is very critical to determine quality and performance of the final products. Generally, the rotation-type tool is used most widely in the polishing process. However it is difficult to make the mirror surface, because the method using the rotation-type tool causes a lot of tiny scratch on the polished surface. This paper proposes a new method using the oscillation-type tool that reduces the scratch and improves the surface roughness. As result. the mirror surface was able to obtain by using the oscillation-type tool. AE is known to be closely related to material removal rate(MRR). As the surface is rougher, MRR gets larger and AE increase. The surface roughness can be indirectly estimated using the AE signal measured during automatic die polishing process. In this study. an AE sensor based monitoring system was developed to investigate the relation the level of AE RMS with the surface roughness during polishing process.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.3
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• pp.233-239
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• 2004

Smart material is used in various applications such as for glass frame, for medical instruments and for a part of sensors. Smart composite materials ran be applied to a part of aircraft and to the on-line monitoring system for industrial structures, using the shape memory effect. However, it is very difficult to simulate and analyze the shape memory effect in smart composites. In this paper, a two dimensional axisymmetric model was proposed to analyze the smart composite of one fiber and matrix using the finite element method(FEM). The finite element analysis was carried out in two renditions of the room temperature(293K) and a higher temperature (363K). The results we.e compared with the experimental results to confirm the validity of the analysis. In addition, the acoustic emission(AE) technique was used to study the microscopic damage behavior and the effect of pre-strains on TiNi/A16061 shape memory alloy composite.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.1
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• pp.1-7
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• 2007

As fiber reinforced composite materials are widely used in aircraft, space structures and robot arms, the study on non-destructive testing methods has become an important research area for improving their reliability and safety. AE (acoustic emission) can evaluate the defects by detecting the emitting strain energy when elastic waves are generated by the initiation and growth of crack, plastic deformation, fiber breakage, matrix cleavage, or delamination. In the paper, AE signals generated under uniaxial tension were measured and analyzed using the $8{\times}8$ matrix piezo electric sensor. The electronic circuit to control the transmitting distance of AE signals was designed and constructed. The optical data storage system was also designed to store the AE signal of 64channels using LED (light emitting diode) elements. From the tests, it was shown that the source location and propagation path of AE signals in composite materials could be detected effectively by the $8{\times}8$ matrix piezo electric sensor.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.1
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• pp.47-55
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• 2012

A structural health monitoring technique for locating impact position in a plate structure is presented in this paper. The method employs a single sensor and spatial focusing of time reversal (TR) acoustics. We first examine the TR focusing effect at the impact position and its surroundings through simulation and experiment. The imaging results of impact points show that the impact source location can be accurately estimated in any position of the plate. Compared to existing techniques for locating impact or acoustic emission source, the proposed method has the benefits of using a single sensor and not requiring material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in other ultrasonic testings of plate-like structures.