• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.334-339
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• 2004

Ultraprecision machining and MEMS technology have been taken more and more important position in machining of microparts. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro parts to micro products. Also, the method of micro-grooving using micro endmilling is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This investigation deals with state monitoring using acoustic emission(AE) signal in the micro-grooving. Characteristic evaluation of AE raw signal, AE hit and frequency analysis for state monitoring is also presented in the paper.

• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.214-219
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• 1997

The mechanical seals, which are installed in rotating machines like pump and compressor, are generally used as sealing devices in the many fields of industries. The failure of mechanical seals such as leakage, crack, breakage, fast and severe wear, excessive torque, and squeaking results in big problems. To identify abnormal phenomena on mechanical seals and to propose the proper monitoring parameter for the failure of mechanical seals, sliding wear experiments were conducted. Acoustic emission, torque, and temperature were measured during experiments. Optical microstructure was observed for the wear processing after every 10 minute sliding at rotation speed of 1750 rpm and scanning electron microscopy was also observed. Except for the initial part of every experiment, the variation of acoustic emission was well coincided with torque variation during the experiments. This study concludes that acoustic emission and torque are proper monitoring parameters for the failure of mechanical seals. The intensity of acoustic emission signals is measured in root mean square voltage. Temperature of sealing face will be used as a parallel parameter for increasing the reliability of monitoring system.

• Composites Research
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• v.16 no.1
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• pp.26-33
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• 2003

Utilizing a thermo-acoustic emission (AE) technique, a study on detection and evaluation of microfractures in cross-ply laminate composites was performed. Fiber breakages and matrix fractures formed by a cryogenic cooling at $-191^{\circ}C$ were observed with ultrasonic C-scan, optical and scanning electron microscopy. Those microfractures were monitored in a non-destructive in-situ state as three different types of thermo-AE signals classified on the basis of Fast-Fourier Transform and Short-Time Fourier Transform. Thus, it was concluded that real-time estimation of microfracture processes being formed during cryogenic cooling could be accomplished by monitoring such different types of thermo-AEs in each time-stage and then by analyzing thermo-AE behaviors for the respective AE types on the basis of the AE signal analysis results obtained during thermal heating and cooling load cycles.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.39-45
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• 2001

Fourier transform has been one of the most common tools to study the frequency characteristics of signals. With the Fourier transform alone, however, it is difficult to tell whether signal's frequency contents evolve in time or not. Except for a few special cases, the frequency contents of most signals encountered in the real world change with time. Time-frequency analysis methods are developed recently to overcome the drawbacks of Fourier transform, which can represent the information of signals in time and frequency at the same time. In this study, damage process of a cross-ply carbon fiber reinforced plastic (CFRP) under monotonic tensile loading was characterized by acoustic emission. Different kinds of CFRP specimens were used to determine the characteristics of AE signals. Time-frequency analysis methods were employed for the analysis of fracture mechanisms in CFRP such as mix cracking, debonding, fiber fracture and delamination.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.2
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• pp.258-266
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• 2012

Recently, Acoustic Emission (AE) technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the rolling element bearing problems and Wavelet transform is a powerful method to detect faults occurred on gearboxes. However, exact method for AE signal is not developed yet. Therefore, in this paper, two methods, which is Hilbert transforms (HT) and Hilbert-Huang transforms (HHT), will be compared for development a signal processing method for early fault detection system by using AE. AE signals were measured through a fatigue test. HHT has better advantages than HT because HHT can show the time-frequency domain result. But, HHT needs long time to process a signal, which has a lot of data, and has a disadvantage in de-noising filter.

• Proceedings of the KWS Conference
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• 2001.05a
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• pp.318-321
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• 2001

클래딩은 주요 산업분야에 내마모성, 내부식성의 향상을 위해 사용되고 있다. 그러나 클래딩 공정에서는 모재와 클래딩 재료의 물리적, 화학적 특성의 차이와 여러 가지 공정 변수의 영향으로 제품의 사용에 치명적인 손상을 줄 수 있는 균열, 슬래그 개재물, 기공등의 불연속이 발생하기 쉽다. 본 연구에서는 클래딩 시에 발생되는 불연속을 실시간으로 검출하는데 아주 우수한 검출능력을 갖고 있는 비파괴 검사 방법인 음향방출시험을 적용하고 검출된 신호에 대한 주파수 분석과 2차원 위치표정을 실시하여 균열, 기공 등의 불연속을 검출하였고 이를 주사전자현미경을 통하여 확인하였다. 음향방출법에 의해 클래딩부에서 발생하는 결함에 대한 실시간 평가가 가능함을 입증하였으며, 특히 다층 클래딩이나 넓은 면적의 클래딩시에 불연속을 가장 신속하게 감지할 수 있으므로 이를 생산공정에 활용한다면 클래딩 또는 용접부 품질감시를 위한 효과적인 방법이 될 것이다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.125-137
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• 2009

Acoustic emission-based techniques are being used for the nondestructive inspection of mechanical systems used in service. For reliable fault monitoring related to the crack growth, it is important to identify the dynamical characteristics as well as transient crack-related signals. Widely used methods which are based on physical phenomena of the three damage stages for detecting the crack growth have a problem that crack-related acoustic emission activities overlap in time, therefore it is insufficient to estimate the exact crack growth time. The proposed pattern recognition method uses the dynamical characteristics of acoustic emission as inputs for minimizing false alarms and miss alarms and performs the temporal clustering to estimate the crack growth time accurately. Experimental results show that the proposed method is effective for practical use because of its robustness to changes of acoustic emission caused by changes of pressure levels.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.39-45
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• 1999

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 nrluction of the insulation life. 1berefore the necessity for establishing a rrethod to diagnose the aging of insulation materials and to predict the breakdown of insulation has becorne irrportant. From this viewpoint, our studies diagnose insulation degradation using the rrethod of computer sensing system, which has PD and acoustic emission(AE) sensing system. To use advantages of these two methods can be used effectiveiy to search for treeing location and PD in sorre materials. In analysis rrethod of degradation, we analyzed the PD and AE pulses by regression analysis, corrpared to these obtained the correlation coefficient and retermination coefficient by T-distribution and saw that PD and AE pulses show a similar pattern on the whole. This has a similar teIlrency to the results of the research by Yoshimura and Fujita.Fujita.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.15-22
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• 2002

This study shows how the change of helix angle of different helix angle end mill affects machining accurracy. It was verified that cutting force are remarkably low when endmill has helix angle of different helix angle 250, 310, 370 and AE signal have less reationshap with the change of helix angle. Moreover, as the number of rotations are increases, the AE signal increased with the proportion to the number but cutting force are inversely proportional to the rotation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.95-99
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• 2004

In this study, the leak detection technique of pressure vessel by using acoustic emission(AE) signal is suggested experimentally. The leak of pressure vessel is located at the welding line due to welding defects. we measured the AE signal using Rl5I sensor, and examined the AE parameters in leak condition. It is investigated that the mean value of AE signal is dependent on leak source location. So the absolute mean value of AE signal is adopted as dominant AE parameter. We proposed leak detection algorithm using AE signal mean value for monitoring the leak source location.