• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.1022-1027
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• 1997

The grinding operation is an important machining process for machining of final surface. However. grinding process has inevitable troubles such as loading and glazing for grinding wheel. It is, therefore, an essential research theme to determine the wheel life and the dressing timefor efficient grinding. In this study, AE signals (AEavg) generated in thc grinding operation were measured and the dressing time was determined from the analysis of the AEavg value. To verify the propriety of the obtained result. the AE signals measured on the grinding and the dressing operation were compared with the grinding force signals and the dressing force which were measured at same time. From the obtained result, it was confirmed that the determination of the wheel life and the dressing time by the AE measurement technique proposed in this study can be practically used.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.6
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• pp.520-530
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• 2007

Combination of the parametric and the wavelet analyses of acoustic emission (AE) signals was applied to identify the failure modes in carbon fiber reinforced plastic (CFRP) composite laminates during tensile testing. AE signals detected by surface mounted lead-zirconate-titanate (PZT) and polyvinylidene fluoride (PVDF) sensors were analyzed by parametric analysis based on the time of occurrence which classifies AE signals corresponding to failure modes. The frequency band level-energy analysis can distinguish the dominant frequency band for each failure mode. It was observed that the same type of failure mechanism produced signals with different characteristics depending on the stacking sequences and the type of sensors. This indicates that the proposed method can identify the failure modes of the signals if the stacking sequences and the sensors used are known.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.532-538
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• 2002

This study was performed to classify the fatigue crack opening and closure for three kinds of aluminum alloy using principal component analysis (PCA). Fatigue cycle loading test was conducted to acquire AE signals which come from different source mechanisms such as crack opening and closure, rubbing, fretting etc. To extract the significant feature from AE signal, correlation analysis was performed. Over 94% of the variance of AE parameters could accounted for the first two principal components. The results of the PCA on AE parameters showed that the first principal component was associated with the size of AE signals and the second principal component was associated with the shape of AE signals. An artificial neural network (ANN) an analysis was successfully used to classify AE signals into six classes. The ANN classifier based on PCA appeared to be a promising tool to classify AE signals for fatigue crack opening and closure.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.41-46
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• 2003

This paper deals with the possibility of tap breakage detection by AE sensor. AE signals in the tapping were not seldom generated in low speed but reflected the tapping process exactly in high speed. Using AE raw signals sampled in 500kHz, AE RMS and AE count rate was computed in software. When the converting time of AE RMS is less than 10ms, we could distinguish between normal cutting and tap breakage. And AE count rate was more exact when the converting time is greater than 1ms. When two methods were compared to each other, AE count rate was more accurate.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.4
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• pp.274-286
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• 2005

Fracture behaviors and acoustic emission (AE) characteristics of single-edge-notched monolithic aluminum plates and glass fiber/aluminum hybrid laminate plates have been investigated under tensile loads. AE signals from monolithic aluminum could be classified into two different types: signals with low frequency band and high frequency band. High frequency signals were detected in the post stage of loading beyond displacement of 0.45mm. For glass fiber/aluminum laminates, AE signals with high amplitude and long duration were additionally confirmed on FFT frequency analysis, which corresponded to macro-crack propagation and/or delamination between A1 and fiber layers. On the basis of the above AE analysis and fracture observation with optical microscopy and ultrasonic T scan, characteristic features of AE associated with fracture processes of single-edge-notched glass fiber/aluminum laminates were elucidated according to different fiber ply orientations.

• Journal of the Korean Society for Nondestructive Testing
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• v.11 no.2
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• pp.15-21
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• 1991

A wireless acoustic emission (AE) system has been developed for continuous monitoring of rotating structures such as turbine rotors. The cable between preamplifier and signal processing unit of a conventional AE system was replaced by the frequency modulated telemetry. The detected signals were modulated and transmitted as an RF signals by the transmitting module, then received and demodulated by the receiving module. The distance between the transmitting and the receiving antennas could be separated up to 10cm within a reasonable signal-to-noise ratio. The simulated AE signals generated by pencil lead breaks from rotating structures were successfully detected using the developed wireless AE monitoring system.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.6
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• pp.451-458
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• 2005

The effects of fiber orientation on acoustic emission(AE) characteristics have been studied for various composite laminates. Reflection and transmission optical microscopy were used to investigate the damage zone of specimens. AE signals were classified through short time Fourier transform(STFT) as different types: AE signals with a high intensity and high frequency band were due to fiber fracture, while weak AE signals with a low frequency band were due to matrix cracking and/or interfacial cracking. Characteristic feature in the rate of hit-events having high amplitudes showed a procedure of fiber breakages, which expressed the characteristic fracture processes of notched fiber-reinforced plastics with different fiber orientations. As a consequence, the behavior of fracture in the continuous composite laminates could be monitored through nondestructive evaluation(NDE) using the AE technique.

• Journal of Ocean Engineering and Technology
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• v.16 no.2
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• pp.67-71
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• 2002

Damage process of CFRP laminates was characterized by Acoustic Emission (AE). The main objective of this study is to determine if the sources of AE in CERP laminates could be identified from the characteristics of the waveform signals recorded during monotonic tensile test. The time history and power spectrum of each individual wave signal recorded during test were examined and classified according to their special characteristics. The wave from and frequency of AE signal from a specimens is an aid to the determination of the extent of the different fracture mechanism such as matrix crack, debonding, fiber pull-out and fiber fracture as load is increased. Four distinct types of signals were observed regardless of specimen condition. The result showed that the AE method could be effectively used for analysis of fracture mechanism in CFRP laminates.

• Nuclear Engineering and Technology
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• v.35 no.1
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• pp.25-34
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• 2003

The research on the development of the fault monitoring system for the thermal reduction reactor has been performed preliminarily in order to support the successful operation of the thermal reduction reactor. The final task of the development of the fault monitoring system is to assure the integrity of the thermal$_3$ reduction reactor by the acoustic emission (AE) method. The objectives of this paper are to identify and characterize the fault-induced signals for the discrimination of the various AE signals acquired during the reactor operation. The AE data acquisition and analysis system was constructed and applied to the fault monitoring of the small- scale reduction reactor, Through the series of experiments, the various signals such as background noise, operating signals, and fault-induced signals were measured and their characteristics were identified, which will be used in the signal discrimination for further application to full-scale thermal reduction reactor.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.199-210
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• 2008

Acoustic emission(AE)/Microseimsic(MS) activities are low-energy seismic events associated with a sudden inelastic deformation such as the sudden movement of existing fractures, the generation of new fractures or the propagation of fractures. These events rapidly increase before major failure and happen within a given rock volume and radiate detectable seismic waves. The main difference between AE and MS signals is that the seismic motion frequencies of AE signals are higher than those of MS signals. As the failure of geotechnical structures usually happens as a high velocity and small displacement, it is not easy to determine the precursor and initiation stress level of failure in displacement detection method. To overcome this problem, AE/MS techniques for detection of structure failure and damage have recently adopt in civil engineering. In this study, AE/MS monitoring system, which consist of sensor, data acquisition and operation program, is constructed with domestic technology. To verify and optimize the developed system, we are now carrying out the field application at an underground research laboratory and the developed AE/MS monitoring will be used in detecting of seismic events with various scales.