• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3383-3388
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• 2007

To compare the sensor performance of AE leak diagnosis system which can measure valve leak conditions, AE activities such as RMS voltage level, AE signal trend, leak rate degree according to AE database, FFT spectrum were measured on valve of the simulated test system for power plant. AE activities were recorded and analyzed from various operating conditions including different temperature, pressure difference, valve size and fluid using both piezoelectric acoustic emission sensor and Pb-Free acoustic emission sensor. The results of this study are utilized to select the type of sensors, the frequency band for filtering and thereby to improve the signal-to-noise ratio for diagnosis or monitoring of valves in operation. As the final result of application study above, portable type leak diagnosis system by AE was developed. The outcome of the study can be definitely applied as a means of the diagnosis or monitoring system for energy saving and prevention of accident for power plant valve.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.40-52
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• 1998

Among the non-traditional machining methods, Abrasive waterjet machining process shows big promise in drilling difficult-to-machine materials due to its numerous advantages such as absence of heat affect zone and thermal distortion. Acoustic emission signal technique is used to understand about material removal mechanisms during abrasive waterjet drilling process. More information about the drilling process is derived through frequency decomposition of auto regressive moving average modeling representing acoustic emission signals.

• Journal of the Korean Society of Safety
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• v.16 no.2
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• pp.22-26
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• 2001

The machining process on be considered as a planned interaction of the workpiece, the tool and the machine tool. In an unmanned situation, the results of this interaction are to be continuously monitored so that any changes in the machining environment on be sensed to corrective actions. In order to design the process monitoring system for unmanned manufacturing, the identification of chip formation is proposed. The system proposes the method of using acoustic emission(AE) signal analysis to identify the chip formation during cutting.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.5
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• pp.430-435
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• 2013

This study is investigation of the characteristics for acoustic emission signal generated by destruction on glass fiber bundles and specimen that was machined composite materials surrounding the outside of GFRP cylinder. The Amplitude of acoustic emission signal gets bigger as the cutting angle of knife increases. Accordingly, the number of hits in destruction of composite materials specimen have more in longitudinal direction (longitudinal direction to the glass fiber) than in hoop direction (horizontal direction to the glass fiber) while the amplitude of signals were bigger in hoop direction than longitudinal direction. It was found out that the amplitude of the glass fiber breakage is more than 40 dB and that the amplitude of signal for matrix crack was less than 40 dB because matrix crack signal was not observed when threshold value is 40 dB and matrix crack signal suddenly appered when threshold value is 32 dB. The slope of the amplitude is related to the acoustic emission source and the slope of the amplitude of the horizontal and vertical directions are 0.16 and 0.08. In particular, The slope of the amplitude of longitudinal direction breakage appear similar to the glass fiber breakage and therefore Acoustic emission source of longitudinal direction breakage is estimated the glass fiber breakage.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.864-871
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• 2002

Acoustic emission(AE) technique has been applied to not only mechanical property testing but also on-line monitoring of the entire structure or a limit zone only. Although several AE devices have already been developed for on-line monitoring, the price of these systems is very high and it is difficult for the field to apply yet. In this study, we developed a specially designed PC-based leak detection system using A/D board. In this paper, AE technique has been applied to detect leak for heat exchanger by analyzing the characteristics of signal obtained from leak. It was confirmed that the characteristics of the signal generated by the turbulence of gas in the heat exchanger is narrow band signal having between 130-250kHz. Generally, the amplitude of leak signal is increased as the leak size increasing, but showed no significant change at frequency characteristic. Leak source location can be found by determining for the paint of highest signal amplitude by comparing with several fixed sensors. In this paper, AE results are compared with the PC-based leak detection system using A/D board.

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.36-43
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• 2023

In this study, a four-point bending test was conducted to assess and detect the damage to reinforced concrete structures using the acoustic emission (AE) technique. Based on the crack investigation results, flexural failure was classified into four stages and compared with the characteristic analysis results of AE parameters. The parametric characterization indicated that the activity of the primary AE signal was high in the early stage, and that of the second signal increased after the flexural cracks stabilized. Because the secondary AE signal included noise generated by friction, parameter-based analysis for damage assessment was performed using the primary signal; the secondary signal was used as complement. The activity analyses of the primary and secondary signals effectively classified crack propagation; however, determining the macrocracks and yielding of reinforcing bars had certain limitations. Nevertheless, applying the damage index with cumulative AE energy is a complementary technique for detecting and assessing structure damage that well detects the occurrence of macrocracks.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.05a
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• pp.789-794
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• 2001

The acoustic emission(AE) signal from concrete cylinder specimen during failure process under cycling compressive loads were recorded and analyzed. Different filters were set on the AE signal duration based on the characteristic of amplitude distribution. From the value of AE signal amplitude, which corresponds to the occurrence of the peak for AE hits, the AE signals from concrete compressive specimen were divided into five sections. The relationship between the AE signal section and the failure mechanism of these materials, analyzed on the meso-structure level was determined. Based on the experiments, the AE characteristics of each failure mechanism are given. The results show that the AE technique is a valuable tool to study the failure mechanism of concrete.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05c
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• pp.170-176
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• 2002

In this papers, we proposed the feature extraction method due to partial discharge type of transformers. For wavelet transform, Daubechie's filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion, skewness, kurtosis) about acoustic emission signal generated from each partial discharge type. The defects which could occur in a transformer were simulated by using needle-plane electrode, IEC electrode and Void electrode. Also, these coefficients are used to identify signal of partial discharge type electrode fault in transformer. As a result, from compare of acoustic emission amplitude and acoustic average value, we are obtained results of IEC electrode> Void electrode> Needle-Plane electrode. otherwise, In case of skewness and kurtosis, we are obtained results of Needle-Plane electrode electrode> Void electrode> IEC electrode.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.743-748
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• 2010

The stability forecasting of rock slope is more difficult than soil slope because catching the sign of failure in monitoring is not easy and deformation of the rock is small in failure process. But in the rock slope, there is small deformation like crack propagation in rock itself and it accumulates gradually in failure process. If it is possible to detect the small change in the rock slope, we can know the failure time exactly. Because the individual signal is gathered in the acoustic emission monitoring, it is possible to monitoring the slope if many sound signal is accumulated. Detection test of acoustic emission was performed. Uniaxial, two types of bending test, and two plane shear test were done with various cement paste sample. Wave propagation velocity of uniaxial test sample was increased with curing time. Wave Analysis give us the result that there is a AE sign signal before the failure, the AE count is suddenly increased. And frequency level 125kHz before failure is changed to level 200-250kHz after failure. In two plane shear test we can catch the AE signal and can know the failure type from wave shape. Monitoring test site is tunnel slope in Hongcheon but special signal is not collected.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.101-104
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• 1995

A acoustic emission (AE) sensor has been used to monitor tool were during milling process. The relation between tool wear and AE RMS (Root mean Square) signal was investigated experimentally. A avaliable monitoring index for monitoring toolwear was newly extracted form AE RMS. And on-line monitoring program was developed. The proposed monitoring system has verified experimentally by roughing end milling titanium alloy with TIN coated HSS tool.