• 한국기계연구소 소보
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• s.19
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• pp.61-68
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• 1989

As the system monitoring technology become required in order to improve the system performance and the productivity, we’ve studied to the detection for the tool wear and the tool breakage using AE sensors that is able to detection of generated high frequency stress pulse at cutting. The detection system is consist of a sensing part, a amplifier part, a signal processing part, and a analysis & output part. The moment (a rms and a kurtosis) of statistical method is used for analysis of AE singnal. The experiment are carried out in a CNC lathe. In this study, we achieved that the amplitude level of the AE signal and statistical moments was largely changed as the tool failure. The change rate of Kurtosis was especially large, but the change rate of the rms was small.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.05a
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• pp.34-39
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• 2002

The surfaces of machine components in sliding contact such as bearing, gears and pistons etc. frequently operate under the condition of mixed lubrication due to high load, high speed and slip. These machine components often undergo the inception of scuffing in practical application. The scuffing failure is a critical problem in modern machine components, especially for the requirement of high efficiency and small size. However, it is difficult to find a universal mechanism to explain all scuffing phenomena because there are so many factors affecting the onset of scuffing. In this study, scuffing experiments are conducted using Acoustic Emission(AE) measurement by an indirect sensing approach to detect scuffing failure. Acoustic Emission(AE) signal has been widely utilized to monitor the interaction at the friction interface. Using AE signals we can get an indication about the state of the friction processes, about the quality of solid and liquid layers eon the contacting surfaces in real time. The FFT(Fast Fourier Transform)analyses of the AE signal are used to understand the interfacial interaction and the relationship between the AE signal and the state of contact is presented

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.1
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• pp.44-51
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• 2000

In this paper, using a wide-band AE sensor with the frequency range from 100[kHz] to 1.5[kHz], the frequency spectra of AE signals generated from the corona discharges of the needle-plane gap and from the partial discharges of an epoxy void were analyzed to determine the proper ultrasonic sensor with optimum frequency range according to the patterns of corona discharges. We also examined the propagation characteristics of AE signals in oil and the relationship between the magnitude of corona discharge and the magnitude of AE signals in peak-to-peak value under the application of 60[Hz] ac high-voltage. From these results, the main frequency spectra of AE signals emitted from the corona discharges of the needle-plane gap were about 130[kHz] by the fast fourier transform, but the main frequency spectra appeared to be 230[kHz] in the partial discharges of an epoxy void. The magnitude of AE signals was proportional to the magnitude of corona discharge and discharge current pulse with increasing the applied voltages.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2029-2030
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• 2011

이 논문에서는 최근 활발히 연구되고 있는 BCI 실험에서 센서 위치의 변화에 따른 정확도 감소를 줄이는 방법을 알아본다. 이를 위해 특징추출 방법에서 많이 사용되는 두 가지 방법 (Power Spectrum Density, Phase Lock Value) 을 비교 및 평가 한다. motor imagery BCI 실험 결과 phase정보를 이용하는 Phase Lock Value가 달라지는 센서 위치에 덜 민감하다는 것을 확인할 수 있었다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.7
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• pp.891-897
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• 2013

In this study, the compressive deformation behaviors of aluminum alloy under high strain rates were investigated by means of a SHPB test. An acoustic emission (AE) technique was also employed to monitor the signals detected from the deformation during the entire impact by using an AE sensor connected to the specimen with a waveguide in real time. AE signals were analyzed in terms of AE amplitude, AE energy and peak frequency. The impacted specimen surface and side area were observed after the test to identify the particular features in the AE signal corresponding to the specific types of damage mechanisms. As the strain increased, the AE amplitude and AE energy increased whereas the AE peak frequency decreased. It was elucidated that each AE signal was closely associated with the specific damage mechanism in the material.

• Composites Research
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• v.14 no.5
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• pp.46-53
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• 2001

In this research, damage behavior of singly oriented ply (SOP) fiber metal laminate (FML) subjected to concentrated load was studied. The static indentation tests were conducted to study fiber orientation effect on damage behavior of FML. During the static indentation tests, acoustic emission technique (AE) was adopted to study damage characteristics of FML. AE signals were obtained by using AE sensor with 150kHz resonance frequency and the signals were compared with indentation curves of FML. The damage process of SOP FML was divided by three parts, i.e., crack initiation, crack propagation, and penetration. The AE characteristics during crack initiation show that the micro crack is initiated at lower ply of the plate, then propagate along the thickness of the plate with creating tiber debonding. The crack grow along the fiber direction with occurring 60∼80dB AE signal. During the penetration, the fiber breakage was observed. As fiber orientation increases, talc fiber breakage occurs more frequently. The AE signal behaviors support these results. Cumulative AE counts could well predict crack initiation and crack propagation and AE amplitude were useful for the prediction of damage failure mode.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.641-650
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• 2010

Color image sensors (CIS) output color images through image sensors and image signal processing. Image sensors that convert light to electrical signal are divided into CMOS image sensor and CCD image sensor according to transferring method of signal charge. In general, a CIS has RGB output signals from tri-stimulus XYZ of the scene through image signal processing. This paper presents an adaptive colorimetric analysis method to obtain chromaticity and luminance using CIS under various environments. An image sensor for the use of colorimeter is characterized based on the CIE standard colorimetric observer. We use the method of least squares to derive a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values. We first survey the camera characterization in the standard environment then derive a SGL(shutter-gain-level) function which is relationship between luminance and auto exposure (AE) characteristic of CIS, and read the status of an AWB(auto white balance) function. Then we can apply CIS to measure luminance and chromaticity from camera outputs and AE resister values without any preprocessing. Camera RGB outputs, register values, and camera photoelectric characteristic are used to analyze the colorimetric results for real scenes such as chromaticity and luminance. Experimental results show that the proposed method is valid in the measuring performance. The proposed method can apply to various fields like surveillant systems of the display or security systems.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.4
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• pp.601-607
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• 2012

The magnetic abrasive polishing (MAP), for online monitoring with AE sensor attachment, was performed in this study. To predict the surface roughness after the magnetic abrasive polishing of NAK80, the signal data acquired from the AE sensor were analyzed. A dimensionless coefficient, which consisted of average of AErms and standard deviation of AE signal, was defined as a characteristic of the MAP and a prediction model was obtained using least square method. A neural network, which had multiple input parameters from AE signals and polishing conditions, was applied for predicting the surface roughness. As a result of this study, it was seen that there was very close correlation between the AE signal and the surface roughness in the MAP. And then on-line prediction of the surface roughness after the MAP of the NAK80 was possible by the developed prediction model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.1
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• pp.29-36
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• 2009

In this paper, we proposed auto exposure(AE) algorithm and hardware implementation for apply to mobile phone camera. AE is a function that control camera exposure automatically for appropriate to object. Existing AE is using micro controller unit and there are some problems about high expense and slow processing speed. For improve these problems, we proposed AE algorithm for hardware implementation without micro controller unit therefor we can expect improvement about the content of a production and operation speed. We proposed the algorithm that is considered efficiency of hardware resource and the results of hardware implementation of proposed AE algorithm apply to mobile phone camera sensor, we verified proposed AE function.

• Tribology and Lubricants
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• v.18 no.5
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• pp.351-356
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• 2002

The surfaces of machine components in sliding contact such as bearing, gears and pistons etc. frequently operate under the condition of mixed lubrication due to high load, high speed and slip. These machine components often undergo the inception of scuffing in practical application. The scuffing failure is a critical problem in modern machine components, especially for the requirement of high efficiency and small size. However, it is difficult to find a universal mechanism to explain all scuffing phenomena because there are so many factors affecting the onset of scuffing. In this study, scuffing experiments are conducted using Acoustic Emission(AE) measurement by an indirect sensing approach to detect scuffing failure. Acoustic Emission(AE) signal has been widely utilized to monitor the interaction at the friction interface. Using AE signals we can get an indication about the state of the friction processes, about the quality of solid and liquid layers on the contacting surfaces in real time. The FFT(Fast Fourier Transform) analyses of the AE signal are sued to understand the interfacial interaction and the relationship between the AE signal and the state of contact is presented.