• Journal of the Korean Society for Precision Engineering
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• v.12 no.4
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• pp.19-27
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• 1995

Face milling is required to study cutting process with a view of multipoint cutter. This experimental study mainly deals with the single and multi-insert cutting characteristics using coated tool. Because metal cutting of the single and multi-insert has a large relation to the improvement of productivity, the economic cutting process can be achieved by the analysis of proper metal cutting mechanism. Therefore, machining characteristics of face molling in this paper has been studied by investigating the role of different insert number which is concerned with mean cutting force, the RMS values of AE(acoustic emission) signal, tool life and surface roughness in milling SS 41 and SUS 304. The cutting force and AE signal are monitored to make an analysis of cutting process. The surface roughness of the specimens machined by inserts of different numbers is measured at different speeds, feeds and depth of cut. The width of flank wear is also observed.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.47-54
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• 2003

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.238-242
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• 2007

자동차의 고장은 그 종류나 특징면에서 다양하게 나타나게 되므로 자동차의 진단과 점검에는 많은 노동력과 비용, 시간이 소요되며 운전자에 의한 정보를 기대하기 힘든 경우에는 진단이나 정비과정에 많은 어려움을 겪게 된다. 따라서 본 연구에서는 운전자에 의한 일반적인 정보와 진동 소음센서에 의한 정보의 신호처리기술을 종합하여 자동차 부품의 이상 신호 분석을 하였다. 그리고 정상 상태 대비 이상 신호에 따른 진동 소음 데이터 변화율을 계산하여 작동 모드 별 실내음압에 영향을 미치는 신호 및 해당 주파수 특성을 분석하였다. 이에 따라 자동차 정비 전문가 시스템 구축을 위한 기초 연구로 엔진부의 이상 신호와 각 부품 별 이상 신호로 나누어 분석하여 데이터 처리 과정 및 이상 증상 별 경향 파악에 본 연구의 목적을 둔다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.243-246
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• 2007

자동차의 고장은 그 종류나 특징 면에서 다양하게 나타나게 되므로 자동차의 진단과 점검에는 많은 노력과 비용, 시간이 소요되며 운전자에 의한 정보를 기대하기 힘든 경우에는 진단이나 정비과정에 많은 어려움을 겪게 된다. 따라서 본 연구에서는 운전자에 의한 일반적인 정보와 진동 소음 센서에 의한 정보의 신호처리기술을 종합하여 자동차 부품의 이상 신호 분석을 하였다. 그리고 정상 상태 대비 이상 신호에 따른 진동 소음 데이터 변화율을 계산하여 작동 모드 별 실내 음압에 영향을 미치는 신호 및 해당 주파수 특성을 분석하였다. 이에 따라 자동차 정비 전문가 시스템 구축을 위한 기초 연구로 엔진부의 이상 신호와 각 부품 별 이상 신호로 나누어 분석하여 데이터 처리 과정 및 이상 증상 별 경향 파악에 본 연구의 목적을 둔다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.843-850
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• 2017

The EMG amplitude estimator, which has been investigated as an indicator of muscle force, is utilized as the control input to artificial prosthetic limbs. This paper describes an application of the optimal EMG amplitude estimator to the surface EMG signals recorded during constant isometric %MVC (maximum voluntary contraction) for 30 seconds and reports on assessing performance of the amplitude estimator from the application. Surface EMG signals, a total of 198 signals, were recorded from biceps brachii muscle over the range of 20-80%MVC isometric contraction. To examine the estimator performance, a SNR(signal-to-noise ratio) was computed from each amplitude estimate. The results of the study indicate that ARV(average rectified value) and RMS(root mean square) amplitude estimation with forth order whitening filter and 250[ms] moving average window length are optimal and showed the mean SNR improvement of about 50%, 40% and 20% for each 20%MVC, 50%MVC and 80%MVC surface EMG signals, respectively.

• Tribology and Lubricants
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• v.17 no.3
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• pp.244-250
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• 2001

A rotating axis diagnostic system supported with journal bearing has been established that has been widely used in the industry. In order to measure the most sensitive signals that would be generated in the abnormal operation, sensors which measure AE(acoustic emission), gap and acceleration have been attached at the various location on the experimental apparatus. Data were obtained in the steady state operational condition of the system which was verified through the empirical measurement. Notable discrepancies were observed in RMS acceleration signal which could be utilized to predict the undesirable operational condition of the system.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.90-98
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• 2005

A monitoring system is necessary to make the polishing process more reliable in order to ensure the high quality and performance of the final products. Generally, AE (Acoustic Emission) is known to be closely related to the material removal rate (MRR). As the surface becomes rougher, the MRR and AE increase. Therefore, the surface roughness can be indirectly estimated using the AE signal measured during the polishing. In this study, an AE sensor-based monitoring system was fabricated to detect the very small AE signal resulting from the friction between a tool and a workpiece during polishing. The performance of this monitoring system was estimated according to polishing conditions, the relation between the level of the AE RMS and the surface roughness during the polishing was investigated.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2106-2108
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• 2003

단상 또는 3상의 AC 전원의 전류나 전압 또는 전력을 계측하기 위해 Analog Signal들을 Digital Signal로 변환하여 특정 Algorithm의 연산을 수행하여 결과를 얻는 과정을 Microprocessor를 이용하여 처리하는 방법은 산업현장이나 연구개발에서 흔히 사용하는 방법이다. 본 논문에서는 Microprocessor를 이용하여 보편화된 3가지의 계측 Algorithm인 DFT, True RMS, Summation Algorithm을 사용하여 동일 System에 3상 AC의 전류 부하를 일정 범위에서 가변 하여 인가시키면서 계측 값을 사용하여 Algorithm의 계측 결과의 오차율과 연산에 소요되는 시간과 외부 잡음인 Surge, Impulse, 정전기, 방파, 고조파에 대한 System의 처리 효율을 연구 하였다.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.466-472
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• 2009

An acoustic leak monitoring system(ALMS) using acoustic emission(AE) technique was applied for leakage detection of nuclear power plant's pipeline which is operated in high temperature and pressure condition. Since this system only monitors the existence of leak using the root mean square(RMS) value of raw signal from AE sensor, the difficulty occurs when the characteristics of leak size and shape need to be evaluated. In this study, dual monitoring system using AE sensor and accelerometer was introduced in order to solve this problem. In addition, artificial neural network(ANN) with Levenberg.Marquardt(LM) training algorithm was also applied due to rapid training rate and gave the reliable classification performance. The input parameters of this ANN were extracted from varying signal received from experimental conditions such as the fluid pressure inside pipe, the shape and size of the leak area. Additional experiments were also carried out and with different objective which is to study the generation and characteristic of lamb and surface wave according to the pipe thickness.

• Korean Journal of Optics and Photonics
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• v.25 no.5
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• pp.273-278
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• 2014

We present an algorithm for surface reconstruction from the second-derivative data for free-form aspherics, which uses a subaperture scanning system that measures the local surface profile and determines the three second-derivative values at those local sampling points across the free-form surface. The three second-derivative data were integrated to get a map of x- and y-slopes, which went through a second Southwell integration step to reconstruct the surface profile. A synthetic free-form surface 200 mm in diameter was simulated. The simulation results show that the reconstruction error is 19 nm RMS residual difference. Finally, the sensitivity to noise is diagnosed for second-derivative Gaussian random noise with a signal to noise ratio (SNR) of 16, the simulation results proving that the suggested method is robust to noise.