• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.947-951
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• 1997

Recently, the necessity of the detection of abnormal machining process is being emphasized in order to improve the machining accuracy and reduce the cost in unmanned operating system. The vibration by chatter generated in cutting processes within machine tools is a relative motion between tools and workpieces. So, if the chatter occurs, the surface roughness and accuracy of workpieces will be deteriorate and it leads to the rapid wear of tools. The author intended to use the I /sab/RMS (current of root mean square) of current sigals and the movimg C.V. (coefficient of variation) of each phase for the detection method of chatter.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.7 s.94
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• pp.1783-1793
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• 1993

Pattern recognition technique using fuzzy c-means algorithm and multilayer perceptron was applied to classify tool wear states in turning. The tool wear states were categorized into the three regions 'Initial', 'Normal', 'Severe' wear. The root mean square(RMS) value of acoustic emission(AE) and current signal was used for the classification of tool wear states. The simulation results showed that a fuzzy c-means algorithm was better than the conventional pattern recognition techniques for classifying ambiguous informations. And normalized RMS signal can provide good results for classifying tool wear. In addition, a fuzzy c-means algorithm(success rate for tool wear classification : 87%) is more efficient than the multilayer perceptron(success rate for tool wear classification : 70%).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.212-216
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• 1996

Recently, with the development of NC and CNC machine tools and the high labor wage, the cutting process requires the high speed and automatic system which uses industrial robots and the flexible manufacturing system(FMS) that combines several machine tools. In this system, the whole system can be influenced by just one of the machin tools. So it needs to detect a problem and to solve it immediately In in-process state. The monitoring system through measuring the motor current with current sensor has been attracting the attention of lots of researchers view of its low cost and flexibility. By using the pattern discriminant with the detected three-phase-current signal, that is, $I_{RMS}$, a system which can monitor and analyze abnormal machining process condition of the workpiece during the machining will be able to be developed in this research.h.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.150-156
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• 1996

Static variations of cutting forces are estimated using spindle motor current. Static sensitivity of spindle motor current is higher than feed motor current. The linear relationship between the cutting force and RMS value of the spindle motor current is obtained. Using cutting force estimation, tool overload in milling process can be well detected, and cutting force is regulated at a constant level by feedrate adaptive control.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.76-78
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• 1993

간접적인 방법으로 가공중(In process)공구상태를 감시하기 위해, 센서신호를 분석하는 방법으로 시간영역 (Time Domain) 해석과 주파수 영역(Frequency Domain)해석이 주로 이용되어 왔다. 시간영역해석의 경우 RMS,PEak Value, 평균/분산을 이용한 정적분석과 AR 모델, ARMA 모델, Kalman Filter등 동적 시계열 모델이 연구되어 왔다. 주파수영역해석의 경우 푸리에 변환 (Fourier Transform)에 의한 신호해석 기술이 주로 이용되고 있다. 그러나 푸리에 변환된 결과에는 시간정보가 포함되어 있지 않고, 국부적인 변환결과가 전체를 대표하는 성질을 가지고 있다. 이에 비해 웨이브렛(Wavelet) 변환은 고주파성분에 대해서는 시간분해능이 높고, 저주파 성분에 대해서는 주파수분해능이 높은 다중해상도 해석기술로서 국소적인 변동점을 민검하게 검지하는 것이 가능하다. 본연구에서는 엔드밀 가공중 발생하는 공구의 파손을 검출하기 위해, 전류센서로 부터 얻은 이송축 부하 전류의 변화에 웨이브렛 변환을 통해 공구의 파손을 검출하는 방법에 대한 연구결과를 소개한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.86-89
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• 2015

Quantitative Evaluation of Image Quality using Automatic Exposure Control This it leads, the relationship of control and image between of photographing condition, DR proper use method proposing. Chest phantom acquires Chest PA images which it follows in conditional change, Image evaluation factor (SNR (Signal to Noise Ratio), CNR (Contrast to Noise Ratio), PSNR (Peak Signal to Ratio), RMS (Root Mean Square)). It excepted RMS price, SNR, CNR, PSNR the case which uses AEC it came out being high The fact that the quality of image is better there was a case which does not use AEC. but Price it was slight. Image qualitative it was deficient in AEC use presence. Through this, the overall situation and most efficient use of radiation workers is better suited. But Passive AEC use would be appropriate for use rather than proactive AEC.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.994-995
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• 2015

이 논문은 전자석용 전원장치의 안정도 개선에 대하여 기술하였다. 이 전원장치는 4세대 가속기에 설치될 예정이며, 디지털 신호처리 기술을 적용하여 ~10ppm-rms 이하의 출력 전류 안정도를 가진다. 여기서는 전원장치에서 입력 정류기의 리플 성분이 출력 전류 안정도에 미치는 영향을 보였다. 또한 출력 안정도를 향상시키기 위한 전원장치 전체의 접지 설계에 대해서 기술하였다.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.451-452
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• 2014

본 논문에서는 단상 계통연계형 컨버터의 전원 위상각을 추종함에 있어 필수적인 전압 센서의 옵셋 오차에 대한 영향을 분석하고 이를 검출 및 보상하기 위한 알고리즘을 제안하였다. 전원전압 측정에 따른 옵셋 오차는 전원 주파수의 1배 맥동을 야기하여 전원 위상각이 왜곡된다. 왜곡된 전원 위상각에 의한 좌표변환시 동기 좌표계 dq축 전류에 전원 주파수 1배의 맥동을 야기하며 이는 계통측 상전류에 직류성분과 전원 주파수 2배의 고조파 성분을 발생시키게 된다. 따라서, 본 논문에서는 전원측정시 야기되는 옵셋 오차의 영향을 분석하고 이의 검출신호로 전원 위상각 제어기의 적분출력을 선정하였다. 또한 RMS(Root Mean Square) 기법을 이용하여 옵셋 성분을 검출 및 보상하는 알고리즘을 제안하였다. 제안된 알고리즘의 성능은 시뮬레이션과 실험을 통하여 검증하였다.

• Journal of the Korean Society of Safety
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• v.29 no.2
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• pp.12-17
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• 2014

This paper is aimed to analyze the characteristics of simultaneous voltage, current and temperature signals for poor connection on electrical connector. In order to attain this purpose, detected were the current and voltage signals on electric wire with series arc, named arc signals, and also monitored were the changes of RMS, instantaneous value of waveform in time domain and temperature value with video. Two states are made normal state over $5kgf{\cdot}cm$ and poor connections state below $0.5kgf{\cdot}cm$ by screw gage. In the voltage signal case, the voltage drop was increased with which the current was increased. In the current signal case, poor connections at the time interval 1~4A all showed "shoulder", as distinct difference from the normal state shown waveform pattern. In the temperature signal case, poor connections are twice at 1A and five times at 4A in the normal state. The temperature continues insulation of electrical wiring and connector can be carbonized. The results of this study will be effectively used in developing the preventive devices and system for electric fire by poor connections.

• Korean Journal of Optics and Photonics
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• v.11 no.5
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• pp.347-352
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• 2000

We have stabIhzed the laser frequency of a commercial dIode laser using a ULE (Ultra-low expansion material) reference cavIty and the cunent modulation charactenstics of the dIode itself The liuewIdth of the frce running laser was about a 1 MHz (rms) for a sampling time of 1 s and the drift rate was 300 kHz/s. Vvhen the laser is locked to oue sIde of the transmission signal from the ULE reference cavity, the lincwidth was reduced to 46 kHz (nus) for a sampling time longer than 10 ms. The root Allan variance was less than 2 kHz for a sampling time langeI than10 ms. 10 ms.