• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.817-821
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and system, which were hitherto based on linear models. Theory of chaos, which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end millingprocess. Then, it will be verified that cutting force is low-dimensional deterministic chaos calculating Lyapunov exponents, Fractal dimension, Embedding dimension. Aen it will be investigated that the relations between characteristic parameter caculated form sensor signal and tool wear.

• 한국소음진동공학회논문집
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• 제13권1호
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• pp.48-55
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• 2003

Hidden Markov Model(HMM) has a doubly embedded stochastic process with an underlying stochastic process that can be observed through another set of stochastic processes. This structure of HMM is useful for modeling vector sequence that doesn't look like a stochastic process but has a hidden stochastic process. So, HMM approach has become popular in various areas in last decade. The increasing popularity of HMM is based on two facts : rich mathematical structure and proven accuracy on critical application. In this paper, we applied continuous HMM (CHMM) approach with AR coefficient to detect and predict the chatter of lathe bite and to diagnose the wear of oil Journal bearing using rotor shaft displacement. Our examples show that CHMM approach is very efficient method for machine health monitoring and prediction.

• 한국정밀공학회지
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• 제16권6호
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• pp.160-165
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• 1999

In surface grinding, the conditions of the grinding wheel give a significant effect on the ground workpieces comparing with other metal removal provesses. In this paper, to assist the development, a non-contacting optical method by the laser beam is introduced. The in-process measurement of scattering intensities has been made during surface grinding processes and the surface textures of wheel working surfaces are captured. Also, in order to determine the dressing time monitoring method of a grinding wheel, a three-dimensional computer simulation of the grinding operation has been attempted based on the contact mechanism and the surface-shaping system between the grinding wheel and the workpiece. The optimal dressing time is determined by the amount of the grain wear and work surface roughness.

• 한국정밀공학회지
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• 제7권2호
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• pp.47-57
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• 1990

In-process recognition of the cutting states is one of the very important technologies to increase the reliability of mordern machining process. In this study, practical methods which use the dynamic component of the cutting force are proposed to recognize cutting states (i.e. chip formation, tool wear, surface roughness) in turning process. The signal processing method developed in this study is efficient to measure the maximum amplitude of the dynamic component of cutting force which is closely related to the chip breaking (cut-off frequency : 80-500 Hz) and the approximately natural frequency of cutting tool (5, 000-8, 000 Hz). It can be clarified that the monitoring of the maximum apmlitude in the dynamic component of the cutting force enables the state of chip formation which chips can be easily hancled and the inferiority state of the machined surface to be recognized. The microcomputer in-process tool wear monitor- ing system introduced in this paper can detect the determination of the time to change cutting tool.

• 비파괴검사학회지
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• 제27권6호
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• pp.509-519
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• 2007

This paper presents new techniques under development for monitoring the health and vibration of the active components in nuclear power plants, The purpose of this study is to develop an automated system for condition classification of a check valve one of the components being used extensively in a safety system of a nuclear power plant. Acoustic emission testing for a check valve under controlled flow loop conditions was performed to detect and evaluate disc movement for valve failure such as wear and leakage due to foreign object interference in a check valve, It is clearly demonstrated that the evaluation of different types of failure types such as disc wear and check valve leakage were successful by systematically analyzing the characteristics of various AE parameters, It is also shown that the leak size can be determined with an artificial neural network.

• 한국생산제조학회지
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• 제8권1호
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• pp.74-80
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• 1999

Recently, manufacturing work has been transformed to small scale production form with various types to act up to user's expectation from mass production with a little items required in the past. Then FMS using NC type machinaries has been applied actively also in domestic manufacturing line to meet thus tendency, but there are many machining troubles occured during work process not be settled yet. Nowdays high efficiently has been required no less than high precision in grinding work for the improvement of productivity. In this study, to represent more advance FMS can be adapted to thus situation In-process type monitoring method using AE and Current sensors is suggested to investigate the machining condition in grinding process. As results form this experimental study, it is recognized well that grinding conditions and dressing point of in time cab be estimated effectively using monitoring method suggested. Furthermore, surface shape of grinding wheel on voluntary point of in time can be predicted indirectly through the observation and comparison of AE signal waveform obtained as performance of continuous dressing work.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.162-167
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• 2005

Recently, the advanced industries using micro parts are rapidly growing. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro to micro parts. Also, the method of micro-grooving using micro endmilling is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This study deals with condition monitoring using acoustic emission(AE) signal in the micro-grooving. First, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by using the fuzzy C-means algorithm, which is one of the methods to recognize data patterns. These result is effective monitoring method of micro endmill state by the AE sensing techniques which can be expected to be applicable to micro machining processes in the future.

• Tribology and Lubricants
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• 제37권6호
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• pp.203-207
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• 2021

This study presents the development of dielectric constant sensors to measure lubricant properties. The lubricant oil sensor is used to measure oil properties and machine conditions. Various condition monitoring methods are applied to diagnose machine conditions. Machine condition monitoring using oil sensors has advantage over other machine condition monitoring methods. The fault conditions can be noticed at the early stages by the detection of wear particles using oil sensors. Therefore, it provides an early warning in the failure procedure. A variety of oil sensors are applied to check the machine condition. Among all oil sensors, only one sensor can measure the tendency of several properties such as acidity and water content. A dielectric constant sensor is also used to measure various oil properties; therefore, it is very useful. The dielectric constant is the ratio of the capacitance of a capacitor using that material as a dielectric to that of a similar capacitor using vacuum as its dielectric. The dielectric constant has an effect on water content, contaminants, base oil, additive, and so forth. In this study, the dielectric constant sensor is fabricated using MEMS process. In the fabrication process, the shape, gap of the electrode array, and thickness of the insulation material are considered to improve the sensitivity of the sensor.

• 한국의류학회지
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• 제48권1호
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• pp.94-107
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• 2024

This study developed compression pants with excellent wearability and signal quality by approaching the design of wireless sEMG monitoring pants from the perspective of technical design, including the evaluation of wearability and the stable wireless transmission of signals through electrode and circuit design, and using e-textiles. An electrode, sewn with silver thread and a circuit stitched in a zigzag pattern using stainless steel wire, were applied. Additionally, polyurethane sealing tape was used to enhance adherence to the skin and reduce electrical resistance. Conductive snaps completed the design, allowing attachment and detachment to the bio-signal acquisition mainboard. Through the subjects' evaluation, it was determined that the final pants were applied with a pattern reduction rate of 25% to provide superior comfort according to different body parts while also minimizing skin irritation around the thigh circuit. The final pants for wireless sEMG monitoring, which demonstrated stable transmission of wireless measurements, was positively evaluated in terms of cognitive acceptability. This study is significant in that it achieved an optimal design by considering both technical aspects and the electrical characteristics of bio-signal monitoring garments, as well as the wearer's perception when designing smart wear.

• 감성과학
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• 제21권1호
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• pp.83-90
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• 2018

본 연구의 목적은 정신적, 신체적 힐링을 위한 명상용 스마트 의류 개발을 위한 기초연구로서 명상 시 복식호흡 수를 측정함으로써, 의복을 통해 명상의 진입상태를 모니터링 하기 위한 방법을 연구하는 것이다. 이를 위해 본 연구에서는 Single Wall Carbon Nano-Tube (SWCNT)를 기반으로 한 스트레인 게이지 타입의 직물센서를 구현하고, 1차 실험으로 0.1 Hz의 주기로 복부형태의 더미를 5 cm 길이로 2분간 개폐를 반복하여 명상호흡을 시뮬레이션 한 결과 참조전극인 BIOPAC과 직물호흡센서의 신호가 매우 높은 일치도를 나타냈다(p<0.001). 같은 조건으로 2차 본 실험에서 피험자 4명에게 명상호흡을 수행하도록 하였고, 배꼽점, 횡경막 부근 중심과 측면 총 4군데 위치에서 출력된 전압 값을 비교한 결과 배꼽점 중심 위치와 횡경막 측면에서 신호의 일치도가 높고, 크고 안정된 신호형태를 보여 명상호흡을 측정하기에 적합한 위치로 선정되었다. 따라서 본 연구에서는 긴 호흡주기의 명상호흡을 측정하기 위한 직물센서를 구현하고, 이 센서의 명상 호흡수 측정을 위한 신뢰성과 타당성을 검토하며, 인체 상 측정위치에 따른 호흡 수 측정효율을 비교, 고찰하는 것을 목표로 하였다.