• 디지털융복합연구
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• 제15권11호
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• pp.231-243
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• 2017

본 논문은 전기적 감지 방식 바이오센서의 개념을 리뷰하고, 의류 및 텍스트 기반의 바이오센서의 연구 사례를 조사하였다. 생체 신호를 측정 할 수 있는 바이오센서는 생물학적 감지 물질을 이용하여 생물학적 물질의 물리적, 화학적 특성을 감지하는 장치이다. 따라서 바이오센서를 사용하여 생체신호를 측정할 수 있는 웰니스 의류는 U-Health 서비스를 제공하는데 중요한 역할을 한다. 기존 센서와 다르게 바이오센서의 차별화된 특징은 선택적 반응과 생물학적 물질의 결합을 사용한다는 점이다. 이러한 바이오센서 중 전기적 감지 바이오센서는 전기 신호의 처리로 인해 크기가 매우 작아 유비쿼터스 환경을 조성하는데 이용될 수 있다. 따라서 웰니스 의류를 개발하기 위해 소형화가 쉬운 전기적 감지 바이오센서를 연구할 필요가 있다. 본 논문에서는 전기적 감지 바이오센서(전기화학적 방식, 나노와이어/탄소나노튜브 기반 FET 방식)에 대해 자세히 기술하였다. 마지막으로, 이러한 고찰을 통해 향후 웰니스 의류에 적용 가능할 바이오센서의 기술개발 방향을 제언하였다.

• 한국정밀공학회지
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• 제10권3호
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• pp.81-86
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• 1993

It is well known that the interest on the on-line sensing of tool wear is growing more and more with the aim of controlling machine tools productivity from the point of view of quality. This paper describes the sensing of the amount of flank wear with vision system. To obtain a proper image He-Ne laser generator is used as the lighting source and obtained image is processed with block processing algorithm and morphological image processing method. By means of this system it is possible to evaluate the parameters of tool wear. Experimental tests performed with this system on an NC lathe have shown good performances here described and discussed.

• 감성과학
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• 제20권3호
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• pp.97-108
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• 2017

본 연구의 목적은 스마트 피트니스웨어가 갖추어야 할 요건과 스마트 피트니스웨어의 수용 정도 및 기능 수요를 고찰하고, 이를 기반으로 퍼스널 트레이닝 효과 향상을 지원하는 피트니스용 스마트 스포츠의류의 상품기획 및 디자인 방향을 제시하는 것이다. 이를 위해 전문 피트니스 트레이너를 심층 인터뷰하고 그 응답 자료에 대해 범주분석을 실시한 결과 5개의 범주와 13개 주제어를 도출하였다. 또한 일반 소비자들을 대상으로 설문조사를 실시하여 스마트 피트니스웨어의 수용 정도와 상품개발에 필요한 기능 수요를 탐색하였다. 그 결과 전반적으로 인구통계학적 특성에 따른 차이보다는 운동의 관여도 및 운동관련 문화와 관련된 특성에 따라 스마트 피트니스웨어의 수용 정도에 차이가 있는 것을 발견할 수 있었다. 스마트 피트니스웨어에 대한 기능 수요에 대한 차이점으로는 전문 트레이너의 경우 운동 효과의 과학적 향상에 중점을 두는 반면 일반 소비자는 운동 시 지속성을 고려한 기능을 중요시 하는 것으로 분석되었다. 본 연구 결과를 종합하여 '심박 센싱, 근육 활성도 센싱, 부위별 운동 동작 각도 또는 자세 센싱, 운동량 센싱 등의 기능 탑재', '전문가 라인과 일반 라인별 컨셉 및 컨텐츠 개발', '압박 의류 형태로 디자인', '운동지역에 따른 상품개발의 차별화' 등의 상품기획 및 디자인 방향을 제시하였다.

• 복식
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• 제65권1호
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• pp.118-135
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• 2015

In recent years, smart clothing had been developed in order to better detect and monitor physical movement of the patient, so that such activities such as location identification and biometric recognition could be done. However, most of the sensing devices of smart clothing were limited to smart sensing sports clothing and the designs did not consider the physical characteristics and the behavior of the wearer. Therefore, this study aimed to create an open protection system by developing a wearable sensing device for health monitoring and location information. For this purpose, this study developed eleven types of wearable sensing design that could be commercially sold and worn by people who needed their biological information to be constantly monitored. The study conducted four tests in order to develop three types of sensing devices for various sensing wears. The purpose of this study was to expand the user rang of smart sensing wears, and provide a foundation for the development of distinctive wearable sensing devices reflecting the user. Furthermore, contribute to the design for the person subject to protection.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 추계학술대회 논문집
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• pp.199-203
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• 2001

It is well know that the interest on the on-line sensing of tool wear is groeing more and more with the aim of controlling machine tools productivity form the point of view of quality and quantity. This paper describes the sensing of the amount of flank wear with vision system. To obtain a proper image He-Ne laser generator is used as the lighting source and obtained image is processed with block processing algorithm and morphological image processing method. By means of this system it is possible to evaluate the parameters of tool wear. Experimental tests performed with this system on an NC lathe have shown good performances here described and discussed.

• 비파괴검사학회지
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• 제11권1호
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• pp.31-37
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• 1991

Acoustic emission(AE) signals detected during metal cutting were applied as the experimental test to sensing tool wear and chipping on the NC vertical milling machine. The in-process detection of cutting tool wear including chipping, cracking and fracture has been investigated by means of AE in spite of vibration or noise through intermittent metal cutting, then the following results were obtained 1) When the tool wear is increased suddenly, or the amplitude of AE signals changes largely, it indicates chipping or breaking of the insert tip. 2) It was confirmed that AE signal is highly sensitive to the cutting speed and tool wear. 3) At the early period of cutting, the wear were large and RMS value increased highly by the influence of minute chipping and cracking, etc. Therefore, the above situations should be considered for the time when the tool would be changed.

• 한국정밀공학회지
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• 제9권1호
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• pp.82-95
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• 1992

There is the high interest for sensing of tool wear with the aim of controlling machine tools productivity from the point of view of qualitity. Difficulties in this measurement are also known. This study is on the development of measurement setup for crater wear by CCD image inturning. In this study, the crater wear measurement system consists of the He-Ne gas laser, diffraction grating. CCD camera, noise filter, slit, microcomputer, diverging lens, converging lens and so on. He-Ne laser beam passes through a diverging lens and a diffraction grating is positioned properly. A converging lens focuses so that the interference fringes can be obtained on the crater wear. Performance test revealed that the developed image technique provides precise, absolute tool-wear quantification and reduces human measurement errors. The results obtained are as follows 1. The digitizing of one image requires less than 2ses. 2. It can give detailed information on crater wear with limited times and errors 3. All parameters required by specification are easily obtained for several points of the cutting edge.

• 한국생산제조학회지
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• 제6권3호
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• pp.36-43
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• 1997

In order to make unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstations to provide the required intelligence of the expert. This paper deals with condition monitoring for tool wear and breakage during turning operation. Developing economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique are proposed. The validity of the proposed system is confirmed through the large number of cutting tests.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1998년도 추계학술대회 논문집
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• pp.164-169
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• 1998

This paper deals with condition monitoring for tool wear during tuning operation. To develop economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique are proposed. To identify noise sources of tool wear and reject background noise, noise rejection methodology is proposed. features to represent condition of tool wear are obtained through analysis using adaptive filter and FFT in time and frequency domain. By using fuzzy pattern recognition, we extract features, which are sensitive to condition of tool wear, from several features and make a decision on tool wear. The validity of the proposed system is condirmed through the large number of cutting tests in two cutting conditions.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.1021-1024
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• 2001

Out of all metal-cutting processes, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. In this paper, the vision system of the sensing methods of drill flank wear on the basis of image processing is used to detect the wear pattern by non-contact and direct method and get the reliable wear information about drill. In image processing of acquired image, median filter is applied for noise removal. The vision flank wear area of the drill was measured. Backpropagation neural networks (BPns) were used for no-line detection of drill wear. The neural network consisted of three layers: input, hidden and output. The input vectors comprised of spindle rotational speed, feed rates, vision flank wear, thrust and torque signals. The output was the drill wear state which was either usable or failure. Drilling experiments with various spindle rotational speed and feed rates were carried out. The learning process was peformed effectively by utilizing backpropagation. The detection of the abnormal states using BPNs achieved 96.4% reliability even when the spindle rotational speed and feedrate were changed.