• Journal of Bio-Environment Control
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• v.15 no.4
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• pp.412-416
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• 2006

A magnetic field oscillator was designed and made. The oscillator was installed around a water pipe and radiated into water which was provided for vegetables cultivation. The oscillator was made with a helmholtz coil and installed a magnetic field sensor inside. The class E amplifier circuit with frequency variance was also used. Hydroponic and soil cultural methods were used for cultivation of lettuce and chinese cabbage with magnetic field water and without. Vitamin C ingredients in the lettuce and chinese cabbage which were grown with magnetic field water were 2.8 times and 1.2 times higher than without the magnetic water. Moreover, the growth acceleration effect of vegetables was shown in lettuce cultivated with the magnetic field water.

• Journal of Sensor Science and Technology
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• v.13 no.2
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• pp.110-113
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• 2004

We have designed and fabricated the YBCO single layer directly-coupled SQUID magnetometers for the purpose of magnetocardiography in a magnetically disturbed environment. The SQUID magnetometers were designed three different types of pickup coil such as solid type, PL type I and PL type II for further stable fluxed-locked-loop operation without magnetic shielding. Magnetometer was fabricated with a single layer YBCO thin film deposited on STO(100) bicrystal substrate with misorientation angle of $30^{\circ}$. We have achieved a magnetic field noise BN of 30 fT/$Hz^{1/2}$ at 100 Hz, and less than 70 fT/$Hz^{1/2}$ at 1 Hz. The PL type II SQUIDs have exhibited the most stable fluxed-locked-loop operation in a magnetically unshielded environment.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.39-45
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• 2002

A simple and low cost stylus profiler made of ferrite cores is developed. The devised profiler consists of a contact probe, a measuring transducer, a signal processing unit, and a motorized stage. The contact probe attached to 4-bar spring maintains sufficient stiffness to protect disturbances. An overlap-area type inductive position sensing system is selected as a measuring transducer, which has high sensitivity, repeatability and linearity. The transducer is composed of coil bundles and ferrite cores which have good electromagnetic characteristics in spite of low cost. The repeatability of the profiler with the proposed inductive sensing system is better than 50nm. Experimental results are shown that the proposed profiler can measure the line or 3D profile of an object with sub-micron features.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.215-221
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• 2008

무인 운반설비의 자동화 시스템 개발의 한 부분으로써 여러 Vision 센서 중 레이저 센서를 이용하여 작업공간상에 있는 판재류와 코일류의 경계부분을 인식한다. 다음으로 인식한 물체의 경계를 이용하여 3차원 공간상의 위치좌표를 추출하여 무인크레인에 이동해야할 위치좌표를 전달한다. 본 연구에서는, 첫 번째 레이저 센서를 이용한 물체의 경계 추출, 두 번째 레이저 센서의 z축 기울기 각 추출, 세 번째 인식한 경계를 이용하여 물체의 2차원 위치좌표 추출, 네 번째 레이저 센서를 이용하여 판재와 코일의 판별, 다섯 번째 물체 판별의 결과에 따른 판재와 코일의 3차원 위치좌표 추출을 목적으로 한다. 본 연구의 결과는 무인 운반설비의 자동화 시스템 개발에 상당한 도움이 될 것으로 기대된다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.353-354
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• 2014

An active vibration control technique of a time-varying cantilever beam is proposed in this study. A simple in-house coil sensor instead of expensive commercial sensors was used to measure the vibrational displacement of the beam. Active band pass filters and artificial neutral net works detect the frequencies, amplitudes, and phases of the main vibration mode. The time constants of the low pass filter representing the positive position feedback controller are updated in real-time, which generates the control voltage input to actuate the piezoelectric actuator and suppress the vibration. An experiment was successfully performed to verify the algorithm for a cantilever beam, which fundamental natural frequency arbitrarily varies between 9 Hz ~ 18 Hz. The present active vibration suppression technique can be applied to variety of structures which undergoes large variation of dynamic characteristics while operating.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.421-428
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• 1997

Magnetic field sensors made from superconducting quantum interference device (SQUID) are the most sensitive low-frequency sensors available, enabling measurements of extremely weak magnetic fields from the brain. Neuromagnetic measurements allow superior spatial resolution, compared with the present electric measurements, and superior temporal resolution, compared with the fMRl and PET, providing useful informations for the functional diagnoses of the brain. We developed a 4-channel SQUID system for neuromagnetic applications. The main features of the system are its simple readout electronics and compact pickup coil structure. A magnetically shielded room has been constructed for the reduction of environmental magnetic noises. The developed SQUID system has noise level lower than the magnetic noise from the brain. Magnetic field signals of the spontaneous r-rhythm activity and auditory evoked magnetic fields have been measured.

• ETRI Journal
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• v.31 no.6
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• pp.695-702
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• 2009

We propose a lens-drive unit composed of an ionic polymer-metal composite (IPMC) for an auto-focus compact camera module in cellular phones to solve the power consumption problem of voice coil motors which are widely used in commercial products. In this research, an IPMC incorporated into a lens-drive unit is designed to implement a large displacement in low-power consumption by using an anisotropic plasma treatment. Experimental results show that a camera module containing IPMCs can control and maintain the position of the lens by using proportional integral derivative control with a photo-reflective position sensor despite the non-linear actuation behavior of IPMCs. We demonstrate that the fabrication and commercialization of a lens actuator that has a large displacement and low power consumption using IPMCs is possible in the near future.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.288-294
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• 2013

The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.4
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• pp.92-101
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• 1996

Due to I:he rapid increase of vehicles and poor availability of roads, traffic congestion problem is about to explode. To solve this problem, we need real time information about traffic flow to control traffic signals dynamically. Until now loop coil is the most prevalent sensor used for obtaining traffic flow information. However, it is not able to track individual vehicles which is essential in estimating the average vehicle speed. As a result, image sensors started to find their role in this problem domain. Several systems based on image sensors were proposed which assumes either gray level or color image sequence. In this paper, we propose moving vehicle tracking method based on fizzy clustering assuming a wlor image sequenc.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.52-57
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• 2019

The key technology of the fourth industrial revolution is artificial intelligence and machine learning. In this study, FMEA was performed on fuel pumps used as key items in most systems to identify major failure components, and artificial neural networks were built using big data. The main failure mode of the fuel pump identified by the test was coil damage due to overheating. Based on the artificial neural network built, machine learning was conducted to predict the failure and the mean error rate was 4.9% when the number of hidden nodes in the artificial neural network was three and the temperature increased to $140^{\circ}C$ rapidly.