• 한국정보전자통신기술학회논문지
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• 제13권2호
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• pp.123-128
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• 2020

본 논문에서는 주파수 변화 감지 회로 (FVSC : frequency variation sensing circuit)를 포함하는 부궤환 루프를 가지는 저잡음 위상고정루프를 제안하였다. 위상 고정 상태에서 전압제어발진기의 출력주파수가 변화할 때 주파수 변화 감지 회로는 루프 필터의 커패시터의 전하량을 조절하여 제안한 위상고정루프의 위상잡음과 지터 특성을 개선할 수 있다. 위상고정루프의 출력 주파수가 증가하면 주파수 변화 감지 회로가 루프 필터 커패시터 전하를 감소시킨다. 이는 루프필터 출력 전압을 하강하게 하여 위상고정루프 출력 주파수가 하강하게 된다. 추가된 부궤환 루프는 제안한 위상고정루프의 위상잡음 특성을 더욱 더 좋게 한다. 주파수 변화 감지 회로에 사용된 커패시터 크기는 영점을 결정하는 루프 필터 커패시터 크기와 비교하여도 아주 작은 크기이어서 칩 크기에 영향을 미치지 않는다. 제안된 저잡음 위상고정루프는 1.8V 0.18㎛ CMOS 공정을 이용하여 설계되었다. 시뮬레이션 결과는 273fs 지터와 1.5㎲ 위상고정시간을 보여주었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
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• pp.1549-1552
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• 2003

Semiconductor gas sensor using tin oxide as sensing material has been used to detect gases based on the fact that impedance of the sensing material varies when the gas sensor is exposed to the gases. This variation comprises of two parts. The first one is variation in resistance of the sensing material and the other is expressed in terms of the sensor capacitance variation. Normally, only variation of the sensor resistance is considered. In this paper, using AC measurement with a capacitor-coupled inverting amplifier circuit, both changes in the sensor resistance and variations in the sensor capacitance were investigated. These characteristics were represented as magnitude gain and phase shift of AC signal at a specific frequency after passing it through the sensor and the designed circuit. A two-stage artificial neural network, which utilized the information above, was employed to identify and quantify three combustible gases: methane, propane and butane. The network outputs were approximately proportional to concentrations of test gases with reasonable level of error.

• Journal of electromagnetic engineering and science
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• 제12권1호
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• pp.37-44
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• 2012

This paper describes a compact and novel wireless vital sign sensor at 2.4 GHz that can detect heartbeat and respiration signals. The oscillator circuit incorporates a planar resonator, which functions as a series feedback element as well as a near-field radiator. The periodic movement of a human body during aerobic exercise could cause an input impedance variation of the radiator within near-field range. This variation results in a corresponding change in the oscillation frequency and this change has been utilized for the sensing of human vital signs. In addition, a surface acoustic wave (SAW) filter and power detector have been used to increase the system sensitivity and to transform the frequency variation into a voltage waveform. The experimental results show that the proposed sensor placed 20 mm away from a human body can detect the vital signs very accurately.

• 전기전자학회논문지
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• 제22권1호
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• pp.174-179
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• 2018

본 논문에서 저전력 PMIC를 위한 고효율 DC-DC 변환기를 설계하였다. IoT 및 웨어러블 기기의 발전에 따라 전력 공급을 위한 고효율 에너지 습득 기술이 중요해지고 있다. 에너지 습득을 통해서 얻을 수 있는 전압은 낮고 넓은 분포의 값을 가지므로 이를 사용하기 위해서 넓은 입력 전압 범위에서 고효율을 얻을 수 있는 설계 기법이 필수적이다. 넓은 입력 전압 범위에서 일정한 스위칭 주파수를 얻기 위해 전원 전압 변화 감지 회로를 이용한 주파수 보상 회로를 설계했으며, 낮은 전력에서 고효율을 얻기 위해 burst-mode 제어 회로를 구성하여 정밀한 스위칭 동작을 제어하였다. 설계한 DC-DC 벅 변환기는 0.95~3.3V의 입력 전압 조건에서 0.9V를 출력하며 부하 전류가 180uA일 때 최대 78%의 효율을 얻을 수 있다.

• IEIE Transactions on Smart Processing and Computing
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• 제5권1호
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• pp.10-16
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• 2016

In this paper, a design for a fully digital voltage sensor using a 32-nm fin-type field-effect transistor (FinFET) is presented. A new characteristic of the double gate p-type FinFET (p-FinFET) is examined and proven appropriate for sensing voltage variations. On the basis of this characteristic, a novel technique for designing low-power voltage-to-time converters is presented. Then, we develop a digital voltage sensor with a voltage range of 0.7 to 1.1V at a 50-mV resolution. The performance of the proposed sensor is evaluated under a range of voltages and process variations using Simulation Program with Integrated Circuit Emphasis (SPICE) simulations, and the sensor is proven capable of operating under ultra-low power consumption, high linearity, and fairly high-frequency conditions (i.e., 100 MHz).

• 한국안전학회지
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• 제32권1호
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• pp.21-26
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• 2017

An IoT-based particulate matter (PM2.5) sensing device (PSD) is developed. The PSD consists of a PM2.5 sensor, signal processing circuit, and wi-fi enabled-microprocessor along with temperature and humidity sensors. The PSD estimates PM2.5 density by measuring light scattered by PM2.5. To gauge performance of the PSD, PM2.5 density of open air was measured with the PSD and compared with that of the collocated-government-certified measuring station. Measurements were taken at a sampling frequency of 100 Hz and moving-averaged to remove measurement noise. When compared to the result of the measuring station, average percentile error of PM2.5 density from the PSD is found to be 31%. A correlation coefficient is found to be 0.72 which indicates a strong correlation. Instantaneous variation, however, may far exceed average errors, leading to a conclusion that the PSD is more suitable for estimating average trend of PM2.5 density variations than estimating instantaneous PM2.5 density.