• 한국지능시스템학회논문지
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• 제24권1호
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• pp.58-63
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• 2014

자기테이프를 사용하는 대부분의 경량무인운반차들(AGCs)은 디지털 자기유도센서를 사용한다. 디지털 자기유도센서는 On/Off 타입으로 자기테이프의 위치측정 정밀도가 10~50 mm의 오차를 가진다. 또한 경량무인운반차에 설치된 모터의 자기장이나 주변 환경의 외부 자기장, 지자기 등으로 인하여 정확한 위치를 추정하기 힘들다. 이러한 오차로 인하여 경량무인운반차의 주행 시에 잦은 흔들림이 발생하게 되고, 정도가 심할 경우 이탈현상이 발생하게 된다. 따라서 본 논문은 양극성 아날로그 자기유도센서에 퍼지 추론 시스템의 적용을 제안한다. 퍼지는 다른 알고리즘에 비하여 내고장성과 불확실성에 강인하고, 실시간 작동에 유리하며, 비선형시스템에 사용하기 적합하다. 선행과제에서 제작한 양극성 아날로그 자기유도센서로 threshold를 두어 디지털 자기유도센서를 형성하고, 이를 이용하여 자석위치 값을 계산한다. On으로 인식된 아날로그 Hall sensor의 출력을 이용하여 퍼지 추론 시스템을 설계하고, 그 출력으로 디지털출력 값을 개선한다. 실험 결과, 제안된 방법이 기존의 자기유도센서보다 성능이 향상된 것을 확인하였다.

• 대한기계학회논문집B
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• 제39권2호
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• pp.147-152
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• 2015

본 논문은 감동, 두려움 등 인간의 급격한 감정이나 온도 변화에 따른 피부 입모근 수축 (소름)현상 감지를 위한 정전용량형 전도성 폴리머 센서를 제안하였다. 전도성 폴리머를 이용한 소자 제작을 통해 소자의 착용감을 향상시켰으며, 기존 정성적 소름측정 방식에 비해 정확하고 객관적인 측정을 가능케 하였다. 인공적인 소름돌기를 이용한 실험결과, $0{\sim}326{\mu}m$ 의 정적인 소름의 높이를 $-0.00252%/{\mu}m$의 민감도, 25.9 %의 비선형도로 측정하였다. 또한, 실제 인간의 피부에 부착하여 갑작스런 체온변화의 조건에서 -6.2 fF 과 -9.2 fF 의 정전용량 변화를 측정함으로써 높이 $145{\mu}m$ 와 $194{\mu}m$ 의 피부 소름을 측정하였다. 제안된 소자는 피부 입모근 수축현상에 따른 인간의 소름을 객관적이고, 정량적으로 측정함으로써 인간이 느끼는 급격한 감정변화나 환경변화 정도를 수치화 할 수 있는 방법을 제시하였다.

• 대한전자공학회논문지
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• 제27권11호
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• pp.62-68
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• 1990

표준 Si 공정기술을 이용하여 칩의 크기가 $1.7{\times}1.7{mm^2}$인 소형 압저항형 Si 압력센서를 제작하고 그 동작 특성을 평가하였다. 제작된 센서는 크기 $1.0{\times}1.0{mm^2}$, 두께 $20{\mu}m$의 n형 Si 다이아프램상에 4개의 붕소 확산저항이 브릿지 형태로 연결된 칩 구조를 가지며 최종적으로 게이지압을 측장할 수 있도록 상온 상압하에서 패키징하였다. 이 센서의 동작특성은 상온에서 압력감도 $14.2{\mu}V/V{\cdot}mmHg$ 정격 압력범위 0~760mmHg, 최대 비선형성 $1.0{\%}$ FS로 평가되었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2331-2334
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• 2003

The basic difference between the EKF(Extended Kalman Filter) and UKF(Unscented Kalman Filter) stems from the manner in which Gaussian random variables(GRV) are represented for propagating through system dynamics. In the EKF, the state distribution is approximated by a GRV, which is then propagated analytically through the first-order linearization of the nonlinear system. This can possibly introduce large errors in the true posterior mean and covariance of the transformed GRV, which may lead to sub-optimal performance and sometimes divergence of the filter. However, the UKF addresses this problem by using a deterministic sampling approach. The state distribution is also approximated by a GRV, but is now represented using a minimal set of carefully chosen sample points. These sample points completely capture the true mean and covariance of the GRV, and UKF captures the posterior mean and covariance accurately up to the 2nd order(Taylor series expansion) for any nonlinearity. This paper utilizes the UKF to determine spacecraft orbit when only magnetometer is available. Several catastrophic failures of spacecraft in orbit have been attributed to failures of the spacecraft mission. Recently studies on contingency-major sensor failure cases- have been performed. For mission success, contingency design or plan should be implemented in case of a major sensor failure. Therefore the algorithm presented in this paper can be used for a spacecraft without GPS or contingency design in case of GPS failure.

• International Journal of Aeronautical and Space Sciences
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• 제11권4호
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• 대한기계학회논문집A
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• 제20권12호
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• pp.3909-3916
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• 1996

Magnetic bearing is the machine element that supports the shaft without mechanical contact using the magnetic force induced by permanent magnet of electromagnet. Active magnetic bearing system is composed of sensor, controller, power amplifier, and electromagnet. If all the elements were dieal, shaft position could be controlled to sensor resolution, Because each elements inreal system have mechanical and electricla losses and nonlinearity, it is impossible to attain the desired performance using general control algorithm. So far it has been studied on improvement of the control algorithm of the electric characteristics of each elements. Another factors to affect shaft behavior are the manufacturing errors due to machine work, and assembling errors due to accumulate manufacturing errors of the radial magnetic bearing. This paper describes that the shaft behavior due to accumulate manufacturing errors and asymmetric bolting. This paper describes that the shaft behavior due to assembling errors of the radial bearings donot affect the rotaitonal accuracy of the shaft. But when the amplitude of the assembling errors increasees over the certain value, the bearing can not support the shaft properly.

• Journal of Magnetics
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• 제14권1호
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• pp.42-46
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• 2009

The measurement of external magnetic field orientation using Giant Magneto Impedance (GMI) sensors has been performed. A soft magnetic alloy of $Co_{30}Fe_{34}Ni_{36}$ was electroplated on a Si wafer with a CoFeNi seed layer. V-shaped microwire patterns were formed using a conventional photolithography process. An external magnetic field was generated by a rectangular AlNiCo permanent magnet. The reference direction was defined as the external magnetic field direction oriented in the middle of 2 GMI devices. As the orientation of the magnetic field deviated from the reference direction, variation in the field component along each device introduced voltage changes. It was found that, by taking the voltage difference between the left and right arms of the Vshaped device, the nonlinearity of each device could be significantly reduced. The fabricated angle sensor had a linear range of approximately $70^{\circ}$ and an overall sensitivity of approximately 10 mV.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1437-1445
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• 2014

In this paper a novel method for angular position determination using sensors with sin/cos output and without an excitation signal, is presented. The linearization of the sensor transfer characteristic and digitalization of the measurement results are performed simultaneously with a goal to increase the measurement resolution. This improvement is particularly important for low angular velocities, and can be used to increase the resolution of incremental Hall, magnetic and optical sensors. This method includes two phases of sin/cos signal linearization. In the first linearization phase the pseudo-linear signal is generated. The second linearization phase, executed by the two-stage piecewise linear ADC, is an additional linearization of the pseudo-linear signal. Based on the LabVIEW software simulations of the proposed method, the contribution of each processing phase to a final measurement error is examined. After the proposed method is applied within $2{\pi}$ [rad] range, the maximal nonlinearity is reduced from 0.3307 [rad] ($18.9447^{\circ}$) to $3{\cdot}10^{-4}$ [rad] ($0.0172^{\circ}$).

• 한국정밀공학회지
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• 제9권2호
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• pp.36-43
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• 1992

In this paper, a robot assembly wrist, which is able to assemble chamferless parts, has been developed. The RCC (Remote Center Compliance) structure is used as a basic structure. 5 position sensors and 4 pneumatic actuators are installed additionally to measure the deformation of RCC structure and correct the errors actively. Due to the restricted direction of actuation, a decision rule which selects the suitable actuator according to the position sensor signals is needed. For this purpose, a neural network is used and it is experimentally shown that the nerual network overcomes system's nonlinearity. This paper presents fundamental experiment results for the insertion of parts with several clearance.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 하계학술대회 논문집
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• pp.168-171
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• 2002

A SSIMT(Suppressed Sidewall Injection Magnetotransistor) sensor with high linearity is presented in this thesis. The prototype is fabricated by using the Hynix 0.6$\mu\textrm{m}$ P-substrate twin-well double poly three-metal CMOS Process. The fabricated SSIMT shows that variation of the collector current is extremely linear by varing the magnetic induction from -200mT to 200mT at I$\_$B/=500${\mu}$A, V$\_$CE/=2V and V$\_$SUB/=5V. The relative sensitivity is up to 120%/T. At B = 0, magnetic offset is about 79mT, there relative sensitivity is 30.5%/T. The nonlinearity of the fabricated SSIMT is measured about 1.4%.