• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.310-312
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• 2009

The heterodyne laser interferometer has been widely used in precise measurement field. However, the accuracy is limited by the nonlinearity error caused from incomplete laser sources and nonideal optical components. In this paper, we propose the Dual-EKF which estimates states and weights simultaneously to improve the resolution of heterodyne laser interferometer. As a proof, we demonstrate the effectiveness of our proposed method through experimental results.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1638-1642
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• 2003

Piezoactuator using a flexure hinge mechanism is often used in the precision stages. When the total size of the hinge mechanism become small compared with the deformation of the hinge mechanism, the geometrical nonlinearity makes a considerable error in the output displacement. In this research, the incremental method based on the matrix method is developed to model the effect of the geometrical nonlinearity. Developed modeling method is applied to derive the error of output displacement of the bridge-type hinge mechanism and its results are derived with respect to the design parameters. This method can be easily used to the design optimization of the hinge mechanism and analysis results show that the geometrical nonlinearity error should be considered to achieve a high accuracy to the piezoactuators.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.597-599
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• 2006

In this paper, we propose an artificial intelligence method to compensate the nonlinearity error which occurs in the heterodyne laser interferometer. Some superior properties such as long measurement range, ultra-precise resolution and various system set-up lead the laser interferometer to be a practical displacement measurement apparatus in various industry and research area. In ultra-precise measurement such as nanometer or subnanometer scale, however, the accuracy is limited by the nonlinearity error caused by the optical parts. The feedforward neural network trained by back-propagation with a capacitive sensor as a reference signal minimizes the nonlinearity error and we demonstrate the effectiveness of our proppsed algorithm through some experimental results.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 추계학술대회 논문집
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• pp.249-250
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• 2007

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 추계학술대회 논문집
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• pp.367-368
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• 2006

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.271-272
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• 2007

In heterodyne laser interferometer, we use a phase difference between two beams to calculate target's length. However, there exist an nonlinearity error when measuring length in nanoscale. It is caused from frequency-mixed problem of two polarized beams, called cross talks. This fact limits the usefulness of an laser interferometer. To compensate the error, we propose a WLS(weighted least square) algorithm, which will reduce nonlinearity error and make a better optimization in heterodyne laser interferometer.

• Journal of information and communication convergence engineering
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• 제13권3호
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• pp.167-171
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• 2015

A radio over fiber (RoF) system is a kind of analog optical transmission system and considered as a strong candidate for the next-generation fronthaul link in the future mobile network. In RoF systems, nonlinearity compensation is essential to increase the link capacity. In this paper, we propose a nonlinearity detection and compensation scheme using a monitoring channel in RoF systems. A monitoring channel is added at the transmitter site and used for transmitting a reference signal in an RoF transmission. The nonlinearity in the RoF transmission is detected by comparing the received monitoring signal and the original reference signal at the receiver site. Finally, the nonlinearity is compensated at the receiver by giving the reverse function of the detected nonlinearity. Our results show that the proposed scheme can almost remove the error vector magnitude degradation induced by the nonlinearity in the RoF system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.86-88
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• 2007

In the semiconductor manufacturing industry, the heterodyne laser interferometer plays as an ultra-precise measurement system. However, the heterodyne laser interferometer has some unwanted nonlinearity error which is caused from frequency-mixing. This is an obstacle to improve the measurement accuracy in nanometer scale. In this paper we propose a compensation algorithm based on RLS(recursive least square) method and artificial intelligence method, which reduce the nonlinearity error in the heterodyne laser interferometer. With the capacitance displacement sensor we get a reference signal which can be transformed into the intensity domain. Using the back-propagation Neural Network method, we train the network to track the reference signal. Through some experiments, we demonstrate the effectiveness of the proposed algorithm in measurement accuracy.

• 한국정밀공학회지
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• 제18권9호
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• pp.171-178
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• 2001

The nonlinearity of a laser interferometer usually ranges from sub-nanometer to several manometers. This nonlinearity, which has periodic characteristics, limits the accuracy of the interferometer at the sub-nanometer level. The nonlinearity error of the one-frequency homodyne interferometer with quadrature fringe detection results from a number of factors including polarization mixing by imperfect optical elements, unequal gain of photo detectors, lack of quadrature between two signals and misalignment. In this paper, we described a method for measuring and compensating the nonlinearity of homodyne interferometer using the elliptical fitting technique with least-square method. Experimental results demonstrate that $^\pm$3.5 nm nonlinearity can be reduced to $^\pm$0.2 nm level.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.283-284
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• 2007

In this paper we introduce a compensation of nonlinearity Heterodyne laser interferometer. The Laser Interferometer is used for length measurement in various industries. However, it has nonlinearity error caused by the imperfect optical equipment. This acts as an obstacle in the measurement improvement. We propose an adaptive error compensation using least mean square(LMS) to improve precision.