• 제어로봇시스템학회논문지
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• 제12권6호
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• pp.608-613
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• 2006

Any input acceleration that bends RLG dithering axis causes flexure error, which is a source of the noncommutative error that can not be compensated by simply using integrated gyro sensor output. This paper introduces noncommutative error equations that define attitude errors caused by flexure errors. In this paper, flexure error is classified as sensor level error if the sensing axis coincides with the dithering axis and as system level error if the two axes do not coincide. The relationship between gyro output and the rotation vector is introduced and is used to define the coordinate transformation matrix and angular motion. Equations are derived for both sensor level and system level flexure error analysis. These equations show that RLG based INS attitude error caused by flexure is directly proportional to time, amount of input acceleration and the dynamic frequency of the vehicle.

• 한국자동차공학회논문집
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• 제5권1호
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• pp.69-78
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• 1997

Main sources of the vibration in gear driving system are transmission error and backlash. Transmission error is the difference of the rotation between driving and driven gear due to tooth deformation and profile error. Vibro-impacts induced by backlash between meshing gears lead to excessive vibration and noise in many geared rotation systems. Nonlinear dynamic characteristics of the gear driving system due to transmi- ssion error and backlash are investigated. Transmission error is calculated for spur gear. Nonlinear equation of motion for the gear driving system is developed with the calculated transmission error and backlash. Numerical analysis of the equation and the experimental results show the existence of meshing frequency, superharmonic compon- ents. Instability of the gear driving motion is found on the basis of Mathieu equation. Rattle vibration due to backlash is also discussed on the basis if nonlinear jump phenomenon.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.472-477
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• 2003

Spindle state monitoring is getting more and more important according to the technology trend of spindle that is accurate and automated. Spindle state monitoring is to measure the state of rotation vibrations. The spindle rotation error motion detected by sensing device includes rotation object's unbalance, external forced vibrations, shape error of spindle, as well as measuring error of monitoring device. In this paper, we have inspected the runout characteristics. Also, we introduce the way to exclude the runout element that appear while you monitor a spindle state.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1722-1723
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• 2007

This paper describes a simple method to reduce rotation angle error of mobile robot using omni-wheel[3](omni-bot). This method can be applied to not only omni-bot, but also other robot with a large number of servo motor. Robot using many servo motor as omni-bot is complicated for hardware and software, each servo motor has difficulty in synchronizing. Three servo motor, three omni-wheel and three serial servo motor controller is used, PC or Micro Processor interface with the serial servo controller through "SSC100" protocol. In order to check the improvement of the proposed serial servo synchronization compared to existing sequential communication method. comparing object is rotation angle error of omni-bot. The results of this make building of omni-bot system easy and decrease rotation angle error.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.95-101
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• 2020

We studied the Implementation and design of inertial sensor that enables to improve performance by reduce the noise of rotor which Angle of inclination. Analyze model equation including motion equation and error, signal processing filter algorithm on high frequency bandwidth with eliminates error using estimation of error coefficient method is was designed and the prototype inertial sensor showed the pick off noise up to 0.2 mV and bias error performance of about 0.06 deg/hr by the experiments. Accordingly, we confirmed that the design of inertial sensor was valid for high rotation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.762-766
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• 2003

In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

• Journal of the Optical Society of Korea
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• 제18권4호
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• pp.335-340
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• 2014

Based on Zernike polynomial fitting, we propose an algorithm believed to be new for interferometric measurements of rotationally asymmetric surface deviation of optics. This method tests and calculates each angular surface by choosing specified rotation angles with lowest error. The entire figure can be obtained by superimposing these sub-surfaces. Simulation and experiment studies for verifying the proposed algorithm are presented. The results show that the accuracy of the proposed method is higher than single-rotation algorithm and almost comparable to the rotation-averaging algorithm with fewer rotation measurements. The new algorithm can achieve a balance between the efficiency and accuracy.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.205-206
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• 2013

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 추계학술대회 논문집
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• pp.417-418
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• 2006

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.587-590
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• 1999

Gaze detection is to locate the position on a monitor screen where a user is looking at. We implement it by a computer vision system setting a camera above a monitor, and a user move (rotates and or translates) her face to gaze at a different position on the monitor. Up to now, we have tried several different approaches and among them the Two Neural Network approach shows the best result which is described in this paper (1.7 inch error for test data including facial rotation. 3.1 inch error for test data including facial rotation and translation).