• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.672-676
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• 2004

In this paper, measuring system of 5 DOF motion errors are proposed using two capacitive type sensor, a straight edge and a laser interfoerometer. Yawing error and pitching error are measured using the laser interferometer, and rolling error is measured by the reversal method using a capacitive type sensor. Linear motion errors of horizontal and vertical direction are measured using the sequential two point method. In this case, influence of angular motion errors is compensated using the previously measured angular motion errors. In the horizontal direction, measuring accuracy is within 0.05 $\mu$m and 0.27 arcsec, and in the vertical direction, it is within 0.15 $\mu$m and 0.5 arcsec. From these results, it is confirmed that the proposed measureing system is very effective to the measurement of 5 DOF motion errors in the ultra precision feed tables.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.519-520
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• 2010

• Journal of the Korean Society for Precision Engineering
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• v.15 no.5
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• pp.93-99
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• 1998

Although laser interferometer measurement system has advantages of measurement range and accuracy, it has some disadvantages when measurement of multi degrees of freedom of motion are required. Because the traditional error measurement methods for geometric errors (two straightness and three angular errors) of a slide of machine tools measures error components one at a time. It may also create an optical path difference and affect the measurement accuracy. In order to identify and compensate for geometric errors of a moving rigid body in real time processes, an on-line error measurement system for simultaneous detection of the five error components of a moving object is required. Using laser alignment technique and some optoelectronic components, an on-line measurement system with 5 degrees of freedom was developed for the geometric error detection in this study Performance verification of the system has been performed on an error generating mechanism. Experimental results show the feasibility of this system for identifying geometric errors of a slide of machine tools.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.129-130
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• 2011

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.767-768
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• 2010

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.28-36
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• 2006

In this paper, an algorithm to classify the 4 motions of arm and a control system to position control the prosthesis are studied. To classify the 4 motions, we use flex sensors which is electrical resistance type sensor that can measure warp of muscle. The flex sensors are attached to the biceps brchii muscle and coracobrachialis muscle and the sensor signals are passed the sensing system. 4 motion of the forearm - flexion and extension, the pronation and supination are classified from this. Also position of forearm is measured from the classified signals. Finally, A two D.O.F prosthesis arm with RC servo-motor is designed to verify the validity of the algorithm. At this time, fuzzy controller is used to reduce the position error by rotary inertia and noise. From the experiment, the position error had occurred within about 5 degree.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.135-141
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• 2005

Measurement of five DOF motion errors in a ultra precision feed table was attempted in this study. Yaw and pitch error were measured by using a laser interferometer and roll error was measured by using the reversal method. Linear motion errors in the vertical and horizontal directions were measured by using the sequential two point method. In this case, influence of angular motion errors was compensated by using the previously measured ones by the laser interferometer and the reversal method. The capacitive type sensors and an optical straight edge were used in the reversal method and the sequential two point method. Influence of thermal deformation on sensor jig was investgated and minimized by the periodic measurement according to the variation of room temperature. Deviation of gain between sensors was also compensated using the step response data. 5 DOF motion errors of a hydrostatic table driven by the linear motor werer tested using the measurement method. In the horizontal direction, measuring accuracies for the linear and angular motion were within ${\pm}0.02\;{\mu}m$ and ${\pm}0.04$ arcsec, respectively. In the vertical direction, they were within ${\pm}0.02{\mu}m$ and ${\pm}0.05$ arcsec. From these results, it was found that the introduced measurement method was very effective to measure 5 DOF motion errors of the ultra precision feed tables.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.769-772
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• 2005

Five DOF motion errors of a hydrostatic bearing table driven by the coreless type linear motor were compensated utilizing the active controlled capillaries in this study. Horizontal linear motion and yaw error were simultaneously compensated using two active controlled capillaries and vertical linear motion, pitch and yaw error were also simultaneously compensated using three active controlled capillaries. By the compensation, horizontal linear motion accuracy and yaw were improved from 0.16 ${\mu}m$ and 1.96 arcsec to 0.02 ${\mu}m$ and 0.03 arcsec. Vertical linear motion accuracy, pitch and roll were also largely improved from 0.18 ${\mu}m$, 2.26 arcsec and 0.14 arcsec upto 0.03 ${\mu}m$, 0.07 arcsec and 0.02 arcsec. The compensated motion errors were within the range of measuring repeatability which was ${\pm}0.02\;{\mu}m$ in the linear motion and ${\pm}0.05$ arcsec in the angular motion. From these results, it is found that the motion error compensation method utilizing the active controlled capillaries are very effective to improve the five motion accuracies of the hydrostatic bearing tables.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.505-511
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• 2023

In the present study, a deep learning model was established to predict the motion response of small fishing vessels. Hydrodynamic performances were evaluated for two small fishing vessels for the dataset of deep learning model. The deep learning model of the Long Short-Term Memory (LSTM) which is one of the recurrent neural network was utilized. The input data of LSTM model consisted of time series of six(6) degrees of freedom motions and wave height and the output label was selected as the time series data of six(6) degrees of freedom motions. The hyperparameter and input window length studies were performed to optimize LSTM model. The time series motion response according to different wave direction was predicted by establised LSTM. The predicted time series motion response showed good overall agreement with the analysis results. As the length of the time series increased, differences between the predicted values and analysis results were increased, which is due to the reduced influence of long-term data in the training process. The overall error of the predicted data indicated that more than 85% of the data showed an error within 10%. The established LSTM model is expected to be utilized in monitoring and alarm systems for small fishing vessels.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.493-497
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• 2010

Real time coordinate conversion of vessel was realized, we developed motion control algorithm of DC Servo Motor. We made servo control circuit and PCB, also We developed the system using 3-axis Gyro Sensor based Servo Motion Controller. For ship's movement simulation, we made the ship simulator of 6 degree of freedom. With a mounted camera on developed simulator, We tested the desired ship's movement, and the desired result of error tolerance was obtained.