• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.03b
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• pp.12-12
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• 2010

The hall probe measurement system was used to measure the critical current distribution of superconducting coated conductor. The system consists of reel to reel moving apparatus, 7 array hall probe, a rotary encoder and permanent magnet. The magnetic field profile across the width of superconducting coated conductor using Bean's critical state model was calculated. The effect of various parameters of the formulas on the magnetic field distribution and the effect of shape and size of artificial defects, which were formed on the surface of SmBa2Cu3O7-d(SmBCO) coated conductor using laser marking system, on the hall probe magnetic field signal of the hall probe measurement system was investigated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.1019-1022
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• 2002

Pipe-cutting machines have been used in many fields. Recently, an automatic pipe-cutting machine that uses magnet has born developed. In this paper, a magnetic-type automatic pipe-cutting machine that attaches itself and performs unmanned cutting process is proposed. It is designed that there is a room at the bottom of its body to contain a magnet. And it uses magnetic force between the magnet and the pipe surface to prevent slip and to attach the machine to the pipe against gravity. Also the magnetic force is adjustable by changing the gap between the magnet and the pipe. This machine is, however, necessary to control cutting velocity for the elevation of work efficiency and the adjustable faculties. During pipe cutting process, the gravity acting on the pipe-cutting machine widely varies. That is, the cutting machine gets fast when moving from the top to the bottom of the pipe and slow when moving from the bottom to the top. Actually the system is kind of a non-linear system where the gravity is function of climbing angle of the cutting machine along the pipe. Especially jerking motion is critical. Therefore, authors design the non-linear controller that estimates the current position of the machine along the pipe and compensates the effect of gravity in this paper. It receives the feed back signal from the encoder.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.127-131
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• 2003

This paper describes an initial pole position estimation method of a magnetic pole sensorless permanent magnet synchronous motor(PMSM) with an incremental encoder, The accurate initial pole position is estimated by using an efficient numerical method of Secant Method, which finds either of two zero torque/force positions and then the correct d-axis. It can be simply applicable to both rotary and linear PMSM because it only requires the tuned current controller and the relative position information. The experimental results show the validity of the proposed method with respect to highly accurate pole position estimation under the moderate moving distance and convergence time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.475-478
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• 2004

In this paper, a magnet-type automatic pipe cutting machine that binds itself to the surface of the pipe using magnetic force and executes unmanned cutting process is proposed. During pipe cutting process when the machine moves around the pipe laid vertical to the gravitational field, the gravity acting on the pipe cutting machine widely varies as the position of the machine varies. That is, with same driving force from the driving motor the cutting machine moves faster when it climbs down the surface of the pipe and moves slower when it climbs up to the top of the pipe. To maintain a constant velocity of the pipe cutting machine and improve the cutting quality, the authors adopted a conventional PID controller with a feedforward effort designed based on the encoder measurement of the driving motor. It is, however, impossible for the encoder at the motor to measure the absolute position and consequently the absolute velocity of the cutting machine in the case where the slip between the surface of the pipe and wheel of the cutting machine is not negligible. As an attempt to obtain a better estimation of the absolution angular position/velocity of the machine the authors proposes the use of the MEMS-type accelerometer which can measure static acceleration as well as dynamic acceleration. The estimated angular velocity of the cutting machine using the MEMS-type accelerometer measurement is experimentally obtained and it indicates the significant slipping of the machine during the cutting process.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.25-31
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• 2011

Precise control of antenna position is very critical in ArcSAR system which uses an arc-rail as a platform for the antenna movement instead of linear rail. In order to minimize the antenna positional error, we improved the motion driving system and applied a newly developed motion control S/W which utilizes the real time antenna position information from magnetic linear scale and encoder. The experimental results showed that the rotational RMS error was reduced to $0.0062^{\circ}$ from $0.0432^{\circ}$. In terms of antenna positional RMS error for the arm length of 3m, it was reduced to 0.324mm from 2.262mm. It is expected that the ArcSAR system can be used to monitor the sub-millimetric displacement of terrain and structural targets.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.979-987
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• 2021

Multiple Sclerosis (MS) can be early diagnosed by detecting lesions in brain magnetic resonance images (MRI). Unsupervised anomaly detection methods based on autoencoder have been recently proposed for automated detection of MS lesions. However, these autoencoder-based methods were developed only for 2D images (e.g. 2D cross-sectional slices) of MRI, so do not utilize the full 3D information of MRI. In this paper, therefore, we propose a novel 3D autoencoder-based framework for detection of the lesion volume of MS in MRI. We first define a 3D convolutional neural network (CNN) for full MRI volumes, and build each encoder and decoder layer of the 3D autoencoder based on 3D CNN. We also add a skip connection between the encoder and decoder layer for effective data reconstruction. In the experimental results, we compare the 3D autoencoder-based method with the 2D autoencoder models using the training datasets of 80 healthy subjects from the Human Connectome Project (HCP) and the testing datasets of 25 MS patients from the Longitudinal multiple sclerosis lesion segmentation challenge, and show that the proposed method achieves superior performance in prediction of MS lesion by up to 15%.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.744-749
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• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.541-546
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• 2005

Tracking control of an automatic pipe cutting robot (APCROMB) is studied. Using magnetic force APCROMB, which is designed and developed in Kyung Hee University, binds itself to the pipe and executes unmanned cutting process. The gravity effect on the movement of APCROMB varies as it rotates around the cylindrical pipe laid in the gravitational field. To maintain a constant velocity and consistent cutting performance against the varying gravitational effect, the authors adopt a multi-rate repetitive learning controller (MRLC), which learns the required effort to cancel the repetitive tracking errors caused by nonlinear effect. In addition to the varying gravity effect other types of nonlinear disturbances including backlash in the driving system and the slip between the wheels of APCROMB and the pipe also cause degradation in the cutting process. In order to identify those nonlinear disturbances the position estimation based on the encoder attached at the motor is not good enough. To identify the absolute angular position of APCROMB the authors propose the angular position estimation based on the signals from a MEMS-type two-axis accelerometer mounted on APCROMB. The tracking performances of APCROMB with a MRLC using the encoder-based position estimation is experimentally measured and results are shown. Also the difference between the encoder-based angular displacement measurement and the accelerometerbased angular displacement measurement is included.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.1
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• pp.9-16
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• 2016

A position control system composed of the PMLSM(Permanent Magnet Linear Synchronous Motor), unlike conventional linear permanent magnet synchronous motor is fixed to the permanent magnet moving coil rails (permanent magnet = stator, coil = mover), the coil is fixed, moving the permanent magnet, we propose a position control system (permanent magnet = mover, coil = stator) structure. Position is measured not using conventional encoder or resolver but by adopting vector control method using 2 hall sensors generating rectangular signal. This method estimate the velocity and position of mover by using the quadruple of two hall sensor signal instead of encoder signal. Vector control of PMLSM using 2 hall sensor generating rectangular wave is proved to control the system stable and efficiently through simulation. Also hardware experiment reveals that the position control performance is measured within the range of $30{\sim}50{\mu}m$ in the accuracy of $10{\sim}20{\mu}m$, which is improved twice to the conventional method. The proposed method exhibits its economical efficiency and practical usefulness. The vector control technique using two hall sensors can be installed in narrow place, accordingly it can be implemented on the system where the conventional encoder or resolver cannot operate.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.67-75
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• 2010

This paper presents localization algorithm for mobile robot in outdoor environment. Outdoor environment includes the uncertainty on the ground. Magnetic sensor or IMU(Inertial Measurement Unit) has been used to estimate robot's heading angle. Two sensor is unavailable because mobile robot is electric car affected by magnetic field. Heading angle estimation algorithm for mobile robot is implemented using gyro sensor module consisting of 1-axis gyro sensors. Localization algorithm applied Extended Kalman filter that utilized GPS and encoder, gyro sensor module. Experiment results show that proposed localization algorithm improve considerably localization performance of mobile robots.