• Journal of the Korean Society of Industry Convergence
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• 제17권3호
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• pp.84-92
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• 2014

In this paper, a novel 5-axis hybrid-kinematic machine tool is introduced and the research results on accuracy improvement of the prototype machine tool are presented. The 5-axis hybrid machine tool is made up of a 3-DOF parallel manipulator and a 2-DOF serial one connected in series. The machine tool maintains high ratio of stiffness to mass due to the parallel structure and high orientation capability due to the serial-type wrist. In order to acquire high accuracy, the methodology of measuring the output shafts by additional sensors instead of using encoder outputs at the motor shafts is proposed. In the kinematic view point, the hybrid manipulator reduces to a serial one, if the passive joints in the U-P serial chain at the center of the parallel manipulator are directly measured by additional sensors. Using the method of successive screw displacements, the kinematic error model is derived. Since a ball-bar is less expensive than a full position measurement device and sufficiently accurate for calibration, the kinematic calibration method of using a ball-bar is presented. The effectiveness of the calibration method has been verified through the simulations. Finally, the calibration experiment shows that the position accuracy of the prototype machine tool has been improved from 153 to $86{\mu}m$.

• KIPS Transactions on Software and Data Engineering
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• 제7권2호
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• pp.63-68
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• 2018

Interests in face recognition area have been increasing due to diverse emerging applications. Face recognition algorithm from a two-dimensional source could be challenging in dealing with some circumstances such as face orientation, illuminance degree, face details such as with/without glasses and various expressions, like, smiling or crying. Hopfield Network capabilities have been used specially within the areas of recalling patterns, generalizations, familiarity recognitions and error corrections. Based on those abilities, a specific experimentation is conducted in this paper to apply the Redundant Parallel Hopfield Network on a face recognition problem. This new design has been experimentally confirmed and tested to be robust in any kind of practical situations.

• Special Issue of the Society of Naval Architects of Korea
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• 대한조선학회 2008년도 특별논문집
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• pp.68-75
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• 2008

This paper describes the design and implementation of a low cost inertial navigation system(INS) using an inertial measurement unit(IMU), a digital compass, GPS, and an embedded system. The system has been developed for a transporter that load and unload ship blocks in a shipbuilding yard. When the transporter would move from place to place, they would periodically pass under obstructions that would obscure the GPS signal. This increases the error when estimating the position. Thus the INS has been used to improve position accuracy. INS is also capable of providing continuous estimates of the transporter's position and orientation. Even though IMU is typically very expensive, this INS is made of "low cost" components and the indirect Kalman filtering algorithm.

• Journal of Institute of Control, Robotics and Systems
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• 제20권10호
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• pp.1044-1050
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• 2014

Robots used for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve inspection tasks within pipelines. Localization is an important factor for an inpipe robot to perform successful autonomous operation. However, sensors such as GPS and beacons cannot be used because of the unique characteristics of inpipe conditions. In this paper, an inpipe localization algorithm based on elbow detection is presented. By processing the projected marker images of laser pointers and the attitude and heading data from an IMU, the odometer module of the robot determines whether the robot is within a straight pipe or an elbow and minimizes the integration error in the orientation. In addition, an off-line positioning algorithm has been performed with forward and backward estimation and Procrustes analysis. The experimental environment has consisted of several straight pipes and elbows, and a map of the pipeline has been constructed as the result.

• Proceedings of the KIEE Conference
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2923-2925
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• 1999

The objective of camera calibration is to determine the internal optical characteristics of camera and 3D position and orientation of camera with respect to the real world. Calibration procedure applicable to general purpose cameras and lenses. The general method to revise the accuracy rate of calibration is using mathematical distortion of lens. The effective og calibration show big difference in proportion to distortion of camera lens. In this paper, we propose the method which calibration distortion model by using neural network. The neural network model implicity contains all the distortion model. We can predict the high accuracy of calibration method proposed in this paper. Neural network can set properly the distortion model which has difficulty to estimate exactly in general method. The performance of the proposed neural network approach is compared with the well-known Tsai's two stage method in terms of calibration errors. The results show that the proposed approach gives much more stable and acceptabke calibration error over Tsai's two stage method regardless of camera resolution and camera angle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 1998년도 춘계종합학술대회
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• pp.371-376
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• 1998

This paper describes an approach to a speed estimation method to remove speed sensor of underwater robot's AC drive systems. AC motors have been widely used in the field of underwater robot's manipulator or propulsion system. Most of these AC motors for underwater use have usually filled oil to compensate the high pressure in deep-sea operation, where a resolver is adopted to feed back the speed of rotor But this kind of speed feedback devices gives rise to some defects arising from their mechanical complexity and numerous signal lines; a resolver needs 6 or 7 signal lines for proper operation. This paper presents a speed estimation method to improve these problems of induction motor, which is adopted as a prototype of AC motor. The proposed speed estimation method is based on the RFO(rotor flux orientation) vector control method of voltage-fed AC drives. Using the controller of voltage-fed AC drives, it is unnecessary to measure the voltage for the estimation of rotor speed, which reduces the effects of measurement error Numerical simulation is carried out to investigate the validity of the method and the effects of rotors resistance variation.

• Journal of Information Science Theory and Practice
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• 제3권1호
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• pp.6-23
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• 2015

This study develops an effective method for sentiment analysis of user-generated content on drug review websites, which has not been investigated extensively compared to other general domains, such as product reviews. A clause-level sentiment analysis algorithm is developed since each sentence can contain multiple clauses discussing multiple aspects of a drug. The method adopts a pure linguistic approach of computing the sentiment orientation (positive, negative, or neutral) of a clause from the prior sentiment scores assigned to words, taking into consideration the grammatical relations and semantic annotation (such as disorder terms) of words in the clause. Experiment results with 2,700 clauses show the effectiveness of the proposed approach, and it performed significantly better than the baseline approaches using a machine learning approach. Various challenging issues were identified and discussed through error analysis. The application of the proposed sentiment analysis approach will be useful not only for patients, but also for drug makers and clinicians to obtain valuable summaries of public opinion. Since sentiment analysis is domain specific, domain knowledge in drug reviews is incorporated into the sentiment analysis algorithm to provide more accurate analysis. In particular, MetaMap is used to map various health and medical terms (such as disease and drug names) to semantic types in the Unified Medical Language System (UMLS) Semantic Network.

• Journal of Power Electronics
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• 제15권2호
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• pp.419-430
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• 2015

Flux estimation is a significant foundation of high-performance control for DC-excited synchronous motor. For almost all flux estimators, such as the flux estimator based on phase locked loop (PLL), DC drift causes fluctuations in flux magnitude. Furthermore, significant dynamic error may be introduced at transient conditions. To overcome these problems, this paper proposes an improved flux estimator for the PLL-based algorithm. Filters based on the generalized integrator are used to avoid flux fluctuation problems caused by the DC drift at the back electromotive force. Programmable low-pass filters are employed to improve the dynamic performance of the flux estimator, and the cutoff frequency of the filter is determined by the dynamic factor. The algorithm is verified by a 960V/1.6MW industrial prototype. Simulation and experimental results show that the proposed estimator can estimate the flux more accurately than the PLL-based algorithm in a cycloconverter-fed DC-excited synchronous machine vector control system.

• Journal of Power Electronics
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• 제17권3호
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• pp.695-703
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• 2017

In order to satisfy the urgent requirements for the overheating protection of induction motors, an approach that can be used to identify motor temperature has been proposed based on the rotor slots harmonic (RSH) in this paper. One method to accomplish this is to improve the calculation efficiency of the RSH by predicting the stator winding distribution harmonic order by analyzing the harmonics spectrum. Another approach is to increase the identification accuracy of the RSH by suppressing the influence of voltage flashes or current surges during temperature estimation based on model predictive control (MPC). First, an analytical expression of the stator inductance is extracted from a steady-state positive sequence motor equivalent circuit model developed from the rotor flux field orientation. Then a procedure that applies MPC for reducing the identification error of the rotor temperature caused by voltage sag or swell of the power system is given. Due to this work, the efficiency and accuracy of the RSH have been significantly improved and validated our experiments. This work can serves as a reference for the on-line temperature monitoring and overheating protection of an induction motor.

• Proceedings of the KIEE Conference
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.433-436
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• 2003

The estimation of the position and the orientation for the mobile robot constitutes an important problem in mobile robot navigation. Although the odometry can be used to describe the motions of the mobile robots, there inherently exist the gaps between the real robots and the mathematical model, which may be caused by a number of error sources contaminating the encoder outputs. Hence, applying the standard extended Kalman filter for the nominal model is not supposed to give the satisfactory performance. As a solution to this problem, a new robust extended Kalman filter is proposed based on the Krein space approach. We consider the uncertain discrete time nonlinear model of the mobile robot that contains the uncertainties represented as sum quadratic constraints. The proposed robust filter has the merit of being constructed by the same recursive structure as the standard extended Kalman filter and can, therefore, be easily designed to effectively account for the uncertainties. The simulations will be given to verify the robustness against the parameter variation as veil as the reliable performance of the proposed robust filter.