• 제어로봇시스템학회논문지
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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.

• 한국생산제조학회지
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• 제23권5호
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• pp.485-497
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• 2014

This paper presents the robot vision control schemes based on the Newton-Raphson (N-R) and the Extended Kalman Filter (EKF) methods for the tracking of moving targets. The vision system model used in this study involves the six camera parameters. The difference is that refers to the uncertainty of the camera's orientation and focal length, and refers to the unknown relative position between the camera and the robot. Both N-R and EKF methods are employed towards the estimation of the six camera parameters. Based on the these six parameters estimated using three cameras, the robot's joint angles are computed with respect to the moving targets, using both N-R and EKF methods. The two robot vision control schemes are tested by tracking the moving target experimentally. Given the experimental results, the two robot control schemes are compared in order to evaluate their strengths and weaknesses.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.3304-3306
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• 1999

In this study, we used the sputtering method with single target to obtain the thick and uniform PZT($PbZrTiO_3$) films for micromached IR sensor application. Then, we investigated the etching characteristics and conditions which is necessary process to fabricate the IR sensor. We tested the C-axis orientation and P-E loop of the deposited PZT films with the XRD and RT66A, respectively. Also we investigated the surface of the films by the AFM and SEM analysis.

• International Journal of Automotive Technology
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• 제6권2호
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• pp.171-181
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• 2005

The purpose of this paper is two-fold: 1) A novel algorithm in order to extract lane-related information from road images is presented; 2) Design specifications of an image processing onboard unit capable of extracting lane­related information in real-time is also presented. Obtaining precise information from road images requires many features due to the effects of noise that eventually leads to long processing time. By exploiting a FPGA and DSP, we solve the problem of real-time processing. Due to the fact that image processing of road images relies largely on edge features, the FPGA is adopted in the hardware design. The schematic configuration of the FPGA is optimized in order to perform 3 $\times$ 3 Sobel edge extraction. The DSP carries out high-level image processing of recognition, decision, estimation, etc. The proposed algorithm uses edge features to define an Edge Distribution Function (EDF), which is a histogram of edge magnitude with respect to the edge orientation angle. The EDF enables the edge-related information and lane-related to be connected. The performance of the proposed system is verified through the extraction of lane-related information. The experimental results show the robustness of the proposed algorithm and a processing speed of more than 25 frames per second, which is considered quite successful.

• 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.

• Advances in aircraft and spacecraft science
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• 제3권3호
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• pp.331-349
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• 2016

Stiff and light fibre reinforced composites as used in air- and space-craft applications tend to high sound emission. Therefore, the damping properties are essential for the entire structural and acoustic engineering. Viscous damping is an established and reasonably linear model of the dissipation behaviour. Commonly, it is assumed to be isotropic and constant over all modes. For anisotropic materials it depends on the fibre orientation as well as the elastic and thermal material properties. To portray the orthogonal anisotropic behaviour, a model for unidirectional fibre reinforced plastics (frp) has been developed based on the classical laminate theory by ADAMS and BACON starting in 1973. Their approach includes three damping coefficients - for longitudinal damping in fibre direction, damping transversal to the fibres and shear based dissipation. The damping of a laminate is then accumulated layer wise including the anisotropic stiffness. So far, the model has been applied mainly to thermoset matrix materials. In this study, an experimental parameter estimation for different thermoplastic frp with angle ply and cross ply layups was carried out by measuring free vibrations of cantilever beams. The results show potential and limits of the ADAMS/BACON damping criterion. In addition, a possibility of modelling the anisotropic damping is shown. The implementation in standard FEA software is used to study the influence of boundary conditions on the damping properties and numerically estimate the radiated sound power of thin-walled frp parts.

• Geomechanics and Engineering
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• 제39권1호
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• pp.27-41
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• 2024

Accurately estimating the performance of tunnel boring machines (TBMs) is crucial for mitigating the substantial financial risks and complexities associated with tunnel construction. Machine learning (ML) techniques have emerged as powerful tools for predicting non-linear time series data. In this research, six advanced meta-heuristic optimization algorithms based on long short-term memory (LSTM) networks were developed to predict TBM penetration rate (TBM-PR). The study utilized 1125 datasets, partitioned into 20% for testing, 70% for training, and 10% for validation, incorporating six key input parameters influencing TBM-PR. The performances of these LSTM-based models were rigorously compared using a suite of statistical evaluation metrics. The results underscored the profound impact of optimization algorithms on prediction accuracy. Among the models tested, the LSTM optimized by the particle swarm optimization (PSO) algorithm emerged as the most robust predictor of TBM-PR. Sensitivity analysis further revealed that the orientation of discontinuities, specifically the alpha angle (α), exerted the greatest influence on the model's predictions. This research is significant in that it addresses critical concerns of TBM manufacturers and operators, offering a reliable predictive tool adaptable to varying geological conditions.

• 비파괴검사학회지
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• 제23권1호
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• pp.21-29
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• 2003

실시간 로봇 위치 제어를 위해 비젼시스템을 사용할 때 이 모델에 포함된 매개변수를 추정하는데 있어 계산시간을 줄이는 것은 매우 중요하다. 불행히도 흔히 사용되고 있는 일괄 처리 기법은 반복적으로 계산이 수행되기 때문에 많은 계산 시간을 필요로 하여 실시간 로봇 위치 제어를 어렵게 한다. 반면에 본 연구에서 사용하고자 하는 화장 칼만 필터링은 사용하기 편리하고, 또한 순환적 방법으로 계산되기 때문에 비젼시스템의 매개변수를 계산하는데 있어 시간을 줄이는 커다란 장점을 가지고 있다. 따라서 본 연구에서는 실시간 로봇 위치 제어를 위해 사용하는 비젼 제어 기법에 확장 칼만 필터링을 적용되었다 여기서 사용된 비젼시스템 모델은 카메라 내부 매개변수(방향, 초점거리 등) 및 외부 매개변수(카메라와 로봇 사이의 상대적 위치)를 설명하기 위해 6개 매개변수를 포함하고 있다. 이러한 매개변수를 추정하기 위해 확장 칼만 필터링 기법이 적용되었다. 또한 이렇게 추정된 6개 매개변수를 사용하여 로봇을 구동시키기 위해 필요한 로봇 회전각 추정에도 화장 칼만 필터링 기법이 적용되었다. 최종적으로 확장 칼만 필터링을 사용하여 개발된 비젼 제어 기법의 타당성을 로봇 위치 제어 실험을 수행하여 확인하였다.

• 한국농림기상학회지
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• 제2권1호
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• pp.16-23
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• 2000

자료가 불충분한 북한지방의 강수기후정보를 얻기 위해 상대적으로 자료가 풍부한 남한의 지형강수 관계를 도출하여 이를 북한지방에 적용하는 방법을 모색하였다. 남한 전역을 대략적인 경사방향에 따라 8개지대로 구분하고 10년간(1986년-1995년) 강수자료를 수집 할 수 있는 277개 관측소를 지대에 따라 8개 그룹으로 나누었다. 관측소가 위치한 지점의 지형특성을 정량화 하여 월별 강수량의 공간변이를 가장 잘 설명하는 지형변수로 구성된 회귀모형을 각 그룹별로 작성하였다. 이 때 회귀식의 y축 절편값 대신 24개 기상청 표준관측소의 월별 강수량값을 사용하였다. 1 km 해상도의 수치고도모형을 토대로 북한 전역을 역시 경사방향에 따라 8개지대로 구분하고, 27개 북한 표준관측소 월별 강수량자료로부터 등우량선도를 작성하였다. 이를 근거로 모든 격자점의 기준강수량을 파악하였다. 각 지대별로 남한자료로부터 작성된 회귀모형을 적용하여 월별 및 연간 강수량을 계산하고 이들을 통합하여 북한전역의 강수량 분포를 1 km$\times$1km 해상도로 표출하였다. 이 계산에 따르면 북한지방의 연간 총 강수량은 지역평균이 938mm이며 표준편차는 246mm 인 것으로 추정된다.