• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2008년도 춘계학술대회 논문집
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• pp.303-304
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• 2008

• Journal of Welding and Joining
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• 제11권2호
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• pp.27-41
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• 1993

The estimation of nugget sizes was attempted by utilizing the artificial neural networks method. Artificial neural networks is a highly simplified model of the biological nervous system. Artificial neural networks is composed of a large number of elemental processors connected like biological neurons. Although the elemental processors have only simple computation functions, because they are connected massively, they can describe any complex functional relationship between an input-output pair in an autonomous manner. The electrode head movement signal, which is a good indicator of corresponding nugget size was determined by measuring the each test specimen. The sampled electrode movement data and the corresponding nugget sizes were fed into the artificial neural networks as input-output pairs to train the networks. In the training phase for the networks, the artificial neural networks constructs a fuctional relationship between the input-output pairs autonomusly by adjusting the set of weights. In the production(estimation) phase when new inputs are sampled and presented, the artificial neural networks produces appropriate outputs(the estimates of the nugget size) based upon the transfer characteristics learned during the training mode. Experimental verification of the proposed estimation method using artificial neural networks was done by actual destructive testing of welds. The predicted result by the artifficial neural networks were found to be in a good agreement with the actual nugget size. The results are quite promising in that the real-time estimation of the invisible nugget size can be achieved by analyzing the process variable without any conventional destructive testing of welds.

• 대한의용생체공학회:의공학회지
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• 제31권2호
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• pp.162-169
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• 2010

This paper deals with the recognition algorithm of walking will based on torque estimation. Recently, concern about walking assistant aids is increasing according to the increase in population of elder and handicapped person. However, most of walking aids don't have any actuators for its movement. So, general walking aids have weakness for its movement to upward/download direction of slope. To overcome the weakness of the general walking aids, many researches for active type walking aids are being progressed. Unfortunately it is difficult to control aids during its movement, because it is not easy to recognize user's walking will. Many kinds of methods are proposed to recognize of user's walking will. In this paper, we propose walking will recognition algorithm by using torque estimation from wheels. First, we measure wheel velocity and voltage at the walking aids. From these data, external forces are extracted. And then walking will that is included by walking velocity and direction is estimated. Here, all the processes are verified by simulation and experiment in the real world.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.46-48
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• 2004

This paper presents a simple method of rotational and translational motion estimation for digital image stabilization. The scheme first computes the rotation center by taking least squares of selected local velocity vectors, and the rotational angle is found from special subset of motion vectors. And then translational motion can be estimated by the relation among movement of rotation center, rotation angle and translation movement. To show the effectiveness of our approach, the synthetic images are evaluated, resulting in better performance.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.1014-1020
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• 2011

This presents a motion and force estimation system of human fingers by using an Electromyography (EMG) sensor module and a data glove system to be proposed in this paper. Both EMG sensor module and data glove system are developed in such a way to minimize the number of hardware filters in acquiring the signals as well as to reduce their sizes for the wearable. Since the onset of EMG precedes the onset of actual finger movement by dozens to hundreds milliseconds, we show that it is possible to predict the pattern of finger movement before actual movement by using the suggested system. Also, we are to suggest how to estimate the grasping force of hand based on the relationship between RMS taken EMG signal and the applied load. Finally we show the effectiveness of the suggested estimation system through several experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권8호
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• pp.1444-1456
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• 2011

This paper presents a low-complexity algorithm for an H.264/AVC encoder. The proposed motion estimation scheme determines the best coding mode for a given macroblock (MB) by finding motion-blurred MBs; identifying, before motion estimation, an early selection of MBs; and hence saving processing time for these MBs. It has been observed that human vision is more sensitive to the movement of well-structured objects than to the movement of randomly structured objects. This study analyzed permissible perceptual distortions and assigned a larger inter-mode value to the regions that are perceptually less sensitive to human vision. Simulation results illustrate that the algorithm can reduce the computational complexity of motion estimation by up to 47.16% while maintaining high compression efficiency.

• 정보과학회 논문지
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• 제42권12호
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• pp.1544-1550
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• 2015

최근 웨어러블 로봇에 활용이 가능한 실용적인 웨어러블 로봇 인터페이스 개발이 활발하게 이루어지고 있다. 본 논문은 인간의 생체신호 중 근전도를 활용하여, 회귀 기법 기반 연속적인 손목 움직임 의도 추정 방법을 제안한다. 실생활에서 사용자의 상지 자세 변화는 근전도 신호를 변조시켜 성능 저하의 주요한 원인이 되는데, 이를 해결하기 위해 서로 다른 상지 자세에서 학습된 회귀 기법 기반 움직임 추정모델을 통합함으로써 상지 자세 변화에도 강인한 연속적인 손목 움직임 의도 추정 방법을 제안한다. 실험결과에서 서로 다른 상지 자세에서 손목 움직임 의도를 추정하였을 때 제안 방법의 성능이 기존 방법보다 우수함을 확인하였다.

• 한국정보통신학회논문지
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• 제21권9호
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• pp.1697-1702
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• 2017

본 논문은 영상 기반 전방 추돌 경고를 위한 전방 차량 움직임 추정 알고리즘을 제안한다. 사전에 취득된 영상에서 차도 영역이 관심 영역으로 지정되고 거리 참조표가 생성된다. 거리 참조표는 실험 차량 위치인 기준 화소에서 관심 영역 상 차량 위치인 임의 화소까지 수평과 수직 실제 거리를 보여주다. 제안된 알고리즘은 관심영역에서 차량들을 검출하고, 검출된 차량들에게 레이블을 지정하고, 거리 참조표를 이용해 그들의 거리 정보를 저장한다. 그리고 나서 제안된 알고리즘은 프레임간 거리 변화를 이용해 접근 거리, 측방 접근 속도, 전방 접근 속도 같은 차량 움직임들을 추정한다. 도로 주행 동영상들을 이용한 전방 차량 움직임 추정 실험에서 제안된 알고리즘은 차량 움직임들에 대해 각각 평균 98.7%, 95.9%, 94.3%를 유효하게 추정하고 있다.

• 한국강구조학회 논문집
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• 제21권3호
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• pp.203-210
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• 2009

가스배관이 매설된 지역에서 지면고에 변화가 발생하는 공사 수행시 가스배관의 안정성을 확보하기 위한 위치이동을 수행한다. 본 논문에서는 위치이동에 따른 배관의 구조해석을 위한 모델링 방법의 최적화와 함께 위치이동의 단계별 발생 응력을 실시간으로 예측하기 위한 방법을 제안하였다. 모델링 방법으로는 요소의 종류와 크기, 배관 매설부의 경계조건 처리 방법, 세장비에 의한 기하학적 비선형 특성 등의 영향에 관하여 분석하였으며 정확성을 확보하면서 해석 효율을 높일 수 있는 조건을 구하였다. 배관의 응력 예측을 위해서는 위치이동의 수 단계에 발생하는 배관위치 및 최대응력 정보를 이용하여 인공신경망을 학습시켰으며 학습 후 세부 이동단계별 배관의 위치와 최대응력을 예측할 수 있도록 하였다. 개발된 응력예측시스템은 윈도우 환경의 프로그램으로 개발하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.1121-1124
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• 1999

Linear motor is able to produce line movement without rotary-to-line converter at the system required line moving. Thus Linear motor has no gear, screw, belt for line movement. Therefore it has some advantage which decrease friction loss, noise, vibration, maintenance effort and prevent decay of control performance due to backlash. This paper proposes the estimation method of unknown parameters from the BLDC Linear motor and determine the PI controller gain through this estimation. Each control movement that is current, speed, position control, and PWM wave generation is performed on Processor, which is DSP(Digital Signal Processor), having high speed performance. PI theory is adopted to each for controller for control behavior More fast convergence to command position is accomplished by applying the new velocity locus which derived from position error.