• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.664-669
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• 2003

This paper proposes a swing-arm type dual-stage actuator, which consists of a PZT actuator for fine motion and a VCM(Voice Coil Motor) for coarse motion, for SFF ODD(Small Form Factor Optical Disk Drive), in order to achieve fast access speed and precise track following control. We focus our attention on the design and control of the PZT actuator, because there have been a lot of previous researches related to the VCM and dual-stage actuators. Due to the dual cantilever structure, the PZT actuator can generate precise translational tracking motion at its tip where optical pickup is attached at, and the effect of hysteric behavior of the PZT element is reduced. The dynamic model of the PZT actuator is derived by using the Hamilton's principle, and verified by comparing with the experimental frequency response. The sliding mode control is designed in order to be robust against modeling uncertainties. Simulations and experimental results confirm the effectiveness of the suggested control scheme.

• 전기의세계
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• 제18권1호
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• pp.15-23
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• 1969

A lot of recent researches have shown that a Pseudo Random Binary Signal is a quite effective test signal to measure the impulse response of a plant. Generally speaking, however, such a response itself is not satisfactory to determine the appropriate control parameters or control inputs. Here, the author intends to estimate the unknown parameters of the First Order Plant with Dead Time by means of correlation method using M-sequence signal. The time constant T and the dead time L of the plant are eatimated with one tracking loop by automatically adjusting delay time .tau. of M-sequence signal according to variations of T and L. In this paper, a three level M-sequence signal is used as a test signal in order to avoid troublesome operations to calculate partial derivatives of a given performance index with respect to the parameters which are usually required in the Model Method. Several experiments with analogue computer using low pass filters as averaging circuits showed good results as expected.

• Nuclear Engineering and Technology
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• 제48권1호
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• pp.129-143
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• 2016

Sometimes, we need or try to figure out somebody's thoughts from his or her behaviors such as eye movement, facial expression, gestures, and motions. In safety-critical and complex systems such as nuclear power plants, the inference of operators' thoughts (understanding or diagnosis of a current situation) might provide a lot of opportunities for useful applications, such as development of an improved operator training program, a new type of operator support system, and human performance measures for human factor validation. In this experimental study, a novel method for inference of an operator's thoughts from his or her eye movement data is proposed and evaluated with a nuclear power plant simulator. In the experiments, about 80% of operators' thoughts can be inferred correctly using the proposed method.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 추계학술대회 논문집
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• pp.69-73
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• 2002

A study on photovoltaic system has a lot of problems. Such as repetition experiment in the same condition, development of MPPT(Maximum Power Point Tracking) algorithm, development of islanding detection algorithm and so forth. The reason Is that solar cell output characteristics are varied by insolarion and surface temperature of solar cell. Therefore, the assistance equipment is required which emulates the solar cell characteristics. In this paper, propose the new modeling of solar cell and verify this modeling using MATLAB simulation. And experiment virtual implement of solar cell system using this modeling.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2015년도 전력전자학술대회 논문집
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• pp.11-12
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• 2015

This study has looked into ways to cut the power supply by predicting electrical fire that may occur in low-voltage cable, which is most frequently used in industrial settings and households. In addition, we have designed a system that cuts off electricity to prevent the fire upon occurrence of events that may cause electrical fire, including short circuit, tracking and contact failure. A lot of previous researches have designed arc suppressors built in analog circuit, which left much to be desired such as difficulty in remote control and inability to identify the location of arc suppressor when it is activated. To address these issues, the study seeks to develop an arc suppressor using micom and to verify its performance through simulations designed to detect arc faults.

• 드라이브 ㆍ 컨트롤
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• 제17권4호
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• pp.72-79
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• 2020

To ensure the safety of Advanced Driver Assistance Systems (ADAS) or autonomous vehicles, it is important to recognize the vehicle position, and specifically, the increased accuracy of the lateral position of the vehicle is required. In recent years, the quality of GPS signals has improved a lot and the price has decreased significantly, but extreme urban environments such as tunnels still pose a critical challenge. In this study, we proposed stable and precise lane recognition and tracking methods to solve these two issues via fusion of AVM images and vehicle sensor data using an extended Kalman filter. In addition, the vehicle's lateral position recognition and the abnormal state of RTK GPS were determined using this approach. The proposed method was validated via actual vehicle experiments in urban areas reporting multipath and signal disconnections.

• 한국군사과학기술학회지
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• 제26권1호
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• pp.72-82
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• 2023

The EOTS(Electro Optical Tracking System) must have stabilization performance to provide high-quality images under disturbance environment. In this paper, we present a controller that can minimize the LOS error and has a simple structure. Hence, to evaluate the performance of this controller, analysis in the frequency domain and LOS error measurement are performed. In order to measure the LOS error without a 'rate table' that requires a lot of facility investment, we propose a design method for disturbance model that considers the operating environment of the EOTS. Finally, the performance of the stabilization algorithm is evaluated by the proposed disturbance model.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.587-591
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• 2013

Measuring the process of construction operations for productivity improvement remains a difficult task for most construction companies due to the manual effort required in most activity measurement methods. There are many ways to measuring the process. But past measurement methods was inefficient. Because they needed a lot of manpower and time. So, this article focus on the vision-based object recognition and tracking methods for automated construction. These methods have the advantage of efficient that human intervention was reduced. Therefore, this article is analyzed the performance of vision-based methods in the construction sites and is expected to contribute to selection of vision-based methods.

• 한국산업정보학회논문지
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• 제12권5호
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• pp.39-46
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• 2007

최근 유비쿼터스 환경에서 개인 인증을 위한 연구가 활발하게 진행되고 있다. 그 중에서 걸음걸이 인식은 원거리에서 사람의 물리적인 특성을 이용하여 개인을 인증하는데 효과적인 방법이다. 본 논문에서는 걸음걸이 인식을 위해 평균 이동 알고리즘(mean shift algorithm)과 geodesic 활성 윤곽선 모델(active contour models) 기반의 사람 외형 추출 및 추적 시스템을 제안한다. 활성 윤곽선 모델은 움직이고, 변화하기 쉬운 물체를 다루는데 효과적이다. 그러나 활성 윤곽선 모델의 성능은 초기 커브에 의존적인 한계를 가지고 있다. 이 문제를 극복하기 위해 전형적인 geodesic 활성 윤곽선 모델에 평균 이동 알고리즘을 결합한다. 기본 개념은 진화시키기 전에 level set 방법을 사용하여 초기 커브를 사람 영역에 위치시키고, 그 영역을 충분히 둘러싸도록 크기를 조정한 후에 커브를 진화시킨다. 이러한 방법은 움직임이 큰 물체를 다루거나 진화 횟수를 줄이기 위해 효과적이다. 제안된 시스템은 사람 영역 검출 모듈과 사람 외형 추적모듈로 구성된다. 사람 영역 검출 모듈에서는 배경영상 제거(background subtraction)와 모폴로지 연산(morphologic operation)으로 사람의 실루엣을 검출한다. 이때, 사람의 외형은 평균 이동 알고리즘과 geodesic 활성 윤곽선 모델에 의해 정확하게 검출된다. 실험 결과에서 제안된 방법이 걸음걸이 인식(gait recognition)을 위해 사람의 외형을 효과적으로 정확하게 추출하고 추적됨을 보여준다.

• 적정기술학회지
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• 제5권2호
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• pp.70-81
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• 2019

의류산업은 대표적인 노동집약적인 산업 중 하나로 의류 제조의 기본 공정인 봉제 작업은 인력에 대한 의존도가 매우 높다. 의류 생산비용은 라인의 효율성에서 큰 영향을 받는데, 생산비용의 절감을 위해서는 생산 속도를 조절하여 라인의 균형 유지하는 것이 중요하다. 그러나, 현재 의류 생산라인에서 활용되고 있는 인력에 의한 생산 실적 집계 방식은 이를 위한 부수적인 인력의 소요 등으로 인한 추가 비용이 소요되어 중소기업들이 직접 적용하기 쉽지 않다. 완제품의 인력에 대한 의존도는 집계 시간의 추가 소요와 인적 오류가 크게 잠재되어 생산비용의 증가와 함께 효율성의 저하를 초래할 수 있다. 본 논문에서는 에너지 소비 데이터를 수집하고 이를 CNN (Convolutional Neural Network) 기법을 적용하여 분석함으로써 재봉 작업을 통하여 생산한 제품의 수량을 추적하고 자동으로 집계할 수 있는 봉제 작업 생산 추적 시스템을 제안한다. 개발된 시스템을 통하여 2종의 재봉 작업을 테스트 한 결과, 최대 98.6 %의 정확도를 보이며 재봉 작업을 감지할 수 있었다. 개발도상국에서 의류봉제산업은 매우 중요한 산업이나, 위에 언급한 문제들을 해결하기 위하여 고가의 첨단기술을 적용하는 등 많은 자본을 투입하는 것은 크게 제한된다. 적정 기술을 적용한 본 기술은 이러한 개발도상국의 의류산업에 큰 도움을 줄 수 있을 것으로 판단된다.