• Smart Structures and Systems
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• 제24권5호
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• 한국컴퓨터그래픽스학회논문지
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• 제19권4호
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• pp.13-22
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• 2013

모션 캡처 장치는 자연스러운 인체 동작을 생성하는 것을 용이하게 하여 영화, 컴퓨터 게임, 컴퓨터 애니메이션 등 여러 분야에서 폭넓게 사용되고 있다. 그 중 관성 센서를 활용한 모션 캡처 장치는 보다 널리 사용되고 있는 광학 모션 캡처 장비에 비해 소요 공간과 비용 측면에서 이점을 가지고 있으나 비교적 높은 노이즈로 인해 측정 결과의 정밀도가 떨어지는 단점이 있다. 특히 관성 센서에 포함되어 중력 방향을 계측하는 가속도 센서는 센서의 선형 가속 운동으로 인해 중력 방향의 계측 정밀도가 떨어지는 문제를 갖는다. 본 논문에서는 관절체에 부착된 센서의 자세 측정 정확도를 높이기 위해 가속도 센서에서 선형 가속도 성분을 제거하는 기법을 제안한다. 아울러 센서가 부착되어 있는 관절체의 회전축 및 센서의 부착 위치를 보정하는 기법을 소개한다. 이 보정 기법은 관성 센서가 관절체의 임의의 위치와 방향으로 부착되는 것을 가능하게 한다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.384-389
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• 2005

The objective on this project is to develop a cooperative Field Robot (FR), by using a customize Open Control Platform (OCP) as design and development process. An OCP is a CORBA-based solution for networked control system, which facilitates the transitioning of control designs to embedded targets. In order to achieve the cooperation surveillance system, two FRs are distributed by navigation messages (GPS and sensor data) using CORBA event-channel communication, while graphical information from IR night vision camera is distributed using CORBA Asynchronous Method Invocation (AMI). The QoS features of AMI in the network are to provide the additional delivery method for distributing an IR camera Images will be evaluate in this experiment. In this paper also presents an empirical performance evaluation from the variable chunk sizes were compared with the number of clients and message latency, some of the measurement data's are summarized in the following paragraph. In the AMI buffers size measurement, when the chuck sizes were change, the message latency is significantly change according to it frame size. The smaller frame size between 256 bytes to 512 bytes is more efficient fur the message size below 2Mbytes, but it average performance in the large of message size a bigger frame size is more efficient. For the several destination, the same experiment using 512 bytes to 2 Mbytes frame with 2 to 5 destinations are presented. For the message size bigger than 2Mbytes, the AMI are still able to meet requirement far more than 5 clients simultaneously.

• 한국지리정보학회지
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• 제15권4호
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• pp.55-64
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• 2012

본 연구에서는 지적재조사사업을 비롯하여 다양한 지적업무를 효과적으로 추진하기 위해 필요한 지적정보를 서비스하기 위한 모바일 애플리케이션 시스템을 개발하였다. 먼저 스마트폰이나 태블릿 PC 등의 모바일 기반 지적정보시스템을 구현하기 위해 BlackPoint-Xr을 공간 클라이언트 엔진으로 선정하였다. 모바일 지적정보 시스템은 항공사진, 지적도, 행정구역도, DEM 등의 공간정보를 기반으로 GPS를 통한 위치 찾기, 주소와 지번을 통한 필지 검색 그리고 필지에 대한 주소, 지목, 공시지가 등의 토지대장 정보를 확인할 수 있는 기능이 포함되어 있다. 특히 본 연구에서는 건설공사나 토지정비사업 등에 활용하기 위해 필지에 대한 거리, 면적, 경사 그리고 횡단면도 등을 분석할 수 있는 기능도 개발하였다. 본 시스템은 현장에서 다양한 지적정보를 사용자들에게 서비스해 줌으로서 지적업무와 건설공사 등을 효과적으로 지원할 수 있고 디지털 지적정보 분야에도 응용될 수 있을 것으로 판단된다.

• Journal of Biosystems Engineering
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• 제43권2호
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• pp.103-109
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• 2018

Purpose: This study has been conducted to develop a potato yield monitoring system, consisting of a segmentation algorithm to detect potatoes scattered on a soil surface and a counting system to count the number of potatoes and convert the data from two-dimensional images to masses. Methods: First, a segmentation algorithm was developed using top-hat filtering and processing a series of images, and its performance was evaluated in a stationary condition. Second, a counting system was developed to count the number of potatoes in a moving condition and calculate the mass of each using a mass estimation equation, where the volume of a potato was obtained from its two-dimensional image, and the potato density and a correction factor were obtained experimentally. Experiments were conducted to segment potatoes on a soil surface for different potato sizes. The counting system was tested 10 times for 20 randomly selected potatoes in a simulated field condition. Furthermore, the estimated total mass of the potatoes was compared with their actual mass. Results: For a $640{\times}480$ image size, it took 0.04 s for the segmentation algorithm to process one frame. The root mean squared deviation (RMSD) and average percentage error for the measured mass of potatoes using this counting system were 12.65 g and 7.13%, respectively, when the camera was stationary. The system performance while moving was the best in L1 (0.313 m/s), where the RMSD and percentage error were 6.92 g and 7.79%, respectively. For 20 newly prepared potatoes and 10 replication measurements, the counting system exhibited a percentage error in the mass estimation ranging from 10.17-13.24%. Conclusions: At a travel speed of 0.313 m/s, the average percentage error and standard deviation of the mass measurement using the counting system were 12.03% and 1.04%, respectively.

• 센서학회지
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• 제19권2호
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• pp.99-111
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• 2010

This paper proposes an efficient hardware architecture to estimate disparities between 2D images for generating 3D depth images in a stereo vision system. Stereo matching methods are classified into global and local methods. The local matching method uses the cost functions based on pixel windows such as SAD(sum of absolute difference), SSD(sum of squared difference) and NCC(normalized cross correlation). The NCC-based cost function is less susceptible to differences in noise and lighting condition between left and right images than the subtraction-based functions such as SAD and SSD, and for this reason, the NCC is preferred to the other functions. However, software-based implementations are not adequate for the NCC-based real-time stereo matching, due to its numerous complex operations. Therefore, we propose a fast pipelined hardware architecture suitable for real-time operations of the NCC function. By adopting a block-based box-filtering scheme to perform NCC operations in parallel, the proposed architecture improves processing speed compared with the previous researches. In this architecture, it takes almost the same number of cycles to process all the pixels, irrespective of the window size. Also, the simulation results show that its disparity estimation has low error rate.

• 대한조선학회논문집
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• 제51권1호
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• pp.34-41
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• 2014

When a ship sails in shallow water, it is well known that an additional sinkage and trim of the ship(squat) is caused by change of hydrodynamic force between the seabed and the bottom of a ship. In this paper, to examine this phenomenon by model tests, the squat of KCS model ship at a low speed is measured by the vision based ship motion measurement system during HPMM tests. Various combinations of a ship speed, a rudder angle and a drift angle were tested at three depth conditions(H/T = 1.2, 1.5 & 2.0). As a result, increase of the ship's speed and ship's drift angle caused an increase in ship squat, but the ship's rudder angle did not. The rate of increase in ship squat was the most at H/T = 1.2 condition. Lastly these experimental results are compared to the results by three empirical formulas and two CFD methods. The tendency of ship squat measured by experiment is similar to those of empirical formulas.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1993년도 춘계학술대회논문집
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• pp.1-9
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• 1993

A human gait study is required for the biomechanical design of running shoes. A tow-dimensional dynamic model was developed in order to analyze lower extremity kinematics and loadings at the right ankle, knee, and hip joints. The dynamic model consists of three segments, the upper leg, the lower leg, and the foot. Each segment was assumed to be a rigid body with one or two frictionless hinge joints. The lower extremity motion was assumed to be planar in the sagittal plane. A young male subject was involved in the gait test and his anthropometric data were measured for the calculation of segement mass and moment of inertia. The experimental data were obtained from three trials of walking at 1.2m/s. The foot-floor reaction data were measured from a Kistler force plate. The kinematic data were acquired using a three-dimensional motion measurement system (Expert Vision) with six markers, five of which were placed on the right lower extremity segments and the rest one was attached to the force plate. Based on the model and experimental data for the stance phase of the right foot, the calculated vertical forces reached up to 492, 540, and 561 N at the hip, knee, ankle joints, respectively. The flexion-extension moments reached up to 155, 119, and 33 Nm in magnitude at the corresponding joints.

• 한국전기전자재료학회논문지
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• 제37권3호
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• pp.314-321
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• 2024

Low road lighting is a lighting device that complements the shortcomings of existing pillar-type street lights. It is a lighting device that emits light from the side of the road surface and adjusts the luminance of the road surface like a light carpet. In this paper, to achieve full commercialization, we analyzed the luminance of the installed road surface and studied whether lighting could replace existing road lighting. In this study, the LMK (Luminance Measurement Camera) LABSOFT program was used to measure and analyze the surface luminance of road lighting, and the RELUX program was used to evaluate and analyze the simulation performance to determine light-based lighting conditions. A study was conducted to determine whether replacing pillar-type road lighting with low-level road lighting in a real environment would ensure comfortable and safe night vision for drivers at night.

• 한국수자원학회논문집
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• 제49권6호
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• pp.469-480
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• 2016

본 연구는 안드로이드 기반의 스마트폰을 이용한 실시간 표면영상유속계를 개발하는 것이다. 스마트폰이 내장한 카메라, GPS, 방향 센서, CPU를 활용하여, 실시간으로 현장에서 하천의 표면유속을 측정하는 것이다. 먼저, 스마트폰의 GPS를 이용하여 측정 현장의 위치를 파악하고, 경사계(방향 센서)를 활용하여 카메라와 촬영면의 기하적인 관계를 설정한다. 이 때 입력해야 할 유일한 변수는 수면과 카메라의 연직 높이뿐이다. 내장된 카메라로 정해진 시간만큼 동영상을 촬영한다. 촬영된 동영상을 개방 소스의 영상처리 라이브러리인 OpenCV를 이용하여 프레임별로 분할하고, 이를 시공간 영상 분석하여 하천 표면의 2차원 유속장을 추정한다. 시판되는 안드로이드 스마트폰에 적용하여 현장 시험한 결과 약 11초에 1회의 순간유속 측정 (1초간의 평균유속 측정)을 할 수 있어, 현장에서 즉각적으로 하천 수표면의 표면유속을 측정할 수 있었다. 또한 이 순간유속을 수십회 반복한 뒤 평균하여 시간평균유속을 구할 수 있었다. 개발된 시스템을 실험 수로에서 시험한 결과, 측정이 매우 효과적이며 편리하였다. 측정된 결과를 프로펠러 유속계에 의한 측정값과 비교한 결과, 최대 오차 13.9%, 평균적으로 10 % 이내의 오차로 실험 수로의 표면 유속을 측정할 수 있었다.