• 한국건설순환자원학회논문집
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• 제11권4호
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• pp.355-363
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• 2023

노후 교량의 안전성을 평가하는 방법에 있어서 동특성과 처짐은 구조계의 강성과 직접 연관이 있으며, 처짐의 경우에는 교량 사용자가 직접 감지할 수 있는 물리량으로 가장 중요한 인자이다. 하지만 교량의 처짐을 측정하기 위해서는 교량의 하부에 처짐계를 설치하고 교통 차단 및 재하시험을 실시해야 하는 번거로움이 있어 교량의 환경에 따라서 비용이 증가하거나 측정이 불가능한 문제들이 발생하고 있다. 본 연구에서는 처짐계의 설치 없이 가속도계만을 이용하고 재하시험 없이 상시 진동을 이용하여 교량의 처짐을 측정하는 방법을 제안하였다. 상시 진동을 이용한 교량 동특성 및 처짐 분석을 위해 단순한 연산으로 빠른 분석이 가능하다고 알려진 TDD 기법을 이용하여 교량의 모드형상과 고유진동수를 추출하였으며, 유연도 분석을 통하여 교량의 단위하중 처짐을 분석하여 정적 처짐까지 산정하였다. 본 제안 기술의 검증을 위해 공용중 교량인 C대교(사장교)에 적용하여 모드형상, 고유진동수, 정적 처짐 분석을 수행하였으며 재하시험 실측값과 구조해석 자료와 비교하였다. 그 결과 모드형상 및 고유진동수는 0.42~1.13 %, 중앙경간에서의 최대 처짐은 3.58 %의 오차율을 확인하였다. 따라서 제안기술은 처짐계의 설치가 어려워 실측이 불가능한 교량의 처짐을 추정하여 설계값 및 해석값 대비 처짐 발생량 비교로 교량의 안전성을 간접적으로 파악할 수 있는 근거 자료로 활용 가능할 것으로 사료된다.

• 대한건축학회연합논문집
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• 제20권6호
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• pp.47-54
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• 2018

The purpose of this study is to verify the long - range measurement performance for practical field application of VDMS. The reliability of the VDMS was verified by comparison with the existing monitoring sensor, GPS, Accelerometer and LDS. It showed the ability to accurately measure the dynamic displacement by tracking a motion of free vibration of target. And using the PSD function of measured data, the results in the frequency domain were also analyzed. We judged that VDMS is able to identify the higher system mode and has sufficient reliability. Based on the reliability verification, we conducted tests for long-distance applicability for actual application of VDMS. The distance from the stationary target model structure was increased by 50m interval, and the maximum distance was set to 400m. From the distance of 150m, the image obtained by the commercial camcorder has an error in the analysis, so the measured displacement comparison was performed between the LDS and the refractor telescope measurement results. In the measurement results of the displacement area of VDMS, the data validity was deteriorated due to the data shift by the external force and the quality degradation of the enlarged image. However, even under the condition that the effectiveness of the displacement measurement data of VDMS is low, the first mode characteristic included in the free vibration of the object is clearly measured. If the influence from the external environment is controlled and stable data is collected, It is judged that reliability of long-distance VDMS can be secured.

• 한국CDE학회논문집
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• 제20권1호
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• pp.55-64
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• 2015

The earthquake is a natural disaster causing loss of life or property damage and happens more often in Korea recently. Moreover, considering the increase of massive buildings, it is required to predict and visualize the information of the vibration in a building. In this paper, we developed a prototype framework to visualize the displacement information in the AR environments. In order to avoid the irregular halts of the scene and the unnatural distortion of the object, this framework uses the synchronization method at the scene update time and the interpolation of the sensor data for the displacement of vertices. In addition, we studied displacement estimation methods with the acceleration data to extend this framework to the system with accelerators.

• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.43-49
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• 2018

In this paper, we propose a displacement measurement method based on deep learning using image data obtained from tensile tests of a material specimen. We focus on the fact that the sequential images during the tension are generated and the displacement of the specimen is represented in the image data. So, we designed sample generation model which makes sequential images of specimen. The behavior of generated images are similar to the real specimen images under tensile force. Using generated images, we trained and validated our model. In the deep neural network, sequential images are assigned to a multi-channel input to train the network. The multi-channel images are composed of sequential images obtained along the time domain. As a result, the neural network learns the temporal information as the images express the correlation with each other along the time domain. In order to verify the proposed method, we conducted experiments by comparing the deformation measuring performance of the neural network changing the displacement range of images.

• Smart Structures and Systems
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• 제30권5호
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• pp.521-535
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• 2022

Efficient management of deteriorating civil infrastructure is one of the most important research topics in many developed countries. In particular, the remote displacement measurement of bridges using linear variable differential transformers, global positioning systems, laser Doppler vibrometers, and computer vision technologies has been attempted extensively. This paper proposes a remote displacement measurement system using closed-circuit televisions (CCTVs) and a computer-vision-based method for in-situ bridge bearings having relatively large displacement due to temperature change in long term. The hardware of the system is composed of a reference target for displacement measurement, a CCTV to capture target images, a gateway to transmit images via a mobile network, and a central server to store and process transmitted images. The usage of CCTV capable of night vision capture and wireless data communication enable long-term 24-hour monitoring on wide range of bridge area. The computer vision algorithm to estimate displacement from the images involves image preprocessing for enhancing the circular features of the target, circular Hough transformation for detecting circles on the target in the whole field-of-view (FOV), and homography transformation for converting the movement of the target in the images into an actual expansion displacement. The simple target design and robust circle detection algorithm help to measure displacement using target images where the targets are far apart from each other. The proposed system is installed at the Tancheon Overpass located in Seoul, and field experiments are performed to evaluate the accuracy of circle detection and displacement measurements. The circle detection accuracy is evaluated using 28,542 images captured from 71 CCTVs installed at the testbed, and only 48 images (0.168%) fail to detect the circles on the target because of subpar imaging conditions. The accuracy of displacement measurement is evaluated using images captured for 17 days from three CCTVs; the average and root-mean-square errors are 0.10 and 0.131 mm, respectively, compared with a similar displacement measurement. The long-term operation of the system, as evaluated using 8-month data, shows high accuracy and stability of the proposed system.

• 제어로봇시스템학회논문지
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• 제18권6호
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• pp.579-583
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• 2012

The purpose of this paper is to suggest IDE (Incremental Displacement Estimation) algorithm for the previously proposed visually servoed paired structured light system. The system is composed of two sides facing with each other, each with one or two lasers with a 2-DOF manipulator, a camera, and a screen. The 6-DOF displacement between two sides can be estimated by calculating the positions of the projected laser beams and rotation angles of the manipulators. In the previous study, Newton-Raphson or EKF (Extended Kalman Filter) has been used as an estimation algorithm. Although the various experimental tests have validated the performance of the system and estimation algorithms, the computation time is relatively long since aforementioned algorithms are iterative methods. Therefore, in this paper, a non-iterative incremental displacement estimation algorithm which updates the previously estimated displacement with a difference of the previous and the current observed data is introduced. To verify the performance of the algorithm, experimental tests have been performed. The results show that the proposed non-iterative algorithm estimates the displacement with the same level of accuracy compared to the EKF with multiple iterations with significantly less computation time.

• Wind and Structures
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• 제36권6호
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• pp.379-392
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• 2023

Structural health monitoring is used to ensure the well-being of civil structures by detecting damage and estimating deterioration. Wind flow applies external loads to high-rise buildings, with the horizontal force component of the wind causing structural displacements in high-rise buildings. This study proposes a deep learning-based predictive model for measuring lateral displacement response in high-rise buildings. The proposed long short-term memory model functions as a sequence generator to generate displacements on building floors depending on the displacement statistics collected on the top floor. The model was trained with wind-induced displacement data for the top floor of a high-rise building as input. The outcomes demonstrate that the model can forecast wind-induced displacement on the remaining floors of a building. Further, displacement was predicted for each floor of the high-rise buildings at wind flow angles of 0° and 45°. The proposed model accurately predicted a high-rise building model's story drift and lateral displacement. The outcomes of this proposed work are anticipated to serve as a guide for assessing the overall lateral displacement of high-rise buildings.

• Smart Structures and Systems
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• 제20권4호
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• pp.397-413
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• 2017

Precast concrete (PC) members are currently being employed for general construction or partial replacement to reduce construction period. As assembly work in PC construction requires connecting PC members accurately, measuring the 6-DOF (degree of freedom) relative displacement is essential. Multiple planar markers and camera-based displacement measurement systems can monitor the 6-DOF relative displacement of PC members. Conventional methods, such as direct linear transformation (DLT) for homography estimation, which are applied to calculate the 6-DOF relative displacement between the camera and marker, have several major problems. One of the problems is that when the marker is partially hidden, the DLT method cannot be applied to calculate the 6-DOF relative displacement. In addition, when the images of markers are blurred, error increases with the DLT method which is employed for its estimation. To solve these problems, a hybrid method, which combines the advantages of the DLT and MCL (Monte Carlo localization) methods, is proposed. The method evaluates the 6-DOF relative displacement more accurately compared to when either the DLT or MCL is used alone. Each subsystem captures an image of a marker and extracts its subpixel coordinates, and then the data are transferred to a main system via a wireless communication network. In the main system, the data from each subsystem are used for 3D visualization. Thereafter, the real-time movements of the PC members are displayed on a tablet PC. To prove the feasibility, the hybrid method is compared with the DLT method and MCL in real experiments.

• 한국지반신소재학회논문집
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• 제14권4호
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• pp.23-33
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• 2015

소단은 굴착 후 지지구조물이 설치되기 전 벽체의 강성과 더불어 가설벽체의 안정성을 좌우하는 역할을 한다. 특히 굴착지반이 느슨하거나 연약한 경우 소단의 역할은 매우 중요하다. 본 연구에서는 소단을 이용한 도심지 버팀굴착현장의 계측결과와 수치해석을 사용하여 가설벽체의 최대수평변위에 미치는 소단의 규모(폭과 경사) 및 굴착깊이, 지반물성의 영향을 분석하였다. 계측결과 소단 폭이 짧아질수록 벽체의 수평변위는 증가하는 경향을 보였다. 수치해석 결과 소단의 경사가 급해질수록, 소단폭이 짧아질수록 최대수평변위량은 크게 나타나 소단이 벽체의 변위를 억제하는데 효과가 있음을 알 수 있었다. 또한 굴착심도가 깊어질수록 소단폭과 경사의 영향을 크게 받는 것으로 나타났다. 동일한 소단 조건에서 지반물성이 높을수록 벽체의 최대수평변위를 억제하는 것으로 나타났다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1417-1422
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• 2005

Among the sensors mainly used for displacement measurement, there are a linear CCD(Charge Coupled Device) and a PSD(Position Sensitive Detector) as a non-contact type. Their structures are different very much, which means that the signal processing of both sensors should be applied in the different ways. Most of the displacement measurement systems to get the 3-D shape profile of an object using a linear CCD are a computer-based system. It means that all of algorithms and mathematical operations are performed through a computer program to measure the displacement. However, in this paper, the developed system has microprocessor and other digital components that make the system measure the displacement of an object without a computer. The thing different from the previous system is that AVR microprocessor and FPGA(Field Programmable Gate Array) technology, and a comparator is used to play the role of an A/D(Analog to Digital) converter. Furthermore, an ATC(Automatic Threshold Control) algorithm is applied to find the highest pixel data that has the real displacement information. According to the size of the light circle incident on the surface of the CCD, the threshold value to remove the noise and useless data is changed by the operation of AVR microprocessor. The total system consists of FPGA, AVR microprocessor, and the comparator. The developed system has the improvement and shows the better performance than the system not using the ATC algorithm for displacement measurement.