• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.58-66
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• 2023

In this study, cable tension was measured using the vibration method, and a vision-based system was applied as a sensor to measure the displacement response of a cable in a non-contact method. In the vision-based system, the camera is installed in a location that considers the target structure and the field of view of the camera. However, it can be difficult to recognize the control points required to measure the displacement response of a structure as the target structure and other structures such as vehicles may be included in the image at the intended installation location. In this study, a distorted image including a vehicle shows inaccurate results in image analysis due to the installation position of the vision-based system. Accordingly, the image including the vehicle was eliminated by calculating the similarity between the two images. To verify the validity of the method of estimating the cable tension of cable-stayed bridges using the proposed method, the vibration method was applied to cable-stayed bridges in service to measure the tension.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.53-56
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• 2007

It was previously introduced a new displacement measuring technique using terrestrial laser scanning (TLS) that remotely samples the surface of an object using laser pulses and generates the three-dimensional (3D) coordinates of numerous points on the surface. In this paper, for an assessment of the capabilities of the measuring technique about existing structures, the field tests for vertical displacement measurement of an existing long span steel box-girder are experimentally carried out. The performance of the technique is evaluated by comparing the displacements obtained from TLS system and displacements directly measured from linear variable displacement transducer (LVDT).

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.989-994
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• 2011

This study aims to demonstrate the feasibility of a visual servoing-based paired structured light (SL) robot for estimating structural displacement under various external loads. The former paired SL robot, which was proposed in the previous study, was composed of two screens facing with each other, each with one or two lasers and a camera. It was found that the paired SL robot could estimate the translational and rotational displacement each in 3-DOF with high accuracy and low cost. However, the measurable range is fairly limited due to the limited screen size. In this paper, therefore, a visual servoing-based 2-DOF manipulator which controls the pose of lasers is introduced. By controlling the positions of the projected laser points to be on the screen, the proposed robot can estimate the displacement regardless of the screen size. We performed various simulations and experimental tests to verify the performance of the newly proposed robot. The results show that the proposed system overcomes the range limitation of the former system and it can be utilized to accurately estimate the structural displacement.

• Smart Structures and Systems
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• v.24 no.6
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• pp.723-732
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• 2019

Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.935-940
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• 2002

For robot navigation and visual reconstruction, structure from motion (SFM) is an active issue in computer vision community and its properties arc also becoming well understood. In this paper, when using stereo image sequence and direct method as a tool for SFM, we present a new method for overcoming bas-relief ambiguity. We first show that the direct methods, based on optical flow constraint equation, are also intrinsically exposed to such ambiguity although they introduce robust methods. Therefore, regarding the motion and depth estimation by the robust and direct method as approximated ones. we suggest a method that refines both stereo displacement and motion displacement with sub-pixel accuracy, which is the central process f3r improving its ambiguity. Experiments with real image sequences have been executed and we show that the proposed algorithm has improved the estimation accuracy.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.1
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• pp.1-2
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• 2015

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.4
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• pp.27-35
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• 2013

• Smart Structures and Systems
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• v.9 no.3
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• pp.273-286
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• 2012

As civil structures are exposed to various external loads, it is essential to assess the structural condition, especially the structural displacement, in every moment. Therefore, a visually servoed paired structured light system was proposed in the previous study. The proposed system is composed of two screens facing with each other, each with a camera, a screen, and one or two lasers controlled by a 2-DOF manipulator. The 6-DOF displacement can be calculated from the positions of three projected laser beams and the rotation angles of the manipulators. In the estimation process, one of well-known iterative methods such as Newton-Raphson or extended Kalman filter (EKF) was used for each measurement. Although the proposed system with the aforementioned algorithms estimates the displacement with high accuracy, it takes relatively long computation time. Therefore, an incremental displacement estimation (IDE) algorithm which updates the previously estimated displacement based on the difference between the previous and the current observed data is newly proposed. To validate the performance of the proposed algorithm, simulations and experiments are performed. The results show that the proposed algorithm significantly reduces the computation time with the same level of accuracy compared to the EKF with multiple iterations.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.117-124
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• 2023

In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.

• Computers and Concrete
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• v.31 no.5
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• pp.457-468
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• 2023

Buildings, bridges, and dams are examples of civil infrastructure that play an important role in public life. These structures are prone to structural variations over time as a result of external forces that might disrupt the operation of the structures, cause structural integrity issues, and raise safety concerns for the occupants. Therefore, monitoring the state of a structure, also known as structural health monitoring (SHM), is essential. Owing to the emergence of the fourth industrial revolution, next-generation sensors, such as wireless sensors, UAVs, and video cameras, have recently been utilized to improve the quality and efficiency of building forensics. This study presents a method that uses a target-based system to estimate the dynamic displacement and its corresponding dynamic properties of structures using UAV-based video. A laboratory experiment was performed to verify the tracking technique using a shaking table to excite an SDOF specimen and comparing the results between a laser distance sensor, accelerometer, and fixed camera. Then a field test was conducted to validate the proposed framework. One target marker is placed on the specimen, and another marker is attached to the ground, which serves as a stationary reference to account for the undesired UAV movement. The results from the UAV and stationary camera displayed a root mean square (RMS) error of 2.02% for the displacement, and after post-processing the displacement data using an OMA method, the identified natural frequency and damping ratio showed significant accuracy and similarities. The findings illustrate the capabilities and reliabilities of the methodology using UAV to evaluate the dynamic properties of structures.