• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.321-332
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• 1999

It is important to detect objects movement for obstacle recognition and path searching of UCT(unmanned container transporters) with vision sensor. This paper shows the method to draw out objects and to trace the trajectory of the moving object using a CCD camera and it describes the method to recognize the shape of objects by neural network. We can transform pixel points to objects position of the real space using the proposed viewport. This proposed technique is used by the single vision system based on floor map.

• Smart Structures and Systems
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• v.19 no.6
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• pp.679-694
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• 2017

The complexity, enlargement and irregularity of structures and multi-directional dynamic loads acting on the structures can lead to unexpected structural behavior, such as torsion. Continuous torsion of the structure causes unexpected changes in the structure's stress distribution, reduces the performance of the structural members, and shortens the structure's lifespan. Therefore, a method of monitoring the torsional behavior is required to ensure structural safety. Structural torsion typically occurs accompanied by displacement, but no model has yet been developed to measure this type of structural response. This research proposes a model for measuring dynamic torsional response of structure accompanied by displacement and for identifying the torsional modal parameter using vision-based displacement measurement equipment, a motion capture system (MCS). In the present model, dynamic torsional responses including pure rotation and translation displacements are measured and used to calculate the torsional angle and displacements. To apply the proposed model, vibration tests for a shear-type structure were performed. The torsional responses were obtained from measured dynamic displacements. The torsional angle and displacements obtained by the proposed model using MCS were compared with the torsional response measured using laser displacement sensors (LDSs), which have been widely used for displacement measurement. In addition, torsional modal parameters were obtained using the dynamic torsional angle and displacements obtained from the tests.

• Smart Structures and Systems
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• v.24 no.5
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• pp.641-648
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• 2019

The authors investigate the feasibility of applying a vision-based displacement-measurement technique in the characterization of a SMA damper recently introduced in the literature. The experimental campaign tests a steel frame on a uni-axial shaking table driven by sinusoidal signals in the frequency range from 1Hz to 5Hz. Three different cameras are used to collect the images, namely an industrial camera and two commercial smartphones. The achieved results are compared. The camera showing the better performance is then used to test the same frame after its base isolation. U-shaped, shape-memory-alloy (SMA) elements are installed as dampers at the isolation level. The accelerations of the shaking table and those of the frame basement are measured by accelerometers. A system of markers is glued on these system components, as well as along the U-shaped elements serving as dampers. The different phases of the test are discussed, in the attempt to obtain as much possible information on the behavior of the SMA elements. Several tests were carried out until the thinner U-shaped element went to failure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.709-717
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• 2016

In this study, the convenience and efficiency of vision-based displacement measurement (VBDM) to estimate the cable tension of cable-stayed bridges and the requirements for its effective application were examined. To demonstrate its convenience and efficiency, it was confirmed that VBDM can be accomplished with a minimum amount of equipment using a commercial camcorder. In this case, it was found that the accuracy of estimation of the natural frequencies is sufficient, even though magnitude errors can occur when conducting high-speed recording at the low resolution afforded by the minimal equipment employed. It was also confirmed that the most important factor in detecting the precise natural frequencies is the use of the appropriate frequency range in the tension estimation using vibration. Based on these results, a study was carried out on the accuracy variation of the estimated tension according to the frame rate of a commercial camcorder. For this purpose, an experiment was performed to estimate the cable tension in a cable-stayed bridge model. Through this experiment, the detectable tensions of cables with various natural frequencies as a function of the frame rate were summarized. As a result, it was shown that the frame rate should be determined based on the natural frequency which is estimated to be located within the appropriate frequency range (approximately 10~75% of theoretical range) considering the aliasing and low-frequency distortion due to excitations.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1194-1201
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• 2013

This paper introduces a vision-based automatic system (VAMS) for non-contact measurement of morphometric characteristics of flatfish, such as total length (TL), body width (BW), height (H), and weight (W). The H and W are simply measured by a laser displacement and a load cell, respectively. The TL and BW are measured by a proposed morphological image processing algorithm. The proposed algorithm cans measurement, when the tail of flatfish is deformed, and when it is randomly oriented. In the experiment, the average and maximum measurement errors were recorded, and standard deviations and coefficients of variation (CVs) for the measurements were calculated. From those results, when flatfish the TL measurements had an average of 266.844 mm, a standard deviation of 0.351 mm, a CV of 0.131%, and a maximum error of 0.87 mm with straightened flatfish ($TL_A$ : 267 mm, $BW_A$ : 141 mm), and when flatfish of different sizes were measured, the errors in the TL and BW measurements were both about 0.2 %. Using a single conveyor, the VAMS can process up to 900 fishes per hour. Moreover, it can measure morphometric characteristics of flatfish with a TL of up to 500 mm.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.37-45
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• 2022

It is very important to measure the displacement of a structure to evaluate the safety of the structure. This study shows a methodology to measure the displacement to determine the stability of a structure when it is damaged by loads. The methodology used Moiré's phenomenon and was verified through experiments. The experiments utilized pipes to simulate the pipe supports in the construction site and measured the vertical displacement of the Moiré interference patterns according to the horizontal displacement of the pipes. Experiments confirmed that the linear relationship between horizontal displacement of pipes and vertical displacement of Moiré patterns and derive a relational expression. In conclusion, the methodology presented in this work allows us to simultaneously measure a number of vertical members' displacements regardless of distance and determine the safety of the structure.

• Smart Structures and Systems
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• v.31 no.4
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• pp.421-436
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• 2023

This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.

• Smart Structures and Systems
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• v.30 no.3
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• pp.255-261
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• 2022

When no extensometer is available in a generic tensile-compression test carried out by a universal testing machine (for instance the model BIONIX from Material Testing Systems (MTS)), the test results only provide the relative displacement between the machine grips. The test does not provide any information on the local behaviour of the material. This contribution presents the potential of an application of Digital Image Correlation (DIC) toward the reconstruction of the behaviour along the specimen. In particular, the authors test a Ni-Ti shape memory alloys (SMA) specimen with emphasis on the coupling of the two measurement techniques.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1051-1056
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• 2014

In this paper, we introduce an intelligent robotic arc welding system which exploits sensors like as LVS (Laser Vision Sensor), Hall effect sensor, voltmeter and so on. The use of industrial robot is saturated because of its own limitation, and one of the major limitations is that industrial robot cannot recognize the environment. Lately, sensor-based environmental awareness research of the industrial robot is performed actively to overcome such limitation, and it can expand application field and improve productivity. We classify the sensor-based intelligent arc welding robot system by the goal and the sensing data. The goals can be categorized into detection of a welding start point, tracking of a welding line and correction of a torch deformation. The Sensing data can be categorized into welding data (i.e. current, voltage and short circuit detection) and displacement data (i.e. distance, position). This paper covers not only the explanation of the each category but also its advantage and limitation.