• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.22-30
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• 2011

In the construction operation, foundation work should be done in advance for the building structure to be installed. This foundation work include a number of activities such as excavation, ground water prevention, piling, wale installation, etc. Caution should be taken in the operation because the dynamics of earth movement can cause a significant failure in the temporary structure. The temporary structure, therefore, should be constantly monitored to understand its behavior. This paper introduces the USN-based monitoring system to automatically identify the behavior of the temporary structure in addition to visual inspection. The autonomous capability of the monitoring system can increase the safety in the construction operation by providing the detailed structural changes of temporary structures.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.10
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• pp.1017-1026
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• 2009

The solar cell system operates by facing the sun-light. Minor cracks, static discharge, and thermal shock that can happen during production/testing phase can lead to degradation in performance during operation, since solar cells are exposed to extreme thermal/mechanical environment in space. In order to detect small cracks and internal damages in the solar cells due to thermal shocks, which are the core units of a solar cell system, expensive equipment, complicated test process, and much time are required. Therefore, a qualitative method for easily and quickly testing the 'health' of solar cell functionality is required. This dissertation describes a theoretical and technical grounds for quickly and easily evaluating the health of solar cells using electroluminescence effect of Gallium-Arsenide solar cells that are most widely used by spacecrafts in recent years. Also described in the dissertation is the technical issues and constraining factors for applying the proposed method to actual space-rated solar cell systems.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.107-115
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• 2021

Purpose: This study aimed to demonstrate the presence of dental caries through a photoacoustic imaging system with visible and near-infrared wavelengths, highlighting the differences between the 2 spectral regions. The depth at which carious tissue could be detected was also verified. Materials and Methods: Fifteen permanent molars were selected and classified as being sound or having incipient or advanced caries by visual inspection, radiography, and optical coherence tomography analysis prior to photoacoustic scanning. A photoacoustic imaging system operating with a nanosecond pulsed laser as the light excitation source at either 532 nm or 1064 nm and an acoustic transducer at 5 MHz was developed, characterized, and used. En-face and lateral(depth) photoacoustic signals were detected. Results: The results confirmed the potential of the photoacoustic method to detect caries. At both wavelengths, photoacoustic imaging effectively detected incipient and advanced caries. The reconstructed photoacoustic images confirmed that a higher intensity of the photoacoustic signal could be observed in regions with lesions, while sound surfaces showed much less photoacoustic signal. Photoacoustic signals at depths up to 4 mm at both 532 nm and 1064 nm were measured. Conclusion: The results presented here are promising and corroborate that photoacoustic imaging can be applied as a diagnostic tool in caries research. New studies should focus on developing a clinical model of photoacoustic imaging applications in dentistry, including soft tissues. The use of inexpensive light-emitting diodes together with a miniaturized detector will make photoacoustic imaging systems more flexible, user-friendly, and technologically viable.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.157-166
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• 2022

In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.20-29
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• 2018

Owing to the changing climate and recent flood events, flood damage caused by river levee collapse and overflow is on the rise in Korea, making it necessary to enhance river levee maintenance technologies to deal with various flood damage scenarios. This paper proposes the evaluation system of a river-levee safety map to improve maintenance efficiency and disaster responsiveness. A river-levee safety map, indicating sliding, piping, visual inspection, scouring, and safety index of a levee fill material on a GIS map will enable the dangerous zone to be identified visually and the development of proactive measures to deal with it. This will maximize the river-levee maintenance efficiency, which is a break from traditional practice in that restoration measures are taken only after the damage has occurred. This study includes scouring and levee fill material in addition to previously-proposed sliding, piping and visual inspections. The research activities conducted in the study include 1) categorization of scouring and levee fill material based on document and data examination, 2) evaluation of sliding and piping at 5 locations on the left levee in the Nam river according to the duration time of the flood water level, and 3) evaluation of the characteristics of scouring and levee fill material at 9 locations on the left/right levee in the Nam River. The river levee safety map proposed in this study would be more useful and practical but further study on the manual for river management organization, repair and reinforcement methods, and budget is required.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1339-1347
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• 2015

This study discusses a remote control torch system equipped with a GMAW double wire reel. The welding machine is 30m away from the wire feeder at the industrial site and the feeder is three to five meters away from the torch. Accordingly, the welders cannot control the current and voltage that meets the welding condition during work when they are working at a place that prevents them from seeing the control panel, such as inside a vehicle or tank or at a far work site. They also have no choice but to stop working to change the wire reel when it is burned out completely. Such work suspension resulting from frequent moves to adjust the current and voltage as well as to replace the wire and subsequent cooling causes welding defects. This study produced a remote control torch equipped with a double wire reel by simplifying and streamlining the existing GMAW functions to reduce the troubling issue. The remote control torch equipped with a double wire reel and the existing $CO_2$ /MAG welding torch were applied as a V-groove butt in the vertical position using 6mm rolled steel for a SM50A welding structure. After welding, the condition of welded surface beads underwent a visual inspection and radiographic inspection to analyze the welding quality inside the welded part. This study also evaluated the reduction of welding defects, cost saving, the replacing performance against the existing commercial welders, and the effects on possible compatibility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.887-895
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• 2013

Metastatic bone cancer, the cancer which occurred in the various organs and progressively spread to bone, is one of the complications in cancer patients. This cancer is divided into the osteoblast and osteolytic metastasis. Although Computer Tomography(CT) could be an useful tool in diagnosis of bone metastasis, lesions are often missed by the visual inspection and it makes clinicians difficult to detect metastasis earlier. Therefore, in this study, we construct a three-dimensional(3D) volume rendering data from tomography images of the chest CT, and apply a 3D based image processing algorithm to them for detection bone metastasis lesions. Then we perform a three-dimensional visualization of the detected lesions.From our test using 10 clinical cases, we confirmed 94.1% of average sensitivity for osteoblast, and 90.0% of average sensitivity, respectively. Consequently, our findings showed a promising possibility and potential usefulness in diagnosis of metastastic bone cancer.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.159-164
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• 2013

It is well known that a single moving camera video is capable of extracting the 3-dimensional position of an object. With this in mind, current research performed image-based monitoring to establish a floating structure model using a camcorder system. Following this, the present study extracted frame images from digital camcorder video clips and matched the interest points to obtain relative 3D coordinates for both regular and irregular wave conditions. Then, the researchers evaluated the transformation accuracy of the modified SURF-based matching and image-based displacement estimation of the floating structure model in regular wave condition. For the regular wave condition, the wave generator's setting value was 3.0 sec and the cycle of the image-based displacement result was 2.993 sec. Taking into account mechanical error, these values can be considered as very similar. In terms of visual inspection, the researchers observed the shape of a regular wave in the 3-dimensional and 1-dimensional figures through the projection on X Y Z axis. In conclusion, it was possible to calculate the displacement of a floating structure module in near real-time using an average digital camcorder with 30fps video.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.867-873
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• 1999

Camera calibration is a procedure which calculates internal and external parameters of a camera with the Down world coordinates of the control points. Accurate camera calibration is required for achieving accurate visual measurements. In this paper, we propose a simple and flexible camera calibration using neural networks which doesn't require a special knowledge of 3D geometry and camera optics. There are some applications which are not in need of the values of the internal and external parameters. The proposed method is very useful to these applications. Also, the proposed camera calibration has advantage that resolves the ill-condition as object plane is near parallel image plane. The ill-condition is frequently met in product inspection. For little more accurate calibration, acquired image is divided into two regions according to radial distortion of lens and neural network is applied to each region. Experimental results and comparison with Tsai's algorithm prove the validity of the proposed camera calibration.