• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.189-192
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• 2008

Generally, the inspection is hard work and needs a lot of time. So, this work contains subjectivity of inspector owing to carry out the visual evaluations through naked eye. Thus, the result of inspection is not objective and reliable. The purpose of this study is to develop new inspection technique to solve above problems and to provide convenient inspection work. We make a new inspection system using digital image processing technology. This program can stitch each image and detect cracks of surface of concrete bridge. Also, It can extract an investigation drawing from the picture. Also, this program is a kind of management tools designed to have some functions such as converting the image data obtained from cameras to Data-Base format, searching and storing the data. At first, we try to make a automatic extracting program. But, changed by semiautomatic method because of various problems. Through field experiments, the application of this inspection system with specialty software has proven to be much faster, safer, and reliable than the inspections carried out by the naked eyes in managing safety of the bridges. The new inspection method may be able to make the inspection of bridge more efficient and reliable.

• Corrosion Science and Technology
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• v.7 no.4
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• pp.208-211
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• 2008

Safety operation of main pipelines is primarily provided by anticorrosive monitoring. Anticorrosive monitoring of oil pipeline transportation objects is based on results of complex corrosion inspections, analysis of basic data including design data, definition of a corrosion residual rate and diagnostic of general equipment's technical condition. All the abovementioned arrangements are regulated by normative documents. For diagnostics of corrosion-technical condition of oil pipeline transportation objects one presently uses different methods such as in-line inspection using devices with ultrasonic, magnetic or another detector, acoustic-emission diagnostics, electrometric survey, general external corrosion diagnostics and cameral processing of obtained data. Results of a complex of diagnostics give a possibility: $\cdot$ to arrange a pipeline's sectors according to a degree of corrosion danger; $\cdot$ to check up true condition of pipeline's metal; $\cdot$ to estimate technical condition and working ability of a system of anticorrosive protection. However such a control of corrosion technical condition of a main pipeline creates the appearance of estimation of a true degree of protection of an object if values of protective potential with resistive component are taken into consideration only. So in addition to corrosive technical diagnostics one must define a true residual corrosion rate taking into account protective action of electrochemical protection and true protection of a pipeline one must at times. Realized anticorrosive monitoring enables to take a reasonable decision about further operation of objects according to objects' residual life, variation of operation parameters, repair and dismantlement of objects.

• Publications of The Korean Astronomical Society
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• v.27 no.3
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• pp.39-47
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• 2012

MIRIS, Multi-purpose Infra-Red Imaging System, is the main payload of STSAT-3 (Korea Science & Technology Satellite 3), which will be launched in the end of 2012 (the exact date to be determined) by a Russian Dnepr rocket. MIRIS consists of two camera systems, SOC (Space Observation Camera) and EOC (Earth Observation Camera). During a shock test for the flight model stability in the launching environment, some lenses of SOC EQM (Engineering Qualification Model) were broken. In order to resolve the lens failure, analyses for cause were performed with visual inspections for lenses and opto-mechanical parts. After modifications of SOC opto-mechanical parts, the shock test was performed again and passed. In this paper, we introduce the solution for lens safety and report the test results.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2009.04a
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• pp.255-263
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• 2009

A indoor hydrant proportioner that is installed as fire extinction equipment when a fire breaks out in a building plays a vital role for a fire extinction at an early stage. The indoor waterproof hydrant proportioner installed currently can function in case of fire as fire extinction equipment only when it can maintain proper waterproof pressure meeting the standards stipulated in NFSC. The results of the survey on the waterproof pressure of the indoor hydrant proportioner installed in most buildings showed that the waterproof pressure installed inside the buildings was higher than the agreed level suggested by NFSC, which is very desirable state and is regarded as the results of fire facilities being maintained and managed by regular fire inspections. It is thought that the safety management of fire extinction facilities should be kept up both regularly and steadily through TAB.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Smart Structures and Systems
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• v.29 no.1
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.

• Journal of Korean Society of Disaster and Security
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• v.15 no.3
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• pp.1-14
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• 2022

Recently, the risk of water disasters are increasing due to climate change and the aging of river levees. Existing conventional river embankment inspections have many limitations due to the consumption of a lot of manpower and budget. Thus, it is necessary to establish a new monitoring and forecast/warning method for effective flood response. This study proposes the river levee health monitoring system by analyzing the relationship between river levee deformation and hydrological factors using Sentinel-1. The variance index calculated in this study was classified into 4 grades. And the levees collapse section was judged to be a high vulnerable point in which the variance rapidly increased based on the result of the rapid increase in soil moisture. In the future, it is expected that it will be possible to advance levee maintenance technology and improve national disaster management through the advancement of the existing levee management system and automated monitoring through the forensic method that combines remote technology.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.371-393
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• 2023

Crack detection in structures plays a vital role in ensuring their safety, durability, and reliability. Traditional crack detection methods sometimes need significant manual inspections, which are laborious, expensive, and prone to error by humans. Deep learning algorithms, which can learn intricate features from large-scale datasets, have emerged as a viable option for automated crack detection recently. This study presents an in-depth review of crack detection methods used till now, like image processing, traditional machine learning, and deep learning methods. Specifically, it will provide a comparative analysis of crack detection methods using deep learning, aiming to provide insights into the advancements, challenges, and future directions in this field. To facilitate comparative analysis, this study surveys publicly available crack detection datasets and benchmarks commonly used in deep learning research. Evaluation metrics employed to check the performance of different models are discussed, with emphasis on accuracy, precision, recall, and F1-score. Moreover, this study provides an in-depth analysis of recent studies and highlights key findings, including state-of-the-art techniques, novel architectures, and innovative approaches to address the shortcomings of the existing methods. Finally, this study provides a summary of the key insights gained from the comparative analysis, highlighting the potential of deep learning in revolutionizing methodologies for crack detection. The findings of this research will serve as a valuable resource for researchers in the field, aiding them in selecting appropriate methods for crack detection and inspiring further advancements in this domain.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3260-3267
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• 2023

Zr-Nb alloy have been widely used as fuel rods in nuclear power plants. However, from the Fukushima nuclear accident, the weakness of the rod was revealed under harsh conditions, and research on the safety of these types of rods was conducted after the disaster. The method of depositing chromium onto the existing Zr-Nb alloy fuel rods is being considered as a means by which to compensate for the weakness of Zr-Nb alloy rods because chromium is strong against oxidation at high temperatures and has high strength. In order to secure these advantages, it is important to maintain the Cr thickness of the rods and properly inspect the rods before and during their use in power generation. Eddy current testing is a typical means of evaluating the thickness of thin metals and detecting surface defects. Depending on the size and shape of the inspected object, various eddy current sensors can be applied. In particular, because pancake sensors can be manufactured in very small sizes, they can be used for inspections even in narrow spaces, such as a nuclear fuel assembly. In this study, an eddy current technique was developed to confirm the feasibility of Cr coating thickness evaluations. After determining the design parameters of the pancake sensor by means of a FEM simulation, a FPCB pancake sensor was manufactured and the optimal frequency was selected by measuring minute changes in the Cr-coating thickness using the developed sensor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.187-188
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• 2022

As information processing technology develops with the trend of the times, the possibility of cyber threats to nuclear facilities is increasing. In the 2000s, there was a growing perception that cyberattacks on nuclear facilities were needed, and in fact, a cybersecurity regulatory system for nuclear power plants began to be established to prepare for cyberattacks. In Korea, in order to prepare for cyber threats, in 2013 and 2014, the Act on Protection and Radiation Disaster Prevention, Enforcement Decree, and Enforcement Rules of Nuclear Facilities, etc., and notices related to the Radioactive Disaster Prevention Act were revised. In 2015, domestic nuclear operators prepared information system security regulations for each facility in accordance with the revised laws and received approval from the Nuclear Safety Commission for implementation of information system security regulations divided into seven stages. In 2019, a special inspection for step-by-step implementation was completed, and since 2019, the cybersecurity system of operators has been continuously inspected through regular inspections. In this paper, we present some measures to build improved training to suit the steadily revised inspection of the nuclear facility cybersecurity system to counter cyber threats to the ever-evolving nuclear facilities.