• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.396-399
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• 2004

This study was performed to develop necessary Visual Inspection System for the PSC Bridges precision safety diagnosis which to enhance the efficiency and accuracy of visual inspection by using mobile PC and adopted IT. This system was constructed to the automatic visual inspection map generating program and the Visual Inspection System using mobile PC that predicted high efficiency.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.3
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• pp.85-91
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• 2021

Type 1 and type 2 buildings must regularly conduct precise safety inspections and precise safety diagnosis for the safety and maintenance of facilities, and the safety grade of the building is determined according to the results of the implementation. In addition, the cycle of inspection and diagnosis is determined according to the safety grade of the building. In order to determine the safety grade of the building, a precise safety inspection conducts condition evaluation, and a precise safety diagnosis conducts condition evaluation and safety evaluation. Therefore, since the inspection and diagnosis cycle is determined according to the safety grade of the building, the condition evaluation and safety evaluation must be precise. However, in the case of member unit evaluation, which is the first step in evaluating the current condition, the evaluation grade is determined by using the representative value of the measurement result, and this may result in an error in the evaluation grade. To solve this problem, this study analyzed evaluation criteria for each evaluation item and presented evaluation criteria using inequalities to respond to measurement results and evaluation scores. In addition, we present a functional formula that can reflect performance scores for each evaluation item.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.3
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• pp.77-84
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• 2013

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.1-8
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• 2016

In 2008, 17, 596 dams and reservoirs are scattered across South Korea, and 17, 505 of them (99.5 %) are used for agriculture and 99.3 % are fill dam types. This study aimed to review literature related to the precise safety diagnosis system for agricultural reservoirs established by Korea Rural Community Corporation (KRCC) and analyze problems of its evaluation method. And then, it proposed ways to improve the system including a modified diagnosis system, which was applied to pilot districts in order to verify the utility. For assessment model development of agricultural reservoir, we reviewed status of precision safety inspections systems of agricultural reservoir. There are many problems such as assess agricultural reservoir not by sheet which used in fill dam but by block which used in concrete dam construction and diversion tunnel which main element in reservoir levee is treated as water intake facility. For considering diversion tunnel in reservoir levee, previous precision safety inspection systems which summed in separated phenomenon, separated element, separated site, separated facility was change to new systems which summed in site, phenomenon, element, and facility. Compared results of previous inspection system calculated total assessment index (Ec) with new system calculated total assessment index (Ec) are not show statistical difference.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.96-104
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• 2003

To assess tunnel safety, cracks in tunnel lining are measured by inspectors who observe cracks with their eyes. A manual inspection is, however, slow and subjective. This paper, therefore, proposes vision-based inspection system for measuring cracks in the tunnel lining that inspects cracks fast and objective. The system is consisted of an on-vehicle system and a lab system. An on-vehicle system acquires image data with line CCD camera. A lab system extracts crack then inform their thickness, length and orientation by using image processing. To improve accuracy of crack recognition the geometric properties of a crack was applied to image processing. The proposed system were verified with experiments in both laboratory and field environment.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.9
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• pp.777-782
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• 2014

Usually, railway axles are designed for infinite life based on endurance limit of the material and the axle is not fractured immediately when a surface crack initiated. The railway axles have been inspected regularly by NDT such as ultrasonic testing, magnetic testing and eddy current testing and so on. Because the axle failure is profoundly influenced by the probability of missing a fatigue crack during an NDT inspection, it is necessary to evaluate the Non Destructive Interval of railway axle. In the present paper, the Non Destructive Interval of railway axle based on fracture mechanics and finite element analysis was investigated. It was shown that the Non Destructive Interval of railway axle can be evaluated using fracture mechanics approach and extended using NDT which a crack can detect clearly.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• Journal of the Korea Safety Management & Science
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• v.26 no.2
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• pp.23-31
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• 2024

In the military, ammunition and explosives stored and managed can cause serious damage if mishandled, thus securing safety through the utilization of ammunition reliability data is necessary. In this study, exploratory data analysis of ammunition inspection records data is conducted to extract reliability information of stored ammunition and to predict the ammunition condition code, which represents the lifespan information of the ammunition. This study consists of three stages: ammunition inspection record data collection and preprocessing, exploratory data analysis, and classification of ammunition condition codes. For the classification of ammunition condition codes, five models based on boosting algorithms are employed (AdaBoost, GBM, XGBoost, LightGBM, CatBoost). The most superior model is selected based on the performance metrics of the model, including Accuracy, Precision, Recall, and F1-score. The ammunition in this study was primarily produced from the 1980s to the 1990s, with a trend of increased inspection volume in the early stages of production and around 30 years after production. Pre-issue inspections (PII) were predominantly conducted, and there was a tendency for the grade of ammunition condition codes to decrease as the storage period increased. The classification of ammunition condition codes showed that the CatBoost model exhibited the most superior performance, with an Accuracy of 93% and an F1-score of 93%. This study emphasizes the safety and reliability of ammunition and proposes a model for classifying ammunition condition codes by analyzing ammunition inspection record data. This model can serve as a tool to assist ammunition inspectors and is expected to enhance not only the safety of ammunition but also the efficiency of ammunition storage management.

• Journal of Korean Association for Spatial Structures
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• v.21 no.3
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• pp.85-92
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• 2021

The purpose of this paper is to understand the key factors for efficient maintenance of rapidly aging facilities. Therefore, the safety inspection/diagnosis reports accumulated in the unstructured data were collected and preprocessed. Then, the analysis was performed using a text mining analysis method. The derived vulnerabilities of tunnel facilities can be used as elements of inspections that take into account the characteristics of individual facilities during regular inspections and daily inspections in the short term. In addition, if detailed specification information and other inspection results(safety, durability, and ease of use) are used for analysis, it provides a stepping stone for supporting preemptive maintenance decision-making in the long term.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.133.6-133
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• 2001

Reactor vessel is one of the most important equipment of Nuclear Power Plant (NPP) with regard to the nuclear safety. Thus reactor vessel must be examined periodically by certified experts. Currently, ultra-sonic(UT) non-destructive inspection is executed on reactor vessel. Two different techniques are used in this inspection. One is using the movable manipulator fixed with the support-guide placed on the vessel, and the other is using mobile robot moving in the vessel. Movable manipulator machine is very heavy, hard to handle, and very expensive. Mobile robot equipment is small and convenient but has a weak point on positional precision. To solve these problems we developed a reactor inspection system based on laser-driven mobile robot. This paper describes the main concept and structure of integrated inspection units and the feature of implemented units.