• Smart Structures and Systems
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• v.31 no.6
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• pp.573-583
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• 2023

Although unmanned aerial vehicles have been used to overcome the limited accessibility of human-based visual inspection, unresolved issues still remain. Onsite inspectors face difficulty finding previously detected damage locations and tracking their status onsite. For example, an inspector still marks the damage location on a target structure with chalk or drawings while comparing the current status of existing damages to their previous status, as documented onsite. In this study, an augmented-reality-based structural inspection system with onsite damage information marking was developed to enhance the convenience of inspectors. The developed system detects structural damage, creates a holographic marker with damage information on the actual physical damage, and displays the marker onsite via an augmented reality headset. Because inspectors can view a marker with damage information in real time on the display, they can easily identify where the previous damage has occurred and whether the size of the damage is increasing. The performance of the developed system was validated through a field test, demonstrating that the system can enhance convenience by accelerating the inspector's essential tasks such as detecting damages, measuring their size, manually recording their information, and locating previous damages.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.3
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• pp.101-110
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• 2002

Most of the agricultural structures are in shortage of feasible facility management because these structures are small in size and spacially distributed in rural area. Inspection tools based on visual inspections are generally used for agricultural structures in most of the countries, including Korea. It is necessary to survey data of the irrigation structures to maintain records, and to develop the interface program by constructing database of inspection data. This study was conducted to develop a system for safe appraisal and repair works on agricultural irrigation structures. Repair and rehabilitation method can be chosen from an optimum viewpoint if the information between the method and life-cycle management cost of agricultural structures is constructed in the database. In this study, the system assisting onsite field investigation and determining the typical rehabilitation method of typical agricultural structural problems such as fractures and cracks of members was developed.

• Fire Science and Engineering
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• v.28 no.5
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• pp.58-63
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• 2014

Fire-resistance paints are supposed to become intumescent and diminish heat transfer along the steel frames in case of a fire. If unsatisfactory fire-resistance paints which do not satisfy their standard specification are used, it may result in a severe disaster. Because satisfactory fire-resistance paints are hardly discriminated from the unsatisfactory ones by a simple visual inspection, more reliable and convenient onsite evaluation methods are necessary. Here we report the preliminary study result on the fire safety testing method for fire-resistance paints using an X-ray analysis method. It was found that the existence and quantity of effective constituents in fire-resistance paints can be detected by the X-ray analysis method. X-ray fluorescence (XRF) analyses showed that P and Cl elements are much more enriched in fire-resistance paints, compared to normal paints. X-ray diffraction (XRD) analyses showed that ammonium polyphosphate is present as the main crystalline material in fire-resistance paints, but absent in normal paints. The X-ray analysis method is expected to be used for the onsite inspection of fire-resistance paints with the upcoming availability of portable XRF and XRD instruments.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.657-665
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• 2021

Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high value assets or assets with a high consequence of failure, such as aerospace and nuclear components. Recent advances in convolution neural networks can support and automate these inspection efforts. This paper proposes using residual neural networks (ResNets) for real-time detection of corrosion, including iron oxide discoloration, pitting and stress corrosion cracking, in dry storage stainless steel canisters housing used nuclear fuel. The proposed approach crops nuclear canister images into smaller tiles, trains a ResNet on these tiles, and classifies images as corroded or intact using the per-image count of tiles predicted as corroded by the ResNet. The results demonstrate that such a deep learning approach allows to detect the locus of corrosion via smaller tiles, and at the same time to infer with high accuracy whether an image comes from a corroded canister. Thereby, the proposed approach holds promise to automate and speed up nuclear fuel canister inspections, to minimize inspection costs, and to partially replace human-conducted onsite inspections, thus reducing radiation doses to personnel.

• Journal of Construction Engineering and Project Management
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• v.6 no.2
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• pp.30-39
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• 2016

This research presents the development of a self-governing mobile robot navigation system for indoor construction applications. This self-governing robot navigation system integrated robot control units, various positioning techniques including a dead-reckoning system, a UWB platform and motion sensors, with a BIM path planner solution. Various algorithms and error correction methods have been tested for all the employed sensors and other components to improve the positioning and navigation capability of the system. The research demonstrated that the path planner utilizing a BIM model as a navigation site map could effectively extract an efficient path for the robot, and could be executed in a real-time application for construction environments. Several navigation strategies with a mobile robot were tested with various combinations of localization sensors including wheel encoders, sonar/infrared/thermal proximity sensors, motion sensors, a digital compass, and UWB. The system successfully demonstrated the ability to plan an efficient path for robot's movement and properly navigate through the planned path to reach the specified destination in a complex indoor construction site. The findings can be adopted to several potential construction or manufacturing applications such as robotic material delivery, inspection, and onsite security.

• Journal of People, Plants, and Environment
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• v.22 no.5
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• pp.467-480
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• 2019

Standard estimates are the numerical data of a unit quantity required for construction work such as the amount of materials, manpower, and the use of equipment required and are also a basis to calculate construction costs. Unfortunately, standard estimates for construction have also been used for garden construction these days as no standard estimates for garden construction have been developed or documented until now. As a result, many problems have arisen at garden construction sites since landscape construction and garden construction differ in terms of scope, size, design and construction methods. The purpose of this study was to develop standard estimates for garden construction for proper calculation of the cost of garden construction and to ensure gardens are created following appropriate construction processes. In order to develop standard estimates for garden construction, a preliminary survey was conducted on experts to understand current issues at first. After that, a questionnaire survey was done to examine problems of construction processes and ways of improvement, and on-site inspections were conducted utilizing CCTVs at construction sites to identify the actual amount of manpower required on site. Based on the results of the surveys and on-site inspections, a draft version of standard estimates for 5 types of planting work for garden construction was developed. Developing standard estimates for garden construction will serve as a stepping stone for the transparent and proper compensation for garden construction work, which will not only contribute to addressing issues between consumers and construction companies, but also to the stabilization of market economy and job creation.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.451-463
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• 2022

Whenever a mineshaft accidentally collapses, speedy risk assessment is both required and crucial. But onsite safety diagnosis by humans is reportedly difficult considering the additional risk of collapse of the unstable mineshaft. Generally, drones equipped with high-speed lidar sensors can be used for such inspection. However, the drone technology is restrictively applicable at very shallow depth, failing in mineshafts with depths of hundreds of meters because of the limit of wireless communication and turbulence inside the mineshaft. In previous study, a three-dimensional (3D) scanning system with a single channel lidar was fabricated and operated using towed cable in a mineshaft to a depth of 200 m. The rotation and pendulum movement errors of the measuring unit were compensated for by applying the data of inertial measuring unit and comparing the similarity between the scan data of the adjacent depths (Kim et al., 2020). However, the errors grew with scan depth. In this paper, a multi-channel lidar sensor to obtain a continuous cross-sectional image of the mineshaft from a winch system pulled from bottom upward. In this new approach, within overlapped region viewed by the multi-channel lidar, rotation error was compensated for by comparing the similarity between the scan data at the same depth. The fabricated system was applied to scan 0-165 m depth of the mineshaft with 180 m depth. The reconstructed image was depicted in a 3D graph for interpretation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.107-116
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• 2022

Recently, research has been actively conducted on the technology of inspection facilities through image-based analysis assessment of human-inaccessible facilities. This research was conducted to study the conditions of deep learning-based imaging data on bridges and to develop an evaluation prototype program for bridges. To develop a deep learning-based bridge damage detection prototype, the Semantic Segmentation model, which enables damage detection and quantification among deep learning models, applied Mask-RCNN and constructed learning data 5,140 (including open-data) and labeling suitable for damage types. As a result of performance modeling verification, precision and reproduction rate analysis of concrete cracks, stripping/slapping, rebar exposure and paint stripping showed that the precision was 95.2 %, and the recall was 93.8 %. A 2^nd performance verification was performed on onsite data of crack concrete using damage rate of bridge members.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.5
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• pp.431-439
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• 2016

This paper dealt with contents of the quality evaluation method of lattice girder utilizing non-destructive method. Quality evaluation of ordinary lattice girder is performed through the tensile strength test of structural steel and visual inspection. The tensile strength test of structural steel is performed by collecting samples of lattice girder brought into the site, during which lattice girder must be damaged to obtain sample. In addition to such disadvantage, tensile strength tester is not available at the site in most cases, requiring an inconvenient service from test certification agency. In addition, it is substituted by mile sheet issued during the production of structural steel, which inevitably lacks reliability. Furthermore, visual inspection at the site entails a problem of lack of reliability, thereby requiring a method of easily and quickly evaluating the quality of lattice girder without damaging the material. Accordingly, this study comparatively analyzed the yield strength of tensile strength test and the yield strength of instrumented indentation test with same sample. The test results ensured over 95% precision level for the instrumented indentation test, based on which a quality evaluation method based on instrumented indentation test that allowed onsite direct quality evaluation is proposed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.25-32
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• 2023

In this study, a double wall system is introduced, which was invented to simplify the complicated manufacturing process of the existing precast concrete (PC) double wall systems and to remove defects such as laitance that may occur during the production of concrete panels. An experimental study was conducted to investigate the tensile resisting capacity of the steel tube which is embedded in the precast concrete panel to keep the spacing between PC panels and to prevent damage of the PC panels during transportation and casting concrete onsite. The experiment was planned to determine the detail of effective steel tube connection considering the steel plate treatment method according to the formation of the opening, the presence of embedded concrete, and the reinforcement welding for additional dowel action as key variables. As a result, the ultimate tensile strength increased by 20-30% compared to the control specimen (ST) except for the steel tube specimen (ST_CP) which has steel plates bent inward at the end part of the steel tube. Since the specimen (ST_CON) filled with concrete inside the control specimen has no additional process and cost for the steel tube connections compared to the control specimen during the production of the developed double wall system, it is determined to be the appropriate detail of steel tube connection.