• Title/Summary/Keyword: 교량 점검

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A Condition Rating Method of Bridges using an Artificial Neural Network Model (인공신경망모델을 이용한 교량의 상태평가)

  • Oh, Soon-Taek;Lee, Dong-Jun;Lee, Jae-Ho
    • Journal of the Korean Society for Railway
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    • v.13 no.1
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    • pp.71-77
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    • 2010
  • It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.

A Study on Life Cycle Cost According to Bridge Condition (교량 상태에 따른 생애주기비용 영향 분석)

  • Park, Jun-Yong;Lee, Keesei
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.802-809
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    • 2021
  • To cope with the increasing maintenance costs due to aging, the maintenance cost was evaluated from the perspective of asset management. The maintenance cost can be predicted based on the condition of the bridge, and the life cycle cost is used as an index. In general, the condition of a bridge has a wide distribution characteristic depending on the deterioration, load, and material characteristics. In this paper, to evaluate the effect of the bridge conditions on the life cycle cost, condition prediction models were constructed considering the service life, deterioration rate, and inspection error, which are the main variables of the bridge condition and life cycle cost calculation. In addition, condition prediction models were constructed based on the distribution of the health index to estimate the upper and lower bounds of the life cycle costs that can occur in individual bridges. Life cycle cost analysis showed that the life cycle cost differed significantly according to the condition of the bridge. Accordingly, research will be needed to increase the reliability of predicting the life cycle cost of individual bridges.

Image-Based Automatic Bridge Component Classification Using Deep Learning (딥러닝을 활용한 이미지 기반 교량 구성요소 자동분류 네트워크 개발)

  • Cho, Munwon;Lee, Jae Hyuk;Ryu, Young-Moo;Park, Jeongjun;Yoon, Hyungchul
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.41 no.6
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    • pp.751-760
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    • 2021
  • Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

Comparative Study of Bridge Maintenance: United States, United Kingdom, Japan, and Korea (교량 유지관리 프로그램과 보수보강 공법에 대한 국가 간 비교 연구: 미국, 영국, 일본, 한국을 중심으로)

  • Jeong, Yo-Seok;Min, Geun-Hyeong;Lee, Il-Keun;Youn, Il-Ro;Kim, Woo-Seok
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.25 no.5
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    • pp.114-126
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    • 2021
  • This paper compared bridge maintenance in United Stated, United Kingdom, Japan, and Korea. Bridges play an essential role in transportation network and in the economic production process. To provide a desirable level of service to the public within limited budgets, it is required to provide effective bridge maintenance activities (e.g. inspection and repair/rehabilitation) at acceptable level of bridge service. A number of bridges are expected to age rapidly in Korea, which will be the excess burden of government. Since several countries have experienced a number of deteriorated bridges because of aging, the countries aforementioned in this study have already developed comprehensive bridge maintenance programs such as inspection practice and repair/rehabilitation techniques. Therefore, the goal of this paper is to synthesize and to compare useful knowledge on bridge maintenance and bridge crack repair/restoration of deteriorated concrete bridge in the four countries. Finally, recommendations that will serve as guidance to transportation agencies for potential enhancements to bridge maintenance and bridge repairs are presented.

The Development of Visual Inspection System for National Road Facility Maintenance Management (국도 시설물 유지관리를 위한 현장점검시스템 개발)

  • 주기범;김태학;박상근
    • Proceedings of the CALSEC Conference
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    • 2003.09a
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    • pp.72-77
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    • 2003
  • Visual inspection works are very important part of facility maintenance and management life cycle as a step of creating base data for decision making and maintenance and repair. But currently, visual inspection works have been performed unefficiently and unreliably as works on hand, duplication of works, decisions of defect state, unutilization of inspection history, lack of professional and so on. In this research, we developed visual inspection system that processes inspection work efficiently and provides reliability of inspection output, as a target of bridges, tunnels, underground roadway on national road. We defined problems through visual inspection work analysis, examined the solutions and reflected to functional design of system. We will plan to utilize this system in HMCS(Highway Maintenance and Construction Service).

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Correlation Analysis of Load-carrying Capacity by Safety Inspection Indicators in Bridges (교량 안전점검 지표별 내하성능 상관관계 분석)

  • Jung, Kyu San;Seo, Dong Woo;Kim, Jae Hwan;Cho, Han Min;Park, Ki Tae;Shin, Yeon-Woo
    • Journal of Korean Society of Disaster and Security
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    • v.15 no.3
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    • pp.89-99
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    • 2022
  • Bridges are a key infrastructure that underpins economic and social activities. In Korea, bridges began to be built with economic development in the 1970s and were built intensively in the 1980s and 1990s. In recent years, as the number of bridges with a service life of more than 30 years is increasing, continuous maintenance is required to ensure the safety of the bridges. In particular, in order to cope with the aging of bridges, research on technology development such as maintenance using ICT technology, preventive maintenance, life cycle cost reduction, and long life bridge is being actively promoted. This paper presents the results of correlation analysis based on the safety evaluation data of bridges as part of the research on the development of a model for estimating load-carrying capacity of bridges. As a analysis result, indicators highly correlated with the load-carrying capacity of the bridge was derived.

Orientation Analysis between UAV Video and Photos for 3D Measurement of Bridges (교량의 3차원 측정을 위한 UAV 비디오와 사진의 표정 분석)

  • Han, Dongyeob;Park, Jae Bong;Huh, Jungwon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.6
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    • pp.451-456
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    • 2018
  • UAVs (Unmanned Aerial Vehicles) are widely used for maintenance and monitoring of facilities. It is necessary to acquire a high-resolution image for evaluating the appearance state of the facility in safety inspection. In addition, it is essential to acquire the video data in order to acquire data over a wide area rapidly. In general, since video data does not include position information, it is difficult to analyze the actual size of the inspection object quantitatively. In this study, we evaluated the utilization of 3D point cloud data of bridges using a matching between video frames and reference photos. The drones were used to acquire video and photographs. And exterior orientations of the video frames were generated through feature point matching with reference photos. Experimental results showed that the accuracy of the video frame data is similar to that of the reference photos. Furthermore, the point cloud data generated by using video frames represented the shape and size of bridges with usable accuracy. If the stability of the product is verified through the matching test of various conditions in the future, it is expected that the video-based facility modeling and inspection will be effectively conducted.

Maintenance of the Sea-crossing Bridge for Ship Collision Problems (선박충돌 문제에 대한 해상교량의 유지관리)

  • Bae, Yong-Gwi;Lee, Seong-Lo
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.20 no.6
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    • pp.56-64
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    • 2016
  • Damage of sea-crossing bridge by ship collision is related to estimate frequencies of overloading due to impact, and bridge accordingly must be designed to satisfy related acceptance criteria. Another important aspect is the management on increment of collision risk during the service period. In this study, related plan, main span length, air draft clearance and collision risk are analyzed for the interim assessment of Incheon Bridge focusing on the ship collision problem. In particular, for the increment of collision risk, the optimized navigation speed is proposed by reviewing the research findings and navigation guidelines etc. as a temporary expedient. Also basic procedure for reasonable prediction of target vessel and passage is established and probabilistic prediction method to embrace the uncertainty of the prediction is proposed as a fundamental solution. It is necessary to conduct further research on collision risk management and promptly carry out interim assessments of other marine bridges.