• 제목/요약/키워드: Road Damage Detection

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Extraction of quasi-static component from vehicle-induced dynamic response using improved variational mode decomposition

  • Zhiwei Chen;Long Zhao;Yigui Zhou;Wen-Yu He;Wei-Xin Ren
    • Smart Structures and Systems
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    • v.31 no.2
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    • pp.155-169
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    • 2023
  • The quasi-static component of the moving vehicle-induced dynamic response is promising in damage detection as it is sensitive to bridge damage but insensitive to environmental changes. However, accurate extraction of quasi-static component from the dynamic response is challenging especially when the vehicle velocity is high. This paper proposes an adaptive quasi-static component extraction method based on the modified variational mode decomposition (VMD) algorithm. Firstly the analytical solutions of the frequency components caused by road surface roughness, high-frequency dynamic components controlled by bridge natural frequency and quasi-static components in the vehicle-induced bridge response are derived. Then a modified VMD algorithm based on particle swarm algorithm (PSO) and mutual information entropy (MIE) criterion is proposed to adaptively extract the quasi-static components from the vehicle-induced bridge dynamic response. Numerical simulations and real bridge tests are conducted to demonstrate the feasibility of the proposed extraction method. The results indicate that the improved VMD algorithm could extract the quasi-static component of the vehicle-induced bridge dynamic response with high accuracy in the presence of the road surface roughness and measurement noise.

RECENT R&D ACTIVITIES ON STRUCTURAL HEALTH MONITORING FOR CIVIL INFRA-STRUCTURES IN KOREA

  • Yun, Chung-Bang
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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    • pp.21-32
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    • 2003
  • Developments and applications of the structural health monitoring (SHM) systems have become active particularity for long-span bridges in Korea. They are composed of sensors, data acquisition system, data transmission system, information processing, damage assessment, and information management. In this paper, current status of research and application activities on SHM systems for civil infra-structures in Korea are briefly introduced by 4 parts: (1) current status of bridge monitoring systems on existing and newly constructed bridges, (2) research and development activities on smart sensors such as optical fiber sensors and piezo-electric sensors, (3) structural damage detection methods using measured data, and (4) a test road project for pavement design verification and enhancement by the Korea Highway Corporation. Finally the R&D activities of a new engineering research center entitled Smart Infra-Structure Technology Center at Korea Advanced Institute of Science and Technology are also briefly described.

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Encoder Type Semantic Segmentation Algorithm Using Multi-scale Learning Type for Road Surface Damage Recognition (도로 노면 파손 인식을 위한 Multi-scale 학습 방식의 암호화 형식 의미론적 분할 알고리즘)

  • Shim, Seungbo;Song, Young Eun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.2
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    • pp.89-103
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    • 2020
  • As we face an aging society, the demand for personal mobility for disabled and aged people is increasing. In fact, as of 2017, the number of electric wheelchair in the country continues to increase to 90,000. However, people with disabilities and seniors are more likely to have accidents while driving, because their judgment and coordination are inferior to normal people. One of the causes of the accident is the interference of personal vehicle steering control due to unbalanced road surface conditions. In this paper, we introduce a encoder type semantic segmentation algorithm that can recognize road conditions at high speed to prevent such accidents. To this end, more than 1,500 training data and 150 test data including road surface damage were newly secured. With the data, we proposed a deep neural network composed of encoder stages, unlike the Auto-encoding type consisting of encoder and decoder stages. Compared to the conventional method, this deep neural network has a 4.45% increase in mean accuracy, a 59.2% decrease in parameters, and an 11.9% increase in computation speed. It is expected that safe personal transportation will be come soon by utilizing such high speed algorithm.

Pothole Detection Algorithm Based on Saliency Map for Improving Detection Performance (포트홀 탐지 정확도 향상을 위한 Saliency Map 기반 포트홀 탐지 알고리즘)

  • Jo, Young-Tae;Ryu, Seung-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.4
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    • pp.104-114
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    • 2016
  • Potholes have caused diverse problems such as wheel damage and car accident. A pothole detection technology is the most important to provide efficient pothole maintenance. The previous pothole detections have been performed by manual reporting methods. Thus, the problems caused by potholes have not been solved previously. Recently, many pothole detection systems based on video cameras have been studied, which can be implemented at low costs. In this paper, we propose a new pothole detection algorithm based on saliency map information in order to improve our previously developed algorithm. Our previous algorithm shows wrong detection with complicated situations such as the potholes overlapping with shades and similar surface textures with normal road surfaces. To address the problems, the proposed algorithm extracts more accurate pothole regions using the saliency map information, which consists of candidate extraction and decision. The experimental results show that the proposed algorithm shows better performance than our previous algorithm.

Deforestation Patterns Analysis of the Baekdudaegan Mountain Range (백두대간지역의 산림훼손경향 분석)

  • Lee, Dong-Kun;Song, Won-Kyong;Jeon, Seong-Woo;Sung, Hyun-Chan;Son, Dong-Yeob
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.10 no.4
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    • pp.41-53
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    • 2007
  • The Baekdudaegan Mountain Range is a backbone of the Korean Peninsula which carries special spiritual and sentimental signatures for Koreans as well as significant ecological values for diverse organisms. However, in spite of importance of this region, the forests of Baekdudaegan have been damaged in a variety of human activities by being used as highland vegetable grower, lumber region, grass land, and bare land, and are still undergoing destruction. The existing researches had determined the details of the damage through on-site and recent observations. Such methods cannot provide quantitative and integrated analysis therefore could not be utilized as objective data for the ecological conservation of Baekdudaegan forests. The goal of this study is to quantitatively analyze the forest damage in the Baekdudaegan preservation region through land cover categorization and change detection techniques by using satellite images, which are 1980s, and 1990s Landsat TM, and 2000s Landsat ETM+. The analysis was executed by detecting land cover changed areas from forest to others and analyzing changed areas' spatial patterns. Through the change detection analysis based on land cover classification, we found out that the deforested areas were approximately three times larger after the 1990s than from the 1980s to the 1990s. These areas were related to various topographical and spatial elements, altitude, slope, the distance form road, and water system, etc. This study has the significance as quantitative and integrated analysis about the Baekdudaegan preservation region since 1980s. These results could actually be utilized as basic data for forest conservation policies and the management of the Baekdudaegan preservation region.

Damage Detection of Decrepit Tunnel Structures using the NDT (비파괴 검사법에 의한 노후터널의 건전도 평가)

  • Kim, Dong-Gyou;Jung, Ho-Seop
    • Proceedings of the Korean Geotechical Society Conference
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    • 2010.03a
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    • pp.1388-1391
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    • 2010
  • Recently, the construction of road, subway, railroad, and microtunnel for electricity supplement have been increased because of increasement of traffic in urban area, increasement of industrial transportation, and the network between cities in Korea. The deterioration of tunnel structure may occur by various internal and external factors and particularly, tunnel structures tend to contact with either underground water or harmful ions. Therefore, leakage sometimes occurred through the cracks and joints of concrete lining. The leakage in tunnel may affect the durability of concrete lining. In this study, to evaluate the durability and deterioration of concrete lining in tunnel structures, we were performed the various experiments for compressive strength. Compressive strength obtained from nondestructive inspection and compressive strength test varies according to the concrete lining conditions.

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Damage Proxy Map over Collapsed Structure in Ansan Using COSMO-SkyMed Data

  • Nur, Arip Syaripudin;Fadhillah, Muhammad Fulki;Jung, Young-Hoon;Nam, Boo Hyun;Kim, Yong Je;Park, Yu-Chul;Lee, Chang-Wook
    • The Journal of Engineering Geology
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    • v.32 no.3
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    • pp.363-376
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    • 2022
  • An area under construction for a living facility collapsed around 12:48 KST on 13 January 2021 in Sa-dong, Ansan-si, Gyeonggi-do. There were no casualties due to the rapid evacuation measure, but part of the temporary retaining facility collapsed, and several cracks occurred in the adjacent road on the south side. This study used the potential of synthetic aperture radar (SAR) satellite for surface property changes that lies in backscattering characteristic to map the collapsed structure. The interferometric SAR technique can make a direct measurement of the decorrelation among different acquisition dates by integrating both amplitude and phase information. The damage proxy map (DPM) technique has been employed using four high-resolution Constellation of Small Satellites for Mediterranean basin Observation (COSMO-SkyMed) data spanning from 2020 to 2021 during ascending observation to analyze the collapse of the construction. DPM relies on the difference of pre- and co-event interferometric coherences to depict anomalous changes that indicate collapsed structure in the study area. The DPMs were displayed in a color scale that indicates an increasingly more significant ground surface change in the area covered by the pixels, depicting the collapsed structure. Therefore, the DPM technique with SAR data can be used for damage assessment with accurate and comprehensive detection after an event. In addition, we classify the amplitude information using support vector machine (SVM) and maximum likelihood classification algorithms. An investigation committee was formed to determine the cause of the collapse of the retaining wall and to suggest technical and institutional measures and alternatives to prevent similar incidents from reoccurring. The report from the committee revealed that the incident was caused by a combination of factors that were not carried out properly.

Road Patrol Strategy based on Pothole Occurrence Characteristics considering Rainfall Effects (우천에 따른 포트홀 발생 특성을 고려한 도로순찰 전략)

  • Han, Daeseok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.603-611
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    • 2020
  • Potholes on the road directly affect drivers' safety, satisfaction, and vehicle damage. Thus, real-time detection and response are required. Increasing frequency of patrols allows for potholes to be detected and responded to quickly, but this takes much manpower, money, and time. In addition, potholes have different occurrence characteristics depending on the rain conditions, so it is necessary to consider the optimal frequency from an economic and road-service perspective. Therefore, a quantitative analysis was done on the effects of rainfall on the occurrence characteristics of potholes. Information on the persistence, impact of rainfall intensity, and weather information was collected over a long period. Based on the results, a risk-based, optimized, and changeable road-patrol strategy is presented. The analysis results show that the probability of pothole occurrence increases by 2.4 times in rainy weather. Furthermore, the impact continues for 3 days even after the rain stops. The probability of pothole occurrence increases by 0.46% per 1 mm of rainfall, and the occurrence characteristics react sensitively to even a small amount of rain of around 1 mm. It was concluded that road patrol is required at least once every three days for an effect-free period, while twice a day is needed for the "sphere of influence" period to achieve a 95% reliability level.ys for effect-free period, while twice a day for sphere of influence period to satisfy 95% reliability level.

A Design of Passenger Detection and Sharing System(PDSS) to support the Driving ( Decision ) of an Autonomous Vehicles (자율차량의 주행을 보조하기 위한 탑승객 탐지 및 공유 시스템 개발)

  • Son, Su-Rak;Lee, Byung-Kwan;Sim, Son-Kweon;Jeong, Yi-Na
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.2
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    • pp.138-144
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    • 2020
  • Currently, an autonomous vehicle studies are working to develop a four-level autonomous vehicle that can cope with emergencies. In order to flexibly respond to an emergency, the autonomous vehicle must move in a direction to minimize the damage, which must be conducted by judging all the states of the road, such as the surrounding pedestrians, road conditions, and surrounding vehicle conditions. Therefore, in this paper, we suggest a passenger detection and sharing system to detect the passenger situation inside the autonomous vehicle and share it with V2V to the surrounding vehicles to assist in the operation of the autonomous vehicle. Passenger detection and sharing system improve the weighting method that recognizes passengers in the current vehicle to identify the passenger's position accurately inside the vehicle, and shares the passenger's position of each vehicle with other vehicles around it in case of emergency. So, it can help determine the driving of a vehicle. As a result of the experiment, the body pressure sensor applied to the passenger recognition sub-module showed about 8% higher accuracy than the conventional resonant sensor and about 17% higher than the piezoelectric sensor.

Detection of Trees with Pine Wilt Disease Using Object-based Classification Method

  • Park, Jeongmook;Sim, Woodam;Lee, Jungsoo
    • Journal of Forest and Environmental Science
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    • v.32 no.4
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    • pp.384-391
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    • 2016
  • In this study, regions infected by pine wilt disease were extracted by using object-based classification method (OB-infected region), and the characteristics of special distribution about OB-infected region were figured out. Scale 24, Shape 0.1, Color 0.9, Compactness 0.5, and Smoothness 0.5 was selected as the objected-based, optimal weighted value of OB-infected region classification. The total accuracy of classification was high with 99% and Kappa coefficient was also high with 0.97. The area of OB-infected region was approximately 90 ha, 16% of the total area. The OB-infected region in Age class V and VI was intensively distributed with 97% of the total. Also, The OB-infected region in Middle and Large DBH class was intensively distributed with 99% of the total. In terms of the topographic characteristics of OB-infected region, the damages occurred approximately 86% below the altitude of 200 m, and occurred 91% with a slope less than 10 degree. The damage occurred a lot in low hilly mountain and undulating slope. In addition, the accessibility to road and residential area from OB-infected region was less than 300 m in large part. Overall, it was figured out that artificial effect is stronger than natural effect with regard to the spread of pine wilt disease.