Research Progress on Intelligent Detection Technologies of Highway Bridges

被引:0
|
作者
He S.-H. [1 ]
Wang A.-H. [1 ,2 ]
Zhu Z. [1 ]
Zhao Y. [1 ]
机构
[1] Key Laboratory of Transport Industry of Bridge Detection Reinforcement Technology, Chang'an University, Xi'an
[2] SCEGC Mechanized Construction Group Company Ltd., Xi'an
基金
中国国家自然科学基金;
关键词
Bridge engineering; Bridge intelligent detection; Detection devices; Detection technologies; Intelligent evaluation; Review;
D O I
10.19721/j.cnki.1001-7372.2021.12.002
中图分类号
学科分类号
摘要
In order to improve the development of intelligent detection technologies in highway bridges, the detecting equipment, inspection method, damage identification algorithm, intelligent safety evaluation and maintenance decision were reviewed in this study. After comprehensive analysis, the current situation and development trends of intelligent detection technologies were summarized. According to the testing environments and the arrangements of components, unmanned aerial vehicles, mobile robots, ring-type climbing robots, multi-functional detection robots, cable-climbing robots, underwater robots, sonar device were designed and utilized. To collect the damage information of bridges, the image acquisition devices were installed in most of the intelligent detection equipment. Consequently, the obstacle avoidance, anti-environment disturbance ability and the image acquisition accuracy were of significance in estimating the effectiveness of these devices. In the field of intelligent detection methods, image acquisition technology, laser point-cloud scanning approaches and holography became mature gradually. Besides that, ground penetrating radar, interferometric synthetic aperture radar and sonar detection technology were available in detecting bridge foundation and scouring depth. However, owing to the poor anti-interference ability, the innovative technologies consisted of optical fiber sensing, thermography, acoustic emission technology, ultrasonic detection and electromagnetic sensing needed to be improved and validated further. With the development of intelligent detection equipment, improvement of detection technology and accumulation of detection information, the hierarchical comprehensive safety evaluation algorithm was no longer suitable for bridge estimations. To achieve scientific evaluation of service performance and disaster resistance resilience in regional and network bridges, the synchronous reconstruction used digital twinning methods and estimation with multi-source data fusion technologies were major development orientations in intelligent detection and evaluation of highway bridges. © 2021, Editorial Department of China Journal of Highway and Transport. All right reserved.
引用
收藏
页码:12 / 24
页数:12
相关论文
共 99 条
  • [1] COLIN C C, JAMES D M., Long-span Bridges: Analysis of Trends Using a Global Database [J], Structure and Infrastructure Engineering, 16, 1, pp. 219-231, (2020)
  • [2] Long-term Bridge Performance Committee Letter Report: 2012, (2012)
  • [3] Long-term Bridge Performance Committee Letter Report: 2014, (2014)
  • [4] ANNAMDAS V G M, BHALLA S, SOH C K., Applications of Structural Health Monitoring Technology in Asia [J], Structural Health Monitoring, 16, 3, pp. 324-346, (2017)
  • [5] ZOLLINI S, ALICANDRO M, DOMINICI D, Et al., UAV Photogrammetry for Concrete Bridge Inspection Using Objected-based Image Analysis (OBIA), Remote Sensing, (2020)
  • [6] HE Shuan-hai, ZHAO Xiang-mo, MA Jian, Et al., Review of Highway Bridge Inspection and Condition Assessment, China Journal of Highway and Transport, 30, 11, pp. 64-79, (2017)
  • [7] LIU Y F, NIE X, FAN J S, Et al., Image-based Crack Assessment of Bridge Piers Using Unmanned Aerial Vehicles and Three-dimensional Scene Reconstruction, Computer-aided Civil and Infrastructure Engineering, 35, pp. 511-529, (2020)
  • [8] CUEVAS P J S, SORIA P R, ARRUE B, Et al., Robotic System for Inspection by Contact of Bridge Beams Using UAVs, Sensors, (2019)
  • [9] PHUNG M D, QUACH C H, DINH T H, Et al., Enhanced Discrete Particle Swarm Optimization Path Planning for UAV Vision-based Surface Inspection, Automation in Construction, 81, pp. 25-33, (2017)
  • [10] DIAZ S M., 3D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular Vision [J], Journal of Sensors, (2021)