A multi‐degree‐of‐freedom monitoring method for slope displacement based on stereo vision (2024)

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  • Weidong Wang Department of Civil Engineering Central South University Hunan China Center for Railway Infrastructure Smart Monitoring and Management Central South University Hunan China

    Department of Civil Engineering Central South University Hunan China

    Center for Railway Infrastructure Smart Monitoring and Management Central South University Hunan China

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  • Jun Peng Department of Civil Engineering Central South University Hunan China Center for Railway Infrastructure Smart Monitoring and Management Central South University Hunan China

    Department of Civil Engineering Central South University Hunan China

    Center for Railway Infrastructure Smart Monitoring and Management Central South University Hunan China

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    ,
  • Wenbo Hu Department of Civil Engineering Central South University Hunan China

    Department of Civil Engineering Central South University Hunan China

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    ,
  • Jin Wang Department of Civil Engineering Central South University Hunan China

    Department of Civil Engineering Central South University Hunan China

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    ,
  • Xinyue Xu Department of Civil Engineering Central South University Hunan China

    Department of Civil Engineering Central South University Hunan China

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    ,
  • Qasim Zaheer Department of Civil Engineering Central South University Hunan China

    Department of Civil Engineering Central South University Hunan China

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    ,
  • Shi Qiu Department of Civil Engineering Central South University Hunan China Department of Transportation Guangxi Provincial Government Guangxi China

    Department of Civil Engineering Central South University Hunan China

    Department of Transportation Guangxi Provincial Government Guangxi China

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Computer-Aided Civil and Infrastructure EngineeringVolume 39Issue 131 July 2024pp 2010–2027https://doi.org/10.1111/mice.13173

Published:23 February 2024Publication History

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Computer-Aided Civil and Infrastructure Engineering

Volume 39, Issue 13

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A multi‐degree‐of‐freedom monitoring method for slope displacement based on stereo vision (1)

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Abstract

Abstract

Three‐dimensional displacement monitoring over long distances has been a long‐standing concern in the structural health monitoring industry. In this study, a multi‐degree‐of‐freedom slope displacement monitoring method is developed by fusing computer vision and the 3D point triangulation method. Attributed to this method, the problems of outdoor binocular camera calibration, multi‐target mismatching, and outdoor illumination effects were solved. First, a two‐stage camera calibration method is proposed to accurately calibrate intrinsic and extrinsic camera parameters under a large field of view and long working distance conditions. Second, the adaptive spatial‐frequency method is proposed to calculate the coding and pixel coordinates of the monitored target. In this step, to solve the problem of mismatching monitored points in different camera frames, the Augmented Reality University of Cordoba code is introduced to provide a unique identity code for each monitored point. To mitigate the impact of illumination and other factors on pixel coordinate calculation, an adaptive pixel coordinate calculation method that combines information from the spatial and frequency domains is proposed., Third, based on the intrinsic and extrinsic parameters of the stereo camera and the pixel coordinates of the monitored points, the 3D coordinates of the monitored points are obtained through triangulation. Finally, the accuracy experiments and stability experiments are conducted. According to the results of the experiments, the measurement distance is positively correlated with the measurement error. And the baseline length is negatively correlated with the measurement error in the z‐direction. Ultimately, we suggest that the ratio of baseline length to measurement distance should be greater than 40%. When the recommended value is satisfied, the measurement error is less than 1mm when the measurement distance is less than 40m. When the measurement distance is equal to 90m, the measurement error is less than 5mm. Meanwhile, stability experiments of the algorithm were carried out, and in a period of outdoor validation experiments, the fluctuations were only sub‐millimeter, demonstrating good anti‐interference performance. Moreover, the method proposed in this study successfully monitored a landslide disaster in Guangxi, which demonstrated its outstanding practical application capabilities.

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      A multi‐degree‐of‐freedom monitoring method for slope displacement based on stereo vision (58)

      Computer-Aided Civil and Infrastructure Engineering Volume 39, Issue 13

      1 July 2024

      163 pages

      ISSN:1093-9687

      EISSN:1467-8667

      DOI:10.1111/mice.v39.13

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      © 2024 The Authors. Computer‐Aided Civil and Infrastructure Engineering published by Wiley Periodicals LLC on behalf of Editor.

      This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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          • Published: 23 February 2024

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