Detection method of subgrade settlement for the road of ART in coastal tidal flat area based on Vehicle-mounted binocular stereo vision technology
To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method for subgrade settlement based on vehicle-mounted binocular stereo vision technology. This method aims to achieve all season, the whole road,...
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| Published in: | Scientific reports Vol. 15; no. 1; pp. 8077 - 25 |
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08.03.2025
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| Abstract | To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method for subgrade settlement based on vehicle-mounted binocular stereo vision technology. This method aims to achieve all season, the whole road, long-term detection of subgrade settlement for Road of ART (Autonomous rail Rapid Transit) in coastal tidal flat areas. Firstly, improved Schneider encoding is adopted as the marker for subgrade settlement monitoring points. Binocular camera calibration and stereo rectification are performed using Zhang’s method and the Bouguet algorithm before acquiring the marker images at the monitoring points, followed by efficient capture of Schneider ring coding images by the vehicle-mounted binocular stereo vision system. Thirdly, OpenCV is employed to preprocess the images, which improve image quality, eliminate noise, and enhance the features of the ring coding markers. On this basis, an improved SGBM algorithm is utilized for binocular stereo matching. Finally, according to the principle of triangulation, the three-dimensional coordinates of the monitoring points are obtained, and the corresponding settlement values of each monitoring point are determined through decoding and matching. Experimental results indicate that, for a true settlement value of 60 mm, the proposed detection method achieves an average settlement value of 58.897 mm, with a relative error rate of 1.84%. In the same experimental environment, the relative error rate of using a monocular camera detection method is 10.3%. The vehicle-mounted binocular camera method, with lower relative error than the monocular camera, offers a more efficient and accurate solution for nondestructive subgrade settlement detection, enhancing its intelligence. |
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| AbstractList | Abstract To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method for subgrade settlement based on vehicle-mounted binocular stereo vision technology. This method aims to achieve all season, the whole road, long-term detection of subgrade settlement for Road of ART (Autonomous rail Rapid Transit) in coastal tidal flat areas. Firstly, improved Schneider encoding is adopted as the marker for subgrade settlement monitoring points. Binocular camera calibration and stereo rectification are performed using Zhang’s method and the Bouguet algorithm before acquiring the marker images at the monitoring points, followed by efficient capture of Schneider ring coding images by the vehicle-mounted binocular stereo vision system. Thirdly, OpenCV is employed to preprocess the images, which improve image quality, eliminate noise, and enhance the features of the ring coding markers. On this basis, an improved SGBM algorithm is utilized for binocular stereo matching. Finally, according to the principle of triangulation, the three-dimensional coordinates of the monitoring points are obtained, and the corresponding settlement values of each monitoring point are determined through decoding and matching. Experimental results indicate that, for a true settlement value of 60 mm, the proposed detection method achieves an average settlement value of 58.897 mm, with a relative error rate of 1.84%. In the same experimental environment, the relative error rate of using a monocular camera detection method is 10.3%. The vehicle-mounted binocular camera method, with lower relative error than the monocular camera, offers a more efficient and accurate solution for nondestructive subgrade settlement detection, enhancing its intelligence. To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method for subgrade settlement based on vehicle-mounted binocular stereo vision technology. This method aims to achieve all season, the whole road, long-term detection of subgrade settlement for Road of ART (Autonomous rail Rapid Transit) in coastal tidal flat areas. Firstly, improved Schneider encoding is adopted as the marker for subgrade settlement monitoring points. Binocular camera calibration and stereo rectification are performed using Zhang’s method and the Bouguet algorithm before acquiring the marker images at the monitoring points, followed by efficient capture of Schneider ring coding images by the vehicle-mounted binocular stereo vision system. Thirdly, OpenCV is employed to preprocess the images, which improve image quality, eliminate noise, and enhance the features of the ring coding markers. On this basis, an improved SGBM algorithm is utilized for binocular stereo matching. Finally, according to the principle of triangulation, the three-dimensional coordinates of the monitoring points are obtained, and the corresponding settlement values of each monitoring point are determined through decoding and matching. Experimental results indicate that, for a true settlement value of 60 mm, the proposed detection method achieves an average settlement value of 58.897 mm, with a relative error rate of 1.84%. In the same experimental environment, the relative error rate of using a monocular camera detection method is 10.3%. The vehicle-mounted binocular camera method, with lower relative error than the monocular camera, offers a more efficient and accurate solution for nondestructive subgrade settlement detection, enhancing its intelligence. To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method for subgrade settlement based on vehicle-mounted binocular stereo vision technology. This method aims to achieve all season, the whole road, long-term detection of subgrade settlement for Road of ART (Autonomous rail Rapid Transit) in coastal tidal flat areas. Firstly, improved Schneider encoding is adopted as the marker for subgrade settlement monitoring points. Binocular camera calibration and stereo rectification are performed using Zhang's method and the Bouguet algorithm before acquiring the marker images at the monitoring points, followed by efficient capture of Schneider ring coding images by the vehicle-mounted binocular stereo vision system. Thirdly, OpenCV is employed to preprocess the images, which improve image quality, eliminate noise, and enhance the features of the ring coding markers. On this basis, an improved SGBM algorithm is utilized for binocular stereo matching. Finally, according to the principle of triangulation, the three-dimensional coordinates of the monitoring points are obtained, and the corresponding settlement values of each monitoring point are determined through decoding and matching. Experimental results indicate that, for a true settlement value of 60 mm, the proposed detection method achieves an average settlement value of 58.897 mm, with a relative error rate of 1.84%. In the same experimental environment, the relative error rate of using a monocular camera detection method is 10.3%. The vehicle-mounted binocular camera method, with lower relative error than the monocular camera, offers a more efficient and accurate solution for nondestructive subgrade settlement detection, enhancing its intelligence.To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method for subgrade settlement based on vehicle-mounted binocular stereo vision technology. This method aims to achieve all season, the whole road, long-term detection of subgrade settlement for Road of ART (Autonomous rail Rapid Transit) in coastal tidal flat areas. Firstly, improved Schneider encoding is adopted as the marker for subgrade settlement monitoring points. Binocular camera calibration and stereo rectification are performed using Zhang's method and the Bouguet algorithm before acquiring the marker images at the monitoring points, followed by efficient capture of Schneider ring coding images by the vehicle-mounted binocular stereo vision system. Thirdly, OpenCV is employed to preprocess the images, which improve image quality, eliminate noise, and enhance the features of the ring coding markers. On this basis, an improved SGBM algorithm is utilized for binocular stereo matching. Finally, according to the principle of triangulation, the three-dimensional coordinates of the monitoring points are obtained, and the corresponding settlement values of each monitoring point are determined through decoding and matching. Experimental results indicate that, for a true settlement value of 60 mm, the proposed detection method achieves an average settlement value of 58.897 mm, with a relative error rate of 1.84%. In the same experimental environment, the relative error rate of using a monocular camera detection method is 10.3%. The vehicle-mounted binocular camera method, with lower relative error than the monocular camera, offers a more efficient and accurate solution for nondestructive subgrade settlement detection, enhancing its intelligence. To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method for subgrade settlement based on vehicle-mounted binocular stereo vision technology. This method aims to achieve all season, the whole road, long-term detection of subgrade settlement for Road of ART (Autonomous rail Rapid Transit) in coastal tidal flat areas. Firstly, improved Schneider encoding is adopted as the marker for subgrade settlement monitoring points. Binocular camera calibration and stereo rectification are performed using Zhang's method and the Bouguet algorithm before acquiring the marker images at the monitoring points, followed by efficient capture of Schneider ring coding images by the vehicle-mounted binocular stereo vision system. Thirdly, OpenCV is employed to preprocess the images, which improve image quality, eliminate noise, and enhance the features of the ring coding markers. On this basis, an improved SGBM algorithm is utilized for binocular stereo matching. Finally, according to the principle of triangulation, the three-dimensional coordinates of the monitoring points are obtained, and the corresponding settlement values of each monitoring point are determined through decoding and matching. Experimental results indicate that, for a true settlement value of 60 mm, the proposed detection method achieves an average settlement value of 58.897 mm, with a relative error rate of 1.84%. In the same experimental environment, the relative error rate of using a monocular camera detection method is 10.3%. The vehicle-mounted binocular camera method, with lower relative error than the monocular camera, offers a more efficient and accurate solution for nondestructive subgrade settlement detection, enhancing its intelligence. |
| ArticleNumber | 8077 |
| Author | Wu, Qingdong Liu, Zhaohui Li, Fuhao Miao, Jijun Liu, Yihao |
| Author_xml | – sequence: 1 givenname: Qingdong surname: Wu fullname: Wu, Qingdong organization: School of Civil Engineering, Qingdao University of Technology, Shandong Luqiao Group Company, Ltd – sequence: 2 givenname: Jijun surname: Miao fullname: Miao, Jijun organization: School of Civil Engineering, Qingdao University of Technology – sequence: 3 givenname: Zhaohui surname: Liu fullname: Liu, Zhaohui email: zhaohuiliu@sdust.edu.cn organization: School of Transportation, Shandong University of Science and Technology – sequence: 4 givenname: Fuhao surname: Li fullname: Li, Fuhao organization: School of Transportation, Shandong University of Science and Technology – sequence: 5 givenname: Yihao surname: Liu fullname: Liu, Yihao organization: School of Transportation, Shandong University of Science and Technology |
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| Cites_doi | 10.3390/s24061807 10.1007/s11368-022-03294-w 10.1520/JTE20230417 10.1007/s11440-024-02395-9 10.3390/su142013276 10.1080/09500340.2019.1697834 10.1109/ICMA.2017.8015806 10.3390/app13169047 10.3390/jmse12050734 10.3934/mbe.2021160 10.1088/1742-6596/1634/1/012066 10.1109/ICFTIC54370.2021.9647410 10.1049/ipr2.12764 10.1016/j.conbuildmat.2023.130573 10.1109/TPAMI.2006.70 10.1016/j.ijleo.2021.168186 10.1038/s41598-024-63017-8 |
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| Keywords | Camera calibration and rectification Subgrade settlement Encoding marker Preprocessing Stereo matching Vehicle-mounted binocular vision detection |
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| Snippet | To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method... Abstract To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic... |
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| SubjectTerms | 639/166 639/624 639/705 Algorithms Binocular vision Camera calibration and rectification Cameras Encoding marker Humanities and Social Sciences multidisciplinary Preprocessing Roads & highways Science Science (multidisciplinary) Stereo matching Subgrade settlement Tidal flats Vehicle-mounted binocular vision detection |
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| Title | Detection method of subgrade settlement for the road of ART in coastal tidal flat area based on Vehicle-mounted binocular stereo vision technology |
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