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Scanning Scheme for Underwater High-Rise Pile Cap Foundation Based on Imaging Sonar

Author

Listed:
  • Sheng Shen

    (College of Civil Engineering, Fuzhou University, Fuzhou 350108, China)

  • Zheng Cao

    (College of Civil Engineering, Fuzhou University, Fuzhou 350108, China)

  • Changqin Lai

    (College of Civil Engineering, Fuzhou University, Fuzhou 350108, China)

Abstract

This study developed a sonar scanning scheme for underwater high-rise pile cap foundations (HRPCFs) to improve the efficiency of bridge inspection and prolong structural durability. First, two key factors in the measurement point arrangement that significantly affect the accuracy of sonar measurement—the appropriate range of measurement distance and the pitch angle—were determined experimentally. Subsequently, an assembled platform was designed to firmly hold the sonar and conveniently move it under strong currents to effectively provide clear images of the pile. A strategy was developed to determine the appropriate number and horizontal and vertical positions of the measurement points around each pile in the pile group, particularly to avoid the obstruction of signal propagation caused by adjacent piles and pile caps. The method was applied to the scanning of an underwater high-rise pile cap foundation of a bridge, and the results showed that the scanning ranges of the imaging sonar at all arranged measurement points were not affected by adjacent piles. The imaging sonar carried by the proposed platform could obtain clear images stably at a water speed of ~2.0 m/s and obtain all surface data of the pile quickly and completely.

Suggested Citation

  • Sheng Shen & Zheng Cao & Changqin Lai, 2023. "Scanning Scheme for Underwater High-Rise Pile Cap Foundation Based on Imaging Sonar," Sustainability, MDPI, vol. 15(8), pages 1-25, April.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6402-:d:1119004
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    References listed on IDEAS

    as
    1. Pengfei Shi & Xinnan Fan & Jianjun Ni & Zubair Khan & Min Li, 2017. "A novel underwater dam crack detection and classification approach based on sonar images," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-17, June.
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