Analysis of verticality measurement by binocular stereo vision system for offshore monopile

Pengfei Ma; Kun Yang; Haichen Sui; Chongming Wang; Fanlin Yang

doi:10.1117/12.3029234

16 May 2024 Analysis of verticality measurement by binocular stereo vision system for offshore monopile

Pengfei Ma, Kun Yang, Haichen Sui, Chongming Wang, Fanlin Yang

Proceedings Volume 13166, International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024); 131660S (2024) https://doi.org/10.1117/12.3029234
Event: International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024), 2024, Changchun, China

Abstract

To enhance the accuracy and efficiency of detecting verticality in single-pile construction for offshore wind power, a binocular stereo vision measurement system is developed. This system combines binocular stereo imaging and attitude measurement to enable rapid and precise measurement of pile verticality in dynamic environments. The verticality of the inspected pile is determined using a total station, and the results are compared with the verticality data obtained from the binocular stereo vision system. Simulation experiments reveal that when the total station detects a verticality of 2.96‰ for the cylinder, the average verticality detected by the binocular stereo vision system in dynamic environments is 3.05‰. The minimum difference between the detection results of the binocular stereo vision system and the total station is 0.5‰, while the maximum difference is 1.27‰. The binocular stereo vision system exhibits high measurement accuracy, stability, and real-time performance, thereby enriching measurement methods and improving work efficiency in actual construction processes.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Pengfei Ma, Kun Yang, Haichen Sui, Chongming Wang, and Fanlin Yang "Analysis of verticality measurement by binocular stereo vision system for offshore monopile", Proc. SPIE 13166, International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024), 131660S (16 May 2024); https://doi.org/10.1117/12.3029234

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