Research on interface monitoring technology for drilled concrete piles based on grey correlation cluster analysis

Dexiang Zhang; Xiuming Chen; Hong Zhang; Xu Zhou; Lifeng Fan

doi:10.1117/12.3012495

21 December 2023 Research on interface monitoring technology for drilled concrete piles based on grey correlation cluster analysis

Dexiang Zhang, Xiuming Chen, Hong Zhang, Xu Zhou, Lifeng Fan

Author Affiliations +

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129702G (2023) https://doi.org/10.1117/12.3012495
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

Drilled shafts, widely applied in structural engineering foundations such as highways and railway bridges, are favored due to their mature construction techniques, high bearing capacity, and wide applicability. However, inaccurate positioning of the concrete pouring interface within the drilled shaft can easily lead to problems such as overpouring, resulting in material waste and increased costs. The currently used rope and weight method for measurement is time-consuming, labor-intensive, and unable to accurately determine the concrete surface. To dynamically monitor the concrete pouring interface, this paper proposes a recognition technology based on a multi-sensor data acquisition cloud platform and the PSO-GA-BP neural network method. By monitoring data such as turbidity, conductivity, and pH value, the pouring interface is identified using the PSO-GA-BP neural network model, and the location and height are calculated to achieve intelligent monitoring of the concrete pouring interface. This approach effectively solves the issues of overpouring or underpouring.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dexiang Zhang, Xiuming Chen, Hong Zhang, Xu Zhou, and Lifeng Fan "Research on interface monitoring technology for drilled concrete piles based on grey correlation cluster analysis", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129702G (21 December 2023); https://doi.org/10.1117/12.3012495

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