<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study utilizes digital technology to monitor water pressure changes within basement flashings, facilitating targeted drainage operations. By implementing an active water discharge method, drainage holes are strategically placed around or beneath basements to decompress and reduce water levels, thereby alleviating hydrostatic pressure on underground structures. This approach helps prevent basement uplift. The paper addresses challenges such as high energy consumption and ample data storage in long-term monitoring, introducing an acceleration trigger module and a data correction algorithm based on an enhanced BP neural network. A WOA-BP neural network model was developed using historical data to monitor water pressure efficiently. Our findings indicate that at 0.076MPa, flashing connections begin to fail, progressing to shear damage at 0.085MPa. Consequently, to preserve basement integrity, it is crucial to activate complete drainage when monitored pressure exceeds 0.045MPa to maintain pressures below the critical threshold of 0.076MPa.</p>
</abstract>

This study utilizes digital technology to monitor water pressure changes within basement flashings, facilitating targeted drainage operations. By implementing an active water discharge method, drainage holes are strategically placed around or beneath basements to decompress and reduce water levels, thereby alleviating hydrostatic pressure on underground structures. This approach helps prevent basement uplift. The paper addresses challenges such as high energy consumption and ample data storage in long-term monitoring, introducing an acceleration trigger module and a data correction algorithm based on an enhanced BP neural network. A WOA-BP neural network model was developed using historical data to monitor water pressure efficiently. Our findings indicate that at 0.076MPa, flashing connections begin to fail, progressing to shear damage at 0.085MPa. Consequently, to preserve basement integrity, it is crucial to activate complete drainage when monitored pressure exceeds 0.045MPa to maintain pressures below the critical threshold of 0.076MPa.

Research on Data Acquisition and Regulation Methods of Basement Flashing Pressure Relief System Based on Digital Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This study utilizes digital technology to monitor water pressure changes within basement flashings, facilitating targeted drainage operations. By implementing...

Research on Data Acquisition and Regulation Methods of Basement Flashing Pressure Relief System Based on Digital Technology

Online veröffentlicht: 15. Mai 2024

Seitenbereich: -

Eingereicht: 26. Jan. 2024

Akzeptiert: 04. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1092

Schlüsselwörter
Water relief and pressure reduction, BP neural network, WOA-BP neural network, Water pressure monitoring

© 2024 Shixiao Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on Data Acquisition and Regulation Methods of Basement Flashing Pressure Relief System Based on Digital Technology

Online veröffentlicht: 15. Mai 2024

Seitenbereich: -

Eingereicht: 26. Jan. 2024

Akzeptiert: 04. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1092

SchlüsselwörterWater relief and pressure reduction, BP neural network, WOA-BP neural network, Water pressure monitoring

© 2024 Shixiao Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Water relief and pressure reduction, BP neural network, WOA-BP neural network, Water pressure monitoring