Long-term prediction of tunnel primary lining deformation based on wireless monitoring
Yuxuan Xia, Dongming Zhang, Bo Zhang, Changze Li, Yue Tong
Abstract. Due to the harsh construction environment such as blasting excavation and dust, conventional monitoring methods are challenging to be continuously deployed at the primary lining section of the drilling and blasting tunnel, which makes it difficult to capture the large deformation evolution trend and warn the deformation risk. Therefore, this paper takes a biased construction section of Xujiacun tunnel as a site case to implement a wireless sensor network, including gateway and laser distance senor, which is embedded into the primary lining to protect sensors in harsh construction environment for high frequency of primary lining deformation monitoring. Subsequently, a DLinear model is applied, which can be used for the long-term prediction of deformation time-series by splitting deformation sequence into trend sequence and residual sequence. Its prediction performance under different prediction steps is tested, so as to provide accurate and long-term risk early-warning in real-time for construction sites.
Keywords
Long-Term Prediction, Wireless Monitoring, Large Deformation, Tunnel Primary Lining
Published online 3/25/2025, 8 pages
Copyright © 2025 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Yuxuan Xia, Dongming Zhang, Bo Zhang, Changze Li, Yue Tong, Long-term prediction of tunnel primary lining deformation based on wireless monitoring, Materials Research Proceedings, Vol. 50, pp 44-51, 2025
DOI: https://doi.org/10.21741/9781644903513-5
The article was published as article 5 of the book Structural Health Monitoring
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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