A tunnel structure health monitoring method based on surface strain monitoring

Abstract

The effectiveness of tunnel monitoring is a challenging task due to the limitations of monitoring gauges and lack of monitoring sections. To address this, a novel theoretical analysis-based monitoring method for tunnel structures was proposed in this study. A theoretical approach was employed to establish the correlation between external loads and structural stress–strain response in tunnel lining during grouting and stability periods. A method has been developed to derive the distribution of external loads and internal forces throughout the entire tunnel using strain monitoring at specific locations on the structure. This method has been further validated through a case study of the Liucun Tunnel, providing insights into the accuracy of the monitoring approach. It is found that during the grouting period, the segment ring is surrounded by grout, resulting in peak external loads and internal forces. As the tunnel lining enters the load stability period, both the external loads and internal forces gradually decrease and stabilize. Comparing the results of the monitored method for deriving tunnel external loads, structural bending moments and axial forces with the on-situ measurements, the new monitoring method yields errors in the response of tunnel external loads and internal forces. The average error in external loads is less than 12%, the average error in bending moments is less than 20%, and the average error in axial forces is less than 8%. The proposed monitoring method effectively addresses the issue of long-term failure of monitoring elements due to its replaceability. Additionally, utilizing theoretical methods for derivation allows obtaining more tunnel structural information based on limited monitoring data from the elements. This provides a new approach for long-term structural health monitoring. To address the existing errors in the monitoring method described in this study, the accuracy can be further improved by optimizing the model, incorporating more advanced monitoring techniques, and implementing standardized and improved construction practices.