Safety Intelligent Control Platform of Deep-Buried Tunnel Based on Multivariate Monitoring Information

In recent years, with the rapid development of social economy and the increasing demand for clean energy, a large number of large-scale hydropower stations have started construction in southwest China. These large-scale hydropower projects often have many tunnels, and the tunnels are long, passing through a variety of complex strata, combined with the impact of strong excavation and unloading, which brings huge challenges to the safety of tunnel construction. In this paper, relying on the diversion tunnel project of Jinchuan Hydropower Station in Southwest China, various monitoring methods such as conventional monitoring, blasting vibration monitoring, microseismic monitoring, environmental monitoring, loose circle testing and 3D laser scanning are used for safety monitoring. And then the evolution characteristics of monitoring data in the unloading process of tunnel excavation are analyzed, the mechanism of abnormal monitoring data caused by tunnel construction is revealed, and the risk discrimination index based on multivariate monitoring information is established. In view of the difficult management and analysis of massive monitoring data during tunnel construction, based on SOA (Service-Oriented Architecture), the B/S (Browser/Server) three-tier architecture is adopted to build a deep-buried tunnel construction safety intelligent control platform that integrates multiple monitoring information. Through real-time input of multiple monitoring information into the platform, timely feedback and guidance of construction, realizing the safety and dynamic control of deep-buried tunnel construction, and it is expected to provide some references for the construction organization and design of the similar deep-buried tunnel excavation.