Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation Monitoring

As tunnel excavation and resource extraction progressively extend into deeper underground environments, the frequency of large deformation incidents in soft surrounding rock tunnels is increasing worldwide. To accurately and efficiently predict the large deformation tendencies of such tunnels, this study establishes, validates, and applies a multi‐index evaluation method based on microseismic (MS) source parameters in the context of plateau railway soft surrounding rock tunnels. A multi‐index evaluation approach based on an attribute recognition model is proposed, which comprehensively considers four key MS event parameters: the number of events ( N ), moment magnitude ( m W ), seismic energy ( E ), and the tunnel’s convergence deformation value. By analyzing various practical engineering cases, the weight of each parameter is assessed using a fuzzy comprehensive evaluation method. The identification model for large deformation tendencies in soft surrounding rock tunnels is constructed through weighted evaluation and the attribute measurement function of each index. The accuracy and applicability of the proposed multi‐index evaluation method are validated through the analysis of large deformation instances in soft surrounding rock tunnels from field engineering. The results demonstrate that the prediction of large deformation tendencies based on MS monitoring closely aligns with the actual occurrences of large deformations in soft surrounding rock tunnels. The findings provide a foundation for assessing significant deformation tendencies in tunnels subjected to high‐ground stress in weak surrounding rocks, with important implications for forecasting large deformation risks in such tunnels.