Research on Cutter Anomaly Identification in Slightly Weathered Metamorphic Rock Formations Based on BO-Light GBM Model

Accurate and timely identification of cutter anomalies is crucial for ensuring the safety and efficiency of shield tunneling. To address the issues of poor timeliness and high costs associated with traditional periodic manual inspection methods, this study establishes a cutter anomaly identification model based on the BO-Light GBM algorithm, focusing on slightly weathered metamorphic rock formations. Six parameters closely related to the tunneling state were selected to construct the feature set, and one-class support vector machines (SVMs) were employed to remove anomalous samples. On this basis, a baseline Light GBM model with preset hyperparameters was developed, achieving a preliminary accuracy of 96.04%. Further hyperparameter tuning using Bayesian optimization boosted the overall accuracy of the final BO-Light GBM model to 99.40% while improving training efficiency by approximately 50% compared to exhaustive grid search. Interpretability analysis conducted via SHAP values revealed that chamber pressure, cutterhead rotation speed, total thrust, and cutterhead torque were the primary contributing features, with patterns consistent with actual tunneling conditions, confirming the accuracy of the model’s predictions. The research outcomes provide valuable theoretical guidance and technical support for similar engineering applications.