Real-time distinguishing method and system for tunnel-diameter-spanning surrounding rock category of TBM (Tunnel Boring Machine) based on rock breaking mechanism

By combining the DFPI and DTPI feature indices based on rock breaking mechanisms with MMD and Bayesian classification models, the real-time performance and interpretability issues of TBM surrounding rock classification were resolved, enabling real-time identification of surrounding rock grades and parameter optimization.

CN121614972AActive Publication Date: 2026-03-06BEIJING JIAOTONG UNIV
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Patent Information

Application Number
CN202511623327.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-07
Publication Date
2026-03-06
Estimated Expiration
2045-11-07

AI Technical Summary

Technical Problem

Traditional TBM surrounding rock classification methods rely on sampling and manual interpretation, which lacks continuity and timeliness. Furthermore, purely data-driven methods are constrained by the scarcity of labels in the early stages of engineering, making it difficult to meet real-time control requirements. The application of these methods across equipment and geological domains is limited, and their interpretability is insufficient.

Method used

Based on the rock-breaking mechanism, by acquiring the tunnel excavation data of TBM construction tunnels, the DFPI and DTPI rock-breaking characteristic indices are constructed. Combined with the MMD method and Bayesian classification model, two-dimensional and one-dimensional surrounding rock discrimination models are constructed to realize real-time discrimination of surrounding rock grade.

Benefits of technology

It enables real-time and robust identification of surrounding rock types, reduces the impact of equipment size and operational disturbances, improves portability across tunnel diameters and engineering projects, and provides a basis for real-time parameter optimization and risk collaborative decision-making.

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Abstract

The invention provides a real-time TBM (Tunnel Boring Machine) cross-tunnel-diameter surrounding rock category distinguishing method and system based on a rock breaking mechanism. The method comprises the following steps: acquiring tunneling data of different TBM construction tunnels, forming a sample data set, extracting tunneling parameters and equipment parameters of each engineering TBM, and forming a refining data set; extracting stable tunneling section data from the refined data set by adopting an MMD method, calculating DFPI and DTPI rock breaking characteristic indexes, and enabling the rock breaking characteristic indexes to correspond to surrounding rock category labels through pile numbers and tunneling time to obtain a surrounding rock grade data set; taking two standardized indexes of DFPI and DTPI as two-dimensional input variables, and constructing a two-dimensional Bayesian surrounding rock classification model; carrying out weighted fusion on [DFPI, DTPI] to obtain an index R, and constructing a one-dimensional surrounding rock discrimination model and a threshold identification method; and inputting the acquired TBM tunneling data into the one-dimensional surrounding rock discrimination model to obtain the surrounding rock grade of the current TBM tunnel face. According to the method, the model generalization ability is improved, and the problem that a current surrounding rock classification method is insufficient in physical interpretation is solved.
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