小断面土石组合地质条件下TBM施工围岩可掘性分级识别

Classification and Predictive Research on Excavability of Surrounding Rock for TBM Construction in Small Section with Soil-RockComposite Geological Condition

围岩可掘性分级以及识别研究对隧道掘进机(TBM)高效率施工及智能化控制意义重大。依托南水北调安阳市西部调水工程TBM施工实际数据,利用掘进性能综合指标单位贯入度推力(FPI)、单位贯入度扭矩(TPI)建立了小断面土石组合地质条件下TBM施工围岩可掘性分级标准;提出了PCA-RF模型对围岩可掘性分级进行识别,并与BP、SVR和RF模型进行了比较讨论。结果表明:①建立的小断面土石组合围岩TBM施工可掘性分级标准是适用的,克服了土石组合围岩下传统围岩分类方法的局限性;②小断面土石组合围岩TBM施工可掘性分级PCA-RF识别模型的识别准确率达到了98.3%,高于BP、SVR和RF模型,可以满足工程施工需要。

The efficient construction and intelligent control of TBM heavily rely on the classification and real-time identification of surrounding rock excavability.To address this,we establish a classification standard for surrounding rock excavability in TBM construction under geological conditions characterized by small sections and soil-rock combinations based on actual data(penetration thrust and torque per unit penetration)from the Anyang Western Water Diversion Project.Moreover,we introduce the PCA-RF model for real-time identification and prediction of surrounding rock excavability,and then compared the results with those of BP,SVR,and RF models.Our research yields the following conclusions:1)The classification standard for surrounding rock excavability in TBM construction under the geological conditions of small sections and soil-rock combinations proves to be applicable.This standard resolves the limitations of traditional methods for classifying surrounding rock in soil-rock composite environments.2)The PCA-RF model demonstrates an identification and prediction accuracy of 98.3%for the surrounding rock excavability in TBM construction under the geological conditions of small sections and soil-rock combinations.This accuracy surpasses that of the BP,SVR,and RF models and fulfills the demands of engineering construction.