A TBM construction surrounding rock drillability grading method based on data mining

Abstract

The invention discloses a TBM construction surrounding rock drillability grading method based on data mining, and the method comprises the steps: building a penetration prediction model by using a stepwise regression method and considering the operation experience of a master driver according to the principle of safety and high efficiency; Performing regression analysis on the engineering project,and establishing a rotating speed prediction model; Summarizing engineering cases at home and abroad, and establishing a TBM construction tunneling utilization rate prediction model on the basis of data mining; And by taking the TBM tunneling speed as an evaluation index, finally establishing a surrounding rock drillability grading model based on TBM construction. The method aims at the current situation that traditional tunnel surrounding rock classification is incapable of well adapting to TBM construction by taking surrounding rock stability as an evaluation basis. A data mining method isprovided, a tunnel surrounding rock systematized classification method under the TBM construction condition is established, the TBM tunneling performance under various surrounding rock grades is accurately predicted, a decision basis is provided for TBM construction cost and construction period prediction, and optimization adjustment of TBM tunneling parameters is achieved.

Description

technical field [0001] The invention relates to a method for grading excavability of surrounding rock in TBM construction, in particular to a method for grading the excavability of surrounding rock for TBM considering the excavability of surrounding rock and equipment adaptability. Background technique [0002] Compared with the traditional tunnel construction method, the TBM method has a fast construction speed, and usually the excavation rate is 3 to 10 times that of the traditional drill and blast method. However, TBM has poor adaptability to geological conditions. If the parameters do not match with it, TBM may not be able to take advantage of its fast excavation speed, which may cause delays in the construction period. [0003] Traditional tunnel construction methods generally design tunnel support and guide construction through the classification of surrounding rocks, and budget the cost and construction period accordingly. However, most of the current tunnel surround...

AI Technical Summary

Problems solved by technology

In 1999, N.Barton proposed the Q system based on the Q system taxonomy. TBM system, although the system considers the interaction between the rock mass and the TBM, if the lithology of the surrounding rock of the tunnel is quite different, the prediction error obtained by using this model will be large, and the system involves too many parameter indicators, It is difficult to be practical and cannot meet the classification requirements of the surrounding rock of TBM construction tunnels

[0004] Therefore, the existing surrounding rock grading and classification system is not universally applicable, and it is often impossible to make reasonable grading predictions for specific projects.

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