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The decision-making of TBM operating parameters has an important guidingsignificance for TBM safe and efficient construction, and it has been one ofthe research hotpots in the field of TBM tunneling. For this purpose, thispaper introduces rock-breaking rules into machine learning method, and arock-machine mapping dual-driven by physical-rule and data-mining isestablished with high accuracy. This dual-driven mappings are subsequently usedas objective function and constraints to build a decision-making method for TBMoperating parameters. By searching the revolution per minute and penetrationcorresponding to the extremum of the objective function subject to theconstraints, the optimal operating parameters can be obtained. This method isverified in the field of the Second Water Source Channel of Hangzhou, China,resulting in the average penetration rate increased by 11.3%, and the totalcost decreased by 10.0%, which proves the practicability and effectiveness ofthe developed decision-making model.

Intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization