TBM tunneling optimization method based on rock slag physical characteristics

Abstract

The invention discloses a TBM tunneling optimization method based on rock slag physical characteristics. The method comprises the steps that firstly, image acquisition and sensor equipment of a system is installed, and TBM field tunneling parameter data and parameter data of geometric characteristics and physical characteristics of rock slag are acquired to serve as a sample set of a model; secondly, a gradient lifting regression tree model optimized by a particle swarm algorithm is established for parameter learning and training feedback, and a TBM tunneling parameter suggestion interval is controlled; thirdly, the TBM net tunneling rate is output, an optimal prediction model is obtained, the working performance of the optimal prediction model is evaluated according to a test set in samples, and optimal tunneling control parameters are provided; and finally, after the optimal tunneling control parameters are compared with related specification requirements, feedback is conducted to a TBM console in time, and TBM tunneling parameters are adjusted. Optimization provided by the invention can be applied to TBM construction, rock slag information is predicted in advance, the tunneling parameters are dynamically adjusted, intelligent prediction of the TBM rock breaking efficiency is achieved, and the method has important significance in safe and efficient construction of tunnels.

Description

technical field [0001] The invention relates to the technical field of tunnel excavation, in particular to a TBM excavation optimization method based on the physical characteristics of rock slag. Background technique [0002] With the continuous development of underground space, the difficulty of excavation and the level of mechanization of tunnel engineering are gradually increasing, and the full-section tunnel boring machine (Tunnel Boring Machine, TBM) has been rapidly developed and applied. The traditional drilling and blasting method has poor construction safety and complicated construction procedures. In contrast, TBM has the following advantages: ① It improves the working conditions of the operators in the cave and ensures the safety of the construction; ② The tunneling speed is 3 times faster than that of the traditional drilling and blasting method. -10 times, and can realize continuous excavation; ③The overall tunnel forming effect is good, and the assembly integra...

AI Technical Summary

Problems solved by technology

In the actual construction progress, due to the heterogeneity and anisotropy of the rock mass on the excavation surface, when the stratum conditions change, it will have a great impact on the TBM excavation process. If the TBM is not adjusted in time according to the current rock state of the stratum The main tunneling control parameters will lead to adverse consequences such as reduced TBM tunneling efficiency, serious hob wear, and equipment jams.

[0004] Regarding the hidden dangers in the construction process, from the perspective of existing testing techniques and prediction methods, there are still some deficiencies that can be optimized: ①About rock slag physics The characteristic test technology is relatively simple. Usually, an industrial camera is set up above the slag belt to collect image information, and combined with the traditional sieve analysis method to judge the particle gradation of the rock slag. The geometric parameters and physical parameters of the rock slag obtained in the test limited and time-consuming, it is impossible to provide timely feedback on the TBM dynamic excavation process; ② Regarding the research content of the algorithm to predict the TBM excavation parameters, in the intelligent prediction and optimization decision-making methods, usually only a single type of parameter is selected as the optimization method Indicators, lack of joint consideration of TBM tunneling parameters and rock residue parameters, the accuracy of the prediction results needs to be improved

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