Study On Tunneling Parameter Optimization Method Of Open TBM Under Specific Surrounding Rock

With the increasing demand of railway and water diversion tunnel projects,the TBM industry has expanded rapidly in recent years,and the construction technology of TBM in China has gradually matured,but there are still many shortcomings.Taking the optimization of TBM tunneling parameters as an example,the research in this field is still in the initial stage.Therefore,this paper took a long-distance water diversion project in Xinjiang as the background,and carried out the following research.Research work:(1)On the basis of introducing the simple principle of TBM,the composition,working principle and main parameters of single beam horizontal floating boot TBM equipment is mainly introduced.These main parameters are the quantitative content of this paper.On this basis,the matching of tunneling parameters and geological parameters is carried out,and the optimum value of tunneling parameters is obtained.(2)On the basis of stability classification of surrounding rock in Engineering Rock Mass Classification Standard,the main geological factors(uniaxial compressive strength,integrity and wear resistance)which affect the tunneling performance of roadheader are further divided into A(excellent),B(good),C(bad)according to the construction conditions of TBM.The adaptability of the optimized tunneling parameters is improved by subdividing the surrounding rock.(3)By using SPSS software to analyze the historical data of tunneling,the correlation between tunneling speed and tunneling parameters is analyzed,and then the model linear analysis is carried out to obtain the estimated values of parameters of each tunneling parameter,and then the functional relationship between tunneling speed and tunneling parameters is obtained.With this functional relationship,the tunneling time can be predicted by tunneling parameters.(4)The regression prediction model of non-linear support vector machine is established by SPSS Modeler software,and the historical data of tunneling are predicted by the model.The difference between the predicted results and the measured results is within 10%,which proves the reliability of the prediction model.Finally,the optimal combination tunneling parameters of all kinds of surrounding rocks are optimized by using the Minimum Decision Particle Swarm Optimization(PSO)algorithm of tunneling specific energy in MATLAB software.By substituting the obtained parameters into the linear model of tunneling speed,it can be concluded that the tunneling speed is relatively large when the specific energy of tunneling is minimum,which meets the construction requirements of high speed and low energy consumption.