郑州大学学报（工学版）2024，Vol.45Issue(1)：107-113,7.DOI:10.13705/j.issn.1671-6833.2023.04.003
软土地层盾构掘进参数分析及掘进速度预测
Analysis of Boring Parameters of Shield in Soft Soil Strata and Prediction of Driving Speed
摘要
Abstract
Taking the tunnel project from Fengsha Station to Creative Park Station of Foshan Metro Line 3 as back-ground,the inherent variation tendency of boring parameters of shield when the EPB shield tunnel crossed the soft soil strata was analyzed in detail through the on-site measured data,and the different prediction models of driving speed were built.Firstly,the shield tunneling parameters were analyzed by mathematical statistics,and the distri-bution of each tunneling parameter was tested.Secondly,the Pearson correlation analysis was performed to find out the variation law between the parameters with strong linear correlation.Then using the feature selection algorithm based on mutual information,the parameter variables with high nonlinear correlation with the driving speed were screened.Finally,the random forest regression prediction and the BP neural network prediction model based on ge-netic algorithm optimization were established respectively to predict the driving speed.The research results showed that in shield tunnel projects in soft formations,lower cutterhead speed,cutterhead torque,higher tunneling speed,penetration,total shield thrust and soil silo pressure were usually used.The parameters such as the excavation speed passed the normality test using the K-S test method.There was a strong correlation between the speed of ex-cavation and the degree of penetration.The average absolute error,root mean square error and goodness of fit of the random forest regression prediction model in the test set were 4.055,5.038 and 0.871,respectively,while the op-timization of the BP neural network prediction model based on genetic algorithm was 0.822,1.244 and 0.991,re-spectively.关键词
土压平衡盾构/掘进参数/正态性检验/互信息/随机森林/遗传算法/BP神经网络Key words
earth pressure balance shield/boring parameters/normality test/mutual information/random forest/genetic algorithm/BP neural network分类
交通工程引用本文复制引用
裴浩东,叶社保,杨平,吴永哲..软土地层盾构掘进参数分析及掘进速度预测[J].郑州大学学报（工学版）,2024,45(1):107-113,7.基金项目
国家自然科学基金资助项目(51978339) （51978339）
