不同工况下的TBM掘进性能预测方法

Prediction Methods of TBM Tunneling Performance Under Different Working Conditions

隧道掘进机(Tunnel Boring Machine,TBM)的掘进速度经常被用于掘进性能评价和工期成本预测,但大多数掘进速度预测模型是基于单一特定工程得出的,致使模型的普适性差。另外,在勘察规划阶段,预测工期时,刀盘转速的选择依赖人工经验,缺少理论指导。所以,研究了基于多个不同直径和不同围岩的TBM工程数据,统计分析了刀盘转速的分布规律及现场贯入度指数(Field Penetration Index,FPI)与地质参数和贯入度(Penetration,P)的相互关系。结果表明:FPI与地质参数和P显著相关。地质参数与掘进参数是影响掘进速度的主要因素。基于此,建立了FPI预测模型、P预测模型和刀盘转速选择的计算模型,进而得出了掘进速度预测模型。该模型的准确性和可靠性经新疆YE(YinEr)工程的现场验证分析,平均预测误差为15.15%,效果良好,能够为勘察规划阶段工期成本预测提供理论支撑。

The penetration rate(PR)of Tunnel Boring Machine(TBM)is often used to evaluate the tunneling performance and predict time cost.But most PR prediction models are based on a single specific project,resulting in poor universality of the models.In addition,the selection of cutterhead speed in the prediction of construction period in the survey and planning stage depends on manual experience and lacks theoretical guidance.Therefore,based on several TBM engineering data of different surrounding rocks and different diameters,this paper statistically analyzes the distribution law of cutterhead speed and the relationship between Field Penetration Index(FPI)and geological parameters and Penetration(P).The results show that FPI is significantly related to geological parameters and P.Geological parameters and tunneling parameters are the main factors affecting the PR.Based on this,the FPI prediction model,P prediction model and the calculation model of cutterhead speed are established,and then the prediction model of PR is obtained.The accuracy and reliability of this model have been verified and analyzed by the YinEr(YE)project in Xinjiang,and the average prediction error is 15.15%,which has a good effect and can provide theoretical support for project time cost prediction in the survey and planning stage.