基于PCA-GMM模型的盾构施工地层特征智能识别研究
Intelligent Identification of Stratum Characteristics During Shield Tunnelling Based on PCA-GMM Model
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摘要: 盾构开挖面前方地质进行实时识别有助于设置适当的盾构施工参数,减少盾构施工事故、保证隧道施工安全,从而确保隧道质量.传统的地质超前预报方法需要附加测试设备,占用施工空间和时间.本文提出一种基于主成分分析-高斯混合模型(PCA-GMM)的聚类分析方法,用盾构施工参数来识别地层特征.依托珠三角城际铁路三灶隧道工程,运用PCA-GMM模型探索盾构掘进参数与地层特征的联系,并用轮廓系数对聚类结果进行地层特征识别.PCA-GMM聚类模型确定盾构掘进参数与地层特征的联系基于力学相关性原理,因此能够很好地区分力学性质有较大差距的地层,将粉砂地层从淤泥质类土层(粉土层、黏土层)中区别开来,但难于区分力学性质差距不大的地层,如淤泥质粉土层与淤泥质黏土层.Abstract: Real-time identification of geological conditions ahead the tunnel excavation face during shield tunnelling can help to set appropriate operational parameters,which guarantees tunnel quality via avoiding construction accidents and ensuring construction safety.The traditional geological prediction methods require additional testing equipment,construction space and time.This paper proposed an identification method based on PCA-GMM (Principal Component Analysis-Gaussian Mixture Model) that identifies geological conditions by using shield tunnelling parameters.The research was conducted via relying on Zhuhai Sanzao tunnelling project.The relationship between tunnelling parameters and geological features was explored using the proposed PCA-GMM model and then geological characteristics was identified based the clustering results using silhouette coefficients.Since this identification from PCA-GMM model is based on the principle of mechanical correlation between tunnelling parameters and geological features,PCA-GMM model can identify soil layer with large mechanical property gaps.The results indicate that PCA-GMM model can identify silty sand layer from silty layer.For those layers with less difference of mechanical property,such as clayey silt layer and the silty clay layer,the identified result is not satisfactory.Even though,the proposed identification method can guide the adjustment of shield operational parameter.