基于K-means聚类算法的盾构掘进参数设定方法研究

Research on Parameter Setting Method of Shield Tunneling Based on K-means Clustering Algorithm

盾构掘进参数的合理设定是保障盾构隧道施工质量和安全的基础。为实现掘进参数的准确设定,基于典型工程类比设定理论,将K-means聚类算法与经验公式设定法相结合,提出盾构掘进参数类比设定法(SAPAS),实现典型工程工况掘进参数的自动提取和匹配。与传统的经验公式法相比,SAPAS改善了经验公式的实际使用效果,能够更准确地进行参数设定,有利于提高施工质量和安全。通过在上海轨道交通的部分工程中进行实践,取得了良好的施工效果。

The rational setting of shield tunneling parameters is the basis guarantee to the construction quality and safety of shield tunnel.In order to realize the accurate setting of tunneling parameters,the K-means clustering algorithm is combined with the empirical formula setting method based on the theory of typical engineering analogy setting,and the shield advancing parameters analog setting method(SAPAS)is proposed to realize automatic extraction and matching of tunneling parameters under typical engineering conditions.Comparing with the traditional empirical formula method,SAPAS improves the practical application effect of empirical formula,and can set parameters more accurately,and it is beneficial to improve the construction quality and safety.By adopting the method in some engineering practices of Shanghai rail transit,good results have been obtained.