Identification of geological characteristics from construction parameters during shield tunnelling

This paper proposes a framework to identify geological characteristics (GC) based on borehole data and operational data during shield tunnelling using a fuzzy C-means algorithm. The proposed fuzzy C-means model was established by integrating the K-means ++ algorithm into the fuzzy set theory. The identified factors for GC include advance rate, cutterhead rotation speed, thrust, cutterhead torque, penetration rate, torque penetration index, field penetration index, and specific energy. Principal component analysis was employed to reduce the dimensions of these factors. The first six principal components were employed to analyse the GC and establish the input data set in the fuzzy C-means model. The types of GC were determined based on elbow method, silhouette coefficient, fuzzy partition coefficient and the geological profile from borehole data. The proposed approach was validated by a case of Guangzhou intercity tunnel construction. The results present that the proposed fuzzy C-means model can effectively determine GC and provide membership to reveal the proportion of hard rock.

Automated summary

This paper proposes a framework to identify geological characteristics using a fuzzy C-means algorithm based on borehole data and operational data. The identified factors are significantly reduced by principal component analysis, and the types of geological characteristics are determined using the fuzzy C-means model.