Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 535-551 |
| Number of pages | 17 |
| Journal | Acta Geotechnica |
| Volume | 18 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2023 |
| Externally published | Yes |
Keywords
- Fuzzy C-means
- Geological characteristics
- Identification and cluster
- K-means ++
- Membership
- Shield tunnel
- Silhouette coefficient
Fingerprint
Dive into the research topics of 'Identification of geological characteristics from construction parameters during shield tunnelling'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver