The strain characteristics
and crack identification of large-scale
prefabricated components during the assembly process in underground metro
stations are crucial. Focusing on a prefabricated metro station project, where
the distributed fiber optic system (DFOS) is utilized to monitor the strain
distribution during the assembly of large-scale
components, a principal component analysis-hierarchical
clustering (PCA-HC) model is proposed, integrating
multiple strain distribution parameters to identify strain distribution
features in crack-prone zones. The model′s effectiveness is validated through field tests on slab assembly
crack detection. Findings are as follows: (1) The strain features obtained from
DFOS indicate average strain growth rates of 105.42% in tension zones and
110.27% in compression zones during roof assembly. The roof assembly process
has the most significant effect on the base slab deformation. (2) DFOS clearly
reflects the abnormal strain signals at the crack locations. Cracks appear at
the contact area between the base slab and the supporting structure during
assembly. Increasing the contact area between the support and the assembled
components is recommended to mitigate the stress/strain concentration caused by
assembly construction. (3) The PCA-HC model effectively
identifies potential crack features through dimensionality reduction, feature
extraction, and hierarchical clustering, enabling automated crack recognition
and classification of large-scale prefabricated
components, providing a methodological basis for the safe construction of large-scale prefabricated structures in metro stations.
HONG Chengyu
,
LI Hong
,
RAO Wei
,
CHEN Xiangsheng
,
LEI Zhen
. Fiber Optics Monitoring and
Crack Identification of Large-Scale Components in Prefabricated Metro Stations[J]. Tunnel Construction, 2025
, 45(3)
: 499
-510
.
DOI: 10.3973/j.issn.2096-4498.2025.03.005
