Large-diameter single-tube double-track shield tunnels with middle partition walls face significant
challenges such as difficult left- and right-line laser scanning point cloud data registration and low convergent
deformation measurement accuracy. To address these challenges, a point-cloud data positioning algorithm that automatically identifies the
circumferential joints of the shield tunnel segments is constructed. In
addition, a full-local dynamic iterative point-cloud automatic registration method for shield tunnel segment rings
is proposed. This method minimizes the deviation of tunnel structure feature
points and distances, thus achieving precise fusion of the full-loop point cloud data of the corresponding left and right line
segments of the tunnel. The overall horizontal convergent deformation of the
shield tunnel with middle partition walls is determined by applying noise
reduction and distance least squares elliptic fitting to the fused full-loop point cloud data of the segments. Integrating a point cloud
data fusion algorithm facilitates the development of a rail transit tunnel
structure inspection vehicle TDD-SD equipped with a
three-dimensional laser scanner and supporting data
processing software. Finally, engineering pilot applications and manual
comparison verification are performed. The results demonstrate that at a
measurement speed of 20 km/h, the maximum absolute deviation between the mobile
measurement of the tunnel horizontal convergent deformation detection vehicle
and the manual measurement is 2.0 mm. This represents a ratio of 0.16‰ to the outer diameter of the tunnel, demonstrating good consistency
between the two measuring methods. The mobile measurement accuracy meets the
industry standards for evaluating the impact of segment convergent deformation
in large-diameter shield tunnels. The feasibility of
the proposed point-cloud data fusion algorithm for the
left and right line segments is also validated.
WANG Jiaye
,
LIU Xingen
,
LIU Xuezeng
,
PANG Gaozhao
. Mobile Measurement and
Point Cloud Data Fusion Method for Convergent Deformation of Shield Tunnels With Middle Partition Walls[J]. Tunnel Construction, 2025
, 45(6)
: 1202
-1209
.
DOI: 10.3973/j.issn.2096-4498.2025.06.015
