Frequent deformation and
collapse are common challenges during tunnel construction. However, existing
monitoring methods face issues such as discontinuity, delays, incomplete data,
poor feedback, and low automation. To address these problems and improve safety
in tunnel construction, a new automated, real-time, continuous, large-scale, and three-dimensional monitoring technology has been developed. This
technology leverages advanced wireless sensing equipment and lidar-based edge data processing devices, designed specifically for high-protection tunnel environments. By employing an efficient
transmission strategy, it collects real-time three-dimensional point cloud data of the tunnel′s
construction profile. The system standardizes measurement values across the
entire cross-section of the surrounding rock, clusters
the data into three-dimensional groups, removes
unconnected noise points, and automatically eliminates interference factors
based on statistical analysis of surrounding rock thickness data. This approach
addresses the challenges of difficult wireless transmission and the high
computational demands arising from disordered point cloud data in complex
tunnel environments. The technology ensures high precision, interference-resistant three-dimensional positioning of
deformed areas, enabling early detection and timely warnings to prevent
significant accidents. Applications of the system include simulation
deformation testing, block identification, regional deformation analysis, and
other engineering cases. For instance, the system can automatically detect
deformations and block removals larger than 0.5 m2 and
thicker than 2 cm. Results demonstrate that the technology provides accurate,
reliable, and visually intuitive monitoring of tunnel face deformations.
AN Zheli
,
WANG Yanping
,
MA Weibin
,
WANG Yong
,
LI Yao
,
PENG Yang
. Safety Monitoring
Technology for Tunnel Construction Based on Lidar[J]. Tunnel Construction, 2024
, 44(12)
: 2393
-2402
.
DOI: 10.3973/j.issn.2096-4498.2024.12.009
