During tunnel blasting
construction, the blasting quality is difficult to control. Therefore, a real-time blasting parameter optimization method based on three-dimensional(3D) laser scanning technology and back propagation(BP)
neural network is proposed. This method percepts the over-and under-excavation of tunnel blasting and corrects subsequent drilling and
blasting parameters in real time. The working procedures of field scanning
method, data processing, point cloud extraction, and over- and under-excavation images are constructed. Finally, the BP neural network
model, algorithm, and model parameters are established. The verification test
results show that: (1) It is feasible to apply 3D laser scanning technology to
the over- and under-excavation
quality perception of tunnel blasting, which is in good agreement with the
manual measurement results, and has the advantages of fast, real-time, and accurate. (2) The 3D laser scanning method can accurately
evaluate the profile line of the tunnel after blasting. After obtaining precise
data on blasting over- and under-excavation, the model training can be completed through sample
learning to infer reasonable blasting parameters. The improved optimization
scheme reduces the average over excavation by 54.8%.
XIAO Qinghua, YUAN Hao, XIA Jinxuan, OU Xiaoqiang, ZANG Xiwei, ZHONG Dechao, LIU Zhiqiang
. Tunnel Blasting Parameters
Optimization Design Method Based on Three-Dimensional Laser Sensing[J]. Tunnel Construction, 2024
, 44(S1)
: 8
-15
.
DOI: 10.3973/j.issn.2096-4498.2024.S1.002
