Identifying the geological
conditions ahead of the cutterhead during slurry balance shield tunneling in
real time is challenging. To address this, a case study is conducted on the
water supply pipeline and road improvement project at Zhijiang road in Hangzhou,
China. Tri-axis accelerometers are
installed on the shield′s main drive to collect
vibration signals. The correlation between these signals and the five typical
stratum profiles is examined. The original signals are divided into several
times segments, with one rotation of the cutterhead as a cycle, thereby
constructing a feature set. Finally, a method combining principal component
analysis (PCA) and support vector machine (SVM) is proposed to identify
geological types in real time ahead of the cutterhead. The results reveal the
following: (1) Geological types considerably affect vibration signals, with the
highest vibration amplitude along the Z-axis
(tunneling direction). The root mean square acceleration across the three axes
shows distinct clustering characteristics in cutterhead torque and penetration
parameters under different stratum conditions. (2) The PCA-SVM method achieves an identification accuracy of 97.98% for these
five typical stratum types along the project. The stratum identification
accuracy using time and frequency domain features extracted by time periods as
input parameters is 23.36% higher than that using the original acceleration
signals as input parameters. (3) The PCA algorithm effectively reduces data
volume, shortens model training time by approximately 29.2%, and improves
identification accuracy by approximately 0.3%.
WANG Haitao
,
ZHOU Chun
,
SUN Jiuchun
,
WANG Yue
. Stratum Identification in
Shield Tunneling Based on Vibration Signals[J]. Tunnel Construction, 2024
, 44(11)
: 2202
-2212
.
DOI: 10.3973/j.issn.2096-4498.2024.11.010
