To explore the coupling relationship between key
geological parameters of rock mass and the working parameters of tunnel boring
machines (TBMs), a multidimensional association algorithm is
developed to establish a coupling model of TBM based on the staticmapping relationship of rock parameters. The Kmeans clustering method is used to determine the coupling
relationship between geological and rock conditions, as well as the tunneling
speed during the service process. After class coding, seven main parameters,
including tensile strength, compressive strength, peak slope index, weak face
spacing, tunneling speed, alpha angle, and rock type, are selected to analyze
and summarize the rules of shield tunneling. Compared with the decision tree,
the rules are more abundant and intuitive, making them suitable for early
decisions. As an effective datamining method, the
association algorithm can provide a theoretical reference for intelligent
tunneling.
QIAO Jinli
,
XU Yuanhao
,
LIU Jianqin
,
HU Jianbang
. Mutual Feedback Data-Mining
Method for Rock-Machinery Information Perception in Tunnel Excavation Based on Association Rules[J]. Tunnel Construction, 2021
, 41(8)
: 1324
.
DOI: 10.3973/j.issn.2096-4498.2021.08.007
