典型文献
Realtime prediction of hard rock TBM advance rate using temporal convolutional network(TCN)with tunnel construction big data
文献摘要：
Real-time dynamic adjustment of the tunnel bore machine(TBM)advance rate according to the rock-machine interaction parameters is of great significance to the adaptability of TBM and its efficiency in construction.This paper proposes a real-time predictive model of TBM advance rate using the temporal convolutional network(TCN),based on TBM construction big data.The prediction model was built using an experimental database,containing 235 data sets,established from the construction data from the Jilin Water-Diversion Tunnel Project in China.The TBM operating parameters,including total thrust,cutterhead rotation,cutterhead torque and penetration rate,are selected as the input parameters of the model.The TCN model is found outperforming the recurrent neural network(RNN)and long short-term memory(LSTM)model in predicting the TBM advance rate with much smaller values of mean absolute percentage error than the latter two.The penetration rate and cutterhead torque of the current moment have significant influence on the TBM advance rate of the next moment.On the contrary,the influence of the cutterhead rotation and total thrust is moderate.The work provides a new concept of real-time prediction of the TBM performance for highly efficient tunnel construction.
文献关键词：
中图分类号：
作者姓名：
Zaobao LIU;Yongchen WANG;Long LI;Xingli FANG;Junze WANG
作者机构：
Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines,Institute of Deep Engineering and Intelligent Technology,Northeastern University,Shenyang 110819,China;State Key Laboratory of Hydraulics and Mountain River Engineering,Sichuan University,Chengdu 610065,China;Software College,Northeastern University,Shenyang 110819,China
文献出处：
引用格式：
[1]Zaobao LIU;Yongchen WANG;Long LI;Xingli FANG;Junze WANG-.Realtime prediction of hard rock TBM advance rate using temporal convolutional network(TCN)with tunnel construction big data)[J].结构与土木工程前沿,2022(04):401-413
A类：
cutterhead
B类：
Realtime,prediction,hard,rock,TBM,advance,using,temporal,convolutional,network,TCN,tunnel,construction,big,dynamic,adjustment,bore,machine,according,interaction,parameters,great,significance,adaptability,its,efficiency,This,paper,proposes,real,predictive,model,was,built,experimental,database,containing,sets,established,from,Jilin,Water,Diversion,Tunnel,Project,China,operating,including,total,thrust,rotation,torque,penetration,are,selected,input,found,outperforming,recurrent,neural,RNN,long,short,term,memory,predicting,much,smaller,values,mean,absolute,percentage,error,than,latter,moment,have,significant,influence,next,On,contrary,moderate,provides,new,concept,performance,highly,efficient
AB值：
0.483462
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