Abstract
Ground loss due to earth pressure balance shield tunneling eventually leads to a surface settlement which can be an issue of great concern. However, the existing machine learning methods ignore the continuous and dynamic nature of EPB shield tunneling. In this work, a multivariate time-series (MTS) model for ground loss is proposed based on an analysis of factors and processes related to ground loss combined with the characteristics of original time-series data involving multiple parameters recorded by EPB shield machines in real time. A method of visualizing MTS features based on a residual network and multichannel fully convolutional neural network is also presented. The validity of the proposed ground-loss model is verified via calculation and comparison with 13 EPB shield construction projects carried out in typical urban areas featuring soft soil. Thermal maps are thus obtained to visualize the classification contributions, which provide a visual basis for feature analysis.
Highlights
Earth pressure balance (EPB) shield tunneling has become one of the main methods used to construct urban metro lines. is is because of its high construction efficiency, wide range of applications, and limited impact on the ground surface and associated human activity
Visualization of multivariate time-series (MTS) Features. e residual networks (ResNets) and multichannel fully convolutional neural network (MCFCN) methods are used to classify the MTS model for the ground loss and calculate the various F1 scores, giving the results shown in Table 5. e calculation data and code of this case can be referred to the appendix of this paper
Ground loss as a result of EPB shield tunneling is a dynamic and continuous process. is paper puts forward an MTS model for ground loss based on an analysis of the most relevant factors and processes associated with ground loss combined with the characteristics of the time series data for various parameters recorded by the shield machine in real time
Summary
Earth pressure balance (EPB) shield tunneling has become one of the main methods used to construct urban metro lines. is is because of its high construction efficiency, wide range of applications, and limited impact on the ground surface and associated human activity. Erefore, the use of a supervised multivariate time series (MTS) model is proposed in this work that is based on an indepth analysis of the continuous and dynamic ground loss due to EPB shield tunneling combined with the time series characteristics of the original data. E new method allows feature visualization to be realized along the time axis and along parameter directions using Grad-CAM It learns which features are related to ground loss by highlighting subsequences that contribute most to the classification. An MTS model for ground loss is constructed in this work based on 13 EPB shield tunneling projects carried out in soft soil typically encountered in urban parts of Changzhou in China.
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