Method of Predicting Tunnel Boring Machine (TBM) Jamming Based on Deep Neural Network and Numerical Simulation and System Thereof

Abstract

A method of predicting tunnel boring machine (TBM) jamming based on deep neural network and numerical simulation and a system thereof are provided, belonging to the technical field of tunnel boring. The method including the following steps: constructing a jamming numerical sample library by using s numerical simulation technology; establishing a jamming prediction model based on the jamming numerical sample library by using a Convolutional Neural Network (CNN) and a Transformer; and implementing real-time monitoring and early warning of TBM jamming by using the jamming prediction model. The present application realizes the real-time monitoring and early warning of TBM jamming, reduces or avoids the jamming phenomenon, and improves the safety and efficiency of TBM construction.

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