Research On Mechanism And Intelligent Prediction Of Shield Tunneling Misalignment Based On Deep Learning

With the expansion of China's Metropolis and the increase of population,large-scale metro construction puts higher requirements on the forming quality of shield tunnels.The shield tunneling misalignment(STM),which means the movement trajectory of shield deviates from the design axis,is one of the key factors affecting the tunnel quality.The control of attitude and position of shield and segment erection are the two main reasons for the STM.In shield tunneling,the shield driver must constantly adjust the attitude and position of the shield machine along the design axis by relying on his own experience.When the segments are assembled,the posture of ring must be optimized according to the shield attitude and the design axis to correct the shield deviation.However,due to the variable geological space environment and complex shield machine operation,the shield attitude and position adjustment strategy based on manual experience and post-control method has problems of lack of control lag,accuracy and stability.In this thesis,the mechanism of STM is taken as the research object,which mainly includes the following work:Firstly,this thesis summarizes the influencing factors of shield attitude and establishes the shield motion mechanics model.Based on this model,it analyzes the mechanism of STM and the existing control strategy of attitude and position of shield machine.From the two aspects of shield tunneling attitude prediction and the segment erection optimization,the adjustment strategy of shield attitude and position based on pre-control is proposed.Then,for the prediction of attitude and position of shield machine,a deep learning-based hybrid model integrated wavelet transform,convolutional neural network and long-short-term memory network is established for predicting the attitude and position of shield machine in the future through fedding historical shield operating data.Secondly,according to the principle of segment erection,the optimization algorithm of the segment erection is designed.The algorithm considers the fitting relationship between the the attitude of shield machine,the segment and the design axis,and can automatically calculate the optimal posture of the current ring.Finally,take a metro tunnel as a case study,collect the shield operation data and the segment erction record,and use Python to write the codes for verification.The results show that the prediction model and the optimization algorithm proposed in this thesis can predict the attitude and position of shield and recommend the posture of the segments erection,assist the driver to control the attitude and position,and improve the quality of the tunnel lining.