Shield tunneling position and pose intelligent prediction method and system based on hybrid depth learning

Abstract

The invention discloses a shield tunneling position and pose intelligent prediction method and system based on hybrid depth learning, and belongs to the field of construction of subway shields. According to the method, a prediction control principle and an artificial intelligence technology are adopted based on a shield misalignment mechanism, positions and poses in a shield tunneling stage are predicted according to a built hybrid depth learning model WCNN-LSTM, an adjustment strategy of the shield positions and poses is formulated, and pre-adjustment and prior control of operation parametersare realized so that the problem of shield misalignment is improved. The method is used for performing intelligent prediction of subsequent change of the positions and poses in a tunneling process ofa shield machine, supports a shield machine driver to adjust the shield positions and poses in advance, solves the snake-shaped motion difficulty of the shield machine, alleviates the modulation control hysteretic effect of the shield positions and poses, realizes accurate control of a tunneling axis of the shield machine, can effective promote formation quality of the tunnels and has higher engineering practical values.

Description

technical field [0001] The invention belongs to the field of subway shield construction, and more specifically relates to a method and system for intelligently predicting the position and posture of shield tunneling based on hybrid deep learning. Background technique [0002] The shield tunneling method is the main construction method for constructing subway projects. During the construction process of the shield tunneling method, there are mainly three problems: instability, failure, and misalignment. Among them, the misalignment of the subway shield will have an all-round impact on the construction quality, progress, cost and safety of the project. The misalignment is mainly manifested as the misalignment of the position and posture of the shield machine, that is, the excavation direction of the shield machine deviates from the design axis, resulting in tunnel penetration errors and poor segment assembly quality. On the one hand, the inaccurate position and posture of th...

AI Technical Summary

Problems solved by technology

However, the control process can only exert influence and produce effects after the controlled quantity deviates from the set value and produces deviations, which belongs to the post-event control method in quality management.

In addition, the shortcoming of post-control delay will lead to the formation of a "serpentine" track in shield tunneling, and the control ...

Images