Method for estimating tunnel surrounding rock displacement by neural network

Abstract

The invention discloses a method for forecasting the displacement of surrounding rocks of a tunnel by utilizing a neural network, which comprises the following steps: an appropriate neural network model is selected, a training sample of the displacement data of the surrounding rocks is input, training is carried out to the neural network , the neural network model with the precision which meets the requirements is obtained, the forecast of the displacement of the surrounding rocks is further carried out by utilizing the trained neural network, the neural network calculates and outputs the forecasted displacement of the surrounding rocks within the following 3 to 5 days of the construction time according to the input measuring point input vector, thereby realizing pre-warning of the displacement of the surrounding rocks. The method utilizes the credible monitoring data in the actual construction, considers the geological features and the related influencing factors of the construction region and carries out the forecast of the deformation and the internal force, etc., of the rocks in the next stage by the feedback analysis of the neural network, thereby guiding the construction, optimizing the construction parameters and reasonably arranging the working procedure.

Description

technical field [0001] The invention relates to a method for predicting the displacement of the surrounding rock of a soft rock tunnel, in particular to a method for predicting the displacement of the surrounding rock of the tunnel by using a neural network. Background technique [0002] my country is in an important period of social and economic development, and infrastructure construction has always played a pivotal role in the national economic structure. The rapid development of economy and society has put forward new and higher requirements for the development of expressways in our country. my country is a mountainous country, especially in many areas in the south and the central and western regions with high mountains and ravines, and its terrain, geology, hydrology, and climate conditions are very complicated. However, due to the high technical requirements of expressways, tunnels have become an inevitable choice to overcome the influence of terrain height difference...

AI Technical Summary

Problems solved by technology

[0005] At present, in the construction of many large-section tunnels in China, either the traditional step method is used to "take risks", which has great construction risks; The blindness will also lead to the emergence of construction risks

Even in the current information-based construction methods, the prediction methods used are time series method and dynamic equation algorithm, which are established mathematical models to predict the displacement of surrounding rock, and the tunnel engineering itself is not considered in the modeling process Some of the characteristics and influencing factors are only predicted by pure mathematics. The error between the predicted results and the measured results is relatively large, resulting in frequent accidents.

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