A Long-term Settlement Deformation-Time Prediction Method for Tunnels

Abstract

A method for predicting long-term settlement deformation-time of a tunnel, comprising the following steps: Step 1: Select a monitoring point, and preset an automatic monitoring device for settlement deformation; Step 2: Prediction system initialization setting; Step 3: The prediction system performs automatic monitoring of settlement deformation; Step 4: The controller CPU analyzes and processes the monitoring data; Step 5: The cloud server establishes the actual settlement deformation curve and generates the predicted settlement deformation curve. The method for predicting long-term settlement deformation-time of tunnels of the present invention can monitor a tunnel with an ultra-long linear structure composed of multiple structural segments, has high accuracy of measurement results, and has a wide range of applications.

Description

technical field [0001] The invention relates to the technical field of tunnel detection equipment, in particular to a method for predicting tunnel long-term settlement deformation-time. Background technique [0002] In existing life, due to the increase of traffic pressure, excavating tunnels and constructing urban subways have become an important way to relieve traffic pressure. The concealment of tunnels and urban subways is relatively large, and the geological conditions during construction are complex, and the potential accident risks cannot be predicted. , and for the sudden accidents of tunnels and subways, the main manifestations are the collapse of the vault and the water and mud on the side wall. There are many methods to control the settlement of the tunnel vault. At present, in tunnel construction, the problem of tunnel roof subsidence is common. , the subsidence of the vault in the tunnel may cause major safety risks or accidents in the tunnel and surrounding con...

AI Technical Summary

Problems solved by technology

[0002] In existing life, due to the increase of traffic pressure, excavating tunnels and constructing urban subways have become an important way to relieve traffic pressure. The concealment of tunnels and urban subways is relatively large, and the geological conditions during construction are complex, and the potential accident risks cannot be predicted. , and for the sudden accidents of tunnels and subways, the main manifestations are the collapse of the vault and the water and mud on the side wall. There are many methods to control the settlement of the tunnel vault. At present, in tunnel construction, the problem of tunnel roof subsidence is common. , the subsidence of the vault in the tunnel may cause major safety risks or accidents in the tunnel and surrounding construction facilities

At present, the method of detecting settlement of tunnels mainly adopts manual detection of total station. However, the detection of total station requires manual point-by-point detection, which is time-consuming and labor-intensive, and cannot be detected in real time. At the same time, the detection accuracy is related to the operation of the staff. , resulting in larger monitoring errors and lower monitoring accuracy

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