Tunnel damage prediction method based on tunnel deformation monitoring

Abstract

The technical problem to be solved by the present invention is to provide a tunnel damage prediction method based on tunnel deformation monitoring. The method includes the following steps: arranging distributed fixed-point optical cables in the monitoring area of ​​the tunnel to form several unit areas for monitoring deformation; The grid unit corresponding to the tunnel unit area is established in the network, the distributed fixed-point optical cable monitoring data corresponding to the grid unit is collected, and the safety threshold of the grid unit monitoring data is set; when the monitoring data of the grid unit exceeds the safety threshold, the surrounding Correlate the monitoring data of the grid unit, analyze the change rate of the historical monitoring data of the associated grid unit, determine whether there is an abnormal change, and predict the damage of the tunnel. Using this method can significantly save the amount of analysis and computation of monitoring data, perform finer monitoring in a more detailed and targeted manner, more accurately determine the type of tunnel damage, and predict subsequent changes in the tunnel damage area.

Description

technical field [0001] The invention relates to the technical field of measuring and monitoring tunnel deformation through optical strain principle, in particular to a tunnel damage prediction method based on tunnel deformation monitoring. Background technique [0002] During the construction and operation of tunnels, especially highway tunnels, the tunnel lining may be cracked and deformed due to geological activities in the area, groundwater activities or construction defects of the secondary lining concrete. and other risk events, which seriously affect the safety of vehicle traffic in the tunnel. In the initial stage of tunnel lining cracking and deformation, timely identification of its deformation or real-time monitoring of its deformation development trend, and early warning before risk events occur, are of great significance to the improvement of highway tunnel management and the safety of vehicle traffic. [0003] At present, the structural monitoring of highway tu...

AI Technical Summary

Problems solved by technology

[0007] (1) It is difficult to monitor the cracking and deformation of the tunnel lining in a targeted manner;

[0008] (2) If there are many monitoring points, a large number of sensors need to be installed, the efficiency is low and the system is complicated;

[0009] (3) The obtained monitoring data is affected by many factors, and the data analysis is difficult;

[0010] (4) In terms of data display, since the deformation and cracking of the tunnel lining may only occur in a small area, or may occur in a section of the tunnel, or even as a whole, this type of monitoring equipment can only be simply displayed in the form of time-curve or table The monitoring data is displayed in a form, and the monitoring of the cracking and deformation of the tunnel lining cannot be displayed intuitively;

[0011] (5) In terms of tunnel early warning, only single-point analysis can be carried out, and it is difficult to carry out regional analysis, let alone comparative analysis of surrounding areas other than fixed monitoring points, so that effective early warning cannot be carried out

When using distributed fixed-point optical cables to monitor deformation, the conventional method is usually to set a safety threshold and give an alarm when the monitoring data exceeds the safety threshold. However, when this method is applied to tunnel monitoring, it can only simply determine whether damage has occurred, and it is difficult Judging the type of damage makes it more difficult to judge and predict subsequent changes in tunnel damage

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