CN114993203B - Tunnel deformation monitoring method based on primary support unequal thickness - Google Patents

Abstract

The invention discloses a tunnel deformation monitoring method based on unequal thickness of primary branches, and relates to the technical field of tunnel deformation monitoring. After scanning and acquiring the surface data of the surrounding rock of the tunnel and the primary branch through non-contact measurement three-dimensional laser scanning technology, a tunnel primary branch model containing the primary branch thickness data can be established. According to the different thickness of the primary branch, the tunnel can be Marking abnormal points enables targeted monitoring during later tunnel monitoring, effectively saving the workload of later monitoring and thus speeding up the acquisition of monitoring data. At the same time, the relationship between the thickness of the primary support and tunnel deformation can be easily studied based on the monitoring data and the tunnel primary support model. By considering the uneven initial support thickness caused by over-excavation and under-excavation of the surrounding rock, it not only conforms to the actual engineering situation, but also can effectively monitor the local stress concentration caused by over-excavation and the insufficient initial support thickness caused by under-excavation. Security risks.

Description

A tunnel deformation monitoring method based on unequal thickness of primary branches

Technical field

The invention relates to the technical field of tunnel deformation monitoring, and specifically relates to a tunnel deformation monitoring method based on unequal thickness of primary branches.

Background technique

Over- and under-excavation of tunnels directly affects the stability of surrounding rock and construction costs of tunnels. However, controlling over- and under-excavation of tunnels has always been one of the most difficult points for on-site technicians to control. During the excavation process, the phenomenon of over-excavation and under-excavation caused by blasting is unavoidable. Too much over-excavation will cause stress concentration problems and affect the stability of the surrounding rock; while under-excavation will result in insufficient initial support thickness, which will affect the stability of the surrounding rock. Hidden risks arise in project quality and safety. However, when monitoring tunnel deformation, the initial support is often considered as equal thickness, which is obviously inconsistent with the actual engineering situation. Therefore, it is of very practical and important engineering significance to monitor the deformation by considering the unequal thickness of the primary support due to the influence of over- and under-excavation.

Traditional tunnel over-under excavation detection and deformation monitoring are mainly based on manual measurement, using equipment such as total stations, section meters and measuring robots to conduct full-section measurements of the tunnel point by point and section by section. This type of method The detection efficiency is low, time-consuming, and requires a lot of manpower and material resources. In addition, the measurement accuracy of traditional detection methods is easily affected by tunnel environmental factors, cannot reflect changes in the overall shape of the tunnel, and cannot meet the actual needs for large-scale detection during tunnel excavation.

Contents of the invention

In view of the above-mentioned shortcomings of the existing technology, the present invention provides a tunnel deformation monitoring method based on unequal thickness of primary branches with non-contact measurement, high data accuracy and fast data acquisition speed.

In order to achieve the above-mentioned object of the invention, the technical solutions adopted by the present invention are:

A tunnel deformation monitoring method based on unequal thickness of primary branches is provided, including the following steps:

S1: Use a laser scanner to scan the surrounding rock of the tunnel to be detected and obtain the surrounding rock point cloud data;

S2: Unify the coordinate axis conversion of the surrounding rock point cloud data to obtain the axis direction of the tunnel to be detected;

S3: Calculate the actual radius of the tunnel according to the axis direction of the tunnel to be detected, and calculate the over- and under-excavation amount of the tunnel to be detected using the actual radius of the tunnel and the theoretical radius of the tunnel;

S4: After the construction of the primary branch of the tunnel to be inspected is completed, the laser scanner is used to scan again to obtain the surface point cloud data of the primary branch of the tunnel;

S5: Establish the tunnel primary support model based on the tunnel primary support surface point cloud data and surrounding rock point cloud data, and mark the thickness abnormal points of the tunnel primary support model through over and under excavation amounts;

S6: After the tunnel is completed, use a laser scanner to scan and detect the corresponding positions of the thickness abnormal points for several periods, and compare the monitoring data of each period to obtain the surface deformation of the tunnel to be detected.

After scanning and acquiring the surface data of the surrounding rock of the tunnel and the primary branch through non-contact measurement three-dimensional laser scanning technology, a tunnel primary branch model containing the primary branch thickness data can be established. According to the different thickness of the primary branch, the tunnel can be Marking abnormal points enables targeted monitoring during later tunnel monitoring, effectively saving the workload of later monitoring and thus speeding up the acquisition of monitoring data. At the same time, the relationship between the thickness of the primary support and tunnel deformation can be easily studied based on the monitoring data and the tunnel primary support model.

Further, in step S2, preprocessing is required before coordinate axis conversion of the surrounding rock point cloud data. Preprocessing of the surrounding rock point cloud data includes one or more of point cloud denoising, point cloud thinning, or point cloud simplification. . Preprocessing point cloud data can remove data noise caused by poor on-site working environment; and can eliminate redundant points in point cloud data without affecting the complete characteristics of the measured subject's point cloud.

Further, in step S2, the coordinate axes of the surrounding rock point cloud data are uniformly converted to the geodetic coordinate axis. The specific methods include the following:

A1: Before the laser scanner scans the tunnel to be detected in step S1, use the total station to position the laser scanner. Record the origin of the total station as the position coordinate in the geodetic coordinate system as (x ₀ , y0 , z ₀ ), and Calculate the x-axis direction vector (x ₁ , y ₁ , z ₁ ) and y-axis direction vector (x ₂ , y ₂ , z ₂ ) of the laser scanner;

A2: Convert the scanning coordinate system of the surrounding rock point cloud data into the geodetic coordinate system: The surrounding rock point cloud data is collected by segmental scanning of the tunnel to be detected by the laser scanner. Record the coordinates of the scanning coordinate system of each section of the surrounding rock point cloud data as: (x _i ', y _i ', z _i '), record the coordinates of the geodetic coordinate system corresponding to the scanning coordinate system of the surrounding rock point cloud data of each section as (x _i , yi, z _i ), and the conversion method is:

Among them, θ is the angle of rotation of the scanning coordinate system around the z-axis, α is the angle of rotation of the scanning coordinate system around the x-axis, γ is the angle of rotation of the scanning coordinate system around the y-axis; T ₁ is the rotation matrix in the z-axis direction; T ₂ is Rotation matrix in x-axis direction; T ₃ is rotation matrix in y-axis direction;

A3: Use the RANSAC algorithm to fit the center coordinates of the surrounding rock point cloud data on the tunnel section, project the center coordinates of any section onto the xoz plane and yoz plane of the geodetic coordinate system, and calculate the center coordinates of all sections The projection points of the coordinates are sorted according to the forward direction of the tunnel;

A4: Use cubic spline interpolation to fit the projection points on the xoz plane and yoz plane of the geodetic coordinate system to obtain two curves respectively located on the xoz plane and yoz plane of the geodetic coordinate system;

A5: Integrate the two curves to obtain the axis direction of the tunnel to be detected.

Further, the integration method of the two curves is:

Take any point (x _q , z _q ) on the curve on the xoz surface, take the point (y _q , z _q ) on the same z coordinate of the curve on the yoz surface, and combine the point (x _q , z _q ) with the point ( y _q , z _q ) are integrated into (x _q , y _q , z _q ), that is, a new curve can be obtained, which is the axis direction of the tunnel to be detected.

Further, the calculation method of the over-under excavation amount of the tunnel to be detected in step S3 is:

Among them, (x _xoy ,y _xoy ) are the outline coordinates of the surrounding rock point cloud data on the tunnel section to be detected, (x _r , y _r ) are the center coordinates of the geodetic coordinate system on the same tunnel section to be detected, r ₀ is the tunnel theory Radius, d is the distance between the surrounding rock point cloud data and the theoretical contour of the tunnel to be detected;

When d>0, it means that the tunnel to be detected is over-excavated in this area, and the over-excavation value is |d|; when d<0, it means that the tunnel to be detected is under-excavated in this area, and the under-excavation value is |d|; When d=0, the tunnel to be detected does not appear to be over- or under-excavated in this area.

Further, the marking method of thickness abnormal points in step S5 is:

The actual thickness T of the primary branch is the surface point cloud data of the tunnel primary branch minus the surrounding rock point cloud data, and t is the design thickness of the primary branch;

When T-t<d<0, mark the area as an abnormal point with ultra-thin thickness;

When d≤T-t<0, mark the area as a thin abnormal point;

When 0<T-t≤d, mark the area as a thick abnormal point;

When 0<d<T-t, the area is marked as an abnormal thickness point;

When T-t=0, this area will not be marked as a thickness abnormal point.

Further, in step S6, the tunnel surface model is established after scanning the corresponding positions of the thickness abnormal points in each period. The tunnel deformation judgment method includes the following:

S61: Divide the tunnel surface model into m segments of length p along the direction of the central axis, 0.01＜p＜0.1m; then divide the tunnel surface model into equal parts along the cross section clockwise from the bottom of the left tunnel side wall with an angle of n segment of a, 0°<a<2°;

At this time, the tunnel surface model is equally divided into m×n unit grids, which are numbered according to the row and column numbers of the unit grids as W _{i, j} , (i=1, 2,...,m; j=1, 2,...,n;);

S62: Project with the center O _i (i=1, 2..., m) of the i-th segment on the central axis of the tunnel as the projection center, and the unit grid W _{i, j} as the projection datum plane. The unit grid The projection range of Wi _,j in the kth tunnel surface point cloud model is Pi _,j,k , (i=1,2,...,m;j=1,2,...,n;k= 1, 2,..., q;); P _{i, j, k} are planar quadrilaterals;

S63: The distance from the projection center O _i to the plane quadrilateral P _{i, j, k} is pi, j, k. Then the projection range of the unit grid W _{i, j} in the tunnel surface model corresponds to the area k+1 relative to the k-th tunnel. The structural deformation is Δ _{i, j, k + 1} = p _{i, j, k + 1} - p _{i, j, k} ;

If Δ _{i, j, k+1} > 0, then the tunnel within the projection range of unit grid W _{i, j} is detected as outward expansion and deformation compared to the previous scan,

If Δ _{i, j, k+1} <0, then the tunnel within the projection range of the unit grid W _{i, j} is detected to be inwardly shrinking and deformed compared to the previous scan;

If Δ _{i, j, k+1} = 0, then the tunnel within the projection range of the unit grid Wi _{, j} has not deformed compared to the previous scanning detection.

Further, the tunnel deformation judgment method also includes S64: establish a corresponding proportional relationship between the tunnel structure deformation Δ _{i, j, k + 1} of the k+1 period relative to all unit grids of the k period and the color level, and produce Grayscale model diagram of tunnel surface deformation.

By establishing a proportional relationship between the detected deformation of the tunnel structure in each period and the previous period and the color scale, a grayscale model diagram of the tunnel surface deformation can be achieved, which can realize the dynamic and visualization of the tunnel deformation and facilitate monitoring personnel to determine the deformation form of the tunnel.

The beneficial effects of the present invention are:

1. The present invention uses non-contact measurement three-dimensional laser scanning technology to scan and obtain the surface data of the surrounding rock of the tunnel and the primary branch, and can establish a tunnel primary branch model including the primary branch thickness data. According to the different thickness of the primary branch , mark abnormal points in the tunnel, so that targeted monitoring can be carried out during later tunnel monitoring, which effectively saves the workload of later monitoring and speeds up the acquisition of monitoring data. At the same time, the relationship between the thickness of the primary support and tunnel deformation can be easily studied based on the monitoring data and the tunnel primary support model.

2. By considering the uneven initial support thickness caused by over-excavation and under-excavation of the surrounding rock, it not only conforms to the actual engineering situation, but also can effectively monitor the local stress concentration caused by over-excavation and the insufficient initial support thickness caused by under-excavation. safety hazards arising.

Description of the drawings

Figure 1 is a schematic diagram of the conversion between the scanning coordinate system and the geodetic coordinate system;

Figure 2 is a schematic cross-section of the tunnel surrounding rock that is over- and under-excavated;

Figure 3 is a schematic diagram of the surrounding rock surface model;

Figure 4 is a schematic cross-section of the tunnel's primary branch.

Detailed ways

The specific embodiments of the present invention are described below to facilitate those skilled in the art to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the technical field, as long as various changes These changes are obvious within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions and creations utilizing the concept of the invention are protected.

A tunnel deformation monitoring method based on unequal thickness of primary branches is provided, including the following steps:

S1: Use a laser scanner to scan the surrounding rock of the tunnel to be detected and obtain the surrounding rock point cloud data;

Preprocessing is required before coordinate axis conversion of surrounding rock point cloud data. Preprocessing of surrounding rock point cloud data includes one or more of point cloud denoising, point cloud thinning, or point cloud simplification. Preprocessing point cloud data can remove data noise caused by poor on-site working conditions; and it can eliminate redundant points in point cloud data without affecting the complete characteristics of the point cloud of the subject being measured. The preprocessed surrounding rock point cloud data is used to establish a surrounding rock surface contour model, as shown in Figure 3.

S2: Unify the coordinate axis conversion of the surrounding rock point cloud data to obtain the axis direction of the tunnel to be detected;

Unify the coordinate axes of the surrounding rock point cloud data into the geodetic coordinate axis. The specific methods include the following:

A1: Before the laser scanner scans the tunnel to be detected in step S1, use the total station to position the laser scanner. Record the origin of the total station as the position coordinate in the geodetic coordinate system as (x0, y0, z ₀ ), and calculate Obtain the x-axis direction vector (x ₁ , y ₁ , z ₁ ) and y-axis direction vector (x ₂ , y ₂ , z ₂ ) of the laser scanner;

A2: Convert the scanning coordinate system of the surrounding rock point cloud data into the geodetic coordinate system: The surrounding rock point cloud data is collected by scanning and collecting the tunnel to be detected in sections using a laser scanner, as shown in Figure 1. Record the surrounding rock point cloud data of each section. The coordinates of the scanning coordinate system are (x _i ', y _i ', z _i '), and the coordinates of the geodetic coordinate system corresponding to the scanning coordinate system of the surrounding rock point cloud data of each section are (x _i , y _i , z _i ) , the conversion method is:

Among them, θ is the angle of rotation of the scanning coordinate system around the z-axis, α is the angle of rotation of the scanning coordinate system around the x-axis, γ is the angle of rotation of the scanning coordinate system around the y-axis; T ₁ is the rotation matrix in the z-axis direction; T ₂ is Rotation matrix in x-axis direction; T ₃ is rotation matrix in y-axis direction;

A3: Use the RANSAC algorithm to fit the center coordinates of the surrounding rock point cloud data on the tunnel section, project the center coordinates of any section onto the xoz plane and yoz plane of the geodetic coordinate system, and calculate the center coordinates of all sections The projection points of the coordinates are sorted according to the forward direction of the tunnel;

A4: Use cubic spline interpolation to fit the projection points on the xoz plane and yoz plane of the geodetic coordinate system to obtain two curves respectively located on the xoz plane and yoz plane of the geodetic coordinate system;

A5: Integrate the two curves to obtain the axis direction of the tunnel to be detected.

The integration method of the two curves is:

Take any point (x _q , z _q ) on the curve on the xoz surface, take the point (y _q , z _q ) on the same z coordinate of the curve on the yoz surface, and combine the point (x _q , z _q ) with the point ( y _q , z _q ) are integrated into (x _q , y _q , z _q ), that is, a new curve can be obtained, which is the axis direction of the tunnel to be detected.

S3: Calculate the actual radius of the tunnel according to the axis direction of the tunnel to be detected, and calculate the over- and under-excavation amount of the tunnel to be detected using the actual radius of the tunnel and the theoretical radius of the tunnel;

The calculation method for the over and under excavation of the tunnel to be detected is:

Among them, (x _xoy ,y _xoy ) are the outline coordinates of the surrounding rock point cloud data on the tunnel section to be detected, (x _r , y _r ) are the center coordinates of the geodetic coordinate system on the same tunnel section to be detected, r ₀ is the tunnel theory Radius, d is the distance between the surrounding rock point cloud data and the theoretical contour of the tunnel to be detected;

As shown in Figure 2, when d>0, it means that the tunnel to be detected is over-excavated in this area, and the over-excavation value is d|; when d<0, it means that the tunnel to be detected is under-excavated in this area. , the under-excavation value is |d|; when d=0, the tunnel to be detected does not have over-under-excavation in this area.

S4: After the construction of the primary support of the tunnel to be inspected is completed, the laser scanner is used to scan again to obtain the surface point cloud data of the primary support of the tunnel; when the tunnel is constructed with the primary support, the thickness of the primary support will be different due to over-excavation of the surrounding rock and the lack of excavation of the surrounding rock. The schematic diagram of the thickness section of the primary support is as follows As shown in Figure 4.

S5: Establish the tunnel primary support model based on the tunnel primary support surface point cloud data and surrounding rock point cloud data, and mark the thickness abnormal points of the tunnel primary support model through the over-under excavation amount; the marking method of thickness abnormal points is:

The actual thickness T of the primary branch is the surface point cloud data of the tunnel primary branch minus the surrounding rock point cloud data, and t is the design thickness of the primary branch;

When T-t<d<0, mark the area as an abnormal point with ultra-thin thickness;

When d≤T-t<0, mark the area as a thin abnormal point;

When 0<T-t≤d, mark the area as a thick abnormal point;

When 0<d<T-t, the area is marked as an abnormal thickness point;

When T-t=0, this area will not be marked as a thickness abnormal point.

S6: After the tunnel is completed, use a laser scanner to conduct multi-stage scanning inspections at the corresponding positions of the thickness abnormal points, and compare the monitoring data of each period to obtain the deformation of the tunnel to be detected.

After scanning the corresponding positions of thickness abnormal points in each period, a tunnel surface model is established. The methods for judging tunnel deformation include the following:

S61: Divide the tunnel surface model into m segments of length p along the direction of the central axis, 0.01＜p＜0.1m; then divide the tunnel surface model into equal parts along the cross section clockwise from the bottom of the left tunnel side wall with an angle of n segment of a, 0°<a<2°;

At this time, the tunnel surface model is equally divided into m×n unit grids, which are numbered according to the row and column numbers of the unit grids as W _{i, j} , (i=1, 2,...,m; j=1, 2,...,n;);

During the specific implementation, the entire tunnel is scanned to establish a tunnel surface model. When judging the tunnel deformation condition on the tunnel surface at non-thickness abnormal points, the non-thickness abnormal point positions of the tunnel surface model are equally divided into lengths p' along the direction of the central axis. m' segment, and p' is greater than p, m' is less than m.

S62: Use the center O _i (i=1, 2..., m) of the i-th segment on the central axis of the tunnel as the projection center unit grid W _{i, j} as the projection datum plane for projection, and the unit grid W The projection range of the tunnel surface point cloud model of _{i, j} in the kth period is P _{i, j, k} , (i=1, 2,..., m; j=1, 2,..., n; k=1 ,2,...,q;);P _i,j,k are planar quadrilaterals;

S63: The distance from the projection center O _i to the plane quadrilateral P _{i, j, k} is p _{i, j, k} . Then the projection range of the unit grid W _{i, j} in the tunnel surface model corresponds to the k+1th period relative to the kth period. The deformation amount of the tunnel structure is Δ _{i, j, k + 1} = p _{i, j, k + 1} - p _{i, j, k} ;

If Δ _{i, j, k+1} > 0, then the tunnel within the projection range of unit grid W _{i, j} is detected as outward expansion and deformation compared to the previous scan,

If Δ _{i, j, k+1} <0, then the tunnel within the projection range of the unit grid W _{i, j} is detected to be inwardly shrinking and deformed compared to the previous scan;

If Δ _{i, j, k+1} = 0, then the tunnel within the projection range of the unit grid Wi _{, j} has not deformed compared to the previous scanning detection.

S64: Establish a corresponding proportional relationship between the tunnel structure deformation Δi, j, k+1 of all unit grids in the k+1 period relative to the k-th period and the color scale, and create a grayscale model diagram of the tunnel surface deformation. By establishing a proportional relationship between the detected deformation of the tunnel structure in each period and the previous period and the color scale, a grayscale model diagram of the tunnel surface deformation can be achieved, which can realize the dynamic and visualization of the tunnel deformation and facilitate monitoring personnel to determine the deformation form of the tunnel.

Claims (5)

1. The tunnel deformation monitoring method based on the primary support unequal thickness is characterized by comprising the following steps of:

s1: scanning surrounding rocks of a tunnel to be detected by using a laser scanner to obtain surrounding rock point cloud data;

s2: performing coordinate axis unified conversion on surrounding rock point cloud data to obtain the axial direction of a tunnel to be detected;

s3: calculating to obtain the actual radius of the tunnel according to the axis direction of the tunnel to be detected, and calculating to obtain the super-underexcavation quantity of the tunnel to be detected by using the actual radius of the tunnel and the theoretical radius of the tunnel;

s4: scanning again by using a laser scanner after the primary support construction of the tunnel to be detected is completed, so as to obtain the point cloud data of the primary support surface of the tunnel;

s5: establishing a tunnel primary support model according to the tunnel primary support surface point cloud data and the surrounding rock point cloud data, and marking abnormal thickness points of the tunnel primary support model through the super-underexcavation quantity;

s6: after the tunnel is completed, scanning and detecting the positions corresponding to the thickness abnormal points for a plurality of periods by using a laser scanner, and comparing the monitoring data of each period to obtain the deformation condition of the surface of the tunnel to be detected;

the marking method of the thickness abnormal point in the step S5 comprises the following steps:

the actual thickness T of the primary support is the design thickness of the primary support, wherein the actual thickness T of the primary support is the surface point cloud data of the primary support minus the surrounding rock point cloud data of the primary support;

when T-T < d <0, marking the area as a thickness ultrathin abnormal point;

when d is less than or equal to T-T <0, marking the area as an abnormal point with thinner thickness;

when 0<T-t is less than or equal to d, marking the area as an abnormal point with thicker thickness;

when 0< d < T-t, marking the area as an extra-thick abnormal point;

when T-t=0, this area is not marked as a thickness outlier;

in the step S2, preprocessing is required before coordinate axis conversion is performed on surrounding rock point cloud data, where the preprocessing of the surrounding rock point cloud data includes one or more of point cloud denoising, point cloud thinning or point cloud simplification;

in the step S2, coordinate axes of surrounding rock point cloud data are uniformly converted into earth coordinate axes, and the specific method comprises the following steps:

a1: before the laser scanner scans the tunnel to be detected in the step S1, the laser scanner is positioned by using the total station, and the origin of the total station is recorded as the position coordinate (x) under the geodetic coordinate system ₀ ，y ₀ ，z ₀ ) And calculates an x-axis direction vector (x ₁ ，y ₁ ，z ₁ ) And a y-axis direction vector (x ₂ ，y ₂ ，z ₂ )；

A2: converting a scanning coordinate system of surrounding rock point cloud data into a geodetic coordinate system: surrounding rock point cloud data are acquired by a laser scanner in a segmented scanning way for a tunnel to be detected, and coordinates of a scanning coordinate system of each segment of surrounding rock point cloud data are recorded as (x) _i '，y _i '，z _i ') the coordinates of the earth coordinate system corresponding to the scanning coordinate system of the surrounding rock point cloud data of each section are recorded as (x) _i ，y _i ，z _i ) The conversion method comprises the following steps:

wherein θ is the angle at which the scan coordinate system rotates about the z-axis, α is the angle at which the scan coordinate system rotates about the x-axis, and γ is the angle at which the scan coordinate system rotates about the y-axis; t (T) ₁ A rotation matrix for the z-axis direction; t (T) ₂ A rotation matrix in the x-axis direction; t (T) ₃ Rotating the matrix for the y-axis direction;

a3: fitting circle center coordinates of surrounding rock point cloud data on tunnel cross sections by using a RANSAC algorithm, respectively projecting the circle center coordinates on any cross section onto a xoz surface and a yoz surface of a geodetic coordinate system, and sequencing projection points of the circle center coordinates of all cross sections according to the advancing direction of the tunnel;

a4: fitting projection points on a xoz surface and a yoz surface of the geodetic coordinate system respectively by using cubic spline interpolation to obtain two curves respectively positioned on a xoz surface and a yoz surface of the geodetic coordinate system;

a5: and integrating the two curves to obtain the axial direction of the tunnel to be detected.

2. The tunnel deformation monitoring method based on the primary support unequal thickness according to claim 1, wherein the method for integrating the two curves is as follows:

taking the point (x) on any one of the curves on the xoz plane _q ，z _q ) Taking the point (y) on the same z coordinate of the curve on the yoz plane _q ，z _q ) Points (x) _q ，z _q ) Sum point (y) _q ，z _q ) Integrated as (x) _q ，y _q ，z _q ) A new curve can be obtained, and the new curve is the axial direction of the tunnel to be detected.

3. The method for monitoring tunnel deformation based on unequal primary support thickness according to claim 1, wherein the method for calculating the super-underexcavation amount of the tunnel to be detected in step S3 is as follows:

wherein, (x) _xoy ,y _xoy ) The contour coordinates (x) of surrounding rock point cloud data on the section of the tunnel to be detected _r ，y _r ) Is the center coordinates, r, of a geodetic coordinate system on the same tunnel section to be detected ₀ D is the theoretical radius of the tunnel, and d is the value of the surrounding rock point cloud data from the theoretical contour of the tunnel to be detected;

when d is more than 0, the tunnel to be detected is overdrawn in the area, and the overdrawing value is |d|; when d is less than 0, namely the tunnel to be detected is undermined in the area, and the undermining value is |d|; when d=0, no undermining of the tunnel to be detected occurs in this region.

4. The method for monitoring tunnel deformation based on unequal primary support thickness according to claim 1, wherein in the step S6, a tunnel surface model is built after scanning the position corresponding to the thickness abnormal point in each period, and the method for judging tunnel deformation condition comprises the following steps:

s61: equally dividing the tunnel surface model into m sections with the length p along the central axis direction, wherein p is more than 0.01 and less than 0.1m; dividing the tunnel surface model into n sections with an angle a along the clockwise annular direction of the cross section from the bottom of the left tunnel sidewall, wherein a is more than 0 degrees and less than 2 degrees;

at this time, the tunnel surface model is equally divided into m×n unit meshes, and the number is W by the row number where the unit meshes are located _i，j ，(i＝1，2，...，m；j＝1，2，...，n；)；

S62: with centre O of the ith segment on the tunnel axis _i (i=1, 2.., m) is the projection center, the cell grid W _i，j For projecting the projection reference plane, the unit grid W _i，j The projection range of the point cloud model on the surface of the tunnel in the k period is P _i，j，k ，(i＝1，2，...，m；j＝1，2，...，n；k＝1，2，...，q；)；P _i，j，k Is a plane quadrangle;

s63: projection center O _i To a plane quadrilateral P _i，j，k Is p _i，j，k Then the unit grid W in the tunnel surface model _i，j The deformation of the tunnel structure in the (k+1) th period relative to the (k) th period of the region corresponding to the projection range is delta _i，j，k+1 ＝p _i，j，k+1 -p _i，j，k ；

If delta _i，j，k+1 > 0, then cell grid W _i，j The tunnel in the projection range is detected as being outwardly distended and deformed compared with the last scanning,

if delta _i，j，k+1 <0, then cell grid W _i，j The tunnel in the projection range is detected as inward shrinkage deformation compared with the last scanning;

if delta _i，j，k+1 =0, then cell grid W _i，j The tunnel in the projection range is not deformed compared with the previous scanning detection.

5. The method for monitoring tunnel deformation based on unequal primary support thickness according to claim 4, wherein the method for judging tunnel deformation condition further comprises S64:

and establishing a corresponding proportional relation between the deformation delta i, j and k+1 of the tunnel structure of the k+1 phase relative to all unit grids of the k phase and the tone scale, and manufacturing a tunnel surface deformation gray scale model graph.