Tunnel support deformation safety analysis method

Abstract

The invention provides a tunnel support deformation safety analysis method which is suitable for the field of tunnel construction. The method comprises the steps of arranging monitoring points, obtaining vault monitoring point image data, performing comparison image data processing, performing edge point coordinate set processing, estimating vault deformation, estimating left and right side wall deformation and performing safety evaluation. The monitoring points are shot every certain time, the shot monitoring points are compared with the first comparison image data, the relative displacement of the center of the deformation indication board in the front image and the rear image is calculated through an algorithm, and the relative displacement is the approximate value of the deformation amount of the monitoring points. The method has the characteristics of high monitoring efficiency, high accuracy and timely deformation result response, and can be widely applied to the field of tunnel construction deformation monitoring.

Description

Technical Field

[0001] The invention relates to the field of tunnel construction deformation monitoring, and in particular to a tunnel support deformation safety analysis method. Background Art

[0002] Tunnel engineering is an important cornerstone of modern infrastructure construction. It is an important hub between cities and has greatly promoted the development of transportation networks between cities and mountainous areas. As urbanization construction is carried out across the country, more and more tunnels need to be built in complex and changeable geological environments, which brings greater challenges to the safety of tunnel construction. As the top priority of tunnel construction, the support structure has always received a high degree of attention in safety monitoring.

[0003] Traditional tunnel support structure deformation monitoring mainly relies on manual measurement, including regular on-site observation using total stations, convergence agents and other tools. This method is very intuitive and reliable, but it also has problems such as low observation efficiency, high labor intensity and inability to achieve continuous monitoring. Therefore, the tunnel support deformation safety analysis method based on this method also has problems such as low efficiency and untimely response to deformation safety analysis results.

[0004] Therefore, it is necessary to propose a tunnel support deformation safety analysis method based on automatic continuous monitoring. Summary of the invention

[0005] The purpose of the present invention is to solve the problems of low monitoring efficiency and untimely response of deformation safety analysis results in existing tunnel support deformation safety analysis methods, and to provide a tunnel support deformation safety analysis method based on automatic continuous monitoring, which can be widely used in the field of tunnel construction deformation monitoring.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] S101, arrange monitoring points;

[0008] The arrangement of monitoring points includes arranging deformation indicator signs at the monitoring points of the arch and left and right side walls specified in the tunnel monitoring plan after the construction of the supporting structure is completed. After the deformation indicator signs are arranged, a supplementary light source stably illuminates the deformation indicator signs. The supplementary light source is arranged on the completed road surface of the tunnel, and a shooting device is arranged on the road surface. The deformation indicator signs are composed of a central red dot and two layers of concentric circles of green and blue. The radius of the central red dot is R1, the radius of the two layers of concentric circles of the arch deformation indicator signs is R2, R3, mm, and the radius of the two layers of concentric circles of the left and right side wall deformation indicator signs is R'2, R'3, mm;

[0009] S102, obtaining image data of the vault monitoring point;

[0010] The step of obtaining the image data of the vault monitoring point includes taking a photo of the vault monitoring point using the photographing device and graying the image data using a weighted average method.

[0011] H(x,y)=0.299R(x,y)+0.587G(x,y)+0.114B(x,y) (1)

[0012] Where, H(x,y)-the grayscale value of the processed image pixel (x,y), R(x,y)-the R component color depth value of the original image pixel (x,y), G(x,y)-the G component color depth value of the original image pixel (x,y), B(x,y)-the B component color depth value of the original image pixel (x,y);

[0013] Then, the image data is tested for clarity, and image data that does not meet the clarity requirement is discarded until image data that meets the clarity requirement is obtained, and the image data is used as comparison image data 1, and the comparison image data 1 remains unchanged. Then, comparison image data 2 is obtained in the same manner at each interval T, and the positions of the shooting device and the supplementary light source remain unchanged during the two image data acquisitions;

[0014] S103, contrast image data processing;

[0015] The contrast image data processing includes performing noise reduction processing on the contrast image data 1 and the contrast image data 2 by combining a switch-type median filter and a bilateral filter, and using a Canny edge detection algorithm to calculate the gradient strength and direction of the image, obtaining isolated edge points through non-maximum suppression and double threshold detection, and outputting a coordinate set of the edge points, wherein the edge point coordinate set includes the coordinates of the concentric circle edge points of the deformed sign;

[0016] S104, edge point coordinate set processing;

[0017] The edge point coordinate set processing includes determining an edge point coordinate subset of the initialization circle center candidate area according to the minimum value (x1, y1) and the maximum value (x2, y2) of the edge point coordinate set, taking the center of the edge point coordinate subset as the starting point of the assumed circle center, and recording the current assumed circle center as (x0, y0). The initial value of the assumed circle center is determined according to formula (2). For any coordinate (x i ,y i ) satisfies formula (3), the coordinate (x i ,y i ) is the edge point of the circle with radius R2, and the number of edge points of the circle with radius R2 of the current assumed circle center is increased by 1. When all coordinates in the edge point coordinate set are filtered by formula (3), the coordinate subset of the circle with radius R2 of the current assumed circle center and the total number of edge points m are obtained. r2, change the coordinates of the assumed circle center, traverse the coordinates of the candidate area in the direction of the minimum and maximum values, and also obtain the coordinate subset of the circle edge points of the radius R2 of the current assumed circle center and the total number of edge points m' r2 , take m r2 and m' r2 The larger one is taken as the new m r2 and take the larger hypothetical center coordinates as the optimal center coordinates (x r2 ,y r2 ), until the assumed center coordinates traverse the coordinates of all candidate regions, the optimal center is the center of the circle with radius R2, and the coordinate subset of the edge points of the circle with radius R2 corresponding to the optimal center is recorded;

[0018]

[0019] Where, α is the ratio of actual distance to pixel number, mm / dot, δ is the tolerable pixel number fluctuation, dot;

[0020] In the same way, the center coordinates (x r3 ,y r3 ) and the corresponding radius R3 circle edge point coordinate subset, according to the radius R3 circle center coordinates further verify the concentric circle R2 center coordinates, and obtain the unified circle center coordinates (x r ,y r );

[0021]

[0022] S105, estimation of vault deformation;

[0023] The estimation of the deformation of the dome includes calculating the coordinates of the center of the circle (x r ,y r ) and the coordinates of the center of the two circles (x' r ,y' r ) corresponds to the actual distance Δ, mm, where the distance Δ is the approximate value of the dome deformation;

[0024]

[0025] S106, estimation of deformation of left and right side walls;

[0026] The estimation of the deformation of the left and right side walls includes replacing the arch with the left and right side walls, repeating steps S102 to S105, and obtaining approximate values ​​of the deformation of the left and right side walls;

[0027] S107, safety evaluation;

[0028] The safety assessment includes the following steps: when the approximate value of the arch deformation reaches R2 of its deformation indicator, or the approximate value of the sum of the left and right side wall deformations reaches 2R'2 of its deformation indicator, the tunnel construction personnel are required to use traditional deformation measurement methods to accurately verify the deformation value and pay close attention to the further development of the deformation; when the approximate value of the arch deformation reaches R3 of its deformation indicator, or the approximate value of the sum of the left and right side wall deformations reaches 2R'3 of its deformation indicator, the tunnel construction personnel are required to formulate a reinforcement plan to prevent tunnel collapse.

[0029] As a preferred technical solution of the present invention, the comparison image is subjected to inverse perspective transformation according to the focal length, optical center, camera height, pitch angle, yaw angle, and captured image size information of the shooting device, and then comparison image data processing and subsequent operations are performed.

[0030] As a preferred technical solution of the present invention, in step S102, before obtaining the image data of the vault monitoring point, the camera device needs to be debugged, and the height and width of the image taken can accommodate 3 deformed indicator signs, and the deformed indicator sign is located in the upper center of the image.

[0031] As a preferred technical solution of the present invention, in step S104, the ratio α of the actual distance to the pixel is obtained based on the existing shooting data. Under the conditions of the same shooting device, the same pitch angle, the same image size, the same shooting distance and the same deformed sign, the existing α value can be directly used.

[0032] As a preferred technical solution of the present invention, the existing α value is used. After the monitoring points are arranged, a clear image is taken and the distance l, mm between the edge of the circle with radius R2 and the edge of the circle with radius R3 of the deformed sign in the image is measured. Then the α value is obtained according to formula (7):

[0033]

[0034] In the formula, DPI-image pixels per inch, dot / inch.

[0035] The beneficial effects of the present invention are as follows: by taking the initial image data after arranging the monitoring points as the subsequent deformation monitoring comparison image data one, taking the monitoring points at regular intervals and comparing them with the comparison image data one, the relative displacement of the center of the deformed indicator sign in the front and back images is calculated by an algorithm, and the relative displacement is the approximate value of the deformation of the monitoring points. This method can automatically and continuously obtain the deformation of the monitoring points, and directly and quickly obtain the current deformation value. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flow chart of the tunnel support deformation safety analysis method of the present invention;

[0037] Figure 2 It is a front schematic diagram of the arrangement of monitoring points according to the first embodiment of the present invention;

[0038] Figure 3 It is a side schematic diagram of the arrangement of monitoring points according to the first embodiment of the present invention;

[0039] Reference numerals in the figure: 1-arch deformation indicator board, 2-side wall deformation indicator board, 3-photographing device, 4-supplementary light source. DETAILED DESCRIPTION

[0040] The specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments given here are only used to illustrate and explain the present invention and cannot be used to limit the present invention. It should be noted that many specific details are set forth in the following description to facilitate a full understanding of the present invention, but the present invention may also have other embodiments and variations thereof, and therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0041] This embodiment 1 is based on the construction process of the 1# Tunnel of C2 Line of the 8th Division of the East Coast Rail Link Project of Malaysia. The total length of the tunnel is 3595m, the entrance mileage is CH000+606, the exit mileage is CH004+201, the line changes from the entrance end to CH 002+400 with a slope of 3‰ uphill to a slope of 6‰ downhill, the maximum burial depth is 335m, the minimum burial depth is 5m, the tunnel is designed as a ballasted composite lining structure, and the standard line spacing is 4.2m. The tunnel support deformation safety analysis method is as follows:

[0042] S101, arrange monitoring points;

[0043] After the construction of the supporting structure is completed, deformation indicators 1 and 2 are arranged at the monitoring points of the arch and left and right side walls specified in the tunnel monitoring plan. After the deformation indicators 1 and 2 are arranged, the supplementary light source 4 stably illuminates the deformation indicators 1 and 2. The supplementary light source 4 is arranged on the completed road surface of the tunnel, and a shooting device 3 is arranged on the road surface. The deformation indicators 1 and 2 are composed of a central red dot and two layers of concentric circles of green and blue. The radius of the central red dot is R1=0.5mm. The radius of the two layers of concentric circles of the arch deformation indicator 1 is R2=30mm and R3=45mm. The radius of the left and right side wall deformation indicators from the inside to the outside is R'2=10mm and R'3=15mm respectively. Before using the shooting device 3 to shoot, the shooting device 3 is debugged so that the height and width of the image taken from the three directions of the arch and the left and right side walls can accommodate three deformation indicators 1 and 2 respectively, and the deformation indicators 1 and 2 are located in the upper middle of the image;

[0044] S102, obtaining image data of the vault monitoring point;

[0045] After taking a picture of the vault monitoring point using the camera 3, the image data is grayed out using the weighted average method.

[0046] H(x,y)=0.299R(x,y)+0.587G(x,y)+0.114B(x,y) (1)

[0047] Where, H(x,y)-the grayscale value of the processed image pixel (x,y), R(x,y)-the R component color depth value of the original image pixel (x,y), G(x,y)-the G component color depth value of the original image pixel (x,y), B(x,y)-the B component color depth value of the original image pixel (x,y);

[0048] The image data is detected for clarity using the Laplacian gradient method, and the gradient reference value is determined to be 4.0. Then, the image data that does not meet the clarity requirement is discarded until the image data that meets the clarity requirement is obtained. The image data is used as the first comparative image data, and the first comparative image data remains unchanged. Then, the second comparative image data is obtained in the same manner at every interval T=24h, and the positions of the shooting device 3 and the supplementary light source 4 remain unchanged during the two acquisitions of the image data.

[0049] S103, contrast image data processing;

[0050] The comparison image data 1 and the comparison image data 2 are subjected to noise reduction processing by combining a switching median filter and a bilateral filter, and the gradient strength and direction of the image are calculated by using a Canny edge detection algorithm, isolated edge points are obtained by non-maximum suppression and double threshold detection, and a coordinate set of the edge points is output, wherein the edge point coordinate set includes the concentric circle edge point coordinates of the deformed sign 1;

[0051] S104, edge point coordinate set processing;

[0052] When the monitoring method is used for the first time, there is no existing α value reference. After the monitoring points are arranged, a clear image is taken and the distance between the edge of the circle with radius R2 and the edge of the circle with radius R3 of the deformed sign in the image is measured. The α value is obtained according to formula (2):

[0053]

[0054] Wherein, DPI-image pixels per inch, in this embodiment is 300dot / inch;

[0055] The initialization center candidate region edge point coordinate subset is determined according to the minimum value (x1, y1) and the maximum value (x2, y2) of the edge point coordinate set. The center of the edge point coordinate subset is taken as the starting point of the assumed center. The current assumed center is (x0, y0). The initial value of the assumed center is determined according to formula (3). For any coordinate (x i ,y i ) satisfies formula (4), the coordinate (x i ,y i ) is the edge point of the circle with radius R2, and the number of edge points of the circle with radius R2 of the current assumed circle center is increased by 1. When all coordinates in the edge point coordinate set are filtered by formula (4), the coordinate subset of the circle with radius R2 of the current assumed circle center and the total number of edge points m are obtained. r2 , change the coordinates of the assumed circle center, traverse the coordinates of the candidate area in the direction of the minimum and maximum values, and also obtain the coordinate subset of the circle edge points of the radius R2 of the current assumed circle center and the total number of edge points m' r2 , take m r2 and m' r2 The larger one is taken as the new m r2 and take the larger hypothetical center coordinates as the optimal center coordinates (x r2 ,y r2 ), until the assumed center coordinates traverse the coordinates of all candidate regions, the optimal center is the center of the circle with radius R2, and the coordinate subset of the edge points of the circle with radius R2 corresponding to the optimal center is recorded;

[0056]

[0057] Wherein, δ is the tolerable pixel dot fluctuation value, which is 5 dots in this embodiment;

[0058] In the same way, the center coordinates (x r3 ,y r3 ) and the corresponding radius R3 circle edge point coordinate subset, according to the radius R3 circle center coordinates further verify the concentric circle R2 center coordinates, and obtain the unified circle center coordinates (x r ,y r );

[0059]

[0060] S105, estimation of vault deformation;

[0061] Calculate the coordinates of the center of the circle (x r ,y r ) and the coordinates of the center of the two circles (x' r ,y' r) corresponds to the actual distance Δ, mm, where the distance Δ is the approximate value of the dome deformation;

[0062]

[0063] S106, estimation of deformation of left and right side walls;

[0064] Replace the arch with the left and right side walls, repeat steps S102 to S105, and obtain the approximate values ​​of the deformation of the left and right side walls as 0.3 mm and 0.2 mm respectively;

[0065] S107, safety evaluation;

[0066] In the first monitoring period T = 24h, the approximate value of the arch deformation is much smaller than the inner circle R2 = 30mm of the arch deformation indicator 1, and the sum of the approximate values ​​of the left and right side wall deformation is 0.5mm, which is much smaller than the inner circle R'2 = 10mm of the left and right side wall deformation indicator.

[0067] The second embodiment of the present invention is based on the construction process of the 1# Tunnel of Shuangwendan on the C2 line of the eighth division of the East Coast Rail Link project. During the construction of a certain section of the tunnel, under the conditions of the same shooting device, the same pitch angle, the same image size, the same shooting distance and the same deformation indicator as in the first embodiment, the existing α=0.169mm / dot is directly used. According to the focal length, optical center, camera height, pitch angle, yaw angle and image size information of the shooting device, the contrast image is subjected to inverse perspective transformation, and the ellipse in the image caused by the shooting angle is restored to a circle, so as to further improve the accuracy of the approximate value of the deformation amount. At the 28th monitoring cycle T=28×24h, the approximate value of the deformation amount of the arch is 31mm, reaching the inner circle R2=30mm of the arch deformation indicator 1. The tunnel construction personnel use the traditional deformation measurement method to accurately verify the deformation value, and the measured deformation value is 29.6mm, which is not much different from the approximate value of the deformation amount of the method of the present invention, and pay close attention to the further development of the deformation.

[0068] In summary, the tunnel support deformation safety analysis method of the present invention has the characteristics of high monitoring efficiency, high accuracy and timely response to deformation results in the field of tunnel construction deformation monitoring.

[0069] It should be understood that the above-mentioned embodiments are one or more embodiments of the present invention, and there are many other embodiments and variations thereof based on the present invention; the variations and modifications made by ordinary technicians in this industry through the present invention without making pioneering innovations all fall within the scope of protection of the present invention.

Claims

1. A tunnel support deformation safety analysis method, characterized in that The specific steps include: S101, arrange monitoring points; The arrangement of monitoring points includes arranging deformation indicator signs at the monitoring points of the arch and left and right side walls specified in the tunnel monitoring plan after the construction of the supporting structure is completed. After the deformation indicator signs are arranged, a supplementary light source stably illuminates the deformation indicator signs. The supplementary light source is arranged on the completed road surface of the tunnel, and a shooting device is arranged on the road surface. The deformation indicator signs are composed of a central red dot and two layers of concentric circles of green and blue. The radius of the central red dot is R1, the radius of the two layers of concentric circles of the arch deformation indicator signs is R2, R3, mm, and the radius of the two layers of concentric circles of the left and right side wall deformation indicator signs is R'2, R'3, mm; S102, obtaining image data of the vault monitoring point; The step of obtaining the image data of the vault monitoring point includes taking a photo of the vault monitoring point using the photographing device and graying the image data using a weighted average method. H(x,y)=0.299R(x,y)+0.587G(x,y)+0.114B(x,y) (1) Where, H(x,y)-the grayscale value of the processed image pixel (x,y), R(x,y)-the R component color depth value of the original image pixel (x,y), G(x,y)-the G component color depth value of the original image pixel (x,y), B(x,y)-the B component color depth value of the original image pixel (x,y); Then, the image data is tested for clarity, and image data that does not meet the clarity requirement is discarded until image data that meets the clarity requirement is obtained, and the image data is used as comparison image data 1, and the comparison image data 1 remains unchanged. Then, comparison image data 2 is obtained in the same manner at each interval T, and the positions of the shooting device and the supplementary light source remain unchanged during the two image data acquisitions; S103, contrast image data processing; The contrast image data processing includes performing noise reduction processing on the contrast image data 1 and the contrast image data 2 by combining a switch-type median filter and a bilateral filter, and using a Canny edge detection algorithm to calculate the gradient strength and direction of the image, obtaining isolated edge points through non-maximum suppression and double threshold detection, and outputting a coordinate set of the edge points, wherein the edge point coordinate set includes the coordinates of the concentric circle edge points of the deformed sign; S104, edge point coordinate set processing; The edge point coordinate set processing includes determining an edge point coordinate subset of the initialization circle center candidate area according to the minimum value (x1, y1) and the maximum value (x2, y2) of the edge point coordinate set, taking the center of the edge point coordinate subset as the starting point of the assumed circle center, and recording the current assumed circle center as (x0, y0). The initial value of the assumed circle center is determined according to formula (2). For any coordinate (x i ,y i ) satisfies formula (3), the coordinate (x i ,y i ) is the edge point of the circle with radius R2, and the number of edge points of the circle with radius R2 of the current assumed circle center is increased by 1. When all coordinates in the edge point coordinate set are filtered by formula (3), the coordinate subset of the circle with radius R2 of the current assumed circle center and the total number of edge points m are obtained. r2 , change the coordinates of the assumed circle center, traverse the coordinates of the candidate area in the direction of the minimum and maximum values, and also obtain the coordinate subset of the circle edge points of the radius R2 of the current assumed circle center and the total number of edge points m' r2 , take m r2 and m' r2 The larger one is taken as the new m r2 and take the larger hypothetical center coordinates as the optimal center coordinates (x r2 ,y r2 ), until the assumed center coordinates traverse the coordinates of all candidate regions, the optimal center is the center of the circle with radius R2, and the coordinate subset of the edge points of the circle with radius R2 corresponding to the optimal center is recorded; Where, α is the ratio of actual distance to pixel number, mm / dot, δ is the tolerable pixel number fluctuation, dot; In the same way, the center coordinates (x r3 ,y r3 ) and the corresponding radius R3 circle edge point coordinate subset, according to the radius R3 circle center coordinates further verify the concentric circle R2 center coordinates, and obtain the unified circle center coordinates (x r ,y r ); S105, estimation of vault deformation; The estimation of the deformation of the dome includes calculating the coordinates of the center of the circle (x r ,y r ) and the coordinates of the center of the two circles (x' r ,y' r ) corresponds to the actual distance Δ, mm, where the distance Δ is the approximate value of the dome deformation; S106, estimation of deformation of left and right side walls; The estimation of the deformation of the left and right side walls includes replacing the arch with the left and right side walls, repeating steps S102 to S105, and obtaining approximate values ​​of the deformation of the left and right side walls; S107, safety evaluation; The safety assessment includes the following steps: when the approximate value of the arch deformation reaches R2 of its deformation indicator, or the approximate value of the sum of the left and right side wall deformations reaches 2R'2 of its deformation indicator, the tunnel construction personnel are required to use traditional deformation measurement methods to accurately verify the deformation value and pay close attention to the further development of the deformation; when the approximate value of the arch deformation reaches R3 of its deformation indicator, or the approximate value of the sum of the left and right side wall deformations reaches 2R'3 of its deformation indicator, the tunnel construction personnel are required to formulate a reinforcement plan to prevent tunnel collapse.

2. The tunnel support deformation safety analysis method according to claim 1 is characterized in that: The comparison image is subjected to inverse perspective transformation according to the focal length, optical center, camera height, pitch angle, yaw angle, and image size information of the shooting device, and then the comparison image data is processed and the subsequent operations are performed.

3. The tunnel support deformation safety analysis method according to claim 1 is characterized in that: In step S102, before obtaining the image data of the vault monitoring point, the camera device needs to be debugged, and the height and width of the image taken can accommodate three deformed indicator signs, and the deformed indicator signs are located in the upper center of the image.

4. The tunnel support deformation safety analysis method according to claim 1 is characterized by: In step S104, the ratio α of the actual distance to the pixel is obtained according to the existing shooting data. Under the conditions of the same shooting device, the same pitch angle, the same image size, the same shooting distance and the same deformed sign, the existing α value can be directly used.

5. The tunnel support deformation safety analysis method according to claim 3 is characterized by: The existing α value is taken after the monitoring points are arranged, and a clear image is taken to measure the distance l, mm between the edge of the circle with radius R2 and the edge of the circle with radius R3 of the deformed sign in the image. Then the α value is obtained according to formula (7): In the formula, DPI-image pixels per inch, dot / inch.

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