A tunnel support deformation safety analysis method

Abstract

The application provides a tunnel support deformation safety analysis method, which is suitable for the field of tunnel construction. The application comprises the following steps: arranging monitoring points, obtaining vault monitoring point image data, comparing image data processing, edge point coordinate set processing, vault deformation amount estimation, left and right side wall deformation amount estimation and safety evaluation. After the monitoring points are arranged, the initial image data is shot as comparison image data one. The monitoring points are shot every certain time interval, and compared with the comparison image data one. The relative displacement of the deformation indicator center in the front and back images is calculated by an algorithm. The relative displacement is the approximate value of the deformation amount of the monitoring points. The method can automatically and continuously obtain the deformation of the monitoring points, and directly and quickly obtain the current deformation value. The method has the characteristics of high monitoring efficiency, high accuracy, timely deformation result reaction, and can be widely applied to the field of tunnel construction deformation monitoring.

Description

Technical Field

[0001] This invention relates to the field of tunnel construction deformation monitoring, and specifically to a method for analyzing the deformation safety of tunnel support. Background Technology

[0002] Tunnel engineering is a crucial cornerstone of modern infrastructure construction, serving as vital hubs between cities and significantly promoting the development of transportation networks between urban and mountainous areas. With urbanization unfolding across the country, an increasing number of tunnels need to be built in complex and varied geological environments, posing greater challenges to ensuring tunnel construction safety. As the most critical component of tunnel construction, the support structure has always received extremely high attention in safety monitoring.

[0003] Traditional tunnel support structure deformation monitoring mainly relies on manual measurement, including periodic on-site observations using tools such as total stations and convergent agents. While this method is intuitive and reliable, it suffers from low observation efficiency, high labor intensity, and the inability to achieve continuous monitoring. Therefore, tunnel support deformation safety analysis methods based on this approach also suffer from low efficiency and untimely results.

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

[0005] The purpose of this 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. It provides a tunnel support deformation safety analysis method based on automatic continuous monitoring, which can be widely applied in the field of tunnel construction deformation monitoring.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] S101. Set up monitoring points;

[0008] The arrangement of monitoring points includes, after the construction of the support structure is completed, placing deformation indicator signs at the monitoring points on the arch and left and right side walls as specified in the tunnel monitoring plan. After the deformation indicator signs are placed, a supplementary light source is used to stably illuminate the deformation indicator signs. The supplementary light source is placed on the completed road surface of the tunnel, and a camera is placed on the road surface. The deformation indicator sign consists of a central red dot and two concentric circles of green and blue. The radius of the central red dot is R1, the radii of the two concentric circles on the arch deformation indicator sign are R2 and R3 mm, and the radii of the two concentric circles on the left and right side wall deformation indicator signs are R'2 and R'3 mm.

[0009] S102. Obtain image data of the arch monitoring point;

[0010] The process of acquiring image data of the arch monitoring point includes taking a picture of the arch monitoring point using the imaging device, and then converting the image data to grayscale using a weighted average method.

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

[0012] In the formula, H(x,y) is the gray value of pixel (x,y) in the processed image, R(x,y) is the R component color depth value of pixel (x,y) in the original image, G(x,y) is the G component color depth value of pixel (x,y) in the original image, and B(x,y) is the B component color depth value of pixel (x,y) in the original image.

[0013] Then, the image data is subjected to sharpness detection, and the image data that does not meet the sharpness requirements is discarded until the image data that meets the sharpness requirements is obtained. The image data is used as the first comparison image data. The first comparison image data remains unchanged. Then, the second comparison image data is obtained in the same way at every time interval T. The positions of the shooting device and the supplementary light source remain unchanged during the two image data acquisitions.

[0014] S103, Comparison image data processing;

[0015] The comparison image data processing includes denoising the comparison image data one and comparison image data two by combining a switched median filter and a bilateral filter, and using the Canny edge detection algorithm to calculate the gradient intensity and direction of the image. After non-maximum suppression and double threshold detection, isolated edge points are obtained, and the coordinate set of the edge points is output. The coordinate set of the edge points includes the coordinates of the concentric circle edge points of the deformable sign.

[0016] S104, Edge point coordinate set processing;

[0017] The edge point coordinate set processing includes determining an initial subset of edge point coordinates for the candidate region of the circle center based on the minimum value (x1, y1) and 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 hypothetical circle center, and denoting the current hypothetical circle center as (x0, y0). The initial value of the hypothetical circle center is then determined according to equation (2). For any coordinate (x1, y1)... i ,y i When equation (3) is satisfied, the coordinates (x) are denoted as (x). i ,y i The edge point at point () is the edge point of the circle with radius R2. The number of edge points of the circle with radius R2 of the current assumed center is incremented by 1. After all coordinates in the set of edge point coordinates have been filtered by equation (3), the subset of the coordinates of the edge points of the circle with radius R2 of the current assumed center and the total number of edge points m are obtained. r2By changing the coordinates of the assumed center of the circle, and traversing the coordinates of the candidate region in both the minimum and maximum directions, the subset of coordinates of the edge points of the circle with radius R2 of the current assumed center and the total number of edge points m' are obtained. r2 Take m r2 and m' r2 The larger one is used as the new m r2 And the hypothetical center coordinates corresponding to the larger one are taken as the optimal center coordinates (x). r2 ,y r2 The optimal center is the center of the circle with radius R2 when the coordinates of the assumed center have traversed all the coordinates of the candidate regions. The subset of coordinates of the edge points of the circle with radius R2 corresponding to the optimal center is recorded.

[0018]

[0019] In the formula, α is the ratio of actual distance to number of pixels, mm / dot, and δ is the tolerable fluctuation in the number of pixels, dot.

[0020] Similarly, determine the center coordinates (x, y) of the circle with radius R3 according to equation (4). r3 ,y r3 The coordinates of the edge points of the circle with radius R3 and the corresponding subset of coordinates are used to further verify the center coordinates of the concentric circle R2, and a unified center coordinate (x) is obtained. r ,y r );

[0021]

[0022] S105. Estimation of arch deformation;

[0023] The estimation of the arch deformation includes calculating the center coordinates (x, y) of the comparative image data. r ,y r The coordinates of the center of the two circles in the comparison image data (x') r ,y' r The corresponding actual distance Δ, in mm, is an approximate value for the arch 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 and repeating steps S102 to S105 to obtain approximate values ​​of the deformation of the left and right side walls.

[0027] S107, Safety Evaluation;

[0028] The safety assessment includes the following: when the approximate value of the arch deformation reaches R2 on its deformation indicator, or when the sum of the approximate values ​​of the left and right sidewall deformations reaches 2R'2 on its deformation indicator, tunnel construction personnel need to accurately verify the deformation value using traditional deformation measurement methods and closely monitor the further development of deformation. When the approximate value of the arch deformation reaches R3 on its deformation indicator, or when the sum of the approximate values ​​of the left and right sidewall deformations reaches 2R'3 on its deformation indicator, tunnel construction personnel need to develop 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 based on 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 subsequent operations are performed.

[0030] As a preferred technical solution of the present invention, in step S102, before acquiring the image data of the arch monitoring point, it is necessary to adjust the camera so that the size, height and width of the captured image can accommodate 3 deformation indicator signs, and the deformation indicator signs are 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 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 deformable sign, the existing α value can be used directly.

[0032] As a preferred technical solution of the present invention, the existing α value is obtained by taking a clear image after the monitoring points are arranged, measuring the distance l, mm between the edge of the deformable indicator circle with radius R2 and the edge of the circle with radius R3 in the image, and then obtaining the α value according to equation (7).

[0033]

[0034] In the formula, DPI is the number of pixels per inch of the image, in dots per inch.

[0035] The beneficial effects of this invention are as follows: by taking the initial image data after setting up monitoring points as the first image data for subsequent deformation monitoring comparison, taking pictures of the monitoring points at regular intervals and comparing them with the first image data, and calculating the relative displacement of the center of the deformation indicator in the images before and after using an algorithm, the relative displacement is the approximate value of the deformation of the monitoring point. This method can automatically and continuously acquire the deformation of the monitoring points and directly and quickly acquire the current deformation value. Attached Figure Description

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

[0037] Figure 2 This is a front view of the monitoring point layout according to Embodiment 1 of the present invention;

[0038] Figure 3 This is a side view of the monitoring point arrangement according to Embodiment 1 of the present invention;

[0039] The attached diagram is labeled as follows: 1-Arch deformation indicator, 2-Side wall deformation indicator, 3-Photography device, 4-Supplementary light source. Detailed Implementation

[0040] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments given herein are for illustration and explanation only and are not intended to limit the invention. It should be noted that many specific details are set forth in the following description to provide a thorough understanding of the invention; however, the invention may have other embodiments and modifications thereof. Therefore, the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0041] This first embodiment is based on the construction process of the Shuangwendan No. 1 Tunnel on Line C2 of the Eighth Division of the East Coast Rail Link (ECRL) project. The tunnel is 3595m long, with an entrance mileage of CH000+606 and an exit mileage of CH004+201. The line slopes from the entrance at 3‰ uphill to 6‰ downhill at CH002+400. The maximum burial depth is 335m, and the minimum burial depth is 5m. The tunnel is designed as a ballast-lined composite structure with a standard track spacing of 4.2m. The tunnel support deformation safety analysis method is as follows:

[0042] S101. Set up monitoring points;

[0043] After the support structure construction is completed, deformation indicator signs 1 and 2 are set up at the monitoring points on the arch and left and right side walls as specified in the tunnel monitoring plan. After the deformation indicator signs 1 and 2 are set up, supplementary light source 4 is used to stably illuminate the deformation indicator signs 1 and 2. Supplementary light source 4 is set up on the completed road surface of the tunnel, and shooting device 3 is set up on the road surface. Deformation indicator signs 1 and 2 are composed of a central red dot and two layers of concentric circles in green and blue. The radius of the central red dot is R1 = 0.5 mm. The radii of the two layers of concentric circles on the arch deformation indicator sign 1 are R2 = 30 mm and R3 = 45 mm. The radii of the left and right side wall deformation indicator signs from the inside to the outside are R'2 = 10 mm and R'3 = 15 mm, respectively. Before using shooting device 3 to take pictures, the shooting device 3 is adjusted so that the image size, height and width of the images taken from the arch, left and right side walls can accommodate 3 deformation indicator signs 1 and 2 respectively, and the deformation indicator signs 1 and 2 are positioned slightly above the center of the image.

[0044] S102. Obtain image data of the arch monitoring point;

[0045] After taking pictures of the monitoring points on the arch using imaging device 3, the image data was converted to grayscale using a weighted average method.

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

[0047] In the formula, H(x,y) is the gray value of pixel (x,y) in the processed image, R(x,y) is the R component color depth value of pixel (x,y) in the original image, G(x,y) is the G component color depth value of pixel (x,y) in the original image, and B(x,y) is the B component color depth value of pixel (x,y) in the original image.

[0048] The Laplacian gradient method is used to detect the sharpness of the image data. The gradient reference value is 4.0. Then, the image data that does not meet the sharpness requirements is discarded until the image data that meets the sharpness requirements is obtained. The image data is used as the first comparison image data. The first comparison image data remains unchanged. Then, the second comparison image data is obtained in the same way every time interval T = 24h. The positions of the shooting device 3 and the supplementary light source 4 remain unchanged during the two image data acquisitions.

[0049] S103, Comparison image data processing;

[0050] The comparison image data 1 and comparison image data 2 are denoised by combining a switch-type median filter and a bilateral filter. The gradient intensity and direction of the image are calculated by the Canny edge detection algorithm. Isolated edge points are obtained by non-maximum suppression and double threshold detection. The coordinate set of the edge points is output. The coordinate set of the edge points includes the coordinates of the concentric circle edge points of the deformable sign 1.

[0051] S104, Edge point coordinate set processing;

[0052] This is the first time this monitoring method has been used, and there is no existing α value for reference. After the monitoring points are set up, a clear image is taken. The distance l = 5mm between the edge of the deformable indicator circle with radius R2 and the edge of the circle with radius R3 in the image is measured. Then, the α value is obtained according to equation (2).

[0053]

[0054] In the formula, DPI is the number of pixels per inch of the image, which is 300 dots per inch in this embodiment;

[0055] Based on the minimum (x1, y1) and maximum (x2, y2) values ​​of the edge point coordinate set, a subset of edge point coordinates for the candidate region of the initial circle center is determined. The center of the subset of edge point coordinates is taken as the starting point of the hypothetical circle center. Let the current hypothetical circle center be (x0, y0). Then, the initial value of the hypothetical circle center is determined according to equation (3). For any coordinate (x1, y1)... i ,y i When equation (4) is satisfied, the coordinates (x) are denoted as (x). i ,y i The edge point at point () is the edge point of the circle with radius R2. The number of edge points of the circle with radius R2 of the current assumed center is incremented by 1. After all coordinates in the set of edge point coordinates have been filtered by equation (4), the subset of the coordinates of the edge points of the circle with radius R2 of the current assumed center and the total number of edge points m are obtained. r2 By changing the coordinates of the assumed center of the circle, and traversing the coordinates of the candidate region in both the minimum and maximum directions, the subset of coordinates of the edge points of the circle with radius R2 of the current assumed center and the total number of edge points m' are obtained. r2 Take m r2 and m' r2 The larger one is used as the new m r2 And the hypothetical center coordinates corresponding to the larger one are taken as the optimal center coordinates (x). r2 ,y r2 The optimal center is the center of the circle with radius R2 when the coordinates of the assumed center have traversed all the coordinates of the candidate regions. The subset of coordinates of the edge points of the circle with radius R2 corresponding to the optimal center is recorded.

[0056]

[0057] In the formula, δ is the tolerable fluctuation in the number of pixels, which is 5 dots in this embodiment;

[0058] Similarly, determine the center coordinates (x, y) of the circle with radius R3 according to equation (5). r3 ,y r3 The coordinates of the edge points of the circle with radius R3 and the corresponding subset of coordinates are used to further verify the center coordinates of the concentric circle R2, and a unified center coordinate (x) is obtained. r ,y r );

[0059]

[0060] S105. Estimation of arch deformation;

[0061] Calculate the center coordinates (x, y) of the contrast image data. r ,y r The coordinates of the center of the two circles in the comparison image data (x') r ,y' rThe corresponding actual distance Δ, in mm, is an approximate value for the arch deformation.

[0062]

[0063] S106. Estimation of deformation of left and right side walls;

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

[0065] S107, Safety Evaluation;

[0066] Within 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 deformation of the left and right side walls is 0.5mm, which is much smaller than the inner circle R'2=10mm of the left and right side wall deformation indicator.

[0067] This second embodiment is based on the construction process of the Shuangwendan No. 1 Tunnel on Line C2 of the Eighth Division of the East Coast Rail Link Project. During the construction of a certain section of the tunnel, under the same conditions as in the first embodiment, including the same shooting device, the same pitch angle, the same image size, the same shooting distance, and the same deformation indicator, the existing α = 0.169 mm / dot was directly used. Based on the focal length, optical center, camera height, pitch angle, yaw angle, and image size information of the shooting device, the captured comparison image was subjected to inverse perspective transformation. The ellipse in the image caused by the shooting angle was restored to a circle, further improving the accuracy of the approximate value of the deformation. At the twenty-eighth monitoring cycle T = 28 × 24 h, the approximate value of the arch deformation was 31 mm, reaching the inner circle R2 of the arch deformation indicator 1 of 30 mm. The tunnel construction personnel used the traditional deformation measurement method to accurately verify the deformation value and measured a deformation value of 29.6 mm, which was not much different from the approximate value of the deformation by the method of the present invention. The further development of the deformation was closely monitored.

[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 of deformation results in the field of tunnel construction deformation monitoring.

[0069] It should be understood that the above embodiments are one or more embodiments of the present invention, and there are many other embodiments and variations based on the present invention; any variations and modifications made by those skilled in the art through the present invention without making pioneering innovations are all within the protection scope of the present invention.

Claims

1. A method for tunnel support deformation safety analysis, characterized in that Specifically, the following steps are included: S101. Set up monitoring points; The monitoring point setup includes, after the support structure construction is completed, placing deformation indicator signs at the arch crown and left and right sidewall monitoring points specified in the tunnel monitoring plan. After the deformation indicator signs are placed, a supplementary light source is used to stably illuminate them. The supplementary light source is positioned on the completed tunnel surface, and a camera is placed on the surface. The deformation indicator sign consists of a central red dot and two concentric green and blue circles, with the central red dot having a radius of [missing information]. R 1. The radius of the two concentric circles on the arch deformation indicator sign is... R 2, R 3 mm, the radius of the two concentric circles of the deformation indicator signs on the left and right side walls is 3 mm. R’ 2, R’ 3 mm; S102. Obtain image data of the arch monitoring point; The process of acquiring image data of the arch monitoring point includes taking a picture of the arch monitoring point using the imaging device, and then converting the image data to grayscale using a weighted average method. （1） In the formula, H ( x , y - Processed image pixels ( x , y The grayscale value of ) R ( x , y - Original image pixels ( x , y )of R Component color depth value, G ( x , y - Original image pixels ( x , y )of G Component color depth value, B ( x , y - Original image pixels ( x , y )of B Component color depth value; Then, the image data undergoes a sharpness test, discarding images that do not meet the sharpness requirements until images that meet the requirements are obtained. These images are then used as the first set of comparison images, which remain constant. Then, at intervals... T The second set of comparative image data was acquired in the same manner, with the positions of the imaging device and supplementary light source remaining unchanged during the two image data acquisitions. S103, Comparison image data processing; The comparison image data processing includes denoising the comparison image data one and comparison image data two by combining a switched median filter and a bilateral filter, and using the Canny edge detection algorithm to calculate the gradient intensity and direction of the image. After non-maximum suppression and double threshold detection, isolated edge points are obtained, and the coordinate set of the edge points is output. The coordinate set of the edge points includes the coordinates of the concentric circle edge points of the deformable sign. S104, Edge point coordinate set processing; The edge point coordinate set processing includes processing based on the minimum value of the edge point coordinate set ( x 1, y 1) and maximum value ( x 2, y 2) Determine the subset of edge point coordinates of the candidate region for initializing the circle center, and take the center of the subset of edge point coordinates as the starting point of the hypothetical circle center. Let the current hypothetical circle center be ( ). x 0, y 0), then assume the initial value of the center is determined according to equation (2), for any coordinate ( x i , y i When equation (3) is satisfied, the coordinates are denoted as ( x i , y i The edge point at () is the radius R 2. The edge point of the circle, and the radius of the currently assumed center of the circle. R 2. Increase the number of edge points by 1. After all coordinates in the set of edge point coordinates have been filtered by equation (3), obtain the radius of the current assumed center of the circle. R 2. Subset of circle edge point coordinates and total number of edge points m r2 By changing the coordinates of the assumed center of the circle and traversing the coordinates of the candidate region in both the minimum and maximum directions, the radius of the current assumed center of the circle can be obtained. R 2. Subset of circle edge point coordinates and total number of edge points m’ r2 ,Pick m r2 and m’ r2 The larger one is the new m r2 And the coordinates of the hypothetical center of the circle corresponding to the larger one are taken as the optimal center coordinates. x r2 , y r2 The optimal center of the circle is the radius, which is obtained by traversing all the candidate regions using the assumed center coordinates. R Find the center of the two circles and record the radius corresponding to the optimal center. R 2. A subset of coordinates of points on the edge of the circle; （2） （3） In the formula, α - The ratio of actual distance to number of pixels, mm / dot. δ - Tolerable pixel count fluctuation, in dots; In the same way, determine the radius according to equation (4). R 3. Coordinates of the center of the circle ( x r3 , y r3 ) and the corresponding radius R 3. A subset of coordinates of the edge points of the circle, based on the radius. R The coordinates of the center of the 3rd circle further verify the concentric circles. R Find the center coordinates of circle 2, and obtain a unified center coordinate system. x r , y r ); （4） （5） S105. Estimation of arch deformation; The estimation of the arch deformation includes calculating the coordinates of the center of the circle in the comparative image data ( x r , y r ) and the coordinates of the center of the two circles in the comparison image data ( x’ r , y’ r The actual distance corresponding to ) Δ , mm, the distance Δ This is an approximate value for the deformation of the arch. （6） 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 and repeating steps S102 to S105 to obtain approximate values ​​of the deformation of the left and right side walls. S107, Safety Evaluation; The safety assessment includes assessing the extent of arch deformation when it approximates the value indicated by the deformation indicator. R When 2, or when the sum of the approximate deformation values ​​of the left and right side walls reaches 2 of the deformation indicator. R’ At point 2, tunnel construction personnel need to accurately verify the deformation value using traditional deformation measurement methods and closely monitor the further development of the deformation. When the approximate value of the arch deformation reaches its deformation indicator... R When 3, or when the sum of the approximate deformation values ​​of the left and right side walls reaches 2 of the deformation indicator. R’ At 3 o'clock, tunnel construction personnel need to develop a reinforcement plan to prevent tunnel collapse.

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

3. The tunnel support deformation safety analysis method according to claim 1, characterized in that: In step S102, before acquiring the image data of the arch monitoring point, the camera needs to be adjusted so that the size, height and width of the captured image can accommodate 3 deformation indicator signs, and the deformation indicator signs are located slightly above the center of the image.

4. The tunnel support deformation safety analysis method according to claim 1, characterized in that: In step S104, the ratio of the actual distance to pixels... α Based on existing shooting data, under the conditions of the same shooting equipment, same tilt angle, same image size, same shooting distance, and same distorted sign, existing data can be directly used. α value.

5. The tunnel support deformation safety analysis method according to claim 4, characterized in that: The existing α After the monitoring points are set up, take a clear image and measure the radius of the deformable indicator in the image. R 2. Circle edge and radius R 3. Distance between the edges of the circle l mm, then α The value is obtained according to equation (7). （7） In the formula, DPI - Number of pixels per inch (dot / inch) for an image.

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