CN112001907A - Method for measuring roughness of surrounding rock in tunnel construction site - Google Patents
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Abstract
The invention discloses a method for measuring the roughness of surrounding rocks in a tunnel construction site, which comprises the following steps: step 1, collecting images of the inner wall of a tunnel formed by tunnel excavation to obtain a surrounding rock surface image; step 2, carrying out gray level processing on the surface image of the surrounding rock to obtain a gray level image; step 3, carrying out color area division on the gray level image and calculating the area ratio of each area; step 4, performing plastering treatment on the area subjected to the surrounding rock image acquisition, and calculating the roughness average depth of the surface of the surrounding rock; and 5, calculating the standard deviation of the roughness depth according to the area ratio of the different color areas, determining a normal distribution function of the surface roughness of the surrounding rock based on the standard deviation and the average depth, and obtaining quantitative evaluation of the surface roughness of the surrounding rock. The method can reflect the roughness of the surface of the surrounding rock of the tunnel, and judge the bonding property of the surrounding rock interface according to the roughness, thereby effectively reducing the waste caused by the falling of the sprayed concrete and ensuring that the formed supporting structure reaches the preset design strength.
Description
Technical Field
The invention relates to the technical field of tunnel construction, in particular to a method and device for measuring the roughness of surrounding rocks in a tunnel construction site.
Background
The roughness of the surrounding rock surface after the tunnel open hole is formed has great influence on the bonding property of the later-stage sprayed concrete, and the quality of the bonding property between the later-stage sprayed concrete and the surrounding rock surface directly influences the quality of the later-stage supporting effect.
Therefore, in the earlier stage of spraying concrete after the tunnel rough hole is formed, the roughness of the surrounding rock surface of the rough hole is evaluated in advance, the bonding performance of the surrounding rock surface is evaluated, the waste caused by the falling of the sprayed concrete can be effectively reduced, the bonding force of the rock and a spraying layer is enhanced, the formed supporting structure can reach the preset design strength, and the safety of later tunnel construction is ensured.
Currently, the roughness of rock surfaces and concrete surfaces is mostly done on small-scale, laboratory test pieces. And the existing sand filling method can not adapt to the vertical surface of the rock on the tunnel construction site, and the scale range of the laser scanning method is limited. The method for judging the surface roughness of the tunnel cavern surrounding rock has the characteristics of large scale and vertical surface, and an effective quantitative measurement method is not available. The current tunnel construction can only carry out the injection of concrete according to construction experience, and when the bonding property of country rock surface and concrete was relatively poor, can cause a large amount of drops of shotcrete, later stage supporting construction's intensity also can greatly reduced.
Disclosure of Invention
The invention provides a method for measuring the roughness of surrounding rocks in a tunnel construction site aiming at the problems.
The technical means adopted by the invention are as follows:
a method for measuring the roughness of surrounding rocks in a tunnel construction site comprises the following steps:
step 1, collecting surrounding rock surface images of partial areas of the inner wall of a tunnel formed by tunnel excavation to obtain surrounding rock surface images of the partial areas;
step 4, performing plastering treatment on the area subjected to the surrounding rock image acquisition, and calculating the average depth of the roughness of the surrounding rock surface of the area subjected to the surrounding rock image acquisition;
and 5, calculating a standard deviation of roughness depth according to the area ratio of the different color areas, determining a normal distribution function of the surface roughness of the tunnel surrounding rock based on the standard deviation and the average depth of the rock surface roughness, and obtaining quantitative evaluation of the surface roughness of the tunnel surrounding rock.
Further, the acquisition of the surrounding rock surface image in the step 1 comprises the following steps;
step 12, pushing the device bottom plate to the inner wall of the hole through a push rod and pushing the device bottom plate to move along the inner wall of the hole;
and step 13, controlling the push rod CCD device to collect surrounding rock surface images of the inner wall of the tunnel through an image collection button on the push rod.
Further, the step 2 comprises the following steps:
step 20, performing histogram equalization processing on the surrounding rock surface image to obtain a histogram equalized image;
step 21, performing Gaussian smoothing processing on the histogram equalization image to obtain a Gaussian smoothing processed image;
step 22, carrying out sharpening processing on the Gaussian smooth processed image to obtain a sharpened processed image;
and step 23, carrying out image edge detection on the sharpened image to obtain the gray-scale image.
Further, the area ratio of the different color regions is calculated by using formula (1):
in the formula: m isiM is the sum of areas divided into regions of the same color zoneARepresenting the area of the region where the surrounding rock image acquisition is performed, PiThe sum of the areas of the regions divided into the same color interval is in proportion to the area of the region for surrounding rock image acquisition.
Further, the step 4 includes the following steps of performing plastering treatment on the region where the surrounding rock image is acquired, leveling the plastering surface with a scraper blade and the highest point of the rock surface, calculating the area a of the region where plastering is performed and the volume V of the plastering material used for performing plastering treatment on the region, and calculating the average depth h of the roughness of the surrounding rock surface by adopting a formula (2):
further, the step 5 includes the following steps of finding out the region with the largest area ratio of the color region according to the characteristics of the normal distribution model, obtaining the area ratio Pimax of the color region, and calculating the standard deviation according to the formula (3):
according to the standard deviation, calculating a normal distribution model of the proportion of different depths of the surface roughness of the tunnel surrounding rock by a formula (4):
in the formula: h isiThe roughness of the surface of the surrounding rock corresponding to different color areas,
therefore, quantitative evaluation of the surface roughness of the tunnel surrounding rock is achieved.
Compared with the prior art, the method can better reflect the roughness of the surface of the surrounding rock of the tunnel, judge the bonding performance of the surrounding rock interface according to the roughness of the surface of the surrounding rock, effectively reduce the waste caused by the falling of the sprayed concrete, ensure that the formed supporting structure reaches the preset design strength, ensure the safe implementation of later construction and play a better guiding role in the construction of engineering.
Drawings
FIG. 1 is a flow chart of a method for measuring the roughness of surrounding rocks in a tunnel construction site, which is disclosed by the invention;
FIG. 2 is a flow chart of the present invention for wall rock surface image acquisition;
FIG. 3 is a schematic diagram of image acquisition of the inner wall of a tunnel cavern in the invention;
FIG. 4 is a structural view of a CCD device;
FIG. 5 is a left side view of FIG. 4;
FIG. 6 is a schematic diagram of surrounding rock image acquisition performed on the inner wall of a tunnel cavern;
FIG. 7 is a flow chart of performing a gray-scale processing on the surface image of the surrounding rock to obtain a gray-scale image;
FIG. 8 is a captured wall rock surface image;
FIG. 9 is a grayscale image of a collected wall rock surface image;
FIG. 10 is an image after histogram equalization;
FIG. 11 is an image after Gaussian smoothing;
fig. 12 is a grayscale image obtained after sharpening;
FIG. 13 is a schematic view of plastering treatment of the inner wall of a burr hole.
Detailed Description
Currently, the roughness of rock surfaces and concrete surfaces is mostly done on small-scale, laboratory test pieces. And the existing sand filling method can not adapt to the vertical surface of the rock on the tunnel construction site, and the scale range of the laser scanning method has limitation. The method for judging the surface roughness of the tunnel cavern surrounding rock has the characteristics of large scale and vertical surface, and an effective quantitative measurement method is not available. As shown in fig. 1, the method includes:
a method for measuring the roughness of surrounding rocks in a tunnel construction site comprises the following steps:
step 1, collecting surrounding rock surface images of partial areas of the inner wall of a tunnel formed by tunnel excavation to obtain surrounding rock surface images of the partial areas;
step 4, performing plastering treatment on the area subjected to the surrounding rock image acquisition, and calculating the average depth of the roughness of the surrounding rock surface of the area subjected to the surrounding rock image acquisition;
and 5, calculating a standard deviation of roughness depth according to the area ratio of the different color areas, determining a normal distribution function of the surface roughness of the tunnel surrounding rock based on the standard deviation and the average depth of the rock surface roughness, and obtaining quantitative evaluation of the surface roughness of the tunnel surrounding rock.
Specifically, as shown in fig. 2, the surrounding rock surface image acquisition in step 1 includes the following steps;
step 12, pushing the device bottom plate to the inner wall of the hole through a push rod and pushing the device bottom plate to move along the inner wall of the hole;
and step 13, controlling the push rod CCD device to collect surrounding rock surface images of the inner wall of the tunnel through an image collection button on the push rod.
As shown in fig. 3, 4, 5 and 6, a surrounding rock image collecting device specially used for collecting surrounding rock surface images of the inner wall of the tunnel can be formed through steps 10 to 13, the device comprises a device bottom plate 3, a CCD device 4 used for collecting images of the inner wall of the tunnel and a spacing structure used for keeping the distance between the CCD device 4 and the inner wall of the tunnel constant are arranged on one side of the device bottom plate 3 facing the inner wall of the tunnel, in the embodiment, 4 support rods 10 with the same length are adopted as the spacing structure, rollers 2 are fixed at the end parts of the support rods 10, push rods 7 capable of rotating relative to the device bottom plate 3 are fixed on the other side of the device bottom plate 3 through rotating shafts 5, preferably, the push rods 7 are of a telescopic structure, the rollers 2 can be abutted against the inner wall 1 of the tunnel through the push rods 7 and can be pushed to move on the inner wall of the tunnel, image collecting buttons 8 capable of controlling the CCD device to collect images are arranged on the push rods, the acquisition of the surrounding rock image of the inner wall of the tunnel can be realized by pressing an image acquisition button 8, a light supplement lamp 6, a storage battery 11 and other devices are also arranged on a device bottom plate and used for providing sufficient light for the image acquisition process, the distance between a CCD device and the rock surface can be ensured to be fixed by arranging a spacing structure due to the arc structure of the tunnel rock surface, so that the focal length is stable, the definition of the image acquisition is ensured, the light supplement lamp button 9 capable of controlling the light supplement lamp to work is also arranged on a push rod, the control of the light supplement lamp can be realized, in the embodiment, in order to ensure that a camera in the CCD device is convenient to install and disassemble, the CCD device comprises a box body structure with an opening at the front end formed by an upper baffle 4-8, a lower baffle 4-2, a left baffle 4-9, a right baffle 4-10 and a rear baffle 4-1, a fixed baffle 4-6 and a squeezing plate 4-7 are fixed at, the fixed baffle 4-6 is fixed on the lower baffle 4-2, the fixed baffle is provided with a connecting rod 4-3, the connecting rod 4-3 is provided with an extrusion plate 4-7, a spring 4-4 is arranged between the fixed baffle 4-6 and the extrusion plate 4-7, the spring can push the extrusion plate to move towards the inner side of the box body, the fixed baffle is provided with a through hole, one end of the connecting rod penetrates through the through hole, extends out of the box body structure and is fixed with a handle 4-5, the extrusion plate can be pulled from the outer side of the fixed baffle and compresses the spring, after the handle is loosened, the extrusion plate moves towards the inner side of the box body under the restoring force of the spring, and the extrusion and fixation of a camera arranged in the. The camera can be quickly installed in the box body or taken out of the box body through the device, and the safety of the camera in the image acquisition process is protected.
As shown in fig. 6, the push rod and the CCD device are respectively fixed on both sides of the device bottom plate, and a spacer device for keeping the distance between the CCD device and the inner wall of the tunnel constant is fixed on one side where the CCD device is arranged, the device B is pressed against the inner wall of the tunnel where the surrounding rock image acquisition area needs to be performed through the push rod, and according to the CCD photographing coverage area, the device (area a in the figure) is firstly pushed circumferentially from one side to the other side along the inner wall of the tunnel, and images are sequentially acquired until the entire tunnel circumference area is completely acquired by the first ring; then, the rock face of the adjacent 2 nd ring is subjected to parallel movement along the axial direction, and image acquisition is carried out; and the analogy is carried out in sequence to cover the whole area of the inner side of the rock surface to be collected.
Further, as shown in fig. 7, the step 2 includes the following steps:
step 20, performing histogram equalization processing on the surrounding rock surface image to obtain a histogram equalized image; the basic idea of the histogram is to make some mapping transformation on the pixel gray scale of the original image, so that the probability density of the transformed image gray scale is uniformly distributed. This means that the dynamic range of the image gray scale is increased, and the contrast of the image is improved. By the technology, the distribution situation of the image brightness can be clearly seen on the histogram, and the image brightness can be adjusted according to the requirement. The image is divided into a plurality of subblocks, and histogram equalization is respectively carried out on the subblocks, so that the local contrast of the image is effectively enhanced.
Step 21, performing Gaussian smoothing processing on the histogram equalization image to obtain a Gaussian smoothing processed image; in the image generation, transmission and reproduction process, noise interference or data loss often occurs for various reasons, which requires an image smoothing algorithm. The image Gaussian smoothing is also a method for smoothing an image by the idea of neighborhood averaging, a Gaussian filter with adjustable smoothing scale and template size is designed, and in the image Gaussian smoothing, pixels at different positions are endowed with different weights when the image is averaged. A better noise removal effect is obtained. A gaussian smoothing process is used.
Step 22, carrying out sharpening processing on the Gaussian smooth processed image to obtain a sharpened processed image; the image smoothing often blurs the boundaries and contours in the image, and in order to reduce the influence of such adverse effects, it is necessary to use an image sharpening technology to sharpen the edges of the image. The laplacian sharpening can strengthen the edge characteristics of the image, so that the edge information of the image is more obvious. The invention employs laplace sharpening.
And step 23, carrying out image edge detection on the sharpened image to obtain the gray-scale image. In a digital image, an edge refers to a portion where local changes of the image are most significant, and is a discontinuity of local characteristics of the image, such as a sudden change in gray scale, an icon of a texture structure, and the like. The means of extracting these features is called edge feature extraction or edge detection. The edge detection operators are various, wherein the Canny operator is an improved operator, a multi-stage edge detection algorithm is adopted, false alarms generated by noise can be reduced as much as possible, and the effect that the detected edge is close to the actual edge to the maximum extent can be achieved.
Further, the area ratio of the different color regions is calculated by using formula (1):
in the formula: m isiM is the sum of areas divided into regions of the same color zoneARepresenting the area of the region where the surrounding rock image acquisition is performed, PiThe sum of the areas of the regions divided into the same color interval is in proportion to the area of the region for surrounding rock image acquisition.
Further, the step 4 includes the following steps of performing plastering treatment on the region where the surrounding rock image is acquired, leveling the plastering surface with a scraper blade and the highest point of the rock surface, calculating the area a of the region where plastering is performed and the volume V of the plastering material used for performing plastering treatment on the region, and calculating the average depth h of the roughness of the surrounding rock surface by adopting a formula (2):
further, the step 5 includes the steps of,
the step 5 includes the following steps of finding out the region with the largest area ratio of the color region according to the characteristics of the normal distribution model, obtaining the area ratio Pimax of the color region, and calculating the standard deviation according to the formula (3):
according to the standard deviation, calculating a normal distribution model of the proportion of different depths of the surface roughness of the tunnel surrounding rock by a formula (4):
in the formula: hi is the depth value of the roughness of the surface of the surrounding rock corresponding to different color areas, and the corresponding relation between the gray value and the depth value needs to be calibrated before measurement. The calibration method comprises the following steps: selecting a small rock surface to be measured, respectively measuring the roughness depth by using a laser scanner (or a roughness measuring instrument), comparing the roughness depth with the gray level acquisition picture of the same rock surface position, and obtaining the corresponding relation between the roughness depth and the gray level value, thereby realizing quantitative evaluation of the surface roughness of the tunnel surrounding rock.
The method better reflects the roughness of the surface of the tunnel surrounding rock, judges the bonding performance of the surrounding rock interface according to the roughness of the surface of the surrounding rock, can effectively reduce the waste caused by the falling of the sprayed concrete, simultaneously ensures that the formed supporting structure reaches the preset design strength, ensures the safe implementation of later construction, and plays a better guiding role in the construction of engineering.
The following embodiments are further described in the present disclosure:
example 1: by utilizing the method and the device for measuring the surrounding rock roughness of the tunnel construction site, the surface roughness quantification of the two surrounding rocks of the cavern in the construction process of the No. 5 linear tunnel in the large continuous area is evaluated, and by adopting the surrounding rock surface picture acquisition device, the acquisition of the picture of the rough surface of the surrounding rock in the specific area of the tunnel is realized by keeping the distance constant by abutting the inner wall of the cavern, as shown in figure 8; in order to reduce the influence of a series of external factors such as illumination on the original image and provide more essential information for the original image, the acquired image is converted into a gray image as shown in fig. 9; in order to avoid that the contrast range is too large and cannot be processed due to too high probability of occurrence of certain colors, the dynamic range of the image needs to be expanded, and histogram equalization processing is performed on the gray level image, so that the contrast, gray level and definition of the image are improved, as shown in fig. 10; in order to reduce the influence of noise occurring during photographing on the quality of an image, the image is subjected to gaussian smoothing processing, as shown in fig. 11; in order to highlight the boundary and other detailed information of the image and improve the accuracy of edge detection, the image is sharpened, in order to detect important and prominent lines, contours and the like in the image and remove edges with excessive details, so that the gray contrast of the image is further improved, the image is subjected to edge detection by using Canny operator, and after the image is acquired on site and processed, the gray image of the acquired image on site is obtained, as shown in fig. 12.
And (3) performing field plastering treatment on the picture acquisition area (the area D in the figure) by adopting a plastering method, wherein a plastering plane (shown in the figure C) is flush with the highest point (the point E in the figure) of the convex part of the rough surface of the surrounding rock, as shown in figure 13. In the field plastering process, the volume of the cement is determined to be 0.25m3The plastering plane area is 10.2m2And determining the average depth h of the rough surface of the surrounding rock to be 24.5 mm. According to the color depth of the gray image, the area ratio of the white, light gray, dark gray and black areas is determined to be 7.2%, 12.5%, 64.3%, 10.8% and 5.2% in sequence.
Determining a tunnel surrounding rock surface roughness normal distribution model:
the quantitative evaluation of the surface roughness is carried out on two measuring surrounding rocks of the hair tunnel in the construction process of the No. 5 tunnel in the large continuous area, the roughness of the surface of the tunnel surrounding rock is better reflected, the judgment is made on the bonding performance of a surrounding rock interface according to the roughness of the surface of the surrounding rock, the waste caused by the falling of sprayed concrete is effectively reduced, meanwhile, the formed supporting structure is ensured to reach the preset design strength, the safe implementation of later-stage construction is ensured, and a better guiding effect is played for the construction of engineering.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (6)
1. A method for measuring the roughness of surrounding rocks in a tunnel construction site is characterized by comprising the following steps: the method comprises the following steps:
step 1, collecting surrounding rock surface images of partial areas of the inner wall of a tunnel formed by tunnel excavation to obtain surrounding rock surface images of the partial areas;
step 2, carrying out gray level processing on the surrounding rock surface image to obtain a gray level image;
step 3, according to the color depth of the gray level image, dividing the color area of the gray level image, and calculating the area ratio of different color areas;
step 4, performing plastering treatment on the area subjected to the surrounding rock image acquisition, and calculating the average depth of the roughness of the surrounding rock surface of the area subjected to the surrounding rock image acquisition;
and 5, calculating a standard deviation of roughness depth according to the area ratio of the different color areas, determining a normal distribution function of the surface roughness of the tunnel surrounding rock based on the standard deviation and the average depth of the rock surface roughness, and obtaining quantitative evaluation of the surface roughness of the tunnel surrounding rock.
2. The method for measuring the roughness of the surrounding rock on the tunnel construction site according to claim 1, wherein the method comprises the following steps: the surrounding rock surface image acquisition in the step 1 comprises the following steps;
step 10, mounting a CCD device for image acquisition on one side of a device bottom plate, and mounting a push rod which can rotate relative to the device bottom plate on the other side of the device bottom plate;
step 11, mounting a spacing structure for keeping the distance between the CCD device and the inner wall of the hole constant on one side of a device bottom plate on which the CCD device is mounted, and fixing a roller at one end of the spacing structure facing the inner wall of the hole;
step 12, pushing the device bottom plate to the inner wall of the hole through a push rod and pushing the device bottom plate to move along the inner wall of the hole;
and step 13, controlling the push rod CCD device to collect surrounding rock surface images of the inner wall of the tunnel through an image collection button on the push rod.
3. The method for measuring the roughness of the surrounding rock on the tunnel construction site according to claim 1, wherein the method comprises the following steps: the step 2 comprises the following steps:
step 20, performing histogram equalization processing on the surrounding rock surface image to obtain a histogram equalized image;
step 21, performing Gaussian smoothing processing on the histogram equalization image to obtain a Gaussian smoothing processed image;
step 22, carrying out sharpening processing on the Gaussian smooth processed image to obtain a sharpened processed image;
and step 23, carrying out image edge detection on the sharpened image to obtain the gray-scale image.
4. The method for measuring the roughness of the surrounding rock on the tunnel construction site according to claim 1, wherein the method comprises the following steps: the area ratio of the different color regions is calculated by formula (1):
in the formula: m isiM is the sum of areas divided into regions of the same color zoneARepresenting the area of the region where the surrounding rock image acquisition is performed, PiThe sum of the areas of the regions divided into the same color interval is in proportion to the area of the region for surrounding rock image acquisition.
5. The method for measuring the roughness of the surrounding rock on the tunnel construction site according to claim 4, wherein the method comprises the following steps: step 4 includes the following steps of performing plastering treatment on the area where the surrounding rock image is acquired, leveling the plastering surface with a scraper blade and the highest point of the rock surface, calculating the area A of the area where plastering is performed and the volume V of a plastering material used for performing plastering treatment on the area, and calculating the average depth h of roughness of the surrounding rock surface by adopting a formula (2):
6. the method for measuring the roughness of the surrounding rock on the tunnel construction site according to claim 5, wherein the method comprises the following steps: the step 5 includes the following steps of finding out the region with the largest area ratio of the color region according to the characteristics of the normal distribution model, obtaining the area ratio Pimax of the color region, and calculating the standard deviation according to the formula (3):
according to the standard deviation, calculating a normal distribution model of the proportion of different depths of the surface roughness of the tunnel surrounding rock by a formula (4):
in the formula: h isiAnd the roughness of the surface of the surrounding rock corresponding to the different color areas is obtained, so that the quantitative evaluation of the roughness of the surface of the surrounding rock of the tunnel is realized.
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| KR100636000B1 (en) * | 2004-11-24 | 2006-10-18 | 손호웅 | Remote Roughness Measurement Method for Discontinuities of Rock Mass by Laser Scanning and System of The Same |
| KR200375453Y1 (en) * | 2004-11-25 | 2005-03-08 | (주)죽림엔지니어링 | Remote Roughness Measurement System for Discontinuities of Rock Mass by Laser Scanning |
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