A tunnel crack identification method and system based on grayscale gain mapping

Abstract

The present invention belongs to the field of tunnel disease detection and provides a method and system for identifying tunnel cracks based on grayscale gain mapping. The scheme includes: establishing an adaptive temperature gradient based on an uneven isothermal gradient zone and performing global grayscale mapping. The highest grayscale pixel point of the grayscale image is extracted, and the edge shape of the pixel group is obtained through an edge detection algorithm to identify the form of lining cracks; then, through a traversal algorithm, the highest grayscale pixel point of the grayscale image is extracted, the center point pixel coordinates are indexed, and converted into the precise coordinate position of the defect. The present invention can significantly enhance the image recognition of lining crack areas and filter out invalid water trace areas, thereby improving the speed and accuracy of lining crack detection and realizing the identification and positioning of water leakage tunnel cracks.

Description

Technical Field

[0001] The present invention belongs to the field of tunnel disease detection, and in particular relates to a tunnel crack damage identification method and system based on grayscale gain mapping. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] During operation, tunnel linings are affected by factors such as material degradation and operational load disturbances, making them prone to varying degrees of cracking. Cracked linings are the direct cause of tunnel leakage. Due to the difference in thermal conductivity between concrete and water, a temperature difference will occur between the leaking area of ​​the tunnel and the surrounding dry area. As a non-contact measurement device, infrared thermal imagers are sensitive to temperature, have a short response time, and are not affected by external light. Therefore, infrared thermal imagers can easily detect surface water marks in leaking tunnels. However, infrared thermal imager images have the disadvantages of poor contrast and high image noise, which causes tiny cracks in the tunnel lining to be masked by image noise. Therefore, infrared images cannot identify and locate cracks in the tunnel lining in the water mark area.

[0004] Patent CN201910856676.3 uses temperature information in infrared thermal images to correct the regional contours extracted from visible light images, and finally calculates the regional area, solving the problem of inaccurate identification of existing water leakage areas; Application No. CN201810373105.X uses the principle of thermal imaging to see the existence and development of lining water damage, and then discovers the existing problems through manual identification; Application No. CN202010483449.3 provides a method for detecting and identifying tunnel water leakage areas based on the fusion of infrared and visible light images; Application No. CN202010264560.3 uses visible light imaging combined with thermal infrared multi-spectral images to accurately identify and quantitatively analyze water leakage target points;

[0005] The above schemes all use tunnel water leakage detection based on infrared thermal imagers and are all aimed at detecting the water leakage area. In order to find out the lining crack damage in the water leakage area, manual intervention or the participation of other instruments and equipment is still required. Summary of the Invention

[0006] To address at least one of the technical issues presented in the aforementioned background technology, the present invention provides a tunnel crack identification method and system based on grayscale gain mapping. This method establishes an adaptive temperature gradient based on non-uniform isothermal gradient zones and performs global grayscale mapping. This method extracts the highest grayscale pixel in the grayscale image and uses an edge detection algorithm to determine the edge shape of the pixel group, thereby identifying the form of the lining crack. A traversal algorithm then extracts the highest grayscale pixel in the grayscale image, indexes the center pixel coordinates, and converts them into the precise coordinate location of the defect. This method significantly enhances image recognition of lining crack areas and filters out invalid watermarks, improving the speed and accuracy of lining crack detection and enabling the identification and location of cracks in leaking tunnels.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A first aspect of the present invention provides a tunnel crack damage identification method based on grayscale gain mapping, comprising the following steps:

[0009] Obtain infrared images of water leakage areas in tunnels;

[0010] Based on the infrared image of the tunnel water leakage area, according to the temperature gradient diffusion trend of the tunnel water leakage area, the coordinates of the temperature extreme value pixels under the corresponding trend are extracted;

[0011] The pixel temperature of the core area of ​​the leakage area is extracted based on the coordinates of the temperature extreme pixel points under the corresponding trend. The global temperature gradient is extracted based on the pixel temperature of the core area of ​​the leakage area. The global temperature field gradient grayscale mapping gain factor is established according to the grayscale division based on the global temperature gradient. The gain grayscale mapping image of the global temperature field under the corresponding trend is constructed through the global temperature field gradient grayscale mapping gain factor.

[0012] The pixel with the highest grayscale level in the gain grayscale mapping image of the global temperature field is extracted, and the real coordinates of the cracked tunnel and the form of lining crack damage are obtained based on the pixel.

[0013] A second aspect of the present invention provides a tunnel crack identification system based on grayscale gain mapping, comprising:

[0014] An image acquisition module, which is used to acquire infrared images of the tunnel water leakage area;

[0015] An extreme value extraction module is used to extract the coordinates of the temperature extreme value pixels under the corresponding trend based on the infrared image of the tunnel water leakage area and the temperature gradient diffusion trend of the tunnel water leakage area;

[0016] A grayscale gain mapping module is used to extract the pixel temperature of the core area of ​​the leakage area based on the coordinates of the temperature extreme value pixel points under the corresponding trend, extract the global temperature gradient based on the pixel temperature of the core area of ​​the leakage area, establish the global temperature field gradient grayscale mapping gain factor according to the grayscale division based on the global temperature gradient, and construct the gain grayscale mapping image of the global temperature field under the corresponding trend through the global temperature field gradient grayscale mapping gain factor;

[0017] The crack damage identification module is used to extract the pixel point with the highest gray level in the gain gray scale mapping image of the global temperature field, and obtain the real coordinates of the cracked tunnel and the lining crack damage form based on the pixel point.

[0018] A third aspect of the present invention provides a computer-readable storage medium.

[0019] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the tunnel crack damage identification method based on grayscale gain mapping as described in the first aspect above.

[0020] A fourth aspect of the present invention provides a computer device.

[0021] A computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the tunnel crack damage identification method based on grayscale gain mapping as described in the first aspect above are implemented.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] Based on the uneven temperature gradient distribution in the lining leakage area, the present invention enhances the image recognition of the lining crack area through infrared image grayscale gain mapping, thereby realizing lining crack identification; and realizes the precise positioning of lining cracks by extracting and indexing the coordinates of crack-related pixels through clear grayscale images.

[0024] The present invention extracts the temperature core area of ​​the water leakage area; that is, in the grayscale gain mapping process, the grayscale of most areas is 0, including some water mark areas, and no further identification is required in the edge detection or positioning steps. The redundant and invalid infrared thermal imaging data of the water mark area in the tunnel water leakage area is indirectly filtered out, which greatly reduces the workload of image analysis and improves the image recognition efficiency.

[0025] Advantages of additional aspects of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0027] Figure 1 Schematic diagram of the overall process of a method for identifying crack damage in a leaking tunnel according to a first embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of a lining crack shape recognition process according to a first embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of the real coordinates of a crack in Example 1 of the present invention;

[0030] Figure 4(a)-Figure 4(d) This is a crack damage detection test diagram and its display effect diagram through adaptive temperature gradient global grayscale mapping according to embodiment 1 of the present invention;

[0031] Figure 5(a)-Figure 5(d) This is a water mark detection test chart and its display effect chart through adaptive temperature gradient global grayscale mapping according to the first embodiment of the present invention;

[0032] Figure 6 This is an example diagram of the lowest temperature pixel extraction and temperature gradient of infrared thermal images;

[0033] Figure 7(a)-Figure 7(c) A tunnel crack damage identification and display effect diagram based on grayscale gain mapping provided by an embodiment of the present invention;

[0034] Figure 8(a)-Figure 8(d) This is a tunnel crack location display effect diagram based on grayscale gain mapping provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0036] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0037] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0038] Because water's specific heat capacity is greater than that of concrete, when water flows out of a cracked lining, it rapidly diffuses across the lining surface due to capillary diffusion and continuously exchanges heat with the air and lining, forming distinct temperature gradient zones in the water-marked areas of the lining surface. Because water continuously releases and absorbs heat during diffusion, the temperature gradient distribution is uneven, with the isothermal gradient lines becoming denser closer to the cracked area.

[0039] To address this issue, the present invention proposes a tunnel crack identification method based on grayscale gain mapping. This approach extracts the core temperature zone based on the non-uniform isothermal gradient region, establishes a grayscale gain factor, and performs global grayscale mapping. This extracts the highest grayscale pixel in the grayscale image and uses an edge detection algorithm to determine the edge shape of the pixel group, thereby identifying the form of the lining crack. A traversal algorithm then extracts the highest grayscale pixel in the grayscale image, indexes the center pixel coordinates, and converts them into the precise coordinate location of the defect. This method significantly enhances image recognition of lining crack areas and filters out invalid watermarks, improving the speed and accuracy of lining crack detection and enabling the identification and location of cracks in leaking tunnels.

[0040] Example 1

[0041] Reference Figure 1 This embodiment provides a tunnel crack damage identification method based on grayscale gain mapping, comprising the following steps:

[0042] Step 1: Obtain an infrared image of the tunnel water leakage area;

[0043] In step 1, the infrared image of the tunnel water leakage area is collected by an infrared thermal imager, such as Figure 4(a)-Figure 4(d) As shown, Figure 4(a) shows the actual cracked lining, Figure 4(b) shows the low-temperature water test, Figure 4(c) shows the high-temperature water test, and Figure 4(d) shows the high-temperature water high-flow rate test. Step 2: Based on the infrared image of the tunnel leakage area and the temperature gradient diffusion trend of the tunnel leakage area, the coordinates of the temperature extreme pixel points corresponding to the trend are extracted;

[0044] In step 2, extracting the coordinates of the temperature extreme pixel points corresponding to the temperature gradient diffusion trend in the tunnel water leakage area includes:

[0045] If the temperature increases along the water trace toward the dry area, the extracted temperature extreme point is the lowest temperature of the infrared image;

[0046] If the temperature decreases along the water trace toward the dry area, the extracted temperature extreme point is the highest temperature of the infrared image;

[0047] The pixel point can directly obtain the coordinates and temperature value of the pixel point by querying the water mark area through the traversal algorithm.

[0048] Step 3: Extract the pixel temperature of the core area of ​​the leakage area based on the coordinates of the temperature extreme value pixels under the corresponding trend, extract the global temperature gradient based on the pixel temperature of the core area of ​​the leakage area, establish the global temperature field gradient grayscale mapping gain factor according to the grayscale division based on the global temperature gradient, and construct the gain grayscale mapping image of the global temperature field under the corresponding trend through the global temperature field gradient grayscale mapping gain factor;

[0049] In step 3, extracting the pixel temperature of the core area of ​​the leakage area based on the pixel coordinates of the temperature extreme value includes:

[0050] The pixel point passing the temperature extreme value is intercepted perpendicular to the temperature gradient expansion direction, wherein the temperature gradient expansion direction is the shortest straight line direction connecting the extreme value point between the two isothermal circles outside the temperature extreme value pixel.

[0051] Figure 6 For the infrared thermal image minimum temperature pixel extraction and temperature gradient example, refer to Figure 6 , the temperature gradient of the infrared thermal image diffuses, the pixel point section is the central axis, and it expands to both sides until the sum of the pixels in the area accounts for 1% of the total pixels × focal length / 1.5, completing the temperature core area extraction of the leakage area.

[0052] Therefore, the extraction of the temperature core area of ​​the leakage water area is calculated based on the focal length, that is, under 32° (H) × 24° (V) (standard lens), the value is taken as 1% × focal length / 1.5.

[0053] In step 3, the global temperature gradient is extracted based on the pixel temperature of the temperature core area of ​​the leaking water area, that is, the global temperature gradient is extracted based on the mean square error of the maximum and minimum values ​​of the temperature core area of ​​the leaking water area, specifically including: judging whether the temperature difference between the maximum and minimum values ​​of the temperature core area is greater than or equal to the temperature threshold; if so, extracting the temperature gradient according to a five-term arithmetic progression; otherwise, extracting the temperature gradient according to a three-term arithmetic progression;

[0054] In this embodiment, the temperature threshold is set to 1°C.

[0055] It is expressed as follows:

[0056] If the temperature difference between the maximum and minimum values ​​in the temperature core area is ≥1°C, then press a n =a1+(n-1)*d, 1≤n≤5;

[0057] If the temperature difference is less than 1℃, press a n =a1+(n-1)*d, 1≤n≤3 extract temperature gradient;

[0058] Wherein, d is the maximum and minimum temperature difference. In step 3, a global temperature field gradient grayscale mapping gain factor is established based on the global temperature gradient according to the grayscale division, and a gain grayscale mapping image of the global temperature field under the corresponding trend is constructed by the global temperature field gradient grayscale mapping gain factor, specifically including:

[0059] According to the number of temperature gradient items minus 1, it is divided into 255 gray levels, and gray β = 255 / n max-1 ×(n-1) establish β max =n max Gray gain factor;

[0060] If the extreme temperature of the infrared image is the lowest temperature, then

[0061] If the extreme temperature of the infrared image is the highest temperature, then

[0062] Among them, gray β1=0, gray β max =255,a min The meaning is the lowest temperature in the core area, pixel X 温度 The meaning is the temperature of the infrared thermal image pixel, a max The meaning of is the highest temperature in the temperature core area, and gray β is the grayscale value of the pixel point in the corresponding temperature gradient.

[0063] In order to explain the above solution more clearly, the following is described in detail with reference to specific embodiments:

[0064] Assuming that the temperature extreme value of the infrared image is the highest temperature, if the extracted arithmetic progression temperature gradient is a five-term arithmetic progression, then 255 grayscales are divided into four parts, and a grayscale gain factor is established. That is, the grayscale mapping of the pixel point temperature in the infrared image lower than the first temperature (the lowest temperature in the core area) is 0, and the pixel points in the remaining four temperature gradients are grayscaled 65, 130, 195, and 255 respectively, to construct a gain grayscale mapping image of the global temperature field;

[0065] If the temperature gradient is a three-term arithmetic progression, it is divided into two parts with 255 grayscales, and a grayscale gain factor is established. That is, the grayscale of the pixel point in the infrared image whose temperature is lower than the first temperature is 0, and the pixels in the remaining two temperature gradients take grayscale values ​​of 130 and 255 respectively to construct a gain grayscale mapping image of the global temperature field.

[0066] On the contrary, assuming that the temperature extreme value of the infrared image is the lowest temperature, the grayscale mapping of the pixel point in the infrared image with a temperature higher than the first temperature (the highest temperature in the core area) is 0, and the remaining gradients are mapped in sequence.

[0067] Figure 5(a) shows the visible light image of the leaking lining. Figure 5(b)-Figure 5(d) Shown is a gain grayscale map image of the global temperature field.

[0068] Step 4: Extract the pixel with the highest grayscale level in the gain grayscale mapping image of the global temperature field, and obtain the real coordinates of the cracked tunnel and the form of lining crack damage based on the pixel.

[0069] The method for obtaining the lining crack damage form based on the pixel point with the highest gray level is: obtaining the edge shape of the pixel group through the edge detection algorithm, thereby identifying the lining crack damage form.

[0070] This embodiment does not specifically limit the edge detection algorithm. For example, the Canny edge detection algorithm may be used.

[0071] like Figure 7(a)-Figure 7(c) As shown in the figure, the boundary of the detected image is circular, which is very similar to the actual crack.

[0072] In step 4, obtaining the real coordinates of the damaged tunnel based on the pixel with the highest gray level specifically includes:

[0073] Use the for_each traversal algorithm to extract the pixel with the highest grayscale level in the grayscale image and index the two-dimensional array coordinates of the pixel;

[0074] Based on the maximum and minimum X and Y array coordinates of the pixel points, index the center point pixel array coordinates, such as Figure 6 The pixel array coordinates on the left are shown;

[0075] Based on the size of a single pixel, the formula Get the actual side length of a single pixel, S 图像 The area of ​​the infrared image obtained by the initial shooting is then calculated by the formula X 实际坐标 =L 单像素 ×X 数组坐标 ; Y 实际坐标 =L 单像素 ×Y 数组坐标转 The coordinates of the crack in the infrared image are converted to the coordinates of the crack. Finally, the real coordinates of the crack in the tunnel can be obtained according to the real tunnel coordinates of the infrared detection image, such as Figure 8(a)-Figure 8(d) shown.

[0076] The advantage of the above scheme is that, based on the uneven temperature gradient distribution in the lining leakage area, the scheme enhances the image recognition of the lining crack area through adaptive temperature gradient global grayscale mapping, thereby realizing lining crack identification; and realizes precise positioning of lining cracks by extracting and indexing the coordinates of crack-related pixels through clear grayscale images.

[0077] Example 2

[0078] This embodiment provides a system for identifying cracks in leaking tunnels based on global grayscale mapping, including:

[0079] An image acquisition module, which is used to acquire infrared images of the tunnel water leakage area;

[0080] An extreme value extraction module is used to extract the coordinates of the temperature extreme value pixels under the corresponding trend based on the infrared image of the tunnel water leakage area and the temperature gradient diffusion trend of the tunnel water leakage area;

[0081] A grayscale gain mapping module is used to extract the pixel temperature of the core area of ​​the leakage area based on the coordinates of the temperature extreme value pixel points under the corresponding trend, extract the global temperature gradient based on the pixel temperature of the core area of ​​the leakage area, establish the global temperature field gradient grayscale mapping gain factor according to the grayscale division based on the global temperature gradient, and construct the gain grayscale mapping image of the global temperature field under the corresponding trend through the global temperature field gradient grayscale mapping gain factor;

[0082] The crack damage identification module is used to extract the pixel point with the highest gray level in the gain gray scale mapping image of the global temperature field, and obtain the real coordinates of the cracked tunnel and the lining crack damage form based on the pixel point.

[0083] Example 3

[0084] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of the method for identifying cracks in a leaking tunnel based on global grayscale mapping as described in the first embodiment above are implemented.

[0085] Example 4

[0086] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method for identifying cracks in a leaking water tunnel based on global grayscale mapping as described in the first embodiment above are implemented.

[0087] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage and optical storage, etc.) containing computer-usable program code.

[0088] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0089] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0090] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0091] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware through a computer program. The program can be stored in a computer-readable storage medium, and when executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0092] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A tunnel crack damage identification method based on grayscale gain mapping, characterized in that: The steps include: Obtain infrared images of water leakage areas in tunnels; Based on the infrared image of the tunnel water leakage area, according to the temperature gradient diffusion trend of the tunnel water leakage area, the coordinates of the temperature extreme value pixels under the corresponding trend are extracted; The pixel temperature of the core area of ​​the leakage area is extracted based on the coordinates of the temperature extreme pixel points under the corresponding trend. The global temperature gradient is extracted based on the pixel temperature of the core area of ​​the leakage area. The global temperature field gradient grayscale mapping gain factor is established according to the grayscale division based on the global temperature gradient. The gain grayscale mapping image of the global temperature field under the corresponding trend is constructed through the global temperature field gradient grayscale mapping gain factor. Extract the pixel with the highest grayscale level in the gain grayscale mapping image of the global temperature field, and obtain the real coordinates of the cracked tunnel and the form of lining crack damage based on the pixel with the highest grayscale level; Among them, the global temperature gradient is extracted based on the mean square error of the maximum and minimum values ​​of the temperature core area of ​​the leakage water area; Based on the global temperature gradient, a global temperature field gradient grayscale mapping gain factor is established according to the grayscale division. The gain grayscale mapping image of the global temperature field under the corresponding trend is constructed by the global temperature field gradient grayscale mapping gain factor. Specifically, the following steps are performed: According to the number of temperature gradient items minus 1, it is divided into 255 gray levels. Establish grayscale gain factor; If the extreme temperature of the infrared image is the lowest temperature, then ; If the extreme temperature of the infrared image is the highest temperature, then ; in, n is the number of terms in the global temperature gradient, , Pixel X 温度 The meaning is the temperature of the infrared thermal image pixel point, gray β It is the grayscale value of the pixel in the corresponding temperature gradient.

2. The tunnel crack damage identification method based on grayscale gain mapping according to claim 1, characterized in that: The method of extracting the coordinates of the temperature extreme pixel points corresponding to the temperature gradient diffusion trend of the tunnel water leakage area based on the infrared image of the tunnel water leakage area includes: If the temperature increases along the water trace toward the dry area, the extracted temperature extreme point is the lowest temperature of the infrared image; If the temperature decreases along the water trace toward the dry area, the extracted temperature extreme point is the highest temperature of the infrared image.

3. The tunnel crack damage identification method based on grayscale gain mapping according to claim 1, characterized in that: The method for extracting the temperature core area of ​​the leakage area based on the coordinates of the temperature extreme value pixel points under the corresponding trend is: The pixel coordinates of the temperature extreme point are intercepted perpendicular to the direction of temperature gradient expansion; The temperature gradient expansion direction is the direction of the shortest straight line connecting the temperature extreme pixel point and the two isothermal circles outside the temperature extreme pixel point.

4. The tunnel crack damage identification method based on grayscale gain mapping according to claim 1, characterized in that: The calculation process of the mean square error of the maximum and minimum temperatures in the core area of ​​the leakage water area includes: Determine whether the temperature difference between the maximum and minimum values ​​of the temperature core area of ​​the leakage water area is greater than the set temperature threshold. If so, extract the temperature gradient according to the five-term arithmetic progression; otherwise, extract the temperature gradient according to the three-term arithmetic progression.

5. The tunnel crack damage identification method based on grayscale gain mapping according to claim 1, characterized in that: The actual coordinates of the cracked tunnel obtained based on the pixel point with the highest gray level specifically include: The two-dimensional array coordinates of the pixel indexed based on the highest grayscale pixel in the grayscale image; According to the maximum and minimum array coordinates in the two-dimensional array coordinates, index the center point pixel array coordinates; Get the actual side length of a single pixel based on the size of a single pixel; The coordinates of the center point pixel array and the actual side length of a single pixel are converted into the coordinate position of the crack in the infrared image. Combined with the real tunnel coordinates of the infrared detection image, the real coordinates of the crack in the tunnel are obtained.

6. A tunnel crack identification system based on grayscale gain mapping, characterized in that: A method for identifying tunnel cracks based on grayscale gain mapping according to any one of claims 1 to 5, comprising: An image acquisition module, which is used to acquire infrared images of the tunnel water leakage area; An extreme value extraction module is used to extract the coordinates of the temperature extreme value pixels under the corresponding trend based on the infrared image of the tunnel water leakage area and the temperature gradient diffusion trend of the tunnel water leakage area; A grayscale gain mapping module is used to extract the pixel temperature of the core area of ​​the leakage area based on the coordinates of the temperature extreme value pixel points under the corresponding trend, extract the global temperature gradient based on the pixel temperature of the core area of ​​the leakage area, establish the global temperature field gradient grayscale mapping gain factor according to the grayscale division based on the global temperature gradient, and construct the gain grayscale mapping image of the global temperature field under the corresponding trend through the global temperature field gradient grayscale mapping gain factor; The crack recognition module is used to extract the highest grayscale pixel point of the gain grayscale mapping image of the global temperature field, and obtain the real coordinates of the cracked tunnel and the lining crack form based on the highest grayscale pixel point.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the tunnel crack identification method based on grayscale gain mapping as claimed in any one of claims 1 to 5 are implemented.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the tunnel crack damage identification method based on grayscale gain mapping according to any one of claims 1 to 5 are implemented.

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