Pumped storage power station anti-seepage panel crack detection method and device and medium

Abstract

The invention discloses a pumped storage power station anti-seepage panel crack detection method and device and a medium. The method comprises the following steps: S1, acquiring a panel surface image to generate a to-be-detected image; s2, carrying out gray processing on the to-be-detected image and filtering noise; s3, traversing all pixel points of the to-be-detected image, comparing each to-be-detected pixel point with an adjacent pixel point, and calculating a reference value Z of gray level change of each to-be-detected pixel point; and S4, identifying a crack edge pixel point set. According to the method, crack detection can be efficiently and accurately carried out on the pumped storage power station impermeable panel structure by utilizing the change of the pixel point reference value, so that the crack detection efficiency is improved. The invention further discloses a pumped storage power station anti-seepage panel crack detection device and a medium.

Description

Technical Field

[0001] The present invention relates to the technical field of anti-seepage panel detection for pumped-storage power stations, and in particular to a method and device for detecting cracks in anti-seepage panels for pumped-storage power stations, and a computer-readable storage medium. Background Art

[0002] First of all, the anti-seepage panel of the reservoir bank is an important part of the dam of the pumped storage power station. It bears the huge pressure of the reservoir water body and the influence of environmental factors, including temperature changes, humidity changes, etc. The quality and performance of the panel are directly related to the safety and stability of the entire dam. Therefore, regular inspection of the anti-seepage panel of the reservoir bank is a necessary measure to ensure the safe operation of the power station dam. Secondly, during the operation of the power station, the anti-seepage panel of the reservoir bank may be affected by external forces such as circulating hydraulics, foundation surface constraints and natural environment, resulting in bulging, peeling, cracking and other diseases. These diseases not only affect the anti-seepage ability of the panel, but also may threaten the safe operation of the entire project. Therefore, timely detection and repair of these diseases are crucial to prevent further damage to the panel and ensure the safe operation of the power station. In addition, with the advancement of technology and the improvement of detection methods, advanced technologies such as non-destructive testing and radar detection have gradually been applied to the detection of anti-seepage panels of the reservoir bank. These technologies can more accurately detect minor defects and hidden dangers of the panel, providing more reliable protection for the safe operation of the power station.

[0003] In summary, the necessity of detecting cracks in the anti-seepage panel structure of a pumped storage power station is to ensure the safety and stability of the dam, prevent the panel from being damaged and affecting the operation of the project, and use advanced technology to more accurately evaluate the panel status. Regular inspection and timely repair can extend the service life of the power station and improve the economic and social benefits of the power station. Therefore, a detection technology for cracks in the anti-seepage panel structure of a pumped storage power station is proposed. Summary of the invention

[0004] In order to solve the technical problem of efficiently and accurately detecting cracks in the anti-seepage panel structure of a pumped storage power station, the embodiments of the present invention provide a method, device and computer-readable storage medium for detecting cracks in the anti-seepage panel of a pumped storage power station. The technical solution is as follows:

[0005] In a first aspect, a method for detecting cracks in an anti-seepage panel of a pumped storage power station is provided, the method comprising:

[0006] S1: collecting the panel surface image to generate an image to be detected;

[0007] S2: grayscale processing is performed on the image to be detected and noise is filtered;

[0008] S3: Traverse all the pixels of the image to be detected, compare each pixel to be detected with the adjacent pixels, and calculate the reference value Z of the grayscale change of each pixel to be detected. The calculation formula is as follows:

[0009]

[0010] Where n represents the number of adjacent pixels, M represents the total number of pixels to be tested in the panel surface image, and M i Represents the number of pixels adjacent to the pixel to be tested and with the same grayscale value, H i represents the grayscale value of the pixel points adjacent to the pixel point to be tested, and H represents the grayscale value adjacent to the pixel point to be tested;

[0011] S4: Identify the pixel points whose grayscale change reference value of the pixel points to be tested is greater than a predetermined threshold as suspected crack pixel points, form a set of pixel points with the same reference value as the suspected crack pixel points, and identify a continuous pixel point sequence in the set whose number is greater than a predetermined threshold as a crack edge pixel point set.

[0012] Optionally, the step S1 of collecting the panel surface image to generate the image to be detected includes:

[0013] S11: determining a flight route for aerial photography and shooting points on the flight route based on the laying position of the anti-seepage panel of the pumped-storage power station;

[0014] S12: determining the maximum distance between the flying device for aerial photography and the anti-seepage panel of the pumped-storage power station based on a preset minimum crack identification width;

[0015] S13: Generate the image to be detected.

[0016] Optionally, the grayscale processing and noise filtering of the image to be detected in step S2 includes:

[0017] S21: grayscale processing is performed on the image to be detected, so as to convert the color image into a single-channel gray image;

[0018] S22: In the image to be detected, a connected area of ​​a two-dimensional image consisting of an i×k pixel matrix is ​​extracted, and a Gaussian filter is used to perform linear optimization to filter noise in the two-dimensional image. The operation satisfies the function:

[0019]

[0020] Wherein, x and y are the horizontal and vertical coordinates of the pixel coordinates, λ and ξ represent the preset system compensation values ​​of the horizontal and vertical coordinates, δ represents the standard deviation, i and k represent the two-dimensional image composed of the i×k pixel matrix, and F() represents the linearly optimized two-dimensional Gaussian function;

[0021] S23: Performing an expansion operation on the image to be detected according to an image expansion formula to further remove noise:

[0022]

[0023] Where x and y represent the horizontal and vertical coordinates of the pixel coordinates, respectively, and θ represents the preset expansion coefficient. represents the dilation process, and F() represents the linearly optimized two-dimensional Gaussian function;

[0024] S24: performing an erosion operation on the image to be detected according to an image erosion formula:

[0025]

[0026] Among them, x and y represent the horizontal and vertical coordinates of the pixel coordinates respectively, θ represents the preset expansion coefficient, FΘG represents the corrosion process, and F() represents the linearly optimized two-dimensional Gaussian function.

[0027] Optionally, it also includes: S5: sorting each crack edge pixel point set from large to small according to the reference value, and combining the pixel point coordinate values ​​in each crack edge pixel point set according to the sequence to obtain the shape of the crack.

[0028] Optionally, the cracks include: transverse cracks, longitudinal cracks or annular cracks.

[0029] In a second aspect, a pumped storage power station anti-seepage panel crack detection device is provided, comprising:

[0030] An image acquisition module, used for acquiring the panel surface image to generate an image to be detected;

[0031] An image preprocessing module, used for performing grayscale processing on the image to be detected and filtering noise;

[0032] The calculation module traverses all the pixels of the image to be detected, compares each pixel to be detected with the adjacent pixels, and calculates the reference value Z of the grayscale change of each pixel to be detected. The calculation formula is as follows:

[0033]

[0034] Where n represents the number of adjacent pixels, M represents the total number of pixels to be tested in the panel surface image, and M i Represents the number of pixels adjacent to the pixel to be tested and with the same grayscale value, H i represents the grayscale value of the pixel points adjacent to the pixel point to be tested, and H represents the grayscale value adjacent to the pixel point to be tested;

[0035] The crack identification module is used to identify the pixel points whose grayscale change reference value of the pixel points to be tested is greater than a predetermined threshold as suspected crack pixels, to form a set of pixel points with the same reference value as the suspected crack pixels, and to identify a continuous sequence of pixel points in the set whose number is greater than a predetermined threshold as a crack edge pixel point set.

[0036] Optionally, the image preprocessing module further includes:

[0037] Grayscale processing module: grayscale processing is performed on the image to be detected, and the color image is converted into a single-channel gray image;

[0038] Noise filtering module: In the image to be detected, the connected area of ​​the two-dimensional image composed of the i×k pixel matrix is ​​extracted, and the noise in the two-dimensional image is filtered by linear optimization through the Gaussian filter. The operation satisfies the function:

[0039]

[0040] Wherein, x and y are the horizontal and vertical coordinates of the pixel coordinates, λ and ξ represent the preset system compensation values ​​of the horizontal and vertical coordinates, δ represents the standard deviation, i and k represent the two-dimensional image composed of the i×k pixel matrix, and F() represents the linearly optimized two-dimensional Gaussian function;

[0041] The image to be detected is expanded according to the image expansion formula to further remove noise:

[0042]

[0043] Where x and y represent the horizontal and vertical coordinates of the pixel coordinates, respectively, and θ represents the preset expansion coefficient. represents the dilation process, and F() represents the linearly optimized two-dimensional Gaussian function;

[0044] S24: performing an erosion operation on the image to be detected according to an image erosion formula:

[0045]

[0046] Among them, x and y represent the horizontal and vertical coordinates of the pixel coordinates respectively, θ represents the preset expansion coefficient, FΘG represents the corrosion process, and F() represents the linearly optimized two-dimensional Gaussian function.

[0047] Optionally, the crack identification module further includes: sorting each crack edge pixel point set from large to small according to the reference value, and combining the pixel point coordinate values ​​in each crack edge pixel point set according to the sequence to obtain the shape of the crack.

[0048] In a third aspect, an electronic device is provided, characterized in that the electronic device comprises: a processor; a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the above-mentioned method for detecting cracks in the anti-seepage panel of a pumped-storage power station is implemented.

[0049] In a fourth aspect, a computer-readable storage medium is provided, characterized in that a program code is stored in the computer-readable storage medium, and the program code is loaded by a processor and executes the above-mentioned method for detecting cracks in the anti-seepage panel of a pumped-storage power station.

[0050] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least: by utilizing the change of the pixel reference value, the cracks in the anti-seepage panel structure of the pumped storage power station can be detected efficiently and accurately, thereby improving the efficiency of crack detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 is a flow chart of a method for detecting cracks in an anti-seepage panel of a pumped storage power station shown in an exemplary embodiment of the present invention;

[0053] Figure 2 is a schematic block diagram of a pumped storage power station anti-seepage panel crack detection device according to an exemplary embodiment of the present invention;

[0054] Figure 3 It is a schematic structural diagram of an electronic device shown in an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0055] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0056] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0057] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0058] In the embodiments of the present invention, sometimes the subscripts such as W 1 It may be mistakenly written as a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0059] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0060] Specifically, an embodiment of the present invention provides a method for detecting cracks in an anti-seepage panel of a pumped storage power station. The method can utilize the change in pixel reference value to efficiently and accurately detect cracks in the anti-seepage panel structure of a pumped storage power station, thereby improving the efficiency of crack detection. Figure 1 The flowchart of the method 100 for detecting cracks in the anti-seepage panel of a pumped storage power station is shown. The processing flow of the method may include the following steps:

[0061] Step S1: Collect panel surface images, that is, collect panel surface images to generate images to be detected. For pumped storage power station anti-seepage panels, images can be collected for multiple panels separately, or images can be collected for one panel multiple times to generate an image set to be detected; the image to be detected can be manually selected from the image set to be detected.

[0062] In some exemplary embodiments of the present invention, step S1: collecting the panel surface image to generate a set of images to be detected, may include: step S11: determining the flight route of aerial photography and the shooting points on the flight route based on the laying position of the anti-seepage panel of the pumped-storage power station; step S12: determining the maximum distance between the flying device for aerial photography and the anti-seepage panel of the pumped-storage power station based on a pre-set minimum crack identification width; step S13: generating images to be detected.

[0063] Step S2: Image preprocessing, that is, grayscale processing and noise filtering of the image to be detected.

[0064] In some exemplary embodiments of the present invention, step S2: traversing each panel surface image in the image set to be detected to perform grayscale processing and filter noise may include:

[0065] Step S21: grayscale processing is performed on the image to be detected to convert the color image into a single-channel gray image;

[0066] Step S22: In the image to be detected, a connected area of ​​a two-dimensional image consisting of an i×k pixel matrix is ​​extracted, and a Gaussian filter is used to perform linear optimization to filter noise in the two-dimensional image. The operation satisfies the function:

[0067]

[0068] Wherein, x and y are the horizontal and vertical coordinates of the pixel coordinates, λ and ξ represent the preset system compensation values ​​of the horizontal and vertical coordinates, δ represents the standard deviation, i and k represent the two-dimensional image composed of the i×k pixel matrix, and F() represents the linearly optimized two-dimensional Gaussian function;

[0069] Step S23: Perform an expansion operation on the image to be detected according to the image expansion formula to further remove noise:

[0070]

[0071] Where x and y represent the horizontal and vertical coordinates of the pixel coordinates, respectively, and θ represents the preset expansion coefficient. represents the dilation process, and F() represents the linearly optimized two-dimensional Gaussian function;

[0072] Step S24: performing an erosion operation on the image to be detected according to the image erosion formula:

[0073]

[0074] Among them, x and y represent the horizontal and vertical coordinates of the pixel coordinates respectively, θ represents the preset expansion coefficient, FΘG represents the corrosion process, and F() represents the linearly optimized two-dimensional Gaussian function.

[0075] Step S3: Calculate the reference value, that is, traverse all the pixels of the image to be detected, compare each pixel to be detected with the adjacent pixels, and calculate the reference value Z of the grayscale change of each pixel to be detected. The calculation formula is as follows:

[0076]

[0077] Where n represents the number of adjacent pixels, M represents the total number of pixels to be tested in the panel surface image, and M i Represents the number of pixels adjacent to the pixel to be tested and with the same grayscale value, H irepresents the grayscale value of the pixel points adjacent to the pixel point to be tested, and H represents the grayscale value adjacent to the pixel point to be tested. Preferably, the points adjacent to the pixel point to be tested may be the pixel points surrounding the pixel point to be tested, for example, when the pixel point to be tested is located at the center, there may be at most 8 adjacent pixel points around it; when the pixel point to be tested is at the edge, there may be 3 or 5 adjacent pixel points around it.

[0078] Step S4: Identify cracks, that is, identify the pixels whose grayscale change reference value of the pixel to be tested is greater than a predetermined threshold as suspected crack pixels, form a set of pixels with the same reference value as the suspected crack pixels, and identify a continuous sequence of pixels in the set whose number is greater than a predetermined threshold as a crack edge pixel set.

[0079] In some exemplary embodiments of the present invention, the following may also be included: Step S5: sorting each crack edge pixel point set from large to small according to the reference value, and combining the pixel point coordinate values ​​in each crack edge pixel point set according to the order of the pixel point coordinate values ​​to obtain the shape of the crack.

[0080] In some exemplary embodiments of the present invention, the crack may include a transverse crack, a longitudinal crack or an annular crack.

[0081] Figure 2 1 is a schematic block diagram of a pumped storage power station anti-seepage panel crack detection device 200 according to an exemplary embodiment. The pumped storage power station anti-seepage panel crack detection device is characterized by comprising: an image acquisition module 202, an image preprocessing module 204, a calculation module 206 and a crack identification module 208.

[0082] An image acquisition module 202 is used to acquire the panel surface image to generate an image to be detected;

[0083] An image preprocessing module 204 is used to perform grayscale processing on the image to be detected and filter noise;

[0084] The operation module 206 traverses all the pixels of the image to be detected, compares each pixel to be detected with adjacent pixels, and calculates the reference value Z of the grayscale change of each pixel to be detected. The calculation formula is as follows:

[0085]

[0086] Where n represents the number of adjacent pixels, M represents the total number of pixels to be tested in the panel surface image, and M i Represents the number of pixels adjacent to the pixel to be tested and with the same grayscale value, H i represents the grayscale value of the pixel points adjacent to the pixel point to be tested, and H represents the grayscale value adjacent to the pixel point to be tested;

[0087] The crack identification module 208 is used to identify the pixel points whose grayscale change reference value of the pixel points to be tested is greater than a predetermined threshold as suspected crack pixels, to form a set of pixel points with the same reference value as the suspected crack pixels, and to identify a continuous sequence of pixel points in the set whose number is greater than a predetermined threshold as a crack edge pixel point set.

[0088] In some exemplary embodiments of the present invention, the image preprocessing module 204 may further include:

[0089] Grayscale processing module: grayscale processing is performed on the image to be detected, and the color image is converted into a single-channel gray image;

[0090] Noise filtering module: In the image to be detected, the connected area of ​​the two-dimensional image composed of the i×k pixel matrix is ​​extracted, and the noise in the two-dimensional image is filtered by linear optimization through the Gaussian filter. The operation satisfies the function:

[0091]

[0092] Wherein, x and y are the horizontal and vertical coordinates of the pixel coordinates, λ and ξ represent the preset system compensation values ​​of the horizontal and vertical coordinates, δ represents the standard deviation, i and k represent the two-dimensional image composed of the i×k pixel matrix, and F() represents the linearly optimized two-dimensional Gaussian function;

[0093] According to the image expansion formula, the image to be detected is expanded to further remove noise:

[0094]

[0095] Where x and y represent the horizontal and vertical coordinates of the pixel coordinates, respectively, and θ represents the preset expansion coefficient. represents the dilation process, and F() represents the linearly optimized two-dimensional Gaussian function;

[0096] S24: Perform corrosion operation on the image to be detected according to the image corrosion formula:

[0097]

[0098] Among them, x and y represent the horizontal and vertical coordinates of the pixel coordinates respectively, θ represents the preset expansion coefficient, FΘG represents the corrosion process, and F() represents the linearly optimized two-dimensional Gaussian function.

[0099] In some exemplary embodiments of the present invention, the crack identification module 208 may further include: sorting each crack edge pixel point set from large to small according to the reference value, and combining the pixel point coordinate values ​​in each crack edge pixel point set according to the sequence to obtain the shape of the crack.

[0100] In an exemplary embodiment, the present invention further provides an electronic device, the electronic device comprising:

[0101] processor;

[0102] A memory having computer-readable instructions stored therein, which, when loaded and executed by a processor, implement the steps of the above-mentioned method for detecting cracks in an anti-seepage panel of a pumped-storage power station.

[0103] Figure 3 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Figure 3 As shown, the electronic device 300 may include a processor 3001 and a memory 3002. Optionally, the electronic device 300 may further include a transceiver 3003. The processor 3001, the memory 3002 and the transceiver 3003 may be connected, for example, via a communication bus. The memory 3002 stores computer-readable instructions, and when the computer-readable instructions are executed by the processor 3001, the steps of the above-mentioned method for detecting cracks in the anti-seepage panel of a pumped storage power station are implemented.

[0104] In a specific implementation, as an embodiment, the processor 3001 may include one or more CPUs, such as Figure 3 CPU0 and CPU1 are shown in FIG.

[0105] In a specific implementation, as an embodiment, the electronic device 300 may also include multiple processors, such as Figure 3 3001 and processor 3004 are shown in FIG. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). A processor herein may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0106] The memory 3002 is used to store the software program for executing the solution of the present invention, and the execution is controlled by the processor 3001. The specific implementation method can refer to the above method embodiment, which will not be repeated here.

[0107] The transceiver 3003 is used to communicate with a network device or a terminal device.

[0108] Optionally, the transceiver 3003 may include a receiver and a transmitter, wherein the receiver is used to implement a receiving function, and the transmitter is used to implement a sending function.

[0109] Optionally, the transceiver 3003 may be integrated with the processor 3001 , or may exist independently and be coupled to the processor 3001 via an interface circuit of the electronic device 300 , which is not specifically limited in the embodiment of the present invention.

[0110] It should be noted that Figure 3 The structure of the electronic device 300 shown in the figure does not constitute a limitation on the electronic device. The actual electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. In addition, the technical effects of the electronic device 300 can refer to the technical effects of the above-mentioned method embodiment, which will not be repeated here.

[0111] In an exemplary embodiment, the present invention further provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is loaded and executed by a processor to implement the steps of the above-mentioned pumped storage power station anti-seepage panel crack detection method. For example, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0112] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0113] In the specification, references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments", etc. indicate that the embodiments may include specific features, structures, or characteristics, but not every embodiment may include the specific features, structures, or characteristics. In addition, when a specific feature, structure, or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the relevant art to implement such feature, structure, or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0114] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0115] In the present invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0116] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0117] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0118] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0120] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0121] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0122] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for detecting cracks in an anti-seepage panel of a pumped storage power station, characterized in that: include: S1: collecting the panel surface image to generate an image to be detected; S2: grayscale processing is performed on the image to be detected and noise is filtered; S3: Traverse all the pixels of the image to be detected, compare each pixel to be detected with the adjacent pixels, and calculate the reference value Z of the grayscale change of each pixel to be detected. The calculation formula is as follows: Where n represents the number of adjacent pixels, M represents the total number of pixels to be tested in the panel surface image, and M i Represents the number of pixels adjacent to the pixel to be tested and with the same grayscale value, H i represents the grayscale value of the pixel points adjacent to the pixel point to be tested, and H represents the grayscale value adjacent to the pixel point to be tested; S4: Identify the pixel points whose grayscale change reference value of the pixel points to be tested is greater than a predetermined threshold as suspected crack pixel points, form a set of pixel points with the same reference value as the suspected crack pixel points, and identify a continuous pixel point sequence in the set whose number is greater than a predetermined threshold as a crack edge pixel point set.

2. The method for detecting cracks in the anti-seepage panel of a pumped storage power station according to claim 1, characterized in that: The step S1 of collecting the panel surface image to generate the image to be detected includes: S11: determining a flight route for aerial photography and shooting points on the flight route based on the laying position of the anti-seepage panel of the pumped-storage power station; S12: determining the maximum distance between the flying device for aerial photography and the anti-seepage panel of the pumped-storage power station based on a preset minimum crack identification width; S13: Generate the image to be detected.

3. The method for detecting cracks in the anti-seepage panel of a pumped storage power station according to claim 1, characterized in that: The grayscale processing and noise filtering of the image to be detected in step S2 includes: S21: grayscale processing is performed on the image to be detected, so as to convert the color image into a single-channel gray image; S22: In the image to be detected, a connected area of ​​a two-dimensional image consisting of an i×k pixel matrix is ​​extracted, and a Gaussian filter is used to perform linear optimization to filter noise in the two-dimensional image. The operation satisfies the function: Wherein, x and y are the horizontal and vertical coordinates of the pixel coordinates, λ and ξ represent the preset system compensation values ​​of the horizontal and vertical coordinates, δ represents the standard deviation, i and k represent the two-dimensional image composed of the i×k pixel matrix, and F() represents the linearly optimized two-dimensional Gaussian function; S23: Performing an expansion operation on the image to be detected according to an image expansion formula to further remove noise: Where x and y represent the horizontal and vertical coordinates of the pixel coordinates, respectively, and θ represents the preset expansion coefficient. represents the dilation process, and F() represents the linearly optimized two-dimensional Gaussian function; S24: performing an erosion operation on the image to be detected according to an image erosion formula: Among them, x and y represent the horizontal and vertical coordinates of the pixel coordinates respectively, θ represents the preset expansion coefficient, FΘG represents the corrosion process, and F() represents the linearly optimized two-dimensional Gaussian function.

4. The method for detecting cracks in the anti-seepage panel of a pumped storage power station according to claim 1, characterized in that: Also includes: S5: sorting each crack edge pixel point set from large to small according to the reference value, and combining the pixel point coordinate values ​​in each crack edge pixel point set according to the order of the pixel point coordinate values ​​to obtain the shape of the crack.

5. The method for detecting cracks in the anti-seepage panel of a pumped storage power station according to any one of claims 1 to 4, characterized in that: The cracks include: transverse cracks, longitudinal cracks or annular cracks.

6. A pumped storage power station anti-seepage panel crack detection device, characterized in that: include: An image acquisition module, used for acquiring the panel surface image to generate an image to be detected; An image preprocessing module, used for performing grayscale processing on the image to be detected and filtering noise; The calculation module traverses all the pixels of the image to be detected, compares each pixel to be detected with the adjacent pixels, and calculates the reference value Z of the grayscale change of each pixel to be detected. The calculation formula is as follows: Where n represents the number of adjacent pixels, M represents the total number of pixels to be tested in the panel surface image, and M i Represents the number of pixels adjacent to the pixel to be tested and with the same grayscale value, H i represents the grayscale value of the pixel points adjacent to the pixel point to be tested, and H represents the grayscale value adjacent to the pixel point to be tested; The crack identification module is used to identify the pixel points whose grayscale change reference value of the pixel points to be tested is greater than a predetermined threshold as suspected crack pixels, to form a set of pixel points with the same reference value as the suspected crack pixels, and to identify a continuous sequence of pixel points in the set whose number is greater than a predetermined threshold as a crack edge pixel point set.

7. The pumped storage power station anti-seepage panel crack detection device according to claim 6, characterized in that: The image preprocessing module also includes: Grayscale processing module: grayscale processing is performed on the image to be detected, and the color image is converted into a single-channel gray image; Noise filtering module: In the image to be detected, the connected area of ​​the two-dimensional image composed of the i×k pixel matrix is ​​extracted, and the noise in the two-dimensional image is filtered by linear optimization through the Gaussian filter. The operation satisfies the function: Wherein, x and y are the horizontal and vertical coordinates of the pixel coordinates, λ and ξ represent the preset system compensation values ​​of the horizontal and vertical coordinates, δ represents the standard deviation, i and k represent the two-dimensional image composed of the i×k pixel matrix, and F() represents the linearly optimized two-dimensional Gaussian function; The image to be detected is expanded according to the image expansion formula to further remove noise: Where x and y represent the horizontal and vertical coordinates of the pixel coordinates, respectively, and θ represents the preset expansion coefficient. represents the dilation process, and F() represents the linearly optimized two-dimensional Gaussian function; S24: performing an erosion operation on the image to be detected according to an image erosion formula: Among them, x and y represent the horizontal and vertical coordinates of the pixel coordinates respectively, θ represents the preset expansion coefficient, FΘG represents the corrosion process, and F() represents the linearly optimized two-dimensional Gaussian function.

8. The pumped storage power station anti-seepage panel crack detection device according to claim 6, characterized in that: The crack identification module also includes: Each crack edge pixel point set is sorted from large to small according to the reference value, and the pixel point coordinate values ​​in each crack edge pixel point set are combined according to the sequence to obtain the shape of the crack.

9. An electronic device, characterized in that: The electronic device comprises: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method for detecting cracks in an anti-seepage panel of a pumped-storage power station as claimed in any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, and the program codes are loaded by a processor and executed by the method for detecting cracks in an anti-seepage panel of a pumped-storage power station as described in any one of 1 to 4.

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