Corrosion area identification method and device and storage medium

Abstract

The invention discloses a corrosion area identification method and device and a storage medium, relates to the technical field of corrosion detection, and aims to solve the problem of how to determine a reason for corrosion of equipment. The identification of the eroded region includes acquiring chemical compositions of the eroded region and three-dimensional image data of the eroded region. Based on the chemical components and the three-dimensional image data, corrosion characteristic information of the corrosion area is obtained. Based on the corrosion characteristic information, a corrosion identification result is obtained, and the corrosion identification result is used for indicating the corrosion condition of the corrosion area.

Description

Technical Field

[0001] The present application relates to the field of corrosion detection technology, and in particular to a method, device and storage medium for identifying a corrosion area. Background Art

[0002] When equipment is corroded, its performance may be degraded. Therefore, targeted maintenance is required to ensure that the equipment can operate normally. However, during the process of equipment corrosion, it is affected by many factors.

[0003] Therefore, how to determine the cause of equipment corrosion and carry out targeted maintenance on the corroded equipment has become an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present application is to provide a method, device and storage medium for identifying a corrosion area, aiming to solve the problem of how to determine the cause of corrosion of equipment.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a method for identifying a corrosion region, the method comprising obtaining chemical composition of the corrosion region and three-dimensional image data of the corrosion region. Based on the chemical composition and the three-dimensional image data, corrosion feature information of the corrosion region is obtained. Based on the corrosion feature information, a corrosion identification result is obtained, and the corrosion identification result is used to indicate the corrosion condition of the corrosion region.

[0007] The method for identifying a corrosion area provided in an embodiment of the present application can obtain the chemical composition of the corrosion area and the three-dimensional image data of the corrosion area. Afterwards, the corrosion feature information of the corrosion area can be obtained based on the chemical composition and the three-dimensional image data. Afterwards, a corrosion identification result can be obtained based on the corrosion feature information, and the corrosion identification result is used to indicate the corrosion condition of the corrosion area. In this way, the corrosion condition of the corrosion area can be judged more accurately, and the accurate identification of the corrosion features can be achieved, so as to carry out targeted maintenance on the corroded equipment.

[0008] In some embodiments, the corrosion feature information includes chemical corrosion information and three-dimensional corrosion information, the chemical corrosion information is used to indicate the corrosion feature corresponding to the chemical composition, and the three-dimensional corrosion information is used to indicate the corrosion feature corresponding to the morphology of the corrosion area. Based on the chemical composition and the three-dimensional image data, the corrosion feature information of the corrosion area is obtained, including: based on the chemical composition, obtaining chemical corrosion information. Performing a profile analysis on the three-dimensional image data to obtain corrosion profile information, the corrosion profile information is used to indicate the corrosion state of the cross section of the corrosion area. Based on the corrosion profile information, the three-dimensional corrosion information is obtained.

[0009] In some embodiments, performing a profile analysis on the three-dimensional image data to obtain corrosion profile information includes: converting the three-dimensional image data into two-dimensional image data. Processing the two-dimensional image data based on a mathematical morphology algorithm and an image binarization algorithm to obtain foreground image data. Processing the foreground image data based on a density peak clustering algorithm to obtain corrosion profile information.

[0010] In some embodiments, the corroded area is an area in the target object where corrosion exists, and the corroded area is an area that has been pre-treated. The pre-treatment includes: fixing the area where corrosion exists by an organic solution, and embedding, staining, and gelling the fixed area. The contrast ratio of the three-dimensional image data is greater than the preset contrast ratio.

[0011] In some embodiments, embedding the immobilized region comprises: embedding through a gel solution, wherein the gel solution is prepared by sodium acrylate, ammonium acrylate, N-methylenebisacrylamide, nitroxyl piperidinol, tetramethylethylenediamine and ammonium persulfate.

[0012] In some embodiments, obtaining three-dimensional image data of the corroded area includes: obtaining a two-dimensional image of the corroded area, and performing three-dimensional reconstruction processing on the two-dimensional image to obtain three-dimensional image data.

[0013] In some embodiments, the method for identifying a corrosion area further includes: establishing a corrosion assessment database based on chemical composition, three-dimensional image data and corrosion identification results.

[0014] In a second aspect, the present application provides a device for identifying a corrosion area, the device comprising an acquisition module and a processing module.

[0015] The acquisition module is used to acquire the chemical composition of the corrosion area and the three-dimensional image data of the corrosion area. The processing module is used to obtain the corrosion characteristic information of the corrosion area based on the chemical composition and the three-dimensional image data. The processing module is also used to obtain the corrosion identification result based on the corrosion characteristic information, and the corrosion identification result is used to indicate the corrosion condition of the corrosion area.

[0016] In some embodiments, the corrosion feature information includes chemical corrosion information and three-dimensional corrosion information, the chemical corrosion information is used to indicate the corrosion feature corresponding to the chemical composition, and the three-dimensional corrosion information is used to indicate the corrosion feature corresponding to the morphology of the corrosion area. The processing module is used to obtain the chemical corrosion information based on the chemical composition. The processing module is also used to perform a profile analysis on the three-dimensional image data to obtain corrosion profile information, and the corrosion profile information is used to indicate the corrosion state of the cross section of the corrosion area. The processing module is also used to obtain the three-dimensional corrosion information based on the corrosion profile information.

[0017] In some embodiments, the processing module is used to convert the three-dimensional image data into two-dimensional image data. The processing module is also used to process the two-dimensional image data based on a mathematical morphology algorithm and an image binarization algorithm to obtain foreground image data. The processing module is also used to process the foreground image data based on a density peak clustering algorithm to obtain corrosion profile information.

[0018] In some embodiments, the corroded area is an area in the target object where corrosion exists, and the corroded area is an area that has been pre-treated. The pre-treatment includes: fixing the area where corrosion exists by an organic solution, and embedding, staining, and gelling the fixed area. The contrast ratio of the three-dimensional image data is greater than the preset contrast ratio.

[0019] In some embodiments, embedding the immobilized region comprises: embedding through a gel solution, wherein the gel solution is prepared by sodium acrylate, ammonium acrylate, N-methylenebisacrylamide, nitroxyl piperidinol, tetramethylethylenediamine and ammonium persulfate.

[0020] In some embodiments, the acquisition module is used to acquire a two-dimensional image of the corrosion area. The processing module is also used to perform three-dimensional reconstruction processing on the two-dimensional image to obtain three-dimensional image data.

[0021] In some embodiments, the processing module is used to establish a corrosion assessment database based on the chemical composition, the three-dimensional image data and the corrosion identification results.

[0022] In a third aspect, the present application provides a device for identifying a corrosion area, the device comprising: a processor and a memory; the processor and the memory are coupled; the memory is used to store one or more programs, the one or more programs comprising computer-executable instructions, and when the device for identifying a corrosion area is running, the processor executes the computer-executable instructions stored in the memory to implement the method described in the first aspect and any possible implementation of the first aspect.

[0023] In a fourth aspect, the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed on a computer, the computer executes the method described in the above-mentioned first aspect and any possible implementation of the first aspect.

[0024] In a fifth aspect, the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run a computer program or instructions to implement the method described in the first aspect and any possible implementation of the first aspect.

[0025] In a sixth aspect, the present application provides a computer program product comprising instructions, which, when executed by a computer, enables the computer to execute the method described in the above-mentioned first aspect and any possible implementation manner of the first aspect.

[0026] In the above scheme, the technical problems that can be solved and the technical effects achieved by the corrosion area identification device, computer equipment, computer storage medium, chip or computer program product can be referred to the technical problems and technical effects solved by the above-mentioned first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 A system architecture diagram of an optical microscopy imaging system provided in an embodiment of the present application;

[0029] Figure 2 A schematic diagram of a process for identifying a corrosion area provided in an embodiment of the present application;

[0030] Figure 3 A schematic diagram of an example of pre-treating a corrosion area provided in an embodiment of the present application;

[0031] Figure 4 A schematic diagram of an example of fluorescence intensity distribution provided in an embodiment of the present application;

[0032] Figure 5 An example schematic diagram of performance evaluation data provided in an embodiment of the present application;

[0033] Figure 6 A schematic diagram of the structure of a corrosion area identification device provided in an embodiment of the present application;

[0034] Figure 7 A schematic diagram of the structure of another device for identifying a corrosion area provided in an embodiment of the present application;

[0035] Figure 8 A conceptual partial view of a computer program product provided for an embodiment of the present application. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0037] In the description of this application, it should be understood that the terms "upper", "lower", "left", "right", "front", "back", "inside", "outside", etc. indicate directions or positional relationships based on the directions or relative positional relationships shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on this application. Unless otherwise specified, the above-mentioned directional description can be flexibly set in the process of actual application under the condition that the relative positional relationship shown in the accompanying drawings is met.

[0038] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0039] In the present application, the terms "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, article or 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, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, article or device including the element.

[0040] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0041] When equipment is corroded, its performance may be degraded. Therefore, targeted maintenance is required to ensure that the equipment can operate normally. However, during the process of equipment corrosion, it is affected by many factors.

[0042] Therefore, how to determine the cause of equipment corrosion and carry out targeted maintenance on the corroded equipment has become an urgent problem to be solved.

[0043] In the field of oil and gas pipelines, corrosion can affect the performance and safety of pipeline equipment. The corrosion of pipeline equipment is affected by many factors. For example, the physical and chemical properties of the soil, microorganisms, stray currents, and lightning strikes. Under different environmental conditions, the rate and form of corrosion of pipeline equipment vary greatly, and the corrosion characteristics exhibited are also different. By identifying the characteristics of the corrosion area, the cause of the corrosion of the pipeline equipment can be determined. Therefore, in-depth understanding and accurate identification of corrosion characteristics has become an important research direction in the field of materials science and engineering.

[0044] Corrosion characteristics are usually manifested as surface damage, color change, cracks and peeling. The corrosion state of the material can be preliminarily judged by naked eye observation. However, it is difficult to confirm the cause of corrosion of pipeline equipment by naked eye observation alone. Therefore, it is necessary to use advanced detection technology and evaluation methods to identify the corrosion area.

[0045] In some scenarios, due to the complexity and diversity of corrosion areas, and the combined influence of microorganisms, stray currents and soil physical and chemical environment, the spatial distribution of corrosion products has overlapping and intersection problems that affect the identification of corrosion areas, making the corrosion identification process difficult.

[0046] Traditional corrosion identification technology can identify the corroded area, but cannot identify the structure of the corrosion. For example, scanning electron microscopy and X-ray diffraction analysis can be used to conduct a preliminary analysis of the morphology and elemental composition of the corroded area, but the data obtained can only reflect the microscopic information of the corroded area, and cannot determine the type of the corroded area, and thus cannot determine the cause of the corrosion of the pipeline equipment.

[0047] Therefore, it is difficult to accurately identify corrosion characteristics only through visual inspection, electrochemical testing, modern sensor technology and other corrosion identification technologies. This not only makes it impossible to effectively identify corrosion characteristics, but also makes it impossible to maintain corroded pipeline equipment in a targeted manner.

[0048] Therefore, a new corrosion identification method is needed to identify the corrosion area and the structure of the corrosion area, so as to effectively identify the corrosion area caused by complex environment.

[0049] In order to solve the above technical problems, an embodiment of the present application provides a method for identifying a corrosion area. In this method, the chemical composition of the corrosion area and the three-dimensional image data of the corrosion area can be obtained. Afterwards, the corrosion feature information of the corrosion area can be obtained based on the chemical composition and the three-dimensional image data. Afterwards, a corrosion identification result can be obtained based on the corrosion feature information, and the corrosion identification result is used to indicate the corrosion condition of the corrosion area. In this way, the corrosion condition of the corrosion area can be judged more accurately, and the accurate identification of the corrosion features can be achieved, so as to carry out targeted maintenance on the corroded equipment.

[0050] The implementation environment of the embodiments of the present application is introduced below.

[0051] like Figure 1 , which is a system architecture diagram of an optical microscopy imaging system provided in an embodiment of the present application, the system includes: a laser 101, a polarizer 102, a spatial light modulator 103, a sample support 104, an eyepiece 105, and a camera 106.

[0052] The laser 101 is a light source of the optical microscopic imaging system, and is used to excite the fluorescent molecules in the corrosion area to obtain fluorescent spots.

[0053] The polarizer 102 is used to adjust the polarization state of light.

[0054] The spatial light modulator 103 is used to adjust the intensity and distribution of the light field to achieve more precise excitation and positioning of fluorescent molecules.

[0055] The sample support frame 104 is used to fix and support the sample to be imaged to ensure that the sample remains stable during the imaging process.

[0056] The eyepiece 105 is used to magnify the image to make the image clearer.

[0057] The camera 106 is used to record the imaging results of the corrosion area containing the fluorescent spots.

[0058] In an embodiment of the present application, the optical microscopy imaging system includes an illumination light path, an imaging light path, a sample support frame, a sample slot, a camera, a laser, a one-dimensional galvanometer, an XYZ high-precision mobile platform, a nano-displacement stage, an acousto-optic tunable filter, an eyepiece, a spatial light modulator, a polarizer, and a deformable mirror.

[0059] Optionally, the illumination light path is separated from the imaging light path. The illumination light path includes a fiber laser and an objective lens, and the imaging light path includes a water mirror and an objective lens. The objective lens of the imaging light path is placed vertically with the objective lens of the illumination light path. The objective lens hole matches the objective lens size. The sample support frame is a groove structure with one side closed and the other three sides open. Among them, a thin layer of optical glass is provided on one side of the sample support frame in the imaging direction, and the sample can be placed on the sample support frame before imaging. The sample groove is a structure with an open top and closed on all sides.

[0060] It should be noted that the objective lens hole matches the size of the objective lens. The nanometer displacement stage can be a piezoelectric ceramic nanometer displacement stage, which is used to achieve precise displacement of the sample.

[0061] Optionally, the optical microscopy imaging system can control the imaging picture based on software and a Gaussian fitting algorithm, and correct the imaging picture based on adaptive optics technology.

[0062] It is understandable that the optical microscopic imaging system can achieve the displacement of the camera and the imaging screen through software. The optical microscopic imaging system controls the imaging screen through the Gaussian fitting algorithm and corrects the imaging screen through adaptive optical technology, which can achieve precise positioning of the imaging screen to obtain more accurate and effective imaging pictures.

[0063] It should be noted that the present application does not limit the optical microscopic imaging system. For example, the optical microscopic imaging system may be a stochastic optical reconstruction microscopy (STORM) system.

[0064] The embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0065] like Figure 2 As shown, a method for identifying a corrosion area provided in an embodiment of the present application includes:

[0066] S201, obtaining chemical composition of the corrosion area and three-dimensional image data of the corrosion area.

[0067] Optionally, the chemical composition of the corrosion area can be obtained by analyzing the corrosion area using X-ray diffraction (XRD) technology.

[0068] Specifically, the X-ray diffractometer can irradiate the corrosion area to obtain an X-ray diffraction spectrum of the corrosion area. Afterwards, the X-ray diffractometer can analyze the X-ray diffraction spectrum to obtain diffraction peaks in the X-ray diffraction spectrum. Afterwards, the X-ray diffractometer can determine the chemical composition of the corrosion area based on the diffraction peaks and send the chemical composition of the corrosion area to the corrosion area identification device.

[0069] Optionally, the three-dimensional image data of the corrosion area includes fluorescent image data, and the fluorescent image data is image data with fluorescent markers.

[0070] It should be noted that the fluorescent marker can be a fluorescent dot.

[0071] In a possible implementation, a two-dimensional image of the corroded area may be acquired, and then a three-dimensional reconstruction process may be performed on the two-dimensional image of the corroded area to obtain three-dimensional image data.

[0072] Optionally, a two-dimensional image of the corrosion area transmitted by an image acquisition device may be received.

[0073] Alternatively, the corroded area may be processed based on a two-dimensional imaging technology to obtain a two-dimensional image of the corroded area.

[0074] In a possible design, the two-dimensional image of the eroded area can be processed based on the point spread function (PSF) modulation technology to obtain a two-dimensional super-resolution image. After that, the two-dimensional super-resolution image can be subjected to three-dimensional reconstruction processing to obtain three-dimensional image data.

[0075] Specifically, the corrosion area recognition device is deployed with an imaging module. The corrosion area can be imaged by the imaging module to obtain original two-dimensional image data. Afterwards, the original two-dimensional image data can be positioned and drift corrected based on the fitting algorithm, and the processed original two-dimensional image data can be processed based on the super-resolution algorithm to obtain a two-dimensional image. Afterwards, a PSF model can be established. Afterwards, the shape and parameters of the PSF model can be modulated, and the two-dimensional image can be processed to obtain a two-dimensional super-resolution image. Afterwards, the two-dimensional super-resolution image can be three-dimensionally reconstructed to obtain a three-dimensional model of the corrosion area. Afterwards, three-dimensional image data can be obtained based on the three-dimensional model of the corrosion area.

[0076] Optionally, the imaging module includes a deformable mirror. The point spread function can be modulated based on the deformable mirror so that corrosion areas at different axial positions can be focused and imaged.

[0077] It is understandable that the three-dimensional image can more accurately obtain the information of the complex structure in the corrosion area. In addition, through the PSF modulation technology, the three-dimensional image can be made clearer and more accurate, and the noise and interference in the imaging process can be reduced, thereby improving the signal-to-noise ratio of the image.

[0078] S202: Obtain corrosion characteristic information of the corrosion area based on the chemical composition and the three-dimensional image data.

[0079] The corrosion feature information includes chemical corrosion information and three-dimensional corrosion information. The chemical corrosion information is used to indicate the corrosion features corresponding to the chemical composition, and the three-dimensional corrosion information is used to indicate the corrosion features corresponding to the morphology of the corrosion area.

[0080] In a possible implementation manner, chemical corrosion information of the corrosion region may be obtained based on the chemical composition of the corrosion region.

[0081] For example, the chemical composition of the steel plate contains metal sulfide. Since the main product of high-temperature sulfidation corrosion is metal sulfide, the chemical corrosion information of the steel plate is metal sulfide.

[0082] In another possible implementation manner, three-dimensional corrosion information of the corrosion area may be obtained based on the three-dimensional image data of the corrosion area.

[0083] Exemplarily, the corrosion area is a corrosion area of ​​a titanium alloy plate. Based on the three-dimensional image data of the corrosion area of ​​the titanium alloy plate, it can be obtained that there are circular or elliptical pitting pits on the surface of the titanium alloy plate. Since pitting pits are a feature of local corrosion, the three-dimensional corrosion information of the titanium alloy plate is the presence of pitting pits.

[0084] In another possible implementation, a cross-sectional analysis may be performed on the three-dimensional image data to obtain corrosion cross-sectional information of the corrosion region, where the corrosion cross-sectional information is used to indicate the corrosion state of the cross-sectional area of ​​the corrosion region. Then, three-dimensional corrosion information of the corrosion region may be obtained based on the corrosion cross-sectional information.

[0085] In the embodiment of the present application, the corrosion profile information includes the morphological information and distribution information of the corrosion area in the profile.

[0086] The corrosion area includes organic compounds and inorganic compounds. The morphological information includes the morphology of organic compounds, the morphology of inorganic compounds, the phase change information of organic compounds, and the phase change information of inorganic compounds. The corrosion area includes corrosion products. The distribution information includes the location of the corrosion products in the corrosion area, the structure of the corrosion products in the corrosion area, and the degree of corrosion at different locations in the corrosion area.

[0087] For example, the corrosion profile information of the steel plate includes: the thickness of the steel plate, and cracks with multiple branches on the steel plate. Since the cracks are manifestations of stress corrosion cracking, the three-dimensional corrosion information is cracks with multiple branches.

[0088] In this way, the corrosion characteristics corresponding to the chemical composition of the corrosion area can be obtained, and the corrosion characteristics corresponding to the morphology of the corrosion area can be obtained through the three-dimensional corrosion information. In this way, the identification result of the corrosion area can be made more accurate.

[0089] In a possible design, the three-dimensional image data can be converted into two-dimensional image data. Then, the two-dimensional image data can be processed based on a morphological operation algorithm and an image binarization algorithm to obtain foreground image data. Then, the foreground image data can be processed based on a density peak clustering algorithm to obtain corrosion profile information of the corrosion area.

[0090] In an embodiment of the present application, the three-dimensional image data includes coordinate data of the three-dimensional image data, and the coordinate data of the three-dimensional image data is the coordinate data of the three-dimensional model of the erosion area on each coordinate axis. The two-dimensional image data includes coordinate data of the two-dimensional image data, and the coordinate data of the two-dimensional image data is the coordinate data of the three-dimensional model of the erosion area mapped to a plane. The coordinate data of the three-dimensional image data can be converted into the coordinate data of the two-dimensional image data.

[0091] Optionally, the coordinate data of the three-dimensional image data can be processed to obtain the triangular surface data of the eroded area. The triangular surface data includes the coordinate data of multiple triangular surfaces, and the coordinate data of each triangular surface includes the vertex coordinate data of the three vertices of the triangular surface. Afterwards, the three-dimensional section coordinate data can be obtained, and the three-dimensional section is a plane parallel to any coordinate axis. Afterwards, the three-dimensional section coordinate data can be processed to obtain the triangular surface data of the three-dimensional section. Afterwards, the triangular surface data of the eroded area and the triangular surface data of the three-dimensional section can be processed to obtain the intersection vertex set data of the intersection of the eroded area and the three-dimensional section. Afterwards, coordinate conversion can be performed based on the intersection vertex set data to obtain the coordinate data of the two-dimensional image data.

[0092] For example, the intersection vertex set R' includes m vertices (such as vertex r 1 ', vertex r 2 '). Vertex r i ' is any vertex in the vertex set R', r i The coordinates of ' are (x i ',y i ', z i '). The coordinate data of the two-dimensional image data includes a vertex set of the two-dimensional image. The vertex set R' of the two-dimensional image includes n vertices (such as vertex r 1 "、Vertex r 2 ”). Vertex r i " is any vertex in the vertex set R", r i The coordinates of ” are (x i ”,y i ”). The coordinate transformation formula can satisfy Formula 1.

[0093]

[0094] Where Δx is the vertex r in the vertex set R of the two-dimensional image.i " is the change in the horizontal coordinate of the two-dimensional image, Δy is the vertex r in the vertex set R of the two-dimensional image i "The change in the vertical axis. i " is the vertex r in the vertex set R of the two-dimensional image i "The horizontal axis, y i " is the vertex r in the vertex set R of the two-dimensional image i "The vertical coordinate of ". x0 is the horizontal coordinate of the coordinate origin, and y0 is the vertical coordinate of the coordinate origin. a is used to indicate the offset of the horizontal coordinate in the coordinate data of the two-dimensional image data, and b is used to indicate the offset of the vertical coordinate in the coordinate data of the two-dimensional image data.

[0095] Optionally, b may be the value of the coordinate point located on any coordinate axis in the three-dimensional coordinate system before the transformation, or may be the difference between the values ​​of the coordinate point located on any two coordinate axes in the three-dimensional coordinate system before the transformation.

[0096] It can be understood that by calculating the vertex r in the vertex set R of the two-dimensional image i The change in the horizontal and vertical coordinates of the " can be used to process the coordinate data of the two-dimensional image data to ensure that the coordinate data of the two-dimensional image data is more accurate after the transformation.

[0097] In this way, by converting the three-dimensional image data into two-dimensional image data, the three-dimensional image data and the two-dimensional image data can be automatically associated and updated, thereby improving the availability and accuracy of the data.

[0098] Optionally, the morphological operation algorithm includes a corrosion algorithm. The two-dimensional image data can be processed based on a Gaussian filtering algorithm and a wavelet multi-scale transform algorithm to remove background noise and strengthen the fluorescence signal of the fluorescent point. Afterwards, feature extraction can be performed on the processed two-dimensional image data based on the corrosion algorithm and the image binarization algorithm to obtain foreground image data, which includes fluorescence recognition signal data. Afterwards, the fluorescence recognition signal data can be input into a density peak clustering algorithm to obtain corrosion profile information of the corrosion area.

[0099] Specifically, the standard deviation can be input into the difference of gaussians (DOG) algorithm, and the two-dimensional image data can be processed based on the first-order wavelet transform and the preset wavelet coefficient threshold to obtain the processed two-dimensional image data. Afterwards, the processed two-dimensional image data can be extracted based on the preset corrosion threshold, corrosion algorithm, preset binary threshold and image binarization algorithm to obtain the fluorescence signal information. Afterwards, the fluorescence recognition signal data can be input into the density peak clustering algorithm to obtain the cluster center. Afterwards, the fluorescence points in the foreground image data can be located, clustered and screened based on the cluster center, and the corrosion profile information of the corrosion area can be obtained.

[0100] Optionally, the preset wavelet coefficient threshold may be twice the initial set threshold, which is used to distinguish foreground and background pixels.

[0101] It should be noted that the present application does not limit the preset wavelet coefficient threshold, the preset erosion threshold and the preset binary threshold. For example, the preset wavelet coefficient threshold can be 30, the preset erosion threshold can be 800, and the preset binary threshold can be 0. The preset binary threshold of 0 means that all non-zero pixels are foregrounds, and zero pixels are backgrounds, and the image only contains two pixel values, foreground and background.

[0102] In this way, noise and impurities in the image can be removed, the clarity of the image can be improved, and similar objects can be classified into one category, which is helpful for subsequent image analysis and processing. In addition, simplifying the image data into black and white pixel values ​​can reduce the amount of data and improve the efficiency of image processing.

[0103] S203: Obtain corrosion identification results based on the corrosion feature information.

[0104] Among them, the corrosion identification result is used to indicate the corrosion condition of the corrosion area.

[0105] In a possible implementation, a corrosion identification result may be obtained based on chemical corrosion information and three-dimensional corrosion information.

[0106] In a possible design, a chemical evaluation result can be obtained based on chemical corrosion information, and the chemical evaluation result includes the chemical corrosion type, chemical corrosion rate and chemical corrosion reaction of the corrosion area. The chemical corrosion type of the corrosion area is the corrosion type of the corrosion area in terms of chemistry. A three-dimensional evaluation result can be obtained based on three-dimensional corrosion information, and the three-dimensional evaluation result includes the three-dimensional corrosion type and three-dimensional corrosion rate of the corrosion area. The three-dimensional corrosion type of the corrosion area is the corrosion type of the corrosion area in terms of physical morphology. Afterwards, a corrosion identification result can be obtained based on the chemical evaluation result and the three-dimensional evaluation result.

[0107] For example, the chemical corrosion types of the corrosion area are sulfur corrosion and electrochemical corrosion. The three-dimensional corrosion types of the corrosion area are pitting corrosion, stress corrosion, and sulfur corrosion. The corrosion identification result is that the corrosion types of the area are sulfur corrosion, stress corrosion, and pitting corrosion.

[0108] Optionally, the chemical corrosion type of the corrosion area may be determined based on the chemical corrosion information of the corrosion area.

[0109] Exemplarily, if the chemical corrosion information of the corrosion area is that it contains chloride ions exceeding a preset value, it can be determined that the chemical corrosion type of the corrosion area is electrochemical corrosion.

[0110] Optionally, based on the chemical corrosion information of the corrosion area, an experiment may be conducted on the corrosion area to determine the relationship between the chemical corrosion information and the corrosion rate of the corrosion area, thereby determining the chemical corrosion rate.

[0111] For example, the chemical corrosion information of the corrosion area is 20% zinc. Then, the corrosion area can be tested to obtain the relationship between the zinc content and the corrosion rate. Then, the chemical corrosion rate of the corrosion area can be determined based on the relationship between the zinc content and the corrosion rate.

[0112] Optionally, the chemical corrosion reaction of the corrosion area may be determined based on the chemical corrosion information of the corrosion area.

[0113] For example, if the chemical corrosion information of the corrosion area is basic copper carbonate of copper, then the chemical corrosion reaction of the corrosion area can be determined as follows: the copper plate reacts with oxygen, water and carbon dioxide to generate basic copper carbonate.

[0114] Optionally, the three-dimensional corrosion type and three-dimensional corrosion rate of the corrosion area may be determined based on the three-dimensional corrosion information of the corrosion area.

[0115] For example, if the three-dimensional corrosion information of the corrosion area of ​​the steel plate is the presence of pitting pits, then the three-dimensional corrosion type of the corrosion area is local corrosion. If the three-dimensional corrosion information of the corrosion area is the corrosion depth of 0.35 cm and the corrosion area area of ​​20 square centimeters, then based on the same uncorroded steel plate, the three-dimensional corrosion rate of the corrosion area can be determined.

[0116] It should be noted that the present application does not limit the corrosion type of the corrosion area. For example, the corrosion type may be uniform corrosion, pitting corrosion, AC interference corrosion, DC interference corrosion, microbial corrosion, sulfur corrosion, electrochemical corrosion or stress corrosion.

[0117] Based on the above technical solution, the chemical composition of the corrosion area and the three-dimensional image data of the corrosion area can be obtained. Then, the corrosion feature information of the corrosion area can be obtained based on the chemical composition and the three-dimensional image data. Then, the corrosion identification result can be obtained based on the corrosion feature information, and the corrosion identification result is used to indicate the corrosion condition of the corrosion area. In this way, the corrosion condition of the corrosion area can be judged more accurately, and the accurate identification of the corrosion features can be realized, so as to carry out targeted maintenance on the corroded equipment.

[0118] In some embodiments, a corrosion assessment database may be established based on the chemical composition of the corrosion region, the three-dimensional image data of the corrosion region, and the corrosion identification results.

[0119] In this way, the corrosion situation of the corroded area can be quickly obtained through the corrosion assessment database.

[0120] In some embodiments, the corrosion area is an area in the target object where corrosion exists, and the corrosion area is an area that has been pretreated; wherein the pretreatment includes: fixing the area where corrosion exists by an organic solution, and embedding, staining, and solidifying the fixed area; the contrast ratio of the three-dimensional image data is greater than a preset contrast ratio.

[0121] In one possible design, the method of fixing the area where corrosion exists by means of an organic solution comprises: dyeing the area where corrosion exists by means of a fluorescent dye, eluting the dyed area by means of an elution solution, and fixing the eluted area where corrosion exists by means of an organic solution.

[0122] Optionally, the fluorescent dye includes at least one of the following: fluorescein, rhodamine B, infiber cyanine, fluorescein isothiocyanate (FITC), tetramethylrhodamine (TRITC), cyanine dyes. The elution solution may be a pH buffer.

[0123] It can be understood that by utilizing the coloring effect of fluorescent substances on the corrosion area and obtaining the morphological distribution of corrosion products in the corrosion area, more detailed information about the corrosion area can be obtained.

[0124] It should be noted that the present application does not limit the organic solution. For example, the organic solution can be an ethyl compound solution or a methyl compound solution (such as a paraformaldehyde solution). Among them, the methyl compound solution has a better curing effect. The present application does not limit the preset contrast ratio. For example, the preset contrast ratio can be 100:1, 120:1, 130:1, 140:1, 150:1.

[0125] It can be understood that by performing a fixation treatment on the corroded area with an organic solution, the corroded area can better retain the original components.

[0126] Specifically, the fixed corrosion area is embedded, including embedding through a gel solution, wherein the gel solution is prepared by sodium acrylate, ammonium acrylate, N-methylenebisacrylamide, nitroxyl piperidinol, tetramethylethylenediamine and ammonium persulfate.

[0127] It can be understood that the gel solution is prepared by sodium acrylate, ammonium acrylate, N-methylenebisacrylamide, nitroxyl piperidinol, tetramethylethylenediamine and ammonium persulfate. These solutions will not react with metal oxides, and can prevent the corrosive substances in the corrosion area from reacting with the gel solution, making the corrosion identification results more accurate.

[0128] Exemplarily, the corrosion area is fixed by an organic solution, and the fixed corrosion area is embedded, dyed, and solidified by steps one, two, three, four, five, and six:

[0129] Step 1, such as Figure 3 As shown, it is a schematic diagram of an example of pre-treating a corrosion area provided by an embodiment of the present application. Corrosion substances in the corrosion area can be obtained. Afterwards, the area with corrosion can be stained with a fluorescent dye, and the stained area can be immersed in a pH buffer solution to wash out excess fluorescent dye in the stained area. Afterwards, the corrosion substances can be fixed based on a paraformaldehyde solution.

[0130] Step 2: The immobilized corrosion material can be cut into slices of 100-300 μm using a vibrating microtome. Afterwards, the sample is immersed in phosphate buffered saline (PBS) and stored in a dark environment at 4°C.

[0131] Step 3: The etched slice can be placed in a dimethyl sulfoxide solution (DMSO). The DMSO solution contains an Acryloyl-SE compound, and the concentration of the acryloyl group (i.e., Acryloyl) is in the range of 5 mg / ml to 20 mg / ml. Then, sodium acrylate, ammonium acrylate, and bisacrylamide (i.e., N,N-methylenebisacrylamide) can be prepared into a fixing solution at a refrigerated temperature (i.e., ice box temperature).

[0132] In step 4, nitroxyl piperidinol, tetramethylethylenediamine and ammonium persulfate can be added to the fixing solution in step 3 in sequence and shaken to obtain a gel solution. Then, the corrosion section placed in the DMSO solution in step 3 is placed in the gel solution and stored at 4°C.

[0133] In step 5, the corroded slices stored for 20 minutes to 60 minutes in step 4 can be placed on a fixed support so that the corroded slices can be polymerized on the surface of the fixed support. Afterwards, the polymerized corroded slices can be stained based on anti-GFP-AlexaFluor647 dye. Afterwards, the stained corroded slices are washed to remove free dyes in the stained corroded slices.

[0134] Step 6: The washed corrosion slices can be solidified with agar. After that, a buffer solution can be prepared, and the expansion coefficient of the solidified corrosion slices can be controlled with the buffer solution.

[0135] In this way, an isotropically expanded corrosion area can be obtained, achieving a uniform structure of the sample components and high light transmittance, making the light and dark contrast of the three-dimensional image stronger, thereby improving the spatial resolution. In addition, by fixing the corrosion area with an organic solution, the dilution of the corrosion area can be reduced while fixing the corrosion area, and it will not react with the corrosion area. In this way, a more complete corrosion area can be obtained, making the corrosion identification result more accurate.

[0136] The embodiments of the present application are introduced below with reference to specific examples.

[0137] Exemplarily, a corrosion region image dataset may be obtained based on an adeno-associated virus (AAV) anterograde tracing algorithm, wherein the corrosion region image dataset includes a plurality of data blocks, each of which includes fluorescent point signal region information and background region information of the corrosion region.

[0138] It should be noted that the AAV anterograde tracing algorithm is a neural circuit tracing method that can carry fluorescent proteins or other marker genes through AAV viral vectors and label neurons through anterograde transport to obtain the projection path and connection relationship of neurons.

[0139] It should be noted that the present application does not limit the number and volume of data blocks. For example, there may be eight data blocks with a volume of 200×200×200 cubic millimeters (μm 3 ).

[0140] Afterwards, the image dataset of the corrosion area can be analyzed to obtain the three-dimensional corrosion information of the corrosion area.

[0141] It should be noted that, in order to quantitatively analyze the fluorescence intensity distribution characteristics, the fluorescent spots in the image can be intercepted to obtain the fluorescence type of each fluorescent spot, and the proportion of fluorescent spots of each fluorescence type in all fluorescent spots can be counted.

[0142] For example, a data block may be subjected to a 10 mm (μm) thick two-dimensional projection process to obtain 80 two-dimensional images. Then, the fluorescent points in the two-dimensional images may be intercepted. Then, a fluorescence intensity distribution diagram may be drawn.

[0143] For example, Figure 4 As shown, it is a schematic diagram of an example of fluorescence intensity distribution provided by an embodiment of the present application. Among them, based on the distribution morphology information of the fluorescence intensity, three types of fluorescence intensity distribution, namely, single peak, double peak and multi-peak, can be obtained. After that, a 95% confidence zone can be taken to obtain the fluorescence point characteristics of each corrosion type, that is, the diameter range and fluorescence intensity of the fluorescence point.

[0144] It should be noted that the fluorescent spots need to be intact during the interception process.

[0145] Exemplarily, as shown in Table 1, is the relationship between the corrosion type and the fluorescent spot characteristics.

[0146] Table 1

[0147]

[0148]

[0149] Among them, the diameter of the fluorescent spot of the uniform corrosion type is between 0.3μm and 1.4μm, and the fluorescence intensity is between 200 astronomical units (AU) and 1200AU. The diameter of the fluorescent spot of the uniform corrosion type is between 2.4μm and 5.8μm, and the fluorescence intensity is between 600AU and 1400AU.

[0150] For the introduction of the diameter range and fluorescence intensity range of the fluorescent spots of other corrosion types in Table 1, please refer to the introduction of the diameter range and fluorescence intensity range of the fluorescent spots of the above corrosion types, which will not be repeated here.

[0151] It should be noted that since the fluorescence characteristics are affected by the characteristics of the corrosion type, they have different shapes and density distributions, which increases the difficulty of identification. Therefore, in order to provide accurate identification indicators for the automatic identification method, the three-dimensional image data of the corrosion area can be extracted and analyzed by manual identification to obtain the spatial distribution information and component characteristic information of the corrosion products in the corrosion area, the fluorescence distribution characteristics of the fluorescence points, and establish a database to realize the extraction and identification of corrosion characteristics.

[0152] It should be noted that the fluorescent spots are local highlight spots that conform to the unimodal distribution.

[0153] In some embodiments, the fluorescent image of the corrosion area can be cropped to obtain 30 data blocks, each of which has a volume of 1024×1024×10 cubic millimeters. Afterwards, the volume of each data block can be two-dimensionally projected to obtain multiple two-dimensional image data sets. Afterwards, the data set can be identified by the particle analysis tool detection method, probability point detection method, multi-threshold segmentation method and the method provided in the present application in the ImageJ software to obtain performance evaluation data of the corrosion identification result.

[0154] For example, Figure 5As shown, an example schematic diagram of performance evaluation data provided by an embodiment of the present application. Among them, the three evaluation indicators of accuracy (i.e., Precision), recall (i.e., Recall) and F1 score (i.e., F-score) of the method provided by the present application are all higher than those of the particle analysis tool detection method, probability point detection method and multi-threshold segmentation method, and the F1 score is the value after weighted harmonic average of accuracy and recall.

[0155] It should be noted that the particle analysis tool detection method does not filter the image, so that the image noise and uneven illumination affect the recognition of the fluorescence signal, resulting in under-segmentation and low recall. The multi-threshold analysis method adds multiple thresholds on the basis of the particle analysis tool detection method, which can segment the signal at multiple levels and gradually approach the target recognition area. Therefore, the accuracy is higher than that of the particle analysis tool detection method, but the overall performance is still low. The probability point detection method converts the fluorescence signal of the image into a probability space, that is, all pixels are assigned probabilities, so that the choice of threshold has a greater impact on the result. Choosing a higher threshold will eliminate weak signals, and choosing a lower threshold will retain the background and noise of the image. Therefore, the probability point detection method has better overall performance than the particle analysis tool detection method and the multi-threshold analysis method, but the threshold needs to be adjusted continuously to balance the accuracy and recall rate, and the stability is poor.

[0156] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. It can be understood that in order to realize the above functions, the device for identifying the corrosion area includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the steps of the method for identifying the corrosion area of ​​each example described in the embodiment disclosed in this application, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0157] The embodiment of the present application also provides a device for identifying a corrosion area. The device for identifying a corrosion area can be an optical microscopic imaging system, or a CPU in the optical microscopic imaging system, or a module for evaluating a corrosion area in the optical microscopic imaging system, or a client for evaluating a corrosion area in the optical microscopic imaging system.

[0158] The embodiment of the present application can divide the corrosion area identification device into functional modules or functional units according to the above method example. For example, each functional module or functional unit can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules or functional units. Among them, the division of modules or units in the embodiment of the present application is schematic, which is only a logical function division. There may be other division methods in actual implementation.

[0159] The present application embodiment provides a device for identifying a corrosion area. Figure 6 As shown, the device for identifying the corrosion area may include: an acquisition module 601 and a processing module 602 .

[0160] The acquisition module 601 is used to acquire the chemical composition of the corrosion area and the three-dimensional image data of the corrosion area.

[0161] The processing module 602 is used to obtain corrosion characteristic information of the corrosion area based on the chemical composition and the three-dimensional image data. The processing module 602 is also used to obtain a corrosion identification result based on the corrosion characteristic information, and the corrosion identification result is used to indicate the corrosion condition of the corrosion area.

[0162] Figure 7 7 is a schematic diagram of another device for identifying a corrosion region according to an exemplary embodiment. The device for identifying a corrosion region may include a processor 702, and the processor 702 is used to execute application code to implement the method for identifying a corrosion region in the present application.

[0163] The processor 702 may be a central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the present application.

[0164] like Figure 7 As shown, the device for identifying a corrosion region may further include a memory 703. The memory 703 is used to store application program codes for executing the solution of the present application, and the execution is controlled by the processor 702.

[0165] The memory 703 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 703 may exist independently and be connected to the processor 702 via a bus 704. The memory 703 may also be integrated with the processor 702.

[0166] like Figure 7 As shown, the device for identifying a corrosion region may further include a communication interface 701, wherein the communication interface 701, the processor 702, and the memory 703 may be coupled to each other, for example, via a bus 704. The communication interface 701 is used to exchange information with other devices, for example, to support information exchange between the device for identifying a corrosion region and other devices.

[0167] It should be pointed out that Figure 7 The device structure shown in the figure does not constitute a limitation on the identification device of the corrosion area, except Figure 7 In addition to the components shown, the corrosion area identification device may include more or fewer components than shown, or combine certain components, or have a different arrangement of components.

[0168] In actual implementation, the functions implemented by the processing module 602 can be Figure 7 The processor 702 shown calls the program code in the memory 703 to implement.

[0169] The present application also provides a computer-readable storage medium, on which instructions are stored. When the instructions in the computer-readable storage medium are executed by a processor of a computer device, the computer can execute the method for identifying a corrosion area provided in the above-mentioned embodiment. For example, the computer-readable storage medium may be a memory 703 including instructions, and the above instructions may be executed by a processor 702 of a computer device to complete the above method. Optionally, the computer-readable storage medium may be a non-temporary computer-readable storage medium, for example, a non-temporary computer-readable storage medium may be a ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

[0170] Figure 8 A conceptual partial view of a computer program product provided by an embodiment of the present application is schematically shown, where the computer program product includes a computer program for executing a computer process on a computing device.

[0171] In one embodiment, the computer program product is provided using a signal bearing medium 800. The signal bearing medium 800 may include one or more program instructions that, when executed by one or more processors, may provide the above-described Figure 2 Thus, for example, reference to Figure 2 In the embodiment shown in , one or more features of S201 to S203 may be undertaken by one or more instructions associated with the signal bearing medium 800. In addition, Figure 8 The program instructions in also describe example instructions.

[0172] In some examples, the signal bearing medium 800 may include a computer readable medium 801, such as, but not limited to, a hard drive, a compact disk (CD), a digital video disk (DVD), a digital tape, a memory, a read-only memory (ROM) or a random access memory (RAM), and the like.

[0173] In some implementations, the signal bearing medium 800 may include a computer recordable medium 802 such as, but not limited to, a memory, a read / write (R / W) CD, a R / W DVD, or the like.

[0174] In some implementations, signal bearing medium 800 may include communication medium 803 such as, but not limited to, digital and / or analog communication media (eg, fiber optic cables, waveguides, wired communication links, wireless communication links, etc.).

[0175] The signal bearing medium 800 may be communicated by a wireless form of communication medium 803. The one or more program instructions may be, for example, computer executable instructions or logic implemented instructions.

[0176] In some examples, the corrosion region identification device can be configured to provide various operations, functions, or actions in response to one or more program instructions in the computer readable medium 801, the computer recordable medium 802, and / or the communication medium 803.

[0177] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0178] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or 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.

[0179] The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0180] In addition, each functional unit in each embodiment of the present application 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. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0181] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the full classification part or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including a number of instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute the full classification part or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes various media that can store program codes, such as-U disk, mobile hard disk, ROM, RAM, disk or CD.

[0182] In the description of this specification, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.

[0183] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for identifying a corrosion area, characterized in that: The method comprises: Acquiring chemical composition of the corrosion area and three-dimensional image data of the corrosion area; Based on the chemical composition and the three-dimensional image data, obtaining corrosion characteristic information of the corrosion area; Based on the corrosion feature information, a corrosion identification result is obtained, and the corrosion identification result is used to indicate the corrosion condition of the corrosion area.

2. The method according to claim 1, characterized in that The corrosion feature information includes chemical corrosion information and three-dimensional corrosion information, wherein the chemical corrosion information is used to indicate the corrosion feature corresponding to the chemical composition, and the three-dimensional corrosion information is used to indicate the corrosion feature corresponding to the morphology of the corrosion area; the corrosion feature information of the corrosion area is obtained based on the chemical composition and the three-dimensional image data, including: Based on the chemical composition, obtaining the chemical corrosion information; Performing a cross-sectional analysis on the three-dimensional image data to obtain corrosion cross-sectional information, wherein the corrosion cross-sectional information is used to indicate the corrosion state of the cross-sectional area of ​​the corrosion region; Based on the corrosion profile information, the three-dimensional corrosion information is obtained.

3. The method according to claim 2, characterized in that The step of performing a cross-section analysis on the three-dimensional image data to obtain corrosion cross-section information includes: converting the three-dimensional image data into two-dimensional image data; Processing the two-dimensional image data based on a mathematical morphology algorithm and an image binarization algorithm to obtain foreground image data; The foreground image data is processed based on a density peak clustering algorithm to obtain the corrosion profile information.

4. The method according to claim 1, characterized in that: The corrosion area is an area in the target object where corrosion exists, and the corrosion area is an area that has been pretreated; wherein the pretreatment includes: fixing the area where corrosion exists by an organic solution, and embedding, staining, and solidifying the fixed area; the contrast ratio of the three-dimensional image data is greater than a preset contrast ratio threshold.

5. The method according to claim 4, characterized in that The immobilized region is embedded, including: embedding through a gel solution, wherein the gel solution is prepared by sodium acrylate, ammonium acrylate, N-methylenebisacrylamide, nitroxyl piperidinol, tetramethylethylenediamine and ammonium persulfate.

6. The method according to any one of claims 1 to 5, characterized in that Acquiring three-dimensional image data of the corrosion area includes: Acquire a two-dimensional image of the corrosion area; Perform three-dimensional reconstruction processing on the two-dimensional image to obtain the three-dimensional image data.

7. The method according to any one of claims 1 to 5, characterized in that The method further comprises: A corrosion assessment database is established based on the chemical composition, the three-dimensional image data and the corrosion identification result.

8. A device for identifying a corrosion area, characterized in that: The device comprises an acquisition module and a processing module: The acquisition module is used to acquire the chemical composition of the corrosion area and the three-dimensional image data of the corrosion area; The processing module is used to obtain corrosion characteristic information of the corrosion area based on the chemical composition and the three-dimensional image data; The processing module is further used to obtain a corrosion identification result based on the corrosion feature information, and the corrosion identification result is used to indicate the corrosion condition of the corrosion area.

9. A device for identifying a corrosion area, characterized in that: include: Processor and memory; The processor is coupled to the memory; The memory is used to store one or more programs, and one or more of the programs include computer-executable instructions. When the corrosion area identification device is running, the processor executes the computer-executable instructions stored in the memory to enable the corrosion area identification device to perform the method described in any one of claims 1-7.

10. A computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, characterized in that: When a computer executes the instruction, the computer performs the method according to any one of claims 1 to 7.

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