Component inner cavity size measurement method and system based on DR detection reconstruction three-dimensional imaging

Abstract

The invention belongs to the technical field of quality detection, and discloses a component inner cavity size measurement method and system based on DR detection reconstruction three-dimensional imaging, and the method comprises the steps: building a position angle relation model of a component, a ray source and an imaging plate, and obtaining a complex inner cavity multi-morphology flaw detection image of the component through the position angle relation model; adjusting the position relation of the radiation source, the imaging plate and the non-inner-cavity twin of the component to be the same as the position angle relation model, and obtaining a multi-morphology flaw detection image of the non-inner-cavity twin; carrying out difference processing on the multi-morphology flaw detection images of the component and the twin without the inner cavity, carrying out adaptive threshold processing on a difference result, and carrying out pixel conversion to obtain a complex inner cavity contour coordinate; and reconstructing a three-dimensional entity of the inner cavity by using the complex inner cavity contour coordinates and the position angle relation model, and obtaining the feature size of the inner cavity to be measured from the three-dimensional entity of the inner cavity. The method can break through the limitation of image definition and a detection area, and achieves the measurement of the size of the complex inner cavity of the component based on DR detection.

Description

Technical Field

[0001] The present application belongs to the field of quality inspection, and more specifically, to a method and system for measuring the inner cavity size of a component based on DR inspection and reconstruction of three-dimensional imaging. Background Art

[0002] Complex inner cavity components such as hollow turbine blades, integral casings, and turbo pumps are widely used in advanced core equipment with surging demand in aerospace and other fields. The internal dimension measurement is a key technology to ensure the reliability and safety of equipment, and is also a core element to promote high-quality, low-cost, and short-cycle intelligent manufacturing. The main means of measuring complex inner cavity dimensions include three-dimensional optical imaging scanning and industrial CT full-size detection (i.e., industrial computed tomography detection, ICT, Industrial Computed Tomography). Three-dimensional optical imaging scanning relies on manually operated endoscopes to guide low-coherence light beams to the inner cavity surface of components, and sends reflected light signals to the detector through optical fibers. There are pain points such as low precision of complex surfaces, many detection space restrictions, and low manual operation efficiency, which leads to inefficient fluctuations in the measurement of inner cavity dimensions and is difficult to meet the current intelligent and efficient detection needs of advanced core equipment. Industrial CT full-size detection uses the attenuation characteristics of rays to obtain a large number of two-dimensional tomographic images, and generates three-dimensional images based on image reconstruction algorithms. There are pain points such as low data processing efficiency and high equipment operating costs, which makes it difficult to apply industrial CT full-size detection in engineering, resulting in the inability to measure some complex inner cavity dimensions, which seriously affects the performance, life and safety of major equipment such as casings. Summary of the invention

[0003] In view of the defects of the prior art, the purpose of this application is to provide a method and system for measuring the inner cavity dimensions of a component based on DR detection and reconstruction of three-dimensional imaging, aiming to solve the problems of low data processing efficiency, low accuracy in scanning complex surfaces and many detection space limitations in the existing measurement methods.

[0004] To achieve the above-mentioned purpose, the present application provides a method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging, comprising the following steps:

[0005] S1 establishes a position angle relationship model of a component, a radiation source and an imaging plate, and uses the position angle relationship model to obtain a complex inner cavity multi-morphology flaw detection image of the component;

[0006] S2: adjusting the positional relationship between the ray source, the imaging plate and the twin body without inner cavity of the component to be the same as the position angle relationship model, and obtaining a multi-morphological flaw detection image of the twin body without inner cavity by using DR detection technology;

[0007] S3 performs subtraction of the complex inner cavity multi-morphology flaw detection image and the multi-morphology flaw detection image without the inner cavity twin, and obtains the complex inner cavity image after adaptive threshold processing of the subtraction result; performs pixel conversion on the complex inner cavity image to obtain the complex inner cavity contour coordinates;

[0008] S4 reconstructs the three-dimensional entity of the inner cavity by using the complex inner cavity contour coordinates and the position angle relationship model, and obtains the characteristic dimensions of the inner cavity to be measured from the three-dimensional entity of the inner cavity.

[0009] The twin-driven inner cavity contour extraction method provided in the present application obtains the inner cavity contour based on the same group of flaw detection images and flaw detection parameter information, breaks through the limitations of image clarity and detection area, and solves the problems of low precision of complex surfaces in three-dimensional optical imaging scanning and many detection space restrictions.

[0010] Furthermore, in step S3, the step of performing adaptive threshold processing on the difference result includes:

[0011] S301: Divide the difference result into a plurality of rectangular areas of W*W pixel size, and calculate the local threshold of each rectangular area;

[0012] S302 compares each pixel value with the local threshold of its corresponding rectangular area: if the pixel value is greater than the corresponding local threshold, the pixel is retained; if the pixel value is less than the local threshold, the pixel is removed.

[0013] Furthermore, in step S302, the expression for calculating the local threshold is:

[0014]

[0015] Among them, T(x,y) represents the local threshold of position (x,y), N represents the total number of pixels in the neighborhood, (i,j) represents the neighborhood pixels around (x,y); I(i,j) represents the pixel value, and C represents a constant used to avoid over-thresholding.

[0016] Furthermore, in step S3, the complex inner cavity contour coordinates are expressed as:

[0017] {P i |P i =(x i ,y i ),i=1,2,…,n}

[0018] Among them, P i represents the coordinates of the i-th contour point, x i Represents the horizontal coordinate of the i-th contour point, y i represents the ordinate of the i-th contour point, and n represents the number of contour points.

[0019] Furthermore, in step S3, the complex inner cavity contour coordinates obtained after pixel conversion of the complex inner cavity image are expressed as:

[0020]

[0021] Among them, X i is the horizontal coordinate of the complex inner cavity contour point after pixel conversion, Y i is the ordinate of the complex inner cavity contour point after pixel conversion, ray d is the flaw detection distance from the ray source to the component, img d is the imaging distance from the imaging plate to the center of the component, m is the height of the imaging plate, n is the width of the imaging plate, M represents the number of pixels in the horizontal direction of the image, and N represents the number of pixels in the vertical direction of the image.

[0022] Furthermore, in step S4, the step of reconstructing the inner cavity three-dimensional entity includes:

[0023] S401: a virtual ray source and a virtual imaging plate are arranged on both sides of a component model, and the centers of the virtual ray source and the virtual imaging plate are arranged opposite to each other;

[0024] S402: establishing an image coordinate system with the upper left corner of the virtual imaging plate as the origin, and establishing a world coordinate system with the center of the virtual turntable as the origin;

[0025] S403 acquires the center coordinates of the virtual imaging plate based on the coordinates of the virtual ray source in the world coordinate system; calculates the three-dimensional world coordinates of the defect contour point based on the two-dimensional image coordinates of the defect contour point and the center coordinates of the virtual imaging plate;

[0026] S404: starting from the virtual ray source and taking all defect contour points as the end points, drawing rays, rotating the rays in sequence and finding intersections with the component model, counting the coordinates of the intersections at different rotation angles, and obtaining a polyhedron containing all the intersections to obtain a three-dimensional solid of the inner cavity.

[0027] Furthermore, in step S403, the formula for calculating the three-dimensional world coordinates of the defect contour point is:

[0028]

[0029] Among them, (X2, Y2, Z2) are the center coordinates of the virtual imaging plate, (X3, Y3) are the two-dimensional image coordinates of the defect contour point, (X4, Y4, Z4) are the three-dimensional world coordinates of the defect contour point, m is the height of the virtual imaging plate, n is the width of the virtual imaging plate, and θ is the imaging angle formed by the line connecting the virtual ray source and the center of the virtual imaging plate and the X-axis in the world coordinate system.

[0030] Furthermore, the center coordinates of the virtual imaging plate are expressed as:

[0031]

[0032] Among them, (X2, Y2, Z2) is the center coordinate of the virtual imaging plate, (X1, Y1, Z1) is the coordinate of the virtual ray source in the world coordinate system, and ray D is the flaw detection distance from the virtual ray source to the component model, img D is the imaging distance from the virtual imaging plate to the center of the component model, and θ is the imaging angle formed by the line connecting the virtual ray source and the center of the virtual imaging plate and the X-axis in the world coordinate system.

[0033] According to another aspect of the present application, a system for implementing a method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging is also provided, comprising:

[0034] The first image acquisition module is used to establish a position angle relationship model of the component, the radiation source and the imaging plate, and to obtain a complex inner cavity multi-morphology flaw detection image of the component using the position angle relationship model;

[0035] A second image acquisition module is used to adjust the positional relationship between the ray source, the imaging plate and the twin body without inner cavity of the component to be the same as the position angle relationship model, and to acquire a multi-morphological flaw detection image of the twin body without inner cavity by using DR detection technology;

[0036] A contour parameter acquisition module is used to perform a subtraction between the complex inner cavity multi-morphology flaw detection image and the multi-morphology flaw detection image of the twin body without inner cavity, and obtain a complex inner cavity image after performing adaptive threshold processing on the subtraction result; and is also used to perform pixel conversion on the complex inner cavity image to obtain the complex inner cavity contour coordinates;

[0037] The inner cavity characteristic dimension acquisition module is used to reconstruct the inner cavity three-dimensional entity by using the complex inner cavity contour coordinates and the position angle relationship model, and to acquire the inner cavity characteristic dimension to be measured from the inner cavity three-dimensional entity.

[0038] According to yet another aspect of the present application, a computer program product is provided. When the computer program product is executed on a processor, the processor is enabled to execute any of the above methods.

[0039] It can be understood that the beneficial effects of the second to third aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0040] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the prior art:

[0041] (1) This application proposes a twin-driven inner cavity contour extraction algorithm for the component to be measured, which obtains the complex inner cavity contour of the component based on the same group of flaw detection images and flaw detection parameter information, breaks through the limitations of image clarity and detection area, and realizes high-precision and unlimited spatial detection, solving the pain points of low precision and many spatial restrictions in three-dimensional optical imaging scanning of complex surfaces.

[0042] (2) This application creates a multi-angle inner cavity entity reconstruction model and proposes a coordinate dimension upgrade method from a two-dimensional image to a three-dimensional entity, breaking through the limitations of machine automatic fitting and two-dimensional to three-dimensional, improving the efficiency of component inner cavity detection, and solving the pain point of low efficiency of three-dimensional optical imaging scanning and industrial CT full-size detection.

[0043] (3) The present application develops a system for measuring the dimensions of complex internal cavities of components, providing an integrated solution from component reconstruction to dimension measurement, filling the technical gap in the existing technology of dimension measurement based on DR detection, i.e., digital radiography (DR) reconstruction, and further reducing the pain point of high operating costs of component internal cavity detection equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic flow chart of a component inner cavity size measurement method based on DR detection and reconstruction of three-dimensional imaging provided in an embodiment of the present application;

[0045] Figure 2 It is a schematic diagram of the process flow of the twin-driven inner cavity contour extraction algorithm provided in the embodiment of the present application;

[0046] Figure 3 It is a schematic diagram of the process of multi-angle inner cavity entity reconstruction and measurement model provided in an embodiment of the present application;

[0047] Figure 4 It is a schematic diagram of the coordinate dimensionality increase model provided in the embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0049] The term "and / or" in this article is 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. The symbol " / " in this article indicates that the associated objects are in an or relationship, for example, A / B means A or B.

[0050] The terms "first" and "second" in the specification and claims herein are used to distinguish different objects rather than to describe a specific order of the objects. For example, a first response message and a second response message are used to distinguish different response messages rather than to describe a specific order of the response messages.

[0051] 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.

[0052] In the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more than two. For example, multiple processing units refer to two or more processing units, etc.; multiple elements refer to two or more elements, etc.

[0053] Next, the technical solutions provided in the embodiments of the present application are introduced.

[0054] This embodiment provides a method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging. Figure 1 As shown, the following steps are included:

[0055] S1 establishes a position angle relationship model of the component, the radiation source and the imaging plate, and uses the position angle relationship model to obtain the complex inner cavity multi-morphology flaw detection image of the component.

[0056] Place the component on the turntable of the industrial X-ray detection device, set the initial position of the component and the turntable, adjust the position of the radiation source and the imaging plate to form a position angle relationship model of the component, the radiation source and the imaging plate. Use the automatic positioning system and software-assisted tools in the detection device to record the distance from the radiation source to the casting (ray d ), the distance from the casting to the imaging plate (img d ), the rotation angle of the turntable (θ). Set the step size of each turntable rotation, and continuously modify the turntable rotation angle during the inspection and shooting process. Each flaw detection image generated has corresponding position angle parameters, and then save these position angle parameters in XML format files, and keep the file name consistent with the image name so that it can be called and applied in subsequent steps.

[0057] S2 adjusts the positional relationship between the ray source, the imaging plate and the cavity-free twin of the component to be the same as the position angle relationship model, and uses DR detection technology to obtain multi-morphological flaw detection images of the cavity-free twin.

[0058] Before the component is produced, the corresponding three-dimensional model is generated, so the twin component without inner cavity can be produced based on the three-dimensional model of the component in step 1. Figure 2 As shown, it is a schematic diagram of the process flow of the twin-driven inner cavity contour extraction algorithm provided in this embodiment, such as Figure 2 As shown in a, the obtained twin component is placed on the turntable of the industrial X-ray detection device, and the initial position of the twin component and the turntable is set. Read the XML file parameters saved in step 1, adjust the positions of the ray source, imaging plate and turntable to make them consistent with the parameters of the position angle relationship model in step S1. Then follow Figure 2 As shown in b, the twin component is photographed and tested at multiple angles, and multiple morphological flaw detection images of the twin component without inner cavity are generated. Each flaw detection image has position angle parameters corresponding to the image in step 1. The position angle parameters are saved in an XML format file, and the file name is consistent with the image name.

[0059] S3 performs subtraction on the complex inner cavity multi-shape flaw detection image and the multi-shape flaw detection image, obtains the complex inner cavity image after adaptive threshold processing on the subtraction result; performs pixel conversion on the complex inner cavity image to obtain the complex inner cavity contour coordinates.

[0060] The specific steps of subtracting the complex inner cavity multi-morphology flaw detection image from the multi-morphology flaw detection image are as follows: subtract the grayscale values ​​of the two images corresponding to the position angle parameter items of the complex inner cavity multi-morphology flaw detection image and the multi-morphology flaw detection image without the inner cavity twin, so as to obtain the complex inner cavity image; specifically, read the XML format file generated by step S1 and step S2, subtract the grayscale values ​​of the two images with the same corresponding position angle parameters, and obtain the preliminary complex inner cavity image.

[0061] The specific steps of obtaining a complex lumen image after adaptive threshold processing of the difference result are as follows:

[0062] S301 divides the difference result (i.e., the preliminary complex lumen image) into a plurality of rectangular areas of W*W pixels, and calculates the local threshold of each rectangular area. Specifically, for each local window, the mean of all pixels in the window is calculated, and then the mean is used as the local threshold. The expression for calculating the local threshold is:

[0063]

[0064] Among them, T(x,y) represents the local threshold of position (x,y), N represents the total number of pixels in the neighborhood; (i,j)∈N(x,y) represents the neighborhood pixels around (x,y); I(i,j) represents the pixel value, and C represents a constant used to avoid over-thresholding.

[0065] S302 compares each pixel value with the local threshold of the corresponding rectangular area: if the pixel value is greater than the local threshold of the corresponding rectangular area, the pixel is retained; if the pixel value is less than the local threshold of the corresponding rectangular area, the pixel is removed.

[0066] A complex inner cavity image is obtained based on the retained pixel values, and the coordinates of the contour points of the complex inner cavity image are pixel-converted to obtain the coordinates of the complex inner cavity contour.

[0067] Specifically, the contour extraction function in the opencv library is used to obtain the coordinates of the complex inner cavity contour and expressed as:

[0068] {P i |P i =(x i ,y i ),i=1,2,…,n}(2)

[0069] Among them, P i represents the coordinates of the i-th contour point, x i Represents the horizontal coordinate of the i-th contour point, y i represents the ordinate of the i-th contour point, and n represents the number of contour points.

[0070] After pixel conversion, the coordinates of the complex lumen image are expressed as:

[0071]

[0072] Among them, X i is the horizontal coordinate of the complex inner cavity contour point after pixel conversion, Y i is the ordinate of the complex inner cavity contour point after pixel conversion, ray d is the flaw detection distance from the ray source to the component, img d is the imaging distance from the imaging plate to the center of the component, m is the height of the imaging plate, n is the width of the imaging plate, M represents the number of pixels in the horizontal direction of the image, and N represents the number of pixels in the vertical direction of the image.

[0073] S4 uses the contour parameters and position angle relationship model of the complex inner cavity to reconstruct the inner cavity three-dimensional entity, and obtains the inner cavity characteristic dimensions to be measured from the inner cavity three-dimensional entity.

[0074] Specifically, Figure 3 As shown, it is a schematic diagram of the process of reconstructing and measuring the model based on the multi-angle inner cavity entity. The steps of reconstructing the inner cavity three-dimensional entity include:

[0075] S401 Figure 3As shown in a, the virtual ray source and the virtual imaging plate are placed on both sides of the component model, and the centers of the virtual ray source and the virtual imaging plate are set relative to each other. The distance from the virtual ray source to the component model is defined as the flaw detection distance (ray D ), the distance from the virtual imaging plate to the center of the component model is defined as the imaging distance (img D ). The height of the virtual imaging plate is recorded as m, and its width is recorded as n. The angle between the line connecting the virtual ray source and the center of the virtual imaging plate and the X-axis in the world coordinate system is defined as the imaging angle θ. The above parameters are adjusted according to the XML format file generated in step S1 and step S2.

[0076] S402 Figure 3 As shown in b, the image coordinate system is established with the upper left corner of the imaging plate as the origin, and the world coordinate system is established with the center of the virtual turntable as the origin;

[0077] S403 Figure 4 As shown, the center coordinates of the virtual imaging plate are obtained based on the coordinates of the virtual ray source in the world coordinate system; the three-dimensional world coordinates of the defect contour point are calculated based on the two-dimensional image coordinates of the defect contour point and the center coordinates of the virtual imaging plate to achieve coordinate dimensionality upgrade.

[0078] Specifically, the formula for calculating the three-dimensional world coordinates of the defect contour point is:

[0079]

[0080] Among them, (X2, Y2, Z2) are the center coordinates of the virtual imaging plate, (X3, Y3) are the two-dimensional image coordinates of the defect contour point, (X4, Y4, Z4) are the three-dimensional world coordinates of the defect contour point, m is the height of the virtual imaging plate, n is the width of the virtual imaging plate, and θ is the imaging angle formed by the line connecting the virtual ray source and the center of the virtual imaging plate and the X-axis in the world coordinate system.

[0081] The center coordinates of the virtual imaging plate in the above formula (4) are expressed as:

[0082]

[0083] Among them, (X2, Y2, Z2) is the center coordinate of the virtual imaging plate, (X1, Y1, Z1) is the coordinate of the virtual ray source in the world coordinate system, and ray D is the flaw detection distance from the virtual ray source to the component model, img D is the imaging distance from the virtual imaging plate to the center of the component model.

[0084] S404 uses the ray source as the starting point and all defect contour points as the end points to draw rays, rotate the rays in sequence and intersect with the component, count the coordinates of the intersection points at different rotation angles, and obtain a polyhedron containing all the intersection points to obtain the following: Figure 3 The three-dimensional solid of the inner cavity shown in c.

[0085] Specifically, after converting the two-dimensional points of the defect contour in the image into three-dimensional points in the world coordinate system through the above formulas (4)-(5), the virtual ray source is used as the starting point and the numerous defect contour points are used as the end points to intersect with the component model in sequence. The coordinates of the intersection points at each angle are counted, and the Delaunay triangulation method is used to generate a polyhedron containing all the intersection points. Each flaw detection angle can generate a polyhedron generated by the intersection. By intersecting these polyhedrons, the characteristic polyhedron representing the inner cavity entity can be obtained, and the reconstruction process is completed.

[0086] The complex inner cavity dimension measurement system is created. The measurement system has a series of functions such as creating a new project, saving, setting, and reading. After creating a new project, input the component inner cavity flaw detection image, the twin component flaw detection image without inner cavity, and the XML format file into the measurement system, and finally output the reconstructed inner cavity entity. After selecting the measurement range, use pyvista and numpy library functions to measure the inner cavity characteristic dimensions to obtain the measurement results.

[0087] The twin-driven inner cavity contour extraction method provided in the present application obtains the inner cavity contour based on the same group of flaw detection images and flaw detection parameter information, breaks through the limitations of image clarity and detection area, and solves the problems of low precision of complex surfaces in three-dimensional optical imaging scanning and many detection space restrictions.

[0088] In another embodiment, a system for implementing a method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging is also provided, comprising:

[0089] The first image acquisition module is used to establish a position angle relationship model of the component, the radiation source and the imaging plate, and to obtain a complex inner cavity multi-morphology flaw detection image of the component using the position angle relationship model;

[0090] The second image acquisition module is used to adjust the positional relationship between the ray source, the imaging plate and the twin body without inner cavity of the component to be the same as the position angle relationship model, and to obtain a multi-morphological flaw detection image of the twin body without inner cavity by using DR detection technology;

[0091] The contour parameter acquisition module is used to perform subtraction between the complex inner cavity multi-shape flaw detection image and the multi-shape flaw detection image to obtain the contour parameters of the complex inner cavity in the image;

[0092] The inner cavity characteristic dimension acquisition module is used to reconstruct the inner cavity three-dimensional entity by using the contour parameters and position angle relationship model of the complex inner cavity, and obtain the inner cavity characteristic dimension to be measured from the inner cavity three-dimensional entity.

[0093] It can be understood that the detailed functional implementation of each of the above-mentioned units / modules can be found in the introduction of the aforementioned method embodiment, and will not be repeated here.

[0094] It should be understood that the above-mentioned device is used to execute the method in the above-mentioned embodiment. The implementation principle and technical effect of the corresponding program module in the device are similar to those described in the above-mentioned method. The working process of the device can refer to the corresponding process in the above-mentioned method, which will not be repeated here.

[0095] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0096] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0097] It is understandable that the processor in the embodiment of the present application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor.

[0098] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0099] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0100] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0101] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging, characterized in that: The following steps are involved: S1 establishes a position angle relationship model of a component, a radiation source and an imaging plate, and uses the position angle relationship model to obtain a complex inner cavity multi-morphology flaw detection image of the component; S2: adjusting the positional relationship between the ray source, the imaging plate and the twin body without inner cavity of the component to be the same as the position angle relationship model, and obtaining a multi-morphological flaw detection image of the twin body without inner cavity by using DR detection technology; S3: subtract the complex inner cavity multi-morphology flaw detection image from the multi-morphology flaw detection image of the twin body without inner cavity, and obtain the complex inner cavity image after adaptive threshold processing of the subtraction result; perform pixel conversion on the complex inner cavity image to obtain the complex inner cavity contour coordinates; S4 reconstructs the three-dimensional entity of the inner cavity by using the complex inner cavity contour coordinates and the position angle relationship model, and obtains the characteristic dimensions of the inner cavity to be measured from the three-dimensional entity of the inner cavity.

2. The method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging as claimed in claim 1, characterized in that: In step S3, the step of performing adaptive threshold processing on the difference result includes: S301: Divide the difference result into a plurality of rectangular areas of W*W pixel size, and calculate the local threshold of each rectangular area; S302 compares each pixel value with the local threshold of its corresponding rectangular area: if the pixel value is greater than the corresponding local threshold, the pixel is retained; if the pixel value is less than the local threshold, the pixel is removed.

3. The method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging as claimed in claim 2, characterized in that: In step S302, the expression for calculating the local threshold is: Among them, T(x,y) represents the local threshold of position (x,y), N represents the total number of pixels in the neighborhood, (i,j) represents the neighborhood pixels around (x,y); I(i,j) represents the pixel value, and C represents a constant used to avoid over-thresholding.

4. The method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging as claimed in claim 1, characterized in that: In step S3, the coordinates of the complex lumen image are expressed as: {P i |P i =(x i ,y i ),i=1,2,…,n} Among them, P i represents the coordinates of the i-th contour point, x i Represents the horizontal coordinate of the i-th contour point, y i represents the ordinate of the i-th contour point, and n represents the number of contour points.

5. The method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging as claimed in claim 4, characterized in that: In step S3, the complex inner cavity contour coordinates obtained after pixel conversion of the complex inner cavity image are expressed as: Among them, X i is the horizontal coordinate of the complex inner cavity contour point after pixel conversion, Y i is the ordinate of the complex inner cavity contour point after pixel conversion, ray d is the flaw detection distance from the ray source to the component, img d is the imaging distance from the imaging plate to the center of the component, m is the height of the imaging plate, n is the width of the imaging plate, M represents the number of pixels in the horizontal direction of the image, and N represents the number of pixels in the vertical direction of the image.

6. The method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging as claimed in claim 1, characterized in that: In step S4, the step of reconstructing the inner cavity three-dimensional entity includes: S401: a virtual ray source and a virtual imaging plate are arranged on both sides of a component model, and the centers of the virtual ray source and the virtual imaging plate are arranged opposite to each other; S402: establishing an image coordinate system with the upper left corner of the virtual imaging plate as the origin, and establishing a world coordinate system with the center of the virtual turntable as the origin; S403 acquires the center coordinates of the virtual imaging plate based on the coordinates of the virtual ray source in the world coordinate system; calculates the three-dimensional world coordinates of the defect contour point based on the two-dimensional image coordinates of the defect contour point and the center coordinates of the virtual imaging plate; S404: starting from the virtual ray source and taking all defect contour points as the end points, drawing rays, rotating the rays in sequence and finding intersections with the component model, counting the coordinates of the intersections at different rotation angles, and obtaining a polyhedron containing all the intersections to obtain a three-dimensional solid of the inner cavity.

7. The method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging as claimed in claim 6, characterized in that: In step S403, the formula for calculating the three-dimensional world coordinates of the defect contour point is: Among them, (X2, Y2, Z2) are the center coordinates of the virtual imaging plate, (X3, Y3) are the two-dimensional image coordinates of the defect contour point, (X4, Y4, Z4) are the three-dimensional world coordinates of the defect contour point, m is the height of the virtual imaging plate, n is the width of the virtual imaging plate, and θ is the imaging angle formed by the line connecting the virtual ray source and the center of the virtual imaging plate and the X-axis in the world coordinate system.

8. The method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging as claimed in claim 6, characterized in that: The center coordinates of the virtual imaging plate are expressed as: Among them, (X2, Y2, Z2) is the center coordinate of the virtual imaging plate, (X1, Y1, Z1) is the coordinate of the virtual ray source in the world coordinate system, and ray D is the detection distance from the virtual ray source to the component model, img D is the imaging distance from the virtual imaging plate to the center of the component model, and θ is the imaging angle formed by the line connecting the virtual ray source and the center of the virtual imaging plate and the X-axis in the world coordinate system.

9. A system for realizing a method for measuring the inner cavity size of a component based on DR detection and reconstruction of three-dimensional imaging, characterized in that: include: The first image acquisition module is used to establish a position angle relationship model of the component, the radiation source and the imaging plate, and to obtain a complex inner cavity multi-morphology flaw detection image of the component using the position angle relationship model; A second image acquisition module is used to adjust the positional relationship between the ray source, the imaging plate and the twin body without inner cavity of the component to be the same as the position angle relationship model, and to acquire a multi-morphological flaw detection image of the twin body without inner cavity by using DR detection technology; A contour parameter acquisition module is used to perform a subtraction between the complex inner cavity multi-morphology flaw detection image and the multi-morphology flaw detection image of the twin body without inner cavity, and obtain a complex inner cavity image after adaptive threshold processing of the subtraction result; and is also used to perform pixel conversion on the complex inner cavity image to obtain complex inner cavity contour coordinates; The inner cavity characteristic dimension acquisition module is used to reconstruct the inner cavity three-dimensional entity by using the complex inner cavity contour coordinates and the position angle relationship model, and to acquire the inner cavity characteristic dimension to be measured from the inner cavity three-dimensional entity.

10. A computer program product, characterized in that When the computer program product runs on a processor, the processor is caused to execute the method according to any one of claims 1 to 8.

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