Ceramic matrix composite material structure nondestructive testing method based on gray scale identification

Abstract

The invention provides a nondestructive testing method for a ceramic-based composite material structure based on gray scale recognition. The nondestructive testing method comprises the following steps: obtaining a slice gray scale image of the ceramic-based composite material structure; de-noising processing is carried out on the slice gray level image by adopting a morphological expansion algorithm to obtain a processed feature image; identifying the feature image to obtain a contour boundary analysis result; according to a contour boundary analysis result, multiple groups of actual characteristic parameters are obtained to form a section characteristic data set; identifying a typical structure region where the typical structure is located in the feature image, obtaining typical feature parameters of the ceramic matrix composite structure in the typical structure region, and forming a typical structure region feature data set; and comparing the section feature data set and the typical structure region feature data set with design feature parameters of the ceramic matrix composite structure to obtain a consistency test result. According to the invention, nondestructive testing and consistency testing of the SiC / SiC composite material structure can be realized.

Description

Technical Field

[0001] The invention relates to the technical field of nondestructive testing, and more specifically to a nondestructive testing method for ceramic-based composite materials based on grayscale recognition. Background Art

[0002] Ceramic matrix composites have developed into key materials for high-temperature thermal structural components in the aerospace field due to their excellent properties such as high strength, high temperature resistance and designability. SiC / SiC composites prepared using continuous fiber preforms have structural designability. They can achieve performance "regulation" and near-net-shape preparation of complex structures through typical structural design and optimization of fiber preform weaving parameters. However, in the preparation process of SiC / SiC composites, changes in the structural characteristics of components such as fibers, matrix, and pores directly affect the product quality and performance stability of the final composite. In view of the structural characteristics of multi-component composites of ceramic matrix composites, quality monitoring and organizational evaluation of its components during the manufacturing cycle are important measures to improve product reliability. Nondestructive testing and analysis have been carried out for simple SiC / SiC composite specimens of flat type at home and abroad. However, for SiC / SiC composite components with complex structures (typical structures such as reinforcement, bending, and variable curved surfaces), how to evaluate the organizational integrity and structural consistency of composite components has become a key technical problem in the industrial quality evaluation of ceramic matrix composites.

[0003] At present, non-destructive testing of SiC / SiC composite materials is limited to the detection and analysis of flat structure test pieces and annular structures of equal thickness. Micro-scale detection methods such as X-CT and scanning electron microscope (SEM) are mostly used. The observation size is only at the 5-20mm level, which is difficult to meet the structural scanning of complex and large-sized (over 500mm) SiC / SiC composite materials. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] The technical problem to be solved by the present invention is that the existing nondestructive testing methods are unable to achieve structural scanning of large-sized SiC / SiC composite materials with complex structures, and thus are unable to perform consistency inspection on large-sized SiC / SiC composite materials with complex structures.

[0006] (II) Technical solution

[0007] To achieve the above object, the technical solution adopted by the present invention is:

[0008] The present invention provides a nondestructive testing method for a ceramic matrix composite material structure based on grayscale recognition, comprising the following steps:

[0009] S1, performing a tomographic scan on the ceramic matrix composite material structure along a preset slicing direction and at a preset slicing distance to obtain a slicing grayscale image of the ceramic matrix composite material structure;

[0010] S2, using a morphological dilation algorithm to perform denoising on the slice grayscale image to obtain a processed feature image;

[0011] S3, identifying the characteristic image, determining the contour boundary of the ceramic-based composite material structure in the characteristic image, and obtaining a contour boundary analysis result;

[0012] S4, obtaining actual characteristic parameters of the ceramic matrix composite material structure according to the contour boundary analysis result, analyzing multiple slice grayscale images in the preset slice direction one by one along the preset slice direction, obtaining multiple groups of actual characteristic parameters, and forming the multiple groups of actual characteristic parameters into a section characteristic data set;

[0013] S5, identifying a typical structure region where a typical structure in the characteristic image is located, and combining the section feature data set to obtain typical feature parameters of the ceramic matrix composite material structure in the typical structure region to form a typical structure region feature data set;

[0014] S6. Compare the section feature data set and the typical structural region feature data set with the design feature parameters of the ceramic matrix composite material structure, perform a consistency test on the ceramic matrix composite material structure, and obtain a consistency test result.

[0015] Preferably, the morphological dilation algorithm performs denoising on the slice grayscale image specifically through the following formula:

[0016]

[0017] Among them, N(X,Y) is the set of new grayscale images after denoising. It indicates that the slice grayscale image G is expanded using a disk-shaped structure element F. (x, y) represents the coordinates of the slice grayscale image G. The domain coordinate change of the disk-shaped structure element F is (i, j). The diameter of the disk-shaped structure element F is smaller than the characteristic node size of the fiber woven structure.

[0018] Preferably, the actual characteristic parameters include contour boundary size, cross-sectional fiber volume fraction, porosity, and pore distribution histogram.

[0019] Preferably, the step S3 specifically includes the following steps:

[0020] Acquiring the actual size of the ceramic matrix composite material structure corresponding to the characteristic image;

[0021] By calculating the image sizes at different gray values ​​one by one within the preset gray value range, an image size set corresponding to the characteristic image within the preset gray value range is obtained;

[0022] Comparing the image size corresponding to each grayscale value with the actual size, and determining a reference image size closest to the actual size;

[0023] Taking the grayscale value corresponding to the reference image size as the effective grayscale value of the corresponding feature image;

[0024] According to the effective grayscale value, the contour boundary of the ceramic matrix composite material structure in the characteristic image is determined to obtain a contour boundary analysis result.

[0025] Preferably, the preset grayscale value range is 5-30.

[0026] Preferably, the preset slicing direction includes at least one of an X-axis direction, a Y-axis direction, and a Z-axis direction.

[0027] Preferably, the preset slicing distance is 0.05mm-0.5mm.

[0028] Preferably, the typical structure includes a flange structure and a rib structure.

[0029] Preferably, the design feature parameters are determined according to the design model and weaving design specifications of the ceramic matrix composite material structure.

[0030] (III) Beneficial effects

[0031] The above technical solution of the present invention has at least the following advantages:

[0032] 1. The present invention uses X-ray computed tomography technology to achieve data set acquisition of large-size (more than 500 mm) SiC / SiC composite material structures, and adopts morphological expansion algorithm to solve the problem of noise in image acquisition of SiC / SiC composite material structures.

[0033] 2. Compared with conventional composite nondestructive testing methods, the nondestructive testing method provided by the present invention introduces relevant evaluation factors such as component strength design and weaving design specifications of the design model, improves the evaluation effectiveness of typical structural areas, and avoids misjudgment caused by simple grayscale differences.

[0034] 3. The present invention conducts consistency analysis on SiC / SiC composite material structures through a nondestructive testing method for ceramic-based composite materials based on grayscale recognition, realizes process-design testing of typical structures of large-size SiC / SiC composite materials, and provides technical and data support for quality improvement of subsequent typical structure weaving and molding processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 It is a schematic flow chart of a nondestructive testing method for a ceramic matrix composite material structure based on grayscale recognition provided in an embodiment of the present invention.

[0037] Figure 2 It is a specific implementation flow chart of the nondestructive testing method for ceramic-based composite material structure based on grayscale recognition provided by an embodiment of the present invention.

[0038] Figure 3 These are the slice grayscale images and characteristic images of the SiC / SiC composite material flanged rib structure provided by the embodiments of the present invention.

[0039] Figure 4 It is an extraction area diagram of actual characteristic parameters of the SiC / SiC composite material flanged rib structure provided by an embodiment of the present invention.

[0040] Figure 5 It is a pore distribution histogram of the SiC / SiC composite material flanged rib structure provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention 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 invention and are not intended to limit the present invention.

[0042] It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it may be directly located on the other element or indirectly located on the other element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or indirectly connected to the other element.

[0043] It should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present invention, and do not indicate that a device or element must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation on the present invention.

[0044] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating relative importance or indicating the number of technical features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. The specific implementation of the present invention is described in more detail below in conjunction with specific embodiments:

[0045] like Figure 1 and Figure 2 As shown, an embodiment of the present invention provides a nondestructive testing method for a ceramic matrix composite material structure based on grayscale recognition, comprising the following steps:

[0046] S1, performing a tomographic scan on the ceramic matrix composite material structure along a preset slicing direction and at a preset slicing distance to obtain a slicing grayscale image of the ceramic matrix composite material structure;

[0047] S2, using a morphological dilation algorithm to perform denoising on the slice grayscale image to obtain a processed feature image;

[0048] S3, identifying the characteristic image, determining the contour boundary of the ceramic matrix composite material structure in the characteristic image, and obtaining the contour boundary analysis result;

[0049] S4, according to the contour boundary analysis result, obtaining the actual characteristic parameters of the ceramic matrix composite material structure, analyzing multiple slice grayscale images in the preset slice direction one by one along the preset slice direction, obtaining multiple groups of actual characteristic parameters, and forming the multiple groups of actual characteristic parameters into a section characteristic data set;

[0050] S5, identifying the typical structure region where the typical structure is located in the feature image, and combining the section feature data set to obtain the typical feature parameters of the ceramic matrix composite material structure in the typical structure region to form a typical structure region feature data set;

[0051] S6. Compare the section feature data set and the typical structural region feature data set with the design feature parameters of the ceramic matrix composite material structure, perform a consistency test on the ceramic matrix composite material structure, and obtain a consistency test result.

[0052] In one embodiment, the morphological dilation algorithm specifically performs denoising on the slice grayscale image by the following formula:

[0053]

[0054] Among them, N(X,Y) is the set of new grayscale images after denoising. It indicates that the slice grayscale image G is expanded using a disk-shaped structure element F. (x, y) represents the coordinates of the slice grayscale image G. The domain coordinate change of the disk-shaped structure element F is (i, j). The diameter of the disk-shaped structure element F is smaller than the characteristic node size of the fiber woven structure.

[0055] In one embodiment, the actual characteristic parameters include contour boundary size, cross-sectional fiber volume fraction, porosity, and pore distribution histogram.

[0056] In one embodiment, step S3 specifically includes the following steps:

[0057] Acquire the actual size of the ceramic matrix composite structure corresponding to the feature image;

[0058] By calculating the image sizes at different gray values ​​one by one within the preset gray value range, an image size set corresponding to the characteristic image within the preset gray value range is obtained;

[0059] Compare the image size corresponding to each grayscale value with the actual size to determine the reference image size closest to the actual size;

[0060] The grayscale value corresponding to the reference image size is used as the effective grayscale value of the corresponding feature image;

[0061] According to the effective gray value, the contour boundary of the ceramic matrix composite material structure in the characteristic image is determined to obtain the contour boundary analysis result.

[0062] In one embodiment, the preset grayscale value range is 5 to 30. For characteristic images at different positions in the same preset slice direction, the X-ray will be exhausted when passing through the component, so for different characteristic images, the corresponding effective grayscale values ​​will also be different.

[0063] In one embodiment, the preset slicing direction includes at least one of an X-axis direction, a Y-axis direction, and a Z-axis direction.

[0064] In one embodiment, the preset slicing distance is 0.05 mm-0.5 mm.

[0065] In one embodiment, the typical structure includes a flange structure and a rib structure.

[0066] In one embodiment, the design feature parameters are determined based on a design model of the ceramic matrix composite structure and a weaving design specification.

[0067] The nondestructive testing method provided by the present invention is further described in detail below by taking the SiC / SiC composite material flanged rib structure as an example.

[0068] Step 1: Before preparing the SiC / SiC composite material flanged ribbed structure, it is necessary to first verify the braiding parameters and strength margin of the typical structure (such as rib structure and flange structure) of the SiC / SiC composite material flanged ribbed structure to obtain the fiber arrangement characteristics and fiber volume fraction range of each region of the typical structure. A structural design model is formed according to the formed material design specifications for subsequent typical structure verification.

[0069] Step 2: Use industrial CT to perform computer tomography to obtain an X-ray image of the SiC / SiC composite material flanged rib structure to be tested, which is a slice grayscale image. The preset slice distance is set according to the thickness, and the general slice distance is 0.05-0.5mm. The preset slice directions are X, Y, and Z directions to achieve slicing of components in three-dimensional directions.

[0070] Step 3: Remove noise from the acquired grayscale image of the slice, and fill the grayscale image with a morphological dilation algorithm using a disk-shaped structural element to reduce discontinuous fiber noise caused by X-ray acquisition.

[0071] Define a disk-shaped structure F, whose diameter is 0.35-1.3 mm, which is smaller than the characteristic node size of the fiber woven structure. Dilate the grayscale image G, and the expanded new grayscale image N satisfies the following relationship:

[0072]

[0073] in, It means that the grayscale image G is expanded using a disk-shaped structure element F. (x, y) represents the coordinates of the grayscale image G. The change in the domain coordinates of the disk-shaped structure element F is (i, j). After the operation, a set of new grayscale images N is obtained.

[0074] Step 4, according to the structural design model of the SiC / SiC composite material flanged ribbed structure, the actual size of the ceramic matrix composite material structure corresponding to the characteristic image is obtained; the image size of the corresponding characteristic image at each gray value in the gray value range of 5-30 is calculated to obtain the image size corresponding to each gray value, specifically, the calculation starts from the gray value 5, and then the image size at the gray value 30 is calculated; the image size corresponding to each gray value is compared with the actual size to determine the reference image size closest to the actual size; the gray value corresponding to the reference image size is used as the effective gray value of the corresponding characteristic image; according to the effective gray value, the contour boundary of the ceramic matrix composite material structure in the characteristic image is determined to obtain the contour boundary analysis result, and the gray scale screening of the boundary recognition needs to correspond to the X-ray scanning parameters. For example, if the image size at the gray value of 14 is closest to the actual size, the gray value of 14 is used as the effective gray value, and the contour boundary of the SiC / SiC composite material flanged ribbed structure under the same characteristic image is identified according to the effective gray value. Each characteristic image selects a unified actual size as the gray calibration reference. Specifically, in this embodiment, the corner contour boundary of the SiC / SiC composite material flanged rib structure obtained after CT scanning is as follows: Figure 3 (b) shows that Figure 3 Compared with the X-ray image of the SiC / SiC composite material flanged rib structure shown in (a), the two have a good agreement. By comparing with the corresponding corner contour boundary of the design model, the corner contour of the section is obtained.

[0075] Step 5: Based on the contour boundary analysis results, the cross-sectional area of ​​the SiC / SiC composite material flanged rib structure in the feature image can be determined. Under the same effective grayscale value of the feature image, the pores of the fiber preform can be determined by grayscale recognition. The pore area is as follows: Figure 4 As shown in the white area in Figure 4 The black area in the middle is SiC. By counting the area of ​​the white pores in the cross section, the fiber volume fraction and porosity of the cross section can be determined. And by counting the area of ​​the pores, the pore distribution histogram is obtained, as shown in Figure 5 According to the preset slice distance, multiple slice grayscale images in the preset slice direction are analyzed one by one along the preset slice direction to obtain multiple groups of actual feature parameters, and the multiple groups of actual feature parameters are combined into a section feature data set.

[0076] Step 6, identify the typical structural area (such as rib structure) where the typical structure is located in the feature image, perform grayscale recognition and grayscale distribution analysis on the rib structure, determine the regional width of the local ribbed area (i.e., rib width), and obtain the rib height of the ribbed structure based on the Z-axis slice data set. Perform collaborative analysis on the feature images in each preset slicing direction to obtain multiple typical feature parameters (such as rib thickness, width, fiber arrangement parallelism, etc.), summarize the parameters of the ribbed area, and form a typical structural area feature data set. The validity of the data can be improved by cross-verifying the data of the feature images in each preset slicing direction.

[0077] Step 7. Comparing the data in the section feature data set and the typical structure area feature data set with the design digital model and the weaving design specifications of the design preform, it can be found that the SiC / SiC composite material flanged rib structure obtained after densification, the fiber volume fraction, the reinforcement characteristics, etc. are consistent with the design. The actual SiC / SiC composite material flanged rib structure is consistent with the design requirements, and the non-destructive testing, inspection and evaluation of the SiC / SiC composite material flanged rib structure are achieved.

[0078] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition, characterized in that: The following steps are involved: S1, performing a tomographic scan on the ceramic matrix composite material structure along a preset slicing direction and at a preset slicing distance to obtain a slicing grayscale image of the ceramic matrix composite material structure; S2, using a morphological dilation algorithm to perform denoising on the slice grayscale image to obtain a processed feature image; S3, identifying the characteristic image, determining the contour boundary of the ceramic-based composite material structure in the characteristic image, and obtaining a contour boundary analysis result; S4, obtaining actual characteristic parameters of the ceramic matrix composite material structure according to the contour boundary analysis result, analyzing multiple slice grayscale images in the preset slice direction one by one along the preset slice direction, obtaining multiple groups of actual characteristic parameters, and forming the multiple groups of actual characteristic parameters into a section characteristic data set; S5, identifying a typical structure region where a typical structure in the characteristic image is located, and combining the section feature data set to obtain typical feature parameters of the ceramic matrix composite material structure in the typical structure region to form a typical structure region feature data set; S6. Compare the section feature data set and the typical structural region feature data set with the design feature parameters of the ceramic matrix composite material structure, perform a consistency test on the ceramic matrix composite material structure, and obtain a consistency test result.

2. The nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition according to claim 1, characterized in that: The morphological dilation algorithm specifically performs denoising on the slice grayscale image through the following formula: Among them, N(X,Y) is the set of new grayscale images after denoising. It indicates that the slice grayscale image G is expanded using a disk-shaped structure element F. (x, y) represents the coordinates of the slice grayscale image G. The domain coordinate change of the disk-shaped structure element F is (i, j). The diameter of the disk-shaped structure element F is smaller than the characteristic node size of the fiber woven structure.

3. The nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition according to claim 1, characterized in that: The actual characteristic parameters include contour boundary size, cross-sectional fiber volume fraction, porosity, and pore distribution histogram.

4. The nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition according to claim 1, characterized in that: Step S3 specifically includes the following steps: Acquiring the actual size of the ceramic matrix composite material structure corresponding to the characteristic image; By calculating the image sizes at different gray values ​​one by one within the preset gray value range, an image size set corresponding to the characteristic image within the preset gray value range is obtained; Comparing the image size corresponding to each grayscale value with the actual size, and determining a reference image size closest to the actual size; Taking the grayscale value corresponding to the reference image size as the effective grayscale value of the corresponding feature image; According to the effective grayscale value, the contour boundary of the ceramic matrix composite material structure in the characteristic image is determined to obtain a contour boundary analysis result.

5. The nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition according to claim 4, characterized in that: The preset grayscale value range is 5-30.

6. The nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition according to claim 1, characterized in that: The preset slicing direction includes at least one of an X-axis direction, a Y-axis direction, and a Z-axis direction.

7. The nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition according to claim 1, characterized in that: The preset slicing distance is 0.05mm-0.5mm.

8. The nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition according to claim 1, characterized in that: The typical structure includes a flange structure and a rib structure.

9. The nondestructive testing method for ceramic matrix composite material structure based on grayscale recognition according to claim 1, characterized in that: The design feature parameters are determined according to the design model and weaving design specifications of the ceramic matrix composite material structure.

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