Method and system for identifying interface crack of epoxy resin adhesive based on image processing and application of method and system

Abstract

The invention discloses a method and a system for identifying an epoxy resin adhesive interface crack based on image processing and application thereof. The method comprises the following steps: S1, acquiring an original image P0 of a structure sample bonded by an epoxy resin adhesive; s2, converting the image into a single-channel grayscale image P1; s3, performing noise reduction processing to obtain P2; s4, carrying out histogram equalization processing to obtain a contrast-enhanced image P3; s5, performing bilateral filtering processing to obtain a preprocessed image; s6, carrying out edge detection and recognition on the preprocessed image to obtain a binarized crack contour mask; and S7, extracting crack characteristic parameters based on the crack contour mask, and completing the interface crack detection of the epoxy resin adhesive. According to the method, the epoxy resin adhesive interface crack can be automatically identified, and compared with a manual identification mode, the method has the advantages of being more accurate, objective and efficient, and can be well applied to analysis and evaluation of whether newly developed adhesives meet design requirements or not.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method, system, and application for identifying interface cracks in epoxy resin adhesives based on image processing. Background Technology

[0002] Epoxy resin adhesives are advanced materials based on epoxy resin, achieving stable bonding performance at high temperatures through molecular design and modification techniques. Due to their excellent bonding properties, good functionality, relatively low price, and simple bonding process, they have been widely used in the home appliance, automotive, water conservancy and transportation, electronics, and aerospace industries in recent decades.

[0003] To improve product performance, researchers are continuously developing new epoxy resin adhesives. Crack resistance is one of the important indicators for evaluating and analyzing the performance of epoxy resins. A common method involves subjecting epoxy resin-bonded workpieces to thermal cycling treatment, followed by inspection for cracks at the bonding interface. However, this inspection method is generally based on manual observation, which suffers from drawbacks such as large errors, strong subjectivity, and low efficiency.

[0004] Therefore, it is necessary to improve existing technologies to provide more reliable solutions. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method, system and application of image processing for identifying interface cracks in epoxy resin adhesives, which addresses the shortcomings of the prior art.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: In its first aspect, the present invention provides a method for identifying interface cracks in epoxy resin adhesives based on image processing, comprising the following steps: S1. Obtain the original image P0 of the structural sample after it has been bonded with epoxy resin adhesive; S2. Convert the original image into a single-channel grayscale image P1; S3. Denoise the single-channel grayscale image P1 to obtain the denoised image P2. S4. Perform histogram equalization on the denoised image P2 to enhance contrast, resulting in contrast-enhanced image P3. S5. Perform bilateral filtering on the contrast-enhanced image P3 to obtain the preprocessed image; S6. Perform edge detection and recognition on the preprocessed image to obtain a binarized crack contour mask; S7. Extract crack feature parameters based on the crack contour mask to complete the detection of cracks at the epoxy resin adhesive interface.

[0007] Preferably, the structural sample is a structure formed by bonding two workpieces together with epoxy resin adhesive and then curing it.

[0008] Preferably, the original image P0 is an RGB three-channel color image containing the bonding interface region of the structural sample.

[0009] Preferably, in step S3, a Gaussian blur denoising algorithm is used to denoise the grayscale image P1.

[0010] Preferably, in step S6, the Canny edge detection algorithm performs edge detection and recognition on the preprocessed image to obtain a binarized crack contour mask.

[0011] Preferably, the crack characteristic parameters in step S7 include the number of cracks and the total crack length.

[0012] In a second aspect, the present invention provides an application of the method described above in analyzing the bonding performance of epoxy resin adhesives. The application method is as follows: two metal workpieces are bonded together and cured using the epoxy resin adhesive to be analyzed to obtain a structural sample. The structural sample is subjected to a hot and cold cycle treatment. During the treatment, the method described in any one of claims 1-6 is used to identify cracks at the epoxy resin adhesive interface of the structural sample.

[0013] A third aspect of the present invention provides a system for identifying interface cracks in epoxy resin adhesives based on image processing, characterized in that it uses the method described above to identify interface cracks in epoxy resin adhesives.

[0014] A fourth aspect of the present invention provides a storage medium having a computer program stored thereon, characterized in that the program, when executed, is used to implement the method described above.

[0015] A fifth aspect of the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method described above.

[0016] The beneficial effects of this invention are: This invention provides a method, system, and application for identifying interface cracks in epoxy resin adhesives based on image processing. The method mainly includes the following steps: S1, acquiring the original image P0 of a structural sample bonded with epoxy resin adhesive; S2, converting the original image into a single-channel grayscale image P1; S3, performing noise reduction processing on P1 to obtain a noise-reduced image P2; S4, performing histogram equalization processing on P2 to enhance contrast, obtaining a contrast-enhanced image P3; S5, performing bilateral filtering processing on P3 to obtain a preprocessed image; S6, performing edge detection and recognition on the preprocessed image to obtain a binarized crack contour mask; S7, extracting crack feature parameters based on the crack contour mask to complete the detection of interface cracks in epoxy resin adhesives.

[0017] This invention employs image processing technology to automatically identify interface cracks in epoxy resin adhesives. Compared to manual identification, this invention is more accurate, objective, and efficient, and can be well applied to the analysis and evaluation of whether newly developed adhesives meet design requirements. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method for identifying interface cracks in epoxy resin adhesives based on image processing according to the present invention. Detailed Implementation

[0019] The present invention will be further described in detail below with reference to embodiments, so that those skilled in the art can implement it based on the description.

[0020] It should be understood that terms such as “having,” “comprising,” and “including” as used herein do not exclude the presence or addition of one or more other elements or combinations thereof.

[0021] Unless otherwise specified, the experimental methods used in the following examples are conventional methods. Unless otherwise specified, the materials and reagents used in the following examples are commercially available. For examples where specific conditions are not specified, conventional conditions or conditions recommended by the manufacturer are followed. For reagents or instruments whose manufacturers are not specified, they are all commercially available products.

[0022] Example 1 This invention provides a method for identifying interface cracks in epoxy resin adhesives based on image processing, comprising the following steps: S1. Obtain the original image P0 of the structural sample after it has been bonded with epoxy resin adhesive. The original image is an RGB three-channel color image and includes the bonding interface area of ​​the structural sample. The structural sample is a structure formed by bonding two workpieces together with epoxy resin adhesive and then curing it.

[0023] S2. Convert the original image into a single-channel grayscale image P1 to reduce computational complexity while highlighting the brightness differences of the cracks; S3. The single-channel grayscale image P1 is denoised based on the Gaussian blur denoising algorithm to obtain the denoised image P2; isotropic smooth denoising is achieved by convolving the image with a Gaussian kernel to suppress high-frequency noise in the image and avoid noise being misjudged as cracks; in this embodiment, a 3×3 two-dimensional Gaussian kernel is used. S4. Perform histogram equalization on the denoised image P2 to expand the dynamic range of image grayscale, solve the problem of uneven illumination, and significantly improve the contrast between the crack (low grayscale area) and the background (high grayscale area) to obtain the contrast-enhanced image P3. S5. Perform bilateral filtering on the contrast-enhanced image P3 to preserve edge details and avoid edge blurring caused by Gaussian blur (crack edges are key detection features), and obtain the preprocessed image. S6. The Canny edge detection algorithm is used to perform edge detection and recognition on the preprocessed image to obtain a binarized crack contour mask. S7. Extract crack feature parameters based on the crack contour mask, including the number of cracks and the total length, to complete the detection of cracks at the epoxy resin adhesive interface.

[0024] This method can accurately detect interfacial cracks in epoxy resin adhesives, thereby objectively evaluating the crack resistance of epoxy resin adhesives.

[0025] Example 2 This embodiment provides the application of the method of Example 1 in analyzing the bonding performance of epoxy resin adhesives. The application method is as follows: two metal workpieces are bonded together and cured using the epoxy resin adhesive to be analyzed to obtain a structural sample. The structural sample is then subjected to a cold and hot cycling treatment (for example, in one embodiment, the cold and hot cycling treatment procedure is: -50℃ to 150℃, cycle period of 1 hour, and total number of cycles of 1000). During the treatment, the method of Example 1 is used to identify cracks at the epoxy resin adhesive interface of the structural sample in order to analyze whether the developed adhesive meets the design requirements.

[0026] Example 3 A system for identifying interface cracks in epoxy resin adhesives based on image processing, which uses the method of Example 1 to identify interface cracks in epoxy resin adhesives.

[0027] Example 4 A storage medium having a computer program stored thereon, which, when executed, is used to implement the method of Embodiment 1.

[0028] Example 5 A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method of embodiment 1.

[0029] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details.

Claims

1. A method for identifying interface cracks in epoxy resin adhesives based on image processing, characterized in that, Includes the following steps: S1. Obtain the original image P0 of the structural sample after it has been bonded with epoxy resin adhesive; S2. Convert the original image into a single-channel grayscale image P1; S3. Denoise the single-channel grayscale image P1 to obtain the denoised image P2. S4. Perform histogram equalization on the denoised image P2 to enhance contrast, resulting in contrast-enhanced image P3. S5. Perform bilateral filtering on the contrast-enhanced image P3 to obtain the preprocessed image; S6. Perform edge detection and recognition on the preprocessed image to obtain a binarized crack contour mask; S7. Extract crack feature parameters based on the crack contour mask to complete the detection of cracks at the epoxy resin adhesive interface.

2. The method for identifying epoxy resin adhesive interface cracks based on image processing according to claim 1, characterized in that, The structural sample is a structure formed by bonding two workpieces together with epoxy resin adhesive and then curing it.

3. The method for identifying epoxy resin adhesive interface cracks based on image processing according to claim 1, characterized in that, The original image P0 is an RGB three-channel color image containing the bonding interface region of the structural sample.

4. The method for identifying epoxy resin adhesive interface cracks based on image processing according to claim 1, characterized in that, In step S3, the Gaussian blur denoising algorithm is used to denoise the grayscale image P1.

5. The method for identifying epoxy resin adhesive interface cracks based on image processing according to claim 1, characterized in that, In step S6, the Canny edge detection algorithm performs edge detection and recognition on the preprocessed image to obtain a binarized crack contour mask.

6. The method for identifying epoxy resin adhesive interface cracks based on image processing according to claim 1, characterized in that, The crack characteristic parameters in step S7 include the number of cracks and the total crack length.

7. An application of the method as described in any one of claims 1-6 in analyzing the bonding performance of epoxy resin adhesives, wherein the application method is as follows: two metal workpieces are bonded together and cured using the epoxy resin adhesive to be analyzed to obtain a structural sample; the structural sample is subjected to a hot and cold cycle treatment; during the treatment, the method as described in any one of claims 1-6 is used to identify cracks at the epoxy resin adhesive interface of the structural sample.

8. A system for identifying interface cracks in epoxy resin adhesives based on image processing, characterized in that, It uses the method described in any one of claims 1-6 to identify interface cracks in epoxy resin adhesives.

9. A storage medium having a computer program stored thereon, characterized in that, When executed, this program is used to implement the method as described in any one of claims 1-6.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1-6.

Images