CN-121978150-A - Analysis method for adhesive fibrosis degree

CN121978150ACN 121978150 ACN121978150 ACN 121978150ACN-121978150-A

Abstract

The embodiment of the application provides an analysis method of the fibrosis degree of an adhesive, which comprises the steps of S1, S2, using target equipment to scan the surface of a sample to characterize the surface of the sample to obtain a microscopic morphology graph of the sample, S3, carrying out image processing on the microscopic morphology graph to enhance the fiber image characteristics in the microscopic morphology graph, and S4, carrying out analysis based on the microscopic morphology graph after the image processing to obtain an analysis result, wherein the analysis result is used for judging the fibrosis degree of the adhesive of the material to be analyzed. The method for analyzing the fibrosis degree of the adhesive solves the technical problems of large measurement deviation and large fluctuation of a test result in the prior art.

Inventors

WEN PENGCHAO
XIE CHENLIN
KONG SHAOFENG

Assignees

奇瑞汽车股份有限公司

Dates

Publication Date: 20260505
Application Date: 20260203

Claims (10)

1. A method for analyzing the degree of fibrosis of an adhesive, comprising: s1, preparing a material to be analyzed into a sample; s2, using scanning imaging equipment to characterize the surface of the sample, and obtaining a microscopic topography of the sample; S3, performing image processing on the micro-topography map to enhance the fiber image characteristics in the micro-topography map; And S4, analyzing based on the micro-morphology graph after image processing to obtain an analysis result, wherein the analysis result is used for judging the degree of fibrosis of the material binder to be analyzed.
2. The method according to claim 1, wherein in step S4, analysis is performed based on the image-processed microscopic topography map to obtain an analysis result, comprising the steps of: step S41, determining fiber size parameters of a plurality of fiber areas based on the micro-topography map after image processing, wherein the fiber size parameters comprise a long axis length and a short axis length; step S42 of determining aspect ratios of a plurality of the fiber regions based on the fiber size parameters of the plurality of the fiber regions; step S43, determining an average length-diameter ratio based on the length-diameter ratios of a plurality of the fiber regions; And step S44, analyzing based on the average length-diameter ratio to obtain the analysis result.
3. The method according to claim 2, wherein in step S4, analysis is performed based on the image-processed microscopic topography map to obtain an analysis result, comprising the steps of: step S45, determining coverage rate based on the micro-morphology graph after image processing, wherein the coverage rate is used for representing the ratio of the area of a fiber area in a selected analysis area to the area of the selected analysis area; And step S46, analyzing based on the coverage rate to obtain the analysis result.
4. A method of analyzing the degree of fibrosis of an adhesive according to any one of claims 1-3 wherein in step S3 the microscopic topography is image processed comprising the steps of: step S31, converting the micro topography map into a target gray scale map; step S32, filtering the target gray scale image; And step S33, performing threshold segmentation on the target gray level image after the filtering processing to obtain a target binary image, wherein a white image of the target binary image represents fibers, and a black image of the target binary image represents a background.
5. The method according to claim 4, wherein in step S3, the image processing is performed on the micro topography map, further comprising the steps of: And step S34, performing fiber segmentation processing on the target binary image so as to separate adhered fibers.
6. The method according to claim 4, wherein before the target gray scale is subjected to the filtering process in step S3, the method further comprises the steps of: performing contrast adjustment on the target gray scale image to enhance the contrast of the target gray scale image, and/or, And carrying out noise reduction processing on the target gray level image.
7. The method according to claim 4, wherein in step S3, the image processing is performed on the micro topography map, further comprising the steps of: And step S35, processing the target binary image by adopting morphological operation to remove non-fiber objects in the target binary image.
8. The method according to claim 4, wherein in step S31, the target gray scale image is a floating point type 8-bit gray scale image.
9. The method for analyzing the degree of fiberization of an adhesive according to claim 1, wherein said material to be analyzed comprises a powder after dry mixing and fiberization, and wherein in step S1, the material to be analyzed is prepared into a sample, comprising the steps of: Step S11, placing the powder subjected to dry mixing and fiberization into a silica gel mold, and injecting epoxy resin to obtain an initial sample; Step S12, the initial sample is subjected to vacuum degassing and solidification; step S13, polishing the initial sample after vacuum degassing and curing by using sand paper; Step S14, polishing the initial sample polished by the sand paper by using a diamond suspension; And S15, performing spraying treatment on the initial sample after the polishing treatment so that the outer peripheral surface of the initial sample is covered with a metal film, and obtaining the sample.
10. The method for analyzing the degree of fiberization of an adhesive according to claim 1, wherein said material to be analyzed comprises a dry pole piece, and in step S1, the material to be analyzed is prepared into a sample, comprising the steps of: s16, cutting the dry pole piece to obtain a sample; And step S17, grinding the sample by using an ion beam grinding instrument until the sample has a flat surface, so as to obtain the sample, wherein the roughness of the flat surface is less than 0.1 mu m.

Description

Analysis method for adhesive fibrosis degree Technical Field The embodiment of the application relates to the technical field of adhesive fibrosis degree, in particular to an analysis method of adhesive fibrosis degree. Background In the prior art, a specific surface area change method is commonly used for indirectly evaluating the degree of fibrosis, the method cannot analyze the details of fiber morphology, such as fracture, agglomeration and the like, and the method is remarkably interfered by the specific surface area of a conductive agent (such as the specific surface area of carbon black of 60-1200m 2/g), so that measurement deviation is caused. In addition, a secondary image color difference proportion method is also commonly used, and the method and the means based on the surface optical color/gray scale difference are easy to be interfered by the problems of the color and the reflecting effect of other materials (such as active materials and conductive carbon), the bright and dark areas of the secondary image, the agglomeration condition of powder and the like, and the test false signal is very high, so that the fluctuation of the result is huge. There is currently no good solution to the above problems. Disclosure of Invention The embodiment of the application provides an analysis method for the fibrosis degree of an adhesive, which is used for at least solving the technical problems of large measurement deviation and large fluctuation of a test result. According to one aspect of the embodiment of the application, an analysis method of the fibrosis degree of the adhesive is provided, which comprises the steps of S1, preparing a sample from a material to be analyzed, S2, using a target device to scan an imaging device to characterize the surface of the sample to obtain a microscopic morphology image of the sample, S3, performing image processing on the microscopic morphology image to enhance the fiber image characteristics in the microscopic morphology image, and S4, analyzing based on the microscopic morphology image after image processing to obtain an analysis result, wherein the analysis result is used for judging the fibrosis degree of the adhesive of the material to be analyzed. Further, in the step S4, analysis is performed based on the image-processed micro-topography map to obtain an analysis result, and the method comprises the steps of determining fiber size parameters of a plurality of fiber regions based on the image-processed micro-topography map, wherein the fiber size parameters comprise long axis lengths and short axis lengths, determining the length-diameter ratio of the plurality of fiber regions based on the fiber size parameters of the plurality of fiber regions, determining the average length-diameter ratio based on the length-diameter ratio of the plurality of fiber regions, determining the average length-diameter ratio, and analyzing based on the average length-diameter ratio to obtain the analysis result, wherein the step S41 is used for determining the fiber size parameters of the plurality of fiber regions based on the image-processed micro-topography map. Further, in the step S4, analysis is performed based on the image-processed micro-topography map to obtain an analysis result, and the method comprises the steps of determining coverage rate based on the image-processed micro-topography map, wherein the coverage rate is used for representing the ratio of the area of the fiber region in the selected analysis region to the area of the selected analysis region, and analyzing based on the coverage rate to obtain the analysis result in the step S46. Further, in the step S3, image processing is performed on the micro-topography map, and the method comprises the steps of S31, S32, and S33, respectively, performing filtering processing on the target gray map, wherein the step S31 is used for converting the micro-topography map into the target gray map, the step S33 is used for performing threshold segmentation on the filtered target gray map to obtain a target binary map, white images of the target binary map represent fibers, and black images of the target binary map represent background. Further, in step S3, the image processing is performed on the micro topography map, and further, the method further comprises the step of performing a fiber segmentation process on the target binary map to separate the adhered fibers in step S34. Further, before the filtering process is performed on the target gray scale image in step S3, the method further includes the steps of performing contrast adjustment on the target gray scale image to enhance the contrast of the target gray scale image, and/or performing noise reduction process on the target gray scale image. Further, in step S3, the image processing is performed on the micro-topography map, and further comprises the step of S35, processing the target binary map by adopting morphological operation to remove non-fibrous objects in the t