Method, device and equipment for detecting broken filaments on end face of carbon fiber spool

Abstract

The invention relates to the technical field of composite material production and detection, in particular to a broken filament detection method, device and equipment for the end face of a carbon fiber spool, and the method comprises the steps: carrying out the image collection of the end face of the spool, and carrying out the graying processing of the collected image, and obtaining a gray image; carrying out image enhancement on the grayscale image, screening pixel points of the end face of a spool in the enhanced image through a grayscale condition, and obtaining a plurality of region sets by segmenting a connected domain; selecting an area with the largest area in the plurality of area sets, and removing pixel points belonging to the yarn drum to obtain a plurality of sub-areas; and screening the areas of the plurality of sub-regions, and if the area of the sub-region is greater than a set threshold value, judging that broken filaments exist. According to the invention, high-efficiency and accurate detection of broken filaments on the end face of the carbon fiber spool can be realized, and the quality and performance of carbon fibers in the subsequent processing process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of composite material production and detection, and in particular to a method, device and equipment for detecting hairiness on the end face of a carbon fiber yarn bobbin. Background Art

[0002] Carbon fiber has a series of excellent properties such as high specific strength, high specific modulus, fatigue resistance, creep resistance, corrosion resistance and small coefficient of thermal expansion. Therefore, it is widely used as a reinforcing body of carbon fiber reinforced resin matrix composites (CFRP) in national defense cutting-edge technologies such as aerospace and aviation, and is also a new material for the upgrading of civil industries.

[0003] After the carbon fiber is produced, it needs to be wound onto a bobbin. During the winding process, sometimes hairiness will appear on the carbon fiber at the end face of the bobbin. At this time, the hairiness needs to be cleaned. If not cleaned, during subsequent processes such as bobbin transfer and storage, the hairiness will continue to elongate, reducing the local performance of the carbon fiber. Therefore, when winding carbon fiber onto the bobbin, it is necessary to detect the hairiness on the end face of the bobbin in real time.

[0004] The information disclosed in this background art section is only intended to deepen the understanding of the overall background art of the present invention, and should not be regarded as an admission or any form of suggestion that this information constitutes prior art known to those skilled in the art. Summary of the Invention

[0005] The present invention provides a method, device and equipment for detecting hairiness on the end face of a carbon fiber yarn bobbin, thus effectively solving the problems in the background art.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is: a method for detecting hairiness on the end face of a carbon fiber yarn bobbin, comprising the following steps: Collect an image of the end face of the bobbin, and perform grayscale processing on the collected image to obtain a grayscale image; Perform image enhancement on the grayscale image, and screen the pixel points on the end face of the bobbin in the enhanced image through grayscale conditions. By segmenting the connected domains, a number of region sets are obtained; Select the region with the largest area among a number of the region sets, and remove the pixel points belonging to the bobbin therein to obtain a number of sub-regions; Screen the areas of a number of the sub-regions. If there is a sub-region with an area greater than a set threshold, it is determined that there is hairiness.

[0007] Further, performing image enhancement on the grayscale image includes: A(x,y)=round((R(x,y)-mean)*F)+R(x,y); Wherein, A(x, y) represents the gray value of the pixel at the coordinate (x, y) in the enhanced image, round is the round function for rounding, R(x, y) is the gray value of the pixel at the coordinate (x, y) in the image before enhancement, mean represents the average of the gray values of the pixels within the set size range of the pixels centered at the coordinate (x, y) in the image before enhancement, and F represents the contrast factor.

[0008] Further, the screening of the pixels of the end face of the yarn bobbin in the enhanced image by gray conditions includes the following steps: Invert the gray value of each pixel in the enhanced image to obtain an inverted image; Screen the pixels in the inverted image through a gray value threshold range.

[0009] Further, the inversion of the gray value of each pixel in the enhanced image includes: B(x, y) = 255 - A(x, y); Wherein, B(x, y) represents the gray value of the pixel at the coordinate (x, y) in the inverted image; A(x, y) represents the gray value of the pixel at the coordinate (x, y) in the enhanced image.

[0010] Further, the removal of the pixels belonging to the yarn bobbin includes the following steps: Fill the hollow part inside the region with the largest area to obtain a filled region; Find the minimum inscribed circle of the filled region; Perform morphological erosion and dilation operations on the filled region based on the minimum inscribed circle to obtain a circular region; Calculate the complement of the filled region and the circular region.

[0011] Further, the morphological erosion and dilation operations on the filled region based on the minimum inscribed circle include: Find the radius R of the minimum inscribed circle; First, erode the filled region with a circular structuring element of size R / 2; Then, dilate the eroded region with a circular structuring element of size R / 2.

[0012] The present invention further includes a hairiness detection device for the end face of a carbon fiber yarn bobbin, using the method as described above. The device includes: An acquisition unit for collecting an image of the end face of the yarn bobbin and performing gray-scale processing on the collected image to obtain a gray-scale image; A screening unit for enhancing the grayscale image and screening the pixel points of the end face of the yarn bobbin in the enhanced image through grayscale conditions, and obtaining a number of region sets by segmenting the connected domains; A processing unit for selecting the region with the largest area from a number of the region sets and removing the pixel points belonging to the yarn bobbin therein to obtain a number of sub-regions; A detection unit for screening the areas of a number of the sub-regions, and if there is a sub-region with an area greater than a set threshold, it is determined that there are hairinesses.

[0013] The present invention further includes a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method as described above is implemented.

[0014] The present invention further includes a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method as described above is implemented.

[0015] The beneficial effects of the present invention are as follows: converting the collected color image into a grayscale image, reducing the computational complexity and highlighting the contrast between the hairiness and the background, improving the image contrast and clarity through image enhancement technology, and then performing further analysis. By selecting the region with the largest area to remove the background region and removing the yarn bobbin region, the carbon fiber region wound on the yarn bobbin is retained to avoid misidentification. Finally, sub-regions are screened by setting a threshold to determine whether there are hairinesses. Through the above steps and optimization strategies, efficient and accurate detection of hairiness on the end face of the carbon fiber yarn bobbin can be achieved, ensuring the quality and performance of the carbon fiber in the subsequent processing process. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a flowchart of the method of the present invention; Figure 2 It is a grayscale image obtained by grayscale processing; Figure 3 It is the enhanced image; Figure 4 It is an image of the region set after screening the pixel points in the inverse-selected image through the grayscale value threshold range; Figure 5 It is an image of the region with the largest area in the region set; Figure 6 An image of the filled area; Figure 7 An image of the complement set; Figure 8 A schematic structural diagram of the device of the present invention; Figure 9 A schematic structural diagram of the computer device of the present invention. Specific embodiments

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0019] As Figure 1 shown: A method for detecting hairiness on the end face of a carbon fiber yarn bobbin includes the following steps: Collect an image of the end face of the bobbin, and perform grayscale processing on the collected image to obtain a grayscale image. Please refer to Figure 2 ; Perform image enhancement on the grayscale image, and screen the pixel points on the end face of the bobbin in the enhanced image through grayscale conditions. By segmenting the connected regions, several region sets are obtained; Select the region with the largest area in several region sets, and remove the pixel points belonging to the bobbin therein to obtain several sub-regions; Screen the areas of several sub-regions. If there is a sub-region with an area greater than the set threshold, it is determined that there is hairiness.

[0020] Convert the collected color image into a grayscale image to reduce the computational complexity and highlight the contrast between the hairiness and the background. Improve the image contrast and clarity through image enhancement technology, and then perform further analysis. Remove the background region by selecting the region with the largest area, and remove the bobbin region to retain the carbon fiber region wound on the bobbin to avoid misidentification. Finally, screen the sub-regions through the set threshold to determine whether there is hairiness. Through the above steps and optimization strategies, efficient and accurate detection of hairiness on the end face of the carbon fiber yarn bobbin can be achieved, ensuring the quality and performance of the carbon fiber during subsequent processing.

[0021] In this embodiment, performing image enhancement on the grayscale image includes: A(x,y)=round((R(x,y)-mean)*F)+R(x,y); Wherein, A(x, y) represents the gray value of the pixel at the coordinate (x, y) in the enhanced image, round is the round function for rounding, R(x, y) is the gray value of the pixel at the coordinate (x, y) in the image before enhancement, mean represents the average gray value of the pixels within the set size range of the pixels centered on the coordinate (x, y) in the image before enhancement, and F represents the contrast factor.

[0022] The enhanced image is as Figure 3 shown. The image enhancement technology based on local mean and contrast factor aims to enhance the image contrast through local gray information, thereby enhancing the recognizability of the hairiness in the image of the end face of the yarn bobbin. The local mean of the image is calculated, that is, a window is set around each pixel, and the average gray value mean of the pixels within the window is calculated. For each pixel, the difference between it and the local average value is calculated, and then multiplied by the contrast factor F to amplify this difference, thereby enhancing the local contrast of the image. Finally, the enhanced gray value is added to the gray value of the original image, so as to retain the details of the original image while enhancing the local contrast, and rounding is used to ensure that the pixel value is an integer.

[0023] The image enhanced by this method can more prominently show the contour of the hairiness and improve the accuracy of subsequent detection in image processing. With the optimization of parameters such as the contrast factor and the local window size, this method can be applied to complex industrial production environments to achieve real-time detection and cleaning of the hairiness on the end face of the carbon fiber yarn bobbin.

[0024] Among them, screening the pixels on the end face of the yarn bobbin in the enhanced image through gray conditions includes the following steps: Inverting the gray value of each pixel in the enhanced image to obtain an inverted image; Screening the pixels in the inverted image through the gray value threshold range, and the screened image is as Figure 4 shown.

[0025] Inverting the gray value of each pixel in the enhanced image includes: B(x, y) = 255 - A(x, y); Wherein, B(x, y) represents the gray value of the pixel at the coordinate (x, y) in the inverted image; A(x, y) represents the gray value of the pixel at the coordinate (x, y) in the enhanced image.

[0026] Process the enhanced image by inverting the grayscale value of each pixel. The grayscale value inversion is to highlight the pixels of the end face of the yarn bobbin, making it easier for subsequent threshold screening. For the inverted image, pixel screening is performed according to the set grayscale value range. In this embodiment, the grayscale value threshold range is set to [0, 100]. In the enhanced image, the end face of the yarn bobbin may have a lower grayscale value, while the background or other interference parts have a higher grayscale value. Through the inversion operation, the grayscale value of the pixels on the end face of the yarn bobbin can be increased in the new image, thus facilitating accurate segmentation using the threshold screening method. By setting a reasonable grayscale threshold range, the background or noise points can be further excluded, and only the effective pixels of the end face of the yarn bobbin are retained, thereby providing higher-quality input for subsequent connected component segmentation and region screening.

[0027] In this embodiment, removing the pixel points belonging to the yarn bobbin includes the following steps: Fill the hollow part inside the area with the largest area as shown in Figure 5 to obtain a filled area. The image after filling the area is as shown in Figure 6 ; Find the minimum inscribed circle of the filled area; Perform morphological erosion and dilation operations on the filled area based on the minimum inscribed circle to obtain a circular area; Calculate the complement of the filled area and the circular area. The resulting complement image is as shown in Figure 7 ;

[0028] Use a region filling algorithm (such as the seed filling method or the closed region filling method) to fill all the hollow parts inside the area with the largest area to form a complete filled area. The filled area can exclude the hole features on the yarn bobbin and create conditions for subsequent shape analysis. Use geometric algorithms (such as convex hull or least squares fitting) to find the largest inscribed circle tangent to all boundary points. Erode the filled area to make its boundary shrink inward, reducing the edge error of the yarn bobbin. Dilate the eroded area to restore the boundary while ensuring that the yarn bobbin area remains circular. After erosion and dilation, a standardized circular area is formed. Through erosion and dilation, noise interference can be effectively reduced while retaining the shape features of the yarn bobbin. Calculate the complement of the filled area and the circular area. This complement area contains possible hairiness features and removes the pixel points belonging to the yarn bobbin body.

[0029] As a preference of the above embodiment, performing morphological erosion and dilation operations on the filled area based on the minimum inscribed circle includes: Find the radius R of the minimum inscribed circle; First, erode the filled area with a circular structuring element of size R / 2; Then, dilate the eroded area with a circular structuring element of size R / 2.

[0030] The filled area is first eroded with a circular structuring element of size R / 2. This operation shrinks the boundary of the yarn bobbin area inward by a range of R / 2, removing noise and edge burrs and retaining the main structure of the yarn bobbin.

[0031] Then, the eroded area is dilated with a circular structuring element of size R / 2. This operation expands the boundary of the shrunk yarn bobbin area outward by R / 2, restoring its nearly circular structure and enhancing the connectivity of the yarn bobbin area. After the above erosion and dilation treatments, a standardized circular area is finally obtained, with a smoother boundary and excluding voids or edge noise inside the yarn bobbin. Erosion is used to remove burrs and noise points on the area boundary, while dilation is used to restore the overall coherence of the area. The combination of the two can maintain the overall shape of the yarn bobbin area while reducing misjudgment. According to the radius R of the minimum inscribed circle, the range of morphological operations is dynamically adjusted to make this method adaptable to yarn bobbins of different sizes, with good adaptability.

[0032] As Figure 8 shown, this embodiment also includes a device for detecting hairiness on the end face of a carbon fiber yarn bobbin. Using the method as described above, the device includes: An acquisition unit for acquiring an image of the end face of the yarn bobbin and performing grayscale processing on the acquired image to obtain a grayscale image; A screening unit for enhancing the grayscale image and screening the pixel points of the end face of the yarn bobbin in the enhanced image through grayscale conditions, and obtaining several region sets by segmenting connected domains; A processing unit for selecting the region with the largest area among several region sets and removing the pixel points belonging to the yarn bobbin therein to obtain several sub-regions; A detection unit for screening the areas of several sub-regions. If there is a sub-region with an area greater than a set threshold, it is determined that there is hairiness.

[0033] Please refer to Figure 9 the structural schematic diagram of the computer device provided by the embodiment of the present application shown. A computer device 400 provided by an embodiment of the present application includes: a processor 410 and a memory 420. The memory 420 stores a computer program executable by the processor 410. When the computer program is executed by the processor 410, the method as described above is executed.

[0034] An embodiment of the present application also provides a storage medium 430. A computer program is stored on the storage medium 430. When the computer program is run by the processor 410, the method as described above is executed.

[0035] Among them, the storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disc.

[0036] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The meaning of "a plurality" is two or more, unless otherwise specifically defined.

[0037] In the present invention, unless otherwise clearly specified and defined, terms such as "installed", "connected", "connected to", "fixed" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0038] In the description of this specification, the descriptions with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0039] Any process or method description represented in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations, where functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0040] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered a sequenced list of executable instructions for implementing a logical function, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of the computer-readable medium include the following: an electrical connection having one or more wires (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable medium on which the program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0041] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0042] Those of ordinary skill in the art can understand that all or part of the steps carried out in the methods of the above embodiments can be completed by instructing relevant hardware through a program, and the said program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0043] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disc, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for detecting hair on the end surface of a carbon fiber yarn tube, characterized in that: The steps include: Capturing an image of the end face of the yarn tube, and graying the captured image to obtain a grayscale image; Performing image enhancement on the grayscale image, and screening the pixel points of the yarn tube end surface in the enhanced image by grayscale conditions, and obtaining a plurality of region sets by segmenting the connected domains; Selecting the largest region from the plurality of region sets, and removing the pixels belonging to the yarn tube therein, to obtain a plurality of sub-regions; The areas of several sub-regions are screened, and if there is a sub-region whose area is greater than a set threshold, it is determined that hair exists.

2. The method for detecting hairy fibers at the end surface of a carbon fiber yarn tube according to claim 1, characterized in that: Performing image enhancement on the grayscale image includes: A(x,y)=round((R(x,y)-mean)*F)+R(x,y); Where A(x,y) represents the grayscale value of the pixel at coordinate (x,y) in the enhanced image, round represents the round function, R(x,y) represents the grayscale value of the pixel at coordinate (x,y) in the image before enhancement, mean represents the average grayscale value of the pixel within the set size range centered on the coordinate (x,y) in the image before enhancement, and F represents the contrast factor.

3. The method for detecting hairy fibers at the end surface of a carbon fiber yarn tube according to claim 1, characterized in that: The step of screening the pixel points of the yarn tube end surface in the enhanced image by grayscale conditions comprises the following steps: Inversely select the gray value of each pixel in the enhanced image to obtain an inversely selected image; The pixels in the inverse-selected image are screened by using a gray value threshold range.

4. The method for detecting hairy fibers at the end surface of a carbon fiber yarn tube according to claim 3, characterized in that: The gray value of each pixel in the enhanced image is reversed, including: B(x,y) = 255-A(x,y); Where B(x,y) represents the gray value of the pixel at coordinate (x,y) in the inverse image; A(x,y) represents the gray value of the pixel at coordinate (x,y) in the enhanced image.

5. The method for detecting hairy fibers at the end surface of a carbon fiber yarn tube according to claim 1, characterized in that: The step of removing the pixel points belonging to the yarn tube comprises the following steps: Filling the hollow portion inside the region with the largest area to obtain a filled region; Finding the minimum inscribed circle for the filling area; Performing morphological erosion and expansion operations on the filling area based on the minimum inscribed circle to obtain a circular area; The complement of the filled area and the circular area is calculated.

6. The method for detecting hairy fibers at the end surface of a carbon fiber yarn tube according to claim 5, characterized in that: The performing morphological erosion and expansion operations on the filling area based on the minimum inscribed circle includes: Calculate the radius R of the minimum inscribed circle; The filling area is firstly eroded using a circular structure element with a size of R / 2; Then, the eroded area is expanded using a circular structure element with a size of R / 2.

7. A device for detecting hair on the end surface of a carbon fiber yarn tube, characterized in that: Using the method according to any one of claims 1 to 6, the device comprises: The acquisition unit is used to acquire an image of the end face of the yarn tube and grayscale the acquired image to obtain a grayscale image; A screening unit, used to perform image enhancement on the grayscale image, and screen the pixel points of the yarn tube end surface in the enhanced image according to the grayscale condition, and obtain a plurality of region sets by segmenting the connected domain; A processing unit, used for selecting the largest area among the plurality of area sets, and removing the pixels belonging to the yarn tube therein, to obtain a plurality of sub-areas; The detection unit is used to screen the areas of the plurality of sub-regions, and if there is a sub-region whose area is greater than a set threshold, it is determined that hair exists.

8. 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, the method according to any one of claims 1 to 6 is implemented.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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