Demolding cloth cover line accumulation detection method, device and equipment and medium

Abstract

The invention relates to the technical field of composite material production, in particular to a demolding cloth cover line accumulation detection method, device and equipment and a medium, and the method comprises the steps: obtaining a demolding cloth cover image, and converting the demolding cloth cover image into a grayscale image; enhancing the low-frequency part of the grayscale image by using the filtering vector to obtain an enhanced image; performing dynamic threshold segmentation on the enhanced image, and segmenting an area of which the gray value accords with a set threshold; performing morphological processing on the region, and segmenting a connected domain to obtain a region set; and judging whether a region of which the area size accords with an area threshold value exists in the region set, and if so, judging that a line accumulation region exists. According to the method, surface flaws caused by the defects in carbon plate production can be effectively avoided, the scheme can adapt to demolding cloth of different types and thicknesses through the dynamic threshold segmentation and morphological processing method, the applicability of the scheme is improved, online detection is achieved, and problems in the production process can be rapidly found and processed.

Description

Technical Field

[0001] The present invention relates to the technical field of composite material production, and in particular to a method, device, equipment and medium for detecting surface line accumulation of a demoulding cloth. Background Art

[0002] In the production process of carbon fiber, the release cloth is used as a process auxiliary material attached to the surface of the carbon plate in the pultrusion production line. The release cloth enters the pultrusion plate mold together with the prepreg, and enters the curing oven after preforming.

[0003] Sometimes there will be defects such as line accumulation on the release cloth. Since the release cloth is attached to the surface of the carbon plate, there will be defects on the surface of the carbon plate produced at the line accumulation. Therefore, it is necessary to detect the line accumulation defects on the surface of the release cloth.

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

[0005] The present invention provides a method, device, equipment and medium for detecting surface line accumulation of a demoulding cloth, thereby effectively solving the problems in the background technology.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is: a method for detecting surface line accumulation of a release cloth, comprising the following steps:

[0007] Obtain the surface image of the release cloth and convert it into a grayscale image;

[0008] Using a filter vector to enhance a low-frequency portion of the grayscale image to obtain an enhanced image;

[0009] Performing dynamic threshold segmentation on the enhanced image to segment out areas where the grayscale value meets the set threshold;

[0010] Performing morphological processing on the region and segmenting the connected domain to obtain a region set;

[0011] It is determined whether there is an area in the area set whose area size meets the area threshold. If so, it is determined that there is a line accumulation area.

[0012] Furthermore, the step of enhancing the low-frequency portion of the grayscale image using a filter vector includes:

[0013] The grayscale image is convolved using two basic filter vectors to obtain the enhanced image.

[0014] Furthermore, the two basic filter vectors are respectively:

[0015] l =

[121] ;

[0016] The convolution kernel el composed of the two basic filter vectors is:

[0017]

[0018] Furthermore, the performing dynamic threshold segmentation on the enhanced image includes:

[0019] Performing mean filtering on the enhanced image to obtain a filtered image;

[0020] Comparing the difference in grayscale value of each corresponding pixel in the enhanced image and the filtered image;

[0021] When the gray value difference is greater than the set threshold G, the pixel point is extracted from the enhanced image.

[0022] Furthermore, when the enhanced image is subjected to mean filtering, the size of the synovial membrane of the mean filtering is calculated by using the area threshold.

[0023] Furthermore, the morphological processing of the region includes: first performing a dilation operation and then performing an erosion operation on the region extracted from the enhanced image, and the size of the dilation operation is 5.

[0024] The present invention also includes a device for detecting surface line accumulation of a demoulding cloth, using the above method, the detection device includes:

[0025] An acquisition unit, used for acquiring an image of a surface of the demoulding cloth and converting it into a grayscale image;

[0026] an enhancement unit, configured to enhance the low-frequency portion of the grayscale image using a filter vector to obtain an enhanced image;

[0027] A region segmentation unit, used to perform dynamic threshold segmentation on the enhanced image to segment out regions where the grayscale value meets a set threshold;

[0028] A morphological unit, used for performing morphological processing on the region and segmenting the connected domain to obtain a region set;

[0029] The judging unit is used to judge whether there is an area in the area set whose area size meets the area threshold, and if so, judge that there is a line accumulation area.

[0030] The present invention also includes a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described above is implemented.

[0031] The present invention also includes a storage medium on which a computer program is stored. When the computer program is executed by a processor, the method described above is implemented.

[0032] The beneficial effects of the present invention are as follows: the present invention can effectively avoid surface defects caused by line accumulation defects on the release cloth in time, thereby improving the quality of the final product. The dynamic threshold segmentation and morphological processing methods enable the scheme to adapt to release cloths of different types and thicknesses, thereby improving the applicability of the scheme to achieve online detection, so that problems in the production process can be quickly discovered and handled, reducing the generation of defective products. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 is a flow chart of the method of the present invention;

[0035] Figure 2 It is a structural schematic diagram of the device in the present invention;

[0036] Figure 3 It is a schematic diagram of the structure of the computer device of the present invention. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0038] like Figure 1 As shown: A method for detecting surface line accumulation of a demoulding cloth comprises the following steps:

[0039] Obtain the surface image of the release cloth and convert it into a grayscale image;

[0040] The low-frequency part of the grayscale image is enhanced using the filter vector to obtain an enhanced image;

[0041] Perform dynamic threshold segmentation on the enhanced image to segment the area where the gray value meets the set threshold;

[0042] Perform morphological processing on the region and segment the connected domain to obtain a region set;

[0043] It is determined whether there is an area in the area set whose size meets the area threshold. If so, it is determined that there is a line accumulation area.

[0044] By timely detecting line accumulation defects on the release cloth, surface defects caused by these defects in carbon plate production can be effectively avoided, thereby improving the quality of the final product. The dynamic threshold segmentation and morphological processing methods enable the solution to adapt to release cloths of different types and thicknesses, improving the applicability of the solution to achieve online detection, so that problems in the production process can be quickly discovered and handled, reducing the generation of defective products.

[0045] In this embodiment, the low-frequency part of the grayscale image is enhanced using a filter vector, including:

[0046] The grayscale image is convolved with two basis filter vectors to obtain an enhanced image.

[0047] The two basic filter vectors are:

[0048] l =

[121] ;

[0049] The convolution kernel el composed of two basic filter vectors is:

[0050]

[0051] A small filter matrix (also called convolution kernel) is used for filtering. The small filter matrix is ​​generally a square matrix, that is, the number of rows and columns is the same. Filtering is to calculate the product of the surrounding pixels and the corresponding position elements of the filter matrix for each pixel in the large matrix, and then add the results together. The final value is used as the new value of the pixel, thus completing a filtering. This method can effectively highlight the line pile-up defects in the image, making the subsequent dynamic threshold segmentation more accurate and enhancing the robustness of the detection. By combining edge and low-frequency information, the identifiability of defects can be improved, thereby improving the overall detection effect.

[0052] The enhanced image is subjected to dynamic threshold segmentation, including:

[0053] Perform mean filtering on the enhanced image to obtain a filtered image;

[0054] The difference between the grayscale values ​​of each corresponding pixel in the contrast enhanced image and the filtered image;

[0055] When the gray value difference is greater than the set threshold G, the pixel is extracted from the enhanced image.

[0056] Mean filtering is applied to the enhanced image to smooth the image and reduce noise. Mean filtering calculates the new value of the current pixel by taking the average value of the neighboring pixels around each pixel to obtain a filtered image. Since the surface of the demoulding cloth has small line accumulation, it is easy to filter out the line accumulation features after mean filtering. Then, by comparing the difference in the grayscale value of each corresponding pixel in the enhanced image and the filtered image, the area with a large change after mean filtering is found, thereby finding the area that may be line accumulation. This method can adapt to image features under different conditions, making the detection process more flexible and accurate.

[0057] As a preferred embodiment of the above, when the enhanced image is mean filtered, the size of the sliding film of the mean filter is calculated by the area threshold. By dynamically adjusting the sliding film size according to the area threshold, it adapts to different production scenarios and defect scales, ensuring the accuracy and robustness of detection. By adjusting the sliding film size based on the area threshold, the mean filtering process can be more adaptive and accurate, further improving the effect of the surface line accumulation defect detection of the demoulding cloth.

[0058] In this embodiment, the synovial size is set to 32*32, and the area threshold is set to [50, 200]. Since it is necessary to eliminate the line accumulation features during mean filtering in order to contrast the parts of the pixel grayscale values ​​in the enhanced image and the filtered image with large changes, the synovial size of the mean filtering needs to be larger than the area threshold, and it cannot be only slightly larger than the area threshold, otherwise it is not easy to eliminate the line accumulation features. At this time, the maximum area threshold is 200, and the area of ​​the synovial size is 1024, which can well eliminate the line accumulation features during mean filtering.

[0059] The morphological processing of the region includes: firstly performing a dilation operation and then performing an erosion operation on the region extracted from the enhanced image, and the size of the dilation operation is 5.

[0060] First, dilate the region extracted from the enhanced image. Dilation will expand the boundaries of the target area in the image, merge adjacent but unconnected pixels, fill small holes and breaks, and enhance the connectivity of the target area. The dilation element size is 5×5, which means that a 5-pixel structure element is used for the operation. This size can effectively smooth small boundary irregularities without excessively affecting the shape of the region. Next, an erosion operation is performed. Erosion will shrink the boundaries of the target area and remove noise points or irrelevant small protrusions, making the extracted target area more accurate. The eroded area will maintain the connectivity after dilation and can restore the area size closer to the original, but remove interference and noise.

[0061] The dilation operation can fill small gaps in the line accumulation area to make the defect area more coherent, while the erosion operation can remove isolated small noise points or over-expanded parts, making the final detection result cleaner and more accurate.

[0062] like Figure 2 As shown, this embodiment also includes a stripping cloth surface line accumulation detection device, using the above method, the detection device includes:

[0063] An acquisition unit, used for acquiring an image of a surface of the demoulding cloth and converting it into a grayscale image;

[0064] An enhancement unit, used for enhancing a low-frequency portion of the grayscale image using a filter vector to obtain an enhanced image;

[0065] A region segmentation unit is used to perform dynamic threshold segmentation on the enhanced image to segment the region whose gray value meets the set threshold;

[0066] Morphological unit, used to perform morphological processing on the region and segment the connected domain to obtain a region set;

[0067] The judging unit is used to judge whether there is a region in the region set whose area size meets the area threshold, and if so, it is judged that there is a line accumulation region.

[0068] See also Figure 3 A computer device 400 provided in an embodiment of the present application includes: a processor 410 and a memory 420, wherein the memory 420 stores a computer program executable by the processor 410, and when the computer program is executed by the processor 410, the above method is executed.

[0069] The embodiment of the present application further provides a storage medium 430 on which a computer program is stored. When the computer program is run by the processor 410, the above method is executed.

[0070] 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 red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0071] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0072] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0073] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0074] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0075] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0076] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of 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 by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0077] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0078] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, 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 cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for detecting surface line accumulation of a release cloth, characterized in that: The steps include: Obtain the surface image of the release cloth and convert it into a grayscale image; Using a filter vector to enhance a low-frequency portion of the grayscale image to obtain an enhanced image; Performing dynamic threshold segmentation on the enhanced image to segment out areas where the grayscale value meets the set threshold; Performing morphological processing on the region and segmenting the connected domain to obtain a region set; It is determined whether there is an area in the area set whose area size meets the area threshold. If so, it is determined that there is a line accumulation area.

2. The method for detecting surface line accumulation of a release cloth according to claim 1, characterized in that: The step of using the filter vector to enhance the low-frequency portion of the grayscale image comprises: The grayscale image is convolved using two basic filter vectors to obtain the enhanced image.

3. The method for detecting surface line accumulation of release cloth according to claim 2, characterized in that: The two basic filter vectors are: The convolution kernel el composed of the two basic filter vectors is:

4. The method for detecting surface line accumulation of a release cloth according to claim 1, characterized in that: The step of performing dynamic threshold segmentation on the enhanced image comprises: Performing mean filtering on the enhanced image to obtain a filtered image; Comparing the difference in grayscale value of each corresponding pixel in the enhanced image and the filtered image; When the gray value difference is greater than the set threshold G, the pixel point is extracted from the enhanced image.

5. The method for detecting surface line accumulation of a release cloth according to claim 4, characterized in that: When the enhanced image is subjected to mean filtering, the size of the synovial membrane obtained by the mean filtering is calculated by using the area threshold.

6. The method for detecting surface line accumulation of a release cloth according to claim 1, characterized in that: The morphological processing of the region includes: first performing a dilation operation and then performing an erosion operation on the region extracted from the enhanced image, and the size of the dilation operation is 5.

7. A device for detecting surface line accumulation of a demoulding cloth, characterized in that: Using the method according to any one of claims 1 to 6, the detection device comprises: An acquisition unit, used for acquiring an image of a surface of the demoulding cloth and converting it into a grayscale image; an enhancement unit, configured to enhance the low-frequency portion of the grayscale image using a filter vector to obtain an enhanced image; A region segmentation unit, used to perform dynamic threshold segmentation on the enhanced image to segment out regions where the grayscale value meets a set threshold; A morphological unit, used for performing morphological processing on the region and segmenting the connected domain to obtain a region set; The judging unit is used to judge whether there is an area in the area set whose area size meets the area threshold, and if so, judge that there is a line accumulation area.

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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