Method, device and equipment for detecting apparent fouling in carbon plate forming process

Abstract

The invention relates to the technical field of production and detection of composite materials, in particular to an apparent fouling detection method, device and equipment in a carbon plate forming process, and the method comprises the following steps: obtaining a surface image of a carbon plate, and graying the image to obtain a grayscale image; according to the gray value difference of the pixel points in the gray image, gray area division is carried out on the pixel points in the gray image; selecting and dividing a gray region with the maximum area, and solving a complementary set of the gray region and the gray image; performing connected domain segmentation on the complementary set to obtain a plurality of sub-regions, and extracting the sub-regions meeting conditions in the sub-regions through a set threshold value; and calculating the variance of each extracted sub-region, judging whether the variance of the sub-region is greater than a set value, and if so, judging that the sub-region is stained. According to the invention, tiny and complex stains can be effectively detected, the method is suitable for online real-time detection, and the production efficiency and the product quality are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of composite material production detection, and in particular to a method, device and equipment for detecting surface contamination in a carbon plate forming process. 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 thermal expansion coefficient. Therefore, it is widely used as the reinforcement of carbon fiber reinforced resin-based composites (CFRP) in cutting-edge defense technologies such as aerospace and aviation. It is also a new material for the upgrading of civilian industries.

[0003] During the production process of carbon plates, sometimes there will be stains on the surface, which affects the product quality. However, due to the product process, it is impossible to achieve 100% inspection through manual labor, which is prone to errors.

[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 and equipment for detecting surface contamination in a carbon plate forming process, 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 contamination during the carbon plate forming process, comprising the following steps:

[0007] Acquire the surface image of the carbon plate, and grayscale the image to obtain a grayscale image;

[0008] Dividing the pixels in the grayscale image into grayscale areas according to the grayscale value differences of the pixels in the grayscale image;

[0009] Selecting the grayscale region with the largest area, and obtaining the complement of the grayscale region and the grayscale image;

[0010] Segmenting the complement set into connected domains to obtain a plurality of sub-regions, and extracting sub-regions meeting the conditions from among the sub-regions by setting thresholds;

[0011] The variance of each of the extracted sub-regions is calculated to determine whether there is a sub-region whose variance is greater than a set value, and if so, it is determined to be contaminated.

[0012] Furthermore, dividing the grayscale areas of the pixels in the grayscale image by grayscale value differences of the pixels in the grayscale image comprises the following steps:

[0013] Setting a convolution kernel and traversing the grayscale image through the convolution;

[0014] Calculate the difference between the grayscale value of the center pixel in the convolution kernel and the grayscale value of the center pixel of the convolution kernel in its area;

[0015] If the difference is less than the set grayscale value, the pixels corresponding to the two convolution kernels are merged into the same area;

[0016] The steps of calculating the gray value difference and merging are repeated until the pixels in the gray image are divided into a plurality of gray areas.

[0017] Furthermore, the convolution kernel size is set to be a square.

[0018] Furthermore, extracting the sub-regions meeting the conditions in the sub-regions by setting a threshold comprises:

[0019] Extracting the height value of the grayscale image;

[0020] A sub-region of the sub-region whose height is smaller than the height value of the grayscale image is selected.

[0021] Furthermore, in the determining whether there is a sub-region whose variance is greater than a set value, the set value is 10.

[0022] Furthermore, after the determination as being damaged, the method further includes: marking and sending the position of the sub-region determined to be damaged.

[0023] The present invention also includes a device for detecting surface contamination during the carbon plate forming process, using the above method, the device comprising:

[0024] An acquisition unit is used to obtain a surface image of the carbon plate and grayscale the image to obtain a grayscale image;

[0025] A grayscale division unit, used for dividing the pixel points in the grayscale image into grayscale areas according to the grayscale value differences of the pixel points in the grayscale image;

[0026] A grayscale extraction unit, used for selecting and dividing the grayscale region with the largest area, and obtaining the complement of the grayscale region and the grayscale image;

[0027] A sub-region extraction unit, used for segmenting the complement set into connected domains to obtain a plurality of sub-regions, and extracting sub-regions meeting the conditions in the sub-regions by setting a threshold;

[0028] The judging unit is used to calculate the variance of each of the extracted sub-regions, and judge whether there is a sub-region whose variance is greater than a set value, and if so, judge it as contaminated.

[0029] 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.

[0030] 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.

[0031] The beneficial effects of the present invention are as follows: through grayscale area division, connected domain analysis and variance judgment, it can effectively detect small and complex stains, adapt to the surface characteristics of different types of carbon plates, eliminate interference information, simplify grayscale calculation and segmentation algorithms, be suitable for online real-time detection, realize real-time monitoring and alarm, and improve production efficiency and product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] 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.

[0033] Figure 1 is a flow chart of the method of the present invention;

[0034] Figure 2 is a schematic diagram of a grayscale image;

[0035] Figure 3 is a schematic diagram of the divided grayscale areas;

[0036] Figure 4 is a schematic diagram of the sub-region after screening;

[0037] Figure 5 It is a structural schematic diagram of the device of the present invention;

[0038] Figure 6 It is a schematic diagram of the structure of the computer device of the present invention. DETAILED DESCRIPTION

[0039] 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.

[0040] like Figure 1 As shown: A method for detecting surface contamination during carbon plate forming process, comprising the following steps:

[0041] Obtain the surface image of the carbon plate, and convert the image into grayscale to obtain a grayscale image. The grayscale image of the surface of the carbon plate containing the contamination defect is as follows: Figure 2 As shown;

[0042] According to the gray value difference of the pixel points in the gray image, the pixel points in the gray image are divided into gray areas;

[0043] Select the grayscale region with the largest area and find the complement of the grayscale region and the grayscale image;

[0044] The complement set is segmented into connected domains to obtain several sub-regions, and the sub-regions that meet the conditions are extracted from the sub-regions by setting thresholds;

[0045] The variance of each extracted sub-region is calculated to determine whether there is a sub-region whose variance is greater than a set value. If so, it is determined to be contaminated.

[0046] Use a high-resolution industrial camera to obtain the surface image of the carbon plate, convert the original color image into a grayscale image (grayscale), and the grayscale value represents the brightness information of the pixel, thereby reducing the computational complexity. After the grayscale area is divided, the grayscale area with the largest area (usually the main surface area of ​​the carbon plate) is determined, and the complement of the grayscale area is calculated, that is, all the pixels that do not belong to the area. These pixels may contain contamination information, and thresholds are set for the area, grayscale features and other attributes of each sub-area. The variance of the grayscale value of each sub-area is calculated. The variance reflects the degree of change of the grayscale value in the area. If the variance of a sub-area exceeds the set value (indicating that the grayscale changes in the area are significant and there are abnormal features), the sub-area is determined to be a contaminated area.

[0047] Through grayscale area division, connected domain analysis and variance judgment, it can effectively detect small and complex stains, adapt to different types of carbon plate surface characteristics, eliminate interference information, simplify grayscale calculation and segmentation algorithms, and is suitable for online real-time detection. It can realize real-time monitoring and alarm, and improve production efficiency and product quality.

[0048] In this embodiment, grayscale area division is performed on the pixels in the grayscale image according to the grayscale value differences of the pixels in the grayscale image, and the steps include:

[0049] Set a convolution kernel and traverse the grayscale image through convolution;

[0050] Calculate the difference between the grayscale value of the center pixel in the convolution kernel and the grayscale value of the center pixel of the convolution kernel in its area;

[0051] If the difference is less than the set grayscale value, the pixels corresponding to the two convolution kernels are merged into the same area;

[0052] Repeat the steps of calculating gray value difference and merging until the pixels in the gray image are divided into several gray areas. Figure 3 shown.

[0053] Define a convolution kernel of a fixed size, traverse the grayscale image, extract local pixel information, and calculate the difference between the grayscale value of the pixel at the center of the current convolution kernel and the grayscale value of the pixel at the center of other convolution kernels in its neighborhood:

[0054] |g(i)-g(i+1)| <T;

[0055] g(i) is the gray value of the pixel at the center of the current convolution kernel, and g(i+1) is the gray value of the pixels at the center of other convolution kernels in its neighborhood. A gray difference threshold T is set. If the gray value difference is less than T, the current pixel and the neighborhood center pixel are considered to belong to the same gray area. The pixels that meet the threshold conditions are merged and marked as the same gray area. For pixels that have not yet been divided, the above steps are repeated until all pixels are divided into several gray areas.

[0056] The local calculation method using the convolution kernel can adapt to the change of grayscale value more flexibly and ensure the accuracy of the divided area. By adjusting the grayscale difference threshold T and the convolution kernel size, it can cope with carbon plate surfaces with different textures and complexities. In this embodiment, the grayscale difference threshold T is set to 20. Through multiple iterations, it is ensured that all pixels in the image are correctly grouped to avoid omissions. The convolution kernel operation has the potential for parallelization and is suitable for hardware acceleration (such as GPU) to improve the efficiency of large-scale image processing.

[0057] As a preference of the above embodiment, the convolution kernel size is set to a square. If the surface texture of the carbon plate is more complex and the contaminated area is small, a smaller convolution kernel (such as 3×3) can be selected; if the surface texture is more uniform, a slightly larger convolution kernel (such as 5×5) can be selected to reduce the amount of calculation.

[0058] In this embodiment, sub-regions meeting the conditions are extracted from the sub-regions by setting a threshold, including:

[0059] Extract the height value of the grayscale image;

[0060] Select the sub-region whose height is less than the height value of the grayscale image. The extracted sub-region is as follows Figure 4 shown.

[0061] The largest grayscale area extracted is the area on the surface of the carbon plate. After the complement is calculated, the area on the surface of the carbon plate can be removed. However, due to the difference between the stain on the surface of the carbon plate and the grayscale of the carbon plate, the stain area will be retained. At this time, after segmenting the connected domain, the sub-area will include the stain area and the background area. The height of the background area is usually the height of the image, so it is necessary to extract the sub-area that is less than the height value of the grayscale image. The extracted sub-area contains the stain area. Through this height value-based screening, irrelevant areas can be quickly eliminated and the focus can be placed on potential stain areas.

[0062] In the process of judging whether there is a sub-region with a variance greater than a set value, the set value is 10.

[0063] By calculating the variance and comparing it with the set threshold, it is possible to accurately identify the contaminated area with significant grayscale changes and avoid false detection.

[0064] As a preferred embodiment of the above, after determining that the area is contaminated, the method further includes: marking and sending the location of the sub-area determined to be contaminated, and sending the location information of the marked contaminated sub-area to a back-end system or control system for subsequent processing, such as alarming or adjusting the production process.

[0065] Position marking and information transmission enable contamination detection to be linked to the production process in real time. Marking position information helps to automatically repair or adjust process parameters. By marking the contaminated area and sending information, it can not only be viewed in real time on the production line, but also provide data support for subsequent quality traceability.

[0066] like Figure 5 As shown, this embodiment also includes a surface contamination detection device during the carbon plate forming process, using the above method, the device includes:

[0067] An acquisition unit is used to obtain a surface image of the carbon plate and grayscale the image to obtain a grayscale image;

[0068] A grayscale division unit, used for dividing the grayscale areas of the pixels in the grayscale image according to the grayscale value differences of the pixels in the grayscale image;

[0069] A grayscale extraction unit is used to select and divide the grayscale region with the largest area, and obtain the complement of the grayscale region and the grayscale image;

[0070] A sub-region extraction unit is used to segment the complement set into connected domains to obtain a number of sub-regions, and extract sub-regions that meet the conditions in the sub-regions by setting a threshold;

[0071] The judging unit is used to calculate the variance of each extracted sub-region and judge whether there is a sub-region whose variance is greater than a set value. If so, it is judged as contaminated.

[0072] Use a high-resolution industrial camera to obtain the surface image of the carbon plate, convert the original color image into a grayscale image (grayscale), and the grayscale value represents the brightness information of the pixel, thereby reducing the computational complexity. After the grayscale area is divided, the grayscale area with the largest area (usually the main surface area of ​​the carbon plate) is determined, and the complement of the grayscale area is calculated, that is, all the pixels that do not belong to the area. These pixels may contain contamination information, and thresholds are set for the area, grayscale features and other attributes of each sub-area. The variance of the grayscale value of each sub-area is calculated. The variance reflects the degree of change of the grayscale value in the area. If the variance of a sub-area exceeds the set value (indicating that the grayscale changes in the area are significant and there are abnormal features), the sub-area is determined to be a contaminated area.

[0073] Through grayscale area division, connected domain analysis and variance judgment, it can effectively detect small and complex stains, adapt to different types of carbon plate surface characteristics, eliminate interference information, simplify grayscale calculation and segmentation algorithms, and is suitable for online real-time detection. It can realize real-time monitoring and alarm, and improve production efficiency and product quality.

[0074] See also Figure 6 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.

[0075] 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.

[0076] 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.

[0077] 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.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] 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.

[0084] 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 contamination during carbon plate forming, characterized in that: The steps include: Acquire the surface image of the carbon plate, and grayscale the image to obtain a grayscale image; Dividing the pixels in the grayscale image into grayscale areas according to the grayscale value differences of the pixels in the grayscale image; Selecting the grayscale region with the largest area, and obtaining the complement of the grayscale region and the grayscale image; Segmenting the complement set into connected domains to obtain a plurality of sub-regions, and extracting sub-regions meeting the conditions among the sub-regions by setting thresholds; The variance of each of the extracted sub-regions is calculated to determine whether there is a sub-region whose variance is greater than a set value, and if so, it is determined to be contaminated.

2. The method for detecting surface contamination during carbon plate forming according to claim 1, characterized in that: The grayscale region division of the pixels in the grayscale image according to the grayscale value differences of the pixels in the grayscale image comprises the following steps: Setting a convolution kernel and traversing the grayscale image through the convolution; Calculate the difference between the grayscale value of the center pixel in the convolution kernel and the grayscale value of the center pixel of the convolution kernel in its area; If the difference is less than the set grayscale value, the pixels corresponding to the two convolution kernels are merged into the same area; The steps of calculating the gray value difference and merging are repeated until the pixels in the gray image are divided into a plurality of gray areas.

3. The method for detecting surface contamination during carbon plate forming according to claim 2, characterized in that: The convolution kernel size is set to be a square.

4. The method for detecting surface contamination during carbon plate forming according to claim 1, characterized in that: The extracting the sub-regions meeting the conditions in the sub-regions by setting a threshold comprises: Extracting the height value of the grayscale image; A sub-region of the sub-region whose height is smaller than the height value of the grayscale image is selected.

5. The method for detecting surface contamination during carbon plate forming according to claim 1, characterized in that: In the step of determining whether there is a sub-region where the variance is greater than a set value, the set value is 10.

6. The method for detecting surface contamination during carbon plate forming according to claim 1, characterized in that: After the determination is made as being damaged, the method further includes: marking and sending the position of the sub-region determined to be damaged.

7. A device for detecting surface contamination during carbon plate forming, characterized in that: Using the method according to any one of claims 1 to 6, the device comprises: An acquisition unit is used to obtain a surface image of the carbon plate and grayscale the image to obtain a grayscale image; A grayscale division unit, used for dividing the pixel points in the grayscale image into grayscale areas according to the grayscale value differences of the pixel points in the grayscale image; A grayscale extraction unit, used for selecting and dividing the grayscale region with the largest area, and obtaining the complement of the grayscale region and the grayscale image; A sub-region extraction unit, used for segmenting the complement set into connected domains to obtain a plurality of sub-regions, and extracting sub-regions meeting the conditions in the sub-regions by setting a threshold; The judging unit is used to calculate the variance of each of the extracted sub-regions, and judge whether there is a sub-region whose variance is greater than a set value, and if so, judge it as contaminated.

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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