Method for predicting cable extrusion length based on image recognition filter screen blockage characterization

Abstract

The invention provides a cable extrusion length prediction method based on filter screen blockage characterization image recognition, which comprises the following steps: acquiring an original image of a stripped cable extrusion filter screen, and carrying out preprocessing and feature extraction to obtain a feature image; calculating the clogging degree of the cable extrusion filter screen based on the feature image; and constructing a predicted extrusion length model of the corresponding cable material based on the blockage degree of the cable extrusion filter screen, and calculating to obtain the predicted extrusion length. According to the invention, the characterization result of the cable extrusion filter screen blockage degree can be quickly obtained in a test scene based on an image recognition technology, so that the filter screen blockage degree can be quickly and accurately evaluated, and the filter screen blockage degree is closely associated with insulating material characteristic parameters, extruder process parameters and other factors in the cable extrusion process; the cable extrusion length can be accurately predicted under the condition of different material amounts of filter screens of the same model, good guidance is provided for production, the production cost is reduced, and the production efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of image data processing, and in particular to a method for predicting cable extrusion length based on image recognition of filter screen clogging representation. Background Art

[0002] Cables are usually composed of conductors, insulation layers, shielding layers and sheaths. In the cable manufacturing process, the insulation layer, shielding layer and other parts of the cable are usually prepared by extruders. In the cable production process, the extruder melts and plasticizes the pre-treated cable insulation material, and then extrude it through a specific mold to form a continuous insulation layer wrapped around the conductor, which plays the role of electrical insulation, prevents current leakage, and ensures safe and stable power transmission.

[0003] Extruders are widely used in the production of cable materials, mainly because they can achieve continuous and efficient production. It applies pressure to the material through the rotation of the screw, so that the material undergoes plasticization, melting and other processes in the barrel, and is finally extruded. In this process, the material can be evenly mixed and plasticized to ensure the consistency of the physical and chemical properties of the cable material, thereby meeting the strict requirements of cable production. Setting a filter in the extruder is an important measure to ensure the quality of the cable. In the raw materials and production environment, there will inevitably be some impurities, such as metal particles, dust, and incompletely melted plastic particles. If these impurities are mixed into the cable material, defects will be formed inside the cable. In the insulation layer, impurities may reduce the insulation performance, cause partial discharge, and increase the risk of cable breakdown; around the conductor, impurities may affect the uniform distribution of current, cause local overheating, and reduce the current carrying capacity of the cable.

[0004] In actual work, not only the cross-sectional quality of the cable layer should be considered, but also the production length of the cable layer that can be processed by continuous preparation of cable materials under fixed processing conditions should be estimated. At present, the prediction of production length has always been calculated in the form of experience summary, but this prediction method has the following problems: 1. Inaccurate predicted length makes it difficult to determine the material used; insufficient material input will result in the cable layer length not meeting the standard in a single process, thus resulting in defective products; excessive material input will result in the cable layer length being too long in a single process, which not only increases the subsequent processing steps, but also leads to a waste of cable materials; 2. Poor versatility means that after changing the processing parameters, it is necessary to accumulate experience again in order to predict the processing length, which leads to increased costs and reduced quality of finished products.

[0005] Combined with the above content, it can be seen that the normal operation of the cable extrusion filter in the extruder is crucial to the cable extrusion production. When the filter is seriously clogged, the resistance of the material passing through the filter will increase sharply. This will require the extruder screw to apply greater pressure to push the material forward, resulting in an increase in the motor load. At the same time, the extrusion speed of the material will change significantly, which will not only affect the production efficiency, but also may cause fluctuations in cable quality due to the instability of the production process, increase the scrap rate, and bring economic losses and quality risks to the production company.

[0006] In summary, since the state of the filter has a significant impact on the adjustment of cable extrusion process parameters, cable extrusion efficiency and cable surface quality, it is possible to consider establishing a correlation model between the degree of filter blockage and related factors such as the characteristic parameters of cable extrusion insulation materials and the process parameters of the cable extruder. On the one hand, it will help optimize the production process and improve product quality, and on the other hand, it can also make scientific and accurate predictions on the cable extrusion length. Summary of the invention

[0007] In view of the problems existing in the prior art, the present invention provides a method for predicting cable extrusion length by characterizing filter blockage, which is simple, low-cost and universal.

[0008] To achieve the above purpose, the technical solution adopted by the present invention is as follows: A method for predicting cable extrusion length based on image recognition filter blockage characterization mainly includes the following steps: Establishing a correspondence between the cable extrusion filter and the cable material, and peeling off the cable extrusion filter after the cable is extruded to a preset length; Collecting the original image of the cable extrusion filter after stripping; Preprocessing the original image to obtain a processed image; Extracting features from the processed image using a feature extraction algorithm to obtain a feature image; Calculating the blockage degree of the cable extrusion filter based on the characteristic image; Based on the blockage degree of the cable extrusion filter, a corresponding cable material prediction extrusion length model is constructed, and the formula of the prediction extrusion length model is: In the formula, is the blockage threshold of the cable extrusion filter, is the predicted extrusion length of the corresponding cable material, is the blockage degree of the cable extrusion filter when the cable is extruded to a preset length, Extruding a preset length of the cable, The insulation thickness of the cable when it is extruded to a preset length, The conductor diameter of the cable when it is extruded to a preset length, is the insulation thickness of the cable extruded from the corresponding cable material, The conductor diameter of the cable is extruded from the corresponding cable material.

[0009] Optionally, the acquisition operation of the original image includes: shaping the cable extrusion filter, and laying the cable extrusion filter flat on a solid color background; Continuously photographing the working surface of the cable extrusion filter screen vertically through a camera, and obtaining a photographic set; The photographic atlas is screened based on imaging effects, and at least one photo is selected as the original image.

[0010] Optionally, the original image acquisition operation further includes: A shooting light source is placed at the side of the cable extrusion filter, and the shooting light source is equipped with a soft light tool; The camera is equipped with a polarizing filter, and during continuous shooting, the angle of the polarizing filter is periodically adjusted.

[0011] Optionally, screening the photographed atlas based on imaging effects includes: The amount of reflection of each photo in the photographed atlas is calculated based on the pixel brightness value analysis method, and the photo with the smallest amount of reflection is taken as the original image.

[0012] Optionally, the preset extrusion length of the cable is 20%-35% of the theoretical extrusion length of the cable material.

[0013] Optionally, the step of preprocessing the original image at least includes: The original image is subjected to denoising, contrast enhancement and color correction.

[0014] Optionally, the feature extraction algorithm includes edge detection and texture analysis; The characteristic information of the characteristic image includes porosity, texture and color distribution.

[0015] Optionally, calculating the blockage degree of the cable extrusion filter based on the characteristic image includes: Gray-scale the feature image to obtain a grayscale image; Extracting local texture information from the grayscale image by using a local binary pattern algorithm, and performing binary segmentation to obtain a binary image; Performing median filtering on the binary image to obtain an optimized image; The contour of the optimized image is extracted by a center diffusion method, and a contour map is obtained.

[0016] Optionally, calculating the blockage degree of the cable extrusion filter based on the characteristic image further includes: The proportion of blocked grids in the cable extrusion filter is calculated based on the contour map and used as the blockage degree of the cable extrusion filter.

[0017] Optionally, the blockage threshold of the cable extrusion filter is 25%.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The present invention can quickly obtain the characterization results of the cable extrusion filter blockage degree under the test scenario based on image recognition technology, so as to realize the rapid and accurate evaluation of the filter blockage degree, and closely link the filter blockage degree with the insulating material characteristic parameters, extruder process parameters and other factors in the cable extrusion process, and provide accurate prediction of the cable extrusion length under different material dosage conditions of the same type of filter, which has good guidance for production, reduces production costs and improves production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] 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 will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0020] Figure 1 A flowchart of a method in a specific embodiment of the present invention; Figure 2 is the original image in Example 1 of the present invention; Figure 3 The enhanced image in Embodiment 1 of the present invention; Figure 4 is the binarized image in Example 1 of the present invention; Figure 5 This is a contour diagram in Example 1 of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0023] In the description of the present invention, “plurality” means two or more than two, unless otherwise clearly and specifically defined.

[0024] In the present invention, unless otherwise clearly specified and limited, the terms "installation", "connection" 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 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.

[0025] It is worth noting that the methods used in the present invention are all conventional methods unless otherwise specified; the raw materials and devices used are all conventional commercially available products, and their sources are not specifically limited unless otherwise specified.

[0026] like Figure 1 As shown, this embodiment provides a method for predicting cable extrusion length based on image recognition filter blockage characterization, which mainly includes the following steps: First of all, it is necessary to confirm that in order to accurately predict the length of the cable layer that can be processed under the condition of a known amount of material and the working conditions of the equipment, corresponding experiments need to be carried out. Therefore, short-time extrusion and long-time extrusion are defined. Short-time extrusion corresponds to stopping the machine after the cable is extruded to a preset length; while long-time extrusion corresponds to stopping the machine after a certain amount of cable material is completely processed and extruded.

[0027] Among them, it is known that the working condition that affects the continuous extrusion of cable materials is the clogging of the filter. In the actual extrusion process, when the filter clogging reaches the clogging threshold, the melting pressure will increase sharply, causing the subsequent cable production to stop. Therefore, the goal of this embodiment is to study the relationship between the clogging of the cable extrusion filter and the extrusion length.

[0028] Optionally, the preset length of cable extrusion should allow the filter to present a certain working state (the image clearly identifies the blockage), and on the other hand, it should also reduce the use of raw materials as much as possible. Therefore, the preset length of cable extrusion is designed to be 20%-35% of the theoretical extrusion length of the cable material. Among them, the theoretical extrusion length of the cable material is the calculated length obtained by dividing the cable material used in the task by the cross-sectional area of ​​the cable layer after processing.

[0029] Therefore, the corresponding relationship between the cable extrusion filter and the cable material is first established, that is, the model of the cable extrusion filter used and the model of the cable material to be used (components, ratios or product names, etc.) are determined according to the processing task. In each group of experiments, ensure that the model of the cable extrusion filter is consistent with the model of the cable material and the processing task information.

[0030] In each group of experiments, the cable extrusion filter is peeled off after the cable is extruded to a preset length, that is, the machine is stopped after a short period of extrusion, and the operator uses tools and tools to remove the cable extrusion filter used in this group without damage, such as Figure 2 shown.

[0031] Collecting the original image of the stripped cable extrusion filter; Optionally, the operation of collecting the original image includes the following steps: (1) Shape the cable extrusion filter and lay it flat on a solid color background; Optionally, since the cable extrusion filter is usually made of metal and the force direction is fixed during operation, it may have warped edges, which results in poor imaging effects, especially when there are few blockages, and it is difficult to obtain accurate results. Therefore, it is necessary to reshape the cable extrusion filter to a certain extent to restore its lateral straight state. At present, there are three common shaping methods, specifically: The splint shaping method uses a splint to clamp the cable and extrude the filter, and performs high and low temperature cycles or high temperature-natural cooling to reshape it; its advantages are simple operation and controllable costs, but because the splint will contact the working surface of the filter, it will cause problems such as blockage falling off and deformation, resulting in inaccurate image recognition results, especially in the case of mild blockage.

[0032] The fixture extension method uses a ring-shaped fixture to fix the outer ring of the cable extrusion filter and applies a certain tension to reshape it. Its advantage is that it avoids contact with the working area and affects the shape and total amount of the blockage. However, due to the complex process, it leads to high operating requirements and complex tooling structure. In addition, unreasonable application of tension will cause the filter to deform and affect the calculation accuracy. Moreover, due to the existence of the tooling, additional tooling image removal work is required in the subsequent image recognition process, which not only increases the workload, but also causes an abnormal increase in blockage due to residual pixels, or an abnormal decrease in blockage due to a reduction in the blocked area due to excessive removal.

[0033] The direct scanning method is similar to the splint shaping method, that is, the filter is directly placed in the scanning device for cover scanning. It not only has accuracy problems, but also due to the light control problem of the scanning device, there are a lot of reflections, which distorts the image.

[0034] Therefore, in order to enhance the image shooting effect, the bonding fixation method can be used: if the warping is not serious, a suitable adhesive can be used to fix the warping part on a flat substrate. Choose an adhesive that has good adhesion to stainless steel, such as some epoxy resin adhesives. Before bonding, make sure that the cable extrusion filter and the substrate surface (solid color background) are clean and dry, apply the adhesive evenly to the contact between the warping part and the substrate, and then press the edge of the cable extrusion filter on the substrate to keep it flat. After the adhesive is fully cured, remove the filter from the substrate. This method is relatively simple to operate, but it may cause certain contamination to the surface of the cable extrusion filter, and the selection and use of the adhesive need to be cautious to ensure that its performance meets the requirements. Alternatively, when the cable extrusion filter is made of martensitic stainless steel or ferritic stainless steel, prepare a non-metallic platform, install an electromagnet on the back of the shooting area, place the cable extrusion filter on the shooting area and flatten it, and then energize the electromagnet to adsorb the cable extrusion filter in the area.

[0035] No matter which of the above fixing methods is adopted, in order to obtain better shooting effects, a solid color background can be a white background, such as a flat white background board, white tabletop, white tablecloth, etc.

[0036] (2) Continuously photographing the working surface of the cable extrusion filter screen vertically through a camera and obtaining a photographic set; optionally, this step also includes: The camera is fixed in position, directly above the cable extrusion filter, so there is no adjustment option except shooting distance. The cable extrusion filter is generally made of metal, such as stainless steel, so its reflection problem needs to be considered, because the reflection will significantly affect the judgment of the blockage, thereby directly affecting the blockage calculation results.

[0037] Therefore, the shooting light source is designed to be placed on the side of the cable extrusion filter, and the shooting light source is equipped with soft light tools, such as soft light cover, diffuser, etc., to prevent strong light from directly irradiating the metal mesh and causing strong reflection. At the same time, the position and direction of the light source can be changed to illuminate the metal mesh from the side or above at a certain angle, rather than vertically, to reduce the specular reflection of light. In this way, the light can be evenly distributed on the metal mesh, reducing local excessive reflection and improving the overall shooting effect.

[0038] Furthermore, a polarizing filter is installed on the camera, which can effectively reduce the reflection of non-metallic surfaces and also has a certain effect on metal meshes. By installing a polarizing filter in front of the lens and rotating it to adjust its angle, polarized light in a specific direction can be selectively blocked, thereby reducing the reflection intensity of the metal mesh and enhancing the clarity and details of the image. The principle is to use the optical properties of the polarizing filter to only allow light in a specific direction to pass through, filter out most of the polarized light generated by the reflection, and make the texture and structure of the metal mesh easier to capture. Furthermore, it is necessary to periodically adjust the angle of the polarizing filter during continuous shooting to form a collection of shooting images with different imaging effects.

[0039] (3) Filtering the photo collection based on imaging effects, and selecting at least one photo as the original image; optionally, filtering the photo collection based on imaging effects includes: The amount of reflection of each photo in the photo collection is calculated based on the pixel brightness value analysis method, and the photo with the smallest amount of reflection is taken as the original image. Specifically, in a digital image, each pixel has a corresponding brightness value. The amount of reflection can be quantified by extracting the brightness value of the pixels in the reflective area. Use image processing software (such as Adobe Photoshop or Python's OpenCV library) to select the pixels in the reflective area and count their average brightness value or the distribution of the brightness value. For example, in OpenCV, you can read the image file, convert the image into a grayscale image, and then use the function to obtain the brightness information of the pixels in the reflective area. A higher brightness value usually indicates a stronger reflection. By recording and analyzing these values, the magnitude of the reflection can be reflected to a certain extent. The advantage of this method is that it is relatively simple and direct, and can quickly obtain the basic brightness characteristics of the reflective area in the image. After that, the amount of reflection of the photos in the photo collection is sorted from small to large, and the photo with the smallest amount of reflection is selected as the original image.

[0040] Preprocess the original image and obtain the processed image; optionally, to effectively retain edge information, the collected original image is first denoised using Gaussian denoising, then bilateral filtering denoising, and the image signal-to-noise ratio is calculated. If the signal-to-noise ratio is greater than the standard value, the subsequent steps are performed; if it is lower than the standard value, the denoising operation is continued; then the Sobel operator is applied to calculate the gradient amplitude of the image to further identify the edge, and finally, to avoid the influence of noise, the contrast-limited adaptive histogram equalization method is applied to the local area of ​​the image for equalization preprocessing operations to improve the accuracy of subsequent analysis. Figure 3 As shown, it is the processed image after HSV color enhancement method.

[0041] The feature extraction algorithm is used to extract features from the processed image and obtain a feature image; optionally, this step is to use edge detection, texture analysis and other algorithms to extract features in the processed image, such as porosity, texture changes and color distribution, so as to perform subsequent image recognition work.

[0042] Calculating the blockage degree of the cable extrusion filter based on the characteristic image; Optionally, calculating the blockage degree of the cable extrusion filter based on the characteristic image includes: Grayscale the feature image to obtain a grayscale image; The local binary pattern (LBP) algorithm is used to extract local texture information from the grayscale image, and binary segmentation is performed to obtain a binary image, such as Figure 4 As shown; The binary image is filtered by Canny edge detection to obtain an optimized image. In view of the difference in image quality, the number of pixels of the five grids with obvious sharp edges on the outer edge of the filter is extracted based on the porosity and local texture information obtained above, and finally the grid area of ​​the filter is calculated. Considering the diffusion of filter clogging, the contour of the optimized image is extracted by the center diffusion method, and the contour map is obtained, such as Figure 5 shown.

[0043] Furthermore, the proportion of pixels in the contour area is calculated based on the contour map programming, and the proportion of blocked grids is determined based on the comparison and matching with the unblocked filter image, and is output as the blockage degree of the cable extrusion filter.

[0044] Based on the blockage degree of the cable extrusion filter, a corresponding model for predicting the extrusion length of the cable material is constructed. In the process of cable extrusion, the unit volume flow rate of the cable material remains constant, and the proportion of impurities in the unit volume of the cable material is constant. As the impurity particles are enriched in the cable extrusion filter, the blockage degree of the filter increases; according to the Bernoulli equation, the flow rate and flow velocity present a power nonlinear relationship. Since the unit volume flow rate of the cable material remains constant, the flow velocity will increase nonlinearly. Therefore, the volume of the cable material passing through the unblocked filter increases, resulting in a nonlinear increase in the blockage degree. Moreover, the longer the extruded cable length, the faster the blockage rate increases, indicating that the nonlinear power coefficient is related to the extruded cable length. Assuming the preset length The congestion degree is (0< <1), therefore, according to the above theory, the formula for predicting the extrusion length model is: In the formula, is the clogging threshold of the cable extrusion filter, is the predicted extrusion length of the corresponding cable material, The degree of clogging of the cable extrusion filter when the cable is extruded to a preset length. Extrude a preset length for the cable, The insulation thickness of the cable when it is extruded to a preset length, The conductor diameter of the cable when it is extruded to a preset length, is the insulation thickness of the cable extruded from the corresponding cable material, The conductor diameter of the cable extruded from the corresponding cable material.

[0045] in, and The extruder processing parameters corresponding to the long-term extrusion are shown in Table 1. and Exact consistency is not required.

[0046] Therefore, in this embodiment, the blockage threshold of the cable extrusion filter is set to 25% according to the processing conditions. By introducing the blockage of the cable extrusion filter obtained by the aforementioned image recognition, the length of the cable to be extruded for a long time can be predicted, that is, the expected extrusion length when the upper limit of continuous processing allowed by the extruder is reached.

[0047] Therefore, the timing of shutdown can be clearly determined, that is, when the length of the continuously extruded cable layer reaches the above predicted length, it means that the blockage degree is about 25%, and this can be used as a guide for shutdown work. After that, the cable extrusion filter can be replaced or cleaned, thereby reducing extruder failure or unqualified product quality.

[0048] Embodiment 1; S1: Image acquisition: Use a high-resolution camera to shoot the cable extrusion filter that is stripped after short-term extrusion of 500m (preset cable extrusion length) of cable to obtain the original image of the filter surface.

[0049] S2: Image preprocessing: performing preprocessing operations such as denoising, contrast enhancement and color correction on the collected original images to improve the accuracy of subsequent analysis.

[0050] S3: Feature extraction: using edge detection, texture analysis and other algorithms to extract features from the processed image, such as porosity, texture changes and color distribution.

[0051] S4: Blockage assessment: Based on the extracted features, the image is grayed out, and the local texture information of the filter surface is extracted using an algorithm based on local binary patterns (LBP). Binary segmentation is achieved by setting an appropriate grayscale threshold, and the image is further optimized using the median filtering method. Considering the diffusivity of filter blockage, the contour is extracted using the center diffusion method.

[0052] S5: Result output and decision-making; program to calculate the pixel ratio in the contour area, and determine the ratio of blocked grids based on the comparison and matching with the unblocked filter image. The blockage degree is calculated to be 1.2%.

[0053] S6: Theoretical prediction: According to the above formula, when the filter blockage area is 25%, the predicted extrusion length is 20095.33m.

[0054] in, and The extruder processing parameters corresponding to the long-term extrusion are shown in Table 1. and The parameters are summarized in Table 1: Table 1 Further, even if and The extruder processing parameters corresponding to the long-term extrusion are shown in Table 1. and Inconsistent, better results can also be obtained. In another embodiment, the same method can obtain the following parameters, which are summarized in Table 2: Table 2 Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A method for predicting cable extrusion length based on image recognition filter blockage characterization, characterized in that: The steps include: Establishing a correspondence between the cable extrusion filter and the cable material, and peeling off the cable extrusion filter after the cable is extruded to a preset length; Collecting the original image of the cable extrusion filter after stripping; Preprocessing the original image to obtain a processed image; Extracting features from the processed image using a feature extraction algorithm to obtain a feature image; Calculating the blockage degree of the cable extrusion filter based on the characteristic image; Based on the blockage degree of the cable extrusion filter, a corresponding cable material prediction extrusion length model is constructed, and the formula of the prediction extrusion length model is: In the formula, is the blockage threshold of the cable extrusion filter, is the predicted extrusion length of the corresponding cable material, is the blockage degree of the cable extrusion filter when the cable is extruded to a preset length, Extruding a preset length of the cable, The insulation thickness of the cable when it is extruded to a preset length, The conductor diameter of the cable when it is extruded to a preset length, is the insulation thickness of the cable extruded from the corresponding cable material, The conductor diameter of the cable is extruded from the corresponding cable material.

2. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 1 is characterized by: The acquisition operation of the original image includes: shaping the cable extrusion filter, and laying the cable extrusion filter flat on a solid color background; Continuously photographing the working surface of the cable extrusion filter screen vertically with a camera, and obtaining a photographic set; The photographic atlas is screened based on imaging effects, and at least one photo is selected as the original image.

3. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 2 is characterized by: The acquisition operation of the original image also includes: A shooting light source is placed at the side of the cable extrusion filter, and the shooting light source is equipped with a soft light tool; The camera is equipped with a polarizing filter, and during continuous shooting, the angle of the polarizing filter is periodically adjusted.

4. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 2 or 3, characterized in that: Filtering the photographic atlas based on imaging effects includes: The amount of reflection of each photo in the photographed atlas is calculated based on the pixel brightness value analysis method, and the photo with the smallest amount of reflection is taken as the original image.

5. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 1 is characterized by: The preset extrusion length of the cable is 20%-35% of the theoretical extrusion length of the cable material.

6. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 1 is characterized by: The step of preprocessing the original image at least comprises: The original image is subjected to denoising, contrast enhancement and color correction.

7. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 1 is characterized by: The feature extraction algorithm includes edge detection and texture analysis; The characteristic information of the characteristic image includes porosity, texture and color distribution.

8. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 1 is characterized by: Calculating the blockage degree of the cable extrusion filter based on the characteristic image includes: Gray-scale the feature image to obtain a grayscale image; Extracting local texture information from the grayscale image by using a local binary pattern algorithm, and performing binary segmentation to obtain a binary image; Performing median filtering on the binary image to obtain an optimized image; The contour of the optimized image is extracted by a center diffusion method, and a contour map is obtained.

9. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 8 is characterized by: Calculating the blockage degree of the cable extrusion filter based on the characteristic image also includes: The proportion of blocked grids in the cable extrusion filter is calculated based on the contour map and used as the blockage degree of the cable extrusion filter.

10. The method for predicting cable extrusion length based on image recognition filter blockage characterization according to claim 1, characterized in that: The cable extrusion filter has a blockage threshold of 25%.

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