Cable information tracing method and device, electronic equipment and storage medium

Abstract

This application proposes a cable information traceability method, apparatus, electronic device, and storage medium. The cable information traceability method includes: acquiring a cable image containing visual information of the cable; based on the cable image, performing feature extraction on the visual information using a preset feature extraction model to obtain structural features of identifiers on the cable; determining the authenticity information of the cable based on the structural features and pre-stored Industrial Internet identifiers; and, if the authenticity information indicates that the cable is a qualified product, outputting the cable traceability information based on the Industrial Internet identifiers. This application can improve the accuracy of cable authenticity information during the identification of cable authenticity and can improve the accuracy of cable traceability information based on Industrial Internet identifiers.

Description

Technical Field

[0001] This application relates to the field of industrial internet technology, specifically to the field of cable information traceability technology, and particularly to a cable information traceability method, device, electronic device and storage medium. Background Technology

[0002] With the rapid development of the Industrial Internet and intelligent manufacturing, cables, as a critical energy supply infrastructure, are becoming increasingly important for anti-counterfeiting and life-cycle traceability. Currently, anti-counterfeiting strategies for cables typically employ QR codes attached to labels or certificates of conformity, combined with scratch-off anti-counterfeiting codes. Users need to scratch off the coating and enter the code value for verification.

[0003] However, this explicit anti-counterfeiting method relies on visible graphics or codes, which are easily copied or counterfeited. It also suffers from poor durability, easy duplication, and disconnection from the product itself. Its anti-counterfeiting performance is low, and it cannot achieve uncopyable and highly reliable information traceability. Summary of the Invention

[0004] In view of the above, it is necessary to propose a cable information traceability method, device, electronic equipment, and storage medium to solve the technical problems of low accuracy in identifying the authenticity of cables and the accuracy of traceability information. The relevant equipment includes a cable information traceability device and electronic equipment.

[0005] This application provides a cable information traceability method, the method comprising: acquiring a cable image containing the cable; extracting features from the cable image using a preset feature extraction model to obtain structural features of identifiers on the cable; determining the authenticity information of the cable based on the structural features and a pre-stored industrial internet identifier; and outputting the traceability information of the cable based on the industrial internet identifier if the authenticity information indicates that the cable is a qualified product.

[0006] In some embodiments, the step of extracting features from the cable image using a preset feature extraction model to obtain structural features of identifiers on the cable includes: inputting the cable image into the preset feature extraction model to determine the pixel points corresponding to the cable in the cable image; determining a first pixel point corresponding to the identifier based on the pixel points; determining the structural features of the identifier based on the position information of the first pixel point in the cable image; the structural features are used to indicate the distance between the identifiers.

[0007] In some embodiments, determining the authenticity information of the cable based on the structural features and a pre-stored Industrial Internet identifier includes: determining the configuration information corresponding to the cable from a database based on the Industrial Internet identifier; determining the difference between the identifier feature indicated by the configuration information and the structural feature; if the difference meets a preset tolerance condition, the authenticity information indicates that the cable is a qualified product; if the difference does not meet the preset tolerance condition, the authenticity information indicates that the cable is a non-qualified product.

[0008] In some embodiments, when the authenticity information indicates that the cable is a qualified product, outputting the traceability information of the cable based on the Industrial Internet identifier includes: outputting the authenticity information of the cable; parsing the Industrial Internet identifier to obtain the raw material information, production information, quality inspection information, and logistics information of the cable; encapsulating the raw material information, production information, quality inspection information, and logistics information of the cable into traceability information based on a preset encapsulation format, and outputting the traceability information.

[0009] In some embodiments, the method further includes: when the authenticity information indicates that the cable is a defective product, encapsulating the raw material information, production information, quality inspection information and logistics information of the cable into risk warning information based on a preset encapsulation format, and outputting the risk warning information.

[0010] In some embodiments, the method further includes: acquiring training images corresponding to different cables according to a preset sampling period; determining training labels for the training images based on the cable identifiers in the training images; performing feature extraction on the training images using the feature extraction model to obtain predicted labels for the cables in the training images; the predicted labels are used to indicate the authenticity information of the cables in the training images predicted by the feature extraction model; updating the feature extraction model based on the difference between the training labels and the predicted labels; stopping the update of the feature extraction model when the difference meets a preset termination condition, and obtaining an updated feature extraction model.

[0011] In some embodiments, the method further includes: encoding the production information of the cable according to a preset encoding algorithm to obtain a first code; encoding the distance between the identifiers of the cable according to the encoding algorithm to obtain a second code; determining the first code and the second code as the configuration information of the cable; and binding the configuration information with a preset industrial internet identifier.

[0012] This application embodiment also provides a cable information traceability device, the device comprising: an acquisition module for acquiring a cable image containing the cable; a feature extraction module for extracting features from the cable image using a preset feature extraction model to obtain structural features of identifiers on the cable; a determination module for determining the authenticity information of the cable based on the structural features and a pre-stored industrial internet identifier; and a traceability module for outputting the traceability information of the cable based on the industrial internet identifier when the authenticity information indicates that the cable is a qualified product.

[0013] This application also provides an electronic device, which includes: a memory storing at least one instruction; and a processor executing the instructions stored in the memory to implement the cable information tracing method described above.

[0014] This application also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the cable information tracing method described above.

[0015] As can be seen from the above technical solutions, the embodiments of this application extract features from the non-uniformly varying meter marking characters engraved during the cable production process. Based on the structural features of the meter marking characters, the authenticity of the cable is identified, which can avoid the problems of anti-counterfeiting labels being misused, copied, or tampered with, thereby improving the anti-counterfeiting security level of cable products. The structural features of the cable identifier are determined based on pixel-level edge fitting and spacing measurement, and combined with hierarchical judgment rules to improve the accuracy of identifying counterfeit products, thus improving the accuracy and reliability of anti-counterfeiting verification results. Based on the Industrial Internet Identifier Resolution System, anti-counterfeiting verification and full lifecycle traceability are bound together, thereby establishing a correspondence between Industrial Internet identifiers, meter marking anti-counterfeiting features, and cable entities. This allows for authorized retrieval and legality verification of anti-counterfeiting data through identifier resolution, avoiding the problems of identifier misuse and illegal reuse. Furthermore, after successful anti-counterfeiting verification, the entire lifecycle traceability information of the cable from raw materials, production, quality inspection, logistics to delivery can be obtained, thereby improving the credibility of the traceability data. Attached Figure Description

[0016] Figure 1 This is an application scenario diagram of a cable information tracing method provided in an embodiment of this application.

[0017] Figure 2 This is a flowchart of a cable information tracing method provided in an embodiment of this application.

[0018] Figure 3 This is a flowchart of a method for determining the structural features of an identifier according to an embodiment of this application.

[0019] Figure 4 This is a flowchart of a method for determining the authenticity of a cable according to an embodiment of this application.

[0020] Figure 5 This is a flowchart of a method for tracing the source information of an output cable provided in an embodiment of this application.

[0021] Figure 6 This is a flowchart of a method for training a feature extraction model provided in an embodiment of this application.

[0022] Figure 7 This is a flowchart of a method for binding configuration information and industrial internet identifiers according to an embodiment of this application.

[0023] Figure 8 This is a functional block diagram of a cable information tracing device provided in one embodiment of this application.

[0024] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] To better understand the purpose, features, and advantages of this application, a detailed description of the application is provided below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of this application can be combined with each other. Numerous specific details are set forth in the following description to provide a thorough understanding of this application; the described embodiments are only a part of the embodiments of this application, and not all of them.

[0026] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0028] This application provides a cable information tracing method that can be applied to one or more electronic devices. An electronic device is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0029] Electronic devices can be any electronic product that allows human-computer interaction with a customer, such as personal computers, tablets, smartphones, personal digital assistants (PDAs), game consoles, interactive network television (IPTV), smart wearable devices, etc.

[0030] Electronic devices may also include network devices and / or client devices. The network devices include, but are not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of hosts or network servers.

[0031] The networks in which electronic devices are located include, but are not limited to, the Internet, wide area networks, metropolitan area networks, local area networks, and virtual private networks (VPNs).

[0032] like Figure 1 As shown, the cable information traceability method provided in this application can be applied to an electronic device 100, which is communicatively connected to a terminal device 200 and a database 300. The terminal device 200 can be any device with image acquisition capabilities; the database 300 can be used to store image data of the cable and configuration information corresponding to the cable's Industrial Internet identifier.

[0033] In this application, electronic device 100 acquires cable images, including those of the cable, sent by terminal device 200 in real time. Electronic device 100 uses a preset feature extraction model to extract features from the cable image, obtaining the structural features of identifiers on the cable. These identifiers can be meter markings pre-engraved on the cable's plastic sheath, and the spacing between different meter markings can be used to indicate the cable's identification information.

[0034] In this application, to determine whether a cable is a genuine and qualified product, the electronic device 100 can determine the authenticity of the cable based on its structural features and the Industrial Internet identifiers pre-stored in the database 300. Specifically, if the difference between the identifier features indicated by the configuration information associated with the Industrial Internet identifier and the structural features meets the tolerance conditions, the cable is determined to be an unqualified product; if the difference between the identifier features indicated by the configuration information associated with the Industrial Internet identifier and the structural features does not meet the tolerance conditions, the cable is determined to be a non-qualified product.

[0035] If the authenticity information indicates that the cable is a qualified product, the electronic device 100 also outputs the cable's traceability information based on the Industrial Internet identifier. This enables full-process traceability of cable-related information.

[0036] like Figure 2 The diagram shown is a flowchart of a cable information tracing method according to an embodiment of this application. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The cable information tracing method provided in this embodiment includes the following steps.

[0037] S20, Obtain a cable image including the cable.

[0038] In one embodiment of this application, during the process of identifying the authenticity of a cable, an electronic device can acquire an image of the cable, and the authenticity of the cable or the quality of the cable can be determined based on the visual information in the cable image. The electronic device includes, but is not limited to, smart terminals with image acquisition capabilities such as smartphones, tablets, and industrial handheld devices.

[0039] Specifically, users scan the Industrial Internet identifier corresponding to the cable (e.g., the QR code on the cable's certificate of conformity) using electronic devices, and access the preset anti-counterfeiting identification module based on the encrypted address corresponding to the Industrial Internet identifier to complete the secure start of the verification process. The lightweight AI anti-counterfeiting identification module is an edge-side inference module compiled based on TensorFlow Lite and ONNX Runtime, which can complete the initial image processing locally on the terminal device without relying on cloud computing power, and can also be adapted to various operating systems.

[0040] Specifically, when collecting images of the cable meter marking area, users can point their terminal device's camera at the cable surface with a preset number of meter markings on the visual guidance box on the anti-counterfeiting verification page, triggering continuous shooting or short frame video recording to obtain the original cable image containing at least 3 sets of continuous meter marking characters. The preset number of meters is dynamically set according to the cable model. For example, the preset number of meters for low-voltage power cables is 3 meters, and the preset number of meters for medium- and high-voltage cables is 5 meters, ensuring that the collected images contain complete non-uniform spacing sequence segments, providing sufficient data for subsequent feature comparison.

[0041] In one embodiment of this application, an anti-counterfeiting identification module is used to perform standardized preprocessing on the acquired cable images, thereby improving the quality of the cable images and obtaining standardized cable images. Specifically, the standardization processing of the cable images includes any one or more combinations of the following: perspective transformation algorithm is used to correct the viewing angle of the tilted image, restoring the frontal plane image of the cable meter mark area; adaptive median filtering algorithm is used to denoise the image, eliminating environmental noise and light spot interference during the shooting process; contrast enhancement algorithm is used to enhance the image contrast, highlighting the edge contours of the meter mark characters and the cable sheath; and bilinear interpolation algorithm is used to normalize the resolution of the image, outputting a standardized cable image.

[0042] For example, before using cables for construction, a user can use a terminal device (e.g., a smartphone) to scan the certificate QR code on the cable reel's nameplate. This prompts the user to display visual guidance prompting them to collect an image of the meter marking area on the cable surface. After obtaining a cable image containing multiple sets of meter marking characters using the terminal device, the image can be sent to an electronic device for preprocessing. For instance, perspective correction can be performed to eliminate tilted viewing angles during shooting, filtering can remove light spot interference from on-site construction lighting, and the contrast between the meter marking characters and the cable itself can be enhanced, ultimately outputting a standardized cable image.

[0043] S21, use a preset feature extraction model to extract features from the cable image to obtain the structural features of the identifier on the cable.

[0044] In one embodiment of this application, the electronic device may invoke a pre-trained feature extraction model to locate identifiers (e.g., meter markers) in a cable image and extract structural features based on the spacing between the identifiers.

[0045] Specifically, the feature extraction model performs target detection on the input standardized cable image, locates all meter mark character regions in the image through the target detection head, generates the minimum bounding rectangle of each meter mark character, and records the pixel coordinates of the center point of each character box; the instance segmentation network performs pixel-level segmentation on the meter mark characters, removes the background area of ​​the cable sheath, and obtains the precise contour and position information of each meter mark character.

[0046] The feature extraction model can be a deep learning model based on a visual transfer learning architecture, or it can include deep learning models with fine-grained image recognition capabilities, such as residual networks and EfficientNet. Specifically, the input of the feature extraction model is a standardized cable image, and the output is the position coordinates of the meter marker characters and a segmentation mask.

[0047] Based on the pixel calibration results of the cable image, the pixel coordinate distance of the center point of the meter mark character can be converted into the actual physical distance. Specifically, the pixel calibration results are obtained by on-site calibration using the known character height and width of the cable meter mark character, calculating the actual physical size corresponding to a single pixel in the image with a measurement accuracy of 1 micrometer level; the actual physical distance between the center points of adjacent meter mark characters is calculated sequentially to obtain the meter mark character spacing sequence corresponding to the cable image, and auxiliary structural parameters such as character size, tilt angle, and relative position of the meter mark character are extracted at the same time.

[0048] The measured spacing sequence of meter marks can be normalized and combined with auxiliary structural parameters. Through the feature encoding layer of the feature extraction model, a fixed-dimensional structural feature vector is generated as the core structural feature of the cable meter mark identifier. The structural feature vector is a 128-dimensional floating-point vector that uniquely represents the microscopic non-uniform spacing characteristics of the cable meter mark area.

[0049] For example, after receiving a cable image containing multiple sets of meter-mark characters, the bounding rectangles of multiple meter-mark characters are located using the object detection network in the feature extraction model, and the pixel coordinates of the center point of each character box are recorded; the pixel equivalent of the image (e.g., 10 micrometers / pixel) is determined by using the known character height of the meter-mark characters (e.g., 5 mm); the pixel distance between the center points of adjacent characters is calculated sequentially to obtain the actual physical spacing sequence (e.g., 20.118 mm, 19.916 mm, 20.149 mm); the spacing sequence is normalized and encoded to generate a structural feature vector, which serves as the core structural feature of the cable identifier.

[0050] In one embodiment of this application, a specific method for extracting features from the cable image using a preset feature extraction model to obtain the structural features of identifiers on the cable can be found in [link to relevant documentation]. Figure 3 The corresponding detailed explanation.

[0051] S22, Based on the structural features and the pre-stored industrial internet identifier, determine the authenticity information of the cable.

[0052] In one embodiment of this application, in order to determine the authenticity of a cable, an encrypted verification method can be used to perform a double comparison of the cable's authenticity, thereby realizing a hierarchical judgment logic for the authenticity of the cable, avoiding problems such as identification fraud, feature tampering, and misjudgment or omission. In this way, the authenticity of the cable can be accurately determined by using the industrial internet identifier as an index and the structural features as the core basis.

[0053] Specifically, the system receives encrypted identification information uploaded by the terminal, decodes the industrial internet identifier carried by the QR code, and connects to the national industrial internet identifier resolution secondary node through a standardized interface to conduct multi-level legality verification: checking whether the identifier is a globally unique and valid code, whether it is within the validity period, whether it belongs to the manufacturer's authorized segment, whether it has completed filing and certification, and whether there are any records of loss, cancellation, or misuse, excluding invalid identifiers, forged identifiers, and expired identifiers. If the identifier verification fails, the process is terminated directly, and an invalid identifier prompt is returned to the terminal; if the verification passes, the system proceeds to the baseline feature retrieval stage.

[0054] After the identifier verification is successful, a data access request can be initiated through the permission verification program. After encryption and authentication, the configuration information uniquely bound to the industrial internet identifier is retrieved from the feature database encrypted with national cryptographic algorithms. This includes: meter mark character reference spacing sequence, micro offset parameters, structural feature reference vector, allowed manufacturing tolerance threshold, and feature similarity judgment threshold. The configuration information is readable but not tamper-proof, and the entire retrieval process is logged, generating a call log that is stored in the platform backend.

[0055] In one embodiment of this application, a dual-condition simultaneous compliance judgment method can be adopted, combining production tolerances and shooting errors to set a reasonable tolerance range, strictly distinguishing between three categories of results: qualified genuine products, counterfeit and unqualified products, and suspicious products awaiting review. A dual verification mode of "numerical point-by-point comparison + vector similarity comparison" can be adopted to avoid judgment errors caused by single comparison. For example, based on the precise comparison of spacing values, the measured spacing sequence of adjacent spacing of meter mark characters can be compared with the benchmark spacing sequence one by one, and the absolute error value of each group of spacing can be calculated to determine whether the error is within the preset tolerance range (e.g., within 20 micrometers), covering the reasonable errors caused by production processing and image acquisition; feature vector similarity comparison can also be used, and the extracted 128-dimensional structural feature vector can be compared with the benchmark feature vector to calculate the cosine similarity, quantifying the fit between the two sets of features, and the preset similarity qualification threshold can be 0.95.

[0056] Specifically, the rules and quantitative standards for judging the authenticity of cables are as follows: The criteria for determining whether a cable is a qualified product include: the absolute error between the measured spacing of adjacent meter marks and the reference spacing sequence is ≤ ±20 micrometers, and no set exceeds the manufacturing tolerance range; the cosine similarity between the measured structural feature vector and the reference feature vector is ≥ 0.95, indicating a high degree of matching between the microscopic anti-counterfeiting features. If the above conditions are met, the cable can be determined to be an original, genuine product, and the anti-counterfeiting features have not been tampered with or replicated.

[0057] The criteria for determining whether a cable is a counterfeit and / or substandard product include any of the following: if any set of meter mark spacing errors is greater than ±20 micrometers, exceeding the reasonable tolerance range, it proves that the meter mark anti-counterfeiting features are counterfeit; if the cosine similarity of the feature vector is less than 0.95, the microstructure features do not match the original manufacturer's benchmark, which is a counterfeit feature; if the marking is legal but the features do not match at all, it is determined to be a counterfeit product that misappropriates the marking.

[0058] In one embodiment of this application, the rule for determining suspicious products to be reviewed is as follows: a buffer judgment is set only for critical situations to exclude anomalies not caused by counterfeiting. If only a single group of spacing errors slightly exceeds the standard (error between ±20 micrometers and ±25 micrometers), and the cosine similarity of the feature vector is in the range of 0.90 to 0.95, without obvious counterfeiting characteristics, it is judged as a suspicious product to be reviewed. Such situations are mostly caused by cable surface wear, stains, or shooting angle deviations. They are not directly judged as counterfeit, but trigger the manual review channel. The manufacturer checks the production records and conducts on-site re-inspection before issuing a final conclusion.

[0059] In one embodiment of this application, the verified identification information, feature comparison data, judgment result, timestamp, and terminal information can be encrypted and archived, and simultaneously uploaded to the Industrial Internet Identifier Resolution Node for evidence storage, thereby ensuring the traceability of the verification process. The judgment result can also be sent to the user terminal through a preset encrypted channel (e.g., HTTPS channel). Specifically, if the cable is genuine, the judgment result can include a verification number; if the cable is not counterfeit, the judgment result can include risk warnings and rights protection prompts.

[0060] For example, the industrial internet identifier obtained by parsing the electronic device can be "VAA.123456 / ZT202405001". This identifier indicates that the corresponding configuration information has been verified and confirmed to be legal and valid within the validity period. The configuration information retrieved based on this identifier can be used to indicate that the pre-stored reference spacing sequence corresponding to this identifier is [20.120mm, 19.915mm, 20.150mm], the tolerance can be ±20 micrometers, and the similarity threshold can be 0.95. The measured spacing sequence [20.118mm, 19.916mm, 20.149mm] is compared group by group, and the maximum error is only 2 micrometers, which meets the tolerance requirements. The calculated cosine similarity of the feature vector is 0.992, which far exceeds the qualified threshold. It can be determined that the cable is a qualified genuine product, and the verification result is issued and a unique verification number is generated. If the measured spacing sequence is 20.050mm, 20.020mm, and 20.030mm, the error is far beyond the tolerance range, and the similarity is only 0.62, then it is directly judged as a counterfeit product, a risk warning is sent, and abnormal verification data is recorded at the same time.

[0061] In one embodiment of this application, the specific method for determining the authenticity of the cable based on the structural features and pre-stored industrial internet identifiers can be found in [link to relevant documentation]. Figure 4 The corresponding detailed explanation.

[0062] S23, if the authenticity information indicates that the cable is a qualified product, output the traceability information of the cable based on the industrial internet identifier.

[0063] In one embodiment of this application, after determining that the cable is a qualified product, the full life cycle traceability information of the cable corresponding to the industrial internet identifier can be obtained by connecting to the industrial internet identifier in the electronic device through the full life cycle data interface, and the traceability information can be visualized through the anti-counterfeiting verification page of the user terminal.

[0064] Specifically, using the cable's industrial internet identifier as a unique index, the system connects to the industrial internet identifier resolution secondary node through a standardized interface to obtain the full lifecycle data corresponding to the identifier, including raw material procurement information, production process data, quality inspection reports, logistics and transportation information, delivery information, and maintenance information.

[0065] The acquired full lifecycle data can be structured and sorted according to the timeline of "raw materials, production, quality inspection, logistics, and delivery" to extract key information nodes. For example, key information nodes may include: raw material batch number, production team, quality inspection certificate number, logistics tracking number, receiving unit, and delivery time, generating a structured traceability information archive.

[0066] In one embodiment of this application, the structured traceability information archive is sent to the anti-counterfeiting verification page of the user terminal through an encrypted channel and displayed visually in the form of a timeline and a details list. At the same time, it supports viewing the original quality inspection report and the encrypted download of the product qualification certificate.

[0067] For example, after determining that the cable is genuine, the entire lifecycle data of the cable is obtained by connecting to the identifier resolution node through the industrial internet identifier "VAA.123456 / ZT202405001". For example, the cable's entire lifecycle data may include: raw materials are batch 202404 oxygen-free copper rods and batch 202403 polyethylene sheath material produced by a certain factory; the production team is the sheathing team, and the production date is May 10, 2024; the quality inspection report number is ZT202405001-JC, and the test results are all qualified; the logistics are a logistics package with waybill number SF20240512001 from a certain logistics company, the shipping date is May 12, 2024, the receiving unit is a certain construction group company, and the delivery date is May 14, 2024. The electronic device generates a structured traceability file based on the above entire lifecycle data in a timeline, distributes it to the user's terminal device, displays it in the form of a visual timeline, and provides an encrypted download portal for the quality inspection report.

[0068] In one embodiment of this application, when the authenticity information indicates that the cable is a qualified product, the specific method for outputting the cable's traceability information based on the Industrial Internet identifier can be found in the following article. Figure 5 The corresponding detailed explanation.

[0069] In one embodiment of this application, the method further includes: when the authenticity information indicates that the cable is a defective product, encapsulating the raw material information, production information, quality inspection information and logistics information of the cable into risk warning information based on a preset encapsulation format, and outputting the risk warning information.

[0070] If the product is found to be substandard due to counterfeit information, a structured traceability information file will be sent to the anti-counterfeiting verification page on the user's terminal through an encrypted channel. Risk warning information will be generated in the form of a timeline and a details list, without displaying any traceability information to prevent the leakage of core product production data.

[0071] As can be seen from the above technical solutions, the embodiments of this application extract features from the non-uniformly varying meter marking characters engraved during the cable production process. Based on the structural features of the meter marking characters, the authenticity of the cable is identified, which can avoid the problems of anti-counterfeiting labels being misused, copied, or tampered with, thereby improving the anti-counterfeiting security level of cable products. The structural features of the cable identifier are determined based on pixel-level edge fitting and spacing measurement, and combined with hierarchical judgment rules to improve the accuracy of identifying counterfeit products, thus improving the accuracy and reliability of anti-counterfeiting verification results. Based on the Industrial Internet Identifier Resolution System, anti-counterfeiting verification and full lifecycle traceability are bound together, thereby establishing a correspondence between Industrial Internet identifiers, meter marking anti-counterfeiting features, and cable entities. This allows for authorized retrieval and legality verification of anti-counterfeiting data through identifier resolution, avoiding the problems of identifier misuse and illegal reuse. Furthermore, after successful anti-counterfeiting verification, the entire lifecycle traceability information of the cable from raw materials, production, quality inspection, logistics to delivery can be obtained, thereby improving the credibility of the traceability data.

[0072] like Figure 3 The diagram shown is a flowchart of a method for determining the structural features of an identifier according to an embodiment of this application. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The method for determining the structural features of an identifier provided in this embodiment of the application includes the following steps.

[0073] S30, input the cable image into the preset feature extraction model to determine the corresponding pixel points of the cable in the cable image.

[0074] In one embodiment of this application, a feature extraction model performs target detection on the input standardized cable image and locates the corresponding pixel points of the cable in the cable image based on the target detection layer in the feature extraction model.

[0075] S31, Based on the pixel, determine the first pixel corresponding to the identifier.

[0076] In one embodiment of this application, the identifier region is located based on the target detection layer in the feature extraction model, the minimum bounding rectangle of each identifier is generated, and the pixel coordinates of the center point of each minimum bounding rectangle are determined; the identifier is segmented into pixels by the instance segmentation layer in the feature extraction model, the background area of ​​the cable is removed, and the precise contour and position information of each identifier are obtained, thereby determining the first pixel point corresponding to the identifier.

[0077] S32, based on the position information of the first pixel in the cable image, determine the structural features of the identifier; the structural features are used to indicate the distance between the identifiers.

[0078] In one embodiment of this application, the pixel coordinates of the center point of the meter mark can be converted into the actual physical distance based on the pixel calibration results of the cable image.

[0079] Specifically, the pixel calibration result is obtained by on-site calibration using the known character height and width of the cable meter markings, and the actual physical size corresponding to a single pixel in the image is calculated. For example, the measurement accuracy of any single pixel can be 1 micrometer.

[0080] The actual physical distance between the center points of adjacent meter marker characters is calculated sequentially to obtain the meter marker character spacing sequence corresponding to the cable image. At the same time, auxiliary structural parameters such as character size, tilt angle, and relative position of the meter marker characters are extracted.

[0081] In one embodiment of this application, the measured spacing sequence of meter marker characters can be normalized, and the normalized character spacing can be encoded by the feature encoding layer of the feature extraction model to generate a fixed-dimensional structural feature vector, which serves as the structural feature of the cable identifier. For example, the structural feature can be a 128-dimensional floating-point vector used to characterize the microscopic non-uniform spacing features of the cable identifier.

[0082] like Figure 4 The diagram shown is a flowchart of a method for determining the authenticity of a cable according to an embodiment of this application. The order of steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The method for determining the authenticity of a cable according to an embodiment of this application includes the following steps.

[0083] S40, Based on the Industrial Internet identifier, determine the configuration information corresponding to the cable from the database.

[0084] In one embodiment of this application, the electronic device receives an Industrial Internet Identifier uploaded by a user through a terminal, decodes the encrypted Industrial Internet Identifier, and connects to the national Industrial Internet Identifier Resolution Secondary Node through a standardized interface to conduct multi-level legality verification. For example, it verifies whether the Industrial Internet Identifier is a globally unique and valid code, whether it is within its validity period, whether it belongs to the manufacturer's authorized segment, whether it has completed filing and certification, and whether there are any records of loss, cancellation, or misuse, thereby excluding invalid, counterfeit, or expired identifiers. If the Industrial Internet Identifier verification fails, the process is terminated directly, and an invalid identifier prompt is returned to the terminal.

[0085] If the verification passes, the process proceeds to the baseline feature retrieval stage. Specifically, after the identifier verification is successful, a data retrieval request can be initiated through the permission verification procedure. After encryption and authentication, the configuration information uniquely bound to the industrial internet identifier is retrieved from the feature database encrypted using national cryptographic algorithms. This includes: the meter-marker character baseline spacing sequence, micro-offset parameters, structural feature baseline vector, allowed manufacturing tolerance threshold, and feature similarity judgment threshold. The configuration information is readable but immutable, and the entire retrieval process is logged, generating a retrieval log which is stored in the platform backend.

[0086] S41, determine the difference between the identification feature indicated by the configuration information and the structural feature.

[0087] In one embodiment of this application, a dual-condition simultaneous compliance judgment method can be adopted, combining production tolerances and shooting errors to set a reasonable error tolerance range, strictly distinguishing between three categories of results: qualified genuine products, counterfeit and unqualified products, and suspicious products awaiting review. For example, a dual verification mode of "numerical point-by-point comparison and vector similarity comparison" can be adopted to avoid judgment errors caused by a single comparison. For instance, based on precise comparison of spacing values, the measured sequence of adjacent spacing between meter marker characters can be compared group by group with a benchmark spacing sequence, calculating the absolute error value of each group of spacings, and determining whether the error is within a preset tolerance range (e.g., within 20 micrometers), covering reasonable errors caused by production processing and image acquisition; alternatively, feature vector similarity comparison can be used, calculating the cosine similarity between the extracted 128-dimensional structural feature vector and the benchmark feature vector to quantify the fit between the two sets of features, with a preset similarity pass threshold of 0.95.

[0088] S42, if the difference meets the preset tolerance conditions, the authenticity information indicates that the cable is a qualified product.

[0089] In one embodiment of this application, the criteria for determining whether a cable is a qualified product include: the absolute error between the measured spacing of adjacent meter marks and the reference spacing sequence is ≤ ±20 micrometers, and none of them exceeds the manufacturing tolerance range; the cosine similarity between the measured structural feature vector and the reference feature vector is ≥ 0.95, indicating a high degree of matching between the microscopic anti-counterfeiting features. If the above conditions are met, it can be determined that the cable is an original factory product and that the anti-counterfeiting features have not been tampered with or replicated.

[0090] S43, if the difference does not meet the preset tolerance conditions, the authenticity information indicates that the cable is a defective product.

[0091] In one embodiment of this application, the judgment rule for determining whether a cable is a counterfeit and / or unqualified product includes any one of the following: if any set of meter mark spacing errors is > ±20 micrometers, exceeding the reasonable tolerance range, it proves that the meter mark anti-counterfeiting features are counterfeit; if the feature vector cosine similarity is <0.95, the microstructure features do not match the original manufacturer's benchmark, which is a counterfeit feature; if the marking is legal but the features do not match at all, it is determined to be a counterfeit product that misappropriates the marking.

[0092] like Figure 5 The diagram shown is a flowchart of a method for obtaining traceability information of an output cable according to an embodiment of this application. The order of steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The method for obtaining traceability information of an output cable according to an embodiment of this application includes the following steps.

[0093] S50, output the authenticity information of the cable.

[0094] S51, parse the industrial internet identifier to obtain the raw material information, production information, quality inspection information and logistics information of the cable.

[0095] In one embodiment of this application, the industrial internet identifier of the cable is used as a unique index. The industrial internet identifier resolution secondary node is connected through a standardized interface to obtain the full lifecycle data corresponding to the identifier, including raw material procurement information, production process data, quality inspection reports, logistics and transportation information, delivery information, and maintenance information.

[0096] S52, based on a preset encapsulation format, the raw material information, production information, quality inspection information, and logistics information of the cable are encapsulated into traceability information, and the traceability information is output.

[0097] In one embodiment of this application, the acquired full lifecycle data can be structured, classified and sorted according to the timeline of "raw materials, production, quality inspection, logistics, and delivery," key information nodes can be extracted, and encapsulated into traceability information. For example, key information nodes may include: raw material batch number, production team, quality inspection certificate number, logistics tracking number, receiving unit, and delivery time, generating a structured traceability information archive.

[0098] In one embodiment of this application, in order to improve the performance of the feature extraction model and the accuracy of structural features, the feature extraction model can be trained. For example... Figure 6 The diagram shown is a flowchart of a method for training a feature extraction model according to an embodiment of this application. The order of steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The method for training a feature extraction model according to an embodiment of this application includes the following steps.

[0099] S60 acquires training images corresponding to different cables according to a preset sampling period.

[0100] In one embodiment of this application, training images corresponding to different cables can be acquired based on a preset sampling period to construct an incremental training dataset, and the feature extraction model can be iteratively trained periodically.

[0101] It can also anonymize cable images, extracted structural features, authenticity judgment results, and manual review results in each verification process, remove user privacy information, manually annotate new counterfeit samples and edge case samples, and construct an incremental training dataset; among them, new counterfeit samples include high-precision counterfeit cable samples with imitation inkjet coding and copied meter samples, and edge cases include genuine samples with manufacturing tolerance critical values ​​and verification samples with extreme shooting environments.

[0102] S61, determine the training label of the training image based on the identification of the cable in the training image.

[0103] In one embodiment of this application, training labels are used to indicate the category of cables in training images. For example, training labels may include qualified, unqualified, or pending confirmation.

[0104] S62, the feature extraction model is used to extract features from the training image to obtain the predicted label of the cable in the training image; the predicted label is used to indicate the authenticity information of the cable in the training image predicted by the feature extraction model.

[0105] In one embodiment of this application, a pre-trained feature extraction model is used as the base weight. An incremental learning approach is adopted, and the feature extraction model is iteratively trained using training images in the incremental training dataset. This optimizes the character positioning accuracy, spacing measurement accuracy, and anti-environment interference capability of the feature extraction model, thereby reducing the false negative rate of counterfeit samples and the false positive rate of genuine samples.

[0106] The feature extraction model takes training images as input and outputs predicted labels corresponding to those training images. These predicted labels can be used to indicate the authenticity of cables in the training images predicted by the feature extraction model.

[0107] S63, based on the difference between the training label and the predicted label, update the feature extraction model. When the difference meets the preset termination condition, stop updating the feature extraction model and obtain the updated feature extraction model.

[0108] In one embodiment of this application, the difference between the training label and the predicted label can be used to indicate the accuracy of the predicted label predicted by the feature extraction model. If the difference is large, it indicates low accuracy of the predicted label, and the feature extraction model can be continuously updated until the difference between the training label and the predicted label meets a preset termination condition, at which point the feature extraction model updates are stopped, resulting in an updated feature extraction model.

[0109] The termination condition can be that the difference between the training label and the predicted label is less than or equal to a preset difference threshold.

[0110] In one embodiment of this application, the iteratively optimized model can also be released in a gray-scale manner, and the effect can be verified by selecting a portion of the pilot batch of cable verification services. The recognition accuracy and recall rate of the model can be statistically analyzed. If the accuracy reaches the preset index (e.g., ≥99.9%), then the model can be released in full to replace the original model; if the index is not reached, then the model can be retrained and optimized.

[0111] For example, 12,000 anonymized verification samples can be collected within a preset testing period, including 50 new high-precision counterfeit cable samples and 200 edge case samples from extreme shooting environments. After manual annotation by quality inspectors, an incremental training dataset is constructed. Based on the original feature extraction model as the weight, incremental training is performed to optimize the model's feature extraction capabilities for low-light and blurred images, thereby improving the recognition accuracy of new counterfeit samples.

[0112] like Figure 7 The diagram shown is a flowchart of a method for binding configuration information and an industrial internet identifier according to an embodiment of this application. The order of steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The method for binding configuration information and an industrial internet identifier provided in this embodiment includes the following steps.

[0113] S70, the production information of the cable is encoded according to a preset encoding algorithm to obtain the first code.

[0114] In one embodiment of this application, the production batch, model specifications, production line speed per meter, and extrusion process parameters of the cable can be acquired simultaneously during the cable production process. In the online coding process after the cable sheath is extruded but before cooling and curing, the physical spacing between adjacent meter marks printed by the coding equipment can be dynamically adjusted according to the preset encryption rules for that batch of cables. This physical spacing is a micrometer-level non-uniform variation parameter, forming a unique intrinsic anti-counterfeiting structural feature for that batch and that meter segment of cable.

[0115] The meter marking characters include a combination of characters indicating the cable model, specifications, and consecutive meter lengths. The preset encoding algorithm can be a pseudo-random number generation rule based on national cryptographic algorithms, using the industrial internet identifier of the batch of cables as the key to generate the spacing offset of adjacent meter marking characters. The closed-loop control accuracy of the spacing offset is ±5 micrometers, the base spacing between adjacent meter marking characters is 10mm-50mm, and the non-uniform offset range is ±0.5%-±2% of the base spacing, ensuring that the offset is an indistinguishable microscopic feature that cannot be accurately replicated by conventional copying / inkjet printing equipment.

[0116] S71, the distance between the identifiers of the cable is encoded according to the encoding algorithm to obtain the second encoding.

[0117] In one embodiment of this application, the generated meter mark character spacing parameters, non-uniform offset sequence, batch information, model specifications, and production process parameters are synchronized to an electronic device, and the distance between the identifiers of the cable is encoded according to the encoding algorithm to obtain a second code.

[0118] S72, the first code and the second code are determined as the configuration information of the cable, and the configuration information is bound to a preset industrial internet identifier.

[0119] In one embodiment of this application, a globally unique Industrial Internet identifier can be assigned to the batch of cables. The first code and the second code are determined as the configuration information of the cables, and the configuration information is bound to the preset Industrial Internet identifier. Specifically, the inherent anti-counterfeiting structural features, production information, and quality inspection information can be uniquely bound to the Industrial Internet identifier and encrypted and stored in the platform's feature database.

[0120] Please see Figure 8 , Figure 8This is a functional block diagram of a cable information tracing device according to an embodiment of this application. The cable information tracing device 81 includes an acquisition module 810, a feature extraction module 811, a determination module 812, and a tracing module 813. The module / unit referred to in this application is a series of computer-readable instruction segments that can be executed by the processor 13 and perform a fixed function, stored in the memory 12. In this embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0121] The acquisition module 810 is used to acquire a cable image containing the cable.

[0122] The feature extraction module 811 is used to extract features from the cable image using a preset feature extraction model to obtain the structural features of the identifier on the cable.

[0123] The determining module 812 is used to determine the authenticity information of the cable based on the structural features and the pre-stored industrial internet identifier.

[0124] The traceability module 813 is used to output the traceability information of the cable based on the industrial internet identifier when the authenticity information indicates that the cable is a qualified product.

[0125] In some embodiments, the feature extraction module 811 uses a preset feature extraction model to extract features from the cable image to obtain structural features of identifiers on the cable, including: inputting the cable image into the preset feature extraction model to determine the pixel point corresponding to the cable in the cable image; determining a first pixel point corresponding to the identifier based on the pixel point; determining the structural features of the identifier based on the position information of the first pixel point in the cable image; the structural features are used to indicate the distance between the identifiers.

[0126] In some embodiments, the determining module 812 determines the authenticity information of the cable based on the structural features and a pre-stored industrial internet identifier, including: determining the configuration information corresponding to the cable from the database based on the industrial internet identifier; determining the difference between the identifier feature indicated by the configuration information and the structural feature; if the difference meets a preset tolerance condition, the authenticity information indicates that the cable is a qualified product; if the difference does not meet the preset tolerance condition, the authenticity information indicates that the cable is a non-qualified product.

[0127] In some embodiments, when the authenticity information indicates that the cable is a qualified product, the traceability module 813 outputs the traceability information of the cable based on the industrial internet identifier, including: outputting the authenticity information of the cable; parsing the industrial internet identifier to obtain the raw material information, production information, quality inspection information and logistics information of the cable; encapsulating the raw material information, production information, quality inspection information and logistics information of the cable into traceability information based on a preset encapsulation format, and outputting the traceability information.

[0128] In some embodiments, the traceability module 813 is further configured to, when the authenticity information indicates that the cable is a defective product, encapsulate the raw material information, production information, quality inspection information and logistics information of the cable into risk warning information based on a preset encapsulation format, and output the risk warning information.

[0129] In some embodiments, the feature extraction module 811 is further configured to acquire training images corresponding to different cables according to a preset sampling period; determine the training label of the training image based on the cable identifier in the training image; perform feature extraction on the training image using the feature extraction model to obtain the predicted label of the cable in the training image; the predicted label is used to indicate the authenticity information of the cable in the training image predicted by the feature extraction model; update the feature extraction model based on the difference between the training label and the predicted label; and stop updating the feature extraction model when the difference meets a preset termination condition to obtain the updated feature extraction model.

[0130] In some embodiments, the traceability module 813 is further configured to encode the production information of the cable according to a preset encoding algorithm to obtain a first code; encode the distance between the identifiers of the cable according to the encoding algorithm to obtain a second code; determine the first code and the second code as the configuration information of the cable; and bind the configuration information with a preset industrial internet identifier.

[0131] Please see Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 100 includes a memory 12 and a processor 13. The memory 12 is used to store computer-readable instructions, and the processor 13 executes the computer-readable instructions stored in the memory to implement a cable information tracing method as described in any of the above embodiments.

[0132] In one embodiment of this application, the electronic device 100 further includes a bus and a computer program stored in the memory 12 and executable on the processor 13, such as a cable information tracing program.

[0133] Figure 9Only an electronic device 100 with memory 12 and processor 13 is shown; those skilled in the art will understand that... Figure 9 The structure shown does not constitute a limitation on the electronic device 100, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0134] Combination Figure 2 The memory 12 in the electronic device 100 stores multiple computer-readable instructions to implement a cable information traceability method. The processor 13 can execute the multiple instructions to achieve: acquiring a cable image containing the cable; extracting features from the cable image using a preset feature extraction model to obtain the structural features of the identifier on the cable; determining the authenticity information of the cable based on the structural features and a pre-stored industrial internet identifier; and outputting the traceability information of the cable based on the industrial internet identifier when the authenticity information indicates that the cable is a qualified product.

[0135] Specifically, the processor 13's implementation method for the above instructions can be found in [reference needed]. Figure 2 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0136] Those skilled in the art will understand that the schematic diagram is merely an example of the electronic device 100 and does not constitute a limitation on the electronic device 100. The electronic device 100 may be a bus-type structure or a star-type structure. The electronic device 100 may also include more or fewer other hardware or software than shown in the diagram, or different component arrangements. For example, the electronic device 100 may also include input / output devices, network access devices, etc.

[0137] It should be noted that electronic device 100 is only an example. Other existing or future electronic products that are suitable for this application should also be included within the scope of protection of this application and are incorporated herein by reference.

[0138] The memory 12 includes at least one type of readable storage medium, which can be non-volatile or volatile. The readable storage medium includes flash memory, portable hard drives, multimedia cards, card-type memory (e.g., SD or DX memory), magnetic storage, magnetic disks, optical disks, etc. In some embodiments, the memory 12 can be an internal storage unit of the electronic device 100, such as the portable hard drive of the electronic device 100. In other embodiments, the memory 12 can also be an external storage device of the electronic device 100, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 100. The memory 12 can be used not only to store application software and various types of data installed on the electronic device 100, such as the code of a cable information tracing program, but also to temporarily store data that has been output or will be output.

[0139] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits packaged with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 13 is the control unit of the electronic device 100, connecting to various components of the electronic device 100 via various interfaces and lines. It executes programs or modules stored in the memory 12 (e.g., executing a cable information tracing program) and calls data stored in the memory 12 to perform various functions of the electronic device 100 and process data.

[0140] The processor 13 executes the operating system of the electronic device 100 and various installed applications. The processor 13 executes the applications to implement the steps in each of the above embodiments of the cable information tracing method, for example... Figure 2 The steps are shown.

[0141] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to complete this application. The one or more modules / units may be a series of computer-readable instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device 100. For example, the computer program may be divided into an acquisition module 810, a feature extraction module 811, a determination module 812, and a tracing module 813.

[0142] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium. This software functional module, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, computer equipment, or network device, etc.) or processor to execute portions of the cable information tracing method described in the various embodiments of this application.

[0143] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware devices. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above.

[0144] The computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory, and other memory.

[0145] Furthermore, the computer-readable storage medium may primarily include a stored program area and a stored data area, wherein the stored program area may store the operating system, an application program required for at least one function, etc.; and the stored data area may store data created based on the use of blockchain nodes, etc.

[0146] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, in... Figure 9 The symbol is represented by only one arrow, but this does not indicate that there is only one bus or one type of bus. The bus is configured to enable communication between the memory 12 and at least one processor 13, etc.

[0147] This application also provides a computer-readable storage medium (not shown), which stores computer-readable instructions that are executed by a processor in an electronic device to implement a cable information tracing method as described in any of the above embodiments.

[0148] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0149] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0150] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0151] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices described in the specification may also be implemented by a single unit or device through software or hardware. Terms such as "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application.

Claims

1. A method for tracing cable information, characterized in that, The method includes: Obtain a cable image containing the cable; The cable image is used to extract features using a preset feature extraction model to obtain the structural features of the identifiers on the cable; Based on the structural features and the pre-stored industrial internet identifier, the authenticity of the cable is determined; If the authenticity information indicates that the cable is a qualified product, the traceability information of the cable is output based on the industrial internet identifier.

2. The cable information tracing method as described in claim 1, characterized in that, The step of extracting features from the cable image using a preset feature extraction model to obtain the structural features of identifiers on the cable includes: The cable image is input into the preset feature extraction model to determine the pixel points corresponding to the cable in the cable image; Based on the pixel, determine the first pixel corresponding to the identifier; Based on the position information of the first pixel in the cable image, the structural features of the identifier are determined; the structural features are used to indicate the distance between the identifiers.

3. The cable information traceability method as described in claim 1, characterized in that, The process of determining the authenticity of the cable based on the structural features and pre-stored industrial internet identifiers includes: Based on the industrial internet identifier, the configuration information corresponding to the cable is determined from the database; Determine the difference between the identification features indicated by the configuration information and the structural features; If the difference meets the preset tolerance conditions, the authenticity information indicates that the cable is a qualified product; If the difference does not meet the preset tolerance conditions, the authenticity information indicates that the cable is a defective product.

4. The cable information tracing method as described in claim 1, characterized in that, When the authenticity information indicates that the cable is a qualified product, based on the industrial internet identifier, the traceability information of the cable is output, including: Output the authenticity information of the cable; The industrial internet identifier is parsed to obtain the raw material information, production information, quality inspection information, and logistics information of the cable; Based on a preset encapsulation format, the raw material information, production information, quality inspection information, and logistics information of the cable are encapsulated into traceability information, and the traceability information is output.

5. The cable information traceability method as described in claim 4, characterized in that, The method further includes: If the authenticity information indicates that the cable is a defective product, the raw material information, production information, quality inspection information, and logistics information of the cable are packaged into risk warning information based on a preset packaging format, and the risk warning information is output.

6. The cable information tracing method as described in claim 1, characterized in that, The method further includes: Training images corresponding to different cables are obtained according to a preset sampling period; The training labels of the training images are determined based on the identification of cables in the training images; The feature extraction model is used to extract features from the training image to obtain a predicted label for the cable in the training image; the predicted label is used to indicate the authenticity information of the cable in the training image predicted by the feature extraction model. Based on the difference between the training label and the predicted label, the feature extraction model is updated. When the difference meets a preset termination condition, the update of the feature extraction model is stopped, and the updated feature extraction model is obtained.

7. The cable information tracing method as described in claim 1, characterized in that, The method further includes: The production information of the cable is encoded according to a preset encoding algorithm to obtain a first code; The distance between the identifiers of the cable is encoded according to the encoding algorithm to obtain a second code; The first code and the second code are determined as the configuration information of the cable, and the configuration information is bound to a preset industrial internet identifier.

8. A cable information traceability device, characterized in that, The device includes: The acquisition module is used to acquire cable images containing the cable. The feature extraction module is used to extract features from the cable image using a preset feature extraction model to obtain the structural features of the identifiers on the cable; The determination module is used to determine the authenticity of the cable based on the structural features and pre-stored industrial internet identifiers. The traceability module is used to output the traceability information of the cable based on the industrial internet identifier when the authenticity information indicates that the cable is a qualified product.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory, the processor being used to implement the cable information tracing method as described in any one of claims 1 to 7 when executing a computer program stored in the memory.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which is executed by a processor in an electronic device to implement the cable information tracing method as described in any one of claims 1 to 7.

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