Detection Method and System for High-Frequency NFC Tags of Printing Power Supplies

Abstract

The present invention relates to the field of NFC tag technology, and in particular to a method and system for detecting high-frequency NFC tags of printed power supplies. The method comprises: acquiring a physical image of an NFC tag to be detected, and obtaining a physical information set based on the physical image; constructing a physical feature detection model based on the physical features of the NFC tag; inputting the physical information set into the physical feature detection model to obtain a physical feature detection result; acquiring verification digital information of the NFC tag to be detected, and obtaining a digital information set based on the verification digital information; constructing a digital feature detection model based on expected digital information of the NFC tag, wherein the expected digital information corresponds one-to-one with the verification digital information in the digital information set; and inputting the physical feature detection result and the digital feature detection result into an NFC tag evaluation space to obtain a comprehensive detection result. Through the present invention, the quality and reliability of NFC tags are effectively improved, production inspection of NFC tags is strengthened, and counterfeit and inferior products are prevented from entering the market.

Description

Technical Field

[0001] The present invention relates to the technical field of NFC tags, and in particular to a detection method and system for high-frequency NFC tags of printed power supplies. Background Art

[0002] Printed power supplies (PPs) are a type of power supply that utilizes a printing process to create battery materials and circuit structures on a flexible substrate. They offer advantages such as lightness, flexibility, and low cost, making them suitable for use in a variety of electronic devices and smart tags. With the increasing prevalence of counterfeit and counterfeit goods, anti-counterfeiting technology has become increasingly important. Against this backdrop, detection technology for high-frequency NFC tags used in PPs has emerged.

[0003] Currently, anti-counterfeiting NFC tags are widely used in many fields, such as product anti-counterfeiting, drug safety, high-end consumer goods, identity authentication and cultural relics protection. However, NFC tags are an important basis for identifying goods, drugs, identities, etc., but lack production testing. Once quality problems occur, it will lead to a series of serious problems such as counterfeit products entering the market, damage to brand reputation, and opaque supply chain.

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

[0005] The present invention provides a detection method and system method for a high-frequency NFC tag of a printed power supply, which can effectively solve the problems in the background technology.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] Acquire a physical image of the NFC tag to be detected, and obtain a physical information set based on the physical image;

[0008] Based on the physical characteristics of the NFC tag, a physical feature detection model is constructed;

[0009] Inputting the physical information set into the physical feature detection model to obtain a physical feature detection result;

[0010] Collect and obtain verification digital information of the NFC tag to be detected, and obtain a digital information set based on the verification digital information;

[0011] Constructing a digital feature detection model based on the expected digital information of the NFC tag, wherein the expected digital information corresponds one-to-one with the verification digital information in the digital information set;

[0012] The physical feature detection result and the digital feature detection result are input into the NFC tag evaluation space to obtain a comprehensive detection result.

[0013] Furthermore, the constructing of the physical feature detection model includes:

[0014] Obtaining the size, thickness, and edge burr degree of a standardized NFC tag, where the size, thickness, and edge burr degree are appearance characteristics;

[0015] Obtaining printing quality, reflectivity, and intensity information of the standardized NFC tag, where the printing quality, reflectivity, and intensity information are characterization indicators;

[0016] wherein the physical characteristics are obtained according to the appearance characteristics and the characterization index;

[0017] Setting a physical fluctuation threshold according to the physical characteristics, wherein the physical characteristics of the NFC tag are within the physical fluctuation threshold;

[0018] A physical feature detection model is constructed according to the physical fluctuation threshold.

[0019] Furthermore, the constructing of the digital feature detection model includes:

[0020] Obtaining expected chip information and expected data information from the NFC tag;

[0021] Obtaining expected digital information according to the chip information and the expected data information, wherein the expected chip information and the expected data information respectively correspond one-to-one to the verification digital information in the digital information set;

[0022] A digital feature detection model is constructed according to the expected digital information of the NFC tag.

[0023] Furthermore, obtaining the comprehensive test results includes:

[0024] Select a matching neural network structure, configure it according to the required input and output dimensions, and establish an NFC tag evaluation space;

[0025] Collecting relevant data of NFC tags, training the NFC tag evaluation space using the relevant data, and using a cross-validation method to evaluate the performance of the model;

[0026] The comprehensive detection result is obtained by using the NFC tag evaluation space. Further, the relevant data is pre-processed before training the NFC tag evaluation space with the relevant data.

[0027] Furthermore, the acquisition of verification digital information of the NFC tag to be detected includes:

[0028] Collect chip information of the NFC tag, including function verification, security verification, and trust verification;

[0029] Collecting data information from the NFC tag, the data information including a unique identification code and an encryption key;

[0030] By collecting the chip information and the data information, the verification digital information of the NFC tag to be detected is obtained. Furthermore, a noise reduction process is performed on the physical image of the NFC tag to be detected, and image enhancement is performed after the noise reduction process.

[0031] A method and system for detecting a high-frequency NFC tag of a printed power supply, the system comprising:

[0032] Physical image acquisition module: collects and acquires the physical image of the NFC tag to be detected, and obtains a physical information set based on the physical image;

[0033] Physical feature detection module: constructs a physical feature detection model based on the physical features of the NFC tag, and inputs the physical information set into the physical feature detection model to obtain physical feature detection results;

[0034] Digital information acquisition module: collects and obtains the verification digital information of the NFC tag to be detected, and obtains a digital information set based on the verification digital information;

[0035] Digital feature detection module: constructs a digital feature detection model based on the expected digital information of the NFC tag, and the expected digital information corresponds one-to-one with the verification digital information in the digital information set;

[0036] Comprehensive evaluation module: inputs the physical feature detection result and the digital feature detection result into the NFC tag evaluation space to obtain a comprehensive detection result.

[0037] Furthermore, the system further comprises: an appearance feature acquisition unit for acquiring the size, thickness, and edge burr degree of the standardized NFC tag, wherein the size, thickness, and edge burr degree are appearance features;

[0038] Characterization index acquisition unit: acquires printing quality, reflectivity and intensity information of the standardized NFC tag, wherein the printing quality, reflectivity and intensity information are characterization indicators;

[0039] Wherein, the physical features are obtained by the appearance feature acquisition unit and the characterization index acquisition unit;

[0040] A fluctuation threshold setting unit is configured to set a physical fluctuation threshold according to the physical characteristics, wherein the physical characteristics within the physical fluctuation threshold are those of a qualified NFC tag;

[0041] A physical feature detection model building unit is configured to build a physical feature detection model according to the physical fluctuation threshold.

[0042] Furthermore, the digital feature detection module includes:

[0043] Expected information acquisition unit: obtains expected chip information and expected data information in the NFC tag;

[0044] An expected digital information extraction unit is configured to obtain the expected digital information according to the chip information and the expected data information, wherein the expected chip information and the expected data information correspond one-to-one to the verification digital information in the digital information set;

[0045] A digital feature detection model building unit is configured to build a digital feature detection model according to the expected digital information of the NFC tag.

[0046] The technical solution of the present invention can achieve the following technical effects:

[0047] It effectively improves the quality and reliability of NFC tags, strengthens the production testing of NFC tags, ensures their high quality and high precision production requirements, while also protecting consumer rights, maintaining market order, and promoting the development and innovation of related industries.

[0048] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 A flow chart of a method for detecting a high-frequency NFC tag for a printed power supply;

[0051] Figure 2 A schematic diagram of the process of building a physical feature detection model;

[0052] Figure 3 A flowchart for building a digital feature detection model;

[0053] Figure 4Schematic diagram of the process for obtaining comprehensive test results;

[0054] Figure 5 Schematic diagram of the detection system for high-frequency NFC tags of printed power supplies; DETAILED DESCRIPTION

[0055] 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 only part of the embodiments of the present invention, rather than all the embodiments.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0057] Example 1

[0058] like Figure 1 As shown, a method for detecting a high-frequency NFC tag of a printed power supply includes:

[0059] S100: Acquire a physical image of the NFC tag to be detected, and obtain a physical information set based on the physical image.

[0060] Specifically, capturing a physical image of the NFC tag to be detected typically requires the following steps: First, a device is required to capture the physical image of the NFC tag, and the device parameters are adjusted as needed to obtain a clear and accurate physical image. The captured physical image includes key parameter information derived from the external features, which is then organized into a physical information set.

[0061] S200: Constructing a physical feature detection model based on the physical features of the NFC tag.

[0062] Specifically, the physical characteristics of the NFC tag referred to in this step are standardized or expected external physical characteristics of the NFC tag, and a physical characteristic detection model is constructed based on this. This model is used to evaluate and detect the physical characteristics of produced NFC tags.

[0063] S300: Inputting the physical information set into the physical feature detection model to obtain the physical feature detection result;

[0064] Specifically, the physical information set is converted into a format acceptable to the model, and the processed data is input into the physical feature detection model to obtain physical feature detection results and evaluate the model's performance. It is important to note that the above steps are only general procedures and require adjustment and optimization based on actual conditions during implementation. Furthermore, to ensure the accuracy and reliability of the physical feature detection results, sufficient data preprocessing, feature extraction, and model evaluation are also required.

[0065] S400: Collect and obtain verification digital information of the NFC tag to be detected, and obtain a digital information set according to the verification digital information.

[0066] Typically, this known digital information is a preset verification code or a fixed sequence of numbers. This acquisition process can be performed using a dedicated NFC reader. The acquisition process begins by placing the NFC reader near the NFC tag, maintaining an appropriate distance between the tag and the reader to ensure successful data reading. The program then reads the tag's data and records the verification digital information. This recorded verification digital information is then compared with other known standards to verify the tag's authenticity. Using the obtained verification digital information, the program retrieves the corresponding digital information set from a remote server or local database. This digital information set is compared with the verification digital information. If verification is successful, the NFC tag is considered valid; otherwise, it is invalid. After displaying the verification results, the program closes the NFC tag reader and exits. It is important to note that the specific implementation requires adjustment and optimization based on actual circumstances. Furthermore, when acquiring and processing digital information from NFC tags, data security and privacy protection must be considered.

[0067] S500: Building a digital feature detection model based on the expected digital information of the NFC tag, wherein the expected digital information corresponds one-to-one with the verification digital information in the digital information set;

[0068] Specifically, the purpose of constructing a digital feature detection model is the same as that of constructing a physical feature detection model in step S200. The difference is that the digital feature detection model is constructed for the detection of the digital information features of the NFC tag. Due to the characteristics of the NFC tag itself, the digital information features are dynamic features, and multiple digital parameters are unique, which is an effective identification of the NFC tag. It can be understood that the digital feature detection model is a digital information library established for different NFC tags, and the expected digital information is the standardized data entered into the database. By constructing a digital feature detection model, the accuracy and reliability of the verified digital information in the digital information set can be ensured, the data processing efficiency can be improved, the data analysis capability can be enhanced, and the data security can be improved.

[0069] S600: Input the physical feature detection result and the digital feature detection result into the NFC tag evaluation space to obtain a comprehensive detection result.

[0070] Specifically, the NFC tag evaluation space refers to a set of metrics or indicators used to evaluate NFC tag performance. It represents the range within which NFC tags can be read and written. To obtain a comprehensive test result, it is necessary to fuse the physical feature test results and the digital feature test results. For NFC tag qualification, testing is performed from both the physical features and the verified digital information. That is, both the physical features and the verified digital information must meet the corresponding model requirements. Furthermore, some machine learning algorithms can be used for feature fusion and classification. These algorithms can learn different information from different features and then combine them to generate more accurate comprehensive test results. In short, after obtaining the physical feature and verified digital information test results, more accurate comprehensive test results can be obtained by combining them using appropriate algorithms and techniques.

[0071] The technical solution of the present invention effectively improves the quality and reliability of NFC tags, strengthens the production inspection of NFC tags, ensures their high quality and high precision production requirements, protects consumer rights, maintains market order, and promotes the development and innovation of related industries.

[0072] Further, refer to Figure 2 As shown, building a physical feature detection model includes:

[0073] S210: Acquire the size, thickness, and edge burr degree of the standardized NFC tag, where the size, thickness, and edge burr degree are appearance features;

[0074] Specifically, in the high-frequency NFC tag detection method for printed power supplies, obtaining the physical characteristics of standardized NFC tags, such as size, thickness, and edge burr level, is part of establishing a physical feature detection model. By measuring the NFC tag to be tested, it is determined whether it meets the standardization requirements. Furthermore, the parameters such as size, thickness, and edge burr level of the standardized NFC tag can be used as a benchmark to compare the differences in the physical characteristics of the NFC tag to be tested with those of the standardized NFC tag.

[0075] S220: Acquire printing quality, reflectivity, and intensity information of the standardized NFC tag, where the printing quality, reflectivity, and intensity information are characterization indicators;

[0076] Specifically, during the manufacturing process of high-frequency NFC tags for printed power supplies, printing quality, reflectivity, and intensity information serve as characterization indicators that influence the performance and stability of NFC tags. Printing quality involves aspects such as the detail, clarity, and accuracy of printed materials. For printed circuits or printed labels, the quality of printing can affect their electronic functionality and readability. Reflectivity refers to the degree to which the printed circuit surface reflects incident light, which can affect the brightness and contrast of the image. Intensity information refers to the ability of NFC tags to withstand various physical or environmental factors, including mechanical shock, temperature changes, humidity, and chemicals. Therefore, measuring and analyzing these parameters can help determine the characterization indicators of standardized NFC tags, improve physical characteristics, and be used for subsequent quality testing. By measuring parameters such as printing quality, reflectivity, and intensity of the NFC tags to be tested, it is possible to more comprehensively and accurately determine whether the tags meet the requirements.

[0077] S230: wherein, physical characteristics are obtained according to the appearance characteristics and the characterization index.

[0078] Specifically, the establishment of appearance features and characterization indicators is more comprehensive and accurately reflects the physical characteristics of NFC tags.

[0079] S240: Setting a physical fluctuation threshold based on the physical characteristics. Physical characteristics within the physical fluctuation threshold are considered qualified NFC tags.

[0080] S250: Constructing a physical feature detection model according to the physical fluctuation threshold.

[0081] Specifically, in the actual production process, even NFC tags from the same batch may have differences, and their physical characteristics may fluctuate to a certain extent. Therefore, the mean and standard deviation of the physical characteristics are calculated through statistical methods, and a physical fluctuation threshold is set based on this to determine whether the NFC tag to be tested meets the requirements. If the difference between the physical characteristics of the NFC tag to be tested and the physical fluctuation threshold is within an acceptable range, the tag is considered to meet the physical characteristic requirements; conversely, if the physical characteristic difference exceeds the set threshold, the NFC tag is considered to be unqualified in terms of physical characteristics. Since the physical characteristic detection model is built based on the physical fluctuation threshold, it can quickly and accurately detect the quality and stability of the NFC tag to be tested, greatly shortening the detection time and improving production efficiency.

[0082] Furthermore, if Figure 3 As shown, step S500 of this application includes:

[0083] S510: Obtain expected chip information and expected data information from the NFC tag;

[0084] S520: Obtaining expected digital information according to the chip information and the expected data information, wherein the expected chip information and the expected data information correspond one-to-one with the verification digital information in the digital information set;

[0085] S530: Construct a digital feature detection model according to the expected digital information of the NFC tag.

[0086] Specifically, the expected chip information and expected data information in the NFC tag are obtained, so that the subsequent expected digital information is more accurate, which facilitates the establishment of the subsequent digital feature detection model; the chip information refers to the data stored inside the NFC tag chip, which can be read and verified to ensure the authenticity and legality of the tag; the expected digital information refers to the in-depth acquisition of NFC tag data information, specifically including character strings, numerical values, encrypted hash values and other data types to supplement the verification of the expected digital information of the NFC tag, and the detection and recognition efficiency and speed are improved by establishing the digital feature detection model.

[0087] Furthermore, if Figure 4 As shown, obtaining comprehensive test results also includes:

[0088] S610: Select a matching neural network structure, configure it according to the required input dimension and output dimension, and establish an NFC tag evaluation space;

[0089] S620: Collect relevant data of the NFC tag, train the NFC tag evaluation space based on the relevant data, and use a cross-validation method to evaluate the performance of the model;

[0090] S630: Obtain comprehensive detection results through the NFC tag evaluation space.

[0091] Specifically, selecting a matching neural network structure refers to choosing an appropriate neural network model architecture based on the task requirements and dataset characteristics. This can effectively improve the accuracy and robustness of comprehensive detection. Secondly, configuring according to the required input and output dimensions means determining the input and output dimensions based on the task requirements and selecting the most appropriate neural network model architecture based on these dimensions. Specifically, the input dimension refers to the dimension of the data received by the neural network. Therefore, when selecting a neural network architecture, it is important to consider the correlation and importance of various parameters. In the detection of printed power high-frequency NFC tags, the output dimension is typically a binary classification. Therefore, when selecting a neural network architecture, it is necessary to select an appropriate activation function based on the actual situation. Neural networks require continuous training to optimize model parameters to improve detection accuracy. During the training process, it is necessary to select an appropriate optimization algorithm to update the model. Cross-validation methods can help us test the model's generalization performance, that is, its performance on different datasets, to further improve model performance.

[0092] Furthermore, according to the method for detecting the high-frequency NFC tag of the printed power supply in step S610, the relevant data is pre-processed before the NFC tag evaluation space is trained using the relevant data.

[0093] Specifically, preprocessing NFC tag data before evaluating it in the NFC tag evaluation space involves performing necessary processing and cleaning on the collected NFC tag data before subsequent processing to improve its accuracy and reliability. The goal of preprocessing is to remove noise, redundancy, and irrelevant information, extracting useful features and making subsequent data mining and analysis more accurate and effective. Preprocessing NFC tag data typically includes the following steps: data cleaning, feature extraction, feature selection, and data normalization. Important considerations include avoiding overfitting and paying attention to data distribution.

[0094] Furthermore, according to the detection method of the high-frequency NFC tag of the printed power supply, collecting and obtaining the verification digital information of the NFC tag to be detected includes:

[0095] S410: Collect chip information of the NFC tag, including function verification, security verification, and trust verification;

[0096] S420: Collecting data information from the NFC tag, the data information including a unique identification code and an encryption key;

[0097] S430: Acquire verification digital information of the NFC tag to be detected by collecting chip information and data information.

[0098] In step S410, the chip information of the NFC tag is collected. This chip information refers to information about the microcontroller or other control chip contained in the NFC tag. This information may include the chip model and production date. Functional verification, security verification, and trustworthiness verification of the chip information refer to the process of testing and verifying the microcontroller or other control chip contained in the NFC tag. In step S420, the data information of the NFC tag may include the following: the unique identification code refers to a set of binary data used to uniquely identify the NFC tag; and the encryption key refers to the key used to encrypt and decrypt data in the NFC tag. In summary, the unique identification code and encryption key are important factors in ensuring the security and reliability of NFC tag data and are of great significance in various application scenarios.

[0099] Furthermore, according to the method for detecting a high-frequency NFC tag of a printed power supply, a noise reduction process is performed on a physical image of the NFC tag to be detected, and image enhancement is performed after the noise reduction process.

[0100] Specifically, noise reduction and image enhancement are two commonly used techniques in digital image processing. Their primary purpose is to improve image quality and readability by removing or enhancing noise and detail. Noise reduction involves removing noise from images through filtering, smoothing, and other methods, reducing the impact of interfering signals and improving image clarity and readability. Image enhancement involves adjusting image parameters such as brightness, contrast, and color to enhance the visual quality and clarity of the image. However, care must be taken to avoid image distortion or information loss caused by excessive processing.

[0101] Example 2:

[0102] like Figure 5 As shown, the high-frequency NFC tag detection system of the printed power supply includes:

[0103] Physical image acquisition module: collects and obtains the physical image of the NFC tag to be detected, and obtains the physical information set based on the physical image;

[0104] Physical feature detection module: Based on the physical features of the NFC tag, a physical feature detection model is constructed, and the physical information set is input into the physical feature detection model to obtain the physical feature detection results;

[0105] Digital information collection module: collects and obtains the verification digital information of the NFC tag to be detected, and obtains a digital information set based on the verification digital information;

[0106] Digital feature detection module: Builds a digital feature detection model based on the expected digital information of the NFC tag, and the expected digital information corresponds one-to-one with the verification digital information in the digital information set;

[0107] Comprehensive evaluation module: inputs the physical feature detection results and digital feature detection results into the NFC tag evaluation space to obtain comprehensive detection results.

[0108] The above-mentioned adjustment system in the present invention can effectively implement the detection method of the high-frequency NFC tag of the printed power supply, and the technical effects that can be achieved are as described in the above embodiments and will not be repeated here.

[0109] Furthermore, the physical feature detection module includes:

[0110] Appearance feature acquisition unit: acquires the size, thickness and edge burr degree of the standardized NFC tag, where the size, thickness and edge burr degree are the appearance features;

[0111] Characterization index acquisition unit: acquires printing quality, reflectivity and intensity information of the standardized NFC tag, where the printing quality, reflectivity and intensity information serve as characterization indicators;

[0112] Wherein, the physical features are obtained by the appearance feature acquisition unit and the characterization index acquisition unit;

[0113] Fluctuation threshold setting unit: sets a physical fluctuation threshold according to the physical characteristics, and the physical characteristics within the physical fluctuation threshold are qualified NFC tags;

[0114] Physical feature detection model building unit: builds a physical feature detection model based on the physical fluctuation threshold.

[0115] Furthermore, the digital feature detection module includes:

[0116] Expected information acquisition unit: obtains expected chip information and expected data information in the NFC tag;

[0117] Expected digital information extraction unit: obtains expected digital information according to chip information and expected data information, and the expected chip information and expected data information respectively correspond to the verification digital information in the digital information set;

[0118] Digital feature detection model building unit: builds a digital feature detection model according to the expected digital information of the NFC tag.

[0119] Similarly, the above-mentioned optimization schemes for the system can also respectively achieve the corresponding optimization effects of the method in Example 1, which will not be repeated here.

[0120] Although the present application has been described with reference to specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and drawings are merely illustrative of the present application as defined herein and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, the present application is intended to include such modifications and variations as fall within the scope of the present application and its equivalents.

Claims

1. A method for detecting a high-frequency NFC tag of a printed power supply, characterized in that: The method comprises: Acquire a physical image of the NFC tag to be detected, and obtain a physical information set based on the physical image; Based on the physical characteristics of the NFC tag, a physical feature detection model is constructed; Inputting the physical information set into the physical feature detection model to obtain a physical feature detection result; Collect and obtain verification digital information of the NFC tag to be detected, and obtain a digital information set based on the verification digital information; Constructing a digital feature detection model based on the expected digital information of the NFC tag, wherein the expected digital information corresponds one-to-one with the verification digital information in the digital information set; The physical feature detection result and the digital feature detection result are input into the NFC tag evaluation space to obtain a comprehensive detection result.

2. The method for detecting a high-frequency NFC tag of a printed power supply according to claim 1, wherein: The constructing of the physical feature detection model comprises: Obtaining the size, thickness, and edge burr degree of a standardized NFC tag, where the size, thickness, and edge burr degree are appearance characteristics; Obtaining printing quality, reflectivity, and intensity information of the standardized NFC tag, where the printing quality, reflectivity, and intensity information are characterization indicators; wherein the physical characteristics are obtained according to the appearance characteristics and the characterization index; Setting a physical fluctuation threshold according to the physical characteristics, wherein the physical characteristics of the NFC tag are within the physical fluctuation threshold; A physical feature detection model is constructed according to the physical fluctuation threshold.

3. The method for detecting a high-frequency NFC tag of a printed power supply according to claim 1, wherein: Building a digital feature detection model involves: Obtaining expected chip information and expected data information from the NFC tag; Obtaining expected digital information according to the chip information and the expected data information, wherein the expected chip information and the expected data information respectively correspond one-to-one to the verification digital information in the digital information set; A digital feature detection model is constructed according to the expected digital information of the NFC tag.

4. The method for detecting a high-frequency NFC tag of a printed power supply according to claim 1, wherein: Obtaining the comprehensive test results includes: Select a matching neural network structure, configure it according to the required input and output dimensions, and establish an NFC tag evaluation space; Collect relevant data of NFC tags, train the NFC tag evaluation space using the relevant data, and use a cross-validation method to evaluate the performance of the model; The comprehensive detection result is obtained through the NFC tag evaluation space.

5. The method for detecting a high-frequency NFC tag of a printed power supply according to claim 4, characterized in that: The relevant data is preprocessed before training the NFC tag evaluation space using the relevant data.

6. The method for detecting a high-frequency NFC tag of a printed power supply according to claim 1, wherein: The acquisition of verification digital information of the NFC tag to be detected includes: Collect chip information of the NFC tag, including function verification, security verification, and trust verification; Collecting data information from the NFC tag, the data information including a unique identification code and an encryption key; By collecting the chip information and the data information, the verification digital information of the NFC tag to be detected is obtained.

7. The method for detecting a high-frequency NFC tag of a printed power supply according to claim 1, characterized in that: The physical image of the NFC tag to be detected is subjected to noise reduction processing, and image enhancement is performed after the noise reduction processing.

8. The high-frequency NFC tag detection system of the printed power supply is characterized in that: The system comprises: Physical image acquisition module: collects and acquires the physical image of the NFC tag to be detected, and obtains a physical information set based on the physical image; Physical feature detection module: constructs a physical feature detection model based on the physical features of the NFC tag, and inputs the physical information set into the physical feature detection model to obtain physical feature detection results; Digital information acquisition module: collects and obtains the verification digital information of the NFC tag to be detected, and obtains a digital information set based on the verification digital information; Digital feature detection module: constructs a digital feature detection model based on the expected digital information of the NFC tag, and the expected digital information corresponds one-to-one with the verification digital information in the digital information set; Comprehensive evaluation module: inputs the physical feature detection result and the digital feature detection result into the NFC tag evaluation space to obtain a comprehensive detection result.

9. The high-frequency NFC tag detection system for a printed power supply according to claim 8, characterized in that: The physical feature detection module includes: Appearance feature acquisition unit: acquires the size, thickness, and edge burr degree of the standardized NFC tag, where the size, thickness, and edge burr degree are appearance features; Characterization index acquisition unit: acquires printing quality, reflectivity and intensity information of the standardized NFC tag, wherein the printing quality, reflectivity and intensity information are characterization indicators; Wherein, the physical features are obtained by the appearance feature acquisition unit and the characterization index acquisition unit; A fluctuation threshold setting unit is configured to set a physical fluctuation threshold according to the physical characteristics, wherein the physical characteristics within the physical fluctuation threshold are those of a qualified NFC tag; A physical feature detection model building unit is configured to build a physical feature detection model according to the physical fluctuation threshold.

10. The high-frequency NFC tag detection system for a printed power supply according to claim 8 or 9, characterized in that: The digital feature detection module includes: Expected information acquisition unit: obtains expected chip information and expected data information in the NFC tag; An expected digital information extraction unit is configured to obtain the expected digital information according to the chip information and the expected data information, wherein the expected chip information and the expected data information correspond one-to-one to the verification digital information in the digital information set; A digital feature detection model building unit is configured to build a digital feature detection model according to the expected digital information of the NFC tag.

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