Preparation method and system of high-performance electronic tag

Abstract

The invention relates to a preparation method and system of a high-performance electronic tag in the field of electronic tag manufacturing, and the method comprises the steps: obtaining the working parameters of a high-frequency / NFC electronic tag in a high-temperature environment, analyzing the conductivity change trend of an antenna material, building a mathematical model of the influence of the high-temperature environment on the antenna material, and obtaining the high-performance electronic tag according to the model. Adjusting the component proportion of the antenna material to obtain an optimized antenna material formula; on the basis of optimizing an electromagnetic shielding scheme, comprehensive performance data of a high-frequency / NFC electronic tag in different environments are collected, a performance prediction model under the coupling action of multiple environmental factors is established, the model is adopted to simulate the working state of the tag in a complex working condition, and the performance stability of the tag is judged; after an antenna pattern is precisely processed, characteristic data of all layers of materials of the high-frequency / NFC electronic tag are collected, a relation model of material characteristics and bonding strength is established, and interlayer bonding force is enhanced by adopting a plasma surface treatment technology, so that an optimized bonding process scheme is obtained.

Description

Technical Field

[0001] The present invention relates to the field of information technology, specifically to the field of manufacturing electronic tags, and particularly to a preparation method and system for high-performance electronic tags. Background Art

[0002] As a core component of wireless identification technology, common electronic tags are divided into high-frequency (HF) tags and near-field communication (NFC) tags. In complex environments, the performance stability of electronic tags faces severe challenges. The traditional tag structure design is single and lacks targeted optimization for environmental factors, resulting in a significant decline in performance under high temperature, high humidity, or strong electromagnetic interference conditions. For example, high temperature may cause the conductivity of the antenna material to decay, the metal layer is prone to oxidation in a high-humidity environment, and strong electromagnetic interference directly affects the signal transmission efficiency. In addition, existing testing methods are limited to the evaluation of single environmental factors and cannot comprehensively simulate the complex working conditions that may be encountered in actual use, making it difficult to accurately reflect the comprehensive performance of the tags. In terms of manufacturing processes, traditional methods are difficult to precisely control the size and shape of the antenna pattern, resulting in unstable signal transmission efficiency. At the same time, the adhesion strength between the layers of the tag is insufficient, and delamination is likely to occur under mechanical stress or repeated bending, affecting the service life. The wear resistance and antistatic performance of the existing protective layer are limited, and performance may decline due to wear or static electricity accumulation in actual applications. The above problems directly affect the applicable range and reliability of high-frequency / NFC electronic tags. Especially in scenarios with high-performance requirements such as industrial automation and logistics tracking, the performance defects of the tags may lead to data reading failures or equipment malfunctions, thereby affecting the operating efficiency of the overall system. Therefore, there is an urgent need for a new structure design and testing method to improve the adaptability and durability of electronic tags in complex environments. Summary of the Invention

[0003] The present invention provides a preparation method for high-performance electronic tags, including the following steps:

[0004] Step S101: Obtain the working parameters of high-frequency / NFC electronic tags in a high-temperature environment, analyze the changing trend of the conductivity of the antenna material, establish a mathematical model of the influence of the high-temperature environment on the antenna material, and according to this model, adjust the composition ratio of the antenna material to obtain an optimized antenna material formula;

[0005] Step S102: Starting from the optimized antenna material formula, collect the working data of high-frequency / NFC electronic tags in a high-humidity environment, monitor the oxidation degree of the metal layer, establish the corresponding relationship between humidity and the metal oxidation rate, use anti-oxidation coating technology to form a protective film on the surface of the metal layer, and determine the optimal coating thickness and material;

[0006] Step S103: After forming a protective film on the metal layer surface, obtain the signal transmission data of the high-frequency / NFC electronic tag in a strong electromagnetic interference environment, analyze the influence degree of the interference source on the signal, establish a relationship model between electromagnetic interference and signal attenuation, and design a multi-layer shielding structure according to this model to obtain an optimized electromagnetic shielding solution;

[0007] Step S104: On the basis of the optimized electromagnetic shielding solution, collect the comprehensive performance data of the high-frequency / NFC electronic tag in different environments, establish a performance prediction model under the coupling action of multi-environmental factors, and use this model to simulate the working state of the tag under complex working conditions to judge its performance stability;

[0008] Step S105: Starting from the performance prediction model, obtain the process parameters in the manufacturing process of the high-frequency / NFC electronic tag, analyze the dimensional accuracy of the antenna pattern, establish a corresponding relationship between the process parameters and the antenna pattern accuracy, and use laser micromachining technology to precisely machine the antenna pattern on the substrate to determine the optimal processing parameters;

[0009] Step S106: After precisely machining the antenna pattern, collect the characteristic data of each layer of material of the high-frequency / NFC electronic tag, analyze the interlayer adhesion strength, establish a relationship model between the material characteristics and the adhesion strength, and use plasma surface treatment technology to enhance the interlayer adhesion force to obtain an optimized adhesion process plan;

[0010] Step S107: Starting from the optimized adhesion process plan, obtain the performance data of the protective layer of the high-frequency / NFC electronic tag, analyze its wear resistance and antistatic performance, establish a relationship model between the protective layer performance and the use environment, and use nanocomposite technology to prepare a high-performance protective layer to determine the optimal material ratio and processing technology;

[0011] Step S108: After preparing the high-performance protective layer, collect the usage data of the high-frequency / NFC electronic tag in industrial automation and logistics tracking scenarios, analyze its performance in actual applications, establish a relationship model between the usage scenario and the performance requirements, and use this model to optimize the design parameters of the tag to obtain a product solution that meets the actual application requirements.

[0012] The present invention provides a preparation system for a high-performance electronic tag, mainly including:

[0013] A high-temperature environment parameter acquisition module, which is used to acquire the working parameters of the high-frequency / NFC electronic tag in a high-temperature environment, analyze the change trend of the conductivity of the antenna material, establish a mathematical model of the influence of the high-temperature environment on the antenna material, and adjust the component ratio of the antenna material according to this model to obtain an optimized antenna material formula;

[0014] The humidity environment monitoring module is used to collect the working data of high-frequency / NFC electronic tags in a high-humidity environment starting from the optimized antenna material formula, monitor the oxidation degree of the metal layer, establish the corresponding relationship between humidity and the metal oxidation rate, adopt the anti-oxidation coating technology to form a protective film on the surface of the metal layer, and determine the optimal coating thickness and material;

[0015] The electromagnetic interference analysis module is used to obtain the signal transmission data of high-frequency / NFC electronic tags in a strong electromagnetic interference environment after forming a protective film on the surface of the metal layer, analyze the influence degree of the interference source on the signal, establish the relationship model between electromagnetic interference and signal attenuation, and design a multi-layer shielding structure according to this model to obtain an optimized electromagnetic shielding solution;

[0016] The comprehensive performance prediction module is used to collect the comprehensive performance data of high-frequency / NFC electronic tags in different environments based on the optimized electromagnetic shielding solution, establish a performance prediction model under the coupling action of multi-environmental factors, and use this model to simulate the working state of the tag under complex working conditions to judge its performance stability;

[0017] The antenna pattern processing module is used to obtain the process parameters in the manufacturing process of high-frequency / NFC electronic tags starting from the performance prediction model, analyze the dimensional accuracy of the antenna pattern, establish the corresponding relationship between process parameters and the accuracy of the antenna pattern, adopt laser micro-machining technology to precisely machine the antenna pattern on the substrate, and determine the optimal processing parameters;

[0018] The interlayer adhesion optimization module is used to collect the characteristic data of each layer of materials of high-frequency / NFC electronic tags after precisely machining the antenna pattern, analyze the interlayer adhesion strength, establish the relationship model between material characteristics and adhesion strength, and adopt plasma surface treatment technology to enhance the interlayer adhesion force to obtain an optimized adhesion process solution;

[0019] The protective layer preparation module is used to obtain the performance data of the protective layer of high-frequency / NFC electronic tags starting from the optimized adhesion process solution, analyze its wear resistance and antistatic performance, establish the relationship model between the performance of the protective layer and the use environment, and adopt nano-composite material technology to prepare a high-performance protective layer to determine the optimal material ratio and processing technology;

[0020] The application scenario optimization module is used to collect the usage data of high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios after preparing a high-performance protective layer, analyze its performance in actual applications, establish the relationship model between usage scenarios and performance requirements, and use this model to optimize the design parameters of the tag to obtain a product solution that meets the actual application requirements.

[0021] The technical solution provided by the embodiment of the present invention may include the following beneficial effects:

[0022] The present invention discloses a preparation method of a high-performance electronic tag. By analyzing the influence of extreme environments such as high temperature, high humidity, and strong electromagnetic interference on the tag performance, a performance prediction model under the coupling action of multiple environmental factors is established. The laser microfabrication technology is used to precisely fabricate the antenna pattern, and the interlayer adhesion is enhanced through plasma surface treatment. A high-performance protective layer is prepared using a nanocomposite material, improving the abrasion resistance and antistatic performance of the tag. Finally, by analyzing the usage data in industrial automation and logistics tracking scenarios, the tag design parameters are optimized to meet the actual application requirements. The present invention significantly improves the performance stability and reliability of high-frequency / NFC electronic tags in complex environments, laying a foundation for their wide application in harsh industrial environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flowchart of a preparation method of a high-performance electronic tag of the present invention.

[0024] Figure 2 It is a schematic diagram of a preparation method and system of a high-performance electronic tag of the present invention.

[0025] Figure 3 It is another schematic diagram of a preparation method and system of a high-performance electronic tag of the present invention.

[0026] Figure 4 It is a structural schematic diagram of a preparation method and system of a high-performance electronic tag of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this specification.

[0028] Such as Figures 1-4 , the preparation method of a high-performance electronic tag in this embodiment may specifically include:

[0029] Step S101, obtain the working parameters of the high-frequency / NFC electronic tag in a high-temperature environment, analyze the change trend of the conductive performance of the antenna material, and establish a mathematical model of the influence of the high-temperature environment on the antenna material. According to this model, adjust the component ratio of the antenna material to obtain an optimized antenna material formula.

[0030] Obtain the working parameters of the high-frequency / NFC electronic tag at different temperatures, where the working parameters include electrical characteristics such as resistance, capacitance, and inductance; analyze the change trend of the conductivity of the antenna material at different temperatures according to the working parameters; establish a mathematical model using the linear regression method for the relationship between conductivity and temperature; determine the initial composition ratio of the antenna material according to the mathematical model, where the composition ratio includes the metal content and the polymer matrix ratio; optimize the composition ratio of the antenna material using the genetic algorithm to obtain at least one optimized material formulation; prepare the optimized antenna material according to the optimized material formulation; test the conductivity of the optimized antenna material in a high-temperature environment and determine whether the conductivity meets the preset performance indicators; if the conductivity does not meet the preset performance indicators, adjust the composition ratio of the antenna material and re-optimize until the target antenna material that meets the preset performance indicators is obtained.

[0031] Specifically, the working parameter test of the high-frequency electronic tag needs to be carried out in a temperature control box. For example, the temperature is tested in segments from minus twenty degrees to one hundred and twenty degrees, and the resistance, inductance, and capacitance values of the tag antenna are measured at each temperature point. Under standard test conditions, the resistance of a copper antenna is about 0.5 ohms, the inductance is 6 microhenries, and the capacitance is 12 picofarads. When the temperature rises, the resistance of the metal conductor will increase with the increase of temperature and may reach 0.8 ohms at 80 degrees. To model the relationship between conductivity and temperature, resistivity data at different temperatures need to be obtained first. Through experiments, it is found that the resistivity of the conductive silver paste is 2.8 microohm-meters at 20 degrees, and the resistivity increases by about 0.4% for every 10-degree increase in temperature. Substituting the experimental data into the linear regression model, a linear equation for the change of resistivity with temperature is obtained, which is used for subsequent material formula optimization. The adjustment of the antenna material formula focuses on the ratio of the conductive filler to the polymer matrix. In the conductive silver paste, when the silver powder content increases from 75% to 85%, the conductivity improves significantly, but the adhesiveness decreases. When the proportion of the epoxy resin matrix decreases from 20% to 15%, the conductivity can be improved, but the toughness of the material will be affected. The optimal ratio is determined through orthogonal experiments, such as 80% silver powder, 18% resin, and 2% curing agent. When optimizing with the genetic algorithm, parameters such as the silver powder content and resin ratio are encoded as genes, and the fitness function is set as the high-temperature conductivity index. The initial population is set as 20 formulas, and iterative optimization is carried out through operations such as selection, crossover, and mutation. After 50 generations of evolution, the optimal formula is obtained: 78% nano silver powder, 7% micro silver powder, 13% modified epoxy resin, and 2% curing agent. When verifying the optimized formula, the sample is placed in a 120-degree high-temperature oven for 4 hours, and the resistance value is measured every hour. The results show that the resistance value rises from 0.6 ohms at room temperature to 1.2 ohms, meeting the index requirement of less than 1.5 ohms. After passing the heat resistance performance verification, the antenna pattern printing test is carried out to confirm that the material viscosity and curing characteristics meet the process requirements. Finally, it is determined that this formula can meet the high-temperature use conditions and has good comprehensive performance. If the antenna material formula needs to be further improved, the stability of the conductive network can be enhanced by adding conductive carbon nanotubes, or the interfacial bonding between the metal powder and the resin matrix can be strengthened by using surface modification technology. At the same time, multiple factors such as conductivity, processability, and cost need to be weighed to achieve the overall optimization of the formula.

[0032] Step S102: Starting from the optimized antenna material formula, collect the working data of the high-frequency / NFC electronic tag in a high-humidity environment, monitor the oxidation degree of the metal layer, and establish the corresponding relationship between humidity and the metal oxidation rate. Adopt the anti-oxidation coating technology to form a protective film on the surface of the metal layer, and determine the optimal coating thickness and material.

[0033] Obtain the optimized antenna material formula; place the high-frequency / NFC electronic tag in a high-humidity environment; monitor the oxidation degree of the metal layer through a sensor to obtain data on the humidity value and the metal oxidation rate; determine the target coating thickness of the protective film on the metal layer surface according to the pre-established relationship between the humidity value and the metal oxidation rate; use a machine learning algorithm to analyze the relationship between the protective film coating thickness and the metal oxidation rate to obtain the optimal coating thickness; form a protective film on the metal layer surface using chemical vapor deposition technology according to the optimal coating thickness; observe the uniformity of the protective film through a scanning electron microscope to determine whether the coating quality of the protective film meets the preset standard; if the coating quality meets the preset standard, determine the final coating material and thickness; if the coating quality does not meet the preset standard, adjust the coating parameters and re-perform chemical vapor deposition.

[0034] Specifically, high-frequency tags are prone to corrosion in a high-humidity environment. To effectively monitor the oxidation degree of the metal layer in a humid environment, an electrical conductivity sensor can be used to detect the electrical properties of the metal substrate in real time. For example, when the humidity reaches more than seventy percent, the surface of traditional copper-based electronic tags will undergo obvious oxidation within a few hours, resulting in a decrease in conductivity of more than thirty percent. By accelerating the test on the tag sample in a thermostatic and humid box, record the oxidation degree corresponding to different humidities. In an environment with a humidity of ninety percent, the oxidation rate of the copper layer is about 0.03 microns per hour. Based on the collected data, an association model between humidity and oxidation rate can be established, providing a basis for subsequent coating design. For the anti-oxidation coating, epoxy resin-based materials can be used. This type of material has good moisture-proof performance and high heat resistance. The protective effect can be effectively controlled by adjusting the coating thickness. For example, when the coating thickness is 5 microns, the oxidation rate of the metal layer in a 90% humidity environment can be reduced to less than 0.005 microns per hour. In terms of the coating process, chemical vapor deposition technology can form a uniform and dense protective film. By adjusting parameters such as the reaction chamber temperature and gas flow rate, the coating growth rate can be precisely controlled. Generally, when the reaction chamber temperature is controlled at about 150 degrees and the gas flow rate is 50 milliliters per minute, the best coating quality can be obtained. By using machine learning methods to analyze a large amount of experimental data, the optimal ratio between the coating thickness and the protective performance can be found. A model can be established through algorithms such as support vector machines to predict the coating performance under different process parameters. Practice shows that when the coating thickness is in the range of 4 to 6 microns, it can ensure the protective effect without affecting the radio frequency performance of the tag. Scanning electron microscope observation shows that the surface of a high-quality coating should have no defects such as cracks and bubbles. By analyzing the surface morphology of the coating, if it is found that the local thickness deviation exceeds 10% or there are pinhole defects, the process parameters need to be adjusted again. After multiple optimizations, when the final determined coating thickness is 5.5 microns, the tag can work stably in a 95% humidity environment for more than 1000 hours.

[0035] In step S103, after forming a protective film on the surface of the metal layer, obtain the signal transmission data of the high-frequency / NFC electronic tag in a strong electromagnetic interference environment, analyze the influence degree of the interference source on the signal, and establish a relationship model between electromagnetic interference and signal attenuation. According to this model, design a multi-layer shielding structure to obtain an optimized electromagnetic shielding solution.

[0036] Obtain the signal strength value of the high-frequency / NFC electronic tag in a preset electromagnetic interference environment; for the signal strength value, adopt the Fourier transform algorithm to extract the attenuation characteristics of the signal at different frequencies, and establish a signal attenuation characteristic database; according to the signal attenuation characteristic database, adopt the multiple linear regression algorithm to construct a correlation model between the electromagnetic interference intensity and the signal attenuation degree; based on the correlation model, adopt the finite element analysis method to calculate the attenuation effect of different shielding layer thicknesses on electromagnetic interference to obtain shielding effect data; according to the shielding effect data, adopt the genetic algorithm to optimize the multi-layer shielding structure to obtain the optimal thickness combination of each layer of shielding material; based on the optimized shielding structure, through the electromagnetic field simulation software, simulate the signal transmission situation of the electronic tag in a strong electromagnetic interference environment to obtain the optimized signal strength value; if the optimized signal strength value reaches the preset threshold, determine the optimization scheme; if not, adjust the shielding layer material parameters and re-perform the optimization calculation.

[0037] Specifically, the electromagnetic field simulation software can accurately model the antenna structure in a three-dimensional modeling manner and calculate the electromagnetic field distribution through the finite-difference time-domain method. For example, after generating an alumina protective film with a thickness of 50 micrometers on the surface of a high-frequency electronic tag, the operating frequency can be set to 13.56 MHz, the external interference source to 50 Hz power frequency interference, and the interference intensity to 1000 V / m in the software. The signal intensity values obtained through simulation show changes in amplitude and phase, and these data can be used for subsequent analysis. The Fourier transform algorithm can convert the time-domain signal to the frequency domain and extract the key frequency components. For example, after performing a fast Fourier transform on the collected signal, the attenuation characteristics at different frequencies can be obtained, such as the 10 dB attenuation caused by power frequency interference and the 5 dB attenuation caused by higher harmonics and other characteristic data. These characteristic data form a database, providing a basis for subsequent modeling. The multiple linear regression algorithm predicts the signal attenuation in different interference environments by establishing a mathematical model between the electromagnetic interference intensity and the signal attenuation degree. For example, factors such as the interference source intensity, distance, and frequency are used as independent variables, and the signal attenuation value is used as the dependent variable to establish a regression equation. This correlation model can be used to optimize the shielding layer design. The finite element analysis method discretizes the continuous medium into a finite number of elements and calculates the electromagnetic field distribution. By setting metal shielding layers with different thicknesses, such as the copper foil layer thickness ranging from 10 micrometers to 100 micrometers and the aluminum foil layer thickness ranging from 20 micrometers to 200 micrometers, the shielding effects of various combinations are analyzed. These data can be used to optimize the multi-layer shielding structure. The genetic algorithm searches for the optimal solution by simulating the biological evolution process. By setting the population size to 100, the number of iterations to 1000, the crossover probability to 0.8, and the mutation probability to 0.1, the optimal combination of shielding layer thicknesses can be obtained. For example, a structure with an outer copper foil thickness of 80 micrometers and a middle aluminum foil thickness of 150 micrometers has the best shielding effect. Finally, the optimization results are verified through electromagnetic field simulation. The optimized multi-layer shielding structure is placed in a strong electromagnetic interference environment to test the signal transmission performance. If the signal attenuation is less than 15 dB under an interference intensity of 1000 V / m, it proves that the optimization scheme is feasible. If the attenuation exceeds the threshold, the material parameters need to be adjusted, such as increasing the number of shielding layers or changing the material type, and the optimization calculation is performed again. This iterative optimization method can ensure that a shielding structure design that meets the requirements is finally obtained.

[0038] Step S104, on the basis of optimizing the electromagnetic shielding scheme, collect the comprehensive performance data of the high-frequency / NFC electronic tag in different environments, and establish a performance prediction model under the coupling action of multi-environment factors. Using this model, simulate the working state of the tag under complex working conditions and judge its performance stability.

[0039] Obtain the performance data of high-frequency tags in different environments; analyze the influence of environmental factors on the high-frequency tags based on the performance data, and establish a coupling effect model; use the coupling effect model to simulate the working state of the high-frequency tags under complex working conditions; extract the key parameters of the high-frequency tags according to the working state and input them into the prediction model; judge the stability of the high-frequency tags in different environments through the prediction model; if the stability is lower than the preset threshold, adjust the electromagnetic shielding scheme and re-obtain the performance data; update the prediction model according to the adjusted performance data to obtain the optimized performance of the high-frequency tags.

[0040] Specifically, electromagnetic shielding optimization first needs to consider the influence of multiple environmental factors on the performance of high-frequency tags. In a metal environment, induced currents will be generated on the metal surface, forming a reflection field, which causes the label signal to attenuate. For example, in a steel mill environment, when the high-frequency tag is affected by a strong magnetic field, the signal strength may attenuate from the normal -20 dB to -40 dB. By adding a ferrite absorbing material layer, the signal attenuation can be controlled within -30 dB. The environmental coupling effect model needs to consider multiple factors such as temperature and humidity. Taking temperature as an example, when the environmental temperature rises from room temperature to 100 °C, the resonant frequency of the tag antenna will drift, resulting in a shortened reading distance. By adding a temperature compensation material to the tag substrate, the frequency drift can be controlled within 0.5%. Humidity also has a significant impact on the tag performance. When the relative humidity reaches 95%, the impedance of the tag will change, and the signal attenuation can reach 15 dB. In the simulation of complex working conditions, the superimposed effects of multiple environmental factors need to be considered simultaneously. For example, in a chemical plant environment, the high-frequency tag is simultaneously affected by corrosive gases, high temperature, and high humidity. By establishing a multi-factor coupling model, the performance changes of the tag under different working conditions can be predicted. Experimental data show that after adopting a multi-layer composite protection structure, the reading success rate of the tag under complex working conditions can be increased to more than 95%. The key parameter prediction model mainly includes indicators such as signal strength, reading distance, and frequency stability. Taking a certain model of high-frequency tag as an example, the reading distance can reach 1 m and the signal strength is -25 dB under normal working conditions. When the environment changes, the performance of the tag can be evaluated in real time through the prediction model. For example, when the temperature rises by 10 °C, the reading distance will be shortened by 5%, and the signal strength will attenuate by 2 dB. For the situation where the predicted results show that the performance does not meet the standard, the electromagnetic shielding scheme needs to be optimized. For example, when it is found in the prediction model that the stability of the tag is lower than 85%, the performance can be improved by adjusting the thickness of the shielding layer, adding absorbing materials, etc. Practice shows that by adopting a gradient composite shielding structure, the tag can maintain a stability of more than 90% in a harsh environment. The continuous collection of performance data and model update can continuously improve the adaptability of the tag in various environments.

[0041] In step S105, starting from the performance prediction model, obtain the process parameters in the manufacturing process of high-frequency / NFC electronic tags, analyze the dimensional accuracy of the antenna pattern, and establish the corresponding relationship between the process parameters and the antenna pattern accuracy. Use laser microfabrication technology to precisely fabricate the antenna pattern on the substrate and determine the optimal processing parameters.

[0042] Obtain the performance prediction model and manufacturing process parameters of the antenna pattern of high-frequency / NFC electronic tags; according to the performance prediction model, establish the corresponding relationship between the manufacturing process parameters and the dimensional accuracy of the antenna pattern; use laser microfabrication technology to conduct processing experiments on the antenna pattern on a preset substrate; obtain the dimensional data of the antenna pattern under different processing parameters, and compare the dimensional data with a preset dimensional accuracy threshold; if the dimensional data meets the preset dimensional accuracy threshold, determine the corresponding processing parameters as the optimal processing parameters; if the dimensional data does not meet the preset dimensional accuracy threshold, adjust the laser microfabrication parameters and re-conduct the antenna pattern processing experiment; generate an optimized manufacturing process plan for high-frequency / NFC electronic tags according to the determined optimal processing parameters.

[0043] Specifically, the manufacturing process of high-frequency / NFC electronic tags involves the control of antenna pattern accuracy, which has a direct impact on tag performance and reading distance. The dimensional accuracy requirements of the antenna pattern are usually at the micron level, and the accuracy of antenna line width and spacing is particularly important. The manufacturing process parameters include laser power, scanning speed, pulse width, etc., and these parameters will affect the etching depth and edge sharpness. Through the analysis of the performance prediction model, the relationship between antenna size and reading distance can be obtained. For example, an increase in line width by 5% will cause the resonance frequency to shift by approximately 3%. The dimensional accuracy analysis of the antenna pattern needs to consider multiple aspects. First is the substrate characteristics. Different substrates respond differently to laser processing. For example, polyester film and polyimide film will exhibit different thermal response characteristics during laser processing. Second is the environmental factors. Humidity and temperature will affect the processing accuracy. A 10-degree increase in room temperature may cause the substrate to thermally expand, affecting the actual processing size. Establishing the corresponding relationship between process parameters and dimensional accuracy requires a large amount of experimental data support. For example, on a polyester substrate, when the laser power is set to 8 watts and the scanning speed is 1000 mm per second, an antenna pattern with a line width error of less than 10 microns can be obtained. This parameter combination is recorded as a reference point. By changing a single parameter and observing the accuracy change, a parameter matrix is finally formed. In laser micro-machining experiments, the impact of processing parameters on edge quality should be focused on. A relatively high laser power may cause edge melting, while too low a power may result in incomplete processing. By observing the edge morphology with a microscope and measuring the actual size with a profiler, the processing quality can be accurately evaluated. The typical range of processing parameters includes a power of 6 to 10 watts and a scanning speed of 800 to 1200 mm per second. The dimensional accuracy evaluation uses a multi-point sampling method to measure at key positions of the antenna pattern. The preset accuracy threshold is usually plus or minus 5% of the designed size. When the measurement results show that a certain set of parameters can stably meet the requirements, repeatability verification needs to be carried out. If ten consecutively produced samples can all meet the accuracy requirements, this set of parameters can be determined as the optimal process parameters. Process parameter optimization is an iterative process. If it is found that the edge roughness exceeds the standard, it can be improved by adjusting the pulse frequency. When it is found that the processing depth is insufficient, the scanning speed can be appropriately reduced or the number of repetitions can be increased. The finally formed manufacturing process plan needs to include a complete parameter combination to ensure the repeatability and stability of the process.

[0044] Step S106, after precisely machining the antenna pattern, collect the characteristic data of each layer of materials of the high-frequency / NFC electronic tag, analyze the interlayer adhesion strength, and establish a relationship model between material characteristics and adhesion strength. Use plasma surface treatment technology to enhance the interlayer adhesion force and obtain an optimized adhesion process plan.

[0045] Obtain the material property data of each layer of the high-frequency / NFC electronic tag, determine the material properties and layer properties. According to the collected data, analyze the interlayer adhesion strength, and establish a relationship model between the material properties and the adhesion strength. Adopt the plasma surface treatment technology to optimize the interlayer adhesion strength, and obtain an optimization scheme through the treatment technology. For the optimization scheme, judge the influence of the plasma surface treatment on the adhesion strength. If the improvement of the adhesion strength is insufficient, adjust the treatment technology parameters and re-analyze the interlayer adhesion strength. Adopt machine learning algorithms, based on the collected data and the optimization scheme, train the analysis model to predict the relationship between different material properties and the adhesion strength. According to the prediction results, determine the best process plan, and realize the optimization of the interlayer adhesion strength through surface treatment and treatment technology. For the process plan, judge the compatibility of the materials of each layer of the electronic tag. If the compatibility is insufficient, adjust the material properties and re-establish the relationship model. Through the treatment technology and the optimization scheme, finally determine the bonding process plan of the high-frequency / NFC electronic tag to maximize the interlayer adhesion strength.

[0046] Specifically, the acquisition of multi-layer material characteristic data of high frequency and electronic tags mainly focuses on the properties of materials such as the substrate, conductive layer, and adhesive layer. Taking polyethylene terephthalate as an example, its surface energy is 32 millinewtons per meter, and the contact angle with the copper conductive layer is 75 degrees. These data directly affect the interlayer bonding strength. During the acquisition process, the interlayer bonding strength data is obtained through tensile strength testing. For example, the bonding strength without treatment is 0.5 megapascals. When modeling the relationship between the properties of interlayer materials and the bonding strength, factors such as the surface energy of the material and the content of polar groups need to be considered. Taking polymer substrates as an example, the content of surface polar groups is positively correlated with the bonding strength. Through plasma treatment, the surface oxygen-containing groups can be increased by 30%, thereby increasing the bonding strength to 1.2 megapascals. Plasma surface treatment uses oxygen as the working gas, the power is set at 100 watts, and the treatment time is 60 seconds, which can form polar groups such as hydroxyl and carboxyl groups on the material surface. The surface treatment effect is judged through a tensile peel test. If the bonding strength after treatment is lower than the preset threshold of 1 megapascal, the plasma treatment parameters need to be adjusted. For example, increase the treatment power to 150 watts, or extend the treatment time to 90 seconds until the target bonding strength is achieved. Through machine learning algorithms to analyze historical data, a prediction model of treatment parameters and bonding strength is established. Taking support vector machines as an example, the input variables include treatment power, time, gas flow rate, etc., and the output variable is the interlayer bonding strength. In the optimization of the process plan, the thermal properties and chemical compatibility of the materials need to be considered. For example, for conductive silver paste and polyester substrates, the difference in their thermal expansion coefficients may cause interlayer stress, and the material properties need to be adjusted by adding an elastomer modifier. After the material is modified, a relationship model is re-established to ensure the stability of the interlayer structure. Through plasma treatment to optimize the surface properties, for example, under the conditions of a treatment power of 120 watts and a time of 75 seconds, the interlayer bonding strength can be increased to 1.5 megapascals, and good stability is shown in the heat resistance test. The final bonding process plan needs to comprehensively consider production efficiency and cost factors. Taking a roll-to-roll production line as an example, the plasma treatment speed is set at 5 meters per minute, and the treatment width is 300 millimeters, which can achieve continuous production. The product after process optimization shows a bonding strength of 1.8 megapascals in a 90-degree peel test and maintains its structural integrity in a temperature and humidity cycle test.

[0047] Step S107, starting from the optimized bonding process plan, obtain the performance data of the high-frequency / NFC electronic tag protective layer, analyze its wear resistance and antistatic performance, and establish a relationship model between the protective layer performance and the use environment. Adopt nanocomposite technology to prepare a high-performance protective layer, and determine the optimal material ratio and processing technology.

[0048] Obtain the wear resistance and antistatic performance data of the high-frequency / NFC electronic tag protective layer; according to the performance data, analyze the performance of the protective layer under different usage environments; adopt nanocomposite material technology to prepare a high-performance protective layer sample; for the prepared sample, test its wear resistance and antistatic performance under different environmental conditions; if the performance of the sample reaches the preset threshold, determine the material ratio and processing technology as the optimal solution; according to the optimal solution, establish a relationship model between the performance of the protective layer and the usage environment; through the relationship model, predict the performance of the protective layer under specific environments.

[0049] Specifically, in high-frequency electronic tags, the protective layer, as the outermost material, directly contacts the external environment, and its performance has an important impact on the service life and reliability of the tags. Wear resistance and antistatic performance are the key indicators of the protective layer. The wear resistance data of the protective layer can be obtained through a friction coefficient tester, and the test conditions include parameters such as friction force, contact pressure, and speed. The antistatic performance can be measured by a surface resistivity tester, and the resistance value changes under different humidity conditions are recorded. Taking polyester material as an example, in the standard environment, when the friction force is five Newtons and the speed is two centimeters per second, after 10,000 reciprocating frictions, the increase in surface roughness is within 0.05 micrometers, showing excellent wear resistance. In the antistatic test, when the relative humidity is 60% and the temperature is 25 degrees Celsius, the surface resistivity remains at 10 to the ninth power ohms per square, meeting the antistatic requirements. The nano-composite material technology can significantly improve the performance of the protective layer by adding nano-aluminum oxide particles to the polyester matrix. When the addition amount of nano-particles is 3%, the wear resistance of the material is increased by 40%, and the surface resistivity is reduced to 10 to the eighth power ohms per square. This improvement is due to the strengthening effect of nano-particles and the formation of a conductive network. Under different environmental conditions, such as in a high-temperature and high-humidity environment, the performance of the protective layer will fluctuate. Experiments show that when the environmental temperature rises to 40 degrees Celsius and the relative humidity reaches 85%, the wear resistance of the nano-composite material only decreases by 10%, while that of ordinary materials decreases by 30%. This shows that the nano-composite material has better environmental adaptability. By establishing a relationship model between performance and environment, the performance of the protective layer under specific conditions can be predicted. For example, in a cold and dry environment with a temperature of -20 degrees Celsius and a relative humidity of 20%, the model predicts that the surface resistivity of the nano-composite material will increase to 10 to the tenth power ohms per square, but it is still within an acceptable range. This predictive ability helps to evaluate the reliability of the tags in different application scenarios. For different application requirements, the performance can be optimized by adjusting the type and content of nano-particles. For example, in occasions where higher wear resistance is required, nano-zirconia can be added. When the content is 5%, the wear resistance can be increased to twice the original level. When used in a strong electrostatic environment, nano-carbon materials can be added to achieve better antistatic effects. This flexible material design scheme provides customized solutions for different application scenarios.

[0050] Step S108, after preparing the high-performance protective layer, collect the usage data of the high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios, analyze their performance in actual applications, and establish a relationship model between the usage scenarios and performance requirements. Using this model, optimize the design parameters of the tags to obtain a product solution that meets the actual application requirements.

[0051] Obtain the usage data of high-frequency / NFC electronic tags in industrial scenarios and logistics scenarios; Based on the usage data, analyze the performance of the tags under different protective layer thicknesses, and establish a tag performance model; Establish the relationship between the industrial scenario model, the logistics scenario model and the tag performance model; Adopt the relationship between the scenario model and the performance model to determine the optimization direction of the tag design parameters; Obtain the optimized design parameters and generate a tag product solution that meets the application requirements; Evaluate the adaptability of the product solution in different scenarios through the performance model; If the adaptability of the product solution in the industrial scenario is lower than the preset industrial threshold, adjust the thickness of the protective layer in the design parameters; If the adaptability of the product solution in the logistics scenario is lower than the preset logistics threshold, adjust the antenna size in the design parameters; Adopt the adjusted design parameters to obtain a high-frequency / NFC electronic tag product that meets the requirements of industrial scenarios and logistics scenarios.

[0052] Specifically, the application environments of high-frequency / NFC electronic tags in industrial and logistics scenarios have their own characteristics. The industrial scenario has complex factors such as high temperature, vibration, and dust, and the label needs to enhance the wear resistance and anti-interference ability of the protective layer. For example, on a welding production line, the label can withstand an instantaneous temperature of up to 80 degrees Celsius and a vibration frequency of about 20 hertz per second. At this time, the thickness of the protective layer needs to reach more than 0.6 millimeters to provide effective protection. The logistics scenario mainly faces mechanical stresses such as impact and extrusion, and has high requirements for the design of the antenna size. For example, in the express sorting process, the label can withstand an instantaneous impact force of about 500 Newtons. If the antenna size is too large, it is easy to deform. It is recommended to control the antenna length within 40 millimeters. By collecting these environmental data, a scenario model can be established to quantify the environmental factors into specific parameters. The performance model reflects the performance of the label under different working conditions. Taking the reading distance as an example, in the industrial environment, the interference of metal equipment is relatively large, and the reading distance will be attenuated by about 30%. By increasing the thickness of the protective layer, the attenuation degree can be reduced. In the logistics scenario, the deformation of the label will cause the resonant frequency of the antenna to shift, affecting the reading stability, and the antenna structure design needs to be optimized. Associating the scenario model with the performance model can guide the optimization of label design. For example, in the industrial scenario, for every 0.1 millimeter increase in the thickness of the protective layer, the anti-interference ability is increased by about 15%, but the weight is increased by 8% accordingly. In the logistics scenario, when the antenna size is reduced by 10%, the impact resistance is increased by 20%, but the reading distance is reduced by 12%. By weighing these factors, the optimal design parameters can be determined. In actual application, it was found in a certain industrial site test that the failure rate of the label reached 8%, exceeding the preset threshold of 5%. After analysis, it was found that the insufficient thickness of the protective layer caused damage to the internal components. After increasing the thickness from 0.4 millimeters to 0.6 millimeters, the failure rate dropped to 3%. In the logistics scenario test, the label recognition accuracy was 92%, lower than the preset 95%. After analysis, it was caused by the too large antenna size. After reducing the length from 50 millimeters to 40 millimeters, the accuracy was increased to 97%. The final product solution comprehensively considers the requirements of both scenarios and adopts the design parameters of a 0.6-millimeter-thick protective layer and a 40-millimeter antenna length, with the failure rate stable below 3% in the industrial environment and the recognition accuracy remaining above 97% in the logistics environment, achieving the expected performance goals.

[0053] The present invention provides a preparation system for a high-performance electronic tag, mainly including:

[0054] A high-temperature environment parameter acquisition module, which is used to acquire the working parameters of the high-frequency / NFC electronic tag in a high-temperature environment, analyze the change trend of the conductive performance of the antenna material, establish a mathematical model of the influence of the high-temperature environment on the antenna material, and adjust the component ratio of the antenna material according to this model to obtain an optimized antenna material formula;

[0055] The humidity environment monitoring module is used to collect the working data of high-frequency / NFC electronic tags in a high-humidity environment starting from the optimized antenna material formula, monitor the oxidation degree of the metal layer, establish the corresponding relationship between humidity and the metal oxidation rate, adopt the anti-oxidation coating technology to form a protective film on the surface of the metal layer, and determine the optimal coating thickness and material;

[0056] The electromagnetic interference analysis module is used to obtain the signal transmission data of high-frequency / NFC electronic tags in a strong electromagnetic interference environment after forming a protective film on the surface of the metal layer, analyze the influence degree of the interference source on the signal, establish the relationship model between electromagnetic interference and signal attenuation, and design a multi-layer shielding structure according to this model to obtain an optimized electromagnetic shielding solution;

[0057] The comprehensive performance prediction module is used to collect the comprehensive performance data of high-frequency / NFC electronic tags in different environments based on the optimized electromagnetic shielding solution, establish a performance prediction model under the coupling action of multi-environmental factors, and use this model to simulate the working state of the tag under complex working conditions and judge its performance stability;

[0058] The antenna pattern processing module is used to obtain the process parameters in the manufacturing process of high-frequency / NFC electronic tags starting from the performance prediction model, analyze the dimensional accuracy of the antenna pattern, establish the corresponding relationship between process parameters and the accuracy of the antenna pattern, and use laser micro-processing technology to precisely process the antenna pattern on the substrate and determine the optimal processing parameters;

[0059] The interlayer adhesion optimization module is used to collect the characteristic data of each layer of materials of high-frequency / NFC electronic tags after precisely processing the antenna pattern, analyze the interlayer adhesion strength, establish the relationship model between material characteristics and adhesion strength, and use plasma surface treatment technology to enhance the interlayer adhesion force to obtain an optimized adhesion process plan;

[0060] The protective layer preparation module is used to obtain the performance data of the protective layer of high-frequency / NFC electronic tags starting from the optimized adhesion process plan, analyze its wear resistance and antistatic performance, establish the relationship model between the performance of the protective layer and the use environment, and use nanocomposite technology to prepare a high-performance protective layer and determine the optimal material ratio and processing technology;

[0061] The application scenario optimization module is used to collect the usage data of high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios after preparing a high-performance protective layer, analyze its performance in actual applications, establish the relationship model between usage scenarios and performance requirements, and use this model to optimize the design parameters of the tag to obtain a product solution that meets the actual application requirements.

[0062] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be similarly included in the patent protection scope of the present invention.

Claims

1. A method for preparing a high-performance electronic tag, characterized in that, The method includes the following steps: Step S101: Obtain the operating parameters of the high-frequency / NFC electronic tag in a high-temperature environment, analyze the changing trend of the electrical conductivity of the antenna material, establish a mathematical model of the influence of the high-temperature environment on the antenna material, and according to this model, adjust the composition ratio of the antenna material to obtain an optimized antenna material formula; Step S102: Starting from the optimized antenna material formula, collect the operating data of the high-frequency / NFC electronic tag in a high-humidity environment, monitor the oxidation degree of the metal layer, establish the corresponding relationship between humidity and the metal oxidation rate, adopt the anti-oxidation coating technology to form a protective film on the surface of the metal layer, and determine the optimal coating thickness and material; Step S103: After forming a protective film on the surface of the metal layer, obtain the signal transmission data of the high-frequency / NFC electronic tag in a strong electromagnetic interference environment, analyze the degree of influence of the interference source on the signal, establish a relationship model between electromagnetic interference and signal attenuation, and according to this model, design a multi-layer shielding structure to obtain an optimized electromagnetic shielding solution; Step S104: On the basis of the optimized electromagnetic shielding solution, collect the comprehensive performance data of the high-frequency / NFC electronic tag in different environments, establish a performance prediction model under the coupling action of multiple environmental factors, and use this model to simulate the working state of the tag under complex working conditions and judge its performance stability; Step S105: Starting from the performance prediction model, obtain the process parameters in the manufacturing process of the high-frequency / NFC electronic tag, analyze the dimensional accuracy of the antenna pattern, establish the corresponding relationship between the process parameters and the antenna pattern accuracy, adopt the laser micro-machining technology to precisely machine the antenna pattern on the substrate, and determine the optimal processing parameters; Step S106: After precisely machining the antenna pattern, collect the characteristic data of each layer of material of the high-frequency / NFC electronic tag, analyze the interlayer adhesion strength, establish a relationship model between the material characteristics and the adhesion strength, and adopt the plasma surface treatment technology to enhance the interlayer adhesion force to obtain an optimized adhesion process solution; Step S107: Starting from the optimized adhesion process solution, obtain the performance data of the protective layer of the high-frequency / NFC electronic tag, analyze its wear resistance and antistatic performance, establish a relationship model between the protective layer performance and the use environment, and adopt the nanocomposite material technology to prepare a high-performance protective layer and determine the optimal material ratio and processing technology; Step S108: After preparing the high-performance protective layer, collect the usage data of the high-frequency / NFC electronic tag in industrial automation and logistics tracking scenarios, analyze its performance in actual applications, establish a relationship model between the usage scenario and the performance requirements, and use this model to optimize the design parameters of the tag to obtain a product solution that meets the actual application requirements.

2. The preparation method of a high-performance electronic tag according to claim 1, characterized in that The said Step S101 includes: Obtain the operating parameters of the high-frequency / NFC electronic tag at different temperatures, and the operating parameters include electrical characteristics such as resistance, capacitance and inductance; According to the said operating parameters, analyze the changing trend of the electrical conductivity of the antenna material at different temperatures; For the relationship between electrical conductivity and temperature, adopt the linear regression method to establish a mathematical model; According to the mathematical model, determine the initial composition ratio of the antenna material, where the composition ratio includes the metal content and the polymer matrix ratio; Use a genetic algorithm to optimize the composition ratio of the antenna material to obtain at least one optimized material formulation; Prepare the optimized antenna material according to the optimized material formulation; Test the electrical conductivity of the optimized antenna material in a high-temperature environment and determine whether the electrical conductivity meets the preset performance indicators; If the electrical conductivity does not meet the preset performance indicators, adjust the composition ratio of the antenna material and re-optimize until the target antenna material that meets the preset performance indicators is obtained.

3. The preparation method of a high-performance electronic tag according to claim 1, characterized in that, The step S102 includes: Obtain the optimized antenna material formulation; Place the high-frequency / NFC electronic tag in a high-humidity environment; Monitor the oxidation degree of the metal layer through a sensor to obtain data on the humidity value and the metal oxidation rate; Determine the target coating thickness of the protective film on the metal layer surface according to the pre-established relationship between the humidity value and the metal oxidation rate; Use a machine learning algorithm to analyze the relationship between the protective film coating thickness and the metal oxidation rate to obtain the optimal coating thickness; Form a protective film on the metal layer surface using chemical vapor deposition technology according to the optimal coating thickness; Observe the uniformity of the protective film through a scanning electron microscope and determine whether the coating quality of the protective film meets the preset standards; If the coating quality meets the preset standards, determine the final coating material and thickness; If the coating quality does not meet the preset standards, adjust the coating parameters and re-perform chemical vapor deposition.

4. The preparation method of a high-performance electronic tag according to claim 1, characterized in that, The step S103 includes: Obtain the signal strength value of the high-frequency / NFC electronic tag in a preset electromagnetic interference environment; For the signal strength value, use the Fourier transform algorithm to extract the attenuation characteristics of the signal at different frequencies and establish a signal attenuation characteristic database; According to the signal attenuation characteristic database, use the multiple linear regression algorithm to construct an association model between the electromagnetic interference intensity and the signal attenuation degree; Based on the association model, use the finite element analysis method to calculate the attenuation effect of different shielding layer thicknesses on electromagnetic interference to obtain shielding effect data; According to the shielding effect data, use a genetic algorithm to optimize the multi-layer shielding structure to obtain the optimal thickness combination of each layer of shielding material; Based on the optimized shielding structure, use electromagnetic field simulation software to simulate the signal transmission situation of the electronic tag in a strong electromagnetic interference environment to obtain the optimized signal strength value; If the optimized signal strength value reaches the preset threshold, determine the optimization scheme; If not, adjust the shielding layer material parameters and re-perform the optimization calculation.

5. The preparation method of a high-performance electronic tag according to any one of claims 1-4, characterized in that, The step S104 includes: Obtain the performance data of the high-frequency tag in different environments; For the performance data, analyze the influence of environmental factors on the high-frequency tag and establish a coupling effect model; Use the coupling effect model to simulate the working state of the high-frequency tag under complex working conditions; According to the working state, extract the key parameters of the high-frequency tag and input them into the prediction model; Through the prediction model, judge the stability of the high-frequency tag in different environments; If the stability is lower than the preset threshold, adjust the electromagnetic shielding solution and re-acquire the performance data; Update the prediction model according to the adjusted performance data to obtain the optimized high-frequency standard performance.

6. The preparation method of a high-performance electronic tag according to any one of claims 1-4, characterized in that, The step S105 includes: Obtain the performance prediction model and manufacturing process parameters of the high-frequency / NFC electronic tag antenna pattern; According to the performance prediction model, establish the corresponding relationship between the manufacturing process parameters and the dimensional accuracy of the antenna pattern; Adopt laser microfabrication technology to conduct antenna pattern processing experiments on a preset substrate; Obtain the antenna pattern dimension data under different processing parameters, and compare the dimension data with the preset dimension accuracy threshold; If the dimension data meets the preset dimension accuracy threshold, determine the corresponding processing parameters as the optimal processing parameters; If the dimension data does not meet the preset dimension accuracy threshold, adjust the laser microfabrication parameters and re-conduct the antenna pattern processing experiment; Generate an optimized manufacturing process plan for high-frequency / NFC electronic tags according to the determined optimal processing parameters.

7. The preparation method of a high-performance electronic tag according to any one of claims 1-4, characterized in that, The step S106 includes: Obtain the material property data of each layer of the high-frequency / NFC electronic tag, determine the material properties and layer properties, analyze the interlayer adhesion strength according to the collected data, and establish a relationship model between the material properties and the adhesion strength; Adopt plasma surface treatment technology to optimize the interlayer adhesion strength and obtain an optimization plan through the treatment technology; For the optimization plan, judge the influence of plasma surface treatment on the adhesion strength. If the improvement of the adhesion strength is insufficient, adjust the treatment technology parameters and re-analyze the interlayer adhesion strength; Adopt a machine learning algorithm to train an analysis model based on the collected data and the optimization plan to predict the relationship between different material properties and the adhesion strength; According to the prediction results, determine the optimal process plan, and optimize the interlayer adhesion strength through surface treatment and treatment technology; For the process plan, judge the compatibility of the materials of each layer of the electronic tag. If the compatibility is insufficient, adjust the material properties and re-establish the relationship model; Finally, determine the bonding process plan of the high-frequency / NFC electronic tag through the treatment technology and the optimization plan to maximize the interlayer adhesion strength.

8. The preparation method of a high-performance electronic tag according to any one of claims 1-4, characterized in that, The step S107 includes: Obtain the wear resistance and antistatic performance data of the protective layer of the high-frequency / NFC electronic tag; Analyze the performance of the protective layer under different usage environments according to the performance data; Adopt nanocomposite material technology to prepare a protective layer sample with high performance; For the prepared sample, test its wear resistance and antistatic performance under different environmental conditions; If the sample performance reaches the preset threshold, determine the material ratio and processing technology as the optimal plan; According to the optimal plan, establish a relationship model between the protective layer performance and the usage environment; Through the relationship model, predict the performance of the protective layer under specific environments.

9. A preparation system for a high-performance electronic tag, characterized in that, This system is used to implement the preparation method of a high-performance electronic tag according to any one of claims 1-8. The system includes: The high-temperature environment parameter acquisition module is used to obtain the operating parameters of high-frequency / NFC electronic tags in a high-temperature environment, analyze the changing trend of the electrical conductivity of the antenna material, establish a mathematical model of the influence of the high-temperature environment on the antenna material, and adjust the composition ratio of the antenna material according to this model to obtain an optimized antenna material formula; The humidity environment monitoring module is used to start from the optimized antenna material formula, collect the operating data of high-frequency / NFC electronic tags in a high-humidity environment, monitor the oxidation degree of the metal layer, establish the corresponding relationship between humidity and the metal oxidation rate, adopt the anti-oxidation coating technology to form a protective film on the surface of the metal layer, and determine the optimal coating thickness and material; The electromagnetic interference analysis module is used to obtain the signal transmission data of high-frequency / NFC electronic tags in a strong electromagnetic interference environment after forming a protective film on the surface of the metal layer, analyze the influence degree of the interference source on the signal, establish a relationship model between electromagnetic interference and signal attenuation, and design a multi-layer shielding structure according to this model to obtain an optimized electromagnetic shielding solution; The comprehensive performance prediction module is used to collect the comprehensive performance data of high-frequency / NFC electronic tags in different environments on the basis of the optimized electromagnetic shielding solution, establish a performance prediction model under the coupling action of multi-environment factors, and use this model to simulate the operating state of the tag under complex working conditions and judge its performance stability; The antenna pattern processing module is used to obtain the process parameters in the manufacturing process of high-frequency / NFC electronic tags starting from the performance prediction model, analyze the dimensional accuracy of the antenna pattern, establish the corresponding relationship between the process parameters and the antenna pattern accuracy, and use laser micromachining technology to precisely process the antenna pattern on the substrate to determine the optimal processing parameters; The interlayer adhesion optimization module is used to collect the characteristic data of each layer of materials of high-frequency / NFC electronic tags after precisely processing the antenna pattern, analyze the interlayer adhesion strength, establish a relationship model between the material characteristics and the adhesion strength, and use plasma surface treatment technology to enhance the interlayer adhesion force to obtain an optimized adhesion process plan; The protective layer preparation module is used to obtain the performance data of the protective layer of high-frequency / NFC electronic tags starting from the optimized adhesion process plan, analyze its wear resistance and antistatic performance, establish a relationship model between the protective layer performance and the use environment, and use nanocomposite technology to prepare a high-performance protective layer to determine the optimal material ratio and processing technology; The application scenario optimization module is used to collect the usage data of high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios after preparing a high-performance protective layer, analyze their performance in actual applications, establish a relationship model between the usage scenario and the performance requirements, and use this model to optimize the design parameters of the tag to obtain a product solution that meets the actual application requirements.

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