Preparation method and system of high-performance electronic tag

Abstract

The application relates to a high-performance electronic tag preparation method and system in the field of electronic tag manufacturing, which comprises the following steps: obtaining the working parameters of a high-frequency / NFC electronic tag in a high-temperature environment, analyzing the conductive performance change trend of an antenna material, establishing a mathematical model of the influence of the high-temperature environment on the antenna material, adjusting the component proportion of the antenna material according to the model to obtain an optimized antenna material formula; on the basis of optimizing an electromagnetic shielding scheme, collecting comprehensive performance data of the high-frequency / NFC electronic tag under different environments, establishing a performance prediction model under the coupling action of multiple environmental factors, simulating the working state of the label under complex working conditions by using the model, and judging the performance stability; after accurately processing an antenna pattern, collecting characteristic data of each layer of the high-frequency / NFC electronic tag, establishing a relationship model of material characteristics and adhesive strength, enhancing the interlayer adhesion by using plasma surface treatment technology, and obtaining an optimized adhesive process scheme.

Description

Technical Field

[0001] This invention relates to the field of information technology, specifically to the field of electronic tag manufacturing, and particularly to a method and system for preparing high-performance electronic tags. Background Technology

[0002] As a core component of wireless identification technology, electronic tags are commonly categorized into high-frequency (HF) tags and near-field communication (NFC) tags. In complex environments, the performance stability of electronic tags faces severe challenges. Traditional tag structures are often simple and lack targeted optimization for environmental factors, leading to significant performance degradation under conditions of high temperature, high humidity, or strong electromagnetic interference. For example, high temperatures can cause the conductivity of antenna materials to degrade, high humidity environments can easily cause oxidation of metal layers, and strong electromagnetic interference directly affects signal transmission efficiency. Furthermore, existing testing methods are limited to evaluating 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 overall performance of the tag. In terms of manufacturing processes, traditional methods struggle to precisely control the size and shape of the antenna pattern, resulting in unstable signal transmission efficiency. Simultaneously, insufficient adhesive strength between tag layers makes them prone to delamination under mechanical stress or repeated bending, affecting service life. The existing protective layers have limited abrasion resistance and antistatic properties, which may lead to performance degradation due to wear or static electricity buildup in practical applications. The aforementioned issues directly impact the applicability and reliability of high-frequency / NFC electronic tags. Especially in high-performance scenarios such as industrial automation and logistics tracking, tag performance defects can lead to data reading failures or equipment malfunctions, thereby affecting the overall system's operational efficiency. Therefore, a new structural design and testing method is urgently needed to improve the adaptability and durability of electronic tags in complex environments. Summary of the Invention

[0003] This invention provides a method for preparing a high-performance electronic tag, comprising the following steps:

[0004] Step S101: Obtain the working parameters of the high-frequency / NFC electronic tag in a high-temperature environment, analyze the trend of the change in 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 composition ratio of the antenna material according to the model to obtain the 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 correspondence between humidity and metal oxidation rate, adopt 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 surface of the metal layer, acquire 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 design a multi-layer shielding structure based on the model to obtain an optimized electromagnetic shielding scheme.

[0007] Step S104: Based on the optimization of the electromagnetic shielding scheme, collect comprehensive performance data of high-frequency / NFC electronic tags under different environments, establish a performance prediction model under the coupling effect of multiple environmental factors, use the model to simulate the working state of the tag under complex working conditions, and judge its performance stability.

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

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

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

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

[0012] This invention provides a high-performance electronic tag manufacturing system, mainly comprising:

[0013] The high-temperature environment parameter acquisition module is used to acquire the working parameters of high-frequency / NFC electronic tags in high-temperature environments, analyze the change trend of the conductivity of antenna materials, establish a mathematical model of the influence of high-temperature environment on antenna materials, and adjust the composition ratio of antenna materials according to the model to obtain the optimized antenna material formula.

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

[0015] The electromagnetic interference analysis module is used to acquire signal transmission data of high-frequency / NFC electronic tags in a strong electromagnetic interference environment after a protective film is formed on the surface of the metal layer. It analyzes the degree of influence of the interference source on the signal, establishes a relationship model between electromagnetic interference and signal attenuation, and designs a multi-layer shielding structure based on the model to obtain an optimized electromagnetic shielding scheme.

[0016] The comprehensive performance prediction module is used to collect comprehensive performance data of high-frequency / NFC electronic tags under different environments based on the optimization of electromagnetic shielding scheme, establish a performance prediction model under the coupling effect 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.

[0017] The antenna pattern processing module is used to obtain process parameters in the manufacturing process of high-frequency / NFC electronic tags based on the performance prediction model, analyze the dimensional accuracy of the antenna pattern, establish the correspondence between process parameters and antenna pattern accuracy, and use laser micromachining technology to accurately process 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 the high-frequency / NFC electronic tag after the antenna pattern is precisely processed, analyze the interlayer adhesion strength, establish a relationship model between material properties and adhesion strength, and use plasma surface treatment technology to enhance interlayer adhesion and obtain an optimized adhesion process scheme.

[0019] The protective layer preparation module is used to obtain performance data of high-frequency / NFC electronic tag protective layers from the perspective of optimizing the bonding process, analyze their wear resistance and antistatic properties, establish a relationship model between the performance of the protective layer and the usage environment, use nanocomposite technology to prepare high-performance protective layers, and determine the optimal material ratio and processing technology.

[0020] The application scenario optimization module is used to collect usage data of high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios after the high-performance protective layer is prepared. It analyzes the performance of the tags in actual applications, establishes a relationship model between usage scenarios and performance requirements, and uses this model to optimize the design parameters of the tags to obtain product solutions that meet the needs of actual applications.

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

[0022] This invention discloses a method for manufacturing high-performance electronic tags. The method analyzes the impact of extreme environments such as high temperature, high humidity, and strong electromagnetic interference on tag performance, establishing a performance prediction model under the coupled effects of multiple environmental factors. Laser micromachining technology is used to precisely fabricate antenna patterns, and plasma surface treatment enhances interlayer adhesion. A high-performance protective layer is prepared using nanocomposite materials, improving the tag's wear resistance and antistatic properties. Finally, by analyzing usage data in industrial automation and logistics tracking scenarios, the tag design parameters are optimized to meet practical application requirements. This invention significantly improves the performance stability and reliability of high-frequency / NFC electronic tags in complex environments, laying the foundation for their widespread application in harsh industrial environments. Attached Figure Description

[0023] Figure 1 This is a flowchart of a method for preparing a high-performance electronic tag according to the present invention.

[0024] Figure 2 This is a schematic diagram of a method and system for preparing a high-performance electronic tag according to the present invention.

[0025] Figure 3 This is another schematic diagram of a method and system for preparing a high-performance electronic tag according to the present invention.

[0026] Figure 4 This is a schematic diagram of the structure of a method and system for preparing a high-performance electronic tag according to the present invention. Detailed Implementation

[0027] 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. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0028] like Figure 1-4 The specific method for preparing a high-performance electronic tag in this embodiment may include:

[0029] Step S101: Obtain the operating parameters of the high-frequency / NFC electronic tag under high-temperature environment, analyze the trend of conductivity change of the antenna material, and establish a mathematical model of the impact of high-temperature environment on the antenna material. Based on the model, adjust the component ratio of the antenna material to obtain the optimized antenna material formula.

[0030] The system acquires the operating parameters of high-frequency / NFC electronic tags at different temperatures, including electrical characteristics such as resistance, capacitance, and inductance. Based on these parameters, it analyzes the trend of conductivity changes in antenna materials at different temperatures. A mathematical model is established using linear regression to examine the relationship between conductivity and temperature. Based on this model, the initial composition ratio of the antenna material is determined, including metal content and polymer matrix ratio. A genetic algorithm is used to optimize the composition ratio of the antenna material, yielding at least one optimized material formulation. The optimized antenna material is then prepared based on this formulation. The conductivity of the optimized antenna material is tested at high temperatures to determine if it meets preset performance indicators. If the conductivity does not meet these indicators, the composition ratio of the antenna material is adjusted, and optimization is repeated until a target antenna material that meets the preset performance indicators is obtained.

[0031] Specifically, the operating parameter testing of high-frequency electronic tags needs to be conducted in a temperature-controlled chamber. For example, the temperature is tested in segments from -20°C to 120°C, and the resistance, inductance, and capacitance of the tag antenna are measured at each temperature point. Under standard testing conditions, the resistance of a copper antenna is approximately 0.5 ohms, the inductance is 6 microhenries, and the capacitance is 12 picofarads. As the temperature rises, the resistance of the metal conductor increases, potentially reaching 0.8 ohms at 80°C. Modeling the relationship between conductivity and temperature first requires obtaining resistivity data at different temperatures. Experiments show that the resistivity of conductive silver paste is 2.8 microohms at 20°C, and increases by approximately 0.4% for every 10°C increase in temperature. Substituting the experimental data into a linear regression model yields a linear equation for resistivity versus temperature, which is used for subsequent material formulation optimization. Adjustments to the antenna material formulation focus on the ratio of conductive filler to polymer matrix. In the conductive silver paste, increasing the silver powder content from 75% to 85% significantly improves conductivity but reduces adhesion. Reducing the epoxy resin matrix ratio from 20% to 15% improves conductivity but affects material toughness. An orthogonal experiment was used to determine the optimal ratio, such as 80% silver powder, 18% resin, and 2% curing agent. During genetic algorithm optimization, parameters such as silver powder content and resin ratio were encoded as genes, and the fitness function was set as a high-temperature conductivity index. An initial population of twenty formulations was used, and iterative optimization was achieved through selection, crossover, and mutation. After fifty generations of evolution, the optimal formulation was obtained: 78% nano-silver powder, 7% micron-silver powder, 13% modified epoxy resin, and 2% curing agent. During formulation optimization verification, the sample was placed in a 120°C high-temperature chamber for four hours, with resistance measured every hour. The results showed that the resistance increased from 0.6 ohms at room temperature to 1.2 ohms, meeting the requirement of less than 1.5 ohms. After successful heat resistance verification, antenna pattern printing tests were conducted to confirm that the material viscosity and curing characteristics met the process requirements. Ultimately, this formulation was determined to meet high-temperature operating conditions and possess excellent overall performance. To further improve the antenna material formulation, the stability of the conductive network can be enhanced by adding conductive carbon nanotubes, or surface modification techniques can be used to strengthen the interfacial bonding between the metal powder and the resin matrix. Simultaneously, multiple factors such as conductivity, processability, and cost need to be balanced to achieve overall formulation optimization.

[0032] Step S102: Starting from the optimized antenna material formulation, collect operating data of high-frequency / NFC electronic tags in a high-humidity environment, monitor the oxidation degree of the metal layer, and establish the correlation between humidity and metal oxidation rate. Using anti-oxidation coating technology, form a protective film on the metal layer surface, and determine the optimal coating thickness and material.

[0033] The process involves: obtaining an optimized antenna material formulation; placing a high-frequency / NFC electronic tag in a high-humidity environment; monitoring the oxidation level of the metal layer using sensors to obtain data on humidity and metal oxidation rate; determining the target coating thickness of the protective film on the metal layer surface based on a pre-established relationship between the humidity and the metal oxidation rate; analyzing the relationship between the protective film coating thickness and the metal oxidation rate using a machine learning algorithm to obtain the optimal coating thickness; forming a protective film on the metal layer surface using chemical vapor deposition based on the optimal coating thickness; observing the uniformity of the protective film using a scanning electron microscope to determine whether the coating quality meets a preset standard; if the coating quality meets the preset standard, determining the final coating material and thickness; if the coating quality does not meet the preset standard, adjusting the coating parameters and repeating chemical vapor deposition.

[0034] Specifically, high-frequency tags are susceptible to corrosion in high-humidity environments. To effectively monitor the oxidation level of the metal layer in humid environments, conductivity sensors can be used to detect the electrical properties of the metal substrate in real time. For example, when the humidity reaches 70% or higher, traditional copper-based electronic tags will show significant surface oxidation within a few hours, resulting in a decrease in conductivity of more than 30%. Accelerated testing of tag samples in a constant temperature and humidity chamber was conducted to record the oxidation level corresponding to different humidity levels. In an environment with 90% humidity, the oxidation rate of the copper layer is approximately 0.03 micrometers per hour. Based on the collected data, a correlation model between humidity and oxidation rate can be established, providing a basis for subsequent coating design. For the anti-oxidation coating, epoxy resin materials can be used. These materials have good moisture resistance and high temperature resistance. The protective effect can be effectively controlled by adjusting the coating thickness. For example, when the coating thickness is 5 micrometers, the oxidation rate of the metal layer in a 90% humidity environment can be reduced to below 0.005 micrometers per hour. In terms of coating technology, chemical vapor deposition (CVD) 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. Optimal coating quality is achieved when the reaction chamber temperature is controlled at around 150 degrees Celsius and the gas flow rate is 50 ml per minute. Analyzing extensive experimental data using machine learning methods reveals the optimal balance between coating thickness and protective performance. Models are built using algorithms such as support vector machines to predict coating performance under different process parameters. Practical experience shows that a coating thickness between four and six micrometers ensures protective effectiveness without compromising the tag's RFID performance. Scanning electron microscopy observation reveals that a high-quality coating surface should be free of defects such as cracks and bubbles. Analysis of the coating surface morphology reveals that if local thickness deviations exceed 10% or pinhole defects are found, process parameters need to be readjusted. After multiple optimizations, a final coating thickness of 5.5 micrometers was determined, enabling the tag to operate stably for over 1000 hours in an environment with 95% humidity.

[0035] Step S103: After forming a protective film on the surface of the metal layer, acquire signal transmission data of the high-frequency / NFC electronic tag under strong electromagnetic interference environment, analyze the degree of influence of interference sources on the signal, and establish a relationship model between electromagnetic interference and signal attenuation. Based on this model, design a multi-layer shielding structure to obtain an optimized electromagnetic shielding scheme.

[0036] The process involves: acquiring the signal strength value of a high-frequency / NFC electronic tag in a preset electromagnetic interference environment; extracting the signal attenuation characteristics at different frequencies using a Fourier transform algorithm to establish a signal attenuation characteristic database; constructing a correlation model between electromagnetic interference intensity and signal attenuation using a multiple linear regression algorithm based on the signal attenuation characteristic database; calculating the attenuation effect of different shielding layer thicknesses on electromagnetic interference using a finite element analysis method based on the correlation model to obtain shielding effect data; optimizing the multi-layer shielding structure using a genetic algorithm based on the shielding effect data to obtain the optimal thickness combination of each shielding material; simulating the signal transmission of the electronic tag in a strong electromagnetic interference environment using electromagnetic field simulation software to obtain the optimized signal strength value; determining the optimization scheme if the optimized signal strength value reaches a preset threshold; otherwise, adjusting the shielding layer material parameters and recalculating the optimization.

[0037] Specifically, electromagnetic field simulation software can accurately model antenna structures using 3D modeling and calculate electromagnetic field distribution using the finite-difference time-domain method. For example, after generating a 50-micrometer-thick aluminum oxide protective film on the surface of a high-frequency electronic tag, the software can be set to a working frequency of 13.56 MHz, an external interference source of 50 Hz power frequency interference, and an interference intensity of 1 kV / m. The signal strength values ​​obtained through simulation are represented by changes in amplitude and phase, and this data can be used for subsequent analysis. Fourier transform algorithms can convert time-domain signals to the frequency domain and extract key frequency components. For example, after performing a fast Fourier transform on the acquired signal, attenuation characteristics at different frequencies can be obtained, such as 10 dB attenuation caused by power frequency interference and 5 dB attenuation caused by higher harmonics. This characteristic data constitutes a database, providing a foundation for subsequent modeling. Multiple linear regression algorithms predict signal attenuation under different interference environments by establishing a mathematical model of electromagnetic interference intensity and signal attenuation. For example, factors such as interference source intensity, distance, and frequency can be used as independent variables, and signal attenuation value as the dependent variable to establish a regression equation. This correlation model can be used to optimize shielding layer design. The finite element method (FEM) discretizes a continuous medium into a finite number of elements and calculates the electromagnetic field distribution. By setting metal shielding layers of varying thicknesses, such as copper foil layers ranging from 10 to 100 micrometers and aluminum foil layers from 20 to 200 micrometers, the shielding effectiveness of various combinations is analyzed. This data can be used to optimize multi-layer shielding structures. A genetic algorithm searches for the optimal solution by simulating biological evolution. With a population size of 100, 1000 iterations, a crossover probability of 0.8, and a mutation probability of 0.1, the optimal combination of shielding layer thicknesses can be obtained. For example, a structure with an outer copper foil layer thickness of 80 micrometers and a middle aluminum foil layer thickness of 150 micrometers exhibits 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 signal transmission performance. If the signal attenuation is less than 15 dB under an interference intensity of 1000 volts per meter, the optimization scheme is proven feasible. If the attenuation exceeds the threshold, material parameters need to be adjusted, such as increasing the number of shielding layers or changing the material type, and the optimization calculation needs to be repeated. This iterative optimization method ensures that a shielding structure design that meets the requirements is ultimately obtained.

[0038] Step S104: Based on the optimized electromagnetic shielding scheme, collect comprehensive performance data of high-frequency / NFC electronic tags under different environments, and establish a performance prediction model under the coupled effects of multiple environmental factors. Using this model, simulate the working state of the tags under complex working conditions and determine their performance stability.

[0039] The process involves: acquiring performance data of a high-frequency beacon under different environments; analyzing the impact of environmental factors on the high-frequency beacon based on the performance data, and establishing a coupling effect model; using the coupling effect model to simulate the working state of the high-frequency beacon under complex conditions; extracting key parameters of the high-frequency beacon based on the working state and inputting them into a prediction model; determining the stability of the high-frequency beacon under different environments using the prediction model; adjusting the electromagnetic shielding scheme if the stability is lower than a preset threshold and reacquiring the performance data; updating the prediction model based on the adjusted performance data to obtain the optimized performance of the high-frequency beacon.

[0040] Specifically, electromagnetic shielding optimization first needs to consider the impact of multiple environmental factors on the performance of high-frequency tags. In metallic environments, induced currents are generated on metal surfaces, forming a reflected field that leads to tag signal attenuation. For example, in a steel plant environment, when a high-frequency tag is subjected to strong magnetic field interference, 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 model needs to consider multiple factors such as temperature and humidity. Taking temperature as an example, when the ambient temperature rises from room temperature to 100 degrees Celsius, the tag antenna resonant frequency will drift, resulting in a shortened reading distance. By adding temperature compensation material to the tag substrate, the frequency drift can be controlled within 0.5%. Humidity also has a significant impact on tag performance. When the relative humidity reaches 95%, the tag impedance will change, and the signal attenuation can reach 15 dB. In complex operating condition simulations, the superimposed effects of multiple environmental factors need to be considered simultaneously. For example, in a chemical plant environment, high-frequency tags are 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 operating conditions can be predicted. Experimental data shows that by adopting a multi-layered composite protection structure, the tag's reading success rate under complex working conditions can be increased to over 95%. The key parameter prediction model mainly includes indicators such as signal strength, reading distance, and frequency stability. Taking a certain type of high-frequency tag as an example, the reading distance can reach one meter under normal working conditions, with a signal strength of -25 dB. When the environment changes, the prediction model can evaluate the tag's performance in real time. For example, for every 10-degree increase in temperature, the reading distance will decrease by 5%, and the signal strength will decrease by 2 dB. For cases where the prediction results show substandard performance, the electromagnetic shielding scheme needs to be optimized. If the prediction model finds that the tag's stability is below 85%, performance can be improved by adjusting the shielding layer thickness and adding absorbing materials. Practice shows that using a gradient composite shielding structure can enable the tag to maintain over 90% stability in harsh environments. Continuous collection of performance data and model updates can continuously improve the tag's adaptability to various environments.

[0041] Step S105: Starting from the performance prediction model, obtain the process parameters in the high-frequency / NFC electronic tag manufacturing process, analyze the dimensional accuracy of the antenna pattern, and establish the correspondence between process parameters and antenna pattern accuracy. Use laser micromachining technology to precisely process the antenna pattern on the substrate and determine the optimal processing parameters.

[0042] A performance prediction model and manufacturing process parameters for high-frequency / NFC electronic tag antenna patterns are obtained. Based on the performance prediction model, a correspondence is established between the manufacturing process parameters and the antenna pattern size accuracy. Laser micromachining technology is used to perform antenna pattern processing experiments on a preset substrate. Antenna pattern size data under different processing parameters is obtained, and the size data is compared with a preset size accuracy threshold. If the size data meets the preset size accuracy threshold, the corresponding processing parameters are determined as the optimal processing parameters. If the size data does not meet the preset size accuracy threshold, the laser micromachining parameters are adjusted, and the antenna pattern processing experiment is repeated. Based on the determined optimal processing parameters, a manufacturing process optimization scheme for high-frequency / NFC electronic tags is generated.

[0043] Specifically, the manufacturing process of high-frequency / NFC electronic tags involves the precision control of antenna patterns, which directly affects tag performance and reading distance. Antenna pattern dimensional accuracy requirements are typically at the micrometer level, with linewidth and spacing being particularly critical. Manufacturing process parameters include laser power, scanning speed, and pulse width, which affect etching depth and edge sharpness. Performance prediction models can be used to analyze the relationship between antenna size and reading distance; for example, a 5% increase in linewidth can lead to a resonant frequency shift of approximately 3%. Dimensional accuracy analysis of antenna patterns requires consideration of multiple aspects. First, the substrate characteristics are crucial; different substrates respond differently to laser processing. For instance, polyester film and polyimide film exhibit different thermal response characteristics during laser processing. Second, environmental factors are important; humidity and temperature affect processing accuracy. A 10-degree increase in room temperature can cause thermal expansion of the substrate, affecting the actual processed dimensions. Establishing the correspondence between process parameters and dimensional accuracy requires extensive experimental data. For example, on a polyester substrate, setting the laser power to 8 watts and the scanning speed to 1000 millimeters per second yields an antenna pattern with a linewidth error of less than 10 micrometers. This parameter combination is recorded as a baseline, and by changing individual parameters and observing the changes in accuracy, a parameter matrix is ​​ultimately formed. In laser micromachining experiments, the impact of processing parameters on edge quality is crucial. High laser power may cause edge melting, while excessively low power may result in incomplete processing. Accurate assessment of processing quality can be achieved by observing edge morphology under a microscope and measuring actual dimensions using a profilometer. Typical processing parameters range from six to ten watts of power and scanning speeds from 800 to 1200 millimeters per second. Dimensional accuracy is assessed using a multi-point sampling method, measuring key locations in the antenna pattern. A preset accuracy threshold is typically ±5% of the design size. When measurement results show that a set of parameters consistently meets the requirements, repeatability verification is necessary. If ten consecutive samples meet the accuracy requirements, this set of parameters can be considered the optimal process parameters. Process parameter optimization is an iterative process. If edge roughness exceeds the standard, it can be improved by adjusting the pulse frequency. If insufficient processing depth is found, the scanning speed can be appropriately reduced or the number of repetitions increased. The final manufacturing process scheme needs to include a complete set of parameters to ensure process repeatability and stability.

[0044] Step S106: After precisely processing the antenna pattern, collect the characteristic data of each layer of the high-frequency / NFC electronic tag material, analyze the interlayer adhesion strength, and establish a relationship model between material properties and adhesion strength. Plasma surface treatment technology is used to enhance interlayer adhesion, resulting in an optimized adhesion process.

[0045] Acquire material property data for each layer of the high-frequency / NFC electronic tag to determine material and layer properties. Based on the acquired data, analyze interlayer adhesion strength and establish a model relating material properties to adhesion strength. Utilize plasma surface treatment technology to optimize interlayer adhesion strength, obtaining an optimized solution. For the optimized solution, assess the impact of plasma surface treatment on adhesion strength. If the increase in adhesion strength is insufficient, adjust the treatment parameters and re-analyze the interlayer adhesion strength. Employ machine learning algorithms to train an analysis model based on the acquired data and the optimized solution, predicting the relationship between different material properties and adhesion strength. Based on the prediction results, determine the optimal process scheme, optimizing interlayer adhesion strength through surface treatment and processing technologies. For the process scheme, assess the compatibility of each layer of the electronic tag material. If compatibility is insufficient, adjust material properties and re-establish the relationship model. Through processing technologies and optimization schemes, ultimately determine the bonding process scheme for the high-frequency / NFC electronic tag to maximize interlayer adhesion strength.

[0046] Specifically, the data acquisition of multilayer material properties for high-frequency and electronic tags mainly focuses on the properties of materials such as the substrate, conductive layer, and adhesive layer. Taking polyethylene terephthalate (PET) as an example, its surface energy is 32 millinewtons per meter, and its contact angle with the copper conductive layer is 75 degrees. These data directly affect the interlayer bonding strength. During the acquisition process, tensile strength tests are used to obtain interlayer bonding strength data; for example, the untreated bonding strength is 0.5 MPa. Modeling the relationship between interlayer material properties and bonding strength requires considering factors such as material surface energy and the content of polar groups. Taking polymer substrates as an example, the content of surface polar groups is positively correlated with bonding strength. Plasma treatment can increase the oxygen-containing groups on the surface by 30%, thereby improving the bonding strength to 1.2 MPa. Plasma surface treatment uses oxygen as the working gas, with a power setting of 100 watts and a treatment time of 60 seconds, which can form polar groups such as hydroxyl and carboxyl groups on the material surface. The surface treatment effect is evaluated through tensile peel tests. If the bond strength after treatment is lower than the preset threshold of 1 MPa, the plasma treatment parameters need to be adjusted. For example, the processing power can be increased to 150 watts, or the processing time extended to 90 seconds, until the target bonding strength is achieved. Historical data is analyzed using machine learning algorithms to establish a predictive model of the relationship between processing parameters and bonding strength. Taking a support vector machine as an example, input variables include processing power, time, and gas flow rate, while the output variable is interlayer bonding strength. In optimizing the process, the thermal properties and chemical compatibility of the materials must be considered. For example, the difference in thermal expansion coefficients between conductive silver paste and polyester substrate may lead to interlayer stress, requiring the addition of elastomer modifiers to adjust material properties. After material modification, a new relationship model is established to ensure the stability of the interlayer structure. Surface properties are optimized through plasma treatment; for example, under a processing power of 120 watts and a time of 75 seconds, the interlayer bonding strength can be increased to 1.5 MPa, and good stability is observed in temperature resistance tests. The final bonding process scheme needs to comprehensively consider production efficiency and cost factors. Taking a roll-to-roll production line as an example, a plasma processing speed of 5 meters per minute and a processing width of 300 millimeters can achieve continuous production. The optimized product exhibited a bond strength of 1.8 MPa in a 90-degree peel test and maintained structural integrity in a temperature and humidity cycling test.

[0047] Step S107: Starting with optimizing the bonding process, obtain performance data of the high-frequency / NFC electronic tag protective layer, analyze its wear resistance and antistatic properties, and establish a model relating the protective layer performance to the usage environment. High-performance protective layers are prepared using nanocomposite material technology, and the optimal material ratio and processing technology are determined.

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

[0049] Specifically, in high-frequency electronic tags, the protective layer, as the outermost material, is in direct contact with the external environment, and its performance significantly impacts the tag's lifespan and reliability. Abrasion resistance and antistatic properties are key indicators of the protective layer. Abrasion resistance data can be obtained using a friction coefficient tester, with test conditions including friction force, contact pressure, and speed. Antistatic properties can be measured using a surface resistivity tester, recording changes in resistance under different humidity conditions. Taking polyester material as an example, in abrasion resistance tests conducted under standard conditions, with a friction force of 5 Newtons and a speed of 2 centimeters per second, after 10,000 cycles of reciprocating friction, the increase in surface roughness is within 0.05 micrometers, demonstrating excellent abrasion resistance. In antistatic tests, with a relative humidity of 60% and a temperature of 25 degrees Celsius, the surface resistivity remains at 10^9 ohms per square meter, meeting antistatic requirements. Nanocomposite technology, by adding nano-alumina particles to the polyester matrix, can significantly improve the performance of the protective layer. When the nanoparticle content is 3%, the material's wear resistance increases by 40%, while the surface resistivity decreases to 10⁸ ohms per square meter. This improvement stems from the reinforcing effect of the nanoparticles and the formation of a conductive network. Under different environmental conditions, such as high temperature and high humidity, the protective layer's performance fluctuates. Experiments show that when the ambient temperature rises to 40 degrees Celsius and the relative humidity reaches 85%, the wear resistance of the nanocomposite material decreases by only 10%, while that of ordinary materials decreases by 30%. This indicates that the nanocomposite material has better environmental adaptability. By establishing a performance-environment relationship model, the performance of the protective layer under specific conditions can be predicted. For example, in a cold, dry environment, at a temperature of -20 degrees Celsius and a relative humidity of 20%, the model predicts that the surface resistivity of the nanocomposite material will increase to 10¹⁰ ohms per square meter, but still within an acceptable range. This predictive ability helps assess the reliability of the label in different application scenarios. For different application needs, performance can be optimized by adjusting the type and content of nanoparticles. For example, in applications requiring higher wear resistance, nano-zirconia can be added; when the content is 5%, the wear resistance can be increased to twice the original level. When used in environments with high static electricity, nano-carbon materials can be added to achieve better antistatic effects. This flexible material design provides customized solutions for different application scenarios.

[0050] Step S108: After preparing the high-performance protective layer, data on the use of high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios are collected. Their performance in practical applications is analyzed, and a relationship model between usage scenarios and performance requirements is established. Using this model, the tag design parameters are optimized to obtain a product solution that meets the needs of practical applications.

[0051] This process involves acquiring usage data of high-frequency / NFC electronic tags in industrial and logistics scenarios; analyzing the tag performance under different protective layer thicknesses based on the usage data, and establishing a tag performance model; establishing the relationship between the industrial scenario model, the logistics scenario model, and the tag performance model; using the relationship between the scenario model and the performance model to determine the optimization direction of tag design parameters; obtaining the optimized design parameters to generate a tag product solution that meets application requirements; evaluating the adaptability of the product solution in different scenarios through the performance model; if the adaptability of the product solution in industrial scenarios is lower than a preset industrial threshold, adjusting the protective layer thickness in the design parameters; if the adaptability of the product solution in logistics scenarios is lower than a preset logistics threshold, adjusting the antenna size in the design parameters; and using the adjusted design parameters to obtain a high-frequency / NFC electronic tag product that meets the needs of industrial and logistics scenarios.

[0052] Specifically, the application environments of high-frequency / NFC electronic tags in industrial and logistics scenarios have distinct characteristics. Industrial scenarios involve complex factors such as high temperatures, vibration, and dust, requiring tags to have enhanced protective layers with improved wear resistance and anti-interference capabilities. For example, on welding production lines, tags can withstand instantaneous temperatures reaching 80 degrees Celsius and vibration frequencies of approximately 20 Hz per second; in such cases, a protective layer thickness of at least 0.6 millimeters is necessary for effective protection. Logistics scenarios primarily face mechanical stresses such as impacts and compression, placing higher demands on antenna size design. For instance, in express delivery sorting, tags withstand instantaneous impact forces of approximately 500 Newtons; excessively large antennas are prone to deformation, so it is recommended to keep the antenna length within 40 millimeters. By collecting this environmental data, scenario models can be established, quantifying environmental factors into specific parameters. Performance models reflect the tag's performance under different operating conditions. Taking reading distance as an example, in industrial environments, interference from metal equipment is significant, causing reading distance to decrease by about 30%. Increasing the thickness of the protective layer can reduce this attenuation. In logistics scenarios, tag deformation can cause antenna resonant frequency shifts, affecting reading stability, necessitating optimization of the antenna structure design. Correlation between scenario models and performance models can guide tag design optimization. In industrial scenarios, for every 0.1 mm increase in protective layer thickness, anti-interference capability improves by approximately 15%, but the weight increases by 8%. In logistics scenarios, a 10% reduction in antenna size improves impact resistance by 20%, but reduces reading distance by 12%. Balancing these factors allows for the determination of optimal design parameters. In practical applications, a field test in an industrial setting revealed a tag failure rate of 8%, exceeding the preset 5% threshold. Analysis showed that insufficient protective layer thickness caused damage to internal components. Increasing the thickness from 0.4 mm to 0.6 mm reduced the failure rate to 3%. In logistics scenario testing, the tag recognition accuracy was 92%, lower than the preset 95%. Analysis indicated this was caused by an excessively large antenna size. Reducing the length from 50 mm to 40 mm improved the accuracy to 97%. The final product solution comprehensively considers the needs of both scenarios, employing a 0.6 mm thick protective layer and a 40 mm antenna length. In the industrial environment, the failure rate remains stable below 3%, while in the logistics environment, the recognition accuracy remains above 97%, achieving the expected performance goals.

[0053] This invention provides a high-performance electronic tag manufacturing system, mainly comprising:

[0054] The high-temperature environment parameter acquisition module is used to acquire the working parameters of high-frequency / NFC electronic tags in high-temperature environments, analyze the change trend of the conductivity of antenna materials, establish a mathematical model of the influence of high-temperature environment on antenna materials, and adjust the composition ratio of antenna materials according to the model to obtain the optimized antenna material formula.

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

[0056] The electromagnetic interference analysis module is used to acquire signal transmission data of high-frequency / NFC electronic tags in a strong electromagnetic interference environment after a protective film is formed on the surface of the metal layer. It analyzes the degree of influence of the interference source on the signal, establishes a relationship model between electromagnetic interference and signal attenuation, and designs a multi-layer shielding structure based on the model to obtain an optimized electromagnetic shielding scheme.

[0057] The comprehensive performance prediction module is used to collect comprehensive performance data of high-frequency / NFC electronic tags under different environments based on the optimization of electromagnetic shielding scheme, establish a performance prediction model under the coupling effect 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.

[0058] The antenna pattern processing module is used to obtain process parameters in the manufacturing process of high-frequency / NFC electronic tags based on the performance prediction model, analyze the dimensional accuracy of the antenna pattern, establish the correspondence between process parameters and antenna pattern accuracy, and use laser micromachining technology to accurately 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 the high-frequency / NFC electronic tag after the antenna pattern is precisely processed, analyze the interlayer adhesion strength, establish a relationship model between material properties and adhesion strength, and use plasma surface treatment technology to enhance interlayer adhesion and obtain an optimized adhesion process scheme.

[0060] The protective layer preparation module is used to obtain performance data of high-frequency / NFC electronic tag protective layers from the perspective of optimizing the bonding process, analyze their wear resistance and antistatic properties, establish a relationship model between the performance of the protective layer and the usage environment, use nanocomposite technology to prepare high-performance protective layers, and determine the optimal material ratio and processing technology.

[0061] The application scenario optimization module is used to collect usage data of high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios after the high-performance protective layer is prepared. It analyzes the performance of the tags in actual applications, establishes a relationship model between usage scenarios and performance requirements, and uses this model to optimize the design parameters of the tags to obtain product solutions that meet the needs of actual applications.

[0062] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection 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 working parameters of the high-frequency / NFC electronic tag in a high-temperature environment, analyze the trend of the change in 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 composition ratio of the antenna material according to the model to obtain the optimized antenna material formula. 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 correspondence between humidity and metal oxidation rate, adopt 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, acquire 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 design a multi-layer shielding structure based on the model to obtain an optimized electromagnetic shielding scheme. Step S104: Based on the optimization of the electromagnetic shielding scheme, collect comprehensive performance data of high-frequency / NFC electronic tags under different environments, establish a performance prediction model under the coupling effect of multiple environmental factors, use the 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 high-frequency / NFC electronic tag manufacturing process, analyze the dimensional accuracy of the antenna pattern, establish the correspondence between process parameters and antenna pattern accuracy, use laser micromachining technology to accurately process the antenna pattern on the substrate, and determine the optimal processing parameters. Step S106: After accurately processing the antenna pattern, collect the characteristic data of each layer of the high-frequency / NFC electronic tag material, analyze the interlayer adhesion strength, establish a relationship model between material characteristics and adhesion strength, and use plasma surface treatment technology to enhance interlayer adhesion and obtain an optimized adhesion process scheme. Step S107: Starting from optimizing the bonding process, obtain the performance data of the high-frequency / NFC electronic tag protective layer, analyze its wear resistance and antistatic properties, establish a relationship model between the performance of the protective layer and the usage environment, use 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 usage data of high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios, analyze their performance in practical applications, establish a relationship model between usage scenarios and performance requirements, and use this model to optimize the design parameters of the tags to obtain a product solution that meets the needs of practical applications.

2. The method for preparing a high-performance electronic tag according to claim 1, characterized in that, Step S101 includes: The operating parameters of high-frequency / NFC electronic tags at different temperatures are obtained, including the electrical characteristics of resistance, capacitance, and inductance. Based on the operating parameters, the trend of the conductivity of the antenna material at different temperatures was analyzed. A mathematical model was established using linear regression to investigate the relationship between electrical conductivity and temperature. Based on the mathematical model, the initial composition ratio of the antenna material is determined, including the metal content and the polymer matrix ratio. A genetic algorithm is used to optimize the composition ratio of the antenna material to obtain at least one optimized material formula; Based on the optimized material formulation, the optimized antenna material was prepared. The conductivity of the optimized antenna material was tested under high temperature conditions to determine whether the conductivity met the preset performance indicators. If the conductivity does not meet the preset performance index, the composition ratio of the antenna material is adjusted and optimized again until a target antenna material that meets the preset performance index is obtained.

3. The method for preparing a high-performance electronic tag according to claim 1, characterized in that, Step S102 includes: Obtain the optimized antenna material formula; Place high-frequency / NFC electronic tags in a high-humidity environment; The degree of oxidation of the metal layer is monitored by sensors to obtain data on humidity value and metal oxidation rate. The target coating thickness of the protective film on the metal layer surface is determined based on the pre-established relationship between the humidity value and the metal oxidation rate. The relationship between the protective film coating thickness and the metal oxidation rate was analyzed using machine learning algorithms to obtain the optimal coating thickness. Based on the optimal coating thickness, a protective film is formed on the surface of the metal layer using chemical vapor deposition technology; The uniformity of the protective film is observed by scanning electron microscopy to determine whether the coating quality of the protective film meets the preset standard. If the coating quality meets the preset standard, then the final coating material and thickness are determined; If the coating quality does not meet the preset standard, the coating parameters are adjusted and chemical vapor deposition is performed again.

4. The method for preparing a high-performance electronic tag according to claim 1, characterized in that, Step S103 includes: Acquire the signal strength value of high-frequency / NFC electronic tags in a preset electromagnetic interference environment; For the signal strength value, the Fourier transform algorithm is used to extract the signal attenuation characteristics at different frequencies and establish a signal attenuation characteristic database. Based on the signal attenuation feature database, a correlation model between electromagnetic interference intensity and signal attenuation degree is constructed using a multiple linear regression algorithm. Based on the aforementioned correlation model, the finite element analysis method is used to calculate the attenuation effect of different shielding layer thicknesses on electromagnetic interference, and the shielding effect data is obtained. Based on the shielding effect data, a genetic algorithm was used to optimize the multi-layer shielding structure and obtain the optimal combination of thicknesses for each layer of shielding material. Based on the optimized shielding structure, electromagnetic field simulation software was used to simulate the signal transmission of electronic tags in a strong electromagnetic interference environment and obtain the optimized signal strength value. If the optimized signal strength value reaches a preset threshold, then the optimization scheme is determined; If the target is not met, adjust the shielding layer material parameters and recalculate for optimization.

5. A method for preparing a high-performance electronic tag according to any one of claims 1-4, characterized in that, Step S104 includes: Obtain performance data of high-frequency targets under different environments; Based on the performance data, the impact of environmental factors on the high-frequency standard is analyzed, and a coupling effect model is established; The coupling model is used to simulate the working state of the high-frequency beacon under complex working conditions; Based on the operating status, extract the key parameters of the high-frequency target and input them into the prediction model; The stability of the high-frequency standard under different environments is determined using the prediction model. If the stability is lower than a preset threshold, adjust the electromagnetic shielding scheme and reacquire the performance data; Based on the adjusted performance data, the prediction model is updated to obtain the optimized high-frequency standard performance.

6. The method for preparing a high-performance electronic tag according to any one of claims 1-4, characterized in that, Step S105 includes: Obtain performance prediction models and manufacturing process parameters for high-frequency / NFC electronic tag antenna patterns; Based on the performance prediction model, establish the correspondence between the manufacturing process parameters and the antenna pattern size accuracy; An experiment was conducted to process antenna patterns on a pre-defined substrate using laser micromachining technology. Obtain antenna pattern size data under different processing parameters, and compare the size data with a preset size accuracy threshold; If the dimensional data meets the preset dimensional accuracy threshold, then the corresponding processing parameters are determined as the optimal processing parameters; If the size data does not meet the preset size accuracy threshold, the laser micromachining parameters are adjusted, and the antenna pattern processing experiment is repeated. Based on the determined optimal processing parameters, a manufacturing process optimization scheme for high-frequency / NFC electronic tags is generated.

7. A method for preparing a high-performance electronic tag according to any one of claims 1-4, characterized in that, Step S106 includes: Acquire material property data for each layer of high-frequency / NFC electronic tags, determine material properties and layer properties, analyze interlayer adhesion strength based on the collected data, and establish a relationship model between material properties and adhesion strength; Plasma surface treatment technology was used to optimize interlayer adhesion strength, and an optimized solution was obtained through the treatment technology. For the optimized solution, determine the impact of plasma surface treatment on adhesion strength. If the adhesion strength improvement is insufficient, adjust the treatment parameters and re-analyze the interlayer adhesion strength. Using machine learning algorithms, based on collected data and optimization schemes, an analysis model is trained to predict the relationship between different material properties and viscous strength. Based on the prediction results, the optimal process scheme is determined, and the interlayer adhesion strength is optimized through surface treatment and processing technology. For the process scheme, determine the compatibility of each layer of materials in the electronic tag. If the compatibility is insufficient, adjust the material properties and re-establish the relationship model. Through processing technology and optimization schemes, the final bonding process scheme for high-frequency / NFC electronic tags was determined to maximize the interlayer adhesive strength.

8. A method for preparing a high-performance electronic tag according to any one of claims 1-4, characterized in that, Step S107 includes: Obtain data on the abrasion resistance and antistatic properties of the protective layer of high-frequency / NFC electronic tags; Based on the performance data, analyze the performance of the protective layer under different usage environments; High-performance protective layer samples were prepared using nanocomposite material technology; The prepared samples were tested for wear resistance and antistatic properties under different environmental conditions. If the performance of the sample reaches a preset threshold, then the material ratio and processing technology are determined to be the optimal solution; Based on the optimal solution, establish a model relating the performance of the protective layer to the usage environment; The performance of the protective layer under specific environments is predicted using the relationship model.

9. A high-performance electronic tag manufacturing system, characterized in that, This system is used to implement the method for preparing a high-performance electronic tag according to any one of claims 1-8, the system comprising: The high-temperature environment parameter acquisition module is used to acquire the working parameters of high-frequency / NFC electronic tags in high-temperature environments, analyze the change trend of the conductivity of antenna materials, establish a mathematical model of the influence of high-temperature environment on antenna materials, and adjust the composition ratio of antenna materials according to the model to obtain the optimized antenna material formula. The humidity environment monitoring module is used to collect the working data of high-frequency / NFC electronic tags in high humidity environments based on the optimized antenna material formula, monitor the oxidation degree of the metal layer, establish the correspondence between humidity and metal oxidation rate, and use anti-oxidation coating technology to form a protective film on the surface of the metal layer to determine the optimal coating thickness and material. The electromagnetic interference analysis module is used to acquire signal transmission data of high-frequency / NFC electronic tags in a strong electromagnetic interference environment after a protective film is formed on the surface of the metal layer. It analyzes the degree of influence of the interference source on the signal, establishes a relationship model between electromagnetic interference and signal attenuation, and designs a multi-layer shielding structure based on the model to obtain an optimized electromagnetic shielding scheme. The comprehensive performance prediction module is used to collect comprehensive performance data of high-frequency / NFC electronic tags under different environments based on the optimization of electromagnetic shielding scheme, establish a performance prediction model under the coupling effect 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. The antenna pattern processing module is used to obtain process parameters in the manufacturing process of high-frequency / NFC electronic tags based on the performance prediction model, analyze the dimensional accuracy of the antenna pattern, establish the correspondence between process parameters and antenna pattern accuracy, and use laser micromachining technology to accurately process the antenna pattern on the substrate and determine the optimal processing parameters. The interlayer adhesion optimization module is used to collect the characteristic data of each layer of the high-frequency / NFC electronic tag after the antenna pattern is precisely processed, analyze the interlayer adhesion strength, establish a relationship model between material properties and adhesion strength, and use plasma surface treatment technology to enhance interlayer adhesion and obtain an optimized adhesion process scheme. The protective layer preparation module is used to obtain performance data of high-frequency / NFC electronic tag protective layers from the perspective of optimizing the bonding process, analyze their wear resistance and antistatic properties, establish a relationship model between the performance of the protective layer and the usage environment, use nanocomposite technology to prepare high-performance protective layers, and determine the optimal material ratio and processing technology. The application scenario optimization module is used to collect usage data of high-frequency / NFC electronic tags in industrial automation and logistics tracking scenarios after the high-performance protective layer is prepared. It analyzes the performance of the tags in actual applications, establishes a relationship model between usage scenarios and performance requirements, and uses this model to optimize the design parameters of the tags to obtain product solutions that meet the needs of actual applications.

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