Electromagnetic shielding effectiveness evaluation method

Abstract

The invention discloses an electromagnetic shielding effectiveness evaluation method, and particularly relates to the field of electromagnetic shielding of nanocrystalline strips, comprising the following steps: establishing an interface electromagnetic resonance model based on a detected nanocrystalline strip composite material, the interface electromagnetic resonance model being used for analyzing electromagnetic wave reflection and scattering effects of the nanocrystalline strip composite material; the influence of the interface resonance frequency and the electromagnetic impedance matching on the shielding effectiveness is quantified; the nanocrystalline strip composite material is formed by compounding a nanocrystalline strip and other materials; the coupling mechanism of electromagnetic energy transmission in the nanocrystalline strip composite material is analyzed based on the contribution of the interface polarization effect, impedance matching and different material characteristics to energy loss. The shielding effectiveness of the nanocrystalline strip composite material is evaluated by constructing an interface electromagnetic resonance model and combining an energy coupling mechanism, a shielding performance prediction model and a genetic algorithm optimization process, so that the problems that the material combination performance cannot be accurately predicted and the composite proportion is difficult to optimize in the prior art are solved.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic shielding technology for nanocrystalline ribbons, and more specifically, to a method for evaluating electromagnetic shielding effectiveness. Background Technology

[0002] Electromagnetic shielding of nanocrystalline ribbons refers to the use of ribbon materials with nanocrystalline structures to block the transmission of electromagnetic waves by absorbing, reflecting or scattering them, thereby reducing their interference with the surrounding environment or equipment. Its superior shielding effectiveness comes from the special electronic structure and high specific surface area of ​​nanoscale grains, which can provide effective electromagnetic wave isolation in a wide frequency range.

[0003] In existing technologies, when nanocrystalline ribbons are combined with other materials, the interfacial electromagnetic resonance effect and energy coupling mechanism lack systematic analysis. This can easily lead to an inability to accurately predict the shielding effectiveness of different material combinations, which in turn affects the selection of the combination ratio and fails to effectively improve the overall electromagnetic shielding performance of nanocrystalline ribbon composite materials. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an electromagnetic shielding effectiveness evaluation method. By constructing an interface electromagnetic resonance model and combining it with an energy coupling mechanism, a shielding performance prediction model, and a genetic algorithm optimization process, the shielding effectiveness of nanocrystalline ribbon composite materials is evaluated, thereby solving the problems of inaccurate prediction of material combination performance and difficulty in optimizing the composite ratio in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an electromagnetic shielding effectiveness evaluation method, comprising:

[0006] An interface electromagnetic resonance model was established based on the tested nanocrystalline ribbon composite material. The interface electromagnetic resonance model was used to analyze the electromagnetic wave reflection and scattering effects of the nanocrystalline ribbon composite material, and to quantify the influence of interface resonance frequency and electromagnetic impedance matching on shielding effectiveness. The nanocrystalline ribbon composite material is composed of nanocrystalline ribbon and other materials.

[0007] The coupling mechanism of electromagnetic energy transfer in nanocrystalline ribbon composite materials is analyzed. Based on the contributions of interfacial polarization effect, impedance matching and different material properties to energy loss, the synergistic effect between materials is quantified.

[0008] Electromagnetic shielding performance parameters of nanocrystalline ribbon composites were measured in different frequency bands, and an electromagnetic shielding effectiveness model was constructed based on the electromagnetic shielding performance parameters. The electromagnetic shielding effectiveness model was used to predict the electromagnetic shielding performance of nanocrystalline ribbon composites in different frequency bands. The accuracy of the model was verified by comparing it with experimental results, providing data support for optimizing material ratios and improving shielding effectiveness.

[0009] Electromagnetic shielding performance parameters include shielding loss, absorption rate, and reflectivity.

[0010] In a preferred embodiment, a genetic algorithm is introduced to analyze the influence of the ratio between nanocrystalline ribbon and other materials on the shielding effectiveness. The influence value is calculated based on the influence degree, and the composite material ratio is optimized based on the influence value so that the ratio between nanocrystalline ribbon and other materials achieves the peak electromagnetic shielding performance in the target frequency band.

[0011] Genetic algorithms include population initialization, fitness evaluation, selection operation, crossover operation, mutation operation, and termination condition.

[0012] In a preferred embodiment, simulated environmental conditions are established based on environmental and mechanical factors. These simulated environmental conditions are used to evaluate the changes in the shielding effectiveness of the composite material. The electromagnetic shielding performance stability of the nanocrystalline ribbon composite material under simulated environmental conditions is verified by evaluating the changes in the shielding effectiveness of the composite material.

[0013] Environmental factors include temperature and humidity.

[0014] Mechanical factors include tensile stress factor and vibration frequency factor.

[0015] In a preferred embodiment, an interface electromagnetic resonance model is constructed based on the tested nanocrystalline ribbon composite material. This model is used to analyze the electromagnetic wave reflection and scattering behavior at the interface between the nanocrystalline ribbon and other materials, and to quantify the influence of the interface resonance frequency and electromagnetic impedance matching on the shielding effectiveness. The interface electromagnetic resonance model is expressed as follows:

[0016]

[0017] Where Φ res (f) represents the interfacial electromagnetic resonance term at frequency f; S represents the total number of interfaces of different types of nanocrystalline ribbons in the composite material; Z s (f) represents the complex impedance of the s-th interface at frequency f; Z0 is the preset free space characteristic impedance; This represents the squared magnitude of the reflection coefficient at the s-th interface, which is used to reflect the resonance caused by impedance mismatch. f is the frequency response function of the s-th interface; s δ is the interface resonance frequency of the s-th interface; δ(·) is the Dirac function, which is used to control the excitation response only at the resonance point.

[0018] In a preferred embodiment, the electromagnetic energy transfer path and coupling mechanism inside the nanocrystalline ribbon composite material are analyzed, and the energy loss distribution and synergistic effect are quantified by comprehensively considering the interfacial polarization effect, electromagnetic parameter heterogeneity and material interlayer distribution.

[0019]

[0020] Where Γ loss Ω represents the total electromagnetic energy loss per unit volume within the entire composite system; Ω represents the spatial volume region of the nanocrystalline ribbon composite material; χ ol (x) is the interface coupling activation function between material 0 and material l at position x; ε o (x) is the complex permittivity of the o-th material at x; E o (x), H l (x) represent the local electric and magnetic field strengths of the o-th and l-th materials, respectively; ρ ol (x) is the energy transfer attenuation function between the o-th material and the l-th material, and the energy transfer attenuation function represents the coupling dissipation strength; L represents the total number of different material types in the nanocrystalline ribbon composite material; This represents the gradient operator with respect to position x. The gradient operator with respect to position x is used to calculate the spatial rate of change of energy density flow in an electromagnetic field.

[0021] In a preferred embodiment, the shielding loss, absorptivity, and reflectivity parameters of the nanocrystalline ribbon composite material are measured at different frequency bands to construct an electromagnetic shielding effectiveness model. This model is used to predict the overall shielding performance of the composite material within a target frequency range. The electromagnetic shielding effectiveness model is expressed as follows:

[0022] Ξ SE (f) = -10·log 10 (1-α(f)-β(f)-γ(f)+ζ(f)·Λ(f))

[0023] Among them Ξ SE α(f) represents the total electromagnetic shielding effectiveness at frequency f; α(f) represents the energy component caused by reflection from the material surface; β(f) represents the energy component caused by internal multilayer absorption; γ(f) represents the non-uniform energy component caused by scattering loss; ζ(f) represents the interface nonlinear response factor, which reflects the degree of excitation of the material structure; 10 in the formula represents the base-10 logarithmic conversion factor, used to convert the linear shielding effectiveness into a logarithmic form in decibels; Λ(f) is the normalized energy coupling loss function, Λ(f) comes from Γ loss The conversion is expressed as:

[0024]

[0025] Where Γ loss (f) represents the electromagnetic energy loss intensity at frequency f; Γ loss (f′) represents the electromagnetic energy loss intensity at frequency f′; fmin f max These represent the lower and upper limits of the frequency range, respectively; the denominator is Γ. loss The integral over the entire frequency band serves as a normalization function; the calculated Λ(f)∈[0,1] represents the proportion of loss contribution at different frequencies; the integral variable f′ represents the intermediate frequency variable when performing integration traversal over the frequency domain.

[0026] In a preferred embodiment, a genetic algorithm including population initialization, fitness evaluation, selection operation, crossover operation, mutation operation, and termination condition is introduced to optimize the composite ratio of nanocrystalline materials with other materials, thereby optimizing the electromagnetic shielding performance within the target frequency band. The target model is represented as follows:

[0027]

[0028] The genetic algorithm process is as follows:

[0029] Population initialization:

[0030] Fitness assessment:

[0031] Selection operation: Select individual P (i) The probability is:

[0032] Crossover operation: Let crossover pair (P) (i) ,P (j) ), generate offspring: P new =λP (i) +(1-λ)P (j) ,λ∈(0,1);

[0033] Mutation operation: Apply a perturbation δ to dimension k. k ~U(-∈,∈):

[0034] Termination condition: If any of the following is satisfied: the maximum number of iterations G is reached. max Or the fitness gain for consecutive generations T is less than η or the output P * ;

[0035] Where P represents the ratio vector of the nanocrystalline ribbon to other materials, in the form {p1, p2, ..., p K}, each p k ∈[0,1]; Represents all that satisfy ∑p k The set of legal pairings with a ratio of 1; P * Indicates the proportion of the target combination obtained through optimization; Ξ SE(f;P) represents the electromagnetic shielding effectiveness value corresponding to frequency f under the combination ratio P; κ(f) is the frequency weighting function;

[0036] Where N p P0 represents the initial population set for the genetic algorithm, which consists of N0 and N0. p P consists of a set of randomly generated legal proportional vectors; (i) Let K represent the material ratio vector of the i-th individual, i.e., the i-th candidate composite material combination; K is the number of material types contained in the composite material. κ(f) represents the proportion of the k-th material in the i-th individual; κ(f) is the shielding effectiveness weighting function under the frequency f weighting function; π (i) The probability of the i-th individual being selected is represented by: individual i represents the individual number currently being evaluated or processed; individual j represents the index individual number used for traversal and summation throughout the entire population; Fit (i) Let be the fitness of the i-th individual; P represents the sum of fitness of all individuals j in the entire population; (i) ,P (j) Let P be the pairing vector of the two selected parent generations. (i) ,P (j) Used for crossover operations; λ is the crossover weight coefficient; P new This represents the new individual allocation vector generated by the crossover operation;

[0037] in δ represents the proportion of the k-th material in the new individuals generated by crossover. k Let δ be the abrupt perturbation of the k-th material. k Let δ be a uniformly distributed random variable k ~U(-∈,∈); ∈ is the maximum amplitude control parameter for abrupt disturbances; U(-∈,∈) represents a uniform distribution on the interval -∈ to ∈; δ k ~U(-∈,∈) represents δ k It is randomly selected from within this interval; η is the fitness gain threshold. If the fitness increase is less than η, the optimization is considered to have converged; T represents the stable detection window of the continuous algebra.

[0038] In a preferred embodiment, simulated environmental conditions are established, taking into account factors such as temperature, humidity, tensile stress and vibration frequency, to evaluate the changes in electromagnetic shielding performance of nanocrystalline ribbon composite materials, and the influence of environmental disturbances on shielding effectiveness is quantitatively described by the rate of variation function.

[0039]

[0040] Among them Ψ var(f) represents the stability variation rate of shielding effectiveness at frequency f; Ξ SE (f;T,H,σ,ν) represents the shielding effectiveness after considering the disturbances of temperature T, humidity H, tensile stress σ, and vibration frequency ν; Represents the composite perturbation vector The gradient of ; ||·|| represents the Euclidean norm.

[0041] The technical effects and advantages of this invention are as follows:

[0042] 1. By constructing an interface electromagnetic resonance model, the influence of the interface resonance frequency and impedance matching of composite materials is quantified, thus solving the problem of inaccurate prediction of shielding effectiveness in existing technologies;

[0043] 2. By modeling the energy coupling mechanism, we can identify the polarization synergy and energy consumption distribution at the interface of multiple materials, providing a structural-level quantitative basis for the shielding effect between materials;

[0044] 3. By constructing a frequency response shielding effectiveness model, the performance prediction output of composite materials under multiple frequency bands can be realized, thereby improving the adaptability of the model to the target application frequency band;

[0045] 4. By introducing a full-process genetic algorithm to optimize material ratios, the system automatically searches for the optimal combination for shielding performance, avoiding errors from manual parameter adjustment and improving the efficiency of ratio control.

[0046] 5. By simulating environmental disturbances and introducing performance variation rate indicators, the stability of shielding effectiveness is quantitatively evaluated to ensure that the material combination has good adaptability to engineering environments. Attached Figure Description

[0047] Figure 1 This is a flowchart outlining the method steps of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] Refer to the instruction manual appendix Figure 1 An embodiment of the present invention provides a method for evaluating electromagnetic shielding effectiveness, comprising:

[0050] An interfacial electromagnetic resonance model was established based on the tested nanocrystalline ribbon composite material. This model was used to analyze the electromagnetic wave reflection and scattering effects of the nanocrystalline ribbon composite material and to quantify the influence of interfacial resonance frequency and electromagnetic impedance matching on shielding effectiveness. The nanocrystalline ribbon composite material is composed of nanocrystalline ribbons and other materials. These other materials include, but are not limited to, functional auxiliary phases that synergistically construct multi-layer interfacial structures with the nanocrystalline ribbon to enhance electromagnetic shielding performance. These include: firstly, conductive filler materials, such as graphene, carbon nanotubes, conductive polymers, or metal particles, used for... The shielding structure consists of four main components: 1) Enhancing overall electrical conductivity and forming a conductive network; 2) Dielectric-enhancing materials, such as high-dielectric ceramic particles like alumina, silicon nitride, and barium titanate, which regulate interfacial polarization behavior and dielectric constant distribution; 3) Polymer matrix materials, such as flexible or thermosetting polymers like polyaniline, polyethylene, and polyetheretherketone, which serve as configurational support and flexible interfacial interlocking layers; and 4) Magnetic fillers, such as ferrites and carbon-coated iron particles, which introduce magnetic loss mechanisms to enhance high-frequency shielding performance. These materials, together with nanocrystalline ribbons, form the overall electromagnetic shielding functional structure of the composite material at the micro-nano scale through mechanisms such as interfacial resonant coupling, impedance matching adjustment, and polarization synergy.

[0051] The coupling mechanism of electromagnetic energy transfer in nanocrystalline ribbon composite materials is analyzed. Based on the contributions of interfacial polarization effect, impedance matching and different material properties to energy loss, the synergistic effect between materials is quantified.

[0052] Electromagnetic shielding performance parameters of nanocrystalline ribbon composites were measured in different frequency bands, and an electromagnetic shielding effectiveness model was constructed based on the electromagnetic shielding performance parameters. The electromagnetic shielding effectiveness model was used to predict the electromagnetic shielding performance of nanocrystalline ribbon composites in different frequency bands. The accuracy of the model was verified by comparing it with experimental results, providing data support for optimizing material ratios and improving shielding effectiveness.

[0053] Electromagnetic shielding performance parameters include shielding loss, absorption rate, and reflectivity.

[0054] By introducing a genetic algorithm, the influence of the ratio between nanocrystalline ribbon and other materials on the shielding effectiveness is analyzed. The influence value is calculated based on the degree of influence, and the composite material ratio is optimized based on the influence value, so that the ratio between nanocrystalline ribbon and other materials can achieve the peak electromagnetic shielding performance in the target frequency band.

[0055] Genetic algorithms include population initialization, fitness evaluation, selection operation, crossover operation, mutation operation, and termination condition.

[0056] Based on environmental and mechanical factors, simulated environmental conditions are established. These simulated environmental conditions are used to evaluate the changes in the shielding effectiveness of composite materials. By evaluating the changes in the shielding effectiveness of composite materials, the stability of the electromagnetic shielding performance of nanocrystalline ribbon composite materials under simulated environmental conditions is verified.

[0057] Environmental factors include temperature and humidity.

[0058] Mechanical factors include tensile stress factor and vibration frequency factor.

[0059] It should be noted that in the formula structure involved in this scheme, dimensionless terms can be used as proportional or structural adjustment factors. When combined with quantities with units, they only play a role in numerical scaling and do not introduce new physical dimensions. Therefore, they will not change or confuse the overall unit system. This combination of "dimensionless terms and terms with units" can be understood as a composite structural expression commonly used in mathematical physics modeling. It conforms to the principle of dimensional consistency and has a clear physical interpretation basis.

[0060] Secondly, in the formula structure of this scheme, if multiple variables with different physical units are involved, including but not limited to time, mass or energy variables, their joint appearance is to express the collaborative modeling relationship of multiple physical mechanisms. Each variable can form a unified structure through function mapping, ratio combination or normalization adjustment, with clear units and clear meaning. The overall expression conforms to the principle of dimensional consistency and the conventional formula of engineering modeling.

[0061] In this solution, constants, weights, adjustment factors, threshold parameters, proportional coefficients, etc., are all adjustable control parameters for different application environments. Their values ​​depend on the target equipment configuration, data input characteristics, and performance optimization goals. During the implementation phase, they are set to converge within a reasonable range through model verification, performance constraints, or engineering calibration. Although these parameters do not have a unique preset value, they have clear adjustment logic and calculation paths. They belong to the deterministic setting process in engineering implementation. The purpose of this setting is to ensure that the solution is both universally adaptable and reproducible and operable, without affecting its technical clarity and feasibility.

[0062] Based on the tested nanocrystalline ribbon composite material, an interfacial electromagnetic resonance model was constructed. This model was used to analyze the electromagnetic wave reflection and scattering behavior at the interface between the nanocrystalline ribbon and other materials, and to quantify the influence of the interfacial resonant frequency and electromagnetic impedance matching on the shielding effectiveness. The interfacial electromagnetic resonance model is expressed as follows:

[0063]

[0064] Where Φ res (f) represents the interfacial electromagnetic resonance term at frequency f; S represents the total number of interfaces of different types of nanocrystalline ribbons in the composite material; Zs (f) is the complex impedance of the s-th interface at frequency f; Z0 is the preset free space characteristic impedance, which is a constant. This represents the squared magnitude of the reflection coefficient at the s-th interface, which is used to reflect the resonance caused by impedance mismatch. f is the frequency response function of the s-th interface; s δ is the interface resonance frequency of the s-th interface; δ(·) is the Dirac function, which is used to control the excitation response only at the resonance point.

[0065] The electromagnetic energy transfer path and coupling mechanism inside the nanocrystalline ribbon composite material were analyzed. By combining the interfacial polarization effect, electromagnetic parameter heterogeneity and material interlayer distribution, the energy loss distribution and synergistic effect intensity were quantified.

[0066]

[0067] Where Γ loss Ω represents the total electromagnetic energy loss per unit volume within the entire composite system; Ω represents the spatial volume region of the nanocrystalline ribbon composite material; χ ol (x) is the interface coupling activation function between material 0 and material l at position x; ε o (x) is the complex permittivity of the o-th material at x; E o (x), H l (x) represent the local electric and magnetic field strengths of the o-th and l-th materials, respectively; ρ ol (x) is the energy transfer attenuation function between the o-th material and the l-th material, and the energy transfer attenuation function represents the coupling dissipation strength; L represents the total number of different material types in the nanocrystalline ribbon composite material; This represents the gradient operator with respect to position x. The gradient operator with respect to position x is used to calculate the spatial rate of change of energy density flow in an electromagnetic field.

[0068] The shielding loss, absorptivity, and reflectivity parameters of the nanocrystalline ribbon composite material were measured at different frequency bands to construct an electromagnetic shielding effectiveness model. This model is used to predict the overall shielding performance of the composite material in the target frequency range. The electromagnetic shielding effectiveness model is expressed as follows:

[0069] Ξ SE (f) = -10·log 10 (1-α(f)-β(f)-γ(f)+ζ(f)·Λ(f))

[0070] Among them Ξ SE(f) represents the total electromagnetic shielding effectiveness at frequency f (in dB); α(f) represents the energy component caused by reflection from the material surface; β(f) represents the energy component caused by internal multilayer absorption; γ(f) represents the non-uniform energy component caused by scattering loss; ζ(f) represents the interface nonlinear response factor, which reflects the degree of excitation of the material structure; 10 in the formula represents the base-10 logarithmic conversion factor, used to convert the linear shielding effectiveness into a logarithmic form in dB; Λ(f) is the normalized energy coupling loss function, Λ(f) comes from Γ loss The conversion is expressed as:

[0071]

[0072] Where Γ loss (f) represents the electromagnetic energy loss intensity at frequency f; Γ loss (f′) represents the electromagnetic energy loss intensity at frequency f′; f min f max These represent the lower and upper limits of the frequency range, respectively; the denominator is Γ. loss The integral over the entire frequency band serves as a normalization function; the calculated Λ(f)∈[0,1] represents the proportion of loss contribution at different frequencies, which is used as a weighting factor in the shielding effectiveness model; the integral variable f′ represents the intermediate frequency variable when performing integral traversal over the frequency domain.

[0073] A genetic algorithm, including population initialization, fitness evaluation, selection, crossover, mutation, and termination conditions, is introduced to optimize the composite ratio of nanocrystalline materials with other materials, thereby optimizing electromagnetic shielding performance within the target frequency band. The target model is represented as follows:

[0074]

[0075] The genetic algorithm process is as follows:

[0076] Population initialization:

[0077] Fitness assessment:

[0078] Selection Operation (Roulette Game): Select individual P (i) The probability is:

[0079] Crossover operation: Let crossover pair (P) (i) ,P (j) ), generate offspring: P new =λP (i) +(1-λ)P (j) ,λ∈(0,1);

[0080] Mutation operation: Apply a perturbation δ to dimension k. k ~U(-∈,∈):

[0081] Termination condition: If any of the following is satisfied: the maximum number of iterations G is reached. max Or the fitness gain for consecutive generations T is less than η or the output P * ;

[0082] Where P represents the ratio vector of the nanocrystalline ribbon to other materials, in the form {p1, p2, ..., p K}, each p k ∈[0,1]; Represents all that satisfy ∑p k The set of legal proportions equal to 1, i.e., the feasible solution space of material proportions; P * This represents the optimized target combination ratio, i.e., the material ratio that achieves maximum shielding effectiveness in the target frequency band; Ξ SE (f;P) represents the electromagnetic shielding effectiveness value corresponding to frequency f under the combination ratio P; κ(f) is the frequency weighting function, which is used to emphasize the priority of shielding requirements in certain frequency bands and is assigned a value under the guidance of preset requirements.

[0083] Where N p P0 represents the initial population set for the genetic algorithm, which consists of N0 and N0. p P consists of a set of randomly generated legal proportional vectors; (i) Let K represent the material ratio vector of the i-th individual, i.e., the i-th candidate composite material combination; K is the number of material types contained in the composite material. κ(f) represents the proportion of the k-th material in the i-th individual; κ(f) is the shielding effectiveness weighting function under the frequency f weighting function, used to assign different importance weights to different frequency bands, reflecting the optimization objective's preference for certain frequency bands or the emphasis on design requirements; π (i) represents the probability that the i-th individual is selected, reflecting the proportion of its fitness to the total fitness of the current population; individual i represents the individual number currently being evaluated or processed; individual j represents the index individual number used for traversal and summation throughout the entire population; Fit (i) Let be the fitness of the i-th individual; P represents the sum of fitness of all individuals j in the entire population; (i) ,P (j) Let P be the pairing vector of the two selected parent generations. (i) ,P (j)Used for crossover operations; λ is the crossover weight coefficient, which controls the weight contribution of the two parents in the offspring, and λ is a preset random number; P new This represents the pairing vector of the new individuals (offspring) generated by the crossover operation;

[0084] in δ represents the proportion of the k-th material in the new individuals generated by crossover. k Let δ be the abrupt perturbation of the k-th material. k Let δ be a uniformly distributed random variable k ~U(-∈,∈); ∈ is the maximum amplitude control parameter for mutation perturbation, used to limit the maximum range within which the proportion of a single material can be perturbed during mutation operations; U(-∈,∈) represents a uniform distribution in the interval -∈ to ∈; δ k ~U(-∈,∈) represents δ k It is randomly selected from this interval; η is the fitness gain threshold. If the fitness increase is less than η, the optimization is considered to have converged; T represents the stable detection window for consecutive generations. If the fitness increase is less than the threshold for consecutive generations of T, the process terminates.

[0085] We established simulated environmental conditions, considering factors such as temperature, humidity, tensile stress, and vibration frequency, to evaluate the changes in electromagnetic shielding performance of nanocrystalline ribbon composite materials, and quantitatively described the impact of environmental disturbances on shielding effectiveness using the rate of variation function.

[0086]

[0087] Among them Ψ var (f) represents the stability variation rate of shielding effectiveness at frequency f; Ξ SE (f;T,H,σ,ν) represents the shielding effectiveness after considering the disturbances of temperature T, humidity H, tensile stress σ, and vibration frequency ν; Represents the composite perturbation vector The gradient; ||·|| represents the Euclidean norm, which is used to measure the sensitivity of performance to changes in perturbations.

[0088] It should be noted that this scheme constructs a systematic, hierarchical, and predictive evaluation mechanism for the electromagnetic shielding performance of nanocrystalline ribbon composite materials. Its formation process is based on an in-depth analysis of existing technologies, addressing issues such as the lack of interface mechanism modeling, inadequate optimization of composite ratios, and unverified environmental adaptability. Firstly, considering that the composite of nanocrystalline ribbons with other auxiliary materials will induce significant electromagnetic wave reflection and scattering behavior at the micro-nano scale interface, this scheme constructs an interface electromagnetic resonance model based on the tested nanocrystalline ribbon composite material. This model, with interface impedance mismatch and resonant frequency excitation as its core, quantitatively analyzes the dominant role of the interface structure in the overall shielding effectiveness. This step provides a physical modeling foundation for understanding the multiphase synergistic shielding mechanism in composite structures.

[0089] Furthermore, since the differences in electromagnetic polarization, dielectric parameters, and spatial distribution at the interface between different materials will lead to non-uniform energy transfer, this scheme introduces energy coupling mechanism modeling on the basis of resonance model. By analyzing the gradient change of electromagnetic energy flow at the multi-material interface, the energy dissipation distribution law between materials is extracted, and the cooperative loss capability inside the composite structure is quantified. This modeling not only reveals the essential contribution of multi-material composite to the shielding mechanism, but also provides a structural parameter mapping basis for subsequent shielding performance simulation.

[0090] After understanding the relationship between structure and performance, this scheme constructs a frequency-responsive electromagnetic shielding effectiveness prediction model by measuring the shielding loss, reflectivity, and absorptivity parameters of nanocrystalline ribbon composite materials at different frequency bands. This model integrates the modeling results from the first two steps and can output the overall shielding performance of the composite material in the target frequency range, providing a simulation prediction basis for evaluating the material scheme in actual electromagnetic interference frequency bands. In particular, the model considers the interface nonlinear response term and frequency weighting mechanism, making the model prediction results not only structurally adaptable but also frequency-domain adaptive.

[0091] To address the challenge of manually fine-tuning the composite ratio, this scheme introduces a genetic algorithm encompassing population initialization, fitness evaluation, selection, crossover, mutation, and termination conditions. By setting the fitness function as an integral expression of shielding effectiveness, the algorithm automatically searches for the optimal composite ratio of nanocrystalline ribbon with other materials within the target frequency band. During each generation of evolution, candidate combinations are screened, crossovered, and subjected to perturbation mutations. Combined with a frequency weighting function to guide weighted optimization of specific frequency bands, global convergence of the combinatorial optimization is achieved. This design avoids performance fluctuations caused by traditional trial-and-error matching and ensures that the composite ratio approaches the optimal value mathematically.

[0092] Considering that electromagnetic performance is easily affected by environmental or mechanical disturbances such as temperature, humidity, tensile stress, and vibration frequency in actual use environments, this scheme also introduces a simulated environmental condition construction module and verifies the stability of the shielding performance of the material under different composite disturbances through the performance variation rate function. By conducting joint sensitivity analysis of disturbance variables, external factors that are prone to shielding degradation can be identified, thereby providing reverse guidance on how to adjust the structure or strengthen the interface of the material in engineering applications.

[0093] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for evaluating electromagnetic shielding effectiveness, characterized in that, include: An interface electromagnetic resonance model was established based on the tested nanocrystalline ribbon composite material. The interface electromagnetic resonance model was used to analyze the electromagnetic wave reflection and scattering effects of the nanocrystalline ribbon composite material, and to quantify the influence of interface resonance frequency and electromagnetic impedance matching on shielding effectiveness. The nanocrystalline ribbon composite material is composed of nanocrystalline ribbon and other materials. The coupling mechanism of electromagnetic energy transfer in nanocrystalline ribbon composite materials is analyzed. Based on the contributions of interfacial polarization effect, impedance matching and different material properties to energy loss, the synergistic effect between materials is quantified. Electromagnetic shielding performance parameters of nanocrystalline ribbon composites were measured in different frequency bands, and an electromagnetic shielding effectiveness model was constructed based on the electromagnetic shielding performance parameters. The electromagnetic shielding effectiveness model was used to predict the electromagnetic shielding performance of nanocrystalline ribbon composites in different frequency bands. The accuracy of the model was verified by comparing it with experimental results, providing data support for optimizing material ratios and improving shielding effectiveness. Electromagnetic shielding performance parameters include shielding loss, absorption rate, and reflectivity.

2. The electromagnetic shielding effectiveness evaluation method according to claim 1, characterized in that: By introducing a genetic algorithm, the influence of the ratio between nanocrystalline ribbon and other materials on the shielding effectiveness is analyzed. The influence value is calculated based on the degree of influence, and the composite material ratio is optimized based on the influence value, so that the ratio between nanocrystalline ribbon and other materials can achieve the peak electromagnetic shielding performance in the target frequency band. Genetic algorithms include population initialization, fitness evaluation, selection operation, crossover operation, mutation operation, and termination condition.

3. The electromagnetic shielding effectiveness evaluation method according to claim 2, characterized in that: Based on environmental and mechanical factors, simulated environmental conditions are established. These simulated environmental conditions are used to evaluate the changes in the shielding effectiveness of composite materials. By evaluating the changes in the shielding effectiveness of composite materials, the stability of the electromagnetic shielding performance of nanocrystalline ribbon composite materials under simulated environmental conditions is verified. Environmental factors include temperature and humidity. Mechanical factors include tensile stress factor and vibration frequency factor.

4. The electromagnetic shielding effectiveness evaluation method according to claim 3, characterized in that: Based on the tested nanocrystalline ribbon composite material, an interfacial electromagnetic resonance model was constructed. This model was used to analyze the electromagnetic wave reflection and scattering behavior at the interface between the nanocrystalline ribbon and other materials, and to quantify the influence of the interfacial resonant frequency and electromagnetic impedance matching on the shielding effectiveness. The interfacial electromagnetic resonance model is expressed as follows: Where Φ res (f) represents the interfacial electromagnetic resonance term at frequency f; S represents the total number of interfaces of different types of nanocrystalline ribbons in the composite material; Z s (f) represents the complex impedance of the s-th interface at frequency f; Z0 is the preset free space characteristic impedance; This represents the squared magnitude of the reflection coefficient at the s-th interface, which is used to reflect the resonance caused by impedance mismatch. f is the frequency response function of the s-th interface; s δ is the interface resonance frequency of the s-th interface; δ(·) is the Dirac function, which is used to control the excitation response only at the resonance point.

5. The electromagnetic shielding effectiveness evaluation method according to claim 4, characterized in that: The electromagnetic energy transfer path and coupling mechanism inside the nanocrystalline ribbon composite material were analyzed. By combining the interfacial polarization effect, electromagnetic parameter heterogeneity and material interlayer distribution, the energy loss distribution and synergistic effect intensity were quantified. Where Γ loss Ω represents the total electromagnetic energy loss per unit volume within the entire composite system; Ω represents the spatial volume region of the nanocrystalline ribbon composite material; χ ol (x) is the interface coupling activation function between material 0 and material l at position x; ε o (x) is the complex permittivity of the o-th material at x; E o (x), H l (x) represent the local electric and magnetic field strengths of the o-th and l-th materials, respectively; ρ ol (x) is the energy transfer attenuation function between the o-th material and the l-th material, and the energy transfer attenuation function represents the coupling dissipation strength; L represents the total number of different material types in the nanocrystalline ribbon composite material; This represents the gradient operator with respect to position x. The gradient operator with respect to position x is used to calculate the spatial rate of change of energy density flow in an electromagnetic field.

6. The electromagnetic shielding effectiveness evaluation method according to claim 5, characterized in that: The shielding loss, absorptivity, and reflectivity parameters of the nanocrystalline ribbon composite material were measured at different frequency bands to construct an electromagnetic shielding effectiveness model. This model is used to predict the overall shielding performance of the composite material in the target frequency range. The electromagnetic shielding effectiveness model is expressed as follows: X SE (f)=-10 log 10 (1-α(f)-β(f)-γ(f)+ζ(f)·Λ(f)) Among them Ξ SE α(f) represents the total electromagnetic shielding effectiveness at frequency f; α(f) represents the energy component caused by reflection from the material surface; β(f) represents the energy component caused by internal multilayer absorption; γ(f) represents the non-uniform energy component caused by scattering loss; ζ(f) represents the interface nonlinear response factor, which reflects the degree of excitation of the material structure; 10 in the formula represents the logarithmic conversion factor with base 10, used to convert the linear shielding effectiveness into a logarithmic form in decibels; Λ(f) is the normalized energy coupling loss function, Λ(f) comes from Γ loss The conversion is expressed as: Where Γ loss (f) represents the electromagnetic energy loss intensity at frequency f; Γ loss (f′) represents the electromagnetic energy loss intensity at frequency f′; f min f max These represent the lower and upper limits of the frequency range, respectively. The denominator is Γ loss The integral over the entire frequency band serves as a normalization function; the calculated Λ(f)∈[0,1] represents the proportion of loss contribution at different frequencies; The integral variable f′ represents the intermediate frequency variable when performing an integral traversal over the frequency domain.

7. The electromagnetic shielding effectiveness evaluation method according to claim 6, characterized in that: A genetic algorithm, including population initialization, fitness evaluation, selection, crossover, mutation, and termination conditions, is introduced to optimize the composite ratio of nanocrystalline materials with other materials, thereby optimizing electromagnetic shielding performance within the target frequency band. The target model is represented as follows: The genetic algorithm process is as follows: Population initialization: Fitness assessment: Selection operation: Select individual P (i) The probability is: Crossover operation: Let crossover pair (P) (i) ,P (j) ), generate offspring: P new =λP (i) +(1-λ)P (j) ,λ∈(0,1); Mutation operation: Apply a perturbation δ to dimension k. k ~U(-∈,∈): Termination condition: If any of the following is satisfied: the maximum number of iterations G is reached. max Or the fitness gain for consecutive generations T is less than η or the output P * ; Where P represents the ratio vector of the nanocrystalline ribbon to other materials, in the form {p1, p2, ..., p K }, each p k ∈[0,1]; Represents all that satisfy ∑p k The set of legal pairings with a ratio of 1; P * Indicates the proportion of the target combination obtained through optimization; Ξ SE (f;P) represents the electromagnetic shielding effectiveness value corresponding to frequency f under the combination ratio P; κ(f) is the frequency weighting function; Where N p Population size represents the number of individuals in each generation of genetic iterations that compete in proportion to each other. P0 represents the initial population set for the genetic algorithm, which is composed of N. p P consists of a set of randomly generated legal proportional vectors; (i) Let K represent the material ratio vector of the i-th individual, i.e., the i-th candidate composite material combination; K is the number of material types contained in the composite material. κ(f) represents the proportion of the k-th material in the i-th individual; κ(f) is the shielding effectiveness weighting function under the frequency f weighting function; π (i) This represents the probability that the i-th individual is selected; individual i represents the individual number currently being evaluated or processed. Individual j represents the index individual number used for traversal and summation in the entire population; Fit (i) Let be the fitness of the i-th individual; P represents the sum of fitness of all individuals j in the entire population; (i) ,P (j) Let P be the pairing vector of the two selected parent generations. (i) ,P (j) Used for crossover operations; λ is the crossover weight coefficient; P new This represents the new individual allocation vector generated by the crossover operation; in δ represents the proportion of the k-th material in the new individuals generated by crossover. k Let δ be the abrupt perturbation of the k-th material. k Let δ be a uniformly distributed random variable k ~U(-∈,∈); ∈ is the maximum amplitude control parameter for abrupt disturbances; U(-∈,∈) represents a uniform distribution on the interval -∈ to ∈; δ k ~U(-∈,∈) represents δ k It is randomly selected from within this interval; η is the fitness gain threshold. If the fitness increase is less than η, the optimization is considered to have converged; T represents the stable detection window of the continuous algebra.

8. The electromagnetic shielding effectiveness evaluation method according to claim 7, characterized in that: We established simulated environmental conditions, considering factors such as temperature, humidity, tensile stress, and vibration frequency, to evaluate the changes in electromagnetic shielding performance of nanocrystalline ribbon composite materials, and quantitatively described the impact of environmental disturbances on shielding effectiveness using the rate of variation function. Among them Ψ var (f) represents the stability variation rate of shielding effectiveness at frequency f; Ξ SE (f;T,H,σ,ν) represents the shielding effectiveness after considering the disturbances of temperature T, humidity H, tensile stress σ, and vibration frequency ν; Represents the composite perturbation vector The gradient of ; ||·|| represents the Euclidean norm.

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