Electromagnetic characteristic measurement device and method based on free space method and FA-PSO algorithm

Abstract

The application provides an electromagnetic characteristic measurement device and method based on a free space method and a FA-PSO algorithm, and relates to the technical field of electromagnetic measurement. The device comprises a vector network analyzer, a transmitting antenna, a receiving antenna and a control computer. The first port of the vector network analyzer is connected to the transmitting antenna through a first coaxial cable. The second port of the vector network analyzer is connected to the receiving antenna through a second coaxial cable. The transmitting antenna and the receiving antenna are arranged relative to the material to be measured in space to form an electromagnetic wave propagation path containing the material to be measured, which is used for measuring the scattering parameters of the material to be measured. The control computer is in communication connection with the vector network analyzer. The physical thickness and the complex dielectric constant of the material are taken as the variables to be inverted, and the high-precision inversion of the electromagnetic parameters and the physical thickness can be realized simultaneously through one nondestructive measurement and calculation, and the solving precision is improved significantly.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic measurement technology, and in particular to an electromagnetic characteristic measurement device and method based on the free space method and the FA-PSO algorithm. Background Technology

[0002] Currently, the main techniques for measuring the complex permittivity of materials include the resonant cavity method, waveguide transmission / reflection method, and coaxial probe method.

[0003] The waveguide method is a classic and relatively mature microwave electromagnetic parameter measurement technique. It involves precisely placing the sample of the material under test inside a transmission line, confining the electromagnetic wave energy to a specific region through its conductive boundary, and measuring the reflection and transmission characteristics of the electromagnetic wave when passing through the waveguide section containing the sample. A vector network analyzer (VNA) is connected to both ends of the waveguide section containing the sample to measure the scattering parameters of the system, thereby retrieving the complex permittivity and complex permeability of the material.

[0004] The open coaxial probe method is a contact technique widely used for measuring the electromagnetic parameters of liquids, solids, and certain solid materials. Its core consists of a truncated waveguide composed of two coaxial cylinders, with open ends that contact the plane of the sample under study. The alternating voltage generated between the two conductors produces an electric field through the internal dielectric, extending to the outside of the waveguide and contacting the material under test. Some energy is radiated into the material and interacts with it. The complex permittivity of the material is then determined by measuring the reflection coefficient at the port using a VNA (Vacuum-based Optical Array).

[0005] The resonant cavity method utilizes a special electromagnetic wave cavity capable of inducing resonance. Within the resonant cavity, electromagnetic waves propagate continuously. When they encounter the cavity wall, the reflected electromagnetic waves superimpose with the original waves, forming a standing wave. When the wavelength of the standing wave and the cavity size satisfy an integer multiple relationship under specific conditions, the resonant cavity enters a resonant state. At this point, the electromagnetic parameters of the material can be obtained through key parameters such as the resonant frequency and quality factor of the resonant cavity.

[0006] However, the above methods typically have their own limitations. While the resonant cavity method offers high measurement accuracy, it is limited to measurements at discrete resonant frequencies and cannot achieve broadband analysis. Waveguide and coaxial probe methods require samples to be precisely machined to specific dimensions or to be in close contact with the probe, which is not only difficult to process but also destructive for large, hard building materials. In contrast, the free-space method avoids these problems. It is a non-contact measurement technique that requires no physical processing of the sample, thus possessing non-destructive characteristics. Furthermore, it can perform frequency sweep measurements over a wide spectral range, offering broadband advantages. The traditional Nicolson-Ross-Weir (NRW) method within the free-space method is a typical electromagnetic parameter extraction algorithm, but when extracting the complex permittivity using transmission / reflection coefficients, it suffers from multi-valued solutions due to phase ambiguity. Summary of the Invention

[0007] To address the shortcomings of the existing technologies, this invention constructs a measurement platform and, for the objective function, builds a hybrid optimization algorithm architecture based on FA-PSO. It proposes an electromagnetic property measurement device and method based on the free space method and the FA-PSO algorithm, aiming to accurately measure the electromagnetic properties and thickness of building materials.

[0008] On the one hand, the present invention proposes an electromagnetic characteristic measurement device based on the free space method and the FA-PSO algorithm. The device includes: a vector network analyzer, a transmitting antenna, a receiving antenna, and a control computer.

[0009] The vector network analyzer includes two ports: a first port is connected to a transmitting antenna via a first coaxial cable; and a second port is connected to a receiving antenna via a second coaxial cable.

[0010] The transmitting antenna and the receiving antenna are positioned in space relative to the material under test to form an electromagnetic wave propagation path containing the material under test, which is used to measure the scattering parameters of the material under test.

[0011] The control computer is communicatively connected to the vector network analyzer.

[0012] Furthermore, the transmitting antenna and the receiving antenna are each mounted by a precision positioning device, and a fixing device for mounting the material to be tested is provided on the electromagnetic wave propagation path formed by the transmitting antenna and the receiving antenna.

[0013] Furthermore, the scattering parameter measurement includes: transmission measurement and reflection measurement; wherein, when performing transmission measurement on the material under test, the transmitting antenna and the receiving antenna are on opposite sides of the material under test; when performing reflection measurement on the material under test, the transmitting antenna and the receiving antenna are on the same side of the material under test.

[0014] During each scattering parameter measurement, the positions of the transmitting antenna and the receiving antenna remain unchanged; transmission and reflection measurements are performed only by changing the position of the material under test.

[0015] Furthermore, the control computer includes:

[0016] The parameter setting module is used to set the operating parameters of the vector network analyzer; wherein the operating parameters include, but are not limited to: scanning frequency range, number of frequency sampling points, transmit power, and intermediate frequency bandwidth.

[0017] The data acquisition module is used to acquire the reference frequency response and material frequency response from the vector network analyzer;

[0018] The data preprocessing module is used to calculate the scattering parameters of the material under test based on the reference frequency response and the material frequency response; wherein the scattering parameters include: reflection coefficient and transmission coefficient;

[0019] The parameter inversion module is used to optimize and invert the dielectric constant, conductivity and material thickness of the material under test based on the scattering parameters of the material under test using the FA-PSO algorithm, and output the inversion results.

[0020] On the other hand, this invention proposes an electromagnetic property measurement method based on the free space method and the FA-PSO algorithm, which includes the following process:

[0021] The scattering parameters of the material under test are obtained by measuring the scattering parameters of the material under test;

[0022] Based on the scattering parameters, an electromagnetic wave propagation model is constructed with the complex permittivity and material thickness of the material under test as variables;

[0023] Based on the electromagnetic wave propagation model, the scattering parameters of the material under test are used as input, and the FA-PSO algorithm is used to optimize and invert the dielectric constant, conductivity and thickness of the material under test, and the inversion results are obtained.

[0024] Furthermore, the specific details of obtaining the scattering parameters of the material under test by measuring its scattering parameters are as follows:

[0025] The electromagnetic characteristic measurement device based on the free space method and FA-PSO algorithm is deployed, the operating parameters of the vector network analyzer are set, and the error correction of the vector network analyzer is performed.

[0026] Without placing the test material, the reference frequency response of the transmission measurement under the current free-space conditions is measured by performing a frequency band scan. ;

[0027] The material under test is placed at the designated location for transmission measurement between the transmitting and receiving antennas, and a frequency band scan is performed to measure the material's frequency response under the current free-space conditions. ;

[0028] Material frequency response to the transmission measurement With reference frequency response The transmittance coefficient of the material under test is obtained by performing point-by-point division and noise reduction.

[0029] A reference copper plate is placed at a predetermined position between the transmitting and receiving antennas, and a frequency band scan is performed to measure the reference frequency response of the reflection measurement under the current free-space conditions. ;

[0030] The material under test is placed at the designated reflection measurement position between the transmitting and receiving antennas, and a frequency band scan is performed to measure the material's frequency response under the current free-space conditions. ;

[0031] Material frequency response to the reflection measurement With reference frequency response The reflection coefficient of the material under test is obtained by performing point-by-point division and noise reduction.

[0032] Furthermore, the electromagnetic wave propagation model is as follows:

[0033]

[0034]

[0035] in, Transmission coefficient; For purely linearly polarized Fresnel reflection coefficients; For material thickness; It is a natural constant; The reflection coefficient; Let be the phase constant, expressed as:

[0036]

[0037] in, Wavelength in free space; Angle of incidence; is the complex permittivity.

[0038] Furthermore, based on the electromagnetic wave propagation model, using the scattering parameters of the material under test as input, the FA-PSO algorithm is used to optimize and invert the dielectric constant, conductivity, and material thickness of the material under test, and the specific content of the inversion result is as follows:

[0039] The root mean square error between the transmittance coefficient of the material under test and the transmittance coefficient obtained by algorithm inversion is used as the objective function.

[0040] Set the FA population size, and generate an initial FA population based on the FA population size; wherein each FA individual in the initial FA population is a set of PSO control parameters, including: inertia weights. Learning factors and learning factors ;

[0041] Set an iteration cycle, and execute the following procedure within each iteration cycle:

[0042] For each FA individual in the current FA population Based on the electromagnetic wave propagation model and the scattering parameters of the material under test, using FA individual The corresponding PSO control parameters are iteratively optimized using an improved PSO algorithm, and the optimal PSO individual and the minimum value of the objective function corresponding to the optimal PSO individual are obtained by minimizing the objective function; wherein the PSO individual is a set of dielectric constant, conductivity and material thickness of the material to be tested;

[0043] The objective function value corresponding to the optimal PSO individual is used as the FA individual. The fitness of;

[0044] If the current iteration cycle does not meet the preset termination condition, the FA algorithm is used to optimize the current FA population based on the fitness of all FA individuals in the current FA population to obtain an updated FA population.

[0045] If the current iteration cycle meets the preset termination condition, the dielectric constant, conductivity, and material thickness of the material to be tested corresponding to the best PSO individual in the current iteration cycle will be used as the inversion result.

[0046] Furthermore, the improved PSO algorithm is as follows: based on the set PSO population size, an initial PSO population is generated using a Gaussian distribution initialization strategy based on prior experience;

[0047] The PSO control parameters remain fixed within each set iteration cycle;

[0048] For each PSO individual in the current PSO population In each iteration, the PSO individual is updated using the PSO control parameters within the current iteration cycle. The position of the PSO individual in the current iteration is calculated. The updated objective function value corresponding to the position;

[0049] PSO individuals in the current iteration The updated objective function value corresponding to the position, and the PSO individual The corresponding historical best objective function value is compared. If the objective function value corresponding to the updated position is less than the historical best objective function value, then the PSO individual in the current iteration is... The updated position is used as the PSO individual in the current iteration. The optimal solution; otherwise, the PSO individual corresponding to the historical optimal objective function value. Position as the PSO individual in the current iteration The optimal solution;

[0050] From the optimal solutions of all PSO individuals in the current PSO population, select the optimal solution with the smallest objective function value as the global optimal solution of the current PSO population.

[0051] Determine whether the current iteration count has reached the preset iteration cycle limit. If not, continue to execute the next iteration and update the global optimal solution and the optimal PSO individual. If it has reached the limit, terminate the PSO algorithm, output the global optimal solution and the minimum value of the objective function corresponding to the global optimal solution, and set the PSO individual corresponding to the global optimal solution as the optimal PSO individual.

[0052] The beneficial effects of adopting the above technical solution are as follows:

[0053] This invention establishes a measurement platform and constructs a hybrid optimization algorithm architecture based on FA-PSO for the objective function. This architecture cleverly utilizes the powerful global search capability of the outer FA layer to periodically and adaptively optimize key control parameters such as the inertia weight and learning factor of the inner PSO layer. This mechanism fundamentally overcomes the inherent defects of traditional PSO algorithms, which are prone to getting trapped in local optima and premature convergence due to fixed parameters, significantly improving the optimization efficiency and solution accuracy of the algorithm. Based on this, this invention achieves a more groundbreaking function: by treating the physical thickness and complex permittivity of the material as variables to be inverted, high-precision inversion of electromagnetic parameters and physical thickness can be achieved simultaneously through a single non-destructive measurement and calculation. This not only completely eliminates the cumbersome physical thickness measurement step, which is difficult to implement in many practical application scenarios, but also opens up the possibility of in-situ, rapid wireless performance evaluation of existing building materials, possessing extremely high engineering application value. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of the electromagnetic property measurement device based on the free space method and FA-PSO algorithm in this embodiment;

[0055] Figure 2This is a schematic diagram of the measurement of transmission coefficient and reflection coefficient in this embodiment; wherein, (a) is a schematic diagram of reflection coefficient measurement; and (b) is a schematic diagram of transmission coefficient measurement.

[0056] Figure 3 This is a flowchart of the electromagnetic property measurement method based on the free space method and FA-PSO algorithm in this embodiment;

[0057] Figure 4 This is a schematic diagram of the transmission coefficient measured and calculated by PET when the incident angle is 0° in this embodiment;

[0058] Figure 5 This is a schematic diagram of the plane wave reflection and transmission model of building materials in this embodiment;

[0059] Figure 6 This is a flowchart of the FA-PSO algorithm in this embodiment;

[0060] Figure 7 This is a schematic diagram of the transmission coefficient measured and calculated in this embodiment; where (a) is a schematic diagram of the transmission coefficient of acrylic; (b) is a schematic diagram of the transmission coefficient of black rubber; and (c) is a schematic diagram of the transmission coefficient of bakelite board.

[0061] In the diagram: 1-Vector Network Analyzer (VNA); 2-Transmitting Antenna (Tx); 3-Receiving Antenna (Rx); 4-Building Material; 5-Precision Positioning Device; 6-Fixing Device; 7-Platform. Detailed Implementation

[0062] To facilitate understanding of this application, specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. The following embodiments are illustrative of the invention but are not intended to limit its scope. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application.

[0063] Example 1:

[0064] This embodiment provides an electromagnetic property measurement device based on the free space method and the FA-PSO algorithm, such as... Figure 1 As shown, the device includes: a vector network analyzer VNA1, a transmitting antenna Tx2, a receiving antenna Rx3, and a control computer.

[0065] The first port of the vector network analyzer VNA1 is connected to the transmitting antenna Tx2 via a first coaxial cable.

[0066] The second port of the vector network analyzer VNA1 is connected to the receiving antenna Rx3 via a second coaxial cable.

[0067] The transmitting antenna Tx2 and the receiving antenna Rx3 are positioned in space relative to the material under test to form an electromagnetic wave propagation path containing the material under test, which is used to measure the scattering parameters of the material under test.

[0068] The control computer is communicatively connected to the VNA1 vector network analyzer.

[0069] In this embodiment, the vector network analyzer VNA1, transmitting antenna Tx2, receiving antenna Rx3, and control computer are physically connected. The vector network analyzer VNA1 is used to measure the scattering parameters of the material under test.

[0070] The transmitting antenna Tx2 and the receiving antenna Rx3 are each fixed in a preset designated position by a precision positioning device 5. A fixing device 6 for installing building material 4 (i.e. the material to be tested) is provided on the electromagnetic wave propagation path formed by the transmitting antenna Tx2 and the receiving antenna Rx3. The fixing device 6 and the precision positioning device 5 are fixed on the same platform 7.

[0071] In this embodiment, the transmitting antenna Tx2 and the receiving antenna Rx3 are mounted on a tripod at a height of 70 centimeters above the ground, and the distance between them is not less than 1 meter.

[0072] The scattering parameter measurement includes transmission measurement and reflection measurement; wherein, when performing transmission measurement on the material under test, the transmitting antenna Tx2 and the receiving antenna Rx3 are on opposite sides of the material under test; when performing reflection measurement on the material under test, the transmitting antenna Tx2 and the receiving antenna Rx3 are on the same side of the material under test.

[0073] In this embodiment, as Figure 2 As shown in (a), the Tx and Rx antennas are placed on the same side of the building material, and the reflection coefficients are obtained from the frequency response of the material and the air. Figure 2 As shown in (b), the Tx and Rx antennas are placed on opposite sides of the material plate to obtain the transmission coefficients from the frequency response of the material and air.

[0074] During each scattering parameter measurement, the positions of the transmitting antenna Tx2 and the receiving antenna Rx3 remain unchanged; transmission and reflection measurements are performed only by changing the position of the material under test.

[0075] In this embodiment, to ensure that the two measurements are performed under the same conditions, the Tx and Rx antennas are kept in fixed positions and only the material sample is moved, that is, the distance between the Tx and Rx antennas is always kept at 1 meter.

[0076] The control computer includes:

[0077] The parameter setting module is used to set the operating parameters of the vector network analyzer VNA1; wherein the operating parameters include, but are not limited to: scan frequency range, number of set frequency sampling points, transmit power and intermediate frequency bandwidth.

[0078] The data acquisition module is used to acquire the reference frequency response and material frequency response from the VNA1 vector network analyzer.

[0079] The data preprocessing module is used to calculate the scattering parameters of the material under test based on the reference frequency response and the material frequency response; wherein the scattering parameters include: reflection coefficient and transmission coefficient.

[0080] The parameter inversion module is used to optimize and invert the dielectric constant, conductivity and material thickness of the material under test based on the scattering parameters of the material under test using the FA-PSO algorithm, and output the inversion results.

[0081] Example 2:

[0082] This embodiment presents an electromagnetic property measurement method based on the free-space method and the FA-PSO algorithm, implemented using the electromagnetic property measurement device based on the free-space method and the FA-PSO algorithm described in Embodiment 1. Figure 3 As shown, the method includes the following steps:

[0083] The scattering parameters of the material under test are obtained by measuring the scattering parameters of the material under test.

[0084] The specific details of obtaining the scattering parameters of the material under test by measuring the scattering parameters are as follows:

[0085] The electromagnetic characteristic measurement device based on the free space method and FA-PSO algorithm is set up, the operating parameters of the vector network analyzer are set, and the error correction of the vector network analyzer is performed.

[0086] In this embodiment, dedicated control software is run on the control computer, and the core operating parameters of the VNA are set accordingly. Specifically, the scanning frequency range is set to 18 GHz to 40 GHz; the number of frequency sampling points is set to 1600 to ensure a frequency resolution of 15 MHz; the transmit power is set to 0 dBm; and the intermediate frequency (IF) bandwidth is set to 1 kHz to balance the measurement speed and the system dynamic range.

[0087] Simultaneously, to eliminate systematic errors introduced by the coaxial cable, connectors, and the VNA's internal pathways, a standard calibration procedure must be manually performed. This calibration process generates a correction file containing calibration coefficients. Before subsequent actual measurements, this correction file must be imported into the VNA, which will then automatically apply these calibration coefficients during the measurement process, ensuring that the measurement results accurately reflect only the responses between the antenna ports.

[0088] Without placing the test material, the reference frequency response of the transmission measurement under the current free-space conditions is measured by performing a frequency band scan. .

[0089] In this embodiment, after system calibration is completed, the positions of the transmitting and receiving antennas are kept fixed, and no material under test is placed. A complete frequency band scan is performed, and the transmission coefficient under this free-space condition is measured and recorded, such as... Figure 4 As shown, its data is stored as a reference frequency response of the transmission measurement. .

[0090] The material under test is placed at the designated location for transmission measurement between the transmitting and receiving antennas, and a frequency band scan is performed to measure the material's frequency response under the current free-space conditions. .

[0091] In this embodiment, as Figure 2 As shown in (b), the material under test is precisely placed at a predetermined position between the transmitting and receiving antennas, and a complete frequency band scan is performed again. The transmission coefficients of the material under test at different frequencies are measured and recorded, and the data is stored as the material frequency response of the transmission measurement. .

[0092] Material frequency response to the transmission measurement With reference frequency response The transmittance coefficient of the material under test is obtained by performing point-by-point division and noise reduction.

[0093] A reference copper plate is placed at a predetermined position between the transmitting and receiving antennas, and a frequency band scan is performed to measure the reference frequency response of the reflection measurement under the current free-space conditions. .

[0094] In this embodiment, after system calibration is completed, the positions of the transmitting and receiving antennas are kept fixed, such as... Figure 2 As shown in (a), a reference copper plate is precisely placed at a predetermined position between the transmitting and receiving antennas. A complete frequency band scan is performed, the transmission coefficient under this free-space condition is measured and recorded, and the data is stored as the reference frequency response for reflection measurements. .

[0095] The material under test is placed at the designated reflection measurement position between the transmitting and receiving antennas, and a frequency band scan is performed to measure the material's frequency response under the current free-space conditions. .

[0096] In this embodiment, the material under test is precisely placed at a predetermined position between the transmitting and receiving antennas, and a complete frequency band scan is performed again. The transmission coefficients of the material under test at different frequencies are measured and recorded, and the data is stored as the second material frequency response. .

[0097] Material frequency response to the reflection measurement With reference frequency response The reflection coefficient of the material under test is obtained by performing point-by-point division and noise reduction.

[0098] In this embodiment, the recorded reference frequency response is invoked in the control computer. and material frequency response For 1600 frequency points within the 18-40 GHz scan band, a complete set of transmission coefficient values ​​was calculated by performing point-by-point division operations. This set of data constitutes the final frequency response characterizing the purely electromagnetic properties of the material under test and will serve as input data for subsequent parameter inversion algorithms. Simultaneously, the VNA's time-domain gating function was enabled, and the measurement averaging was set to 5 times to further filter out environmental multipath reflection interference and random noise, ensuring the accuracy of the final output transmission coefficient data. The accuracy and signal-to-noise ratio. This data will serve as input for subsequent parameter inversion algorithms.

[0099] The transmission coefficient and reflection coefficient are expressed as follows:

[0100]

[0101]

[0102] in Indicates frequency; Represents frequency Transmission coefficient at the specified depth; Represents frequency The reflection coefficient below; Represents frequency Material frequency response measured by transmission under light; Represents frequency Reference frequency response of the lower transmission measurement; Represents frequency Material frequency response measured by lower reflection; Represents frequency Reference frequency response for lower reflection measurement.

[0103] Based on the scattering parameters, an electromagnetic wave propagation model is constructed with the complex permittivity and material thickness of the material under test as variables.

[0104] like Figure 5 As shown, for a single flat plate material, the electromagnetic wave propagation model is:

[0105]

[0106]

[0107] in, Transmission coefficient; The reflection coefficient; For material thickness; It is a natural constant;

[0108]

[0109] in, Wavelength in free space; Angle of incidence; Let be the complex permittivity, expressed as:

[0110]

[0111] in, It is the dielectric constant; Angular frequency; The vacuum permittivity, For electrical conductivity, it is expressed as:

[0112]

[0113] in, and All are constants, and all are defined as The function is used to better fit the data. ;

[0114]

[0115] in, is the Fresnel reflection coefficient for pure direct polarization.

[0116] In this embodiment, based on the electromagnetic wave propagation theoretical model constructed by the aforementioned formula, and establishing the root mean square error between the measured transmission coefficient and the algorithm-inverted transmission coefficient as the optimization objective function, the Hybrid Firefly Algorithm and Particle Swarm Optimization (FA-PSO) algorithm designed in this embodiment, based on the firefly algorithm, is initiated. Figure 6 As shown, the complex permittivity of the material under test can be deduced with high accuracy and high efficiency.

[0117] Based on the electromagnetic wave propagation model, the scattering parameters of the material under test are used as input, and the FA-PSO algorithm is used to optimize and invert the dielectric constant, conductivity and thickness of the material under test, and the inversion results are obtained.

[0118] In this embodiment, based on the hierarchical hybrid strategy, the initial state of the algorithm is first set, that is, the number of particles in the initial population of the inner-layer Particle Swarm Optimization (PSO) algorithm and the outer-layer Fire-fly Algorithm (FA) algorithm are set. Then, an initial population of the inner-layer PSO algorithm is created to represent the parameters of the material to be inverted; these parameters are the dielectric constant, conductivity, and thickness of the material. Simultaneously, an initial population of the outer-layer FA algorithm is created to represent the core control parameters of the PSO algorithm; these parameters are the inertia weights. Learning factors and These control parameters guide the PSO optimization process and have no direct mathematical relationship with the transmission and reflection coefficients. Instead, they affect the efficiency and accuracy of finding the optimal material parameters. After the algorithm starts, the optimal individual in the FA population corresponds to a set of... , , The value will be used as the PSO control parameter in the first iteration of the PSO algorithm.

[0119] Based on the electromagnetic wave propagation model, using the scattering parameters of the material under test as input, the FA-PSO algorithm is used to optimize and invert the dielectric constant, conductivity, and material thickness of the material under test, and the specific content of the inversion results is as follows:

[0120] The root mean square error between the transmittance coefficient of the material under test and the transmittance coefficient obtained by algorithm inversion is used as the objective function.

[0121] Set the FA population size, and generate an initial FA population based on the FA population size; wherein each FA individual in the initial FA population is a set of PSO control parameters, including: inertia weights. Learning factors and learning factors .

[0122] Set an iteration cycle, and execute the following procedure within each iteration cycle:

[0123] For each FA individual in the current FA population Based on the electromagnetic wave propagation model and the scattering parameters of the material under test, using FA individual The corresponding PSO control parameters are iteratively optimized using an improved PSO algorithm, and the optimal PSO individual and the minimum value of the objective function corresponding to the optimal PSO individual are obtained by minimizing the objective function; wherein the PSO individual is a set of dielectric constant, conductivity and material thickness of the material to be tested.

[0124] The improved PSO algorithm is as follows: based on the set PSO population size, an initial PSO population is generated using a Gaussian distribution initialization strategy based on prior experience.

[0125] The PSO control parameters remain fixed within each set iteration cycle.

[0126] For each PSO individual in the current PSO population In each iteration, the PSO individual is updated using the PSO control parameters within the current iteration cycle. The position of the PSO individual in the current iteration is calculated. The updated objective function value corresponding to the position.

[0127] PSO individuals in the current iteration The updated objective function value corresponding to the position, and the PSO individual The corresponding historical best objective function value is compared. If the objective function value corresponding to the updated position is less than the historical best objective function value, then the PSO individual in the current iteration is... The updated position is used as the PSO individual in the current iteration. The optimal solution; otherwise, the PSO individual corresponding to the historical optimal objective function value. Position as the PSO individual in the current iteration The optimal solution.

[0128] From the optimal solutions of all PSO individuals in the current PSO population, select the optimal solution with the smallest objective function value as the global optimal solution of the current PSO population.

[0129] Determine if the current iteration count has reached the set iteration cycle limit. If not, continue to the next iteration and update the global optimal solution and the optimal PSO individual. If the limit has been reached, terminate the PSO algorithm, output the global optimal solution and the minimum objective function value corresponding to the global optimal solution, and set the PSO individual corresponding to the global optimal solution as the optimal PSO individual.

[0130] In this embodiment, the improved inner-layer PSO algorithm is run and executed for a preset iteration cycle. The algorithm is characterized by the fact that the initial particle swarm positions are not randomly generated, but rather set to a Gaussian distribution based on prior experience. The mean and variance of the Gaussian distribution are determined based on the prior experience range of the material parameters to be inverted. Then, based on a preset population size, an initial PSO population is generated by sampling from this Gaussian distribution to improve optimization efficiency. During this iteration cycle, the particle swarm continuously updates its position according to the currently fixed control parameters. For each iteration, the objective function value corresponding to the current position of each particle is calculated, and this objective function value is compared with the particle's historical best objective function value. When the objective function value is smaller in this iteration, the particle's individual optimal solution is updated to the current solution. After updating the individual optimal solutions of all particles, the one with the smallest objective function value from the individual optimal solutions of all particles is selected and updated as the global optimal solution, thereby guiding the particle swarm to continuously approach the material parameter solution that minimizes the mean square error fitness function.

[0131] The objective function value corresponding to the optimal PSO individual is used as the FA individual. The degree of adaptability.

[0132] In this embodiment, for each FA individual, the Particle Swarm Optimization (PSO) process is invoked once, given the FA individual's... , , Under the given conditions, the material parameters to be inverted are optimized to obtain the globally optimal material parameter solution output by the PSO and its corresponding minimum objective function. The minimum objective function is used as the fitness of the FA individual. FA individuals with poor fitness are moved to FA individuals with better fitness to improve their optimization performance for the corresponding PSO control parameters. The FA individual with the best fitness in the current generation is directly retained to the next generation to update the current FA population.

[0133] If the current iteration cycle does not meet the preset termination condition, the FA algorithm is used to optimize the current FA population based on the fitness of all FA individuals in the current FA population, resulting in an updated FA population.

[0134] If the current iteration cycle meets the preset termination condition, the dielectric constant, conductivity, and material thickness of the material to be tested corresponding to the best PSO individual in the current iteration cycle will be used as the inversion result.

[0135] In this embodiment, after the inner PSO completes one iteration cycle, the outer standard firefly algorithm FA is activated. This algorithm will perform optimization operations within its own parameter space, which is determined by the control parameters of the PSO, namely the inertia weights. Learning factors and The goal is to find a set of PSO control parameters that optimizes the performance of the inner-layer PSO algorithm when retrieving the dielectric constant, conductivity, and thickness of the material. The optimal control parameters obtained by optimizing the outer FA are combined. The parameters are passed to the inner PSO algorithm, replacing its original control parameters. Then, a new iteration cycle begins. Furthermore, after each inner PSO iteration cycle, a convergence check is performed on the objective function. If the preset termination condition is met—that is, the total number of iterations reaches the upper limit or the fitness value of the global optimum changes less than a preset threshold for multiple consecutive generations—then the algorithm is considered convergent. At this point, the entire optimization process terminates, and the global optimum of the current PSO population is output. This solution is the high-precision material complex permittivity finally measured in this embodiment.

[0136] To verify the effectiveness of the measurement method proposed in this embodiment, a uniform PET plate (30cm×30cm×2cm) with a length of 30cm, a width of 30cm, and a thickness of 2cm was first selected as a standard reference. PET, as a homogeneous and isotropic material whose electromagnetic properties have been widely characterized, has a recognized dielectric constant that can provide a reliable benchmark for the measurement results of this method.

[0137] The dielectric constant of the PET board described above was measured and inverted using the method described in this embodiment, and the extracted results were compared with the dielectric constant of PET material obtained from other literature. Specific data are shown in Table 1.

[0138] Table 1 Electromagnetic parameters and thickness of building materials

[0139]

[0140] The references mentioned in Table 1 are as follows: [1] C. Liao, Z. He, R. Tang, W. Zhang, C. Liu, and C. Wang, “The research on microwave drying characteristics of polyethylene terephthalate materials based on frequency and power tuning technology,” Processes, vol. 12, 2024.

[0141] [2]M. Haghzadeh, C. Armiento, and A. Akyurtlu, "Microwave dielectric characterization of flexible plastic films using printed electronics," inProc. 87th General Assembly Sci. Symp. Int. Union Radio Sci. (URSI GASS), 2016, pp. 1-4.

[0142] [3]KA El-Farahaty, EA Seisa, and SG El-Sheikh, "Influence ofwavelength and temperature on the optical and some structural properties ofpolyester and polyamide surgical suture fibers," Opt. Mater. vol. 32, no. 9,pp. 928-935, Jul. 2010.

[0143] [4]T. Karpisz, B. Salski, P. Kopyt, and J. Krupka, “Measurement of dielectrics from 20 to 50 GHz with a Fabry-Pérot open resonator,” IEEE Trans.Microw. Theory Techn. vol. 67, no. 5, pp. 1901-1908, 2019.

[0144] As shown in Table 1, the measurement results of this embodiment are in good agreement with those obtained from other literature, thus verifying the accuracy of this measurement and inversion process. While ensuring the reliability of the measurement and extraction results, the transmittance coefficient of the material was extracted using the proposed FA-PSO-based method.

[0145] Extracting electromagnetic parameters from single-component materials is relatively simple. However, for multi-component or non-homogeneous composite materials, parameter extraction remains a significant challenge due to the complexity of their internal structures. Therefore, to verify the superior performance of this invention, three typical building materials commonly used in construction were selected as research objects. Specifically, the transmission coefficients of acrylic, black rubber, and bakelite boards under specific polarization modes were measured in the 20-35 GHz frequency band. The results are as follows: Figure 7 As shown.

[0146] Depend on Figure 7 The results show that all samples exhibit distinct frequency characteristics. Significant differences in response exist among the different materials, directly reflecting their different internal structures. Specifically, compared to the more complex internal structure of bakelite, the relatively simpler structures of acrylic and rubber materials show a smoother change in transmission coefficient with frequency. Subsequently, the complex permittivity of the three materials was obtained by inverting the measured transmission data using the FA-PSO algorithm. The inverted material parameters are shown in Table 2.

[0147] Table 2 Calculated thickness and measured thickness of the measured material

[0148]

[0149] Table 2 summarizes the dielectric constant, conductivity, evaluation thickness, and RMSE of the inversion model for each material sample obtained by this method. The low RMSE values ​​indicate that the proposed FA-PSO inversion model is in high agreement with the experimental data, thus verifying the accuracy and reliability of this method in simultaneously evaluating the dielectric properties and geometry of materials.

[0150] The electromagnetic parameter measurement method described in this invention was used to measure building panels. The measured transmission coefficient was basically consistent with the inverted transmission coefficient. The errors in dielectric constant and conductivity parameters met the requirements for industrial applications. During the thickness measurement process, the thickness error was only 0.6 mm. According to the simulation results, the measurement results of building panels with different thicknesses can reach the lower bound of Clemens, which has the theoretical optimal performance.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the present invention.

Claims

1. An electromagnetic property measurement device based on the free space method and the FA-PSO algorithm, characterized in that, The device includes: a vector network analyzer, a transmitting antenna, a receiving antenna, and a control computer; The vector network analyzer includes two ports: a first port is connected to a transmitting antenna via a first coaxial cable; and a second port is connected to a receiving antenna via a second coaxial cable. The transmitting antenna and the receiving antenna are positioned in space relative to the material under test to form an electromagnetic wave propagation path containing the material under test, which is used to measure the scattering parameters of the material under test. The control computer is communicatively connected to the vector network analyzer.

2. The electromagnetic property measurement device based on the free space method and FA-PSO algorithm according to claim 1, characterized in that, The transmitting antenna and the receiving antenna are each mounted by a precision positioning device, and a fixing device for mounting the material to be tested is provided on the electromagnetic wave propagation path formed by the transmitting antenna and the receiving antenna.

3. The electromagnetic characteristic measurement device based on the free space method and FA-PSO algorithm according to claim 2, characterized in that, The scattering parameter measurement includes: transmission measurement and reflection measurement; wherein, when performing transmission measurement on the material under test, the transmitting antenna and the receiving antenna are on opposite sides of the material under test; when performing reflection measurement on the material under test, the transmitting antenna and the receiving antenna are on the same side of the material under test. During each scattering parameter measurement, the positions of the transmitting antenna and the receiving antenna remain unchanged; transmission and reflection measurements are performed only by changing the position of the material under test.

4. The electromagnetic characteristic measurement device based on the free space method and FA-PSO algorithm according to claim 1, characterized in that, The control computer includes: The parameter setting module is used to set the operating parameters of the vector network analyzer; wherein the operating parameters include, but are not limited to: scanning frequency range, number of frequency sampling points, transmit power, and intermediate frequency bandwidth. The data acquisition module is used to acquire the reference frequency response and material frequency response from the vector network analyzer; The data preprocessing module is used to calculate the scattering parameters of the material under test based on the reference frequency response and the material frequency response; wherein the scattering parameters include: reflection coefficient and transmission coefficient; The parameter inversion module is used to optimize and invert the dielectric constant, conductivity and material thickness of the material under test based on the scattering parameters of the material under test using the FA-PSO algorithm, and output the inversion results.

5. An electromagnetic characteristic measurement method based on the free-space method and the FA-PSO algorithm, implemented using the electromagnetic characteristic measurement device based on the free-space method and the FA-PSO algorithm as described in any one of claims 1-4, characterized in that, This method includes the following steps: The scattering parameters of the material under test are obtained by measuring the scattering parameters of the material under test; Based on the scattering parameters, an electromagnetic wave propagation model is constructed with the complex permittivity and material thickness of the material under test as variables; Based on the electromagnetic wave propagation model, the scattering parameters of the material under test are used as input, and the FA-PSO algorithm is used to optimize and invert the dielectric constant, conductivity and thickness of the material under test, and the inversion results are obtained.

6. The electromagnetic property measurement method based on the free space method and FA-PSO algorithm according to claim 5, characterized in that, The specific details of obtaining the scattering parameters of the material under test by measuring the scattering parameters are as follows: The electromagnetic characteristic measurement device based on the free space method and FA-PSO algorithm is deployed, the operating parameters of the vector network analyzer are set, and the error correction of the vector network analyzer is performed. Without placing the test material, the reference frequency response of the transmission measurement under the current free-space conditions is measured by performing a frequency band scan. ; The material under test is placed at the designated location for transmission measurement between the transmitting and receiving antennas, and a frequency band scan is performed to measure the material's frequency response under the current free-space conditions. ; Material frequency response to the transmission measurement With reference frequency response The transmittance coefficient of the material under test is obtained by performing point-by-point division and noise reduction. A reference copper plate is placed at a predetermined position between the transmitting and receiving antennas, and a frequency band scan is performed to measure the reference frequency response of the reflection measurement under the current free-space conditions. ; The material under test is placed at the designated reflection measurement position between the transmitting and receiving antennas, and a frequency band scan is performed to measure the material's frequency response under the current free-space conditions. ; Material frequency response to the reflection measurement With reference frequency response The reflection coefficient of the material under test is obtained by performing point-by-point division and noise reduction.

7. The electromagnetic property measurement method based on the free space method and FA-PSO algorithm according to claim 5, characterized in that, The electromagnetic wave propagation model is as follows: ； ； in, Transmission coefficient; For purely linearly polarized Fresnel reflection coefficients; For material thickness; It is a natural constant; The reflection coefficient; Let be the phase constant, expressed as: ； in, Wavelength in free space; Angle of incidence; is the complex permittivity.

8. The electromagnetic property measurement method based on the free space method and FA-PSO algorithm according to claim 5, characterized in that, Based on the electromagnetic wave propagation model, using the scattering parameters of the material under test as input, the FA-PSO algorithm is used to optimize and invert the dielectric constant, conductivity, and thickness of the material under test, and the specific contents of the inversion results are as follows: The root mean square error between the transmittance coefficient of the material under test and the transmittance coefficient obtained by algorithm inversion is used as the objective function. Set the FA population size, and generate an initial FA population based on the FA population size; Each FA individual in the initial FA population represents a set of PSO control parameters, including: inertia weights. Learning factors and learning factors ; Set an iteration cycle, and execute the following procedure within each iteration cycle: For each FA individual in the current FA population Based on the electromagnetic wave propagation model and the scattering parameters of the material under test, using FA individual The corresponding PSO control parameters are iteratively optimized using an improved PSO algorithm, and the optimal PSO individual and the minimum value of the objective function corresponding to the optimal PSO individual are obtained by minimizing the objective function; wherein the PSO individual is a set of dielectric constant, conductivity and material thickness of the material to be tested; The objective function value corresponding to the optimal PSO individual is used as the FA individual. The fitness of; If the current iteration cycle does not meet the preset termination condition, the FA algorithm is used to optimize the current FA population based on the fitness of all FA individuals in the current FA population to obtain an updated FA population. If the current iteration cycle meets the preset termination condition, the dielectric constant, conductivity, and material thickness of the material to be tested corresponding to the best PSO individual in the current iteration cycle will be used as the inversion result.

9. The electromagnetic property measurement method based on the free space method and FA-PSO algorithm according to claim 8, characterized in that, The improved PSO algorithm is as follows: based on the set PSO population size, an initial PSO population is generated using a Gaussian distribution initialization strategy based on prior experience. The PSO control parameters remain fixed within each set iteration cycle; For each PSO individual in the current PSO population In each iteration, the PSO individual is updated using the PSO control parameters within the current iteration cycle. The position of the PSO individual in the current iteration is calculated. The updated objective function value corresponding to the position; PSO individuals in the current iteration The updated objective function value corresponding to the position, and the PSO individual The corresponding historical best objective function value is compared. If the objective function value corresponding to the updated position is less than the historical best objective function value, then the PSO individual in the current iteration is... The updated position is used as the PSO individual in the current iteration. The optimal solution; otherwise, the PSO individual corresponding to the historical optimal objective function value. Position as the PSO individual in the current iteration The optimal solution; From the optimal solutions of all PSO individuals in the current PSO population, select the optimal solution with the smallest objective function value as the global optimal solution of the current PSO population. Determine whether the current iteration count has reached the preset iteration cycle limit. If not, continue to execute the next iteration and update the global optimal solution and the optimal PSO individual. If it has reached the limit, terminate the PSO algorithm, output the global optimal solution and the minimum value of the objective function corresponding to the global optimal solution, and set the PSO individual corresponding to the global optimal solution as the optimal PSO individual.

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