Shielding effectiveness prediction method of VPX chassis based on genetic algorithm

Abstract

The present application relates to a kind of genetic algorithm-based VPX cabinet shielding effectiveness prediction method, belong to electromagnetic environment effect field.By CST electromagnetic simulation software, the shielding effectiveness of VPX cabinet under plane wave irradiation is analyzed and simulation modeling is carried out, according to simulation result, the characteristic parameter matrix of VPX cabinet is extracted using transmission line equivalent circuit model and genetic algorithm, the shielding effectiveness of different positions in cabinet is predicted, the accuracy and reliability of algorithm result are verified by comparing the simulation result and algorithm theoretical calculation result of shielding effectiveness, based on the characteristic parameter matrix of extracted cabinet, the influence of distance from plane wave incidence surface on shielding effectiveness under different frequency points is explored, and the optimal point of shielding effectiveness in cabinet under different frequency points is determined according to algorithm result.The beneficial effect is to successfully predict the shielding effectiveness of cabinet at different frequency points and different positions, to provide reference for the selection of internal wiring and sensitive device installation position of cabinet, and a large amount of computing resources is saved.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic environment effects, specifically to a method for predicting the shielding effectiveness of a VPX chassis based on a genetic algorithm. This method can predict the shielding effectiveness at different locations at different frequencies, and the predicted shielding effectiveness results have good accuracy and reliability, which can provide a reference for the selection of wiring inside the chassis and the installation location of sensitive devices. Background Technology

[0002] With the rapid development of electronics, electrical engineering, computer science, and control technology, electromagnetic compatibility issues in complex systems are becoming increasingly common. Especially with the advancements in functional integration, miniaturization, high power, and high reliability of electronic equipment, new requirements have been placed on the structural design of electronic enclosures. Traditional enclosure structures can no longer meet the load-bearing requirements of next-generation electronic equipment. The VPX structure enclosure, based on the VITA46 standard, is a ruggedized type with strong seismic and impact resistance, making it suitable for applications requiring high standards of humidity, low air pressure, salt spray resistance, and mold prevention. Its compact design and small size make it particularly suitable for electronic control equipment in missile-borne aircraft. Furthermore, its structural form is suitable for vehicle-mounted integrated control equipment in certain fields, offering reliable performance and facilitating installation, maintenance, transportation, and replacement.

[0003] The US electronics industry developed earlier and has accumulated considerable experience in the development and application of VPX serial buses. Many of its computer architectures utilize the VITA48.2 ruggedized structure, and various applications employ conductive cooling methods. GE Intelligent Platforms, based in Charlottesville, Virginia, has launched a ruggedized, open VPX-compatible SBC312 3U single-board computer based on the Freescale Semiconductor QorIQ P4080 8-core processor, meeting the needs of embedded computing applications with space and weight constraints, such as drones. General Electric, located in Huntsville, Alabama, has launched the SBC326 ruggedized 3U VPX single-board computer based on a fourth-generation Intel Core i7 processor, primarily for use in severely restricted environments and special operations, such as unmanned combat vehicles.

[0004] With the development of modern computer hardware and software, the design of electronic chassis in China has also progressed rapidly. As new ideas and methods for electronic product design emerge, the structure of electronic devices changes accordingly, leading to the development of chassis with the "three-fold" standard of "generalization, serialization, and modularization." For example, the new generation of VPX chassis adopts a modular, sealed design and vacuum brazing process, which further improves the shock resistance, heat transfer efficiency, electromagnetic shielding performance, welding quality, and chassis precision of electronic equipment chassis, achieving good application results in chassis development. Beijing Guoke Huanyu Space Technology Co., Ltd. (UCAS) has become a member of the VITA organization, sharing VITA standards, and has developed several VPX bus-based electronic devices. For example, they have developed a VPX chassis and functional modules based on VPX46.2, which are smaller and more functional than traditional performance devices. Tianjin Linghao Technology Co., Ltd. has also begun researching VPX system solutions and has started researching the OPEN VITA64 standard, but currently has relatively few chassis and is mainly in the theoretical research stage.

[0005] Currently, the main methods for calculating the shielding effectiveness of perforated shielded cavities include experimental measurement, numerical simulation, and analytical algorithms. Experimental measurement can accurately verify the calculated results of the model, but experiments typically require shielded rooms, microwave anechoic chambers, and spectrum analyzers, as well as expensive instruments, resulting in relatively high costs and significant limitations. Jiao Chongqing et al. developed a testing device and measurement scheme for the shielding effectiveness of materials against power frequency electromagnetic fields based on the shielded room method. In this experiment, the relative positions of the conductive electrode plate and the field strength probe, as well as the distance to the test window of the shielded room, were considered to affect the experimental results. Numerical methods, while capable of accurately modeling complex models, consume large amounts of memory and have long computation times, especially when precise calculation results are required. Furthermore, model remodeling is often necessary when model parameters are changed. Examples include numerical calculation methods based on Maxwell's equations such as the method of moments, finite element method, finite-difference time-domain method, and transmission line matrix method. Analytical methods require equivalent treatment of the shielded cavity during modeling, consume less memory, have high computational efficiency, and facilitate the analysis of the impact of different parameter changes on the cavity's shielding effectiveness.

[0006] Due to the specific structural characteristics of the VPX chassis and its complex working environment, the shielding effectiveness of the computer chassis obtained through equivalent transmission line theory differs significantly from the actual situation. Furthermore, numerical simulation methods using electromagnetic simulation software such as CST often require the selection of a large number of probes and repeated modeling, resulting in long simulation times and high requirements for computer performance. Summary of the Invention

[0007] This invention provides a method for predicting the shielding effectiveness of a VPX chassis based on a genetic algorithm. The method extracts the characteristic parameters of the VPX chassis using a genetic algorithm and combines them with the equivalent transmission line theory to predict the shielding effectiveness of the VPX chassis in complex environments. It can obtain the shielding effectiveness prediction curves of the chassis at different locations at different frequency points, providing a reference for the selection of internal wiring and installation positions of sensitive devices.

[0008] The technical solution adopted by this invention includes the following steps:

[0009] Step 1: Analyze and simulate the shielding effectiveness of the VPX chassis under plane wave irradiation using CST electromagnetic simulation software;

[0010] Step 2: Genetic algorithm parameter settings, including the number of individuals in the population, the number of chromosomes, the maximum number of iterations, the crossover probability, the mutation probability, and the initialization of the population;

[0011] Step 3: Construct the objective function, calculate the fitness of individuals in the population, and obtain the initial individual fitness values. The maximum value is the initial global extreme value, and the corresponding chromosome is the initial global optimal chromosome.

[0012] Step 4: Update the chromosomes corresponding to each individual through selection, crossover, and mutation.

[0013] Step 5: Calculate the fitness of all individuals after the update. If the maximum fitness of the current individual is greater than the maximum fitness of the individual before the update, replace the original chromosome of that individual with the current chromosome. Otherwise, retain the original chromosome and proceed to the next iteration. Repeat the update operation until the maximum number of iterations is reached, terminate the iteration, and output the optimal feature parameter matrix.

[0014] Step 6: Calculate the shielding effectiveness at another point on the VPX chassis based on the characteristic parameter matrix, and compare it with the simulation results to verify the effectiveness and reliability of the method.

[0015] Step 7: Predict the shielding effectiveness of the VPX chassis at other locations under different frequency points based on the feature parameter matrix, analyze the advantageous locations of the chassis shielding effectiveness at different frequency points, and provide a reference for the selection of internal wiring and installation locations of sensitive components.

[0016] Step 1 of this invention, based on the RS103 electric field radiation susceptibility experiment in GJB 151B-2013, uses CST electromagnetic simulation software to numerically model and simulate test conditions. Basic settings are configured in CST according to simulation requirements, including frequency band selection and excitation source selection. Considering the structural characteristics and operating environment of the VPX chassis, the electromagnetic environment effect of the VPX chassis at higher frequencies is taken into account; therefore, a frequency coverage range of 1GHz-10GHz is selected. Since the VPX chassis conforms to the space system in the field strength limit standard of the RS103 electric field radiation susceptibility experiment, a short-time pulsed plane wave with a frequency domain peak value of 20V / m is used as the excitation source to irradiate the chassis, simulating an external high-field-strength electromagnetic environment, and analyzing the electromagnetic coupling characteristics and shielding effectiveness of the VPX chassis under this environment.

[0017] Step 2 of this invention involves setting the parameters of the genetic algorithm and initializing the population parameters. In the genetic algorithm, the number of individuals in the population is N, and each individual has three chromosomes, representing the equivalent aperture impedance parameter, aperture shape parameter, and aperture position parameter of the VPX chassis, respectively. Floating-point encoding is used to encode the chromosomes to ensure that the gene values ​​are within a given range. The encoding expression is as follows:

[0018] f i =a i +x i (b i -a i ), x i ∈[0,1]

[0019] Define the domain [a] i ,b i The chromosome f of the i-th individual within ] i Mapped to a real number x on the interval [0,1] i , i = 1, 2…N;

[0020] Initialize population parameters; maximum number of iterations is iter max The crossover probability is acr. A higher crossover probability results in faster generation of new individuals, but excessively high crossover probability can disrupt the genetic pattern, while excessively low crossover probability slows down the search process. The mutation probability is mut. Excessively high mutation probability turns the genetic algorithm into a random search algorithm, while excessively low mutation probability makes it difficult to generate new individual structures. The random number matrix chrom within [0,1] is generated as shown below and used as the initial population:

[0021]

[0022] Step 3 of this invention involves constructing an objective function, calculating the fitness of individuals in the population, and obtaining initial individual fitness values, including:

[0023] Analyzing the equivalent circuit of the transmission line in the VPX chassis, the opening can be considered as a lossless transmission line with a short-circuited termination, and the shielding shell can be considered as a waveguide with a short-circuited termination. The transmission line telegraph equation is:

[0024]

[0025]

[0026] Where U(x) and I(x) are the voltage and current at any point on the transmission line, respectively, w is the angular frequency, h is the transmission line spacing, L is the transmission line inductance, and C is the transmission line capacitance; according to transmission line theory, Thevenin's theorem, and the definition of shielding effectiveness, the equivalent voltage source V1, equivalent impedance Z1, load Z2, and equivalent voltage V at the observation point are... p and shielding effectiveness SE p The equivalent circuit model of the transmission line is as follows:

[0027]

[0028] Where, k g Z g Let K0 be the phase impedance and characteristic impedance of the rectangular waveguide, K0 = 2π / λ, Z0 be the characteristic impedance of the wave propagating in free space, λ be the wavelength, a be the chassis length, and d be the phase impedance and characteristic impedance of the wave. i d represents the distance from the observation point to the plane wave incident surface and the dimensions of the VPX chassis in the direction of the plane wave incident surface, respectively; k1, k2, and k3 represent the aperture impedance parameters, aperture shape parameters, and aperture position parameters of the VPX chassis, respectively; SE p For the shielding effectiveness at the observation point location, Z ap V is the equivalent resistance at the observation point. ap Let f be the voltage across the resistor and f be the frequency.

[0029] The simulation results of shielding effectiveness are sampled and defined as matrix S, which serves as the criterion for selecting the dominant individual. Using the selected dominant individual and the theoretical shielding effectiveness value of the computer chassis based on the aforementioned transmission line equivalent circuit model, defined as matrix S', an objective function is constructed. The expression of the objective function is as follows:

[0030] min P=|s(f i )-s'(f i )| 2

[0031] Wherein, s(f i ) represents the simulated sampled value of shielding effectiveness, s'(f i The shielding effectiveness is represented by the theoretically calculated value, and through encoding mapping, the objective function value P(x) is obtained. i P(x) represents an individual's adaptability. i The larger the value of P(x), the weaker the adaptability.i The smaller the value, the stronger the adaptability;

[0032] The fitness evaluation function is:

[0033]

[0034] Calculate the fitness of individuals in the population to obtain the initial individual fitness value;

[0035] Where τ=0.001, F(x) i The larger the value of F(x), the stronger the adaptability. i The smaller the value, the weaker the adaptability.

[0036] Step 4 of this invention involves updating the chromosomes corresponding to each individual through selection, crossover, and mutation; specifically as follows:

[0037] Select operation:

[0038] The fitness of an individual is the basis for the selection process. Using roulette wheel selection, the higher the fitness value, the higher the chance of being selected; the lower the fitness value, the lower the chance of being selected. The selection probability is:

[0039]

[0040] Where n is the number of samples drawn;

[0041] Cross operation:

[0042] The new individuals generated after arithmetic crossover and random linear recombination of any two individuals in each subpopulation are:

[0043]

[0044] Where u1 and u2 are random numbers uniformly distributed within [0,1];

[0045] Mutation operation:

[0046] To maintain genetic diversity, escape the local search range, and prevent premature maturation, a small probability perturbation, mut, is added to the genes of the parent chromosome in each subpopulation.

[0047]

[0048] Among them, u n ,u m It is a random number uniformly distributed within [0,1].

[0049] In step 5 of this invention, the optimal individual in the population has the highest fitness value and the best fit with the shielding effectiveness simulation results. The result of the optimal estimate is a feature parameter matrix, containing three sets of feature parameters, denoted as... These represent the equivalent aperture impedance parameter, aperture shape parameter, and aperture location parameter, respectively, and are represented by the chrom_best matrix:

[0050]

[0051] The beneficial effects of this invention are as follows: Based on the traditional transmission line theory formula, this invention combines the equivalent aperture impedance parameters, aperture shape parameters, and aperture position parameters of the VPX chassis to obtain a prediction formula for the shielding effectiveness at any position inside the VPX chassis under complex environments. By extracting the characteristic parameters of the VPX chassis through a genetic algorithm and predicting the chassis's shielding effectiveness, the dominant individuals within the population can be quickly selected, allowing for effective fitting of the VPX chassis's shielding effectiveness simulation results. This successfully predicts the shielding effectiveness of the chassis at different frequencies and positions, solving the problems of significant discrepancies between the shielding effectiveness of the computer chassis calculated using traditional equivalent transmission line theory and actual conditions in complex electromagnetic environments, and the long simulation cycle and high computer performance requirements associated with numerical simulation methods using electromagnetic simulation software such as CST for calculating the shielding effectiveness at different positions of the computer chassis. This invention saves a significant amount of computing resources. Attached Figure Description

[0052] Figure 1 This is a flowchart of the method of the present invention;

[0053] Figure 2 It is the time-domain waveform diagram of the excitation source;

[0054] Figure 3 It is the frequency domain waveform diagram of the excitation source;

[0055] Figure 4 This is a scene depicting a plane wave irradiating a VPX chassis.

[0056] Figure 5 This is a schematic diagram of the probe position;

[0057] Figure 6 This is the equivalent circuit diagram of the shielding enclosure;

[0058] Figure 7 This is a fitting curve of the simulation results and algorithm results of the shielding effectiveness at point P;

[0059] Figure 8 This is a comparison chart of the simulation results and algorithm results of the Q-point shielding effectiveness;

[0060] Figure 9 This is a graph showing the effect of the distance from the plane wave incident surface at a frequency of 5500MHz on the shielding effectiveness;

[0061] Figure 10 This is a graph showing the effect of the distance from the plane wave incident surface at a frequency of 6400MHz on the shielding effectiveness. Detailed Implementation

[0062] like Figure 1 As shown, it includes the following steps:

[0063] Step 1: Analyze and simulate the shielding effectiveness of the VPX chassis under plane wave irradiation using CST electromagnetic simulation software;

[0064] Step 2: Genetic algorithm parameter settings, including the number of individuals in the population, the number of chromosomes, the maximum number of iterations, the crossover probability, the mutation probability, and the initialization of the population;

[0065] Step 3: Construct the objective function, calculate the fitness of individuals in the population, and obtain the initial individual fitness values. The maximum value is the initial global extreme value, and the corresponding chromosome is the initial global optimal chromosome.

[0066] Step 4: Update the chromosomes corresponding to each individual through selection, crossover, and mutation.

[0067] Step 5: Calculate the fitness of all individuals after the update. If the maximum fitness of the current individual is greater than the maximum fitness of the individual before the update, replace the original chromosome of that individual with the current chromosome. Otherwise, retain the original chromosome and proceed to the next iteration. Repeat the update operation until the maximum number of iterations is reached, terminate the iteration, and output the optimal feature parameter matrix.

[0068] Step 6: Calculate the shielding effectiveness at another point on the VPX chassis based on the characteristic parameter matrix, and compare it with the simulation results to verify the effectiveness and reliability of the method.

[0069] Step 7: Predict the shielding effectiveness of the VPX chassis at other locations under different frequency points based on the feature parameter matrix, analyze the advantageous locations of the chassis shielding effectiveness at different frequency points, and provide a reference for the selection of internal wiring and installation locations of sensitive components.

[0070] The specific steps are as follows:

[0071] Step 1: Based on the RS103 electric field radiation susceptibility experiment in GJB 151B-2013, numerical modeling and simulation of test conditions are performed using CST electromagnetic simulation software. Basic settings are configured in CST according to simulation requirements, including frequency band selection and excitation source selection. Due to the structural characteristics and operating environment of the VPX chassis, the electromagnetic environment effect of the VPX chassis at higher frequencies is considered; therefore, a frequency coverage range of 1GHz-10GHz is selected. The VPX chassis conforms to the space system in the field strength limit standard of the RS103 electric field radiation susceptibility experiment; therefore, a short-time pulsed plane wave with a peak frequency of 20V / m is used as the excitation source to irradiate the chassis, simulating the external high-field-strength electromagnetic environment. The electromagnetic coupling characteristics and shielding effectiveness of the VPX chassis under this environment are analyzed. Specifically, as follows... Figures 2 to 4 As shown, Figure 2 The time-domain waveform of the excitation source. Figure 3 The frequency domain waveform of the excitation source, Figure 4 The scene of plane wave irradiation on VPX chassis is shown. In CST electromagnetic simulation software, the basic parameters are set as follows: Dimensions: mm, Frequency: GHz, Temperature: Kelvin, Time: ns. The chassis material is set to PEC (ideal conductor), the background material is set to normal, the boundary condition is set to open, and the chassis size is 200*150*150. Figure 5 The diagram shows the probe positions. The probe positions are selected, with point P having coordinates (0, 0, 75) and located at the geometric center of the chassis, and point Q having coordinates (0, 35, 75).

[0072] CST uses the time-domain TLM method to simulate electromagnetic models. Its basic principle is that the software first sets the spatial excitation source as an impulse pulse during simulation. Since the impulse pulse has an extremely narrow width in the time domain (approaching infinitely narrow), it can cover a very wide frequency band (approaching infinitely wide) in the frequency domain. Then, the impulse pulse excites the entire system in the time domain. The result is the convolution of this pulse with the system function h(t). If it is transformed to the frequency domain by Fourier transform, it is the product of the frequency domain response of the impulse pulse and the system function H(f). Since the frequency domain response of the impulse pulse is 1 after Fourier transform, H(f) is the frequency domain response of the entire system.

[0073] Step 2: Configure the parameters for the genetic algorithm. The population contains N individuals, each with three chromosomes representing the equivalent aperture impedance, aperture shape, and aperture location parameters of the VPX chassis. Floating-point encoding is used to encode the chromosomes, ensuring that gene values ​​remain within a given range. The encoding expression is as follows:

[0074] f i =a i +x i (bi -a i ), x i ∈[0,1]

[0075] Define the domain [a] i ,b i The i-th chromosome f within ] i Mapped to a real number x on the interval [0,1] i , i = 1, 2…N;

[0076] Specifically, the number of individuals in the population is set to 100;

[0077] Initialize population parameters; maximum number of iterations is iter max The crossover probability is acr. A higher crossover probability results in faster generation of new individuals, but excessively high crossover probability can disrupt the genetic pattern, while excessively low crossover probability slows down the search process. The mutation probability is mut. Excessively high mutation probability turns the genetic algorithm into a random search algorithm, while excessively low mutation probability makes it difficult to generate new individual structures. The random number matrix chrom within [0,1] is generated as shown below and used as the initial population:

[0078]

[0079] Specifically, the maximum number of iterations is set to 100, the crossover probability is set to 0.2, and the mutation probability is set to 0.2.

[0080] Step 3: Analyze the equivalent circuit of the transmission line in the VPX chassis. The opening can be considered as a lossless transmission line with a short-circuited termination, and the shielding shell can be considered as a waveguide with a short-circuited termination. The transmission line telegraph equation is:

[0081]

[0082]

[0083] Where U(x) and I(x) are the voltage and current at any point on the transmission line, respectively, w is the angular frequency, h is the transmission line spacing, L is the transmission line inductance, and C is the transmission line capacitance. Figure 6 The diagram shown is the equivalent circuit diagram of the shielding enclosure. Based on transmission line theory, Thevenin's theorem, and the definition of shielding effectiveness, the equivalent voltage source V1, equivalent impedance Z1, load Z2, and equivalent voltage V at the observation point are... p and shielding effectiveness SE p The equivalent circuit model of the transmission line is as follows:

[0084]

[0085] Where, k g Z gLet K0 be the phase impedance and characteristic impedance of the rectangular waveguide, K0 = 2π / λ, Z0 be the characteristic impedance of the wave propagating in free space (taken as a fixed value of 377Ω), λ be the wavelength, a be the chassis length (set to 200), and d be the phase impedance and characteristic impedance of the rectangular waveguide. i d represents the distance from the observation point to the plane wave incident surface and the dimension of the VPX chassis in the direction of the plane wave incident surface, respectively, set to 150 and 75; k1, k2, and k3 represent the aperture impedance parameters, aperture shape parameters, and aperture position parameters of the VPX chassis, respectively, and SE p For the shielding effectiveness at the observation point location, Z ap V is the equivalent resistance at the observation point. ap Let f be the voltage across the resistor, and f be the frequency, which is [1000, 10000].

[0086] The simulation results of shielding effectiveness are sampled and defined as matrix S, which serves as the criterion for selecting the dominant individual. Using the selected dominant individual and the theoretical shielding effectiveness value of the computer chassis based on the aforementioned transmission line equivalent circuit model, defined as matrix S', an objective function is constructed. The expression of the objective function is as follows:

[0087] minP=|s(f i )-s'(f i )| 2

[0088] Wherein, s(f i ) represents the simulated sampled value of shielding effectiveness, s'(f i The shielding effectiveness is represented by the theoretically calculated value, and through encoding mapping, the objective function value P(x) is obtained. i P(x) represents an individual's adaptability. i The larger the value of P(x), the weaker the adaptability. i The smaller the value, the stronger the adaptability;

[0089] The fitness evaluation function is:

[0090]

[0091] Calculate the fitness of individuals in the population to obtain the initial individual fitness value;

[0092] Where τ=0.001, F(x) i The larger the value of F(x), the stronger the adaptability. i The smaller the value, the weaker the adaptability.

[0093] Step 4: Update the chromosomes corresponding to each individual through selection, crossover, and mutation.

[0094] Select operation:

[0095] The fitness of an individual is the basis for the selection process. Using roulette wheel selection, the higher the fitness value, the higher the chance of being selected; the lower the fitness value, the lower the chance of being selected. The selection probability is:

[0096]

[0097] Where n is the number of samples drawn;

[0098] Cross operation:

[0099] The new individuals generated after arithmetic crossover and random linear recombination of any two individuals in each subpopulation are:

[0100]

[0101] Where u1 and u2 are random numbers uniformly distributed within [0,1];

[0102] Mutation operation:

[0103] To maintain genetic diversity, escape the local search range, and prevent premature maturation, a small probability perturbation, mut, is added to the genes of the parent chromosome in each subpopulation.

[0104]

[0105] Among them, u n ,u m A random number uniformly distributed within [0,1].

[0106] The above operations enhance the ability of individuals to escape local solution spaces, prevent them from getting trapped in local optima, and enable them to find the global optimum more effectively, thereby improving the convergence speed and optimization ability of the algorithm.

[0107] Step 5: Calculate the fitness of all individuals after the update. If the maximum fitness of a current individual is greater than the maximum fitness of an individual before the update, replace the original chromosome of that individual with the current chromosome; otherwise, retain the original chromosome and proceed to the next iteration, repeating the update operation. The genetic algorithm terminates when it reaches the set maximum number of iterations. The individual with the highest fitness value in the population shows the best fit to the shielding effectiveness simulation results. The optimal estimate is a feature parameter matrix containing three sets of feature parameters, denoted as... These represent the equivalent aperture impedance parameter, aperture shape parameter, and aperture location parameter, respectively, and are represented by the chrom_best matrix:

[0108]

[0109] The shielding effectiveness of point P on the VPX chassis is calculated based on the globally optimal solution selected by the genetic algorithm, such as... Figure 7As shown in the figure, the fitting curves of the simulation results and the algorithm results are good.

[0110] Step 6: Calculate the shielding effectiveness at point Q inside the VPX chassis based on the extracted feature parameter matrix. Compare this with the CST simulation results at point Q (0, 35, 75). Figure 8 As shown, the two shielding effectiveness curves have a high degree of fit, proving the accuracy and effectiveness of the prediction results. The maximum shielding effectiveness of 18dB was obtained at the 7000MHz frequency point.

[0111] Step 7: Based on the extracted feature parameter matrix, predict the shielding effectiveness at different locations inside the VPX chassis at different frequency points, and analyze the advantageous locations of the chassis shielding effectiveness at different frequency points, such as... Figure 9 The figure shows the effect of distance from the plane wave incident surface on shielding effectiveness at a frequency of 5500MHz. As can be seen from the figure, at 5500MHz, the VPX chassis exhibits good shielding effectiveness when the distance from the plane wave incident surface inside the chassis is 1.5cm, 4cm, 7cm, 9.5cm, and 12.5cm. The maximum shielding effectiveness of 39dB is achieved at a distance of 1.5cm. Figure 10 The figure shows the effect of the distance from the plane wave incident surface on the shielding effectiveness at a frequency of 6400MHz. As can be seen from the figure, at a frequency of 6400MHz, the VPX chassis has good shielding effectiveness when the distance from the plane wave incident surface inside the chassis is 1cm, 3.5cm, 5.5cm, 8cm, 10.5cm, and 12.5cm. The maximum shielding effectiveness of 30dB is obtained when the distance is 8cm. This provides a reference for the selection of the wiring inside the chassis and the installation position of sensitive devices.

[0112] This invention applies a genetic algorithm to extract the characteristic parameters of a VPX chassis and predict its shielding effectiveness. This allows dominant individuals within the population to be selected quickly, enabling the simulation results of the VPX chassis's shielding effectiveness to be effectively fitted. It successfully predicts the shielding effectiveness of the chassis at different frequencies and locations, saving a significant amount of computational resources.

Claims

1. A method for predicting the shielding effectiveness of a VPX chassis based on a genetic algorithm, characterized in that, Includes the following steps: Step 1: Analyze and simulate the shielding effectiveness of the VPX chassis under plane wave irradiation using CST electromagnetic simulation software; Step 2: Genetic algorithm parameter settings, including the number of individuals in the population, the number of chromosomes, the maximum number of iterations, the crossover probability, the mutation probability, and the initialization of the population; Step 3: Construct the objective function, calculate the fitness of individuals in the population, and obtain the initial individual fitness values. The maximum value is the initial global extreme value, and the corresponding chromosome is the initial global optimal chromosome. Step 4: Update the chromosomes corresponding to each individual through selection, crossover, and mutation. Step 5: Calculate the fitness of all individuals after the update. If the maximum fitness of the current individual is greater than the maximum fitness of the individual before the update, replace the original chromosome of that individual with the current chromosome. Otherwise, retain the original chromosome and proceed to the next iteration. Repeat the update operation until the maximum number of iterations is reached, terminate the iteration, and output the optimal feature parameter matrix. Step 6: Calculate the shielding effectiveness at another point on the VPX chassis based on the characteristic parameter matrix, and compare it with the simulation results to verify the effectiveness and reliability of the method. Step 7: Predict the shielding effectiveness of the VPX chassis at other locations under different frequency points based on the feature parameter matrix, analyze the advantageous locations of the chassis shielding effectiveness at different frequency points, and provide a reference for the selection of internal wiring and installation locations of sensitive components.

2. The method for predicting the shielding effectiveness of a VPX chassis based on a genetic algorithm according to claim 1: characterized in that: In step 1, based on the RS103 electric field radiation susceptibility experiment in GJB 151B-2013, the CST electromagnetic simulation software is used to numerically model and simulate the test conditions. Basic settings are configured in CST according to simulation requirements, including frequency band selection and excitation source selection. Considering the structural characteristics and operating environment of the VPX chassis, the electromagnetic environment effect of the VPX chassis at higher frequencies is taken into account; therefore, a frequency coverage range of 1GHz-10GHz is selected. Since the VPX chassis conforms to the space system in the field strength limit standard of the RS103 electric field radiation susceptibility experiment, a short-time pulsed plane wave with a frequency domain peak value of 20V / m is used to irradiate the chassis, simulating the external high-field-strength electromagnetic environment. The electromagnetic coupling characteristics and shielding effectiveness of the VPX chassis under this environment are analyzed.

3. The method for predicting the shielding effectiveness of a VPX chassis based on a genetic algorithm according to claim 1: characterized in that: In step 2, the parameters of the genetic algorithm are set and the population parameters are initialized. In the genetic algorithm, the number of individuals in the population is N, and each individual has three chromosomes, representing the equivalent aperture impedance parameter, aperture shape parameter, and aperture position parameter of the VPX chassis, respectively. Floating-point encoding is used to encode the chromosomes to ensure that the gene values ​​are within a given range. The encoding expression is as follows: f i =a i +x i (b i -a i ),x i ∈[0,1] Define the domain [a] i ,b i The i-th chromosome f within ] i Mapped to a real number x on the interval [0,1] i , i = 1, 2…N; Initialize population parameters; maximum number of iterations is iter max The crossover probability is acr. A higher crossover probability results in faster generation of new individuals, but excessively high crossover probability can disrupt the genetic pattern, while excessively low crossover probability slows down the search process. The mutation probability is mut. Excessively high mutation probability turns the genetic algorithm into a random search algorithm, while excessively low mutation probability makes it difficult to generate new individual structures. The random number matrix chrom within [0,1] is generated as shown below and used as the initial population:

4. The method for predicting the shielding effectiveness of a VPX chassis based on a genetic algorithm according to claim 1: characterized in that: In step 3, the objective function is constructed, the fitness of individuals in the population is calculated, and the initial individual fitness values ​​are obtained, including: Analyzing the equivalent circuit of the transmission line in the VPX chassis, the opening can be considered as a lossless transmission line with a short-circuited termination, and the shielding shell can be considered as a waveguide with a short-circuited termination. The transmission line telegraph equation is: Where U(x) and I(x) are the voltage and current at any point on the transmission line, respectively, w is the angular frequency, h is the transmission line spacing, L is the transmission line inductance, and C is the transmission line capacitance. Based on transmission line theory, Thevenin's theorem, and the definition of shielding effectiveness, the equivalent voltage source V1, equivalent impedance Z1, load Z2, and equivalent voltage V at the observation point are... p and shielding effectiveness SE p The equivalent circuit model of the transmission line is as follows: Z2=jZ g tan[k g (dd i )] SE p =-20lg(V p / V ap ) From ap =k1jtan(k2f) Where, k g Z g Let K0 be the phase impedance and characteristic impedance of the rectangular waveguide, K0 = 2π / λ, Z0 be the characteristic impedance of the wave propagating in free space, λ be the wavelength, a be the chassis length, and d be the phase impedance and characteristic impedance of the wave. i d represents the distance from the observation point to the plane wave incident surface and the dimensions of the VPX chassis in the direction of the plane wave incident surface, respectively; k1, k2, and k3 represent the aperture impedance parameters, aperture shape parameters, and aperture position parameters of the VPX chassis, respectively; SE p For the shielding effectiveness at the observation point location, Z ap V is the equivalent resistance at the observation point. ap Let f be the voltage across the resistor and f be the frequency. The simulation results of shielding effectiveness are sampled and defined as matrix S, which serves as the criterion for selecting the dominant individual. Using the selected dominant individual and the theoretical shielding effectiveness value of the computer chassis based on the aforementioned transmission line equivalent circuit model, defined as matrix S', an objective function is constructed. The expression of the objective function is as follows: minP=|s(f i )-s'(f i )| 2 Wherein, s(f i ) represents the simulated sampled value of shielding effectiveness, s'(f i The shielding effectiveness is represented by the theoretically calculated value, and through encoding mapping, the objective function value P(x) is obtained. i P(x) represents an individual's adaptability. i The larger the value of P(x), the weaker the adaptability. i The smaller the value, the stronger the adaptability; The fitness evaluation function is: Calculate the fitness of individuals in the population to obtain the initial individual fitness value; Where τ=0.001, F(x) i The larger the value of F(x), the stronger the adaptability. i The smaller the value, the weaker the adaptability.

5. The method for predicting the shielding effectiveness of a VPX chassis based on a genetic algorithm according to claim 1: characterized in that: In step 4, the chromosomes corresponding to each individual are updated through selection, crossover, and mutation, as detailed below: Select operation: The fitness of an individual is the basis for the selection process. Using roulette wheel selection, the higher the fitness value, the higher the chance of being selected; the lower the fitness value, the lower the chance of being selected. The selection probability is: Where n is the number of samples drawn; Cross operation: The new individuals generated after arithmetic crossover and random linear recombination of any two individuals in each subpopulation are: Where u1 and u2 are random numbers uniformly distributed within [0,1]; Mutation operation: To maintain genetic diversity, escape the local search range, and prevent premature maturation, a small probability perturbation, mut, is added to the genes of the parent chromosome in each subpopulation. Among them, u n ,u m It is a random number uniformly distributed within [0,1].

6. The method for predicting the shielding effectiveness of a VPX chassis based on a genetic algorithm according to claim 1: characterized in that: In step 5, the individual with the highest fitness value in the population has the best fit with the simulation results of shielding effectiveness. The result of the optimal estimate is a feature parameter matrix containing three sets of feature parameters, denoted as... These represent the equivalent aperture impedance parameter, aperture shape parameter, and aperture location parameter, respectively, and are represented by the chrom_best matrix:

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