Multi-layer frequency selective surface wave-absorbing material modeling and optimization method based on neural network

Abstract

The present invention discloses a multi-layer frequency selective surface wave-absorbing material modeling and optimization method based on a neural network, and belongs to the field of frequency selective surfaces and to the technical field of the wave-absorbing materials. The method comprises: establishing a first-order resonant circuit of a frequency selective surface based on a transmission line; obtaining an S11 parameter curve through full-wave simulation, and using a genetic algorithm to carry out curve fitting to obtain an RLC value; inputting a sufficient number of samples into a BP neural network to obtain a mapping relationship between the geometric parameters of the frequency selective surface unit and the equivalent RLC; and calculating the S11 parameters of the entire wave-absorbing structure through the equivalent transmission line, deriving the equivalent RLC of the frequency selective surface unit, and using the genetic algorithm to optimize the wave-absorbing bandwidth. The method disclosed by the present invention has the advantages of high accuracy and high optimization efficiency.

Description

technical field [0001] The invention belongs to the field of frequency selective surfaces and the technical field of wave-absorbing materials, and in particular relates to an equivalent circuit parameter modeling of frequency-selective surfaces and an optimal design method for designing frequency-selective surface wave-absorbing materials with broadband and low reflectivity. Background technique [0002] Absorbing materials are widely used in military stealth, along with the development of the electronics industry. Absorbing materials have been applied in the fields of electronic communication, electronic devices, energy saving and emission reduction, and radiation protection. [0003] Frequency selective surface (FSS) is a planar periodic array structure composed of scattering surfaces with specific shapes. Due to its special frequency response characteristics, it is widely used in antenna design, electromagnetic compatibility, radome, absorbing materials and other fields. ...

AI Technical Summary

Problems solved by technology

At present, simply based on experience, adjusting parameters to design will consume huge labor costs and time

Moreover, the coupling relationship between each parameter is extremely strong, and it is often difficult to find a structure that meets the requirements by manually adjusting the parameters.

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