Swarm Intelligence Optimization Algorithm Based Coding DGS Resonator For High Q-factor Microwave Sensor Research

The advancement of material science and engineering offers high dielectric materials with a low profile,more durability,and high stability.However,in compact communication devices such as cell-phone shell design,the novel materials with suitable property is required to replace conventional metals.Therefore,the research to design a high sensitivity-based microwave sensor for detecting dielectric material thickness has great significance in the design,processing,and production flow industries.Additionally,these microwave sensors could also assist the material science and engineering field in precisely exploring the required material.Compared with other thickness detection instruments(acoustics,mass spectrometry,eddy current magnetic detection,and optical fiber detection),the microwave detection methods could easily penetrate the low loss dielectric materials under the premise of the non-destructive test.Moreover,it also possesses more accurate and highly reliable detection methods due to the exploration of the dielectric properties of materials corresponding to the individual testing material thickness.However,in existed microwave sensors,the high quality(Q-factor)is a prime requirement to achieve high sensitivity.The split-ring resonator(SRR)resonator structures offer high Q-factor,but they lead to low resolution,which affects the sensitivity of the sensor.Besides,the insufficient concentration of electric field intensity also influences the penetration depth of such resonators.Furthermore,in SRR resonators,the intensity of the electric field is not concentrated,which also restricts the sensor to detect the sensing material's thickness accurately.In this research,a high Q-factor incorporated defective ground structure(DGS)resonator based on Swarm Optimization Intelligent Algorithm(SOIA)is proposed to detect the thickness of monolayer dielectric materials in a non-destructive way.The proposed DGS resonator consists of a high impedance microstrip line,two coupled sharp-edged split square resonators(CS-SSRs),and an adaptive genetic algorithm(AGA)coded DGS structure.The coding for the DGS structure is implemented by using the programming software-CST interface.The multi-dimensional variables-based code is developed to design a novel structure for thickness detection.The developed code self-optimized the structure after analyzing the electromagnetic(EM)simulation automation program.This anticipated research review several common algorithms and explore the potential situation after that the SIOA is applied to construct microwave device design.Finally,an improved AGA has been chosen and considered as the optimization algorithm.The AGA takes the Q-factor as the optimization fitness function and uses the coding structure as the independent variable so that the innovative structural design and performance optimization is achieved to design microwave sensor.Based on the above analysis,the main work of this research is shown as follows:(1)Set the expected indicators of the sensor(sensing material,thickness range,normalized sensitivity,Q-factor,amplitude of S₂₁ center frequency).(2)SRR-based microwave design,simulation,and optimization.(3)The origin,principle,application comparison,and code designing to implement particle swarm optimization algorithm,genetic algorithm,and adaptive genetic algorithm for performing electromagnetic simulations.(4)Design MATLAB-CST interface for EM automation.(5)Apply SIOA(AGA)for iterative optimization and adjustment of coding of DGS resonator.(6)Verify and test the optimized structure after simulation at the physical level.