Microwave Diagnosis Technology Of Plasma Parameters

With the wide application of plasma in various fields,there is an urgent need for fast and efficient diagnostic technology of plasma characteristic parameters.Compared with the traditional contact diagnostic technology,the non-contact microwave diagnostic technology not only does not produce physical interference to the target plasma,but also has the advantages of strong adaptability and low requirement to the wave source,which makes it increasingly become an important direction of the rapid development of plasma characteristic parameter diagnostic technology.Therefore,in this paper,the plasma microwave diagnostic technology is studied as follows:Firstly,on the basis of understanding the basic parameters of plasma,the media characteristics are studied,the basic formulas of conductivity and relative dielectric constant are deduced,and the effects of plasma parameters on the real and imaginary parts of relative dielectric constant are analyzed.Secondly,the microwave transmission method based on classical electromagnetic theory is studied.The scattering matrix(SMM)method is used to obtain the transmission attenuation values of electromagnetic waves with different frequencies passing through the plasma,and then the electron density and collision frequency of the plasma are inverted according to the corresponding attenuation values at two adjacent frequencies.Finally,the microwave reflection method combined with neural network is studied.The complex non-linear relationship between plasma parameters and antenna parameters is approached by using the neural network method,which can directly output the electron density and collision frequency of the target plasma.By diagnosing the plasma with different parameters,it is found that compared with the microwave transmission method based on classical electromagnetic theory,the average relative error of electron density and collision frequency is reduced by 0.5425 and 0.1972 respectively.The results show that the combination of neural network technology and traditional microwave diagnosis technology provides a more powerful theoretical tool for rapid and efficient diagnosis of plasma parameters.