Abstract
In the present study, the machine learning algorithm is utilized for the first time to improve the probe diagnosis. Machine learning methods are utilized to improve the Langmuir probe diagnostic accuracy and the diagnosable plasma parameter range without changing the probe structure based on the Langmuir probe. They provide a new way for experimentally obtaining electron density. A DC glow discharge simulation model and experimental equipment are established. Utilizing the discharge pressure and voltage as independent variables, the simulation and experimental electron densities are collected, the simulation and experimental data are utilized for training, and the plasma electron density outside of the pressure and voltage range of the training data is predicted, thereby achieving the prediction. Simultaneously, when the data amount is large enough, even without experimental measurement, the electron density can be obtained directly through the input parameters, without relying on the plasma physical model.
Highlights
Electron density is one of the important parameters of plasma
The probe is a method of measuring by applying a voltage inside of the plasma,4,5 and the positive column area of the DC glow discharge plasma will be affected by the probe
This paper mainly studies the parameters of DC glow discharge
Summary
Electron density is one of the important parameters of plasma. The existing methods for diagnosing electron density mainly include microwave diagnosis, spectroscopic diagnosis, and Langmuir probe diagnosis. Among them, the Langmuir probe diagnosis method is the most important and most widely used diagnosis method. The probe is a method of measuring by applying a voltage inside of the plasma, and the positive column area of the DC glow discharge plasma will be affected by the probe. From Vladimir’s work, it can be found that as the plasma discharge voltage and pressure increase, the impact will become more severe It will seriously limit the parameter range that the probe can diagnose.. For the probe system that can only diagnose plasma with limited discharge parameters, the traditional data analysis method first needs to obtain the fitting function and the parameters in the fitting function.. For the probe system that can only diagnose plasma with limited discharge parameters, the traditional data analysis method first needs to obtain the fitting function and the parameters in the fitting function.14 In the past, this process could only choose through experience and manual selection.. V, the machine learning method of probe diagnosis is summarized
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