Langmuir probe plasma measurements reduction using a feed-forward neural network: Preliminary results

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Scientific paper

Several environmental plasma parameters, e.g., plasma density and temperature can be derived from Langmuir probe measurements through the analysis of the current-potential characteristics. A neural network has been trained such as to fit the function mapping the space of the current-potential characteristics of a Langmuir probe to the space of the physical plasma parameters (density, temperature, electrostatic potential). The advantage of this technique is that it provides a method of analysis much faster than the systematic comparison with pre-tabulated characteristics and more accurate than a linear curve fitting of the inverse function. Furthermore, the inverse function appears reasonably stable with respect to noise. This opens up the possibility of automatic (on board) Langmuir probe plasma measurements reduction. Preliminary results of this method applied to the plasma tank measurements are shown.

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