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Analysis of Langmuir probe data using wavelet transform

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3 Author(s)
Bong-Kyoung Park ; Samsung SDI, Chunan, South Korea ; Dai-Gyoung Kim ; Gon-Ho Kim

A new algorithm to analyze Langmuir probe (LP) data has been developed with Daubechies (DWT) and bi-orthogonal wavelet transforms (BWT), which remove the noise from the raw data without losing important information. The first derivative of the LP signal is processed using BWT and its result readily provides the peak value, which corresponds to the plasma potential. The LP data processed using DWT provides the saturation current lines directly, which corresponds to the electron and ion saturation currents. The region required to obtain the electron temperature can be automatically determined from the plasma potential to the end of the ion saturation current line so that the input from the analyzer is not required to continue the analysis. The plasma density can be obtained from the electron saturation current and the electron temperature. Accuracy tests of the algorithm are carried out with simulation probe data containing various levels of random noise. The results show that the algorithm based on the wavelet transforms removes noise effectively and that the plasma parameters are obtained accurately.

Published in:

IEEE Transactions on Plasma Science  (Volume:32 ,  Issue: 2 )