A New Langmuir Probe Analysis Algorithm Based on Wavelet Transforms to Obtain the Electron Energy Distribution Function of a Bi-Maxwellian Plasma
2010.01.04 15:02
연도 | 2009 |
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저널명 | Journal of the Korean Physical Society |
쪽 |
A new algorithm to analyze the digitized Langmuir probe (LP) data is
developed with the wavelet transforms, providing the electron energy
distribution function (EEDF) for bi-Maxwellian plasmas. Because most of
algorithms to analyze the probe data have been developed with the Druyvesteyn
formula which is based on the second derivation of current with respect to probe
voltage, the accuracy of analysis is very sensitive to the noise level during
the derivation of probe data. Especially the amount of hot electrons in the
bi-Maxwellian plasma is small enough to compare the noise level and the noise
filtering method is a kernel in the development of the algorithm to analyze the
bi-Maxwellian EEDF. Here, the bi-orthogonal wavelet and continuous wavelet
transforms are chosen for the de-noising and the differentiation processes
respectively. It has an advantage to provide the filtered data with minimum loss
of important information. The artificial LP data sets composed of electrons were
generated with various bulk and hot temperatures and the developed algorithm was
evaluated for the various white noise levels. For the case that the noise levels
are 10 times of ion saturation current, the plasma parameters such as the
population of hot electrons and the temperatures of hot and bulk electron were
accurately analyzed within only a few percent deviations from the input values
for the generation of artificial probe data. As the demonstration of the
algorithm, the analysis of probe data was carried out for the DC glow and the
inductively coupled plasmas (ICP) with various input powers and operating
pressures, respectively. From the EEDF analyses of those plasmas, the variation
of hot electrons in the DC plasma and the Ramsauer effect of low pressure ICP
could be observed clearly.
10.3938/jkps.55.1825