scholarly journals Low frequency azimuthal stability of the ionization region of the Hall thruster discharge. I. Local analysis

2014 ◽  
Vol 21 (4) ◽  
pp. 043505 ◽  
Author(s):  
D. Escobar ◽  
E. Ahedo
Keyword(s):  
Low Frequency ◽  
Hall Thruster ◽  
Local Analysis ◽  
Ionization Region

Low-frequency-oscillation characteristics of ionization distribution in Hall thruster channels

Vacuum ◽  
2021 ◽  
pp. 110320
Author(s):  
Tianyuan Ji ◽  
Liqiu Wei ◽  
Haifeng Lu ◽  
Shangmin Wang ◽  
Ning Guo ◽  
...  
Keyword(s):  
Low Frequency ◽  
Hall Thruster ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Oscillation Characteristics

scholarly journals Numerical and Experimental Investigation of Longitudinal Oscillations in Hall Thrusters

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 148
Author(s):  
Vittorio Giannetti ◽  
Manuel Martín Saravia ◽  
Luca Leporini ◽  
Simone Camarri ◽  
Tommaso Andreussi
Keyword(s):  
Discharge Current ◽  
Fluid Model ◽  
Low Frequency ◽  
Hall Thruster ◽  
Hall Thrusters ◽  
Current Signal ◽  
Plasma Parameters ◽  
Plasma Properties ◽  
Breathing Mode ◽  
Spatio Temporal

One of the main oscillatory modes found ubiquitously in Hall thrusters is the so-called breathing mode. This is recognized as a relatively low-frequency (10–30 kHz), longitudinal oscillation of the discharge current and plasma parameters. In this paper, we present a synergic experimental and numerical investigation of the breathing mode in a 5 kW-class Hall thruster. To this aim, we propose the use of an informed 1D fully-fluid model to provide augmented data with respect to available experimental measurements. The experimental data consists of two datasets, i.e., the discharge current signal and the local near-plume plasma properties measured at high-frequency with a fast-diving triple Langmuir probe. The model is calibrated on the discharge current signal and its accuracy is assessed by comparing predictions against the available measurements of the near-plume plasma properties. It is shown that the model can be calibrated using the discharge current signal, which is easy to measure, and that, once calibrated, it can predict with reasonable accuracy the spatio-temporal distributions of the plasma properties, which would be difficult to measure or estimate otherwise. Finally, we describe how the augmented data obtained through the combination of experiments and calibrated model can provide insight into the breathing mode oscillations and the evolution of plasma properties.

Research of Wavelet Packet Analysis in the De-Noising of Ultrasonic Echo Signal

2011 ◽  
Vol 403-408 ◽  
pp. 1817-1822
Author(s):  
Xi Feng Zhou ◽  
Xiao Wu ◽  
Qian Gang Guo
Keyword(s):  
Signal To Noise Ratio ◽  
Wavelet Packet ◽  
Random Noise ◽  
Flaw Detection ◽  
Low Frequency ◽  
Local Analysis ◽  
Echo Signal ◽  
Wavelet Packet Analysis ◽  
Ultrasonic Flaw

The quality of ultrasonic flaw echo signal is the foundation of achieving qualitative and quantitative analysis in the in ultrasonic flaw detection. In practice, the flaw echo signals are often contaminated or even annihilation by random noise. According to the characteristics of ultrasonic flaw echo signal, wavelet packet has more accurate local analysis ability in low frequency and high frequency part. This paper discusses de-noising in ultrasonic signals based on wavelet packet analysis, and proposes an improved threshold approach for de-noising. The results show that: It remarkably raises the signal-to-noise ratio of ultrasonic flaw echo signal and improves the quality of signal with improved wavelet packet threshold.

High-Frequency Instabilities and Low-Frequency Dynamics in Hall Thruster Plasma

2004 ◽  
Author(s):  
Alexey Lazurenko ◽  
Vanessa Vial ◽  
Luc Albarede ◽  
Michel Dudeck ◽  
Andre Bouchoule
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Hall Thruster

scholarly journals Plasma Properties of Low Frequency Oscillation Phenomena in a Hall Thruster.

2000 ◽  
Vol 48 (561) ◽  
pp. 336-342 ◽  
Author(s):  
Takeshi FURUKAWA ◽  
Yasuyuki SAKURAI ◽  
Takeshi MIYASAKA ◽  
Toshi FUJIWARA
Keyword(s):  
Low Frequency ◽  
Hall Thruster ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Plasma Properties

Deformation Monitoring Data De-Noising Processing Based on Wavelet Packet

2012 ◽  
Vol 166-169 ◽  
pp. 1180-1186 ◽  
Author(s):  
Yan Mei Yang ◽  
Ze Gen Wang ◽  
Yu Yun Gao ◽  
Fa Peng Gao
Keyword(s):  
Wavelet Packet ◽  
Low Frequency ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Local Analysis ◽  
Landslide Monitoring ◽  
Minimum Entropy ◽  
Mathematical Methods ◽  
Lower Amplitude ◽  
Unbiased Risk

Wavelet packet coefficients carrying real signals have large amplitude but are in minority, while those carrying noise has lower amplitude but is of large number. In this case, the Basic principle of de-noising wavelet packet is to process signals carrying noise. A suitable threshold is chosen in different decomposition level. Wavelet packet coefficient of less than this threshold is set to equal zero, while wavelet packet coefficients of greater than this threshold is reserved and reconstructed into de-noising signals. MSE, SNR, PSNR are regarded as the standards of de-noising evaluation, some mathematical methods such as Shannon entropy, norm entropy, logarithm energy entropy, threshold entropy, Stein Unbiased Risk Estimate entropy are adopted to measure whether the wavelet packet basis is optimal , minimum Entropy function D value is the best base. Selecting threshold and threshold quantitative is the key to wavelet packet de-noising. And selection of threshold value abides standards such as Sqtwolog, Rigrsure, Heursure, Manimaxi, or Birge-massart. Wavelet packet de-noising method has been applied to tunnel vault sink and landslide monitoring data de-noising processing, which manifests itself being a more elaborate, flexible method compared to wavelet de-noising, since wavelet packet de-noising can even subdivided the low-frequency part and the high-frequency part of upper layer, thus entertains a more precise local analysis capabilities.

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