Electromagnetic Burst Measurement System Based on Low Cost UHF Dipole Antenna

Escalona, Ismael; Avaria, Gonzalo; Díaz, M.; Ardila-Rey, Jorge Alfredo; Moreno, José; Pavez, Cristian; Soto, Leopoldo

doi:10.3390/en10091415

Cited by 7 publications

(8 citation statements)

References 34 publications

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“…That is to say, the antenna radiation pattern must be oriented towards the source of the transient so that the electric and magnetic fields that are being captured generate the highest possible voltage at the terminals of the antenna and, consequently, receive a higher energy value [46], [47]. Due to the pulsing behavior of DPFs, some spectral components of the transients, generated during their operation, can appear in frequency bands where there are permanently-present spectral contents associated with electromagnetic noise: FM radio, digital TV, Digital Audio Broadcasting (DAB), Global System for Mobile communications (GSM) and Wi-Fi [29], [48]. For this reason, the antenna must be adjusted or calibrated so that it can measure the bands where this noise is not present, and thus, the information captured would correspond as much as possible to the pulse that is being measured.…”

Section: B Vivaldi Antennamentioning

confidence: 99%

“…In parallel to the high energy radiation generated by these devices, emission in the Ultra High Frequency (UHF) range has also been detected and associated to induced damage in electronic circuits through coupling of the high frequency electric field with instrument cables [29]. In order to characterize these electromagnetic transients, antennas with high efficiency and directivity are paramount due to their excellent performance.…”

Section: Introductionmentioning

confidence: 99%

“…Horn antennas with a highly directional radiation pattern and tuned for the microwave range of frequencies, in combination with waveguides and microwave crystal detectors, were used as a time of flight spectrometer for the radiation emitted on the outside from a DPF [34]. A dipole antenna, which has an omni-directional radiation pattern and is tuned for a particular frequency, was used on the outside of the vacuum chamber in order to measure the electromagnetic burst from a DPF device [29]. Except for the papers of Gerdin et al [34] and Schmidt et al [33], no further relationship of the EM radiation with plasma focus phenomena has been reported.…”

Section: Introductionmentioning

confidence: 99%

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Hard X-Ray Emission Detection Using Deep Learning Analysis of the Radiated UHF Electromagnetic Signal From a Plasma Focus Discharge

et al. 2019

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A method to determine the presence of hard X-ray emission processes from a dense plasma focus (205 J, 22 kV, 6.5 mbar H 2) using Ultra High Frequency (UHF) measurements and deep learning techniques is presented. Simultaneously, the electromagnetic UHF radiation emitted from the plasma focus was measured with a Vivaldi UHF antenna, while the hard X-ray emission was measured with a scintillator-photomultiplier system. A classification algorithm based on deep learning methods, using two-dimensional convolutional layers, was implemented to predict the hard X-ray signal standard deviation value using only the antenna signal measurement. Two independent datasets, consisting of 999 and 1761 data pairs each, were used in the analysis. Different realizations of the training/validation process using a deep learning model, obtained overall better results in comparison to other machine learning methods like kneighbors, decision trees, gradient boost, and random forest. The results of the deep learning algorithm, and even its comparison with other machine learning methods, indicate that a relationship between the electromagnetic UHF radiation and hard X-ray emission can be established, enabling the indirect detection of hard X-ray pulses only using the UHF antenna signal. This indirect detection presents the opportunity to have a simple and low-cost diagnostic, compared to the methods currently used to characterize the pulses of X-rays emitted from plasma focus discharges. INDEX TERMS Deep learning, Plasma focus, UHF antenna, X-ray pulse.

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Section: B Vivaldi Antennamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hard X-Ray Emission Detection Using Deep Learning Analysis of the Radiated UHF Electromagnetic Signal From a Plasma Focus Discharge

et al. 2019

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“…In an effort to complement the information obtained with electrical signals, the use of antennas have been tested to remotely diagnose the device in terms of the electromagnetic (EM) burst emitted in the radiofrequency part of the spectrum. EM burst diagnostic has been used either inside or outside the chamber [29]- [32]. Recently, the EM burst measurement has been correlated with the inductive measurement [33] and with the X rays detection using a scintillator-photomultiplier (PMT) system [34].…”

Section: Introductionmentioning

confidence: 99%

Inference of X-Ray Emission From a Plasma Focus Discharge: Comparison Between Characteristic Parameters and Neural Network Analyses

et al. 2020

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Pulsed plasma discharges, such as the plasma focus, are a source of pulsed X rays, therefore it is desirable to understand the relationship between this fast transient phenomena and the electrical variables of the discharge. Parameters from the electrical diagnostic signals are typically used to characterize the plasma focus discharge and for the correlations with X rays measurements via scatter plots. To further evaluate relevant information in the electrical signals, besides the characteristic parameters, an implementation of different types of machine learning algorithms, that included deep learning, was performed. A classification of pulses associated with an X rays measurement, in terms of the electrical signals data as input, was carried out. Two approaches were compared: the selection of the characteristic parameters and the use of the entire signals so the algorithms could find additional information for the classification task. The electrical diagnostic signals corresponded to: the voltage at the electrodes of the discharge chamber measured with a resistive voltage divider; time variation of the circuit current measured with a Rogowski coil and an inductive loop sensor; and the electromagnetic burst from the circuit measured with a Vivaldi antenna. The X rays measurement corresponded to the signal obtained from a scintillator-photomultiplier. In terms of the performance of the algorithms models in this classification problem, the results indicated that there is no significative improvements when using the entire signal or the selection of characteristic parameters. The best results were obtained when the following parameters were used: voltage at time of gas breakdown, voltage at time of pinch, current at time of pinch, time derivative of current at time of pinch, time from breakdown to pinch, and the Fast Fourier Transform of the part of the Vivaldi antenna signal related to the pinch event.

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“…Previously, radiofrequency and microwave measurements from a DPF had been considered as a feasible diagnostic [31]- [33] either on the inside or outside the vacuum chamber. Additionally, a dipole antenna was used by Escalona et al [34] for measuring the electromagnetic noise created by the DPF and how to mitigate its effect in electronic equipment. Recently, a particular antenna design, the Vivaldi, has been used in conjunction with machine learning algorithms to infer the hard X ray measurement from DPF [35].…”

Section: Introductionmentioning

confidence: 99%

On the Relationship Between the Electromagnetic Burst and Inductive Sensor Measurement of a Pulsed Plasma Accelerator

et al. 2019

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A remote and non-invasive diagnostic of the plasma focus using antennas is presented in this work. The main motivation is the application of such diagnostic in a miniaturized plasma accelerator, based on the plasma focus architecture, as a cube satellite thruster. The evaluation of this proposal was carried out measuring a hundred of joules plasma focus operation simultaneously with the inductive measurement and antennas. Three different antennas tuned in the ultra high frequency range were tested: a monopole, Vivaldi and helical. The high frequency transients detected with the antennas were time correlated to the known inductive measurement features. The initial dielectric breakdown and later plasma pinch and subsequent disruption (i.e. the source of the propulsion) were identified to be the principal phenomena to be detected. Signal parameter correlations between the inductive sensor and the antennas showed that the pinch phenomena can be correlated with the antenna signals. Good correlation results were obtained with the monopole antenna when using peak value and signal energy parameter from the antenna transient. An improvement in the correlation results, for the helical and Vivaldi antennas, was obtained when calculating the frequency band energy. In this case, the Vivaldi antenna achieved the best results. The results of the monopole antenna make it an alternative remote sensor for plasma focus, but for the application of a miniaturized plasma focus as pulsed plasma thruster, the Vivaldi antenna is a more feasible design to replace the inductive diagnostic due to its compact design in comparison to the monopole. INDEX TERMS Inductive sensor, pulsed plasma thruster, plasma focus, ultra high frequency antennas.

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Electromagnetic Burst Measurement System Based on Low Cost UHF Dipole Antenna

Cited by 7 publications

References 34 publications

Hard X-Ray Emission Detection Using Deep Learning Analysis of the Radiated UHF Electromagnetic Signal From a Plasma Focus Discharge

Hard X-Ray Emission Detection Using Deep Learning Analysis of the Radiated UHF Electromagnetic Signal From a Plasma Focus Discharge

Inference of X-Ray Emission From a Plasma Focus Discharge: Comparison Between Characteristic Parameters and Neural Network Analyses

On the Relationship Between the Electromagnetic Burst and Inductive Sensor Measurement of a Pulsed Plasma Accelerator

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