Fast Data Acquisition Measurement System For Plasma Diagnostics Using Gem Detectors

Wojeński, Andrzej; Poźniak, Krzysztof T.; Kasprowicz, G.; Zabołotny, W.; Byszuk, A.; Zienkiewicz, P.; Chernyshova, M.; Czarski, Tomasz

doi:10.22323/1.240.0144

Cited by 3 publications

(2 citation statements)

References 10 publications

(13 reference statements)

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“…All of the settings including gain, offset correction and coupling mode needs to be tuned in order to achieve the highest dynamic range of the signal, matching the ADC input range. More details about the construction of the system can be also found in following publications [4,[6][7][8].…”

Section: System Componentsmentioning

confidence: 99%

FPGA-based GEM detector signal acquisition for SXR spectroscopy system

et al. 2016

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The presented work is related to the Gas Electron Multiplier (GEM) detector soft X-ray spectroscopy system for tokamak applications. The used GEM detector has one-dimensional, 128 channel readout structure. The channels are connected to the radiation-hard electronics with configurable analog stage and fast ADCs, supporting speeds of 125 MSPS for each channel. The digitalized data is sent directly to the FPGAs using fast serial links. The preprocessing algorithms are implemented in the FPGAs, with the data buffering made in the on-board 2Gb DDR3 memory chips. After the algorithmic stage, the data is sent to the Intel Xeon-based PC for further postprocessing using PCI-Express link Gen 2. For connection of multiple FPGAs, PCI-Express switch 8-to-1 was designed. The whole system can support up to 2048 analog channels. The scope of the work is an FPGA-based implementation of the recorder of the raw signal from GEM detector. Since the system will work in a very challenging environment (neutron radiation, intense electro-magnetic fields), the registered signals from the GEM detector can be corrupted. In the case of the very intense hot plasma radiation (e.g. laser generated plasma), the registered signals can overlap. Therefore, it is valuable to register the raw signals from the GEM detector with high number of events during soft X-ray radiation. The signal analysis will have the direct impact on the implementation of photon energy computation algorithms. As the result, the system will produce energy spectra and topological distribution of soft X-ray radiation. The advanced software was developed in order to perform complex system startup and monitoring of hardware units. Using the array of two onedimensional GEM detectors it will be possible to perform tomographic reconstruction of plasma impurities radiation in the SXR region.

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Section: System Componentsmentioning

confidence: 99%

FPGA-based GEM detector signal acquisition for SXR spectroscopy system

et al. 2016

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“…In the era of high-speed and high-resolution data acquisition, there is a need for novel yet simple and efficient computational algorithms. , A good example of such modernization is the last generation of analog-to-digital converters. , Affordable price, quality, and size ratio allows the integration of such models (including field programmable gate array-based converters) as the main data acquisition modules not only into the expensive commercial laboratory equipment but also into the portable analytical systems as well. This is important for rapid microseparation methods, where little to none of the peak in the chromatogram/electropherogram should be lost in the filter.…”

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confidence: 99%

Capillary Electrophoresis Sensitivity Enhancement Based on Adaptive Moving Average Method

et al. 2018

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In the present work, we demonstrate a novel approach to improve the sensitivity of the "out of lab" portable capillary electrophoretic measurements. Nowadays, many signal enhancement methods are (i) underused (nonoptimal), (ii) overused (distorts the data), or (iii) inapplicable in field-portable instrumentation because of a lack of computational power. The described innovative migration velocity-adaptive moving average method uses an optimal averaging window size and can be easily implemented with a microcontroller. The contactless conductivity detection was used as a model for the development of a signal processing method and the demonstration of its impact on the sensitivity. The frequency characteristics of the recorded electropherograms and peaks were clarified. Higher electrophoretic mobility analytes exhibit higher-frequency peaks, whereas lower electrophoretic mobility analytes exhibit lower-frequency peaks. On the basis of the obtained data, a migration velocity-adaptive moving average algorithm was created, adapted, and programmed into capillary electrophoresis data-processing software. Employing the developed algorithm, each data point is processed depending on a certain migration time of the analyte. Because of the implemented migration velocity-adaptive moving average method, the signal-to-noise ratio improved up to 11 times for sampling frequency of 4.6 Hz and up to 22 times for sampling frequency of 25 Hz. This paper could potentially be used as a methodological guideline for the development of new smoothing algorithms that require adaptive conditions in capillary electrophoresis and other separation methods.

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International Journal of Electronics and Telecommunications

Wojeński

Poźniak

Mazon

et al. 2018

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Based on the publications regarding new or recent measurement systems for the tokamak plasma experiments, it can be found that the monitoring and quality validation of input signals for the computation stage is done in different, often simple, ways. In the paper is described the unique approach to implement the novel evaluation and data quality monitoring (EDQM) model for use in various measurement systems. The adaptation of the model is made for the GEM-based soft X-ray measurement system FPGA-based. The EDQM elements has been connected to the base firmware using PCI-E DMA real-time data streaming with minimal modification. As additional storage, on-board DDR3 memory has been used. Description of implemented elements is provided, along with designed data processing tools and advanced simulation environment based on Questa software.

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Fast Data Acquisition Measurement System For Plasma Diagnostics Using Gem Detectors

Cited by 3 publications

References 10 publications

FPGA-based GEM detector signal acquisition for SXR spectroscopy system

FPGA-based GEM detector signal acquisition for SXR spectroscopy system

Capillary Electrophoresis Sensitivity Enhancement Based on Adaptive Moving Average Method

International Journal of Electronics and Telecommunications

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