Supervised Image Processing Learning for Wall MARFE Detection Prior to Disruption in JET With a Carbon Wall

Murari, A.; Tiseanu, Ion; Vega, J.

doi:10.1109/tps.2014.2331705

Cited by 2 publications

(3 citation statements)

References 62 publications

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“…A representative result is illustrated in figure 7. The complete details of the implementation are reported in [51].…”

Section: Image Processing For Plasma Physical Events Detectionmentioning

confidence: 99%

“…Possible solutions for this problem are the integration of a cascade-of-rejecters and the use of AdaBoost to train the chain of rejection rules [54], or the parallel implementation using the GPGPU (General Purpose computation on Graphics Processing Units) technology [55,56]. The last approach has been recently applied for MARFE automatic identification [51]. The implementation uses a ROI which encompasses the area where most of the MARFEs in the JET database leave a signature, in order to diminish the computation time for gradient evaluation.…”

Section: Image Processing For Plasma Physical Events Detectionmentioning

confidence: 99%

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Overview of image processing tools to extract physical information from JET videos

Murari

Gelfusa

Tiseanu³

et al. 2014

Plasma Phys. Control. Fusion

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In magnetic confinement nuclear fusion devices such as JET, the last few years have witnessed a significant increase in the use of digital imagery, not only for the surveying and control of experiments, but also for the physical interpretation of results. More than 25 cameras are routinely used for imaging on JET in the infrared (IR) and visible spectral regions. These cameras can produce up to tens of Gbytes per shot and their information content can be very different, depending on the experimental conditions. However, the relevant information about the underlying physical processes is generally of much reduced dimensionality compared to the recorded data. The extraction of this information, which allows full exploitation of these diagnostics, is a challenging task. The image analysis consists, in most cases, of inverse problems which are typically ill-posed mathematically. The typology of objects to be analysed is very wide, and usually the images are affected by noise, low levels of contrast, low grey-level in-depth resolution, reshaping of moving objects, etc. Moreover, the plasma events have time constants of ms or tens of ms, which imposes tough conditions for real-time applications. On JET, in the last few years new tools and methods have been developed for physical information retrieval. The methodology of optical flow has allowed, under certain assumptions, the derivation of information about the dynamics of video objects associated with different physical phenomena, such as instabilities, pellets and filaments. The approach has been extended in order to approximate the optical flow within the MPEG compressed domain, allowing the manipulation of the large JET video databases and, in specific cases, even real-time data processing. The fast visible camera may provide new information that is potentially useful for disruption prediction. A set of methods, based on the extraction of structural information from the visual scene, have been developed for the automatic detection of MARFE (multifaceted asymmetric radiation from the edge) occurrences, which precede disruptions in density limit discharges. An original spot detection method has been developed for large surveys of videos in JET, and for the assessment of the long term trends in their evolution. The analysis of JET IR videos, recorded during JET operation with the ITER-like wall, allows the retrieval of data and hence correlation of the evolution of spots properties with macroscopic events, in particular series of intentional disruptions.

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“…A representative result is illustrated in figure 7. The complete details of the implementation are reported in [51].…”

Section: Image Processing For Plasma Physical Events Detectionmentioning

confidence: 99%

Section: Image Processing For Plasma Physical Events Detectionmentioning

confidence: 99%

Overview of image processing tools to extract physical information from JET videos

Murari

Gelfusa

Tiseanu³

et al. 2014

Plasma Phys. Control. Fusion

View full text Add to dashboard Cite

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“…The MARFE phenomenon has already been observed in many devices [10][11][12][13][14][15][16][17][18][19]. MARFE, which is characterized by low temperature, high electron density and strong radiation in a certain region [20], is commonly locate d on the high field side or near the X point.…”

Section: Introductionmentioning

confidence: 97%

Investigation of multifaceted asymmetric radiation from the edge (MARFE) with impurity injection from the upper divertor on the Experimental Advanced Superconducting Tokamak

Luo

Ding

Wang

et al. 2020

Plasma Phys. Control. Fusion

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The phenomenon of multifaceted asymmetric radiation from the edge (MARFE) is investigated with impurity gas puff from the upper divertor on the Experimental Advanced Superconducting Tokamak (EAST). A typical process in which dense radiation region in the vicinity of the X point (X-point MARFE) further evolves into MARFE on the high field side (wall MARFE) after the plasma ma kes a transition from H-mode to L-mode confinement is observed in discharges with the impurity gas seeding. The electron density distribution and evolution in the divertor volume are measured by means of spectroscopy. It is observed in the experiments that the final position of MARFE is related to the ion ∇B drift direction. After the phase difference of n = 1 resonant magnetic perturbation (RMP) change from 90 • to 270 • , MARFE begins to appear on the high field side, which may be caused by the density pump-out induced by RMP. At the same heating power, the density threshold for MARFE formation is somewhat higher in the Ne seeding discharge than in the Ar seeding discharge. This may be attributed to the fact that the divertor radiation fraction, P rad,div /P rad,main , in the Ne seeding discharge is lower than that in the Ar seeding discharge. In addition, MARFE is successfully suppressed by total radiated energy feedback control in radiative divertor experiments. Therefore, radiation feedback control may play a vital role in avoiding major disruption induced by impurity radiation in radiative divertor experiments.

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Supervised Image Processing Learning for Wall MARFE Detection Prior to Disruption in JET With a Carbon Wall

Cited by 2 publications

References 62 publications

Overview of image processing tools to extract physical information from JET videos

Overview of image processing tools to extract physical information from JET videos

Investigation of multifaceted asymmetric radiation from the edge (MARFE) with impurity injection from the upper divertor on the Experimental Advanced Superconducting Tokamak

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