Overview of intelligent data retrieval methods for waveforms and images in massive fusion databases

Vega, J.; Murari, A.; Pereira, A.; Portas, A.; Rattá, G.A.; Castro, R.

doi:10.1016/j.fusengdes.2008.11.097

Cited by 15 publications

(6 citation statements)

References 8 publications

(10 reference statements)

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“…The storage of meta data as time stamp, event annotations and contextual information is then considered as an indispensable feature allowing quick image retrieval and event mining. To this end, content-based video indexing tools as proposed by Vega et al in [23] must be developed and integrated into the data management system.…”

Section: B Challenges and Needs For Next Step Devicesmentioning

confidence: 99%

Challenges of Video Monitoring for Phenomenological Diagnostics in Present and Future Tokamaks

Martin

Moncada

Travère

2012

IEEE Trans. Plasma Sci.

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With the development of heterogeneous camera networks working at different wavelengths and frame rates and covering a large surface of vacuum vessel, the visual observation of a large variety of plasma and thermal phenomena (e.g., hot spots, ELMs, MARFE, arcs, dusts, etc.) becomes possible. In the domain of machine protection, a phenomenological diagnostic is a key-element towards plasma/thermal event dangerousness assessment during real time operation. It is also of primary importance to automate the extraction and the storage of phenomena information for further off-line event retrieval and analysis, thus leading to a better use of massive image data bases for plasma physics studies. To this end, efforts have been devoted to the development of image processing algorithms dedicated to the recognition of specific events. But a need arises now for the integration of techniques developed so far in both hardware and software directions. We present in this paper our latests results in the field of real time phenomena recognition and management through our image understanding software platform. This platform has been validated on Tore Supra during operation and is under evaluation for the foreseen imaging diagnostic of ITER.

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Section: B Challenges and Needs For Next Step Devicesmentioning

confidence: 99%

Challenges of Video Monitoring for Phenomenological Diagnostics in Present and Future Tokamaks

Martin

Moncada

Travère

2012

IEEE Trans. Plasma Sci.

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“…A package of tools has been developed for the intelligent and automatic handling of the continuously growing database. Content-based image retrieval methods [9,10] have been developed based on data screening of the morphological aspects of images. Assuming that diagnostics generate reproducible patterns for similar physical behaviours, these tools ensure an efficient high level data access to the huge JET image database.…”

Section: Introductionmentioning

confidence: 99%

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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“…In order to standardize the use of these methods and putting together other intelligent data retrieval techniques [5], a deploy- allow the engine to connect over TCP/IP increasing the scope of the distributed data by providing traditional Java database network connections (JDBC). This integration allows hiding of unnecessary details about the installation, distribution, and configuration of other software components but with the flexibility to create and allocate many distributed databases on different servers.…”

Section: Introductionmentioning

confidence: 99%

Distributed open environment for data retrieval based on pattern recognition techniques

Pereira

Vega

Castro

et al. 2010

Fusion Engineering and Design

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Overview of intelligent data retrieval methods for waveforms and images in massive fusion databases

Cited by 15 publications

References 8 publications

Challenges of Video Monitoring for Phenomenological Diagnostics in Present and Future Tokamaks

Challenges of Video Monitoring for Phenomenological Diagnostics in Present and Future Tokamaks

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

Distributed open environment for data retrieval based on pattern recognition techniques

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