Real-time data acquisition and processing platform for fusion experiments

Ruiz, M.; Barrera, E.; López, Secundino; Machón, D.; Vega, J.; Sánchez, E.

doi:10.1016/j.fusengdes.2004.04.024

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…These save on computational resources in the main controller while also providing extra calculation power (even for real-time requirements). In addition, 4GL user programs can be downloaded on-line to a multiprocessor data acquisition system [16,17]. After developing a simulation platform [18], a multiprocessor system was implemented [19], showing that it is possible to increase the processing capabilities of a PXI standard system by adding one or more commercial processing cards and developing the specific software modules that allow the communication between the processing cards and the rest of the system.…”

Section: Multiprocessor Data Acquisition Systemsmentioning

confidence: 99%

Present status of the TJ-II remote participation system

Vega

Sánchez

López

et al. 2005

Fusion Engineering and Design

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Section: Multiprocessor Data Acquisition Systemsmentioning

confidence: 99%

Present status of the TJ-II remote participation system

Vega

Sánchez

López

et al. 2005

Fusion Engineering and Design

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“…These tasks run in the PXI controller as well as in the processing cards. They have been developed under RTAI and use API functions from COMEDI project [1][2] [3]. The performance test of this architecture shows that the enhancement of the processing capability is approximately 115% of the controller's processing capability for each processing card that is added to the system [4].…”

Section: A System Architecturementioning

confidence: 99%

PXI-based architecture for real time data acquisition and distributed dynamical data processing

Barrera¹,

Ruiz²,

López³

et al. 2005

14th IEEE-NPSS Real Time Conference, 2005.

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This paper describes an architecture model for data acquisition systems based on Compact PCI platforms. The aim is to increase real time data processing capabilities in experimental environments such as nuclear fusion devices (e.g. ITER). The model has these features: a) Real Time Data Acquisition: the system has been provided with real time capabilities, developing specific data acquisition kernel modules under Linux and RTAI, using COMEDI project drivers; b) Multiprocessor PXI (PCI eXtensión for Instrumentation) Architecture: the model makes possible to add one or more processing cards (in non-system slots) to each standard PXI chassis. Several real time software modules have been developed to allow the communication between the PXI controller and the processing cards. This way the system performance is not restricted to the PXI controller's own performance. This model provides scalability to the system, adding or removing processing cards; c) Real Time Acquired Data Distribution: with this model it is possible to define how to distribute, in real time, the data from all acquired signals in the system among the processing cards and the PXI controller; and d) Dynamical Data Processing: a software platform has been developed to allow users managing dynamically their own data processing algorithms in the system. This means that users can start, stop, modify, and replace their data processing algorithms without disrupting neither the data acquisition process nor the rest of the data processing algorithms.

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“…The goal of this integration is to guarantee that a user's application, as it has been defined in previous sections, can be run on the real data acquisition system [4] (in this case, on the data acquisition system in the TJ-II device located at the Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT) of Madrid), without any modifications on its code. This involves the development of a resident application in the final data acquisition system that integrates, manages and synchronizes all the user's applications.…”

Section: Integration In the Final Systemmentioning

confidence: 99%