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https://doi.org/10.18429/JACoW-ICALEPCS2017-THPHA032
Title EPICS and Open Source Data Analytics Platforms
Authors
  • C.R. Haskins
    CASS, Epping, Australia
Abstract SKA scale distributed control and monitoring systems present challenges in hardware sensor monitoring, archiving, hardware fault detection and fault prediction. The size and scale of hardware involved and telescope high availability requirements suggest the machine learning and other automated methods will be required for fault finding and fault prediction of hardware components. Modern tools are needed leveraging open source time series database & data analytic platforms. We describe DiaMoniCA for The Australian SKA Pathfinder Radio Telescope which integrates EPICS, our own monitoring archiver MoniCA, with an open source time series database and web based data visualisation and analytic platform.
Paper download THPHA032.PDF [1.704 MB / 3 pages]
Poster download THPHA032_POSTER.PDF [7.517 MB]
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Conference ICALEPCS2017, Barcelona, Spain
Series International Conference on Accelerator and Large Experimental Control Systems (16th)
Proceedings Link to full ICALEPCS2017 Proccedings
Session Poster Session
Date 12-Oct-17   16:45–19:00
Main Classification Data Analytics
Keywords ion, EPICS, monitoring, database, controls
Publisher JACoW, Geneva, Switzerland
Editors Volker RW Schaa (GSI, Darmstadt, Germany); Isidre Costa (ALBA-CELLS, Cerdanyola del Vallès, Spain); David Fernández (ALBA-CELLS, Cerdanyola del Vallès, Spain); Óscar Matilla (ALBA-CELLS, Cerdanyola del Vallès, Spain)
ISBN 978-3-95450-193-9
Published January 2018
Copyright
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cc Creative Commons Attribution 3.0