| Title |
Accelerators and Their Ghosts |
| Authors |
- M. Reščič, R. Seviour
University of Huddersfield, Huddersfield, United Kingdom
- W. Blokland
ORNL, Oak Ridge, Tennessee, USA
|
| Abstract |
The issue of particle accelerator reliability is a problem that currently is not fully defined, understood nor addressed. Conventional approaches to reliability (e.g. RBDs) struggle due to a lack of data about specific component/system reliability and failure. There is a large body of beam current data retrievable from operating accelerators that contains detailed information about the accelerator behaviour, both before and after a machine trip has occurred. Analysing this data could provide insight and help develop a new approach to address accelerator reliability. In this paper, we propose a data-driven approach to detecting emergent behaviour in particle accelerators. Instead of attempting to identify every possible failure of a machine we propose an alternative approach based around a change in perspective, to knowing the normal default operational behaviour of a machine. Taking action when a ghost in the machine emerges that causes accelerator wide aberrant changes to normal machine behaviour.
|
| Paper |
download TUPIK109.PDF [0.866 MB / 4 pages] |
| Export |
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| Conference |
IPAC2017, Copenhagen, Denmark |
| Series |
International Particle Accelerator Conference (8th) |
| Proceedings |
Link to full IPAC2017 Proccedings |
| Session |
Posters Tuesday 2 |
| Date |
16-May-17 16:00–18:00 |
| Main Classification |
06 Beam Instrumentation, Controls, Feedback and Operational Aspects |
| Sub Classification |
T22 Reliability, Operability |
| Keywords |
database, operation, network, target, proton |
| Publisher |
JACoW, Geneva, Switzerland |
| Editors |
Volker RW Schaa (GSI, Darmstadt, Germany); Gianluigi Arduini (CERN, Geneva, Switzerland); Juliana Pranke (ESS, Lund, Sweden); Mike Seidel (PSI, Villigen, Switzerland); Mats Lindroos (ESS, Lund, Sweden) |
| ISBN |
978-3-95450-182-3 |
| Published |
May 2017 |
| Copyright |
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