| Paper |
Title |
Page |
| TUPIK109 |
Accelerators and Their Ghosts |
1975 |
| |
- M. Reščič, R. Seviour
University of Huddersfield, Huddersfield, United Kingdom
- W. Blokland
ORNL, Oak Ridge, Tennessee, USA
|
|
| |
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.
|
|
| DOI • |
reference for this paper
※ https://doi.org/10.18429/JACoW-IPAC2017-TUPIK109
|
|
| Export • |
reference for this paper using
※ BibTeX,
※ LaTeX,
※ Text/Word,
※ RIS,
※ EndNote (xml)
|
|
| |