Accelerators and their ghosts

Miha Rescic, Rebecca Seviour, W. Blokland

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.
Original languageEnglish
Title of host publicationProceedings of the 8th International Particle Accelerator Conference (IPAC '17)
PublisherJoint Accelerator Conferences Website (JACoW)
Number of pages4
ISBN (Print)9783954501823
Publication statusPublished - 14 May 2017
Event8th International Particle Accelerator Conference - Copenhagen, Denmark
Duration: 14 May 201719 May 2017
Conference number: 8 (Link to Conference Website )


Conference8th International Particle Accelerator Conference
Abbreviated titleIPAC'17
Internet address


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