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RIS citation export for THPRB003: Automatic Classification of Post Mortem Data for Reduced Beam Down Time

AU  - Chalmers, M.C.
AU  - Tan, Y.E.
ED  - Boland, Mark
ED  - Tanaka, Hitoshi
ED  - Button, David
ED  - Dowd, Rohan
ED  - Schaa, Volker RW
ED  - Tan, Eugene
TI  - Automatic Classification of Post Mortem Data for Reduced Beam Down Time
J2  - Proc. of IPAC2019, Melbourne, Australia, 19-24 May 2019
CY  - Melbourne, Australia
T2  - International Particle Accelerator Conference
T3  - 10
LA  - english
AB  - Time spent recovering from faults that result in a rapid loss of stored current (a total beam loss event) can be costly to the Australian Synchrotron facility and its researchers. The identification of a fault leading to total beam loss is assisted by a large variety of investigative tools for specific tasks, but they do not often give a thorough overview of all systems required to store beam. Post mortem data uniquely provides insight into how the beam was behaving at the specific time the dump occurred. With machine learning, we find that we can automatically and rapidly identify many types of total beam loss events by learning about the unique characteristics in the post mortem files.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 3799
EP  - 3801
KW  - synchrotron
KW  - power-supply
KW  - real-time
KW  - operation
KW  - dipole
DA  - 2019/06
PY  - 2019
SN  - 978-3-95450-208-0
DO  - DOI: 10.18429/JACoW-IPAC2019-THPRB003
UR  - http://jacow.org/ipac2019/papers/thprb003.pdf
ER  -