Operational data for fault prognosis in particle accelerators with machine learning.

This paper presents real operational data collected from the power systems of the Spallation Neutron Source facility, which provides the most intense neutron beam in the world. The authors have used a radio-frequency test facility (RFTF) and simulated system failures in the lab without causing a catastrophic system failure. Waveform signals have been collected from the RFTF normal operation as well as during fault induction efforts.