Author: Chalmers, M.C.
Paper Title Page
WESPLS3
 Public Awareness Activity  
 
  • M.C. Chalmers, R.T. Dowd
    AS - ANSTO, Clayton, Australia
  
  Instructions on how to participate in the Wiki Edit-a-thon activity.  
slides icon Slides WESPLS3 [0.738 MB]  
Export • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)  
 
THPRB003 Automatic Classification of Post Mortem Data for Reduced Beam Down Time 3799
 
  • M.C. Chalmers, Y.E. Tan
    AS - ANSTO, Clayton, Australia
  
  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.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-THPRB003  
About • paper received ※ 15 May 2019       paper accepted ※ 21 May 2019       issue date ※ 21 June 2019  
Export • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)