• DocumentCode
    1480249
  • Title

    Statistical diagnosis method of conductor motions in superconducting magnets to predict their quench performance

  • Author

    Pugnat, P. ; Khomenko, B. ; Rijllart, A. ; Sanfilippo, S. ; Siemko, A.

  • Author_Institution
    Eur. Lab. for Nucl. Res., CERN, Geneva, Switzerland
  • Volume
    11
  • Issue
    1
  • fYear
    2001
  • fDate
    3/1/2001 12:00:00 AM
  • Firstpage
    1705
  • Lastpage
    1708
  • Abstract
    Premature training quenches are usually caused by the transient energy released within the magnet coil as it is energised. Two distinct varieties of disturbances exist. They are thought to be electrical and mechanical in origin. The first type of disturbance comes from nonuniform current distribution in superconducting cables whereas the second one usually originates from conductor motions or micro-fractures of insulating materials under the action of Lorentz forces. All of these mechanical events produce in general a rapid variation of the voltages in the so-called quench antennas and across the magnet coil, called spikes. A statistical method to treat the spatial localisation and the time occurrence of spikes is presented. It allows identification of the mechanical weak points in the magnet without need to increase the current to provoke a quench. The prediction of the quench level from detailed analysis of the spike statistics can be expected
  • Keywords
    current distribution; statistical analysis; superconducting cables; superconducting coils; superconducting magnets; Lorentz forces; conductor motions; magnet coil; mechanical weak points identification; micro-fractures; nonuniform current distribution; quench antennas; quench performance prediction; spike statistics; statistical diagnosis method; superconducting cables; superconducting magnets; training quenches; Cable insulation; Conducting materials; Conductors; Current distribution; Magnetic materials; Statistical analysis; Superconducting cables; Superconducting coils; Superconducting magnets; Superconducting materials;
  • fLanguage
    English
  • Journal_Title
    Applied Superconductivity, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1051-8223
  • Type

    jour

  • DOI
    10.1109/77.920111
  • Filename
    920111