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DOI:10.18429/JACoW-SRF2015-TUPB082
Title Automatic Surface Defect Detection and Sizing for Superconducting Radio Frequency Cavity Using Haar Cascades
Authors
  • G.V. Eremeev
    JLab, Newport News, Virginia, USA
  • D.C. Iriks
    Santa Rosa Junior College, Santa Rosa, USA
Abstract Serious albeit tiny surface defects can remain on the surface of superconducting radio frequency (SRF) cavities after polishing and cleaning. These defects reduce the efficiency of cavities and often limit the maximum attainable fields. We applied a Haar cascade artificial vision technique for automated identification, counting, and sizing of defects induced on niobium surface by Nb-H precipitates formed at cryogenic temperatures. The defects were counted and sized by a computer program and also counted and measured manually to estimate detection rate and accuracy of sizing. The overall detection rate was 53%, and the overall false positive rate was 29%. The technique that was used to automatically size the features was found to oversize the features, but oversize them consistently, resulting in a size histogram that represents the defect size distribution on the sample. After scaling the histogram data, the average defect area was found to be 90 square micrometers with the standard deviation of 70 square micrometers.
Paper download TUPB082.PDF [0.469 MB / 3 pages]
Conference SRF2015, Whistler, BC, Canada
Series International Conference on RF Superconductivity (17th)
Proceedings Link to full SRF2015 Proccedings
Session Poster Session
Date 15-Sep-15   14:30–17:40
Main Classification SRF Technology - Cavity
Keywords cavity, niobium, background, radio-frequency, SRF
Publisher JACoW, Geneva, Switzerland
Editors Robert E. Laxdal (TRIUMF, Vancouver, BC, Canada); Jana Thomson (TRIUMF, Vancouver, BC, Canada); Volker RW Schaa (GSI, Darmstadt, Germany)
ISBN 978-3-95450-178-6
Published December 2015
Copyright
Copyright © 2015 by JACoW, Geneva, Switzerland     CC-BY Creative Commons License
cc Creative Commons Attribution 3.0