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RIS citation export for TUPB082: Automatic Surface Defect Detection and Sizing for Superconducting Radio Frequency Cavity Using Haar Cascades

TY - CPAPER
AU - Eremeev, G.V.
AU - Iriks, D.C.
TI - Automatic Surface Defect Detection and Sizing for Superconducting Radio Frequency Cavity Using Haar Cascades
J2 - Proc. of International Conference on RF Superconductivity (SRF2015), Whistler, BC, Canada, Sept. 13-18, 2015
AB - 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.
PB - JACoW
CY - Geneva, Switzerland
SP - 788
EP - 790
KW - cavity
KW - niobium
KW - background
KW - radio-frequency
KW - SRF
DA - 2015/12
PY - 2015
SN - 978-3-95450-178-6
DO - 10.18429/JACoW-SRF2015-TUPB082
UR - http://srf2015.vrws.de/papers/tupb082.pdf
ER -