Multiple defect interpretation based on Gaussian processes for MFL technology

Publisher:
SPIE
Publication Type:
Conference Proceeding
Citation:
Proceedings of SPIE - The International Society for Optical Engineering vol 8694 - Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2013, 2013, pp. 1 - 12
Issue Date:
2013-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2012006389OK.pdf4.74 MB
Adobe PDF
Magnetic Flux Leakage (MFL) technology has been used in non-destructive testing for more than three decades. There have been several publications in detecting and sizing defects on metal pipes using machine learning techniques. Most of these literature focus on isolated defects, which is far from the real scenario.
Please use this identifier to cite or link to this item: