Deep learning techniques for magnetic flux leakage inspection with uncertainty quantification / Zi Li.

Pipelines are primary infrastructure to transport oil and natural gas with low cost. Magnetic flux leakage (MFL), one of the most popular electromagnetic nondestructive evaluation (NDE) methods, is a crucial inspection technique of pipeline safety to prevent long-term failures. The important problem...

Full description

Bibliographic Details
Main Author:	Li, Zi (Graduate of Michigan State University) (Author)
Language:	English
Published:	2019.
Subjects:	Petroleum pipeline failures > Prevention. Petroleum pipelines > Nondestructive testing. Gas leakage > Testing. Magnetic flux > Measurement. Electronic dissertations. Academic theses.
Genre:	Electronic dissertations. Academic theses.
Online Access:	Connect to online resource - MSU authorized users Connect to online resource - All users (Digital Object Identifier Permalink)
Dissertation Note:	Thesis M.S. Michigan State University. Electrical Engineering 2019.
Physical Description:	1 online resource (vii, 75 pages) : illustrations
Format:	Thesis Electronic eBook

System Under Maintenance

Our Library Management System is currently under maintenance.

Holdings and item availability information is currently unavailable. Please accept our apologies for any inconvenience this may cause and contact us for further assistance:

Please contact Reference and Discovery Services via their Contact Form or call them directly at: 517-353-8700 for assistance.

Online Access

Connect to online resource - MSU authorized users
Connect to online resource - All users (Digital Object Identifier Permalink)