A Pipeline Defect Inversion Method With Erratic MFL Signals Based on Cascading Abstract Features

Defect inversion, as a key step in magnetic flux leakage (MFL) inspection widely used in nondestructive testing (NDT) systems, is critical to quantitative analysis of pipeline risk level. However, the conventional methods are difficult to achieve desirable results with complex and changeable MFL sig...

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Vydané v:	IEEE transactions on instrumentation and measurement Ročník 71; s. 1 - 11
Hlavní autori:	Zhang, Huaguang, Wang, Lei, Wang, Jianfeng, Zuo, Fengyuan, Wang, Jifeng, Liu, Jinhai
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Abstract feature extraction Adaptation models cascade-stacking defect inversion Defects Estimation Feature extraction Inspection Magnetic flux magnetic flux leakage (MFL) Magnetic flux leakage testing Magnetic resonance imaging Magnetic sensors Nondestructive testing Pipelines Risk levels stacked multipath denoising sparse autoencoder (sMPDS-AE)
ISSN:	0018-9456, 1557-9662
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