Defect identification method for stainless steel welded pipes based on eddy current testing

A defect identification and classification method for 316 stainless steel welded pipes is proposed based on eddy current testing technology. Initially, this approach acquires eddy current signals from steel pipes, applies Empirical Mode Decomposition (EMD) to derive Intrinsic Mode Functions (IMFs),...

Full description

Saved in:
Bibliographic Details
Published in:Journal of physics. Conference series 2024-06, Vol.2785 (1), p.12031
Main Authors: Zhang, Hengxi, Li, Shengtao, Wu, Tinghui, An, Yuxiang
Format: Article
Language:English
Subjects:
Austenitic stainless steels
Eddy current testing
Eddy currents
Identification methods
Parameter identification
Principal components analysis
Signal classification
Steel pipes
Support vector machines
Weld defects
Welded pipes
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A defect identification and classification method for 316 stainless steel welded pipes is proposed based on eddy current testing technology. Initially, this approach acquires eddy current signals from steel pipes, applies Empirical Mode Decomposition (EMD) to derive Intrinsic Mode Functions (IMFs), chooses the principal IMF based on interrelationships, and extracts time-frequency domain characteristic parameters from the selected IMF. To enhance model recognition efficiency, Principal Component Analysis (PCA) is employed to reduce the dimensionality of the feature vector set. Ultimately, a Support Vector Machine (SVM) is utilized to identify and classify weld defects. The results indicate that this method is highly accurate in identifying defects in 316 stainless steel welded pipes.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2785/1/012031