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

Abstract 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...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 2785; no. 1; pp. 12031 - 12036
Main Authors Zhang, Hengxi, Li, Shengtao, Wu, Tinghui, An, Yuxiang
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.06.2024
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
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Summary:Abstract 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