Detection of uniaxial fatigue stress under magnetic flux leakage signals using Morlet wavelet

This paper demonstrates the application of continuous wavelet transform technique for magnetic flux leakage signal generated during a uniaxial fatigue test. This is a consideration as the magnetic signal is weak and susceptible to being influenced by an external magnetic field. The magnetic flux lea...

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Main Authors: S.M. Firdaus, A. Arifin, S. Abdullah, S.S.K. Singh, N. Md Nor
Format: Article
Language:English
Published: Gruppo Italiano Frattura 2022-07-01
Series:Fracture and Structural Integrity
Subjects:
Online Access:https://www.fracturae.com/index.php/fis/article/view/3474/3575
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author S.M. Firdaus
A. Arifin
S. Abdullah
S.S.K. Singh
N. Md Nor
author_facet S.M. Firdaus
A. Arifin
S. Abdullah
S.S.K. Singh
N. Md Nor
author_sort S.M. Firdaus
collection DOAJ
description This paper demonstrates the application of continuous wavelet transform technique for magnetic flux leakage signal generated during a uniaxial fatigue test. This is a consideration as the magnetic signal is weak and susceptible to being influenced by an external magnetic field. The magnetic flux leakage signal response of API steel grade X65 is determined using Metal Magnetic Memory under cyclic load conditions ranging from 50% to 85% of the UTS. To facilitate further signal analysis, the magnetic flux gradient, the dH(y)/dx signal were converted from a length base into time series in this study. Magnetic flux leakage readings indicated a maximum UTS load of 56.5 (A/m)/mm at 85%, where a higher load resulted in a higher reading and the signal contained Morlet wavelet coefficient energy of 1.02�106 �e2/Hz. As increasing percentages of UTS loads were applied, the signal analysis revealed an increasing linear trend in the dH(y)/dx and wavelet coefficient energy. The analysis revealed a strong correlation between the wavelet coefficient energy and the dH(y)/dx amplitude, as indicated by the coefficient of determination (R2) value of 0.8572. Hence, this technique can provide critical information about magnetic flux leakage signals that can be used to detect high stress concentration zones
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institution Kabale University
issn 1971-8993
language English
publishDate 2022-07-01
publisher Gruppo Italiano Frattura
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series Fracture and Structural Integrity
spelling doaj-art-90b65875874042098cd61cb51e18d3272025-01-03T00:38:47ZengGruppo Italiano FratturaFracture and Structural Integrity1971-89932022-07-01166125426510.3221/IGF-ESIS.61.1710.3221/IGF-ESIS.61.17Detection of uniaxial fatigue stress under magnetic flux leakage signals using Morlet waveletS.M. FirdausA. ArifinS. AbdullahS.S.K. SinghN. Md NorThis paper demonstrates the application of continuous wavelet transform technique for magnetic flux leakage signal generated during a uniaxial fatigue test. This is a consideration as the magnetic signal is weak and susceptible to being influenced by an external magnetic field. The magnetic flux leakage signal response of API steel grade X65 is determined using Metal Magnetic Memory under cyclic load conditions ranging from 50% to 85% of the UTS. To facilitate further signal analysis, the magnetic flux gradient, the dH(y)/dx signal were converted from a length base into time series in this study. Magnetic flux leakage readings indicated a maximum UTS load of 56.5 (A/m)/mm at 85%, where a higher load resulted in a higher reading and the signal contained Morlet wavelet coefficient energy of 1.02�106 �e2/Hz. As increasing percentages of UTS loads were applied, the signal analysis revealed an increasing linear trend in the dH(y)/dx and wavelet coefficient energy. The analysis revealed a strong correlation between the wavelet coefficient energy and the dH(y)/dx amplitude, as indicated by the coefficient of determination (R2) value of 0.8572. Hence, this technique can provide critical information about magnetic flux leakage signals that can be used to detect high stress concentration zoneshttps://www.fracturae.com/index.php/fis/article/view/3474/3575ferromagnetic steelmetal magnetic memorywavelet transformuniaxial fatigue stress
spellingShingle S.M. Firdaus
A. Arifin
S. Abdullah
S.S.K. Singh
N. Md Nor
Detection of uniaxial fatigue stress under magnetic flux leakage signals using Morlet wavelet
Fracture and Structural Integrity
ferromagnetic steel
metal magnetic memory
wavelet transform
uniaxial fatigue stress
title Detection of uniaxial fatigue stress under magnetic flux leakage signals using Morlet wavelet
title_full Detection of uniaxial fatigue stress under magnetic flux leakage signals using Morlet wavelet
title_fullStr Detection of uniaxial fatigue stress under magnetic flux leakage signals using Morlet wavelet
title_full_unstemmed Detection of uniaxial fatigue stress under magnetic flux leakage signals using Morlet wavelet
title_short Detection of uniaxial fatigue stress under magnetic flux leakage signals using Morlet wavelet
title_sort detection of uniaxial fatigue stress under magnetic flux leakage signals using morlet wavelet
topic ferromagnetic steel
metal magnetic memory
wavelet transform
uniaxial fatigue stress
url https://www.fracturae.com/index.php/fis/article/view/3474/3575
work_keys_str_mv AT smfirdaus detectionofuniaxialfatiguestressundermagneticfluxleakagesignalsusingmorletwavelet
AT aarifin detectionofuniaxialfatiguestressundermagneticfluxleakagesignalsusingmorletwavelet
AT sabdullah detectionofuniaxialfatiguestressundermagneticfluxleakagesignalsusingmorletwavelet
AT ssksingh detectionofuniaxialfatiguestressundermagneticfluxleakagesignalsusingmorletwavelet
AT nmdnor detectionofuniaxialfatiguestressundermagneticfluxleakagesignalsusingmorletwavelet