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Syed Muhamad Firdaus Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia Azli Arifin Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia Shahrum Abdullah Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia Salvinder Singh Karam Singh Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia Noorsuhada Md Nor Civill Engineering Studies, College of Engineering, Universiti Teknologi MARA, Cawangan Pulau Pinang, 13500 Permatang Pauh, Pulau Pinang, Malaysia.

Abstract

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 µe2/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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Section
SI: Failure Analysis of Materials and Structures

How to Cite

Detection of Uniaxial Fatigue Stress under Magnetic Flux Leakage Signals using Morlet Wavelet. (2022). Fracture and Structural Integrity, 16(61), 254-265. https://doi.org/10.3221/IGF-ESIS.61.17

How to Cite

Detection of Uniaxial Fatigue Stress under Magnetic Flux Leakage Signals using Morlet Wavelet. (2022). Fracture and Structural Integrity, 16(61), 254-265. https://doi.org/10.3221/IGF-ESIS.61.17

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