Title: The probabilistic analysis of fatigue crack effect based on magnetic flux leakage

Authors: M.I.M. Ahmad; A. Arifin; S. Abdullah; W.Z.W. Jusoh; S.S.K. Singh

Addresses: Department of Mechanical Engineering, The University of Sheffield, Sir Frederick Mappin Building, Mappin Street, S1 3JD Sheffield, UK ' Department of Mechanical & Materials Engineering, Faculty of Engineering and Build Environments, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia ' Department of Mechanical & Materials Engineering, Faculty of Engineering and Build Environments, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia ' Department of Mechanical & Materials Engineering, Faculty of Engineering and Build Environments, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia ' Department of Mechanical & Materials Engineering, Faculty of Engineering and Build Environments, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia

Abstract: In this paper, probabilistic analysis on the fatigue crack effect was investigated by applying the Metal Magnetic Memory (MMM) method, based on Self-Magnetic Leakage Field (SMLF) signals on the surface of metal components. The precision of MMM signals is essential in identifying the validity of the proposed method. The tension-tension fatigue test was conducted using the testing frequency of 10 Hz with 4 kN loaded, and the MMM signals were captured using the MMM instrument. As a result, a linear relationship was observed between the magnetic flux leakage and cyclic loading parameter, presenting the R-squared value at 0.72-0.97. The 2P-Weibull distribution function was used as a probabilistic approach to identify the precision of the data analysis from the predicted, and experimental fatigue lives, thereby showing that all points are placed within the range of a factor of 2. Additionally, the characteristics of PDF, CDF, failure rate and failure probability data analysis were plotted and described. Therefore, a 2P-Weibull probability distribution approach is determined to be an appropriate method to determine the accuracy of data analysis for MMM signals in a fatigue test for metal components.

Keywords: metal magnetic memory signals; probabilistic; fatigue lives; Weibull distribution.

DOI: 10.1504/IJRS.2019.097011

International Journal of Reliability and Safety, 2019 Vol.13 No.1/2, pp.18 - 30

Received: 17 Sep 2017
Accepted: 24 Apr 2018
Published online: 14 Dec 2018 *

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