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

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.

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“…If cracks are not detected in time, the cracks will extend during the use of metal structural parts, leading to fracture, causing casualties and property damage, and triggering serious safety accidents [3]. At present, the conventional nondestructive testing methods for metal crack defects mainly include: Ultrasonic Testing [4], Radiographic Testing [5], Magnetic Flux Leakage [6], Eddy Current Testing [7], Penetration Testing [8] and Acoustic Emission [9]. Each technology has corresponding application areas and different defect detection capabilities, but all have certain limitations, such as Ultrasonic Testing and Radiographic Testing for the detection of defects within the metal structure, Magnetic Flux Leakage, Eddy Current Testing and Penetration Testing for the detection of surface and near-surface cracks in metal specimens.…”