Characterisation of Steel Components Fatigue Life Phenomenon Based on Magnetic Flux Leakage Parameters

The metal magnetic memory (MMM) method is highly effective in assessing the extent of early damage, such as fatigue crack in ferromagnetic components due to the existence of stress concentration zones (SCZs). However, there are limited studies on the relationship between the magnetic signal parameter in predicting the fatigue life of ferromagnetic components. With the advent of information relating to fatigue life, the risk of failure of a component can be reduced, if not avoided. Therefore, this study was conducted using the MMM method to establish a relationship between the magnetic signal parameters in the SCZ with fatigue characteristics in predicting the fatigue life of the specimen. A cyclic test was conducted on SAE 1045 steel specimens using a constant amplitude tension–compression stress with a stress ratio of −1. To investigate the effect of load value on the fatigue life of the specimens, seven percentage values of ultimate tensile strength (UTS) were used: 50%, 55%, 60%, 65%, 70%, 75%, and 80%. During the fatigue crack growth test, the MMM sensor was used to scan the magnetic signal data. Then, the data were analysed using the MMM Lifetime 2.0 software to obtain the fatigue life. Correlation graphs were plotted to determine the relationship between the MMM Lifetime 2.0 residual life and experimental residual life. The experimental results show that the distribution of magnetic signals was affected by the number of cycles and measurement line. As the number of cycles increased, the magnetic signal changes were more noticeable. For the measurement line, when the line was located near the crack initiation point, the magnetic signal distribution became clearer due to the presence of the SCZ. The evaluation of the maximum gradient, K max , variation also helped to assess the level of fatigue life based on the three stages of fatigue crack formation. Whereas, for the fatigue life assessment, the second measurement line (L2) and a contraction value of 0.7 were found to be suitable for predicting the fatigue life of specimens using MMM Lifetime 2.0 software. The experimental fatigue life and MMM Lifetime 2.0 fatigue life distribution of both parameters were in the two-factor range with the correlation coefficient, R 2 of 0.9983. As such, the fatigue prediction results were acceptable. Accordingly, this study has demonstrated that the MMM method can be used to predict the remaining life of ferromagnetic components if the right parameters are used.