Acoustic emission monitoring for meaningful fatigue life prediction in aluminium alloy 6061

This study introduces a novel method for predicting the fatigue life of aluminium alloy 6061 under block spectrum loading using acoustic emission (AE) data signals. Specimens were subjected to cyclic loading patterns, specifically constant amplitude loading and block spectrum loading, under Low-High and High-Low conditions. AE signals were continuously monitored and recorded, capturing events related to crack initiation and propagation. Key features of the AE data, such as amplitude, frequency, duration, counts, and energy, were extracted and analysed. The cumulative AE activity was correlated with the material's fatigue life, revealing distinct trends at various stages of fatigue damage. Statistical methods were applied to the AE data to develop predictive models for estimating the remaining fatigue life of the specimens. The proposed method demonstrated high accuracy in predicting fatigue life, offering a reliable, non-destructive tool for early detection of fatigue damage. This approach has significant implications for improving the safety and reliability of aluminium alloy 6061 components in critical applications, such as aerospace and automotive industries.