Abstract
Sensitive structures, such as airframes, need careful inspection and maintenance to avoid fatigue failures. These activities are expensive, discrete and imperfect, since catastrophic failure may occur before cracks can be detected. This paper focuses on using information entropy of acoustic emission (AE) signals to identify precursors to fatigue crack initiation in AA7075-T6. The information entropy is investigated as a means to identify the conditions associated with nucleation and coalescence of microcracks that lead to crack initiation. The methodology is demonstrated using data from multiple fatigue tests on notched dog-bone specimens, under different loadings. It was determined that the information entropy reaches a minimum immediately before a macrocrack is formed, with values within an interval of 2.0–3.0 nats, independent of loading condition. Following the minimum information entropy, the cumulative information entropy rapidly increased. Therefore, combining the minimum information entropy with the rapid increase in cumulative information entropy, the new method could be used to detect fatigue crack initiation reliably.
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