Assessment of fatigue crack growth in 316LN stainless steel based on acoustic emission entropy

Abstract This paper presents an investigation of assessment of fatigue crack growth (FCG) of 316LN stainless steel using the acoustic emission (AE) monitoring technique. A new AE parameter, i.e. AE entropy, was used for accurate assessment of fatigue damage and prediction of fatigue crack length. The effects of peak load on both FCG and AE behaviors were also discussed by fractographic observations and AE parameter analyses. The results showed that AE entropy is effective for accurately identifying the point of crack initiation and assessing the fatigue damage during FCG of 316LN stainless steel under high noise loading environment. Moreover, two distinct damage stages were distinguished by the characteristics of AE entropy. The source mechanisms of AE entropy for stage 1 were fatigue crack initiation and small crack growth, while the mechanisms responsible for stage 2 were the plastic activities in plastic zone at the crack tip, the formation of micro-voids and the ligaments shearing between these micro-voids. The results also indicated that AE entropy is available for identifying the transition in stress condition from plane strain to plane stress state of specimens under high peak load. In addition, a probabilistic model based on the quantitative relationship between the crack growth size and cumulated entropy was proposed for prognosis of crack growth. Bayesian inference was used to estimate the model parameters and the posterior predictive distribution of crack length. The predictive results showed that the model could accurately predict the measured crack growth lengths in all cases. The proposed model is applicable to stable long crack growth and can be applied under high noise loading environment.