Fatigue crack propagation can considerably reduce the life of components, leading to sudden failures. This paper provides a method for fatigue life prediction based on ultrasonic non-destructive inspection applied on Al 2024 T3 material.A new crack quantification model based on ultrasonic waves features is developed. To analyse the performance and efficacity of the model, the probability of detection is determined using the "signal response" technique.The Paris model is used to predict the fatigue life taking into consideration the initial crack distributions, the dispersion of the parameters underlined by the Least-squares method and Monte-Carlo simulations.Reliability evaluation is discussed later for two cases: Detection and No-detection case.If no indication is presented, an inspection detection threshold is determined and optimized. This proposed indicator will be helpful for industrial environments whenever the inspection machine does not have any indication.Considering the ultrasonic inspection data, an updating reliability via the Bayesian approach is suggested. The results of this approach can lead to a gain in the life span or a gain of the costs generated by the failure of the part.
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