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Fatigue crack growth monitoring in aluminum using acoustic emission and acousto‐ultrasonic methods
Author(s) -
Maslouhi Ahmed
Publication year - 2011
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.478
Subject(s) - paris' law , fastener , acoustic emission , prognostics , structural engineering , tension (geology) , materials science , service life , ultrasonic sensor , classification of discontinuities , fracture mechanics , structural health monitoring , engineering , acoustics , crack closure , composite material , reliability engineering , ultimate tensile strength , physics , mathematical analysis , mathematics
SUMMARY Damage monitoring, failure prognostics, and remaining service life prediction represent great technological challenges for reliable maintenance of aeronautical structures. Consequently, there is a whole variety of non‐destructive evaluation techniques that are available to ensure the quality of the metallic structures. The majority of these techniques are able to detect defects such as discontinuities of surface or volume and the variations of section and are applied to discrete intervals. The application of these techniques proves too long and generates high maintenance costs. This paper proposes experimental methodologies to monitor fatigue damage growth in real time and also use a physics‐based model for fatigue life prediction. The aluminum alloy samples, with inserted pre‐cracks in the fastener holes, was tested mechanically in fatigue tension–tension cyclic loading with follow‐up of two complementary health monitoring techniques such as acoustic emission (AE) and acousto‐ultrasonic (AU). The approach uses AE to detect fatigue crack initiation and crack growth in aluminum samples and also applies AU measurements in order to assess global health conditions and damage accumulation during tension–tension cyclic loading. Nasgro analytical fracture mechanic model was used to predict crack growth and to determine the number of the load cycles N f required to grow the initial crack to final crack size a c . The results indicate that exploiting health monitoring data such as AE signals coupled with analytical physics‐based models provides a convenient methodology to determine the fatigue life and to estimate safety factor on life of the materials tested. Furthermore, this paper demonstrates that AU flexural Lamb wave ( A 0 ) offers high potential to track damage before the occurrence of the first crack, such as fatigue damage caused by plastic deformation, and quantitatively to assess fatigue damage stages of the material. Copyright © 2011 John Wiley & Sons, Ltd.