Probabilistic Structural Health Monitoring Using Acoustic Emission

Masoud Rabiei, Mohammad Modarres, and Paul Hoffman
Submission Type: 
Full Paper
Supporting Agencies (optional): 
University of Maryland-College Park
AttachmentSizeTimestamp
phmc_09_43.pdf208.03 KBSeptember 17, 2009 - 5:56am

Fatigue crack initiation and growth during the service of aging aircraft are important life-limiting phenomena. In a previous study, a risk prediction and reliability model for naval aircraft has been developed based on fracture mechanics and inspection field data. Despite significant achievements in the study of fatigue cracks using fracture mechanics, it is still of great interest to find practical techniques for monitoring the crack growth using non-destructive inspection and to integrate the inspection results with the fracture mechanics models to improve the predictions. In this paper, a probabilistic damage-tolerance model based on acoustic emission monitoring is proposed to enhance the reliability and risk prediction for structures subject to fatigue cracking. Experiments were carried out to estimate the stress intensity factor range during fatigue crack propagation using acoustic emission data. The uncertainty of parameters is captured via probability distribution functions. Bayesian regression technique was used to estimate the marginal and joint probability distributions of model parameters. Finally, a risk factor is defined based on the probability that the stress intensity exceeds the fracture toughness of the material given the AE inspection results.

Publication Control Number: 
043
Submission Keywords: 
applications: aviation
crack detection
damage detection
damage propagation model
data driven prognostics
fatigue crack growth
materials damage prognostics
structural health management
structural health monitoring
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