Abstract
This paper presents a reliability-based prediction methodology to obtain the remaining useful life of composite materials subjected to fatigue degradation. Degradation phenomena such as stiffness reduction and increase in matrix micro-cracks density are sequentially estimated through a Bayesian filtering framework that incorporates information from both multi-scale damage models and damage measurements, that are sequentially collected along the process. A set of damage states are further propagated forward in time by simulating the damage progression using the models in the absence of new damage measurements to estimate the time-dependent reliability of the composite material. As a key contribution, the estimation of the remaining useful life is obtained as a probability from the prediction of the time-dependent reliability, whose validity is formally proven using the axioms of Probability Logic. A case study is presented using multi-scale fatigue damage data from a cross-ply carbon-epoxy laminate.
Original language | English |
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Pages (from-to) | 134-147 |
Number of pages | 14 |
Journal | Reliability Engineering and System Safety |
Volume | 142 |
Early online date | 22 May 2015 |
DOIs | |
Publication status | Published - 31 Oct 2015 |
Keywords
- fatigue degradation
- composite materials
- condition-based prediction