| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 8130171 | Ultrasonics | 2016 | 21 Pages |
Abstract
Acoustic emission (AE) technique is a popular tool for materials characterization and non-destructive testing. Originating from the stochastic motion of defects in solids, AE is a random process by nature. The challenging problem arises whenever an attempt is made to identify specific points corresponding to the changes in the trends in the fluctuating AE time series. A general Bayesian framework is proposed for the analysis of AE time series, aiming at automated finding the breakpoints signaling a crossover in the dynamics of underlying AE sources.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Acoustics and Ultrasonics
Authors
E. Agletdinov, E. Pomponi, D. Merson, A. Vinogradov,