title: A novel Bayesian approach to acoustic emission data analysis.
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.
authors: Institute of Advanced Technologies, Togliatti State University, 445667, Russia.
authors: E
authors: E
authors: Agletdinov
authors: Department of Data Science and Analytic, CGnal s.p.a., Via Carducci 38, 20122 Milano, Italy.
authors: E
authors: E
authors: Pomponi
authors: Institute of Advanced Technologies, Togliatti State University, 445667, Russia.
authors: D
authors: D
authors: Merson
authors: Institute of Advanced Technologies, Togliatti State University, 445667, Russia; Department of Engineering Design and Materials, Norwegian University of Science and Technology - NTNU, Trondheim 7491, Norway. Electronic address: alexei.vinogradov@ntnu.no.
authors: A
authors: A
authors: Vinogradov
keywords: Acoustic emission; Bayesian probability; Random time-series; Signal processing