Bayesian Localisation of Acoustic Emissions for Structural Health Monitoring
A Bayesian methodology for localising acoustic emission sources in complex structures
A new probabilistic sourcelocalisation strategy that is robust to complex geometrical features is presented.The new framework is first used to learn the relationship between source locations and the corresponding difference-in-time-of-arrivalvalues for a number of sensor pairings.As an acoustic emission event with an unknown origin is observed, a mapping is then generated that quantifies the likelihood of the emission location across the surface of the structure.The new probabilistic mapping offers multiple benefits, leading to a localisation strategy that is more informative than deterministic predictions or single-point estimates with an associated confidence bound.The performance of the approach is investigated on a structure with numerous complex geometrical features and demonstrates a favourable performance in comparison to other similar localisation methods.
