Bayesian waveform-based calibration of high-pressure acoustic emission systems with ball drop measurements

TitleBayesian waveform-based calibration of high-pressure acoustic emission systems with ball drop measurements
Publication TypeJournal Article
Year of Publication2020
AuthorsGu, C, Mok, U, Marzouk, YM, Prieto, GA, Sheibani, F, J Evans, B, Hager, B
JournalGeophysical Journal International
Volume221
Issue1
Pagination20 - 36
Date PublishedJan-04-2020
ISSN0956-540X
Abstract

Acoustic emission (AE) is a widely used technology to study source mechanisms and material properties during high-pressure rock failure experiments. It is important to understand the physical quantities that acoustic emission sensors measure, as well as the response of these sensors as a function of frequency. This study calibrates the newly built AE system in the MIT Rock Physics Laboratory using a ball-bouncing system. Full waveforms of multibounce events due to ball drops are used to infer the transfer function of lead zirconate titanate (PZT) sensors in high pressure environments. Uncertainty in the sensor transfer functions is quantified using a waveform-based Bayesian approach. The quantification of in situ sensor transfer functions makes it possible to apply full waveform analysis for acoustic emissions at high pressures.

URLhttps://academic.oup.com/gji/article/221/1/20/5680485
DOI10.1093/gji/ggz568