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|Authors: ||De Rubeis, V.*|
Benson, P. M.
|Editors: ||De Rubeis Valerio; Istituto Nazionale di Geofisica e Vulcanologia; Istituto Nazionale di Geofisica e Vulcanologia; Istituto Nazionale di Geofisica e Vulcanologia; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italia|
|Title: ||Acoustic Emission spectra classification from rock samples of Etna basalt in deformation-decompression laboratory experiments|
|Issue Date: ||2010|
|Keywords: ||acoustic emissions|
|Abstract: ||Recent laboratory experiments on Etna basalt have permitted the generation of an extensive
catalogue of acoustic emissions (AE) during two key experimental phases. Firstly, AE have been
generated during triaxial compressional tests and formation of a complex fracture/damage zone.
Secondly, rapid fluid decompression through the damage/shear zone after failure. We report new
results from an advanced analysis method using AE spectrograms, allowing us to qualitatively
identify high and low frequency events; essentially comparable to seismicity in volcanic areas. Our
analysis, for the first time, quantitatively classifies ‘families’ of AE events belonging to the same
experimental stage without prior knowledge. We then test the method using the AE catalogue for
verification, which is not possible with field data.
FFT spectra, obtained from AE, are subdivided into equal log intervals for which a local slope is
calculated. Factor analysis has been then applied, in which we use a data matrix of columns
representing the variables considered (frequency data averaged in bins) vs. rows indicating each AE
data set. Factor analysis shows that the method is very effective and suitable for reducing data
complexity, allowing distinct factors to be obtained.
We conclude that most of the data variance (information content) can be well represented by three
factors only, each one representing a well defined frequency range. Through the factor scores it is
possible to represent data in a lower dimension factor space. Classification is then possible by
identifying clusters of AE belonging to the same experimental stage. This allows us to propose a
deformation/decompression interpretation based solely on the AE frequency analysis and to identify
a third type of AE related to fluid movements in the deformation stage.|
|Appears in Collections:||05.01.04. Statistical analysis|
04.06.08. Volcano seismology
04.08.05. Volcanic rocks
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