Oumar I. Traoré, Laurent Pantera, Nathalie
Favretto-Cristini, Paul Cristini, S. Viguier-Pla,
Philippe Vieu (2017)
Structure analysis and denoising using Singular Spectrum Analysis:
application to acoustic emission signals from nuclear safety experiments.
Measurement, 104, 78-88
ISSN:
- Classification
- 34K08, 35P05, 76Q99
- Keywords
acoustic emission, singular spectrum
analysis, structural changes detection, signal denoising,
nuclear environment
Abstract : We explore the abilities of the Singular Spectrum
Analysis (SSA) to characterize and denoise discrete acoustic emission
signals. The method is first tested on simulated data for which
different types and levels
of noise are considered. It is then applied on real data recorded from
nuclear safety experiments. The results show an excellent ability of
the SSA to characterize the corrupted signal and to detect structural
changes, even for low signal-to-noise ratio. For denoising purposes,
the quality of the results depends mainly on the separability between
the source signal to be estimated and the noise. However, whatever
the case, the main components of the source signal are clearly
identified when the components associated
with the noise are removed.