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European Workshop on Structural Health Monitoring

EWSHM 2022: European Workshop on Structural Health Monitoring pp 630–639Cite as

Entropy-Based Technique for Denoising of Acoustic Emission Signals

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Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 253))

Abstract

The acoustic emission (AE) method has been successfully used in recent years to monitor the condition of industrial and civil infrastructures. In AE, time-of-arrival (ToA) estimation is considered a key parameter for the accurate localization of a growing defect. This paper describes an entropy-based filtering approach for the ToA estimation of noisy signals and compares its performance to that of the commonly adopted Akaike Information Criterion (AIC). The proposed method consists in coarsening the input data using the Crutchfield-Packard algorithm and calculating the local (instantaneous) entropy. In the present study, we demonstrate that the local entropy of the background noise component differs from the useful (informative) signal. As a result, the approach permits filtering the noise component by selecting a proper threshold value. The proposed method has been tested on experimental data aimed at localizing a source of AE in a square \(1 \times 1\) m aluminum plate. The entropy approach allows an overreaching precision in the final localization of the targets compared to the classical AIC.

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Authors and Affiliations

  1. University of Bologna, 40136, Bologna, Italy

    Denis Bogomolov, Nicola Testoni, Luca De Marchi & Alessandro Marzani

  2. Omsk State Technical University, Mira, h. 11, 644050, Omsk, Russian Federation

    Evgeny Burda, Irina Kudryavtseva & Alexandr Naumenko

Authors
  1. Denis Bogomolov
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  2. Evgeny Burda
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  3. Nicola Testoni
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  4. Irina Kudryavtseva
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  5. Luca De Marchi
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  6. Alexandr Naumenko
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  7. Alessandro Marzani
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Corresponding author

Correspondence to Denis Bogomolov .

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Editors and Affiliations

  1. Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA, USA

    Piervincenzo Rizzo

  2. Department of Engineering, University of Palermo, Palermo, Italy

    Alberto Milazzo

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Bogomolov, D. et al. (2023). Entropy-Based Technique for Denoising of Acoustic Emission Signals. In: Rizzo, P., Milazzo, A. (eds) European Workshop on Structural Health Monitoring. EWSHM 2022. Lecture Notes in Civil Engineering, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-031-07254-3_64

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  • DOI: https://doi.org/10.1007/978-3-031-07254-3_64

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-07253-6

  • Online ISBN: 978-3-031-07254-3

  • eBook Packages: EngineeringEngineering (R0)

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