Acoustic emission as a reliable technique for filiform corrosion monitoring on coated AA7075-T6: Tailored data processing

C. Abarkane; A. M. Florez-Tapia; J. Odriozola; A. Artetxe; M. Lekka; E. García-Lecina; H. J. Grande; J. M. Vega

doi:10.1016/j.corsci.2023.110964

Acoustic emission as a reliable technique for filiform corrosion monitoring on coated AA7075-T6: Tailored data processing

C. Abarkane
, A. M. Florez-Tapia
, J. Odriozola
, A. Artetxe
, M. Lekka
, E. García-Lecina
, H. J. Grande
, J. M. Vega^*

^*Autor correspondiente de este trabajo

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

15 Citas (Scopus)

Resumen

Acoustic emission (AE) was used for in-situ filiform corrosion (FFC) monitoring on coated AA77075-T6. The analysis of AE data using DBSCAN as clustering algorithm (validated by Bhattacharyya Coefficients´ evaluation) has revealed the presence of three clusters (out of four) related to phenomena involved in the FFC mechanism: metal-coating interface delamination due to opening (tensile), sliding (shear) and mixed mode enclosing both previous ones. The peak frequency was found to be the most relevant descriptor for clustering by using Random Forest classifier, and the correlation with the dominant frequencies range was validated obtaining the Power Spectrum Density of the AE signals.

Idioma original	Inglés
Número de artículo	110964
Publicación	Corrosion Science
Volumen	214
DOI	https://doi.org/10.1016/j.corsci.2023.110964
Estado	Publicada - 15 abr 2023
Publicado de forma externa	Sí

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10.1016/j.corsci.2023.110964

Acoustic emissionVersión publicada final, 9,27 MBLicencia: CC BY-NC-ND

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title = "Acoustic emission as a reliable technique for filiform corrosion monitoring on coated AA7075-T6: Tailored data processing",

abstract = "Acoustic emission (AE) was used for in-situ filiform corrosion (FFC) monitoring on coated AA77075-T6. The analysis of AE data using DBSCAN as clustering algorithm (validated by Bhattacharyya Coefficients´ evaluation) has revealed the presence of three clusters (out of four) related to phenomena involved in the FFC mechanism: metal-coating interface delamination due to opening (tensile), sliding (shear) and mixed mode enclosing both previous ones. The peak frequency was found to be the most relevant descriptor for clustering by using Random Forest classifier, and the correlation with the dominant frequencies range was validated obtaining the Power Spectrum Density of the AE signals.",

keywords = "Aluminium, Interfaces, Paint coatings",

author = "C. Abarkane and Florez-Tapia, \{A. M.\} and J. Odriozola and A. Artetxe and M. Lekka and E. Garc{\'i}a-Lecina and Grande, \{H. J.\} and Vega, \{J. M.\}",

note = "Publisher Copyright: {\textcopyright} 2023 The Authors",

year = "2023",

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day = "15",

doi = "10.1016/j.corsci.2023.110964",

language = "English",

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journal = "Corrosion Science",

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TY - JOUR

T1 - Acoustic emission as a reliable technique for filiform corrosion monitoring on coated AA7075-T6

T2 - Tailored data processing

AU - Abarkane, C.

AU - Florez-Tapia, A. M.

AU - Odriozola, J.

AU - Artetxe, A.

AU - Lekka, M.

AU - García-Lecina, E.

AU - Grande, H. J.

AU - Vega, J. M.

PY - 2023/4/15

Y1 - 2023/4/15

N2 - Acoustic emission (AE) was used for in-situ filiform corrosion (FFC) monitoring on coated AA77075-T6. The analysis of AE data using DBSCAN as clustering algorithm (validated by Bhattacharyya Coefficients´ evaluation) has revealed the presence of three clusters (out of four) related to phenomena involved in the FFC mechanism: metal-coating interface delamination due to opening (tensile), sliding (shear) and mixed mode enclosing both previous ones. The peak frequency was found to be the most relevant descriptor for clustering by using Random Forest classifier, and the correlation with the dominant frequencies range was validated obtaining the Power Spectrum Density of the AE signals.

AB - Acoustic emission (AE) was used for in-situ filiform corrosion (FFC) monitoring on coated AA77075-T6. The analysis of AE data using DBSCAN as clustering algorithm (validated by Bhattacharyya Coefficients´ evaluation) has revealed the presence of three clusters (out of four) related to phenomena involved in the FFC mechanism: metal-coating interface delamination due to opening (tensile), sliding (shear) and mixed mode enclosing both previous ones. The peak frequency was found to be the most relevant descriptor for clustering by using Random Forest classifier, and the correlation with the dominant frequencies range was validated obtaining the Power Spectrum Density of the AE signals.

KW - Aluminium

KW - Interfaces

KW - Paint coatings

UR - https://www.scopus.com/pages/publications/85147205339

U2 - 10.1016/j.corsci.2023.110964

DO - 10.1016/j.corsci.2023.110964

M3 - Article

AN - SCOPUS:85147205339

SN - 0010-938X

VL - 214

JO - Corrosion Science

JF - Corrosion Science

M1 - 110964

ER -

Acoustic emission as a reliable technique for filiform corrosion monitoring on coated AA7075-T6: Tailored data processing

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