Cargando…

Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites

Electrical Resistance Tomography (ERT) offers a non-destructive evaluation (NDE) technique that takes advantage of the inherent electrical properties in carbon fiber reinforced polymer (CFRP) composites for internal damage characterization. This paper investigates a method of optimum selection of se...

Descripción completa

Detalles Bibliográficos
Autores principales: Escalona Galvis, Luis Waldo, Diaz-Montiel, Paulina, Venkataraman, Satchi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5459171/
https://www.ncbi.nlm.nih.gov/pubmed/28772485
http://dx.doi.org/10.3390/ma10020125
_version_ 1783241921053851648
author Escalona Galvis, Luis Waldo
Diaz-Montiel, Paulina
Venkataraman, Satchi
author_facet Escalona Galvis, Luis Waldo
Diaz-Montiel, Paulina
Venkataraman, Satchi
author_sort Escalona Galvis, Luis Waldo
collection PubMed
description Electrical Resistance Tomography (ERT) offers a non-destructive evaluation (NDE) technique that takes advantage of the inherent electrical properties in carbon fiber reinforced polymer (CFRP) composites for internal damage characterization. This paper investigates a method of optimum selection of sensing configurations for delamination detection in thick cross-ply laminates using ERT. Reduction in the number of sensing locations and measurements is necessary to minimize hardware and computational effort. The present work explores the use of an effective independence (EI) measure originally proposed for sensor location optimization in experimental vibration modal analysis. The EI measure is used for selecting the minimum set of resistance measurements among all possible combinations resulting from selecting sensing electrode pairs. Singular Value Decomposition (SVD) is applied to obtain a spectral representation of the resistance measurements in the laminate for subsequent EI based reduction to take place. The electrical potential field in a CFRP laminate is calculated using finite element analysis (FEA) applied on models for two different laminate layouts considering a set of specified delamination sizes and locations with two different sensing arrangements. The effectiveness of the EI measure in eliminating redundant electrode pairs is demonstrated by performing inverse identification of damage using the full set and the reduced set of resistance measurements. This investigation shows that the EI measure is effective for optimally selecting the electrode pairs needed for resistance measurements in ERT based damage detection.
format Online
Article
Text
id pubmed-5459171
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-54591712017-07-28 Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites Escalona Galvis, Luis Waldo Diaz-Montiel, Paulina Venkataraman, Satchi Materials (Basel) Article Electrical Resistance Tomography (ERT) offers a non-destructive evaluation (NDE) technique that takes advantage of the inherent electrical properties in carbon fiber reinforced polymer (CFRP) composites for internal damage characterization. This paper investigates a method of optimum selection of sensing configurations for delamination detection in thick cross-ply laminates using ERT. Reduction in the number of sensing locations and measurements is necessary to minimize hardware and computational effort. The present work explores the use of an effective independence (EI) measure originally proposed for sensor location optimization in experimental vibration modal analysis. The EI measure is used for selecting the minimum set of resistance measurements among all possible combinations resulting from selecting sensing electrode pairs. Singular Value Decomposition (SVD) is applied to obtain a spectral representation of the resistance measurements in the laminate for subsequent EI based reduction to take place. The electrical potential field in a CFRP laminate is calculated using finite element analysis (FEA) applied on models for two different laminate layouts considering a set of specified delamination sizes and locations with two different sensing arrangements. The effectiveness of the EI measure in eliminating redundant electrode pairs is demonstrated by performing inverse identification of damage using the full set and the reduced set of resistance measurements. This investigation shows that the EI measure is effective for optimally selecting the electrode pairs needed for resistance measurements in ERT based damage detection. MDPI 2017-02-04 /pmc/articles/PMC5459171/ /pubmed/28772485 http://dx.doi.org/10.3390/ma10020125 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Escalona Galvis, Luis Waldo
Diaz-Montiel, Paulina
Venkataraman, Satchi
Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites
title Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites
title_full Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites
title_fullStr Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites
title_full_unstemmed Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites
title_short Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites
title_sort optimal electrode selection for electrical resistance tomography in carbon fiber reinforced polymer composites
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5459171/
https://www.ncbi.nlm.nih.gov/pubmed/28772485
http://dx.doi.org/10.3390/ma10020125
work_keys_str_mv AT escalonagalvisluiswaldo optimalelectrodeselectionforelectricalresistancetomographyincarbonfiberreinforcedpolymercomposites
AT diazmontielpaulina optimalelectrodeselectionforelectricalresistancetomographyincarbonfiberreinforcedpolymercomposites
AT venkataramansatchi optimalelectrodeselectionforelectricalresistancetomographyincarbonfiberreinforcedpolymercomposites