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...
Autores principales: | , , |
---|---|
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 |