Comparison of Cooled and Uncooled IR Sensors by Means of Signal-to-Noise Ratio for NDT Diagnostics of Aerospace Grade Composites.

UAV active infrared thermography aircraft-grade composites pulsed thermography signal-to-noise ratio (SNR)

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
15 Jun 2020
Historique:
received: 08 04 2020
revised: 22 05 2020
accepted: 28 05 2020
entrez: 19 6 2020
pubmed: 19 6 2020
medline: 19 6 2020
Statut: epublish

Résumé

This work aims to address the effectiveness and challenges of non-destructive testing (NDT) by active infrared thermography (IRT) for the inspection of aerospace-grade composite samples and seeks to compare uncooled and cooled thermal cameras using the signal-to-noise ratio (SNR) as a performance parameter. It focuses on locating impact damages and optimising the results using several signal processing techniques. The work successfully compares both types of cameras using seven different SNR definitions, to understand if a lower-resolution uncooled IR camera can achieve an acceptable NDT standard. Due to most uncooled cameras being small, lightweight, and cheap, they are more accessible to use on an unmanned aerial vehicle (UAV). The concept of using a UAV for NDT on a composite wing is explored, and the UAV is also tracked using a localisation system to observe the exact movement in millimetres and how it affects the thermal data. It was observed that an NDT UAV can access difficult areas and, therefore, can be suggested for significant reduction of time and cost.

Identifiants

pubmed: 32549370
pii: s20123381
doi: 10.3390/s20123381
pmc: PMC7348926
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Engineering and Physical Sciences Research Council
ID : EP/N509450/1

Références

PLoS One. 2013 Nov 06;8(11):e77089
pubmed: 24223118
Sensors (Basel). 2014 Jul 10;14(7):12305-48
pubmed: 25014096
Sensors (Basel). 2017 Dec 26;18(1):
pubmed: 29278361
Sensors (Basel). 2018 Feb 16;18(2):
pubmed: 29462953

Auteurs

Shakeb Deane (S)

School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK.

Nicolas P Avdelidis (NP)

School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK.
Computer Vision and Systems Laboratory (CVSL), Department of Electrical and Computer Engineering, Laval University, Quebec City, QC G1V 0A6, Canada.

Clemente Ibarra-Castanedo (C)

Computer Vision and Systems Laboratory (CVSL), Department of Electrical and Computer Engineering, Laval University, Quebec City, QC G1V 0A6, Canada.

Hai Zhang (H)

Computer Vision and Systems Laboratory (CVSL), Department of Electrical and Computer Engineering, Laval University, Quebec City, QC G1V 0A6, Canada.

Hamed Yazdani Nezhad (H)

Department of Mechanical Engineering and Aeronautics, University of London, London WC1E 7HU, UK.

Alex A Williamson (AA)

Mapair Thermography Ltd., Melbourn, South Cambridgeshire SG8, UK.

Tim Mackley (T)

School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK.

Xavier Maldague (X)

Computer Vision and Systems Laboratory (CVSL), Department of Electrical and Computer Engineering, Laval University, Quebec City, QC G1V 0A6, Canada.

Antonios Tsourdos (A)

School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK.

Parham Nooralishahi (P)

Computer Vision and Systems Laboratory (CVSL), Department of Electrical and Computer Engineering, Laval University, Quebec City, QC G1V 0A6, Canada.

Classifications MeSH