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Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network

Damage detection and structural health monitoring (SHM) of an aircraft wing exposed of changing fuel load can lead to a false alarm if the loading effects are not intelligently discriminated. This is due to the effects of loading can alter the vibration response and misinterpreted as damage effects....

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Main Authors: Abdul Rahim, Sharafiz, Manson, Graeme, Mustapha, Faizal
Format: Article
Published: Aeronautical and Astronautical Society of the Republic of China, Taiwan 2024
Online Access:http://psasir.upm.edu.my/id/eprint/110560/
https://www.airitilibrary.com/Article/Detail/P20140627004-N202401190010-00001
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spelling my.upm.eprints.1105602024-05-27T02:59:26Z http://psasir.upm.edu.my/id/eprint/110560/ Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network Abdul Rahim, Sharafiz Manson, Graeme Mustapha, Faizal Damage detection and structural health monitoring (SHM) of an aircraft wing exposed of changing fuel load can lead to a false alarm if the loading effects are not intelligently discriminated. This is due to the effects of loading can alter the vibration response and misinterpreted as damage effects. Thisstudy proposed the Principal Component Analysis (PCA)-Artificial Neural Network (ANN) for detecting damage of on aircraft wing under the effects of varying fuel tank loading conditions. A vibration test is performed on Jabiru wing which the measured signal is applied with Principal Component Analysis (PCA) to reduce the high dimensionalities and extract the features. ANN is then utilized to map the principal component indices into various damage severities and loading classes using multi-layer perceptron ANN. The results from the study show promising results when incorporating PCA with the ANN to predict various damage severities of the aircraft wing under changing fuel load conditions. Aeronautical and Astronautical Society of the Republic of China, Taiwan 2024 Article PeerReviewed Abdul Rahim, Sharafiz and Manson, Graeme and Mustapha, Faizal (2024) Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network. Journal of Aeronautics, Astronautics and Aviation, 56 (1). pp. 1-10. ISSN 1990-7710 https://www.airitilibrary.com/Article/Detail/P20140627004-N202401190010-00001 10.6125/JoAAA.202403_56(1).01
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Damage detection and structural health monitoring (SHM) of an aircraft wing exposed of changing fuel load can lead to a false alarm if the loading effects are not intelligently discriminated. This is due to the effects of loading can alter the vibration response and misinterpreted as damage effects. Thisstudy proposed the Principal Component Analysis (PCA)-Artificial Neural Network (ANN) for detecting damage of on aircraft wing under the effects of varying fuel tank loading conditions. A vibration test is performed on Jabiru wing which the measured signal is applied with Principal Component Analysis (PCA) to reduce the high dimensionalities and extract the features. ANN is then utilized to map the principal component indices into various damage severities and loading classes using multi-layer perceptron ANN. The results from the study show promising results when incorporating PCA with the ANN to predict various damage severities of the aircraft wing under changing fuel load conditions.
format Article
author Abdul Rahim, Sharafiz
Manson, Graeme
Mustapha, Faizal
spellingShingle Abdul Rahim, Sharafiz
Manson, Graeme
Mustapha, Faizal
Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network
author_facet Abdul Rahim, Sharafiz
Manson, Graeme
Mustapha, Faizal
author_sort Abdul Rahim, Sharafiz
title Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network
title_short Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network
title_full Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network
title_fullStr Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network
title_full_unstemmed Damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network
title_sort damage detection of the jabiru's aircraft wing under operational fuel loading conditions using neural network
publisher Aeronautical and Astronautical Society of the Republic of China, Taiwan
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/110560/
https://www.airitilibrary.com/Article/Detail/P20140627004-N202401190010-00001
_version_ 1800721416821145600
score 13.211869

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