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A Preliminary study on feasibility radar cross-section of foreign object debris for size classification

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Main Authors: P. N., Ja’afar, S. M., Idrus, S., Ambran, A., Hamzah, N., Zulkifli, N. A., Hamid, A., Kanno, Shibagaki, N., Kashima, K., T., Kawanishi
Other Authors: sevia@utm.my
Format: Article
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2022
Subjects:
Artificial neural network
Backpropagation
Classification
FOD dataset
Foreign object debris
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/74960
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spelling my.unimap-749602022-12-16T01:21:41Z A Preliminary study on feasibility radar cross-section of foreign object debris for size classification P. N., Ja’afar S. M., Idrus S., Ambran A., Hamzah N., Zulkifli N. A., Hamid A., Kanno Shibagaki, N. Kashima, K. T., Kawanishi sevia@utm.my Artificial neural network Backpropagation Classification FOD dataset Foreign object debris Link to publisher's homepage at http://ijneam.unimap.edu.my In this paper, a preliminary evaluation study is conducted, which aiming to investigate the radar cross-section (RCS) value that is capable to be used as an input parameter for Artificial Neural network (ANN) backpropagation for foreign object debris (FOD) size classification. The experimental work procedure for dataset acquisition is described. The FOD simulator is used as the FOD target which is made of metal cylinder shape with nine various dimensions and its RCS is defined by using Maxwell’s equation. The location varying backscattered electromagnetic field from each target is measured for RCS calibration purposes. It is found that by using the received signal from radar, which is the RCS of the target and its locations, it can be utilized as input parameters of backpropagation algorithms. The ANN classification application is to define its size by the ranges; small (-30.99 to -21 dBsm), medium (-20.99 to -11 dBsm), and large (-10.99 to 0 dBsm). The interference signal getting from measurement (22.46 to 25.2 dBsm) exhibited good reflectivity behavior. The acquired input showed to be useful for ANN for FOD size classification. 2022-04-14T05:03:54Z 2022-04-14T05:03:54Z 2021-12 Article International Journal of Nanoelectronics and Materials, vol.14(Special Issue), 2021, pages 165-173 1985-5761 (Printed) 1997-4434 (Online) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/74960 http://ijneam.unimap.edu.my en Universiti Malaysia Perlis (UniMAP)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Artificial neural network
Backpropagation
Classification
FOD dataset
Foreign object debris
spellingShingle Artificial neural network
Backpropagation
Classification
FOD dataset
Foreign object debris
P. N., Ja’afar
S. M., Idrus
S., Ambran
A., Hamzah
N., Zulkifli
N. A., Hamid
A., Kanno
Shibagaki, N.
Kashima, K.
T., Kawanishi
A Preliminary study on feasibility radar cross-section of foreign object debris for size classification
description Link to publisher's homepage at http://ijneam.unimap.edu.my
author2 sevia@utm.my
author_facet sevia@utm.my
P. N., Ja’afar
S. M., Idrus
S., Ambran
A., Hamzah
N., Zulkifli
N. A., Hamid
A., Kanno
Shibagaki, N.
Kashima, K.
T., Kawanishi
format Article
author P. N., Ja’afar
S. M., Idrus
S., Ambran
A., Hamzah
N., Zulkifli
N. A., Hamid
A., Kanno
Shibagaki, N.
Kashima, K.
T., Kawanishi
author_sort P. N., Ja’afar
title A Preliminary study on feasibility radar cross-section of foreign object debris for size classification
title_short A Preliminary study on feasibility radar cross-section of foreign object debris for size classification
title_full A Preliminary study on feasibility radar cross-section of foreign object debris for size classification
title_fullStr A Preliminary study on feasibility radar cross-section of foreign object debris for size classification
title_full_unstemmed A Preliminary study on feasibility radar cross-section of foreign object debris for size classification
title_sort preliminary study on feasibility radar cross-section of foreign object debris for size classification
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2022
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/74960
_version_ 1753972984238833664
score 13.222552

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