An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel

Number of existing signal processing methods can be used for extracting useful information. However, receiving desired and eliminating undesired information is yet a significant problem of these methods. Empirical Mode Decomposition (EMD) algorithm shows promising results in comparison to other sign...

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Main Authors: Mohd Jaafar, N.S., Aziz, I.A., Jaafar, J., Mahmood, A.K., Gilal, A.R.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.23587 /
Published: Springer Verlag 2019
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047859630&doi=10.1007%2f978-3-319-91189-2_24&partnerID=40&md5=a16ae21db8a5efb5e6a131d50c009adf
http://eprints.utp.edu.my/23587/
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spelling utp-eprints.235872021-08-19T07:55:58Z An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel Mohd Jaafar, N.S. Aziz, I.A. Jaafar, J. Mahmood, A.K. Gilal, A.R. Number of existing signal processing methods can be used for extracting useful information. However, receiving desired and eliminating undesired information is yet a significant problem of these methods. Empirical Mode Decomposition (EMD) algorithm shows promising results in comparison to other signal processing methods especially in terms of accuracy. For example, it shows an efficient relationship between signal energy and time frequency distribution. Though, EMD algorithm still has a noise contamination which may compromise the accuracy of the signal processing. It is due to the mode mixing phenomenon in the Intrinsic Mode Function�s (IMF) which causes the undesirable signal with the mix of additional noise. Therefore, it has still a room for the improvements in the selective accuracy of the sensitive IMF after decomposition that can influence the correctness of feature extraction of the oxidized carbon steel. This study has used two datasets to compare the parameters analysis of the Ensemble Empirical Mode Decomposition (EEMD) algorithm for constructing the signal signature. © 2019, Springer International Publishing AG, part of Springer Nature. Springer Verlag 2019 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047859630&doi=10.1007%2f978-3-319-91189-2_24&partnerID=40&md5=a16ae21db8a5efb5e6a131d50c009adf Mohd Jaafar, N.S. and Aziz, I.A. and Jaafar, J. and Mahmood, A.K. and Gilal, A.R. (2019) An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel. Advances in Intelligent Systems and Computing, 764 . pp. 241-255. http://eprints.utp.edu.my/23587/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Number of existing signal processing methods can be used for extracting useful information. However, receiving desired and eliminating undesired information is yet a significant problem of these methods. Empirical Mode Decomposition (EMD) algorithm shows promising results in comparison to other signal processing methods especially in terms of accuracy. For example, it shows an efficient relationship between signal energy and time frequency distribution. Though, EMD algorithm still has a noise contamination which may compromise the accuracy of the signal processing. It is due to the mode mixing phenomenon in the Intrinsic Mode Function�s (IMF) which causes the undesirable signal with the mix of additional noise. Therefore, it has still a room for the improvements in the selective accuracy of the sensitive IMF after decomposition that can influence the correctness of feature extraction of the oxidized carbon steel. This study has used two datasets to compare the parameters analysis of the Ensemble Empirical Mode Decomposition (EEMD) algorithm for constructing the signal signature. © 2019, Springer International Publishing AG, part of Springer Nature.
format Article
author Mohd Jaafar, N.S.
Aziz, I.A.
Jaafar, J.
Mahmood, A.K.
Gilal, A.R.
spellingShingle Mohd Jaafar, N.S.
Aziz, I.A.
Jaafar, J.
Mahmood, A.K.
Gilal, A.R.
An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
author_sort Mohd Jaafar, N.S.
title An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
title_short An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
title_full An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
title_fullStr An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
title_full_unstemmed An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
title_sort enhance approach of filtering to select adaptive imfs of eemd in fiber optic sensor for oxidized carbon steel
publisher Springer Verlag
publishDate 2019
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047859630&doi=10.1007%2f978-3-319-91189-2_24&partnerID=40&md5=a16ae21db8a5efb5e6a131d50c009adf
http://eprints.utp.edu.my/23587/
_version_ 1741196699676704768
score 11.62408

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