Automated harmonic signal removal technique using stochastic subspace-based image feature extraction

This paper presents automated harmonic removal as a desirable solution to effectively identify and discard the harmonic influence over the output signal by neglecting any user-defined parameter at start-up and automatically reconstruct back to become a useful output signal prior to system identifica...

Full description

Saved in:
Bibliographic Details
Main Authors: Abu Hasan, Muhammad Danial, Ahmad, Zair Asrar, Leong, Mohd. Salman, Lim, Meng Hee
Format: Article
Language:English
Published: MDPI Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:http://eprints.utm.my/id/eprint/90287/1/ZairAsrarAhmad2020_AutomatedHarmonicSignalRemovalTechnique.pdf
http://eprints.utm.my/id/eprint/90287/
http://dx.doi.org/10.3390/jimaging6030010
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Malaysia
Language: English
id my.utm.90287
record_format eprints
spelling my.utm.902872021-04-30T14:30:42Z http://eprints.utm.my/id/eprint/90287/ Automated harmonic signal removal technique using stochastic subspace-based image feature extraction Abu Hasan, Muhammad Danial Ahmad, Zair Asrar Leong, Mohd. Salman Lim, Meng Hee TJ Mechanical engineering and machinery This paper presents automated harmonic removal as a desirable solution to effectively identify and discard the harmonic influence over the output signal by neglecting any user-defined parameter at start-up and automatically reconstruct back to become a useful output signal prior to system identification. Stochastic subspace-based algorithms (SSI) methods are the most practical tool due to the consistency in modal parameters estimation. However, it will be problematic when applied to structures with rotating machines and the presence of harmonic excitations. Difficulties arise when automating this procedure without any human interaction and the problem is still unresolved because stochastic subspace-based algorithms (SSI) methods still require parameters (the maximum within-cluster distance) that are compulsory to be defined at start-up for each analysis of the dataset. Thus, the use of image-based feature extraction for clustering and classification of harmonic components and structural poles directly from a stabilization diagram and for modal system identification is the focus of the present paper. As a fundamental necessary condition, the algorithm has been assessed first from computed numerical responses and then applied to the experimental dataset with the presence of harmonic excitation. Results of the proposed approach for estimating modal parameters demonstrated very high accuracy and exhibited consistent results before and after removing harmonic components from the response signal. MDPI Multidisciplinary Digital Publishing Institute 2020 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/90287/1/ZairAsrarAhmad2020_AutomatedHarmonicSignalRemovalTechnique.pdf Abu Hasan, Muhammad Danial and Ahmad, Zair Asrar and Leong, Mohd. Salman and Lim, Meng Hee (2020) Automated harmonic signal removal technique using stochastic subspace-based image feature extraction. Journal of Imaging, 6 (3). 0010-0010. ISSN 2313-433X http://dx.doi.org/10.3390/jimaging6030010
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Abu Hasan, Muhammad Danial
Ahmad, Zair Asrar
Leong, Mohd. Salman
Lim, Meng Hee
Automated harmonic signal removal technique using stochastic subspace-based image feature extraction
description This paper presents automated harmonic removal as a desirable solution to effectively identify and discard the harmonic influence over the output signal by neglecting any user-defined parameter at start-up and automatically reconstruct back to become a useful output signal prior to system identification. Stochastic subspace-based algorithms (SSI) methods are the most practical tool due to the consistency in modal parameters estimation. However, it will be problematic when applied to structures with rotating machines and the presence of harmonic excitations. Difficulties arise when automating this procedure without any human interaction and the problem is still unresolved because stochastic subspace-based algorithms (SSI) methods still require parameters (the maximum within-cluster distance) that are compulsory to be defined at start-up for each analysis of the dataset. Thus, the use of image-based feature extraction for clustering and classification of harmonic components and structural poles directly from a stabilization diagram and for modal system identification is the focus of the present paper. As a fundamental necessary condition, the algorithm has been assessed first from computed numerical responses and then applied to the experimental dataset with the presence of harmonic excitation. Results of the proposed approach for estimating modal parameters demonstrated very high accuracy and exhibited consistent results before and after removing harmonic components from the response signal.
format Article
author Abu Hasan, Muhammad Danial
Ahmad, Zair Asrar
Leong, Mohd. Salman
Lim, Meng Hee
author_facet Abu Hasan, Muhammad Danial
Ahmad, Zair Asrar
Leong, Mohd. Salman
Lim, Meng Hee
author_sort Abu Hasan, Muhammad Danial
title Automated harmonic signal removal technique using stochastic subspace-based image feature extraction
title_short Automated harmonic signal removal technique using stochastic subspace-based image feature extraction
title_full Automated harmonic signal removal technique using stochastic subspace-based image feature extraction
title_fullStr Automated harmonic signal removal technique using stochastic subspace-based image feature extraction
title_full_unstemmed Automated harmonic signal removal technique using stochastic subspace-based image feature extraction
title_sort automated harmonic signal removal technique using stochastic subspace-based image feature extraction
publisher MDPI Multidisciplinary Digital Publishing Institute
publishDate 2020
url http://eprints.utm.my/id/eprint/90287/1/ZairAsrarAhmad2020_AutomatedHarmonicSignalRemovalTechnique.pdf
http://eprints.utm.my/id/eprint/90287/
http://dx.doi.org/10.3390/jimaging6030010
_version_ 1698696914113921024