Operational modal analysis on a 3D scaled model of a 3-Storey aluminium structure

Obtaining a good experimental modal data is essential in modal analysis in order to ensure accurate extraction of modal parameters. The parameters are compared with other extraction methods to ascertain its consistency and validity. This paper demonstrates the extraction of modal parameters using va...

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Bibliographic Details
Published in:International Journal of Engineering and Technology(UAE)
Main Author: Fadhil Shazmir M.; Ayuni Safari N.; Azhan Anuar M.; Mat Isa A.A.; Zamri A.R.
Format: Article
Language:English
Published: Science Publishing Corporation Inc 2018
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058398122&doi=10.14419%2fijet.v7i4.27.22485&partnerID=40&md5=3df0a304320db3d2b56950897d88f861
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Summary:Obtaining a good experimental modal data is essential in modal analysis in order to ensure accurate extraction of modal parameters. The parameters are compared with other extraction methods to ascertain its consistency and validity. This paper demonstrates the extraction of modal parameters using various identification algorithms in Operational Modal Analysis (OMA) on a 3D scaled model of a 3-storey aluminium structure. Algorithms such as Frequency Domain Decomposition (FDD), Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI) are applied in this study to obtain modal parameters. The model test structure is fabricated of aluminium and assembled using bolts and nuts. Accelerometers were used to collect the responses and the commercial post processing software was used to obtain the modal parameters. The resulting natural frequencies and mode shapes using FDD method are then compared with other OMA parametric technique such as EFDD and SSI algorithm by comparing the natural frequencies and Modal Assurance Criterion (MAC). Comparison of these techniques will be shown to justify the validity of each technique used and hence confirming the accuracy of the measurement taken. © 2018 Authors.
ISSN:2227524X
DOI:10.14419/ijet.v7i4.27.22485