Operational Modal Analysis on a 3D Scaled Model of a 3-Storey Aluminium Structure

M Fadhil Shazmir,A A.Mat Isa,Zamri A.R,N Ayuni Safari,M Azhan Anuar

doi:10.14419/ijet.v7i4.27.22485

Abstract

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.

Highlights

Structural Health Monitoring (SHM) and Vibration-Based Maintenance are becoming more important due to its versatility and without distraction in the operation of the structure or machinery
The first step in considering the results obtained from this study is by cross referencing the Frequency Domain Decomposition (FDD) modes obtained from the modeled structure with the FDD modes obtained by [13]
This initial checking of the visual mode shapes obtained in this study will act as a validation to ensure that FDD result could be used as further reference when compared with the other parametric methods

Summary

Introduction

Structural Health Monitoring (SHM) and Vibration-Based Maintenance are becoming more important due to its versatility and without distraction in the operation of the structure or machinery It requires System Identification (SI) analysis in determining modal parameters of a structure. In OMA technique, the output signals is measured from a structure which is directly or randomly excited in an actual ambient condition from operating forces as an unmeasured input. This technique provides a much needed tool for the determination of the dynamic characteristics of large and complex structures or mechanisms especially when input forces cannot be directly controlled or measured. The algorithms used were Frequency Domain Decomposition (FDD), Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI)

Methods

Results

Conclusion