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

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.

Three-dimensional vibration patterns of alto saxophone reeds measured on different mouthpieces under mimicked realistic playing conditions

“…In brief, the magnitude data over the whole visible surface of the reed of each harmonic component in the frequency domain is stored into a column of a matrix A. Next, a Singular Value Decomposition (SVD) of this large matrix A is performed so that A=USV' (Fadhil Shazmir et al, 2018) where U and V are unitary matrices with U holding the shape modes. S is a diagonal matrix holding the real and nonnegative singular values of A in descending order starting with the highest value at the upper left corner (Brincker, 2015).…”