Sparse stability diagrams of LSCF method via strategic pole destabilization using orthogonal matching pursuit
Shogo Shimada, Akira Saito

TL;DR
The paper introduces a method using orthogonal matching pursuit to sparsify characteristic polynomials, effectively removing non-physical spurious poles from stability diagrams in modal analysis.
Contribution
It proposes a novel pole destabilization technique that enhances stability diagram clarity by making polynomial coefficients sparse, improving modal parameter identification.
Findings
Spurious roots are eliminated without loss of accuracy.
Method validated on numerical and experimental FRFs of plates.
Applicable to complex industrial systems like electric machine stators.
Abstract
In various engineering fields including mechanical, aerospace, and civil engineering, the identification of modal parameters, including natural frequencies, damping ratios, and mode shapes, is crucial for determining the vibration characteristics of engineered structures. A common method for identifying the modal parameters of structures involves experimental modal analysis using frequency response functions (FRFs) obtained from forced vibration tests. The least squares complex frequency (LSCF) domain method is a widely-used frequency-domain curve-fitting method for the FRFs using the polynomials of high order, which can extract modal parameters with high accuracy. However, increasing the polynomial order tends to result in the generation of non-physical spurious poles that need to be eliminated from the stability diagrams. To overcome this issue, we propose a method that strategically…
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