There are many advanced algorithms used to estimate modal parameters. In this paper, the modal parameters extracted from the Poly-reference Least Squares Complex Frequency (PLSCF) algorithm and the Multi-reference Ibrahim Time Domain (MITD) algorithm, are compared. The former, is widely used in the industry and is known to produce almost crystal clear stabilization diagrams with barely any spurious pole estimates. The latter, is less common and the stabilization diagrams typically contain some spurious pole estimates. An Automated Modal Analysis (AMA) algorithm, that utilizes the statistical representation of the pole estimates combined with a number of decision rules based on the Modal Assurance Criteria (MAC), is employed, to detect probable physical poles. Simulated data from a Plexiglas plate is used in the study. Results indicate that the absolute bias error associated with the modal parameter estimates output by the PLSCF algorithm is higher than the bias error related to the modal parameter estimates output by the MITD algorithm. It was not conclusive which of the two methods that had the lowest random error. It should also be mentioned that, while the MITD algorithm could process all references and responses, the PLSCF algorithm relied strongly on a delicate selection of representative references and that not too many references were used.
|Title of host publication||Topics in Modal Analysis & Testing, Vol. 8 : Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics 2020|
|Editors||Brandon J. Dilworth, Michael Mains|
|Publication status||Published - 2021|
|Event||38th IMAC, A Conference and Exposition on Structural Dynamics, 2020 - Houston, United States|
Duration: 10. Feb 2020 → 13. Feb 2020
|Conference||38th IMAC, A Conference and Exposition on Structural Dynamics, 2020|
|Period||10/02/2020 → 13/02/2020|
|Series||Conference Proceedings of the Society for Experimental Mechanics Series|
Bibliographical notePublisher Copyright:
© 2021, The Society for Experimental Mechanics, Inc.
- Automated modal analysis
- Automated operational modal analysis
- Multi-reference Ibrahim time domain
- Poly-reference least squares complex frequency