Exploring and applying sparse regression in admittance-based TPA methods

D. Ocepek, F. Trainotti, J. Korbar, D. J. Rixen, M. Boltežar, G. Čepon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study investigates the use of sparse regression, specifically LASSO (least absolute shrinkage and selection operator), in admittance-based transfer path analysis (TPA) to identify critical transmission paths for sound and vibration propagation in assembled products. Application of TPA methods notoriously requires careful interface modeling in terms of interface degrees of freedom (DoFs) to avoid redundancy and error amplification in the estimated set of forces that replicate assembly's operational response. LASSO sheds light on the selection of the significant interface DoFs by promoting sparsity in the set of DoFs proposed by experimentalist. Case studies on single- and multi-point interfaces provide insights into the implementation and application of the sparse regression for use in inverse problem of TPA methods.

Original languageEnglish
Title of host publicationProceedings of ISMA 2024 - International Conference on Noise and Vibration Engineering and USD 2024 - International Conference on Uncertainty in Structural Dynamics
EditorsW. Desmet, B. Pluymers, D. Moens, J. del Fresno Zarza
PublisherKU Leuven, Departement Werktuigkunde
Pages3572-3586
Number of pages15
ISBN (Electronic)9789082893175
StatePublished - 2024
Event31st International Conference on Noise and Vibration Engineering, ISMA 2024 and 10th International Conference on Uncertainty in Structural Dynamics, USD 2024 - Leuven, Belgium
Duration: 9 Sep 202411 Sep 2024

Publication series

NameProceedings of ISMA 2024 - International Conference on Noise and Vibration Engineering and USD 2024 - International Conference on Uncertainty in Structural Dynamics

Conference

Conference31st International Conference on Noise and Vibration Engineering, ISMA 2024 and 10th International Conference on Uncertainty in Structural Dynamics, USD 2024
Country/TerritoryBelgium
CityLeuven
Period9/09/2411/09/24

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