Statistical error reduction for correlation-driven operational modal analysis

M. Tarpø, P. Olsen, M. Juul, T. Friis, R. Brincker

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    Abstract

    Statistical errors effect the estimated correlation function matrix in Operational Modal Analysis due to the finite time length of the sampled data. When these errors start to dominate the correlation functions, an erratic behaviour appears without any physics – this phenomenon is known as the Noise Tail. This tail region should be disregarded in an identification of modal parameters and it is possible to estimate the location of the Noise Tail for each structural mode. In this paper, an automated removal of the Noise Tail is introduced and studied and the paper finds that this removal reduces bias and random errors in identification of modal parameters for Operational Modal Analysis.
    Original languageEnglish
    Title of host publicationProceedings of the International Conference on Noise and Vibration Engineering — 2018
    Number of pages7
    Publication date2018
    ISBN (Electronic)9789073802995
    Publication statusPublished - 2018
    Event28th International Conference on Noise and Vibration Engineering (ISMA 2018) - Leuven, Belgium
    Duration: 17 Sep 201819 Sep 2018
    Conference number: 28

    Conference

    Conference28th International Conference on Noise and Vibration Engineering (ISMA 2018)
    Number28
    Country/TerritoryBelgium
    CityLeuven
    Period17/09/201819/09/2018

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