Maximum Likelihood Identification of Non-stationary Operational Data

Eli Parloo, Patrick Guillaume, Bart Cauberghe

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

In-operation modal analysis has become a valid alternative for
structures where a classic input-output test would be difficult if not
impossible to conduct. Due to practical considerations, measurements
are sometimes performed in patches (roving sensor setups) instead of
covering the entire structure at once. In practice, one is often
confronted with non-stationary ambient excitation sources (e.g., wind,
traffic, waves, etc.). Since the scaling of operational mode shape
estimates depends on the unknown level of the ambient excitation. an
extra effort is required in order to correctly merge the different
parts of the mode shapes. In this contribution, two different
approaches, for merging operational mode shapes from non-stationary
data, are proposed. Both methods are based upon a single maximum
likelihood estimation procedure. For comparison and validation, both
techniques were applied to non-stationary data sets obtained by
scanning laser vibrometry as well as the Z24 bridge bench mark data.
(C) 2003 Elsevier Ltd. All rights reserved.
Original languageEnglish
JournalJournal of sound and vibration
Publication statusPublished - 2003

Bibliographical note

Journal of Sound and Vibration (JSV), vol. 268, no. 5, pp. 971-991, 2003.

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