On the functional model–based method for vibration-based robust damage detection: versions and experimental assessment
Autor(en): |
Tryfon-Chrysovalantis Aravanis
John Sakellariou Spilios Fassois |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Structural Health Monitoring, Oktober 2020, n. 2, v. 20 |
Seite(n): | 147592172093020 |
DOI: | 10.1177/1475921720930206 |
Abstrakt: |
The problem of random vibration–based robust damage detection for structures operating under varying and non-measurable environmental and operating conditions is considered via a novel unsupervised functional model–based method. Two versions of the method are employed based on either the residual variance or uncorrelatedness (whiteness) of a proper functional model that incorporates the varying environmental and operating conditions in a scheduling vector. This article constitutes a proof-of-concept study in which a comprehensive laboratory assessment of the functional model–based method is undertaken using hundreds of experiments with a composite tail structure of an unmanned aerial vehicle and two early-stage damages under a considerable number of different environmental and operating conditions. Comparisons with two alternative state-of-the-art statistical time series type methods, that is, a multiple model–based method and a principal component analysis–based method, are also performed. The results indicate ideal detection performance for the functional model–based and multiple model–based methods, with the true positive rate reaching 100% at 0% false positive rate, but degraded performance for the pricipal component analysis–based method. |
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Datenseite - Reference-ID
10562470 - Veröffentlicht am:
11.02.2021 - Geändert am:
26.04.2021