Automated modal parameter-based anomaly detection under varying wind excitation

  • Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions.

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Metadaten
Author:Eugen Neu, Frank Janser, Akbar A. Khatibi, Adrian C. Orifici
DOI:https://doi.org/10.1177/1475921716665803
ISSN:1475-9217
Parent Title (English):Structural Health Monitoring
Publisher:Sage
Place of publication:London
Document Type:Article
Language:English
Year of Completion:2016
Volume:15
Issue:6
First Page:1
Last Page:20
Link:https://doi.org/10.1177/1475921716665803
Zugriffsart:campus
Institutes:FH Aachen / ECSM European Center for Sustainable Mobility
FH Aachen / Fachbereich Luft- und Raumfahrttechnik
collections:Verlag / Sage