Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/7871
DC Field | Value | Language |
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dc.contributor.author | Bogoevska, S. | en_US |
dc.contributor.author | Spiridonakos, M. | en_US |
dc.contributor.author | Chatzi, E. | en_US |
dc.contributor.author | Dumova-Jovanoska, E. | en_US |
dc.contributor.author | Hoeffer, R. | en_US |
dc.date.accessioned | 2020-04-29T14:44:14Z | - |
dc.date.available | 2020-04-29T14:44:14Z | - |
dc.date.issued | 2016-07 | - |
dc.identifier.citation | Bogoevska, S., Spiridonakos, M., Chatzi, E., Dumova-Jovanoska, E. and Höffer, R., 2016, July. A novel bi-component structural health monitoring strategy for deriving global models of operational wind turbines. In Proceedings of the 8th European Workshop on Structural Health Monitoring (EWSHM 2016), Bilbao, Spain (pp. 5-8). | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/7871 | - |
dc.description.abstract | The short and long-term variability characterizing operational Wind Turbine (WT) structures limits applicability of existing Structural Health Monitoring (SHM) strategies for diagnostics and condition assessment. In this paper, a novel modeling approach is proposed delivering global models able to account for a wide range of operational conditions of a WT System. The approach relies on the merging of environmental and operational variables into the modeling of monitored vibration response via a two-step methodology: a) implementation of a Smoothness Priors Time Varying Autoregressive Moving Average (SP-TARMA) method for modeling the non-stationary response, and b) implementation of a Polynomial Chaos Expansion (PCE) probabilistic model for modeling the response uncertainty. The bicomponent tool is applied on long-term data, collected as part of a continuous monitoring campaign on a real operating WT structure located in Dortmund, Germany. The delivered statistical model of the structure yields a robust representation of the underlying structural dynamics, distinguishing actual structural damage from performance shifts attributed to environmental and operational agents. | en_US |
dc.language.iso | en | en_US |
dc.subject | Wind Turbines, Life-Cycle Assessment, Data-Driven Simulation, Diagnostic Methods and Tools | en_US |
dc.title | A novel bi-component structural health monitoring strategy for deriving global models of operational wind turbines | en_US |
dc.type | Proceeding article | en_US |
dc.relation.conference | 8th European Workshop on Structural Health Monitoring (EWSHM), July 2016, Bilbao | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | Faculty of Civil Engineering: Conference papers |
Files in This Item:
File | Description | Size | Format | |
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Bogoevska et al.-EWSHM-2016.pdf | 748.76 kB | Adobe PDF | View/Open |
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