Skip to Main content Skip to Navigation
Conference papers

Robust fault detection based on multiple functional series TAR models for structures with time-dependent dynamics

Abstract : Vibration-based Structural Health Monitoring of operating wind turbines is challenging, as those structures are characterized by complex non-stationary response and are subject to environmental and operational uncertainties. FS-TARMA parameter based methods are ideal for this problem since they are capable of summarizing the non-stationary dynamics within a small parameter set. In this work, robust FS-TARMA parameter based fault detection methods are pursued by including several FS-TARMA models in the estimation of the statistical model used for posterior decision making. Different combination rules for the different FS-TARMA models are defined, analyzed and compared within the problem of vibration based fault detection on operating wind turbines using simulated data obtained from the FAST aeroelastic simulation code. Results demonstrate the improvement in terms of accuracy and reliability provided by the multiple model approach.
Complete list of metadata

Cited literature [10 references]  Display  Hide  Download

https://hal.inria.fr/hal-01020452
Contributor : Anne Jaigu <>
Submitted on : Tuesday, July 8, 2014 - 10:13:03 AM
Last modification on : Tuesday, December 26, 2017 - 4:38:01 PM
Long-term archiving on: : Wednesday, October 8, 2014 - 12:11:31 PM

File

0191.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01020452, version 1

Collections

Citation

David Avendano-Valencia, Spilios D. Fassois. Robust fault detection based on multiple functional series TAR models for structures with time-dependent dynamics. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01020452⟩

Share

Metrics

Record views

364

Files downloads

386