Details
| Original language | English |
|---|---|
| Title of host publication | Structural Health Monitoring 2011 |
| Subtitle of host publication | Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring |
| Pages | 2149-2156 |
| Number of pages | 8 |
| Publication status | Published - 2011 |
| Event | 8th International Workshop on Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Stanford, CA, United States Duration: 13 Sept 2011 → 15 Sept 2011 |
Publication series
| Name | Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring |
|---|---|
| Volume | 2 |
Abstract
System identification by measured data is an important procedure, necessary for many applications within the field of structural health monitoring. The resulting modal properties can be used for model-validation and updating, load estimation and damage detection to name a few possibilities. An automated algorithm for identifying a structure's modal properties from dynamic response data (accelerations) using Auto-Regressive (AR) models is presented here. New parameters to estimate the AR-model's order a priori and to extract the physical from the mathematical models are introduced. Furthermore, a tool for automated model validation using several iterative techniques is presented as well. The algorithms are applied to data from two offshore structures. System identification and model updating are accessible through a graphic user interface (GUI) based on MATLAB.
ASJC Scopus subject areas
- Engineering(all)
- Civil and Structural Engineering
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Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring. 2011. p. 2149-2156 (Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring; Vol. 2).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Automated system identification and validation of numerical models of offshore wind turbines as basis for SHM-analysis
AU - Häckell, M. W.
AU - Haake, G.
AU - Rolfes, R.
PY - 2011
Y1 - 2011
N2 - System identification by measured data is an important procedure, necessary for many applications within the field of structural health monitoring. The resulting modal properties can be used for model-validation and updating, load estimation and damage detection to name a few possibilities. An automated algorithm for identifying a structure's modal properties from dynamic response data (accelerations) using Auto-Regressive (AR) models is presented here. New parameters to estimate the AR-model's order a priori and to extract the physical from the mathematical models are introduced. Furthermore, a tool for automated model validation using several iterative techniques is presented as well. The algorithms are applied to data from two offshore structures. System identification and model updating are accessible through a graphic user interface (GUI) based on MATLAB.
AB - System identification by measured data is an important procedure, necessary for many applications within the field of structural health monitoring. The resulting modal properties can be used for model-validation and updating, load estimation and damage detection to name a few possibilities. An automated algorithm for identifying a structure's modal properties from dynamic response data (accelerations) using Auto-Regressive (AR) models is presented here. New parameters to estimate the AR-model's order a priori and to extract the physical from the mathematical models are introduced. Furthermore, a tool for automated model validation using several iterative techniques is presented as well. The algorithms are applied to data from two offshore structures. System identification and model updating are accessible through a graphic user interface (GUI) based on MATLAB.
UR - http://www.scopus.com/inward/record.url?scp=84866722453&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84866722453
SN - 9781605950532
T3 - Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring
SP - 2149
EP - 2156
BT - Structural Health Monitoring 2011
T2 - 8th International Workshop on Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures
Y2 - 13 September 2011 through 15 September 2011
ER -