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Environmental Influence on Modal Parameters: Linear and Nonlinear Methods for Its Compensation in the Context of Structural Health Monitoring

Chapter
Publication Date:
2022
abstract:
Modal-based structural health monitoring (SHM) detects damage and degradation phenomena from the variations of the modal parameters over time. However, the modal parameter estimates are also influenced by environmental and operational variables (EOVs) whose effects have to be compensated. Modeling the influence of EOVs on modal parameters is very challenging, so black-box models, such as regression models, are often adopted as an alternative. However, in many applications, the set of measured EOVs is incomplete or the factors influencing the estimates cannot be identified or measured. In these conditions, output-only techniques for compensation of environmental and operational effects are an attractive alternative. Different linear as well as nonlinear methods for the compensation of the environmental and operational influence on modal parameters in the context of modal-based SHM are reviewed in the present paper. Real datasets collected from vibration-based monitoring systems are analyzed, and the results are presented and discussed to illustrate the applicative perspectives and possible drawbacks of the selected methods.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Environmental influence; Kernel PCA; Modal-based SHM; Principal component analysis; Regression model; Second-order blind identification
List of contributors:
Rainieri, Carlo
Authors of the University:
RAINIERI CARLO
Handle:
https://iris.cnr.it/handle/20.500.14243/443706
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