Validation of an Automated Approach for the Definition of Reference Modal Properties on Onshore Wind Turbines

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Cunha, A. (Author) FEUP; Pereira, S. (Author) FEUP; Pacheco, J. (Author) Other; Pimenta, F. (Author) FEUP; Moutinho, C. (Author) FEUP; Magalhães, F. (Author) FEUP

Conference proceedings International

Title: Lecture Notes in Civil Engineering

Pages: 21-28

Experimental Vibration Analysis for Civil Engineering Structures - EVACES 2023 - Volume 2

Milan, 30 August 2023 through 1 September 2023

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-00Z-4TV

DOI: 10.1007/978-3-031-39109-5_3

Abstract (EN): The continuous application of Operational Modal Analysis (OMA) to time-series recorded on civil engineering structures, and the subsequent tracking of modal properties, allow the characterization of the evolution of their dynamic behaviour, which is particularly important on wind turbines, since their structural performance is highly dependent on it. However, it is impractical to manually analyse long periods of data, being essential to automatize OMA and to link results obtained in different datasets, which can be achieved through the comparison between a reliable set of references and the estimated modal properties. Nevertheless, the establishment of such a set of references is usually accomplished through a manual analysis, which is time-consuming and may produce a biased result. Furthermore, due to the impact of the operating conditions on the modal properties, several sets of references should be defined, making this process even more longstanding and prone to subjectivity. Therefore, the present work validates a clustering-based approach to automatically obtain a group of reference properties to be used in the tracking of the modal properties of an onshore wind turbine, resorting to data from a continuous monitoring program in Portugal. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7