@inproceedings{44753ba5e7ad4359901c429a7d93b38a,

title = "Automated Operational Modal Analysis on a Full-Scale Wind Turbine Tower",

abstract = "This chapter is concerned with the automated extraction of modal parameters (frequency and damping estimates) from accelerometer data measured on a full-scale wind turbine tower without its nacelle and blades installed. The proposed algorithm is based on an existing Operational Modal Analysis research software employing the Stochastic Subspace Identification algorithm for manual selection and extraction of modal parameters. The automatization of the algorithm is discussed in terms of the choices made and their consequences with respect to sensitivity and robustness. The algorithm is finally tested on a large experimental dataset consisting of 10 days of signals sampled at 25 Hz from two accelerometers mounted at the top of the tower in orthogonal directions. The automated algorithm is successful in time tracking the development of the first two modes with respect to frequency and damping despite the challenge posed by the fact that due to the high degree of symmetry in the setup the frequencies of the two modes are very similar.",

keywords = "Operational Modal Analysis, Modal parameter estimation, Automated method, Tracking of modes, Large structures",

author = "Mikkelsen, {Jens Kristian} and Esben Orlowitz and Juhl, {Peter M{\o}ller}",

year = "2023",

month = aug,

doi = "10.1007/978-3-031-34942-3_1",

language = "English",

isbn = "9783031349416",

volume = "9",

series = "Conference Proceedings of the Society for Experimental Mechanics Series",

publisher = "Springer",

editor = "Dilworth, {Brandon J.} and Timothy Marinone and Michael Mains",

booktitle = "Topics in Modal Analysis and Parameter Identification, Volume 9",

note = "IMAC-XLI : Keeping IMAC Weird: Traditional and Non-Traditional Applications of Structural Dynamics ; Conference date: 13-02-2023 Through 16-02-2023",

}