Chapter 1 Automated Operational Modal Analysis on a Full-Scale Wind Turbine Tower Jens Kristian Mikkelsen, Esben Orlowitz, and Peter Møller Juhl Abstrac t 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. Keyword s Operational Modal Analysis · Modal parameter estimation · Automated method · Tracking of modes · Large structures 1.1 Introduction In an experimental modal analysis, also including Operational Modal Analysis (OMA), a frequently used step for the Modal Parameter Estimation (MPE) is the utilization of the so-called stabilization diagram or consistency diagram. The stabilization diagram is a user-interactive tool used to sort out real/physical modes of the structure under test from the unavoidable computational/noise modes that will be present in most MPE methods (e.g., Stochastic Subspace Identification (SSI)). The basic idea of the stabilization diagram is to track mode estimates as a function of model order allowed in the MPE method. The modes of a real physical system will be unaffected by the model order, and they are stable. Computational/noise modes, however, will change as the model order changes, and they will be unstable. Via the stabilization diagram, an experienced user manually selects an estimate of the modes being observable to him/her, and hence this is a subjective decision which depends on the users experience and training. In addition, it is a time-consuming process which is too cumbersome for tracking modal parameters of a structure over long periods of time. Tracking the modal parameters of a structure over time could be relevant for several reasons like model validation, structural health monitoring, etc. Therefore, an automation of the MPE avoiding the manual step of inspecting the stabilization diagram is desirable. The aim of this chapter is to track the modal parameters of the two first-order bending modes of a wind turbine tower over a time period of 10 days. To accomplish this, a method for automatic OMA is proposed that removes the need for a user-interactive stabilization diagram. The method is as such independent of the MPE method employed as long as results for a stabilization diagram are produced. For the present work, the Stochastic Subspace Identification (SSI) method has been chosen [1] as implemented in Ref. [2]. The proposed method is finally tested on 10 days experimental data set from a full-scale wind turbine tower. J. K. Mikkelsen · P. M. Juhl ( ) The Faculty of Engineering, University of Southern Denmark, Odense, Denmark e-mail: pmjuhl@sdu.dk; pmjuhl@sdu.dk E. Orlowitz Siemens Gamesa Renewable Energy, Brande, Denmark e-mail: Esben.Orlowitz@siemensgamesa.com © The Society for Experimental Mechanics, Inc. 2024 B. J. Dilworth et al. (eds.), Topics in Modal Analysis & Parameter Identification, Volume 9 , Conference Proceedings of the Society for Experimental Mechanics Series, https://doi.org/10.1007/978-3-031-34942-3_1 1
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