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Long-Term Monitoring of Modal Parameters for SHM at a 5 MW Offshore Wind Turbine
Abstract
The analysis presented focuses on long term behavior of modal parameters of a 5 MW AREVA M5000 offshore wind turbine (WT). For the analysis, 30.000 data sets, with ten minutes length each, over a period of 17 months were investigated. Each data set holds 24 channels of 50 Hz acceleration data at six different levels and seven environmental & operational conditions (EOCs, 10 min mean). For the given data classification, the major operational states of the WT serve as orientation. Modal parameters are extracted on the basis of stabilization diagrams for different orders of data-driven stochastic subspace identification (SSI-data) in combination with a newly developed, triangulation-based extraction of modal parameters (TEMP) which allows an automated and fast analysis for all collected data sets. Linear trends of modal frequencies and damping are extracted, giving a broad overview of the structures dynamic behavior under varying operational states. Results yield important knowledge for future model updating, simulations and SHM-applications.