Research on Wind Turbine Blade Modal Identification Method Using Joint Excitation-Response Multivariate Empirical Mode Decomposition
Year: 2025
Type: preprint
Abstract: Blade modal testing is a primary approach for evaluating structural performance. To address the reduced accuracy of the Least Squares Complex Frequency-Domain (LSCF) method under non-stationary signals and noise interference, this study proposes an enhanced blade modal identification method with improved noise resistance. This method is based on Multivariate Empirical Mode Decomposition (MEMD) theory, which enables synchronous time-domain decomposition of excitation and response signals. Multiple static modal experiments conducted on the blade demonstrate that the proposed MEMD-based method, which incorporates joint excitation-response signals, achieves identification accuracy comparable to the LSCF method for flapwise blade modes, with frequency deviations consistently remaining below 1.5 Hz. Furthermore, under random noise conditions, deviations do not exceed 2 Hz, thereby validating the feasibility of this method for wind turbine blade modal identification.
Authors: Han Xunjie, Zhiying Gao, Zhao feng, Zhang Jiayuan
Institution: Inner Mongolia University of Technology
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414016720