Research on Evaluation of Tower Vibration State Based on SCADA
Liancheng Su, Jiaojiao Zhu, Yingwei Li · Journal of Physics Conference Series · 2021
Abstract Tower is very critical to the safe operation of wind turbines. In this paper, SCADA data is used to evaluate the vibration state of the tower. A tower vibration correlation analysis method based on denoising autoencoder (DAE) is proposed, which evaluates the impact of state parameters on tower vibration based on the reconstruction residual. The tower vibration is predicted based on the Long Short-Term Memory (LSTM) network, and then the tower vibration state is evaluated based on the Wasserstein distance. The actual SCADA data is used to verify the proposed method. The results show that the method accurately predicts the tower vibration trend and quantitatively evaluates the tower vibration state.