Mar 1, 2023 · A wind turbine fault detection method adapted to the raw data features is proposed. The improved meta-ACON is employed in the proposed method.

Highlights •A wind turbine fault detection method adapted to the raw data features is proposed.•The improved meta-ACON is employed in the proposed method.

By comparing the predicted behavior of the wind turbine by a trained model with the reference space, anomalies can be detected. Finally, wind turbine faults are ...

Wind turbine fault detection based on deep residual networks. https://doi.org/10.1016/j.eswa.2022.119102 ·. Journal: Expert Systems with Applications, 2023, ...

May 10, 2023 · Aimed at the wind turbine (WT) driveline, a new method utilizing the deep residual LSTM network with attention model (ResLSTM-AM) is proposed in this article.

Jun 6, 2022 · Finally, we adopt the developed fault diagnosis model to achieve the fault diagnosis of bearings and gears in the wind turbine gearbox.

Secondly, we establish the neural network by the deep residual network (ResNet), long short-term memory network (LSTM), and attention mechanism (AM) for time ...

Jul 28, 2023 · This study aims to address the limitations of traditional machine learning algorithms in wind turbine fault detection and the imbalance of ...

This paper presents an approach to wind turbine converter fault detection using convolutional neural network models which are developed by using wind turbine ...

Jan 3, 2024 · The proposed strategy is based on a normality model by means of an autoencoder. As of this, faulty data are used for testing from which prediction errors were ...