Wind turbines play an increasingly important role in renewable power generation. To ensure
the efficient production and financial viability of wind power, it is crucial to maintain wind …

As wind energy is becoming a significant utility source, minimizing the operation and
maintenance (O&M) expenses has raised a crucial issue to make wind energy competitive to …

This article presents an intelligent fault diagnosis method for wind turbine (WT) gearbox by
using wavelet packet decomposition (WPD) and deep learning. Specifically, the vibration …

In recent years, autoencoder has been widely used for the fault diagnosis of mechanical
equipment because of its excellent performance in feature extraction and dimension …

Support of artificial intelligence, renewable energy and sustainability is currently increasing
through the main policies of developed countries, eg, the White Paper of the European …

In order to solve the problem of compound fault diagnosis of diesel engine fuel injection
system under the condition of few samples, a comprehensive diagnosis method based on …

In this article, a modified convolutional neural network (CNN) algorithm, namely 1D-
GAPCNN-SVM, is proposed to address the early anomaly diagnosis problem. Considering …

As grid-connected wind farms become more common in the modern power system, the
question of how to maximize wind power generation while limiting downtime has been a …

This paper proposes a Bayesian framework based on particle filters for online fatigue
damage diagnosis and prognosis for wind turbine blades (WTBs). The framework integrates …

Renewable energy-based power generation technologies are becoming more and more
popular since they represent alternative solutions to the recent economic and environmental …