Predictive maintenance (PdM) uses statistical and machine learning methods to detect and
predict the onset of faults. PdM is often used in industrial IoT settings in the energy sector …

This study presents a stationarity-based method, based on sliding window principle, for wind
turbine monitoring and anomaly detection. Initially, the window is formed with a reference …

Wind turbines are expected to provide on the order of 50% of the electricity worldwide in the
near future, and it is therefore fundamental to reduce the costs associated with this form of …

Cointegration theory has been recently proposed for condition monitoring and fault detection
of wind turbines. However, the existing cointegration-based methods and results presented …

In the next decade, further digitalisation of the entire wind energy project lifecycle is
expected to be a major driver for reducing project costs and risks. In this paper, a literature …

We propose a method, a model, and a form of presenting model results for condition
monitoring of a small set of wind turbines with rare failures. The main new ingredient of the …

Manufacturing processes involve multiple machines within a production line. Unexpected
faults in machines reduce productivity and increase maintenance costs. Engineers face …

ABSTRACT The Supervisory Control and Data Acquisition (SCADA) system in wind turbines
generates substantial data that remains underutilized in terms of wind farm operation and …

The accurate condition assessment of wind turbines greatly influences the refined asset
management and maintenance scheduling of wind farms. To address the challenges of …

Wind energy maintenance and operation costs can total millions of dollars each year in an
average industrial‐size wind park. Therefore, moving from preventive and corrective …