Detecting and Isolating Pitch System Faults in Offshore Wind Turbines: A Review

In this paper, we explore the use of structural analysis to detect faults in wind turbines. We begin by explaining that wind turbines are a crucial source of renewable energy, but their production can be affected by various faults. These faults can result in significant financial losses and compromise the environment’s sustainability.
To tackle this issue, we turn to structural analysis, a method used to represent systems as graphs. By analyzing these graphs, we can identify potential faults before they occur and develop strategies for detecting and isolating them. Our approach involves adding sensors to the turbine system to monitor its performance and detect any deviations from normal operation.
We then delve into the specific types of faults that can affect wind turbines, such as those related to the pitch regulation system. These faults can have severe consequences, including missed revenue opportunities and environmental damage. By incorporating these faults into our graph-based model, we can better understand their impact on the turbine’s overall performance.
To demonstrate the effectiveness of our approach, we present a case study using data from a real-world wind farm. We show how our method can identify potential faults and provide actionable insights for maintenance personnel to address them before they become major issues.
Overall, this paper shows that structural analysis is a powerful tool for detecting faults in wind turbines, helping to ensure their reliable operation and minimize their environmental impact. By leveraging graph theory and machine learning techniques, we can create more efficient and sustainable energy systems for the future.