Fault Diagnostics in Wind Turbines Utilizing Advanced Signal Processing Techniques - A Literature Review

Wind energy is recognized as one of the most promising alternatives to conventional energy sources. The generation of electrical power from wind farms has experienced the greatest technological advancements and, simultaneously, the most significant global construction trend over the past two decades, surpassing all other renewable energy sources. Given the potential and future outlook of wind farms, it is imperative to engage in the study of fault detection and strive to find optimal solutions for potential issues. Wind turbines are electromechanical systems composed of numerous components and subsystems. These components exhibit varying fault rates, and their failures result in different downtime periods. It has been demonstrated that faults in gearboxes, generators, rotors, and the overall drive system lead to the longest downtimes. The most effective maintenance is based on fault prognosis (predicting where a fault might occur), requiring continuous condition monitoring. This paper describes various condition-monitoring techniques, focusing on vibration-based monitoring. Data is collected through installed sensors and then processed and diagnosed using signal processing techniques to transform it into intelligible information.