Technological Advances on Fault Diagnosis in Wind Turbines: A Patent Analysis

Abstract

Given the urgency of mitigating the effects of global warming and the depletion of fossil energy sources, renewable sources of energy, such as wind power, are the focus of the future. However, due to the rapid growth of this technology, concerns about the security and reliability of wind turbines are increasing, especially because of associated hazards and financial costs. Hence, health monitoring and fault identification for wind turbine blades have become an important focus of research. Thus, the objective of this study was to generate data on the current scenario of the techniques used to identify failures and defects in wind turbines and their components. Through the results found, companies can find ways to make decisions and identify potential new technologies. In this way, a technology prospection was conducted that focused on patents to investigate the use of vibration analysis, thermography, and machine learning. A total of 635 patent documents were found, and the evolution in the number of patents over the years has demonstrated the current interest in developing new technologies in this research area. China, the world’s leading country in the area of wind energy, was the country with the highest number of filings, followed by the United States. In the patent documents analyzed, it was possible to identify that those innovative technologies for predicting and detecting failures are a topic of interest for the world’s largest economies. Additionally, it was clear from the results that the application of artificial intelligence to traditional techniques is a current trend and will continue in the future. Technological prospection studies can foster the development of new methods and devices, providing economic and environmental gains for the wind energy industry.