# Technological Advances on Fault Diagnosis in Wind Turbines: A Patent Analysis
## 3 Results and Discussion
Several researchers have employed structural health monitoring (SHM) and nondestructive testing (NDT) techniques to further develop effective damage detection tools for WTBs. These techniques can play a key role in improving reliability, optimizing production yield, and managing maintenance strategies for wind turbines. The main techniques used for fault detection are strain measurements, acoustic emission methods, ultrasonic-based methods, and thermography and, more recently, researchers are trying the combination of at least two NDTs to be applied to WTB monitoring. In addition, as wind turbines are usually sited in remote areas, health monitoring with long-distance applications is extremely necessary for instantaneous service. In light of this, signal processing techniques involving data extraction, analysis, and normalization are \begin{table}
\begin{tabular}{c c} \hline \hline
**IPC Code** & **Related to** \\ \hline F03D 17/00 & Monitoring or testing of wind motors, e.g., diagnostics (testing during the commissioning of wind motors F03D13/30) \\ \hline G01M 13/00 & Testing of machine parts \\ \hline F03D 11/00 & Details, parts, and accessories not included in or pertinent to the other groups of this subclass \\ \hline G01R 31/34 & Testing dynamo-electric machines \\ \hline F03D 1/06 & Rotors \\ \hline F03D 80/50 & Maintenance or repair \\ \hline F03D 80/00 & Details, components, or accessories not provided for in groups \\  & F03D1/00—F03D17/00 \\ \hline F03D 7/00 & Controlling wind motors \\ \hline G01R 31/00 & Arrangements for testing electric properties; arrangements for locating electrical faults; arrangements for electrical testing characterized by what is being tested not provided for elsewhere \\ \hline F03D 7/02 & The wind motors have a rotation axis substantially parallel to the air flow entering the rotor \\ \hline \hline \end{tabular}
\end{table} 
Table 4: IPC codes in technological prospecting. Figure 5: Most-used classification codes in area of development of technologies applied to wind turbines. increasingly being employed to extract features from the signals and attempt to determine potential damage and their location and quantify it. Signal-processing algorithms can provide useful and accurate results in order to mitigate the shortcomings of existing and currently employed techniques. Examples of recently developed and applied algorithms for fault diagnosis in wind turbines are the fast S-transformation, empirical WT, full EMD set, and others. Machine learning is a system that can modify its behavior autonomously based on its own experience. Improvements were observed in the integrated application of computational techniques such as machine learning, SCADA, and neural networks (ANNs) with the more traditional techniques [97, 98]. One of the main technological advances in the field of wind energy is not only the identification of faults but also their prediction using the Internet of Things (IoT) on Deep Learning (DL) based on Artificial intelligence (AI). These are considered future directions and have potential benefits, such as high-performance predictive and low false-positive rates via numerical simulations of collapsing phases and the diagnostic troubleshooting of wind energy production equipment [99]. The estimation of patent documents could reflect the newness that is brought by this work, and this may help companies and/or organizations in making decisions about technological developments in this particular area. Based on the information presented, companies can target opportunities as well as review the risks associated with the development of new inventions in the area of renewable energies, especially wind power energy. By leveraging the information extracted from patent research, together with marketing research, consumer analysis, and the assessment of internal production capacity, the process of research and development of new products can be guided to help the industry.