Intelligent Industrial IoT system for detection of short-circuit failure in windings of wind turbines

With the parameters set of the industry 4.0 and the growth of new intelligent and interconnected systems, those concepts have enabled innovative advances in several areas, among them, solutions for different renewable sources of energy efficiency. This study has as its objective the detection of short-circuit faults in wind turbines utilizing an analysis of vibration images. Using the Internet of things (IoT) context, we created a methodology to check the operating condition of a machine. The proposed method obtained excellent results, presenting a new interconnected approach to the industry 4.0 for short-circuit detection of induction generator squirrel-cage model, a widely used and growing model in the renewable energy market. Using the Random Forest-LBP combination, we achieved 87.9% accuracy with no false positives between the normal class and the failure classes.

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