Intelligent Fault Diagnosis and Maintenance Decision Support in Electrical Induction Generators Using Multi-CNN Extreme Ensemble Learning
It is demonstrated that Hjorth-based electrical-signal characterization and Multi-CNN ensemble fusion can provide accurate and computationally efficient support for fault identification and predictive maintenance decisions in electrical induction generators.