A Comprehensive Review of Conventional and Intelligence-Based Approaches for the Fault Diagnosis and Condition Monitoring of Induction Motors

• Published in: Energies (Basel) Vol. 15; no. 23; p. 8938
• Main Authors: Kumar, Rahul R., Andriollo, Mauro, Cirrincione, Giansalvo, Cirrincione, Maurizio, Tortella, Andrea
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2022; MDPI
• Subjects: artificial intelligence; classical techniques; data-driven; Electric fault location; Engineering Sciences; Failure; Fault diagnosis; Induction electric motors; Machine learning; Maintenance costs; Methods; model-based; motor; Preventive maintenance; Signal processing; Fiji

This review paper looks briefly at conventional approaches and examines the intelligent means for fault diagnosis (FD) and condition monitoring (CM) of electrical drives in detail, especially the ones that are common in Industry 4.0. After giving an overview on fault statistics, standard methods for...