Review of Fault Detection and Diagnosis Techniques for AC Motor Drives

Muhammed Ali Gultekin () and Ali Bazzi ()
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Muhammed Ali Gultekin: Electrical and Computer Engineering Department, University of Connecticut, Storrs, CT 06269, USA
Ali Bazzi: Electrical and Computer Engineering Department, University of Connecticut, Storrs, CT 06269, USA

Energies, 2023, vol. 16, issue 15, 1-22

Abstract: Condition monitoring in electric motor drives is essential for operation continuity. This article provides a review of fault detection and diagnosis (FDD) methods for electric motor drives. It first covers various types of faults, their mechanisms, and approaches to detect and diagnose them. The article categorizes faults into machine faults, power electronics (PE) faults, DC link capacitor faults, and sensor faults, and discusses FDD methods. FDD methods for machines are categorized as statistical methods, machine-learning methods, and deep-learning methods. PE FDD methods are divided into logic-based, residual-based, and controller-aided methods. DC link capacitor and sensor faults are briefly explained. Machine and PE faults are listed and presented as tables for easy comparison and fast referencing. Most papers are selected from the past five years but older references are added when necessary. Finally, a discussion section is added to reflect on current trends and possible future research areas.

Keywords: motor drives; condition monitoring; fault detection and diagnosis; fault mechanism; power electronics; power electronics faults; machine faults (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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