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A review and comparison of fault detection and diagnosis methods for squirrel-cage induction motors: State of the art
Affiliation:Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA
Abstract:Preventing induction motors (IMs) from failure and shutdown is important to maintain functionality of many critical loads in industry and commerce. This paper provides a comprehensive review of fault detection and diagnosis (FDD) methods targeting all the four major types of faults in IMs. Popular FDD methods published up to 2010 are briefly introduced, while the focus of the review is laid on the state-of-the-art FDD techniques after 2010, i.e. in 2011–2015 and some in 2016. Different FDD methods are introduced and classified into four categories depending on their application domains, instead of on fault types like in many other reviews, to better reveal hidden connections and similarities of different FDD methods. Detailed comparisons of the reviewed papers after 2010 are given in tables for fast referring. Finally, a dedicated discussion session is provided, which presents recent developments, trends and remaining difficulties regarding to FDD of IMs, to inspire novel research ideas and new research possibilities.
Keywords:Bearing fault  Broken rotor bar fault  Condition monitoring  Eccentricity fault  Fault detection  Fault diagnosis  Stator winding fault  Stator interturn fault
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