A review and comparison of fault detection and diagnosis methods for squirrel-cage induction motors: State of the art. (September 2017) - Liu, Yiqi; Bazzi, Ali M.
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. Highlights: Major types of fault detection and diagnosis methods for the four major faults in induction motors are reviewed and discussed. The paper reviews both conventional methods and state-of-the-art methods published after 2010. A dedicated discussion is provided, which is based on recent developments and trends as well as remaining difficulties.