文章基本信息

标题：A review of intelligent methods for condition monitoring and fault diagnosis of stator and rotor faults of induction machines
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作者：Omar Alshorman ; Ahmad Alshorman
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2021
卷号：11
期号：4
页码：2820-2829
DOI：10.11591/ijece.v11i4.pp2820-2829
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Nowadays, induction motor (IM) is extensively used in industry, including mechanical and electrical applications. However, three main types of IM faults have been discussed in the literature, bearing, stator, and rotor. Importantly, stator and rotor faults represent approximately 50%. Traditional condition monitoring (CM) and fault diagnosis (FD) methods require a high processing cost and much experience knowledge. To tackle this challenge, artificial intelligent (AI) based CM and FD techniques are extensively developed. However, there have been many review research papers for intelligent CM and FD machine learning methods of rolling elements bearings of IM in the literature. Whereas there is a lack in the literature, and there are not many review papers for both stator and rotor intelligent CM and FD. Thus, the proposed study's main contribution is in reviewing the CM and FD of IM, especially for the stator and the rotor, based on AI methods. The paper also provides discussions on the main challenges and possible future works.
关键词：Artificial intelligence;Condition monitoring;Fault detection and diagnosis;Induction motor;Rotor;Stator