Condition Monitoring and Fault Diagnosis of Induction Motor
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REVIEW
Condition Monitoring and Fault Diagnosis of Induction Motor Swapnil K. Gundewar1 · Prasad V. Kane1 Received: 4 July 2020 / Revised: 23 September 2020 / Accepted: 29 September 2020 © Krishtel eMaging Solutions Private Limited 2020
Abstract Background An induction motor is at the heart of every rotating machine and hence it is a very vital component. Almost in every industry, around 90% of the machines apply an induction motor as a prime mover. It is a very important driving unit of the machine. Hence, it is necessary to monitor its condition to avoid any catastrophic failure and stoppage of production. The breakdown of the induction motor would not be affordable due to remarkable financial loss, unpredicted shutdown, and the associated repair cost. Purpose Vibration is a manifestation of induction motor due to the issues in alignment, balancing, and clearances. Bearing, the most vulnerable to failure due to continuous working under fatigue loading leads to defects. These defects cause changes in the vibration signature over time. The vibration monitoring techniques helps to effectively diagnose mechanical faults such as bearing defect and stator rotor rub. The purpose of this review paper is to summarize the major faults in induction motor, recent diagnostics methods augmented with advanced signal processing techniques, and real-life applications in electric vehicles. It also discusses possible research gaps and opportunities to contribute based on the review findings in the field of condition monitoring. Methods This article presents a detailed review of recent trends in the research of condition monitoring and fault diagnosis of the induction motor. The emphasis is given on the major faults in the induction motor covering time-domain, frequencydomain, and time–frequency domain methods along with an application of artificial intelligence techniques for fault detection. Review Factor This article presents a comprehensive review of literature which highlights the development and new propositions by researchers in the field of diagnostic techniques for the different faults of induction motor in the last decade. Researchers documented applications of the different conventional methods, advanced signal processing techniques, and soft computing techniques for fault identification of induction motor. This review is carried out for fault identification of induction motor used in machines in general and in particular for identifying the faults in an induction motor of an electric vehicle. A dedicated discussion on the review findings, research gaps, future trends in the field of condition monitoring of induction motor is presented. Condition monitoring of the induction motor in an electric vehicle is also discussed in this paper. Conclusions It is observed that the vibration-based techniques are reported to be effective for the identification of mechanical faults while motor current signature analysis is effective for electrical fault in an induction motor. The review presented to analyze the suitability of
