A Survey of Broken Rotor Bar Fault Diagnostic Methods of Induction Motor

Author:

Asad Bilal1,Vaimann Toomas2,Rassõlkin Anton3,Kallaste Ants2,Belahcen Anouar4

Affiliation:

1. Ph. D. Student, Tallinn University of Technology , Tallinn , Estonia

2. Senior Researcher, Tallinn University of Technology , Tallinn , Estonia

3. Researcher, Tallinn University of Technology , Tallinn , Estonia

4. Professor, Tallinn University of Technology , Tallinn , Estonia

Abstract

Abstract Electrical machines, induction motors in particular, play a key role in domestic and industrial applications. They act as a work horse in almost every industry and are responsible for a big proportion of total generated electricity consumption worldwide. The faults in induction motors are degenerative in nature and can lead to a catastrophic situation if not diagnosed earlier. The failures can cause considerable financial loss in the form of unexpected downtime. Broken rotor bar is a very common and frequently occurring fault in most of industrial induction motors. To select a better, more accurate and reliable fault diagnostic technique, this paper presents a comprehensive literature survey on the existing motor current signature analysis (MCSA) based fault diagnostic techniques. Different well-known MCSA based fault diagnostic techniques are summarized in the form of basic theories, considering complexity of their implementation, merits and demerits.

Publisher

Walter de Gruyter GmbH

Reference52 articles.

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3. [3] Z. Hou, J. Huang, H. Liu, M. Ye, Z. Liu, and J. Yang, “Diagnosis of Broken Rotor Bar Fault in Open- and Closed-Loop Controlled Wye-Connected Induction Motors Using Zero-Sequence Voltage,” IET Electr. Power Appl., vol. 11, no. 7, pp. 1214–1223, Aug. 2017. https://doi.org/10.1049/iet-epa.2016.050510.1049/iet-epa.2016.0505

4. [4] Y. Gritli, A. O. Di Tommaso, R. Miceli, C. Rossi, and F. Filippetti, “Diagnosis of Mechanical Unbalance for Double Cage Induction Motor Load in Time-Varying Conditions Based on Motor Vibration Signature Analysis,” in 2013 International Conference on Renewable Energy Research and Applications (ICRERA), 2013, pp. 1157–1162. https://doi.org/10.1109/ICRERA.2013.674992710.1109/ICRERA.2013.6749927

5. [5] P. Granjon, “Electromagnetic Vibrations Estimation of an Induction Motor by Nonlinear Optimal Filtering,” in 2005 5th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, 2005, pp. 1–5. https://doi.org/10.1109/DEMPED.2005.466250810.1109/DEMPED.2005.4662508

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