Volume 41, Issue 4, February 2024, Pages 1168–1174
Alexandre N’GUESSAN1, Serge Mouroufié ADOU2, and Abé Simon YAPI3
1 Science and technology department, Laboratory of Technology (Lab-Tech), Félix Houphouët-Boigny University, Abidjan, Côte d’Ivoire
2 Science and technology department, Laboratory of Technology (Lab-Tech), Félix Houphouët-Boigny University, Abidjan, Côte d’Ivoire
3 Science and technology department, Laboratory of Technology (Lab-Tech), Félix Houphouët-Boigny University, Abidjan, Côte d’Ivoire
Original language: English
Copyright © 2024 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In view of the importance of squirrel cage induction machines in industrial applications, effective methods are needed to detect faults that could disrupt their operation. Despite their robustness, squirrel cage induction motors are subject to some faults, such as the broken bar. Current is one of the most widely used parameters for diagnosing squirrel cage induction motors. In most cases, however, the Motor Current Signature Analysis (MCSA) method is used. However, in the specific case of a broken bar, analysis of the current intensity in each rotor bar enables precise detection of a broken bar. The present work analyzes the evolution of the current intensity in each rotor bars in the case of a healthy rotor and in the presence of a broken bar. The current intensity in the rotor bar is strongly impacted, with a greatly reduced current. This situation also leads to a distribution of current intensity in the neighboring bars. As a result, the intensity of the current flowing through these bars increases according to their proximity to the faulty bar.
Author Keywords: induction machine, rotor faults, diagnostic, rotor current, electrical system.
Alexandre N’GUESSAN1, Serge Mouroufié ADOU2, and Abé Simon YAPI3
1 Science and technology department, Laboratory of Technology (Lab-Tech), Félix Houphouët-Boigny University, Abidjan, Côte d’Ivoire
2 Science and technology department, Laboratory of Technology (Lab-Tech), Félix Houphouët-Boigny University, Abidjan, Côte d’Ivoire
3 Science and technology department, Laboratory of Technology (Lab-Tech), Félix Houphouët-Boigny University, Abidjan, Côte d’Ivoire
Original language: English
Copyright © 2024 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In view of the importance of squirrel cage induction machines in industrial applications, effective methods are needed to detect faults that could disrupt their operation. Despite their robustness, squirrel cage induction motors are subject to some faults, such as the broken bar. Current is one of the most widely used parameters for diagnosing squirrel cage induction motors. In most cases, however, the Motor Current Signature Analysis (MCSA) method is used. However, in the specific case of a broken bar, analysis of the current intensity in each rotor bar enables precise detection of a broken bar. The present work analyzes the evolution of the current intensity in each rotor bars in the case of a healthy rotor and in the presence of a broken bar. The current intensity in the rotor bar is strongly impacted, with a greatly reduced current. This situation also leads to a distribution of current intensity in the neighboring bars. As a result, the intensity of the current flowing through these bars increases according to their proximity to the faulty bar.
Author Keywords: induction machine, rotor faults, diagnostic, rotor current, electrical system.
How to Cite this Article
Alexandre N’GUESSAN, Serge Mouroufié ADOU, and Abé Simon YAPI, “Analysis of the current intensity in each rotor bar of a squirrel cage induction motor: Case of a broken bar,” International Journal of Innovation and Applied Studies, vol. 41, no. 4, pp. 1168–1174, February 2024.
