Induction motors are the most commonly used electric motors in the industry. The main reasons for choosing induction motors are their robust structure and low maintenance requirements. However, the harsh working conditions of the industry cause motor faults. Predicting motor faults in advance or determining the cause of fault is very important for businesses. In this study, an attempt was made to detect the eccentricity fault of the induction motor with a cheap and easy method. The eccentricity fault, which is a mechanical fault and is frequently encountered, was tried to be determined by monitoring the motor current signals. The motor current signals were analyzed with the statistical process control method from statistical methods. For the first time, with this study, the eccentricity fault occurring in an induction motor operating under different speed conditions was successfully detected with the statistical process control method.
Induction motors are the most commonly used electric motors in the industry. The main reasons for choosing induction motors are their robust structure and low maintenance requirements. However, the harsh working conditions of the industry cause motor faults. Predicting motor faults in advance or determining the cause of fault is very important for businesses. In this study, an attempt was made to detect the eccentricity fault of the induction motor with a cheap and easy method. The eccentricity fault, which is a mechanical fault and is frequently encountered, was tried to be determined by monitoring the motor current signals. The motor current signals were analyzed with the statistical process control method from statistical methods. For the first time, with this study, the eccentricity fault occurring in an induction motor operating under different speed conditions was successfully detected with the statistical process control method.
Primary Language | English |
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Subjects | Electrical Machines and Drives |
Journal Section | Articles |
Authors | |
Early Pub Date | December 30, 2024 |
Publication Date | December 30, 2024 |
Submission Date | November 12, 2024 |
Acceptance Date | November 26, 2024 |
Published in Issue | Year 2024 Volume: 8 Issue: 2 |