Broken Rotor Bar Detection in Induction Motors Based on Air-Gap Rotational Magnetic Field Measurement

This paper presents a novel technique for the online detection of broken rotor bar(s) (BRBs) in induction motors, based on the analysis of the air-gap rotational magnetic field (RMF), being it indirectly sensed using the voltages induced in dual search coils installed in several stator regions. The...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2019-08, Vol.68 (8), p.2916-2925
Main Authors: Soleimani, Younes, Cruz, Sergio M. A., Haghjoo, Farhad
Format: Article
Language:English
Subjects:
Air gaps
Bars
Broken rotor bars (BRBs)
Coils
Diagnostic systems
Digital signal processing
fault detection
Finite element method
Harmonic analysis
Induction motors
Magnetic fields
Magnetic induction
Magnetic measurement
rotational magnetic field (RMF)
Rotors
search coils (SCs)
Sensitivity analysis
Stator windings
Stators
Time domain analysis
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Summary:This paper presents a novel technique for the online detection of broken rotor bar(s) (BRBs) in induction motors, based on the analysis of the air-gap rotational magnetic field (RMF), being it indirectly sensed using the voltages induced in dual search coils installed in several stator regions. The induced voltages allow obtaining three differential voltages which reveal the symmetricity level of the mentioned field along the stator circumference. Under the presence of the broken bar(s), the RMF is disturbed by the rotor magneto-motive force, being these disturbances detected through the fundamental components of the differential voltages using a new time-domain analysis technique. The proposed diagnostic approach is verified by finite-element analysis and also by several experimental tests. A high sensitivity, robustness in the face of unbalanced voltage sources and motor load level variations are the main advantages of the proposed technique. Moreover, it is a secure method for BRB detection, easily implementable in low-cost digital signal processing units.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2018.2870265